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Chi-square Test and its Application in Hypothesis Testing

Rana, Rakesh; Singhal, Richa

Statistical Section, Central Council for Research in Ayurvedic Sciences, Ministry of AYUSH, GOI, New Delhi, India

Address for correspondence: Dr. Richa Singhal, Central Council for Research in Ayurvedic Sciences, Ministry of AYUSH, GOI, New Delhi, India. E-mail: [email protected]

This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.

In medical research, there are studies which often collect data on categorical variables that can be summarized as a series of counts. These counts are commonly arranged in a tabular format known as a contingency table. The chi-square test statistic can be used to evaluate whether there is an association between the rows and columns in a contingency table. More specifically, this statistic can be used to determine whether there is any difference between the study groups in the proportions of the risk factor of interest. Chi-square test and the logic of hypothesis testing were developed by Karl Pearson. This article describes in detail what is a chi-square test, on which type of data it is used, the assumptions associated with its application, how to manually calculate it and how to make use of an online calculator for calculating the Chi-square statistics and its associated P -value.

The logic of hypothesis testing was first invented by Karl Pearson (1857-1936), a renaissance scientist, in Victorian London in 1900. [ 1 ] Pearson's Chi-square distribution and the Chi-square test also known as test for goodness-of-fit and test of independence are his most important contribution to the modern theory of statistics. The importance of Pearson's Chi-square distribution was that, the statisticians could use the statistical methods that did not depend on the normal distribution to interpret the findings. He invented the Chi-square distribution to mainly cater the needs of biologists, economists, and psychologists. His paper in 1900 published in Philosophical magazine elaborates the invention of Chi-square distribution and goodness of fit test. [ 2 , 3 ]

Chi-square test is a nonparametric test used for two specific purpose: (a) To test the hypothesis of no association between two or more groups, population or criteria (i.e. to check independence between two variables); (b) and to test how likely the observed distribution of data fits with the distribution that is expected (i.e., to test the goodness-of-fit). It is used to analyze categorical data (e.g. male or female patients, smokers and non-smokers, etc.), it is not meant to analyze parametric or continuous data (e.g., height measured in centimeters or weight measured in kg, etc.).

For example if we want to test that in a health camp attended by 50 persons the one who exercise regularly are having lesser body mass index (BMI) by taking their actual BMI values, than it cannot be tested using a Chi-square test. However, if we divide the same set of 50 persons into two categories as obese with BMI ≥ 30 and nonobese with BMI < 30, than the same data can be tested using a Chi-square test by counting the number of obese and nonobese persons across two groups, the one who exercise regularly and the one who does not. A 2×2 contingency table also known as cross tables can be constructed for calculating a Chi-square statistic [ Table 1 ].

ASSUMPTIONS UNDERLYING A CHI-square TEST

• The data are randomly drawn from a population
• The values in the cells are considered adequate when expected counts are not <5 and there are no cells with zero count [ 4 , 5 ]
• The sample size is sufficiently large. The application of the Chi-square test to a smaller sample could lead to type II error (i.e. accepting the null hypothesis when it is actually false). There is no expected cut-off for the sample size; however, the minimum sample size varies from 20 to 50
• The variables under consideration must be mutually exclusive. It means that each variable must only be counted once in a particular category and should not be allowed to appear in other category. In other, words no item shall be counted twice.

HOW TO CALCULATE A CHI-square STATISTICS?

The formula for calculating a Chi-square statistic is:

O stands for the observed frequency,

E stands for the expected frequency.

Expected count is subtracted from the observed count to find the difference between the two. Then the square of the difference is calculated to get rid of the negative vales (as the squares of 2 and −2 are, of course, both 4). Then the square of the difference is divided by the expected count to normalize bigger and smaller values (because we don't want to get bigger Chi-square values just because we are working on large data sets). The sigma sign in front of them denotes that we have, to sum up, these values calculated for each cell.

As an example, suppose we want to find out that whether there is an association between smoking and lung disease.

The null and alternative hypothesis will be:

H 0 : There is no association between smoking and lung disease.

H 1 : There is an association between smoking and lung disease.

The basic step for calculating a Chi-square test is setting up a 2 × 2 contingency table [ Table 2 ].

The general formula for calculating the expected counts from observed count for a particular cell is [(corresponding row total * corresponding column total) /Total no. of patients] [ Table 3 ].

Before we proceed further, we need to know how many degrees of freedom (df) we have. When a comparison is made between one sample and another, a simple rule is that the df equals (number of columns − 1) × (number of rows − 1) excluding the rows and column containing the total. Hence, in our example df = (2−1) × (2−1) = 1.

Hypothetical data for calculating the Chi-square test for our example of testing an association between smoking and lung disease is given in Table 4 . Chi-square test can be calculated manually by using the formula described above. Refer [ Table 5 and Table 6 ] for manual calculations. Chi-square value for our example as shown in Table 6 is 3.42, df = 1. If we want to test our hypothesis at 5% level of significance than our predetermined alpha level of significance is 0.05. Looking into the Chi-square distribution table [ Table 7 ] with 1 degree of freedom and reading along the row we find our value of χ 2 (3.42) lies between 2.706 and 3.841. The corresponding probability is between the 0.10 and 0.05 probability levels. That means that the P value is above 0.05 (it is actually 0.065). Since a P value of 0.065 is greater than the conventionally accepted significance level of 0.05 (i.e., P > 0.05) we fail to reject the null hypothesis or in other words we accept our null hypothesis and conclude that there is no association between smoking and lung disease.

HOW TO USE A CHI-square DISTRIBUTION TABLE TO APPROXIMATE P VALUE?

Scientists and statisticians use large tables of values to calculate the P value for their experiment. These tables are generally set up with the vertical axis on the left corresponding to df and the horizontal axis on the top corresponding to P value. Use these tables by first finding our df, then reading that row across from the left to the right until we find the first value bigger than our Chi-square value. Look at the corresponding P value at the top of the column. Chi-square distribution tables are available from a variety of sources-they can easily be found online or in science and statistics textbooks.

USING AN ONLINE CHI-square CALCULATOR

The Chi-square statistics and its associated P value can be calculated through online calculators also which are easily available on the internet. For user-friendly online calculator, you may visit this uniform resource locator http://www.socscistatistics.com/tests/chisquare/default2.aspx . Many more online calculators are available on the World Wide Web. The basic step for using an online calculator is to correctly fill in your data into it.

Step by step procedure of using an online calculator is described below:

• Step 1: For our example of finding an association between smoking and lung disease we have to fill in the observed values in the cells of an online calculator [ Figure 1 ]

• Step 2: Click on the next button. Another screen will pop up as shown in Figure 2

• Step 3: Click on the Calculate Chi^2 button. And you are done with your calculation Output of the Chi-square test will be as shown in Figure 3 .

The image above shows the Chi-square value as 3.4177 and its associated P value as 0.0645 which is actually greater than P value of 0.05, hence no significant difference has been observed. To conclude, there is no association between smoking and lung disease.

WHAT DOES A CHI-square TEST TELL AND WHAT IT DOES NOT?

It may be clearly understood that Chi-square test only tells us the probability of independence of a distribution of data or in simple terms it will only test that whether two variables are associated with each other or not. It will not tell us that how closely they are associated. For instance in the above example, the Chi-square test will only tell us that whether there is any relation between smoking and lung disease. It will not tell us that how likely it is, that smokers are prone to lung disease. However, once we got to know that there is a relation between these two variables, we can explore other methods to calculate the amount of association between them.

Source of Support:

Conflict of interest:.

None declared.

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Chi-square test under indeterminacy: an application using pulse count data

• Muhammad Aslam   ORCID: orcid.org/0000-0003-0644-1950 1  

BMC Medical Research Methodology volume  21 , Article number:  201 ( 2021 ) Cite this article

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The data obtained from the counting process is known as the count data. In practice, the counting can be done at the same time or the time of the count is not the same. To test either the K counts are differed significantly or not, the Chi-square test for K counts is applied.

The paper presents the Chi-square tests for K counts under neutrosophic statistics. The test statistic of the proposed test when K counts are recorded at the same time and different time are proposed. The testing procedure of the proposed test is explained with the help of pulse count data.

Conclusions

From the analysis of pulse count data, it can be concluded that the proposed test suggests the cardiologists use different treatment methods on patients. In addition, the proposed test gives more information than the traditional test under uncertainty.

Peer Review reports

The data obtained from the counting process is known as the count data. In practice, the counting can be done at the same time or the time of the count is not the same. To test either the K counts are differed significantly or not, the Chi-square test for K counts is applied. This test is applied to test the null hypothesis either the same training or methods should be applied on K counts against the alternative hypothesis that different training or methods should be applied on K counts. The Chi-square test for K counts under classical statistics is applied under the assumption that K counts are obtained under comparable conditions, see [ 1 , 2 ]. Worked on the test for testing two means of Poisson distribution [ 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 ] presented applications of test for count data in a variety of fields.

According to [ 11 ], “statistical data are frequently not precise numbers but more or less non-precise also called fuzzy. Measurements of continuous variables are always fuzzy to a certain degree”. Similarly, the counting data is not always exact but may be in intervals or unclear. For example, the weather record data and pulse count data are expressed in intervals than the exact values. In these situations, the existing Chi-square test for K counts under classical statistics may mislead the decision-makers. The fuzzy-based tests may be an alternative to being applied when the count data is intervals. The applications of statistical tests under fuzzy logic can be seen in [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 ].

The fuzzy logic is a special case of neutrosophic logic [ 20 , 21 ] showed the efficiency of the neutrosophic logic over the fuzzy logic and analysis based on the interval approach. For the application of neutrosophic logic, the reader may refer to [ 22 , 23 , 24 , 25 , 26 ]. The neutrosophic statistics was proposed using the idea of neutrosophic logic by [ 27 ]. This is a branch of mathematical statistics that provides the presentation, analysis, and inference of neutrosophic, fuzzy, interval, and indeterminate data. Classical statistics was considered a special case of neutrosophic statistics [ 28 , 29 , 30 , 31 , 32 , 33 ] discussed various applications of neutrosophic statistics.

The existing Chi-square test for K counts under classical statistics cannot be applied when the counts are in intervals. In this paper, the design of the Chi-square test for K counts under neutrosophic statistics will be given. We will extend the statistic for counts at the same time and at different times under neutrosophic statistics. The testing of the hypothesis will be given. The application of the proposed test will be given using the pulse counts data. By proposing the test, it is expected that the proposed test will be effective, flexible, informative, and adequate to be applied under uncertainty.

The pulse rate is theoretically is considered a discrete variable. The application of the proposed test is given using the counts of the pulse rate of 11 patients. The first 11 values of data are obtained from [ 34 ] and the next values are generated by simulation. The data is shown in Table  1 . A cardiologist is interested to see either the same treatment should be applied to all patients or not. Therefore, the null hypothesis for this case is that the same treatment method should be applied vs. the alternative hypothesis that different methods of treatment should be applied to all patients. As the pulse counts are noted in the same period of time, therefore, the statistic \({\chi}_{1N}^2\epsilon \left[{\chi}_{1L}^2,{\chi}_{1U}^2\right]\) is given in Eq. ( 1 ) a suitable statistic to apply for testing the given hypothesis. The neutrosophic form of \({\overline{N}}_{iN}\epsilon \left[{\overline{N}}_{iL},{\overline{N}}_{iU}\right]\) using the given data is given as \({\overline{N}}_{iN}=73.54+91.8{I}_{i\overline{N}};{I}_{i\overline{N}}\epsilon \left[\mathrm{0,0.1989}\right]\) .The test statistic \({\chi}_{1N}^2\epsilon \left[{\chi}_{1L}^2,{\chi}_{1U}^2\right]\) for the given data is computed as \({\chi}_{1N}^2=\sum_{i=1}^K\frac{{\left({N}_{iN}-{\overline{N}}_{iN}\right)}^2}{{\overline{N}}_{iN}}=\left[\mathrm{146.97,121.78}\right]\) .The neutrosophic form of the statistic \({\chi}_{1N}^2\epsilon \left[{\chi}_{1L}^2,{\chi}_{1U}^2\right]\) using the data is given as \({\chi}_{1N}^2=146.97-121.78{I}_{\chi_{1N}^2};{I}_{\chi_{1N}^2}\epsilon \left[\mathrm{0,0.2068}\right]\) . The proposed test will be implemented as follows

Step-1: State the null H 0 : all patients should be treated by the same method and alternative hypothesis  H 1 : patients should be treated with different methods.

Step-2: Let α  = 5% and critical values are 34.76 and 67.5.

Step-3: Reject H 0 as the values of \({\chi}_{1N}^2\epsilon \left[{\chi}_{1L}^2,{\chi}_{1U}^2\right]\) fall in the rejection region.

From the study, it can be concluded that cardiologists should use different methods of treatment for the patients.

As mentioned earlier, the neutrosophic form of the proposed test consists of two parts. The first and the second parts presented classical statistics and indeterminate, respectively. The neutrosophic form of \({\chi}_{1N}^2={\chi}_{1L}^2+{\chi}_{1U}^2{I}_{\chi_{1N}^2};{I}_{\chi_{1N}^2}\epsilon \left[{I}_{\chi_{1L}^2},{I}_{\chi_{1U}^2}\right]\) reduces to statistic under classical statistics when \({I}_{\chi_{1L}^2}=0\) . The efficiency of the proposed test will be compared with the existing test in terms of uncertainty measures. The neutrosophic form of \({\chi}_{1N}^2\epsilon \left[{\chi}_{1L}^2,{\chi}_{1U}^2\right]\) of pulse count data is \({\chi}_{1N}^2=146.97-121.78{I}_{\chi_{1N}^2};{I}_{\chi_{1N}^2}\epsilon \left[\mathrm{0,0.2068}\right]\) . When \({I}_{\chi_{1L}^2}=0\) , the value 146.97 presents the existing test statistic. The part \(121.78{I}_{\chi_{1N}^2}\) is an indeterminate part and \({I}_{\chi_{1U}^2}\) = 0.2068 is the uncertainty measure associated with statistic \({\chi}_{1N}^2\epsilon \left[{\chi}_{1L}^2,{\chi}_{1U}^2\right]\) . From the neutrosophic form, it can be seen that the proposed test statistic can be expressed in interval rather than the exact value. Under uncertainty, the value of the test statistic is from 146.97 to 121.78. From this study, it can be seen that the proposed test gives the results in the indeterminate interval that is expecting under uncertainty. On the other, the proposed statistic gives information about indeterminacy. Under an indeterminate environment, the proposed test has the interpretation like: when  α  = 5%, the probability of committing a type-I error is 0.05, the probability of accepting H 0 is 0.95 and the chance of indeterminacy about the accepting or rejecting H 0 is 0.2068. Let β is the probability of rejecting H 0 when it is true. To study the power of test (1 −  β ) for the proposed test and the existing test, various values of the level of significance α are considered. The neutrosophic data is generated from 45 to 55 and the values of \({\chi}_{1N}^2\epsilon \left[{\chi}_{1L}^2,{\chi}_{1U}^2\right]\) are computed and compared with the critical values at various levels of  α . The probability of rejecting H 0 when it is true ( β ) is calculated and used to calculate the power of the test (1 −  β ). The values of (1 −  β ) at various values of α are shown in Table  2 and plotted in Fig.  1 . From Table 1 , it can be seen that as the value of α increases from 0.1 to 0.99, the power of the test also increases. Figure  1 clearly indicates that the power curve of the proposed test is higher than the power curve of the existing test. The comparative study shows that the proposed test is efficient, revealing, and stretchy than the existing test. In addition, the proposed test provides higher values of power of the test as compared to the existing test.

Power curves of the proposed and existing tests at various values of α

The existing test for K counts under classical statistics is applied under the assumption that the data of counts must be noted under comparable conditions. The existing test to investigate the existing test between K counts can be applied only when the counts are exact, precise, and clear. In this section, the proposed test for K counts will be introduced when the count data is in indeterminate intervals, unclear and vagueness. The proposed test will be designed when the time of counts is equal and not equal. The method of the proposed test when times of counts are equal is designed first. Let N iN  =  N iL  +  N iU I iN ; I iN ϵ [ I iL ,  I iU ] be neutrosophic counts at ith time, where N iL presents exact counts, N iU I iN presents inexact or indeterminate counts and I iN ϵ [ I iL ,  I iU ] be a measure of indeterminacy associated with the counts. Suppose that \({\overline{N}}_{iN}={\overline{N}}_{iL}+{\overline{N}}_{iU}{I}_{i\overline{N}};{I}_{i\overline{N}}\epsilon \left[{I}_{i\overline{L}},{I}_{i\overline{U}}\right]\) be a neutrosophic average of K counts, where \({\overline{N}}_{iL}\) and \({\overline{N}}_{iU}{I}_{i\overline{N}}\) are the determined and indeterminate part of neutrosophic average and \({I}_{i\overline{N}}\epsilon \left[{I}_{i\overline{L}},{I}_{i\overline{U}}\right]\) be the measure of indeterminacy associated with the neutrosophic average. The proposed test will be applied for testing the null hypothesis H 0  :  N iN = constant, when  i  = 1, 2, 3, …, K . The test statistic under neutrosophic statistics say \({\chi}_{1N}^2\epsilon \left[{\chi}_{1L}^2,{\chi}_{1U}^2\right]\) can be written as follows.

The neutrosophic form of the proposed test \({\chi}_{1N}^2\epsilon \left[{\chi}_{1L}^2,{\chi}_{1U}^2\right]\) can be written as.

Note that the proposed statistic \({\chi}_{1N}^2\epsilon \left[{\chi}_{1L}^2,{\chi}_{1U}^2\right]\) is the extension of the test statistic under classical statistics. The proposed test statistic \({\chi}_{1N}^2\epsilon \left[{\chi}_{1L}^2,{\chi}_{1U}^2\right]\) reduces to classical statistic \({\chi}_{1L}^2\) when \({I}_{\chi_{1L}^2}=0\) . The second part \({\chi}_U^2{I}_{\chi_{1N}^2}\) presents the indeterminate part and \({I}_{\chi_{1N}^2}\epsilon \left[{I}_{\chi_{1L}^2},{I}_{\chi_{1U}^2}\right]\) is the measure of uncertainty.

Suppose now that the time to record ith neutrosophic count is  t i . The test statistic, say \({\chi}_{2N}^2\epsilon \left[{\chi}_{2L}^2,{\chi}_{2U}^2\right]\) under neutrosophic statistics for this case is given by.

where \({\overline{R}}_N=\sum {N}_{iL}/\sum {t}_{iL}+\sum {N}_{iU}/\sum {t}_{iU}{I}_{{\overline{R}}_N};{I}_{{\overline{R}}_N}\epsilon \left[{I}_{{\overline{R}}_L},{I}_{{\overline{R}}_U}\right]\) and \({I}_{{\overline{R}}_N}\epsilon \left[{I}_{{\overline{R}}_L},{I}_{{\overline{R}}_U}\right]\) is a measure of indeterminacy. The neutrosophic form of test statistic \({\chi}_{2N}^2\epsilon \left[{\chi}_{2L}^2,{\chi}_{2U}^2\right]\) is expressed as follows.

Note that the proposed statistic \({\chi}_{2N}^2\epsilon \left[{\chi}_{2L}^2,{\chi}_{2U}^2\right]\) is the extension of the test statistic under classical statistics. The proposed test statistic \({\chi}_{2N}^2\epsilon \left[{\chi}_{2L}^2,{\chi}_{1U}^2\right]\) reduces to classical statistic \({\chi}_{2L}^2\) when \({I}_{\chi_{2L}^2}=0\) . The second part \({\chi}_U^2{I}_{\chi_{2N}^2}\) presents the indeterminate part and \({I}_{\chi_{2N}^2}\epsilon \left[{I}_{\chi_{2L}^2},{I}_{\chi_{2U}^2}\right]\) is the measure of uncertainty. The proposed test will be implemented in the following steps

Step-1: State the null H 0 and alternative hypothesis  H 1 .

Step-2: State the level of significance  α and decide about the critical region using the Chi-square table.

Step-3: Reject H 0 if \({\chi}_{1N}^2\epsilon \left[{\chi}_{1L}^2,{\chi}_{1U}^2\right]\) or \({\chi}_{2N}^2\epsilon \left[{\chi}_{2L}^2,{\chi}_{2U}^2\right]\) falls in the rejection area, otherwise accept H 1 .

In this paper the Chi-square tests for K counts under neutrosophic statistics was presented. The test statistic of the proposed test when K counts were recorded at the same time and different times was proposed. The proposed test was the modified version of the existing test for K counts. The testing of the hypothesis procedure was explained with the help of a real example. From the pulse count data, it is concluded that the proposed test is effective to apply in uncertainty. In addition, the proposed test provides higher values of the power of the test. The proposed test guides the cardiologists to apply different treatment methods for patients. The proposed test using big data can be extended us future research.

Availability of data and materials

All data generated or analysed during this study are included in this published article.

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Aslam, M. Chi-square test under indeterminacy: an application using pulse count data. BMC Med Res Methodol 21 , 201 (2021). https://doi.org/10.1186/s12874-021-01400-z

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DOI : https://doi.org/10.1186/s12874-021-01400-z

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• v.107(19); 2010 May

Choosing Statistical Tests

Jean-baptist du prel.

1 Institut für Epidemiologie, Universität Ulm

Bernd Röhrig

2 Medizinischer Dienst der Krankenversicherung Rheinland-Pfalz (MDK), Referat Rehabilitation/Biometrie

Gerhard Hommel

3 Institut für Medizinische Biometrie, Epidemiologie und Informatik (IMBEI) Universitätsmedizin Mainz

Maria Blettner

The interpretation of scientific articles often requires an understanding of the methods of inferential statistics. This article informs the reader about frequently used statistical tests and their correct application.

The most commonly used statistical tests were identified through a selective literature search on the methodology of medical research publications. These tests are discussed in this article, along with a selection of other standard methods of inferential statistics.

Results and conclusions

Readers who are acquainted not just with descriptive methods, but also with Pearson’s chi-square test, Fisher’s exact test, and Student’s t test will be able to interpret a large proportion of medical research articles. Criteria are presented for choosing the proper statistical test to be used out of the most frequently applied tests. An algorithm and a table are provided to facilitate the selection of the appropriate test.

Medical knowledge is increasingly based on empirical studies and the results of these are usually presented and analyzed with statistical methods. It is therefore an advantage for any physician if he/she is familiar with the frequently used statistical tests, as this is the only way he or she can evaluate the statistical methods in scientific publications and thus correctly interpret their findings. The present article will therefore discuss frequently used statistical tests for different scales of measurement and types of samples. Advice will be presented for selecting statistical tests—on the basis of very simple cases.

Statistical tests used frequently in medical studies

In order to assess which statistical tests are most often used in medical publications, 1828 publications were taken from six medical journals in general medicine, obstetrics and gynecology, or emergency medicine. The result showed that a reader who is familiar with descriptive statistics, Pearson’s chi-square test, Fisher’s exact test and the t-test, should be capable of correctly interpreting the statistics in at least 70% of the articles ( 1 ). This confirmed earlier studies on frequently used statistical tests in medical scientific literature ( 2 , 3 ). There have however been changes over time in the spectrum of the tests used. A survey of the analytical statistical procedures used in publications of the journal Pediatrics in the first six months of 2005 found that the proportion of inferential methods had increased from 48 to 89% between 1982 and 2005 ( 4 ). There was also a trend towards more complex test procedures. Nevertheless, here too, the most frequent tests were the t-test, the chi-square test, and Fisher’s exact test. This article will accordingly discuss these tests and their proper application, together with other important statistical tests. If the reader is familiar with this limited number of tests, he/she will be capable of interpreting a large proportion of medical publications. Information about the rarer statistical tests can be found in the corresponding articles, in advanced literature ( 5 – 7 ), or by consulting an experienced statistician.

What is the purpose of statistical tests?

Clinical studies [for example, [ 5 , 8 ]) often compare the efficacy of a new preparation in a study group with the efficacy of an established preparation, or a placebo, in a control group. Aside from a pure description ( 9 ), we would like to know whether the observed differences between the treatment groups are just random or are really present. This is because differences can be due to chance variability (scatter) in a parameter, such as the success of the treatment in the study group.

If a scientific question is to be examined by comparing two or more groups, one can perform a statistical test. This means that a null hypothesis must be formulated, which can in principle be rejected. Moreover, a suitable test parameter must be identified ( 10 , 11 ).

For example, a clinical study might investigate whether an antihypertensive drug works better than placebo. The test variable may then be the reduction in diastolic blood pressure, calculated from the mean difference in blood pressure between the active treatment and placebo groups. The null hypothesis is then: “There is no difference between the active treatment and the placebo with respect to antihypertensive activity” (effect = 0).

A statistical test then calculates the probability of obtaining the observed data (or even more extreme data), if the null hypothesis is correct. A small p-value means that this probability is slight. The null hypothesis is rejected if the p-value is less than a level of significance which has been defined in advance. A test variable (test statistic) is calculated from the observed data and this forms the basis of the statistical test. In our case, this might be the difference in mean blood pressure after six months. If specific assumptions are made about the distribution of the data (for example, normal distribution), the theoretical (expected) distribution of the test variable can be calculated.

The value of the test variable calculated from the observations is then compared with the distribution expected if the null hypothesis were correct ( 5 ). If this value is greater or less than a specific limit, it is unlikely that the null hypothesis is correct and the null hypothesis is accordingly rejected. The result is then “statistically significant at the level α”. The statistical test is thus a decision whether the observed value can be explained by chance, or whether it is greater than chance (statistically significant). The terms “level of significance” and the principle of the interpretation of p-values have already been discussed ( 10 , 11 ). The underlying steps in a statistical test are shown once again in the Box .

Steps in a statistical test

• Statement of the question to be answered by the study
• Formulation of the null and alternative hypotheses
• Decision for a suitable statistical test
• Specification of the level of significance (for example, 0.05)
• Performance of the statistical test analysis: calculation of the p-value
• p<0.05 leads to rejection of the null hypothesis and acceptance of the alternative hypothesis
• p≥0.05 leads to retention of the null hypothesis
• Interpretation of the test result

It is possible to be mistaken, either in the rejection or in the retention of the null hypothesis. The reason for this is that the values exhibit scatter, as, for example, not all patients react equally to a drug. An “error of the first type” is the mistaken rejection of the null hypothesis; the maximal probability of this error is the level of significance α. This is often chosen to be 5% ( 10 , 11 ). An “error of the second type” is the mistaken retention of the null hypothesis; the probability of this is ß, which is the same as 1 minus the power of the study. The power of the study is specified before the study starts and depends on the sample size, as well as other factors. A power of 80% is often selected ( 10 , 11 ).

Important steps in the decision for a statistical test

The decision for a statistical test is based on the scientific question to be answered, the data structure, and the study design. Before the data are recorded and the statistical test is selected, the question to be answered and the null hypothesis must be formulated. The test and the level of significance must be specified in the study protocol before the study is performed. It must be decided whether the test should be one-tailed or two-tailed. If the test is two-tailed, this means that the direction of the expected difference is unclear. One does not know whether there is a difference between the new drug and placebo with respect to efficacy. It is unclear in which direction the difference may be. (The new drug might even work less well than the placebo). A one-tailed test should only be performed when there is clear evidence that the intervention should only act in one direction.

The outcome variable (endpoint) is defined at the same time the question to be answered is formulated. Two criteria are decisive for the selection of the statistical test:

• The scale of measurement of the test variable (continuous, binary, categorical)
• The type of study design (paired or unpaired).

Scales of measurement: continuous, categorical, or binary

The different scales of measurement have already been discussed in the articles on study design and descriptive statistics, under the selection of suitable measures and methods of illustration ( 9 , 12 ).

For example, in the comparison of two antihypertensives, the endpoint can be the antihypertensive activity in the two treatment groups. The reduction in blood pressure is a continuous endpoint. It is also necessary to distinguish whether a continuous endpoint is (approximately) normally distributed or not.

If however one only considers whether the diastolic blood pressure falls under 90 mm Hg or not, the endpoint is then categorical. It is even binary, as there are only two possibilities. If there is a meaningful sequence in the categorical endpoints, this can be described as an “ordinal endpoint.”

Paired and unpaired study designs

A statistical test is used to compare the results of the endpoint under different test conditions (such as treatments). There are often two therapies.

If results can be obtained for each patient under all experimental conditions, the study design is paired (dependent). For example, two times of measurement may be compared, or the two groups may be paired with respect to other characteristics.

Typical examples of pairs are studies performed on one eye or on one arm of the same person. Typical paired designs include comparisons before and after treatment. “Matched pairs,” for example in case-control studies, are a special case. This involves selecting persons from one group with the same specified characteristics as persons in another group. The data are then no longer independent and should be treated as if they were paired observations from one group ( 5 ).

With an unpaired or independent study design, results for each patient are only available under a single set of conditions. The results of two (or more) groups are then compared. There may be differences in the sizes of the groups.

Common statistical tests

The most important statistical tests are listed in the Table . A distinction is always made between “categorical or continuous” and “paired or unpaired.” If the endpoint is continuous, normal and non-normal distributions are distinguished ( Table ).

Group comparison of two categorical endpoints

The group comparison for two categorical endpoints is illustrated here with the simplest case of a 2 x 2 table (four field table) ( Figure 1 ). However, the procedure is similar for the group comparison of categorical endpoints with multiple values ( Table ).

Test selection for group comparison with two categorical endpoints;

*1 Preconditions: sample size

>ca. 60. Expected number in each field ≥5

If the frequency of success in two treatment groups is to be compared, Fisher’s exact test is the correct statistical test, particularly with small samples ( 7 ). For large samples (about n >60), the chi-square test can also be used ( Table ).

One example of the use of this test would be an intervention within a group at two anatomical sites, such as the implantation of two different sorts of IOL lenses in the right and left eyes, with the endpoint “Operation successful: yes or no.” The samples to be compared are paired. In such a case, one has to perform the McNemar test ( 7 ).

Continuous and at least ordinally scaled variables

Figure 2 shows a decision algorithm for test selection.

Algorithm for test selection for group comparison of a continuous endpoint

Normally distributed variables—parametric tests: So-called parametric tests can be used if the endpoint is normally distributed.

Where subjects in both groups are independent of each other (persons in first group are different from those in second group), and the parameters are normally distributed and continuous, the unpaired t-test is used. If a comparison is to be made of a normally distributed continuous parameter in more than two independent (unpaired) groups, analysis of variance (ANOVA) can be used. One example would be a study with three or more treatment arms. ANOVA is a generalization of the unpaired t-test. ANOVA only informs you whether the groups differ, but does not say which groups. This requires methods of multiple testing ( 11 ).

The paired t-test is used for normally distributed continuous parameters in two paired groups. If a normally distributed continuous parameter is compared in more than two paired groups, methods based on analysis of variance are also suitable. The factor describes the paired groups—for example, more than two points of measurement in the use of a therapy.

Non-normally distributed variables—non-parametric tests: If the parameter of interest is not normally distributed, but at least ordinally scaled, non-parametric statistical tests are used. One of these tests (the “rank test”) is not directly based on the observed values, but on the resulting rank numbers. This necessitates putting the values in order of size and giving them a running number. The test variable is then calculated from these rank numbers. If the necessary preconditions are fulfilled, parametric tests are more powerful than non-parametric tests. However, the power of parametric tests may sink drastically if the conditions are not fulfilled.

The Mann-Whitney U test (also known as the Wilcoxon rank sum test) can be used for the comparison of a non-normally distributed, but at least ordinally scaled, parameter in two unpaired samples ( 5 ). If more than two unpaired samples are to be compared, the Kruskal-Wallis test can be used as a generalization of the Mann-Whitney U test ( 13 ).

The Wilcoxon signed rank test can be used for the comparison of two paired samples of non-normally distributed, but at least ordinally scaled, parameters ( 13 ). Alternatively, the sign test should be used when the two values are only distinguished on a binary scale—for example, improvement versus deterioration ( 7 ). If more than two paired samples are being compared, the Friedman test can be used as a generalization of the sign test.

Other test procedures

Survival time analysis.

If the point of interest is not the endpoint itself, but the time till it is reached, survival time analysis is the most suitable procedure. This compares two or more groups with respect to the time when an endpoint is reached (within the period of observation) ( 13 ). One example is the comparison of the survival time of two groups of cancer patients given different therapies. The endpoint here is death, although it could just as well be the occurrence of metastases. In contrast to the previous tests, it almost never happens that all subjects reach the endpoint in survival time analysis, as the period of observation is limited. For this reason, the data are also described as (right) censored, as it is still unclear when all subjects will reach the endpoint when the study ends. The log rank test is the usual statistical test for the comparison of the survival functions between two groups. A formula is used to calculate the test variable from the observed and the expected numbers of events. This value can be compared with the known distribution which would have been expected if the null hypothesis were correct—the chi-square distribution in this case. A p-value can thus be calculated. A rule can then be given for deciding for or against the null hypothesis.

Correlation analysis

Correlation analysis examines the strength of the correlation between two test variables, for example, the strength of the correlation between the body weight of a neonate and its body length. The selection of a suitable measure of association depends on the scale of measurement and the distribution of the two parameters. The parametric variant (Pearson correlation coefficient) exclusively tests for a linear correlation between continuous parameters. On the other hand, the non-parametric variant—the Spearman correlation coefficient—solely tests for monotonous relationships for at least ordinally scaled parameters. The advantages of the latter are its robustness to outliers and skew distributions. Correlation coefficients measure the strength of association and can have values between –1 and +1. The closer they are to 1, the stronger is the association. A test variable and a statistical test can be constructed from the correlation coefficient. The null hypothesis to be tested is then that there is no linear (or monotonous) correlation.

The null hypotheses for these statistical tests described in this article are that the groups are equal. These commonly used tests are also known as “inequality tests”. There are however other types of test. “Trend tests” examine whether there is a tendency for increasing or decreasing values in at least three groups. There are also “superiority tests”, “non-inferiority tests,” and “equivalence tests.” For example, a superiority test examines whether an expensive new drug is better than the conventional standard medication by a specific and medically relevant difference. A non-inferiority test might examine whether a cheaper new medicine is not much worse than a conventional medicine. The acceptable level of activity is specified before the start of the study on the basis of expert medical knowledge. An equivalence test is intended to show that a medication has approximately the same activity as a conventional standard medication. The advantages of the new medication might be simpler administration, fewer side effects, or a lower price.

The methods of regression analysis and the related statistical tests will be discussed in more detail in the course of this series on the evaluation of scientific publications.

The present selection of statistical tests is obviously incomplete. Our intention has been to make it clear that the selection of a suitable test procedure is based on criteria such as the scale of measurement of the endpoint and its underlying distribution. We would like to recommend Altman’s book ( 5 ) to the interested reader as a practical guide. Bortz et al. ( 7 ) present a comprehensive overview of non-parametric tests (in German).

The selection of the statistical test before the study begins ensures that the study results do not influence the test selection. Moreover, the necessary sample size depends on the test procedure selected. Problems in planning sample size will be discussed in more detail later in this series.

Finally, the point must be made that a statistical test is not necessary for every study. Statistical testing can be dispensed with in purely descriptive studies ( 12 ) or when the interrelationships are based on scientific plausibility or logical arguments. Statistical tests are also usually not helpful when investigating the quality of a diagnostic test procedure or rater agreement (for example, in the form of a Bland-Altman diagram) ( 14 ). Because of the probability of error, statistical tests should be used “as often as necessary, but as little as possible.” The risk of purely chance results is especially high with multiple testing ( 11 ).

Acknowledgments

Translated from the original German by Rodney A. Yeates, M.A., Ph.D.

Conflict of interest statement

The authors declare that no conflict of interest exists according to the guidelines of the International Committee of Medical Journal Editors.

• Research article
• Open access
• Published: 19 September 2005

Aerobic exercise and its impact on musculoskeletal pain in older adults: a 14 year prospective, longitudinal study

• Bonnie Bruce 1 ,
• James F Fries 1 &
• Deborah P Lubeck 2  

Arthritis Research & Therapy volume  7 , Article number:  R1263 ( 2005 ) Cite this article

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We studied the long term impact of running and other aerobic exercise on musculoskeletal pain in a cohort of healthy aging male and female seniors who had been followed for 14 years. We conducted a prospective, longitudinal study in 866 Runners' Association members (n = 492) and community controls (n = 374). Subjects were also categorized as Ever-Runners (n = 565) and Never-Runners (n = 301) to include runners who had stopped running. Pain was the primary outcome measure and was assessed in annual surveys on a double-anchored visual analogue scale (0 to 100; 0 = no pain). Baseline differences between Runners' Association members and community controls and between Ever-Runners versus Never-Runners were compared using chi-square and t-tests. Statistical adjustments for age, body mass index (BMI), gender, health behaviors, history of arthritis and comorbid conditions were performed using generalized estimating equations. Runner's Association members were younger (62 versus 65 years, p < 0.05), had a lower BMI (22.9 versus 24.2, p < 0.05), and less arthritis (35% versus 41%, p > 0.05) than community controls. Runners' Association members averaged far more exercise minutes per week (314 versus 123, p < 0.05) and miles run per week (26 versus 2, p < 0.05) and tended to report more fractures (53% versus 47%, p > 0.05) than controls. Ever-Runners were younger (62 versus 66 years, p < 0.05), had lower BMI (23.0 versus 24.3, p < 0.05), and less arthritis (35% versus 43%, p < 0.05) than Never-Runners. Ever-Runners averaged more exercise minutes per week (291 versus 120, p < 0.05) and miles run per week (23 versus 1, p < 0.05) and reported a few more fractures (52% versus 48%, p > 0.05) than Never-Runners. Exercise was associated with significantly lower pain scores over time in the Runners' Association group after adjusting for gender, baseline BMI, and study attrition (p < 0.01). Similar differences were observed for Ever-Runners versus Never-Runners. Consistent exercise patterns over the long term in physically active seniors are associated with about 25% less musculoskeletal pain than reported by more sedentary controls, either by calendar year or by cumulative area-under-the-curve pain over average ages of 62 to 76 years.

Introduction

The prevalence of older adults in the United States is growing at a substantial rate. By 2030, nearly one-fifth of Americans will be in their sixties or older [ 1 ], which will have a considerable impact on public health. Numerous epidemiological and clinical studies have established that older adults who participate in regular physical activity are healthier and have a better quality of life than those who are inactive [ 2 – 4 ]. Regular exercise has also been shown to reduce pain in patients with knee osteoarthritis [ 5 , 6 ] and to help prevent mechanical low back pain [ 7 ]. In contrast, inactivity has been associated with greater pain with injury and has been associated with lower bone density and muscle tone [ 8 ]. On the other hand, some aerobic activities, such as running, have been found to result in increased risk for stress or other fractures [ 9 , 10 ]. Recurring trauma to soft tissue resulting from excessive physical activity conceivably could increase pain and disability [ 11 ]. Few studies have addressed the relationship between aerobic exercise and the perception of pain with advancing age.

To study the effect of exercise on disability and pain, our group [ 10 ] had investigated the relationship of running and its impact on musculoskeletal pain and disability in cohorts of Runners' Association members and community controls and Ever-Runners and Never-Runners who were followed prospectively for six years. In that study, no increase in joint pain or stiffness with age was observed in subjects who exercised often and intensely compared with their more sedentary counterparts. Pain was reduced, however, at all time points by about 25% in the exercising group. In fact, there was a slight decrease in pain for women who exercised over time.

In this investigation, we have extended that research in those cohorts. We have evaluated the association of vigorous physical activity with pain with advancing age after 14 years of follow-up. We hypothesized that those who regularly participated in running or other aerobic activity would report less musculoskeletal pain rather than more over the long term than did their inactive counterparts.

Materials and methods

Sample selection and data collection methodology have been detailed previously [ 10 ]. Subjects were drawn from two groups: the Fifty-Plus Runners' Association with members across the United States and a Stanford University community-based random sample from the Lipid Research Clinics Study (community controls) which provided access to a sample that was similar in age to the Runners' Association. In this analysis, all subjects with at least two annual questionnaires were included. A total of 961 men and women (538 Runners' Association members and 423 community controls) who met eligibility criteria of being at least 50 years old, had at least a high school education, and used English as their primary language were initially enrolled in 1984. A major re-recruitment effort in 1991 targeted subjects who had dropped out in the first years of the study. To attenuate self-selection bias and exercise effects due to the exercisers among the community controls, we also created groups of Ever-Runners and Never-Runners based on responses to the question at baseline: "Have you ever run for exercise for a period greater than one month?" The study was approved by the Stanford University Investigational Review Board, and each subject gave their informed consent.

Data collection

Each subject completed annual, mailed health assessment questionnaires [ 12 , 13 ]. The questionnaire includes items on medical history, health status, exercise habits, history of musculoskeletal injuries, health care utilization, and demographic variables, such as height and weight, smoking, and alcohol use.

Assessment of physical activity

Physical activity data were obtained from responses to the question: "How many minutes each week do you exercise vigorously (vigorous exercise will cause you to sweat, and your pulse, if taken, will be above 120). Include periods of rapid walking at work and in daily activities." Subjects indicated their participation in running, jogging, swimming, bicycling/stationary bike, aerobic dance/exercises, stair steppers, brisk walking, hiking/treadmill, racket sports, and other.

Assessment of pain

Annually since 1987, pain was assessed using a visual analog scale (VAS) where 0 = no pain and 100 = worst pain. From 1987 through 1989, subjects responded to the question "How bad has pain or stiffness been in the past week?" and marked their response on the VAS. In 1987, the VAS anchors were: 0 = no pain or stiffness; and 100 = very severe pain or stiffness. In 1988 and 1989, the VAS anchors were: 0 = no pain; and 100 = severe pain. Beginning in 1990, a closed-end stem about the presence or absence of pain was added. If the patient affirmed they had pain, then they rated their amount of pain on the VAS. If they responded "No", then their pain score was assigned a value of zero.

Statistical analysis

Differences between groups at first evaluation (baseline) were compared using chi-square and t-tests. Results are reported as mean (SE) or proportion. Longitudinal data were analyzed using generalized estimating equations (GEE) [ 14 ]. Separate analyses were conducted in which repeated measurements were coded by calendar year for questionnaire response and by age. Main-effect predictors were exercise group (Runners' Association/community controls), gender, baseline age, baseline body mass index (BMI; kg/m 2 ), years of education, number of hospital days in the past year, and dichotomous variables for smoking, and history of arthritis, fractures, and cancer at baseline. Baseline values y t = 1987 were defined as weighted means [ 15 ],

For all analyses, exercise group and gender were combined to form a four-level classification factor. Two-way interactions of each predictor with this classification factor were also included. To reduce collinearity, each continuous predictor was dichotomized about its mean. This dichotomization also produced estimates of gender and exercise group main effects that were more meaningful.

Four analytic approaches were employed to help reduce the impact of possible self-selection bias. First, we conducted a separate analysis by Ever-Runner and Never-Runner classification as well as by Runners' Association and community controls groups (from original enrollment). This grouping expanded the cases to include individuals who self-selected to run at an earlier age and who stopped running because of pain or other reasons before entering the study. Second, we used covariate adjustment to account for baseline differences between groups. Direct standardization [ 16 ] was used to produce covariate-adjusted mean VAS pain by exercise group and by study year for statistically significant predictors that were identified by the above regression analyses. Data for the community controls group from the first year that VAS pain was observed (1987) served as the reference standard. In addition to providing adjustment for differences on covariates between Runners' Association and community controls groups, use of a standard taken at baseline also permitted adjustment for possible attrition bias. Third, we assessed attrition bias (because any differential attrition between groups could result in a secondary form of self-selection bias) by performing separate analyses limited to study subjects who completed all questionnaires in addition to all subjects (completers versus all). Finally, we used a longitudinal study design in which an adverse stimulus is expected to eventually result in a poor outcome regardless of initial self-selection bias if groups differ sufficiently in exposure to the stimulus. If running creates damage through accumulated trauma, then runners with about ten-fold the amount of exposure to such trauma should have increased pain over time, and any initial differences due to self-selection should narrow as the study progresses.

In 1987, the first year that VAS pain was assessed, 811 subjects returned questionnaires (458 Runners' Association members; 353 community controls). The 1991 re-recruitment efforts increased study enrollment to 881 subjects (496 Runners' Association members; 385 community controls). Fifteen subjects were excluded from these analyses because classification data for Ever-Runner versus Never-Runner were not available. Over the study duration, subject retention averaged more than 95% on an annual basis (and 98% of living subjects each year) as shown in Fig. 1 . The mean (SE) years of follow up for Runners' Association and community controls were 11.4 (0.17) and 10.1 (0.22) (p < 0.05 for difference), respectively, and for Ever-Runners and Never-Runners it was 11.4 (0.16) and 10.5 (0.25) (p < 0.05 for difference), respectively. Data for this study are based on 866 subjects (492 Runners' Association and 374 community controls), who were also grouped as Ever-Runners (n = 565) and as Never-Runners (n = 301), for whom data were available.

Sample size over time for Runners' Association members and community controls.

Demographic characteristics at the beginning of the study are presented for the four study groups in Table 1 . Overall, subjects were similarly well educated, but Runners' Association members and Ever-Runners were statistically younger, had lower BMI and baseline pain scores, ran more miles, exercised more minutes per week, and smoked less (all p < 0.05) relative to community controls and Never-Runners. History of arthritis was lower in Runners' Association members and Ever-Runners than community controls and Never-Runners, but statistically significant only for Ever-Runners versus Never-Runners. In quintiles of baseline exercise minutes/week, less than a fourth (22%, n = 37) of Ever-Runners and less than a tenth (7%, n = 12) of Runners' Association members were inactive, exercising less than 70 minutes a week (data not shown). In contrast, at the highest quintile, 88% (n = 155) of Runners' Association members and 91% (n = 159) of the Ever-Runners exercised between 355 and 2,119 minutes/week, indicating that subjects in both of these groups were very physically active. At the end of the study period, the groups had maintained similar levels of exercise minutes/week.

Baseline demographic characteristics for the two sets of groups by gender are shown in Table 2 . For both Runners' Association members and Ever-Runners, the greater majority of subjects were male (approximately 83%), whereas in community controls and Never-Runners the sex ratios were more evenly split (56% and 50%, respectively). In females, Runners' Association members were younger, weighed less, reported less pain, fewer hospital days during the past year, ran more miles and exercised more minutes a week (all p < 0.05) than female community controls. Female Runners' Association members were also better educated, smoked less, and drank less alcohol than their community control counterparts (all p > 0.05) and there was a higher proportion of females with a history of arthritis and a lower proportion of females with a history of fractures in the community controls and Never-Runners compared to their counterparts, but these differences were statistically indistinguishable. Characteristics of male Runners' Association members versus community controls followed similar patterns, although differences in VAS pain and hospital days were not statistically significant, whereas education, smoking and alcohol were.

Pain scores over time, adjusted for group, gender and baseline BMI, are presented in Fig. 2 for each study group (Runners' Association members, community controls, Ever-Runners, and Never-Runners). The statistically significant covariates, excluding time and group, were gender (p < 0.01), baseline BMI (p < 0.01), cigarette packs/day and number of hospital days (p = 0.02). For both comparison groups of runners (Runners' Association and Ever-Runners), pain scores remained significantly lower over time (p < 0.01) when compared with community controls or Never-Runners. The dip in scores between 1987 and 1991 is a result of the rephrasing and coding of the pain question as described earlier. Pain scores were consistently about 25% less in the exercising group throughout the period of observation.

Adjusted mean visual analog scale pain scores over time by study group. For both comparison groups of runners (Runners' Association members and Ever-Runners), pain scores remained significantly lower over time (p < 0.01) when compared with community controls or Never-Runners.

Because gender was a significant covariate, pain scores over time are presented by gender in Fig. 3 , adjusted for covariates. Significant covariates, excluding time and group, are fracture in past year (p = 0.026) and the presence of arthritis (p < 0.001). As observed previously, community controls have more pain over time; however, female controls have the greatest self-reported pain, with female and male controls reporting significantly more pain than either female runners (p = 0.048) or male runners (p = 0.004). Similar results were observed for VAS pain scores by gender for Never-Runners and Ever-Runners (data not shown).

Adjusted mean visual analog scale pain scores over time by gender and study group. After adjusting for covariates, the community controls have more pain over time; however, female controls have the greatest self-reported pain, with female and male controls reporting significantly more pain than either female runners (p = 0.0048) or male runners (p = 0.004).

To evaluate the impact of study attrition and the possibility that withdrawal from the study might be associated with increased pain, we repeated the analyses by group and gender for study completers only. There were 61 female runners, 253 male runners, 84 female community controls and 116 male community controls who completed all questionnaires. In addition to time, group, and gender, presence of arthritis (p < 0.001) and education years (p = 0.036) were significant covariates. Similar to results of analyses using all available data, reduced levels of pain for male and female runners were observed in completers, although the only statistically significant difference over time is between female runners and male and female controls (p < 0.05).

Our final analyses tested the extent to which exercise and pain were affected by increasing age (Fig. 4 ). As in previous analyses, a history of arthritis and fractures were significant covariates (p < 0.001). There were significant increases in pain scores for female and male community controls and runners with increasing age, although the rates of increase are relatively modest. Older female runners tended to have the greatest beneficial impact, although these associations were statistically equivalent to differences in male runners and controls (p = 0.51).

Adjusted mean visual analog scale pain scores by age, gender and study group. Significant increases in pain scores for female and male community controls and runners were found with increasing age, although rates of increase are relatively modest. Older female runners tend to have the greatest benefit, although these associations are statistically equivalent to differences in male and female runners and controls (p = 0.51).

This paper addresses the issue as to whether consistent vigorous exercise patterns over the long term are associated with greater or reduced musculoskeletal pain. In these cohorts, runners had substantially reduced pain levels compared with controls, which persisted over average ages of 62 to 76 years. Exercise was associated with a substantial and significant reduction in pain even after adjusting for gender, baseline BMI and attrition, and despite the fact that fractures, a significant predictor of pain, were slightly more common among runners. This relationship held as well when study completers only were evaluated.

Previous studies have indicated that men and women can differ in levels of self-reported pain and its importance [ 17 – 20 ]. In this study, male community controls reported less pain than their female counterparts. Female community controls and Never-Runners tended to report the highest levels of pain on average, whereas female runners appeared to receive the greatest benefit in reduced pain.

This study does not provide insight into the mechanisms that might underlie these results, although we have previously ruled out self-report bias between runners and non-runners by differential validation against spousal values [ 21 ]. A trend toward more frequent reports of a history of arthritis in controls could have played a role; fractures, however, were more common in runners and should have worked in the opposite direction. Other possible mechanisms include endorphin release, exercise protection against secondary fibromyalgia, increased resistance to musculoskeletal micro-injury, psychologically based increase in pain threshold, innately high pain threshold influencing decision to exercise vigorously, or other psychological mechanisms.

Musculoskeletal pain has also been shown to be associated with disability in older individuals and individuals with some chronic diseases [ 22 , 23 ]. But in a study of persons with rheumatoid arthritis, Ward and Leigh [ 22 ] noted that pain was a larger contributor to measurement of overall health status than physical disability and among both older male and female individuals. Leveille and colleagues [ 23 ] evaluated the presence of pain in women over 65 years of age and observed widespread musculoskeletal pain.

The primary finding from this investigation is that while pain does increase with age in subjects in all study groups, there was no progressive increase in musculoskeletal pain in older adults who participated in regular vigorous exercise, including running, compared with those who did not. Initial differences favoring exercisers were shown to be maintained over time. As pain and disability are linked, our findings add to the evidence that morbidity associated with aging can be reduced by participating in regular aerobic activity.

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Acknowledgements

This research was supported by a grant from the National Institutes of Health (5R01-AG15815) to Stanford University, Department of Immunology/Rheumatology (JFF, Principal Investigator).

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BB performed statistical analyses, interpretation of data, and drafting of the manuscript; JFF participated in study design, interpretation of data, and drafting of the manuscript; DL participated in study design, statistical analyses, interpretation of data, and drafting of the manuscript. All authors have read and approved the final manuscript.

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Bruce, B., Fries, J.F. & Lubeck, D.P. Aerobic exercise and its impact on musculoskeletal pain in older adults: a 14 year prospective, longitudinal study. Arthritis Res Ther 7 , R1263 (2005). https://doi.org/10.1186/ar1825

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DOI : https://doi.org/10.1186/ar1825

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How to Conduct a Chi-Square Test

In social science research, one of the common tasks researchers undertake is analyzing relationships between categorical variables. Understanding how variables like gender, ethnicity, or occupation are distributed across different categories can reveal significant insights about patterns of inequality , social behavior, or institutional biases. One powerful statistical tool used to analyze such relationships is the Chi-Square test. This test allows sociologists to explore whether the observed frequencies in a categorical dataset deviate from what would be expected under a given hypothesis. In this article, we will explore how to conduct a Chi-Square test step-by-step, breaking down the concepts and calculations in a way that is accessible to undergraduate sociology students.

Understanding the Chi-Square Test

The Chi-Square test is a statistical method designed to examine the association between two or more categorical variables. These variables represent data that can be categorized into distinct groups or categories. For instance, gender (male, female, other) and level of education (high school, college, graduate) are examples of categorical variables that may be of interest in sociological research. The test compares the observed frequencies of different categories against the expected frequencies, under the assumption that there is no association between the variables.

There are two primary types of Chi-Square tests: the Chi-Square test for independence and the Chi-Square test for goodness of fit. The test for independence examines whether two categorical variables are related, while the goodness-of-fit test determines if the observed distribution of a single categorical variable matches an expected distribution. In this article, we will focus on the Chi-Square test for independence, as it is more commonly used in sociology research.

When to Use a Chi-Square Test

Before diving into the details of how to conduct a Chi-Square test, it is essential to understand when it is appropriate to use this statistical tool. The Chi-Square test is best suited for scenarios where the data is categorical and the researcher is interested in testing the relationship between two variables. Some common sociological research questions that can be addressed using a Chi-Square test include:

• Is there a relationship between gender and voting behavior?
• Are educational attainment levels related to employment status ?
• Does racial or ethnic background correlate with access to healthcare?

To use the Chi-Square test effectively, the data must meet certain conditions:

• Independence : The observations in each category must be independent of each other. This means that no individual or case should appear in more than one category.
• Expected Frequencies : Each cell in the contingency table (which we will discuss shortly) should have an expected frequency of at least 5. If the expected frequencies are too small, the results of the test may be unreliable.
• Sample Size : The test is more reliable with larger sample sizes. While there is no strict rule, having at least 30 observations is generally recommended for a Chi-Square test.

If these conditions are met, the Chi-Square test is an appropriate method for testing relationships between categorical variables.

Steps for Conducting a Chi-Square Test

1. formulating hypotheses.

As with any statistical test, conducting a Chi-Square test begins with formulating two hypotheses: the null hypothesis (H₀) and the alternative hypothesis (H₁).

• Null Hypothesis (H₀) : This hypothesis states that there is no relationship between the two categorical variables. In other words, the variables are independent of each other.
• Alternative Hypothesis (H₁) : The alternative hypothesis suggests that there is a relationship between the variables, meaning that they are not independent.

For example, if you are studying the relationship between gender and voting behavior, your hypotheses might be:

• H₀ : There is no relationship between gender and voting behavior.
• H₁ : There is a relationship between gender and voting behavior.

2. Collecting and Organizing Data

Next, gather data on the variables you are interested in examining. This data should be categorical, with each observation falling into one category for each variable. Once you have collected the data, organize it into a contingency table , which displays the frequencies of observations for each combination of categories.

For instance, if you are analyzing the relationship between gender and voting behavior, your contingency table might look like this:

In this example, the table shows the observed frequencies of individuals who voted or did not vote, broken down by gender.

3. Calculating Expected Frequencies

The next step involves calculating the expected frequencies for each cell in the contingency table, assuming that the null hypothesis is true (i.e., there is no relationship between the variables). The expected frequency for each cell is calculated using the following formula:

E ij = (Row Total of Row i × Column Total of Column j) / Grand Total

• E ij is the expected frequency for cell (i,j),
• Row Total of Row i is the total number of observations in the i-th row,
• Column Total of Column j is the total number of observations in the j-th column,
• Grand Total is the total number of observations in the entire dataset.

Let’s calculate the expected frequencies for the first cell (Male, Voted) using the table above. The row total for males is 60, the column total for those who voted is 110, and the grand total is 155.

E (Male, Voted) = (60 × 110) / 155 = 42.58

You would repeat this process for each cell in the contingency table to obtain the expected frequencies.

4. Computing the Chi-Square Statistic

Once you have the observed and expected frequencies, the next step is to calculate the Chi-Square statistic. This statistic measures the difference between the observed and expected frequencies for each cell in the contingency table. The formula for the Chi-Square statistic is:

χ 2 = ∑ [(O ij – E ij ) 2 / E ij ]

• χ 2 is the Chi-Square statistic,
• O ij is the observed frequency for cell (i,j),
• The sum is taken over all cells in the contingency table.

For each cell, you subtract the expected frequency from the observed frequency, square the result, and divide by the expected frequency. After calculating this value for all cells, you sum the results to obtain the overall Chi-Square statistic.

5. Determining Degrees of Freedom

Degrees of freedom (df) are a critical component in determining the significance of the Chi-Square statistic. In the case of a Chi-Square test for independence, the degrees of freedom are calculated using the formula:

df = (r – 1) × (c – 1)

• r is the number of rows in the contingency table,
• c is the number of columns in the contingency table.

In our example, there are 3 rows (Male, Female, Non-Binary) and 2 columns (Voted, Did Not Vote). Therefore, the degrees of freedom would be:

df = (3 – 1) × (2 – 1) = 2

6. Interpreting the Results

To determine whether the relationship between the variables is statistically significant, compare the calculated Chi-Square statistic to a critical value from the Chi-Square distribution table. The critical value depends on two factors: the degrees of freedom and the chosen significance level (often set at 0.05, or 5%).

If the calculated Chi-Square statistic is greater than the critical value, you can reject the null hypothesis, indicating that there is a significant relationship between the variables. If the Chi-Square statistic is less than the critical value, you fail to reject the null hypothesis, meaning that there is no evidence of a relationship between the variables.

7. Reporting the Results

When reporting the results of a Chi-Square test in a research paper or article, it is important to provide a clear summary of the findings. Typically, this includes the following information:

• The observed Chi-Square statistic,
• The degrees of freedom,
• The p-value (the probability that the observed association occurred by chance),
• Whether the result is statistically significant (i.e., whether you reject the null hypothesis),
• A brief interpretation of the findings in the context of the research question.

For example, you might report your results as follows:

“A Chi-Square test for independence was performed to examine the relationship between gender and voting behavior. The test revealed a significant association between the two variables, χ 2 (2, N = 155) = 6.12, p = 0.047, indicating that voting behavior is not independent of gender.”

The Chi-Square test is an invaluable tool in sociology, enabling researchers to explore the relationships between categorical variables and to test hypotheses about social behavior and structures. By following the steps outlined in this article—formulating hypotheses, collecting data, calculating expected frequencies, computing the Chi-Square statistic, determining degrees of freedom, and interpreting the results—sociologists can rigorously test whether observed patterns in their data reflect significant associations or are merely the result of random chance.

Understanding and correctly applying the Chi-Square test helps sociologists draw meaningful conclusions about the social world, contributing to broader discussions about inequality, social behavior, and institutional practices. As a fundamental part of the sociologist’s toolkit, mastering the Chi-Square test is essential for undergraduate students who wish to engage critically with empirical research.

Mr Edwards has a PhD in sociology and 10 years of experience in sociological knowledge

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• Published: 12 September 2024

Postoperative sensitivity of composites using novel Bacillus subtilis nanofortified adhesives: a triple-blind study

• Nehal Amir 1 ,
• Afsheen Mansoor 2 , 3 ,
• Nabiha Eeman 4 ,
• Muhammad Nouman Ahmed 5 ,
• Emaan Mansoor 6 ,
• Khadim Hussain 7 , 10 &
• Paulo J. Palma 8 , 9  

BMC Oral Health volume  24 , Article number:  1077 ( 2024 ) Cite this article

Metrics details

Nanotechnology

is the art and science of dealing with nanoscale particles. This has transformed contemporary dental practices through myriad contributions to biomaterial science. Titanium dioxide nanoparticles procured from Bacillus subtilis , an eco-friendly and biogenic source, can significantly magnify the physiochemical attributes of dental materials. However, postoperative sensitivity is a major drawback of composite restorations. The incorporation of these nanoparticles into dental adhesives can greatly benefit clinical dentistry by resolving this issue. This trial aimed to evaluate the effectiveness of a novel titanium dioxide nanofortified adhesive on the postoperative sensitivity of composite restorations.

This triple-blind, parallel-group randomized controlled trial was conducted at the Department of Operative Dentistry and Endodontics, School of Dentistry, Islamabad, from May 15, 2023, to November 25, 2023. Participants ( n  = 60) with Class I and II primary carious lesions with a minimum cavity depth of 3–5 mm were randomly assigned to two groups ( n  = 30). After obtaining informed consent, the restorative procedure was accomplished using a minimally invasive approach and etch-and-rinse adhesive strategy. In group A, a nanofortified adhesive was used for composite restoration, whereas in group B, an adhesive without nanoparticles was used. Postoperative sensitivity was evaluated using the Visual Analog Scale (VAS) score at follow-up periods: of one day, one week, two weeks and one month. A Chi-square test was used to compare postoperative sensitivity between the two groups. The level of significance was set at p  < 0.05.

A noteworthy association was observed between sensitivity and the group variable at all four evaluation periods: after one day ( p  = 0.002), 1 week ( p  = 0.002), 2 weeks ( p  = 0.007) and one month. In conclusion, participants who underwent restorative intervention using titanium dioxide nanoreinforced adhesives reported a notable reduction in sensitivity at all time intervals. Hence, the occurrence and severity of postoperative sensitivity are significantly reduced using Bacillus subtilis-procured nanofortified adhesives as compared to conventional adhesives without nanoparticles.

Trial registration

This trial was retrospectively registered at ClinicalTrials.gov (ID: NCT06242184) on 03/02/2024. All procedures involving human participants were performed in conformance with this protocol.

Peer Review reports

Nanotechnology is the implementation of scientific principles to substantially manipulate matter at the nanoscale to attain the prerequisites of dimensions- and structure-dependent attributes that are distinct from those associated with individual atoms, molecules, or extrapolation from larger sizes of the same material. It has gained immense popularity in clinical dentistry owing to its multitudinous contributions to dental biomaterials [ 1 , 2 ]. The pinnacle of nanoscience is nanoparticles, which are composed of atoms or molecules that congregate to form nanostructured agglomerates and provide dental materials with remarkable physiochemical and optical-magnetic qualities [ 3 ].

Nanoparticles are categorized as having organic, inorganic, or carbon-based lineages. Metal and metal oxide-based materials are exemplary inorganic nanoparticles. The outstanding attributes of metal oxide-based nanoparticles include their dimensions, which range from 10 to 100 nm; their configuration, which is spherical and cylindrical; and their surface qualities, which include pore size, enhanced surface-area-to-volume ratio, and surface charge. Titanium dioxide, also known as titania, is one of the most well-characterized metal-oxide nanoparticles. It has illustrious optical, magnetic, physicochemical, rheological, and biological properties. Titanium dioxide has a high refractive index, biocompatibility, and cost-effectiveness, making it an ideal choice for utilization in dental materials [ 4 , 5 ].

Composite resin, an esthetic adhesive material, is a paragon in contemporary restorative dentistry. This has transformed the paradigm to minimally invasive dentistry. Among the advantages of composite restorations are their distinguished aesthetics, adhesion to tooth structure, and preservation of healthy dental substrates [ 6 ]. Nonetheless, they have explicit shortcomings that jeopardize the long-term viability of posterior restorations. Polymerization shrinkage in composites is primarily responsible for these unfavorable outcomes, including cuspal deflection, postoperative sensitivity, secondary caries, marginal discoloration, restorative fracture, and microleakage at the tooth-restorative junction [ 7 ]. Post-operative sensitivity in composite restorations is caused by a multitude of reasons including iatrogenic pulpal damage during caries excavation, inadequate coverage and penetration of adhesives into the dentinal tubules, and the impact of various placement strategies, bonding techniques, curing modes, and the choice of composite material used. Incomplete hybridization is a major cause of sensitivity in composites. This predicament can be resolved by the prospective sealing potential of dental adhesives to occlude patent dentinal tubules at the dentin-adhesive interface. Nevertheless, because of the degeneration and long-term instability of the hybrid layer, this attribute of adhesives is susceptible to time-dependent decline [ 6 , 7 , 8 ].

Appreciable improvements in the physio-chemical properties and long-term stability of the tooth-adhesive interface can be achieved by fortifying dental adhesives with nanoparticles.Nano-particles, when incorporated into dental adhesives, enormously magnify the bonding capability of resins into dental substrate by its deeper penetration and sealing capability of the tubular network of dentin. Thus, it could massively reduce post-operative sensitivity in composite restorations [ 9 , 10 ]. The rationale of this study was to enhance the tubule-sealing ability of dental adhesives by enhancing the bonding performance of resins through the incorporation of nanoparticles, thus minimizing the issue of sensitivity. The objective of this trial was to evaluate the effectiveness of a novel titanium dioxide nanofortified adhesive on the postoperative sensitivity of composite restorations. The hypothesis stated that the occurrence and severity of postoperative sensitivity in composites were lessened using Bacillus subtilis-procured novel nanofortified adhesives compared to dental adhesives without nanoparticles.

Study design

The present study followed the CONSORT (Consolidated Standards of Reporting Trials) 2010 guidelines. This study was formulated as a triple-blind, parallel-group, randomized clinical trial with a 1:1 allocation ratio. The operator, data analyst, and participants were all blinded to the groups to which they were assigned. The participants were divided into two groups. Group A: Nano-fortified adhesive was employed for restorative treatment, whereas in Group B: Adhesive without nanoparticles was used. All participants were briefed about the study, along with its potential merits and demerits, and a consent form was validated by the principal investigator from each participant.

Sample size calculation

The sample size was calculated as 60 using the WHO calculator (30 participants in each interventional group). The test had a power of 80% and significance level of 5%. The population mean test result was 1.38, but the population standard deviation was calculated to be 1.6, and the expected population mean was 3.69 [ 11 ].

Patient selection and blinding

Participants fulfilling the inclusion criteria were selected from the outpatient department using a consecutive non-probability sampling method and were randomly divided by a trial-autonomous researcher in each study group using a Lottery method . For allocation concealment, an opaque sealed envelope with designated coding was employed for each study group. The dental adhesive used in this intervention had identical bottles with the assigned codes (A and B) for each interventional group. In this study, a trial-autonomous investigator performed both the blinding and allocation concealment. Table  1 presents the inclusion and exclusion criteria of this study.

Synthesis of microbial titanium dioxide nanoparticles

The strain of Bacillus Subtilis ( Accessions No; ATCC ® 6633TM-Catalog No/ 0486-SPR ) was obtained from National Institute of Health Islamabad , Pakistan for preparing the Titanium dioxide nanoparticles. They were fabricated via the methodology available in the reported literature [ 9 ]. The supernatant was prepared from fresh Bacillus Subtilis culture after centrifuging it at 10,000 RmP for about 10 min. Then, 80 ml of supernatant and 20 ml of 00.025 m Ti(-OH)2 (Americans Element, 10,884.0 WeYburn AVE/ Los Angeles; CA/90024.0,USA) were mixed together and were placed on metal plate at 60 o C for about 20.0 min where white crystal like deposits appeared at the bottom of the flask confirming the Titanium dioxide nanoparticles formation. The characterization techniques involved to identify its original phase, peak form, size, shape, texture, roughness, morphology, elemental composition, functional groups and biocompatibility were performed through equipments: DMAX/2400 Diffractometer (Rigaaku Corpooration: Akishimau Tokyo’s company Japan-), Scanning electron microscope-(NOVA Nanoseme 4300, FEI-company-HillsBoro, ORA, USA), Atomic force microscope (Quesant/Universal SPMS, Ambios-Technology: SantA Cruz’s, C-A, USA), Transmission electron microscope (Jeols JEMS-200CXX-Bioz Star’s: Tokoyo, Japan), Fourier transform infrared spectrophotometery (JASCOS FT/IRR-6600; Utrecht-T, Netherlands) and Spectrometer-(Lambda-A 9500, Perkins Elmer’s, Waltham-MA, USA) [ 4 , 9 , 12 ].

Properties of microbial titanium dioxide nanoparticles

The Titanium dioxide nanoparticles prepared by the microbes displayed mixed anatase-rutile phase having particle size of about 70.00 nm arranged in aggloremates. They possessed smooth texture with minimal roughness in their morphology. Moreover, these nanoparticles revealed pure titanium and oxygen in their elemental composition and confirmed the presence of carboxyl groups, amine groups and titanium-oxygen bendings in their spectrum. These were found to be biocompatible against fibroblast cell lines that enhanced their unique characteristics [ 4 , 9 , 12 ].

Incorporation of nanoparticles into dental adhesive

In this study, synthesized nanoparticles were mixed into a commercially available 5 mL bottle of adhesive (One Coat Bond SL Coltene, Switzerland) at a mass fraction of 30%.

Clinical procedure

The study was conducted at the Department of Operative Dentistry and Endodontics , School of Dentistry , Shaheed Zulfiqar Ali Bhutto Medical University , Islamabad , from May 15 , 2023 to November 25 , 2023 , after acceptance from the Institutional Ethical Committee ( SOD/ERB/2023/31 − 01 ). Before the initiation of the procedure, circumstantial medical and dental history was recorded. Each participant was anesthetized to ensure comfort during the procedure using the local anesthetic solution Lignospan Special-lidocaine hydrochloride 2% with 1:80,000 epinephrine (Septodont, USA). Under rubber dam isolation, carious lesions were excavated using a high-speed handpiece, the cavity design was delineated by the extent of the carious lesion, and the depth of the prepared cavity was estimated using a periodontal probe. Before initiating restorative treatment, a Palodent Plus Sectional Matrix System (Dentsply Sirona, USA) was used to obtain the desired proximal contour of the restoration.

Acid etching was performed using Phosphoric acid 35% (Etchant gel S Coltene, Switzerland) for 15–30 s. The enamel surface was etched for 30 s while dentin substrate was etched for 15 s. Afterwards, the area was rinsed with water for 20 s and allowed to air-dry for 5 s. The subsequent steps were executed in conformance with the fundamentals of adhesive dentistry (Fig.  1 ).

Group A (nanofortified dental adhesive): In this interventional group, titanium dioxide nanoparticles were incorporated in 5 mL adhesive (One Coat Bond SL Coltene, Switzerland). Using a microbrush, the etched surface was vigorously coated with adhesive for 20 s. This was followed by another application for 20 s. For 40 s, the adhesive coating was light-cured using an LED curing light (Woodpecker DTE LUX E Plus, Woodpecker, China). Subsequently, the restorative material (Brilliant NG Universal Nano Composite Coltene, Switzerland) was placed using the incremental packing strategy and light-cured for 40 s using a curing light Woodpecker DTE LUX E Plus (Woodpecker, China).

Group B (adhesive without nanoparticles): In this experimental group, a commercially available adhesive (One Coat Bond SL Coltene, Switzerland) without nanoparticles was employed, followed by the application of composite (Brilliant NG Universal Nano Composite Coltene, Switzerland) using the incremental packing strategy and light-curing for 40 s with curing light Woodpecker DTE LUX E Plus (Woodpecker, China).

Subsequently, the rubber dam was removed, the restoration was assessed for any occlusal modifications and the adequacy of inter-proximal contacts. Afterwards, the finishing was completed. The restoration was polished using a Jiffy Original Composite System (Ultradent, USA).

Clinical intervention for the restorative treatment

Assessment of postoperative sensitivity

The Visual Analog Scale (VAS) score was used to assess sensitivity after one day, one week, two weeks, and one month. VAS is a psychometric tool for measuring subjective attributes that cannot be measured. It is a 10 cm long scale with markings from 0 to 10, calibrated for sensitivity scores of 0 (none), 1–3 (mild), 4–6 (moderate), and 7–10 (severe) (Fig.  2 ) [ 11 , 13 , 14 ]. Moreover, participants were directed to rate whether their sensitivity was spontaneous or stimulated. They were instructed to mention the provoking stimuli.

Visual Analog Scale (VAS) score

Statistical analysis

The data were analyzed using SPSS software version 26. A Chi-square test was employed to compare the postoperative sensitivity between the two groups at the follow-up period. The level of significance was set at p  < 0.05.

A total of 112 participants were enrolled in this interventional study. Of these, 30 participants did not satisfy the inclusion criteria, 10 refused participation, and 12 had other reservations about this trial. The study comprised 60 participants, who were designated into two groups ( n  = 30). Table  2 provides a detailed overview of the critical variables based on the 60 participants. Figure  3 illustrates the CONSORT 2010 Flow Diagram.

CONSORT 2010 flow diagram

Postoperative sensitivity levels after one day, one week, two weeks, and one month show distinct patterns. After one day, the sensitivities ranged from none (25%) to severe (6.7%). After one and two weeks, the patterns of none, mild, moderate, and severe sensitivity persisted. After one month, 81.7% indicated no sensitivity, 15% indicated mild sensitivity, and 3.3% indicated moderate sensitivity. Table  3 depicts the cross-tabulations and chi-square tests that investigated the relationship between sensitivity at different time intervals and several categorical variables.

A noteworthy correlation was found between sensitivity after one day and the group variable ( p  = 0.002) (Fig.  4 ). The majority of participants in the “Adhesive with Nanoparticles” group reported no or mild sensitivity, whereas the “Adhesive without Nanoparticles” group reported a higher number of participants experiencing moderate and severe sensitivity. The analysis of sensitivity after one day and Black classification showed no statistically significant relationship between these variables ( p  = 0.65). The distribution of sensitivity levels was comparable between the Class I and Class II restorations. Analysis of sensitivity after one day and tooth distribution revealed no statistically significant correlation ( p  = 0.497). The sensitivity levels appeared to be similar for both the premolar and molar tooth distributions.

Distribution of sensitivity between group variables after one day

Sensitivity after one week in the group showed a significant correlation ( p  = 0.002). The group utilizing the “Adhesive with Nanoparticles” has a greater proportion of participants reporting no or mild sensitivity in comparison to the group using the “Adhesive without Nanoparticles” Adhesive without nanoparticles. Sensitivity after one week and black classification were analyzed using cross-tabulation. (Fig.  5 ) The results showed no statistically significant association between the two variables ( p  = 0.493). Sensitivity after one week did not show a statistically significant association with tooth distribution ( p  = 0.193). The sensitivity levels appear to be similar in both premolar and molar tooth distributions.

Distribution of sensitivity between group variables after one week

There were notable connections between sensitivity after two weeks and the group, as indicated by the statistical analysis ( p  = 0.007) (Fig.  6 ). The majority of participants in the “Adhesive with Nanoparticles” group reported either no sensitivity or mild sensitivity. In contrast, the “Adhesive without nanoparticles group had a higher percentage of participants experienced moderate sensitivity. The contingency table analysis for sensitivity after two weeks and black categorization revealed a weakly significant correlation ( p  = 0.05). However, there was no significant correlation between tooth distribution and sensitivity after two weeks ( p  = 0.66).

Distribution of sensitivity between group variables after two weeks

A strong correlation between the sensitivity after one month and the group (p  = 0.001) was observed. The majority of the participants in the “Adhesive with Nanoparticles” group reported no sensitivity. Moreover, sensitivity after one month does not show any significant correlation with black classification ( p  = 0.936) and tooth distribution ( p  = 0.989 ) (Fig.  7 ).

Distribution of sensitivity between the group variables after 1 month

Table  4 shows that participants who used “adhesives with nanoparticles” consistently exhibited reduced levels of sensitivity in comparison to those who used “adhesives without nanoparticles” at all four time points. After one day, a significant percentage of patients who had restorative treatment with nano-reinforced adhesives claimed that they did not experience any sensitivity (13 versus 2), and the group that did not have nanoparticles was the only one that experienced severe sensitivity. At the end of one week, the pattern was maintained, with a greater number of participants expressing no sensitivity (17 rather than 5), while a smaller number reported moderate sensitivity (2 rather than 12). At two weeks, this tendency became more obvious, with 22 patients with nanofortified adhesives reporting no sensitivity, compared to 11 participants in the group that did not use nanoparticles, and there were no reports of moderate sensitivity in the group that used titanium dioxide nanoparticles. Based on the results of this study, it can be deduced that adhesives containing titanium dioxide reinforced nanoparticles resulted in significantly decreased levels of postoperative sensitivity over time when compared to adhesives without nanoparticle fortification.

With the inception of resin composites in clinical practice, the field of restorative dentistry has blossomed. Resin composites, which embody the fundamentals of minimally invasive and adhesive dentistry, provide high-quality esthetic and durable posterior restorations. Despite its long-track record of clinical success, it has several shortcomings. Polymerization shrinkage during the free radical addition reaction produces many undesirable outcomes, one of which is postoperative sensitivity. The drawback of sensitivity subsequent to composite restoration is primarily explained by the hydrodynamic theory, as the fluctuations in tubular hydrostatic pressure cause stimulation of nerve endings in the dental pulp. Many strategies have been employed over the decades to counteract this pitfall of resin composites, such as modifications in placement techniques, variations in restorative materials, utilization of low-viscosity materials, and alterations in curing modes. However, no single treatment modality has completely eliminated this issue [ 15 , 16 , 17 ].

Amid this predicament, a silver lining of hope has emerged from the instigation of nanoscience in clinical dentistry. The philosophy of nanoscience has proven to be a ground-breaking step in the development of dental biomaterials. A multitude of advancements has been made in dental materials through the incorporation of fundamental principles of nanotechnology. Reinforced composites of nano-fortified adhesives encompass the field of restorative dentistry. The core of a successful composite restoration is the establishment of a durable hybrid layer. Incomplete infiltration of adhesives into demineralized dentin is the main culprit for nanoleakage, which is mainly responsible for the postoperative sensitivity of composites. Thus, by fortifying the adhesives with nanoparticles, significant enhancements in physio-chemical attributes can be attained. These reinforced adhesives have better permeability into the dentin matrix, resulting in longevity and stability in the hybrid layer [ 18 , 19 , 20 ].

Thus, the principles of nanoscience can resolve the issues of postoperative sensitivity in composites by utilizing the superlative permeability and mechanical attributes of nanofillers. In this interventional study, nanoparticles were mixed with a commercially available adhesive (One Coat Bond SL Coltene, Switzerland) at a mass fraction of 30% [ 20 , 21 ]. This was attributed to the fact that reinforced nanofillers have a significant impact on the viscoelasticity and flowability of adhesives into dentinal tubules [ 4 , 11 ]. Hence, the percentage of incorporated titanium dioxide nanoparticles was deliberately set at moderate levels to avoid any detrimental impact on the dentin adhesives while upgrading their physio-chemical properties. In this study, titanium dioxide nanoparticles procured from a biogenic source, Bacillus subtilis , were employed to reinforce dental adhesives. The superior physio-chemical, biological, and optical properties of titanium dioxide nanoparticles have already been elucidated in various studies conducted recently [ 22 , 23 , 24 ]. Moreover, an in vitro study has supported the safety profile of these biogenically synthesized nanoparticles as being non-cytotoxic and eco-friendly [ 25 ].

In accordance with the findings of this study, a noticeable association was observed between sensitivity and the group variable at all four evaluation periods: after one day ( p  = 0.002), one week ( p  = 0.002), two weeks ( p  = 0.007) and one month ( p  = 0.001). The majority of participants in the “Adhesive with Nanoparticles” group reported none or mild sensitivity, whereas the “Adhesive without Nanoparticles” group reported a higher number of participants experiencing moderate to severe sensitivity. The results of this trial go hand in gloves with a study conducted at the Department of Operative Dentistry, Faculty of Dentistry, Cairo University [ 11 ] that shows a significant reduction in postoperative sensitivity using bioglass-incorporated nanoparticles in dentin adhesives.

An etch-and-rinse adhesive strategy was used in this interventional study. This was chiefly due to the increased prevalence of postoperative sensitivity in the composites when this adhesive technique was employed. Several studies have shown promising results in favor of the self-etch adhesive technique in terms of sensitivity [ 26 , 27 ]. However, the findings of the systemic review negated the impact of the adhesive strategy on postoperative sensitivity in posterior composites [ 28 , 29 ]. Additionally, an incremental placement technique was utilized for this intervention owing to the proposition that the bulk-fill strategy has a more successful clinical outcome and reduced sensitivity compared to the incremental layering technique [ 14 , 30 ]. This was mainly used to judge the impact of reinforced nanoparticles in adhesives on the sensitivity of the composites. Nonetheless, various studies have highlighted that the placement techniques do not influence the postoperative sensitivity of composite restorations [ 31 , 32 ].

The most striking attribute of this intervention was its novelty. No previous study has utilized Bacillus subtilis-procured nanoparticles in dentin adhesives. This study is the first of its kind to demonstrate the impact of biogenically synthesized titanium dioxide nanoparticles on the sensitivity of composite restorations. Titanium dioxide nanoparticles can significantly improve the properties of adhesives. Due to their biogenic origin, these nanoparticles are eco-friendly, and their cytotoxicity profile has also been authenticated [ 33 ]. Additionally, naturally prepared titanium dioxide nanoparticles displayed outstanding antimicrobial features that might play a significant role in the adhesive dentistry as well [ 34 , 35 ]. Moreover, the triple-blind nature of this intervention rendered the study unbiased, and ratified its authenticity. However, this study had certain limitations. One of the major shortcomings of this trial is that one month could be a short evaluation period to remark the appreciable impact of nano-reinforced adhesives on post-restorative sensitivity in composites. This trial did not evaluate the influence of variables such as cavity depth, arch distribution, adhesive techniques, or different placement strategies on postoperative sensitivity after composite restorations. Moreover, this trial was conducted in a single hospital setting. To authenticate the findings and practicability of this study, it should have been executed at multiple clinical setups. Thus, further research is warranted to validate the efficacy of novel titanium dioxide nanofortified adhesives in restorative dentistry.

Nanotechnology is a cynosure in contemporary science. This study paves the way for further research on nanoscience to synthesize ecologically secure nanoparticles and incorporate them into biomaterials. It can drastically improve the final treatment outcome and benefit healthcare practitioners by providing high-quality dental care to patients.

Clinical relevance

This study shed light on one of the major issues in restorative dentistry, which is post-operative sensitivity. By embodying composite restorative material with nanoparticles, significant enhancement in bonding performance could be achieved. This could enormously improve the longevity of restorations by providing premium dental treatment to patients.

A noteworthy association was observed between sensitivity and the group variable at all four evaluation periods: after one day ( p  = 0.002), one week ( p  = 0.002), two weeks ( p  = 0.007) and one month ( p  = 0.001). The majority of participants in the “Adhesive with Nanoparticles” group reported none or mild sensitivity whereas the “Adhesive without Nanoparticles” group had a higher number of participants experiencing moderate to severe sensitivity. It could be deduced that participants who underwent restorative intervention using titanium dioxide nanoreinforced adhesives reported a notable reduction in sensitivity at all time intervals. Hence, the incidence and severity of postoperative sensitivity are significantly reduced by using Bacillus subtilis-procured nano-fortified adhesives as compared to conventional adhesives without nanoparticles.

Limitations of the study

A limited sample size was used in this clinical trial to investigate patient sensitivity. Therefore, future studies with a larger number of patients involved in the clinical trial are required to clarify any ambiguity regarding the limited sample size.

Data availability

All data generated or analyzed during the study is available in this manuscript.

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Acknowledgements

Authors acknowledge School of Dentistry for their help and support in the research.

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Department of Operative Dentistry and Endodontics, School of Dentistry, Shaheed Zulfiqar Ali Bhutto Medical University, Islamabad, Pakistan

Department of Microbiology, Quaid-i-Azam University, Islamabad, 45320, Pakistan

Afsheen Mansoor

Department of Dental Material Sciences, School of Dentistry, Shaheed Zulfiqar Ali Bhutto Medical University, Islamabad, 44080, Pakistan

Medical Student, Rawalpindi Medical University, Rawalpindi, Pakistan

Nabiha Eeman

Medical Student, Army Medical College, National University of Medical Sciences, Rawalpindi, Pakistan

Muhammad Nouman Ahmed

Islamic International Dental College, Riphah International University Islamabad, Islamabad, 46000, Pakistan

Emaan Mansoor

CRS Agriculture Department, Islamia University, Bahawalpur, Pakistan

Khadim Hussain

Faculty of Medicine, Center for Innovation and Research in Oral Sciences (CIROS), University of Coimbra, Coimbra, 3000-075, Portugal

Paulo J. Palma

Faculty of Medicine, Institute of Endodontics, University of Coimbra, Coimbra, 3000-075, Portugal

Department of Statistics, Islamia University, Bahawalpur, Pakistan

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Conceptualization: N.A, A.M.; Methodology: N.A., A.M.; Data Collection: N.A., N.E., M.N.A., E.M.; Data Processing: N.A., N.E., M.N.A., E.M, K.H.; Data Analysis & Interpretation: K.H, N.A.; Writing - Original Draft: N.A.; Writing - Review & Editing: A.M., P.J.P.; Validation and Critical Review: A.M., P.J.P.; Supervised by: A.M.

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Correspondence to Afsheen Mansoor or Paulo J. Palma .

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The study was conducted after the approval from Institutional Ethical Research Committee , School of Dentistry , Shaheed Zulfiqar Ali Bhutto Medical University with the reference number (SOD/ERB/2023/31 − 01) . An informed consent was obtained from all of the participants included in this trial.

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Amir, N., Mansoor, A., Eeman, N. et al. Postoperative sensitivity of composites using novel Bacillus subtilis nanofortified adhesives: a triple-blind study. BMC Oral Health 24 , 1077 (2024). https://doi.org/10.1186/s12903-024-04825-2

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McNemar chi2 test revisited: comparing sensitivity and specificity of diagnostic examinations

Affiliation.

• 1 Gama Filho University, School of Medicine, Rio de Janeiro, Brazil. [email protected]
• PMID: 18224558
• DOI: 10.1080/00365510701666031

When evaluating a novel diagnostic examination for clinical use, it should be compared with a reference standard, defined as the best available examination, which may include clinical and laboratory criteria. The novel examination and reference standard's results are usually presented in the form of a 2 x 2 table, which allows calculation of sensitivity, specificity and accuracy. It has been recommended that the measures of statistical uncertainty should be reported, such as the 95% confidence interval, when evaluating the accuracy of diagnostic examinations. Comparing the difference in sensitivity or specificity of a novel examination with the reference standard is important when evaluating its usefulness. The McNemar chi(2) test, used to compare discordance of two dichotomous responses, can be applied for this purpose. However, applying the McNemar test to a 2 x 2 table for comparing the accuracy of examinations is not recommended, since this test is sensitive to the proportion of positive versus negative subjects. Moreover, if the novel examination has higher sensitivity than the one considered as the reference standard, constructing a classic 2 x 2 table would result in low specificity of the novel examination. Thus, in order to compare sensitivities and specificities between examinations, this table is inappropriate and an independent reference standard is necessary. In this article, we propose the use of the McNemar chi(2) test to compare sensitivities between examinations using a 2 x 2 table exclusively among diseased patients, defined by a set of criteria and follow-up of patients. Likewise, specificities can be compared applying the McNemar test among healthy individuals.

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• Research Note
• Open access
• Published: 14 September 2024

Prevalence, types and outcome of injuries among abattoir workers in Ghana

• Abigail Aban Tetteh 1 , 2 ,
• Veronica Millicent Dzomeku 1 ,
• Patience Achiamaa Barnie 1 ,
• Adwoa Gyamfi 1 ,
• Ato Kwamina Arhin 3 ,
• Benjamin Noble Adjei 4 ,
• Bernard Barnie 4 ,
• Emmanuel Kwaku Nakua 4 ,
• Charles Mock 5 &
• Peter Donkor 6  

BMC Research Notes volume  17 , Article number:  265 ( 2024 ) Cite this article

Metrics details

In many places in the world, workers in the meat processing industry report high incidence of injuries. Details of such injuries are not well known for Ghana or much of Africa.

A cross-sectional survey involving 300 workers from three major meat processing facilities in the Kumasi metropolis of Ghana was carried out using a structured questionnaire from April to June 2023. The prevalence, types and outcome of injuries among workers were assessed. Test of association was established by Chi square analysis.

Over the prior 6 months, the prevalence of injury was 83.0%. Among the various injury types, lacerations had the highest prevalence (46.0%) followed by musculoskeletal pain (16.7%) bone fractures (14.0%), swelling (13.0%), burns and scalds (7.3%), and dislocations/sprains/strains (6.7%). More than half (58.9%) of injuries sustained were moderately severe (2–7 days of lost work) and nearly half (42.0%) required immediate medical attention. Gender, employment status, wages, availability and use of safety equipment were significantly associated with injuries among abattoir workers.

Conclusions

The incidence of injuries among abattoir workers in Kumasi, Ghana demonstrates a large public health burden requiring attention and improved enforcement through occupational safety interventions.

Peer Review reports

Introduction

Activities in the meat processing industry predispose worker to various form of injuries, such as deep lacerations, falls, fractures and bites from animals [ 1 , 2 , 3 , 4 , 5 ]. Non-fatal injuries such as sprains and strains are common often requiring time off work or job modifications based on severity [ 6 , 7 ]. Most studies on injuries in the meat processing industry come from high-income countries. But the few studies that have addressed injuries in the meat processing industry in Africa have shown a high prevalence of injuries among workers, often associated with factors such as dirty slippery floors, kicks and stamps from irate animals and sharp machinery [ 8 , 9 , 10 ].

Globally and in Ghana, abattoirs are obligated to have occupational safety policies that will mitigate the occurrence of injury. Regrettably these policies are inadequate, poorly coordinated or non-existent in most abattoirs [ 11 , 12 , 13 , 14 ].

In Ghana, there has been attention to other occupational safety issues, such as those in construction and mining, food safety and infectious disease risk from abattoirs [ 15 , 16 , 17 , 18 , 19 ]. However, there has been almost no attention paid to injury and safety risks for abattoir workers in Ghana. To support the development of occupational injury control strategies, it is imperative to obtain detailed information on injury characteristics. This study addressed the gap by assessing injury prevalence, types, and outcomes in abattoirs workers in Ghana.

Study design and setting

The study employed a quantitative research approach using descriptive cross-sectional design to solicit for information from abattoir workers in the Greater Kumasi Metropolis of Ghana. The city has a heterogeneous population and enhanced economic activities. It is the second largest city in Ghana with a population of 3,490,000 and a land size of 299km 2 [ 20 ]. Meat processing industries in Kumasi receive their supply of animals from different regions in the country, and neighboring countries like Mali and Niger [ 21 ].

Study population

The city has 3 major meat processing facilities and 17 smaller facilities with less than 20 workers each. This study was carried out in the three main meat processing facilities. This includes Kumasi Abattoir, the Subtui Musah Slaughterhouse and the Akwatia Line slaughter slab with worker population of 200, 560 and 290 respectively. These three facilities cut across the different grades of meat processing facilities in the country. Workers include those who move animals and work in lairage as well as butchers and slaughterers engaged in killing, singeing and processing of the meat. There are also retailers, administrators and general workers who dispense, inspect the site and keep the facility operating.

Data collection

A structured questionnaire adapted from previous injury literature was employed for the data collection [ 15 , 17 ]. It was divided into demographic characteristics, types and frequencies of injuries, and outcomes of the injuries occurring in the abattoir. A three-day training was done for the research assistants. The training focused on building understanding on the questionnaire and the objective of the study, conducting interviews and maintaining confidentiality. The questionnaire was in English but most of the respondents had low levels of education. Hence research assistants were trained on how to translate the questions into a language directly understood by the participants, mostly Twi and Hausa. The questionnaire asked about injuries over the prior six months. If a respondent had more than one injury event during that time, they were asked to report on whichever injury they chose.

The tool was pretested at a separate facility (Sofoline Slaughterhouse) not involved in the remainder of the study to assess the questions and the interview skills of the research assistants. Four questions were modified to assess the specific department in which the worker is engaged. Content validity assessment was done by seven experts, who have published extensively on injury related studies and necessary modifications were made before the actual data collection.

An estimated sample size of 300 was calculated using the Yamane formula [ 22 ]. Purposive sampling was used. After obtaining ethical clearance and administrative approval from authorities, the principal investigator and research assistants visited the three worksites for a total of eight days. During this time, they approached for interviews workers who were at the worksite that day. The principal investigator sought written informed consent from workers, explaining the objectives of the study. Workers who consented were interviewed. The principal investigator and research assistants interviewed as many workers as possible during the time allotted each day, up until the goal of 300 was achieved. All 300 workers approached agreed to be part of the study. Interviews were anonymous and no names or other identifying information about the respondents were collected. Data collection ran from April to June 2023.

Data analysis

Quantitative tools were employed in data analysis. Data were first cleaned and checked for completeness then exported to IBM SPSS Version 25.0, USA for analysis using descriptive statistics. Continuous variables were expressed as mean ± standard deviation (M ± SD) and the results were presented in tables, frequencies and percentages. Test of association was established by Chi square analysis.

Respondents’ demographic characteristics

A total sample of 300 respondents participated in the study. Table 1 summarizes their demographic characteristics. The largest single group of participants were between 40–49 years, representing 28.3% of the respondents. The industry is predominantly male (96.7%), and are married (78.0%). Similar proportions of the respondents have primary (24.0%), junior high (21.0%) and secondary education (25.0%) with only 9.0% having tertiary education. Nearly fifty percent of respondents have over 10 years of working experience in the abattoir. Majority (60.0%) are casual workers (46.3%) hired and paid daily wages.

Prevalence, types and outcome of injuries

In the 6 months prior to the study, 249 workers reported at least one injury for a prevalence of injury of 83.0% (Table  2 ). Laceration was the most frequent injury sustained by respondents, representing 46.0%, followed by musculoskeletal pain (16.7%) and bone fractures (14.0%). Other leading injuries included swelling of various body parts (13.0%), burns and scalds (7.3%), and dislocation, sprains, or strains (6.7%). Close to half (42.0%) of these injuries sustained required immediate medical attention (42.0%) at health facilities. Another large group (36.7%) were treated first aid by co-workers at the worksite. In terms of long-term outcome, more than half (58.9%) of injuries were moderately severe, leading to 2–7 days of lost work.

Association between socio-demographic characteristics, safety measures and injuries among workers in the abattoir

Table 3 shows a significant association between gender, employment status, wages and injuries among abattoir workers (p < 0.05). There was low availability of fire extinguisher (33.7%), first aid kits (16.8%), smoke detector (1.4%), emergency exit (12.1%), safety boots (63.2%) and injury incidence record book (4.1%). Only 30.1% of the respondents used PPEs at work. Use of PPEs, availability of fire extinguisher, first aid kits, and smoke detector respectively were significantly associated with injuries (p < 0.05).

This study reports the injury burden in the meat processing industry in Kumasi, an industry that has seen little attention in terms of research. The study assessed the prevalence, types and outcome of injuries sustained by workers. This study suggests that the prevalence of injury is high with the types being predominantly lacerations, followed by musculoskeletal pain. A significant number of workers sustained moderately severe injuries, losing 2–7 days of work time, as well as requiring medical attention, both of which represent financial losses for the workers. Gender, employment status, wages and availability and use of safety equipment were significantly associated with injuries.

Our findings need to be put into the context of other studies. In high-income countries, injury rates are generally much lower. For instance, injury incidence rates of 15.2 to 22.8 per 100 full-time employees and an annual total injury rates per 100 workers of 6.4% (poultry) and 13.2% (pork) have been reported in abattoir facilities in the United States [ 7 , 23 , 24 ]. All of these reports show far fewer injuries than the current study's finding of 83.0% of workers sustaining at least one injury during the past 6 months (approximately equivalent to 166 injuries per 100 workers per year).

The high burden of injury in Ghana is similar to what has been reported from other African countries. In a study of slaughterhouses in Kenya, Cook et al. found that 25% of workers reported an injury at least once per month, with 8% of workers still having a wound at the time of the interview [ 25 ]. In a different study, Makori et al. found that 85% of slaughterhouse workers in the Nairobi area had been injured in the past year [ 26 ]. Among 203 workers in five slaughter houses in Ilorin, Nigeria, 88% of workers reported having had at least one injury ever [ 27 ].

We examined the types of injuries sustained by workers and our data highlighted lacerations as the most dominate type of injury. It is unsurprising as workers in this sector are usually exposed to numerous hazards such as sharp cutting tools and bones. This finding agrees with studies, both in Africa and in countries elsewhere [ 9 , 23 , 25 , 28 , 29 , 30 ]. Musculoskeletal pain was the next common type of injury reported by this study possibly due to the repetitive movement and heavy lifting associated with abattoir operations [ 9 , 28 ]. However, in another study conducted in the United States, bovine related injuries dominated [ 31 ].

This study highlights an association between employment status, wages and injuries. Most of the workers in the current study were casual employees who are paid based on their daily wages irrespective of their decade working experience in the industry. Taking a day off is considered as absenteeism and no commission is earned by the worker [ 32 ]. It is possible that employees usually work shifts and overtime to make ends meet. Worker tiredness affects attention and reaction times and raises the risk of accidents. Studies have linked shift work and weariness to the probability of accidents [ 27 , 28 ]. This may possibly be a factor to the high prevalence of injury reported by this study.

Majority of injuries were moderately severe requiring between 2 and 7 days for treatment and recovery, with most respondents needing immediate medical attention. It can be anticipated that the lost wages and cost of treatment will have considerable negative economic consequences to these workers and their families. Most workers received daily pay and would not be paid while out of work. Also, the cost for treatment of even work-related injuries is usually borne by the worker and their families.

Gender of the worker was significantly associated with injuries in this study. It is evident from this and other studies that the industry is male dominated [ 1 , 7 , 25 ] and possibly puts this gender at risk for injuries. This mirrors findings from other studies where gender of the worker has been anticipated to be a major influencer on work place injury [ 33 ]. Although other studies suggest that the risk of injury is equivalent for both male and female [ 8 ].

The study highlights low PPE usage and the absence of safety equipment in the facilities, similar to findings of other studies in the industry [ 9 , 10 , 14 , 24 , 25 ]. Meanwhile there is a significant association between these factors and injuries. This finding agrees with other studies that using PPE properly, dramatically lowers the risk of injuries in the industry [ 27 , 34 ].

The types of injuries noted in the meat processing industry are mostly lacerations, musculoskeletal pain and bone fractures and the frequency of these injuries is high. Most of these injuries are moderately severe necessitating immediate medical treatment. This study highlights a high burden of injuries in the meat processing industries. This reinforces calls for enforcement of existing occupational health policies in this industry.

Strengths and limitations of the study

The study depended on self-report of injuries and there was no way of verifying answers about the types, frequencies and outcome of injuries sustained. A six-month recall period was used which could have led to recall bias for earlier injuries. Despite these limitations, the present study has several strengths. The sample size was large and also the study was conducted in three geographical locations in separate slaughterhouse facilities in the metropolis thereby increasing generalizability.

Availability of data and materials

Datasets used and analyzed in this study are safely kept with the corresponding author and will be available on reasonable request.

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Acknowledgements

We want to express appreciation to all the workers and management of the various abattoirs in Kumasi who were respondents of this study and to Mr. Joel Adusei-Gyamfi for the ideas and support.

This study was supported by grant D43 TW007267 from the Fogarty International Center at the US National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

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Abigail Aban Tetteh, Veronica Millicent Dzomeku, Patience Achiamaa Barnie & Adwoa Gyamfi

Ear, Nose and Throat Nursing School, Komfo Anokye Teaching Hospital, Kumasi, Ghana

Abigail Aban Tetteh

Department of Interdisciplinary Studies, The Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development (AAMUSTED), Kumasi, Ghana

Ato Kwamina Arhin

School of Public Health, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

Benjamin Noble Adjei, Bernard Barnie & Emmanuel Kwaku Nakua

Department of Surgery, University of Washington, Seattle, WA, USA

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Contributions

Conceptualization and design of the study was by AAT, VD, PAB. EKN, screened the tool for data collection. VD, EKN, CM, BB, provided methodological insights. VD, PD, AAT, AG, AKA, coordinated data collection. BNA, AKA, AAT, VD, BB, CM carried out the initial analysis and drafted the initial manuscript. All authors discussed the results and critically reviewed its intellectual contents. VD, BB, EKN, PD and CM critically reviewed and revised the manuscript which as then approved by all other authors for submission.

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Correspondence to Abigail Aban Tetteh .

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Ethical approval was obtained from the ethics committee of Kwame Nkrumah University of Science and Technology (CHRPE AP/203/23) with approval from the administrative wing of each of the facilities visited. Written and verbal consent was obtained from respondents after an explanation of every aspect of the research in their preferred language.

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Tetteh, A.A., Dzomeku, V.M., Barnie, P.A. et al. Prevalence, types and outcome of injuries among abattoir workers in Ghana. BMC Res Notes 17 , 265 (2024). https://doi.org/10.1186/s13104-024-06934-1

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Migrants from Ukraine in the Polish labour market as perceived by Poles from rural areas and towns

Roles Conceptualization, Writing – original draft

* E-mail: [email protected]

Affiliation Faculty of Agriculture and Economics, University of Agriculture in Krakow, Krakow, Poland

Roles Writing – original draft

Affiliation Faculty of Organization and Management, Silesian University of Technology, Gliwice, Poland

• Wioletta Knapik, 
• Lidia Luty, 
• Monika Zioło, 
• Monika Odlanicka-Poczobutt

• Published: September 13, 2024
• https://doi.org/10.1371/journal.pone.0306895
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The article is devoted to presenting the topic of migration of Ukrainian nationals to Poland. The work makes use of a survey under a project carried out in Polish rural areas and small towns. Seven hundred interviews were held in total. We conducted a quantitative analysis of its results here. The employed methods involve variable frequency distribution. The independence of the features was tested with the non-parametric chi-square test of independence. The association of the investigated variables was determined with Cramér’s V. The research shows that the most numerous foreign nationals in the Polish labour market in 2021 were Ukrainians. The positive trend started in 2017. The respondents perceived the migration of Ukrainian nationals to Poland mostly positively, especially regarding seasonal work. They also emphasized that the Ukrainians performed work at variance with their qualifications. Only every fifth participant agreed that migrants took away jobs from Poles. Most of the respondents pointed out that small business owners benefited from employing Ukrainians. The overwhelming majority of the respondents noted an increase in migration from Ukraine after the full-scale invasion and that entire families of Ukrainians were coming to Poland. Nearly half of them agreed that the support system for Ukrainian migrants was a burden on municipal budgets.

Citation: Knapik W, Luty L, Zioło M, Odlanicka-Poczobutt M (2024) Migrants from Ukraine in the Polish labour market as perceived by Poles from rural areas and towns. PLoS ONE 19(9): e0306895. https://doi.org/10.1371/journal.pone.0306895

Editor: Justyna Dominika Kowalska, Medical University of Warsaw, POLAND

Received: January 10, 2024; Accepted: June 25, 2024; Published: September 13, 2024

Copyright: © 2024 Knapik et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All data are in the manuscript and supporting information files.

Funding: This work was supported by the Ministry of Education and Science (grant number 552216/2022).There was no additional external funding received for this study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Migration of Ukrainian nationals to Poland should be considered in two broader contexts, economic and sociocultural [ 1 – 3 ]. In 2022, the media announced Poland was facing a situation nobody would expect a few months back. Over two million Ukrainian nationals fleeing the Russian aggression were crossing the Polish border [ 4 ]. Over one million of them could stay for longer.

Many as 12 million people may want to leave Ukraine permanently and that refugee policies in potential destination countries are likely to have a substantial impact on the distribution of Ukrainian refugees between different countries [ 5 ].

The Polish government had no migration policy and the country was on the brink of an unparalleled migration crisis. No refugee camps were built in Poland but the relocation mechanism seemed to be necessary. Especially with the Polish parliamentary elections in 2023. Anti-immigrant spin is only to be expected during the campaign.

Between June and August 2022 there were conducted a survey of refugees in the border provinces of Podkarpackie voivodeship and Lubelskie voivodeship to identify their actual needs and expected scope of long-term assistance and support. The aim of the survey was to obtain basic information about refugees from Ukraine who left their country across the Polish-Ukrainian border in 2022. It was particularly important to identify their health needs.

The war forced Ukrainians from across the country to flee. Most of them (72%) lived over 500 km from a Polish border crossing. Every fifth refugee lived 101 km to 500 km from a Polish border crossing. Statistics on foreign nationals in the Polish labour market were completely dominated by Ukrainians in 2021. In 2021, Ukrainian nationals were granted 325,213 work permits (64.5% of all permits for foreign nationals), which was a 68.9% increase compared to 2017. The trend reversed in 2022. The number of issued permits for Ukrainian nationals shrunk by 74%, which is 240,000 permits. The change was not due to a smaller number of employees from Ukraine but the Act on aid to Ukrainian nationals [ 6 ], which allows for employment without a permit.

The economic cooperation is growing as Ukrainian businesses move to Poland because of the war, taking advantage of the geographic proximity. Those Ukrainian companies that had already been present in 2022, expand with new branches. Ukrainian nationals become sole proprietors or find employment with Polish companies. The success of these endeavours hinges on historical and cultural factors to a large extent. The number of businesses started by Ukrainian nationals in Poland has been gradually rising since the full-scale invasion. The period from March 2022 to the end of January 2023 saw a total of 17,764 new sole proprietorships. Most of the new Ukrainian businesses recorded with the Polish Central Registration and Information on Business are situated in Mazowieckie Voivodeship (24%), Dolnośląskie Voivodeship (15%), Małopolskie Voivodeship (14%), and Pomorskie Voivodeship (11%). Ukrainian businesswomen make up 41% of all the owners. The structure of new businesses by sex does not reflect the demographic structure of war refugees. The register of Ukrainian nationals and their families who have been granted refugee status under the Act (discussed later in the article) has over 985,000 people (as on 20.02.2023), 49% of which are women and 11% are working-age men [ 7 ].

Data from the Ministry of Labour and Social Policy, Central Statistical Office, and Social Insurance Institution show that recent years saw an increase in the number of foreign nationals employed in Poland. This means Poland has reached the primary goal of its immigration policy liberalised in 2007–2008 to increase the influx of foreigners to Poland and their employment. The grounds for the liberalising Acts assumed seasonal employment of foreign nationals from five Eastern European countries would occur in those professions that Poles find unattractive. The current data neither support nor negates the premise. Still, the hypothesis that the increase in foreign workforce did not affect the employment level of Poles seems justified considering employer declarations of entrusting work to foreign nationals and sectors manned by foreigners. It is evident from the relative employment stability of Poles in sectors where foreigners are most often employed. This suggests a complementary nature of seasonal employment of foreign nationals and Poles, which means the liberalisation of the immigration policy in Poland is [ 8 , 9 ].

To conduct a comprehensive analysis of labour migration from Ukraine to Poland, it is necessary to consider the employment of Ukrainians from 2010 to 2019. This segment of the Polish labour market has undergone significant changes. Although in 2010, 52% of Ukrainians in the Polish labour market worked in agriculture, mainly fruit-picking seasonal jobs, 23% in the construction industry, 21% in services, and merely 4% in industry, in 2019, 60% worked in services and only 12% in agriculture (14% in industry and construction each) [ 10 ].

A new type of seasonal work permit issued by district labour offices on behalf of District Starost was introduced on 1 January 2018 [ 11 ]. The number of seasonal work declarations issued to Ukrainian nationals gradually increased from 2013 to 2017. It declined by 15.67 pp. year-on-year in 2018. The fluctuations persisted until 2020. In 2021, the number rose nearly to the all-time high of 2017. The mean share of permits for Ukrainians compared to other nationals was 93.1% from 2013 to 2020. In 2021, it was much lower, around 82.5%. In a similar manner, the Act on aid to Ukrainian nationals related to the war in Ukraine of 12 March 2022 streamlines their access to the Polish labour market. An amendment to this act signed on 26 March 2022 by the President of the Republic of Poland effective retroactively of 24 February 2022 specifies that foreign nationals not covered by the Act who are displaced persons listed in the implementing decision of the EU Council may apply for the temporary protection under the Act on protection of foreign nationals in the territory of Poland:

• by crossing the Polish border, Ukrainian nationals acquire the right to legal stay and access to the labour market in Poland for 18 months. Should the circumstances so demand, the period can be extended by another 18 months, totalling three years;
• Ukrainian nationals can obtain a PESEL identification number, which streamlines official contacts, such as medical treatment and access to electronic medical documents;
• the refugees have a right to family benefits, parenting benefits, Dobry Start school benefit, family care capital for every child aged 12 to 35 months, subsidy for daycare centre, children’s club, or daycare provider, and welfare benefits under general regulations;
• Ukrainian nationals can start and conduct business in Poland just as Polish nationals. The prerequisite is to have a PESEL number [ 12 ].

The growth of the number of Polish population driven by migration has exacerbated problems that Poland faced even before the Russo-Ukrainian war [ 13 , 14 ]. Long-term integration of Ukrainians will require substantial expenses, while public engagement and the general spirit from the early days of the full-scale invasion are abating.

In addition, the anti-democratic policies of the Polish government, especially in the last months of 2023, have contributed to building an anti-Ukrainian sentiment [ 15 ].

The European Commission provided EUR 348 million for various aid programmes from 28 February 2022 (of the declared EUR 500 million). A humanitarian fund of EUR 11.6 billion is planned for 2021–2027. It is spent on food, water, basic household products, healthcare, psychosocial support, emergency shelters, and the basic needs of those in the worst situation. The humanitarian aid in Ukraine reached eleven million people as of today. Over 8.9 million people were given food, 4.4 million received medical interventions or supplies, and over 2 million, cash. Note that even before the invasion, the EU granted Ukraine various support loans amounting to EUR 5 billion from 2014 to 2021. After the invasion, the European Commission proposed a new EUR 1 billion macro-financial assistance operation for Ukraine in the form of long-term loans on favourable terms on 1 July 2022. It is the first part of the exceptional macro-financial assistance package of up to EUR 9 billion announced in the Commission’s communication on assistance to and reconstruction of Ukraine of 18 May 2022 and endorsed by the European Council on 23–24 June 2022 [ 16 ].

In March 2022, the EU triggered the Temporary Protection Directive, an EU emergency response system applied to mass influxes of migrants. The directive provides for:

• immediate collective protection for displaced persons;
• relieving national asylum systems in EU countries.

The rights of the beneficiaries of temporary protection include a residence permit, access to employment, access to accommodation or housing, access to medical care, and access to education for minors [ 17 ].

The Polish Act on aid to Ukrainian refugees provides for principles of regularising stay and benefits and discounts for Ukrainian nationals. Poles who host refugees from Ukraine will also receive compensation benefits. Institutions and individuals who provided accommodation and food to Ukrainian nationals who arrived in Poland from Ukraine due to the war, as well as Ukrainian nationals holding a Pole’s Card who arrived with their immediate family, will be eligible for a cash benefit. The Act was amended on April 30 to extend the benefit provision for up to 120 days after the Ukrainian national’s arrival in Poland. The benefit period may be extended due to exceptional circumstances. The benefit amount in PLN 40 a day per person [ 18 ].

Material and method

The research aims to investigate the situation of Ukrainian nationals in the seasonal labour market in rural areas and towns in Poland. The problem is presented before the full-scale Russian aggression on Ukraine and during the war against the backdrop of cultural and social conditions, mainly in the context of support for war refugees, their problems, and relationships between Poles and Ukrainians. The study is founded on surveys intended to gather information on seasonal work conditions and perception of Ukrainian immigrants. It reflects a subjective assessment of moods concerning the investigated problem among residents of rural and town areas in Poland. The research objectives are to diagnose the conditions of seasonal labour migration in three areas: 1. labour market, considering sex, age, education, and region of residence of the respondents; 2. characteristics of stay; and 3. institutional support for Ukrainian migrants ( Fig 1 ).

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https://doi.org/10.1371/journal.pone.0306895.g001

In the field of the labour market, respondents were asked several questions related to their opinions on the negative impact of refugees on destabilizing the economy and taking jobs away from Poles. On the positive side, the interviewees were asked whether small enterprises benefit from additional labour force and whether Poland gains more seasonal workers. Additional questions encompassed consistency of current jobs of migrants with their qualifications and if they form long-term relations with their employers.

Next dimension which the survey encompassed was a characteristic of stay. In this aspect respondents were asked on the impact of war on the number of migrants, length of their stay and whether they settled in Poland alone or with their families.

The last aspect addressed was related to the institutional support for Ukrainian migrants. In this section, respondents were asked about various types of financial and non-financial assistance provided to migrants by the government, that they were aware of.

The employed methods involve variable frequency distribution. The independence of the features was tested with the non-parametric chi-square test of independence. The association of the investigated variables was determined with Cramér’s V. The analyses were conducted in Dell Statistica v. 13.1 (StatSoft Polska). Frequency analysis is used to represent information on the general number of occurrences and percentages of individual responses to reveal the data structure. This is how it has been employed in the article. Cramer’s V is a chi-squared measure of the degree of association between variables. The coefficient was calculated for those variables for which the chi-squared test of independence indicated a statistically significant association (at a significance level of 0.05).

Using the Likert scale popular in marketing, market, and social surveys as a model, the authors decided to measure responses on a bipolar, five-point scale. The respondents chose their answers on a scale from complete acceptance to complete rejection, with a neutral position in the middle.

The research is part of the project ‘National Identity of Poles in Light of Migration of Ukrainian Nationals. Prevention of Social Conflicts’ was part of the programme of the Ministry of Education and Science ‘Science for the Public’. The diagnosis of economic dimensions of seasonal migrations of Ukrainian nationals into Polish rural areas and towns employed an original survey questionnaire. The survey was conducted using a computer-assisted telephone interview (CATI) method. It involved a representative sample of adult residents of rural areas and towns. The sampling frame consisted of a database of telephone numbers from rural areas and towns with populations up to fifteen thousand residents. A total of 5,000 randomly selected telephone numbers were used, with a 14% response rate. In total, seven hundred interviews were conducted. The database was purchased legally from ZN Direct sp. z o.o. Up to five attempts were made to reach each respondent. The preliminary assumption was to interview a proportional share of residents in every NUTS 1 unit ( Fig 2 ). The actual sample was consistent with the planned structure (up to 3 pp. difference). The survey was conducted in March 2023.

A new macro-region scheme was introduced in Poland on 1 January 2018 with an additional macro-region, Mazowieckie Voivodeship with the capital of Poland, Warsaw. It is because of the strong impact of the agglomeration on statistics of a large central region with a different profile of urban areas much smaller than the capital.

https://doi.org/10.1371/journal.pone.0306895.g002

Both sexes had a similar representation in the sample. The largest group of respondents was aged 35–54, which was 45.7% of the sample. Most of the respondents held a high school or university diploma ( Table 1 ).

https://doi.org/10.1371/journal.pone.0306895.t001

The literature review covers research areas presented in the Results section, i.e. 1. labour market; 2. characteristics of stay; and 3. institutional support for Ukrainian migrants.

The liberalization of access to the Schengen zone for Ukraine nationals in 2017 allowed many Ukrainians to travel to the Entire European Union (except for Ireland and Great Britain), Iceland, Lichtenstein, Norway, and Switzerland visa-free. This event undoubtedly increased the popularity of Poland as the destination for Ukrainian nationals for whom geographic and cultural proximity are decisive factors. Ukrainian nationals can work without a visa only in Poland as long as they have a biometric passport and a declaration of employment. With a Polish work permit, Ukrainian employees gain protection under the Polish Labour Law. Polish employers are obliged to conform to all employment requirements, including registering Ukrainian employees with the Social Insurance Institution [ 19 ].

1. Labour market

Most of the respondents exhibited a positive perception of the Ukrainian migration to Poland. The majority highlighted the benefit of an additional workforce for seasonal work, a point emphasized by over 82% of the respondents. Only 20.6% of the participants agreed that migrants took away jobs from Poles. Over 60% of the interviewees pointed out that small business owners benefited from employing Ukrainians. Note that nearly 40% of the respondents believed that Ukrainians worked jobs not matching their qualifications. It may be because of the language barrier preventing migrants from taking up jobs in line with their trade, which hurts both them as they are employed beneath their qualifications and the Polish labour market as it cannot access the full potential of the new employees. Most respondents were unsure whether migrants who settled in Poland for an extended period returned to their previous employers.

The opinion of Poles on Ukrainian refugees was positive in each investigated aspect. Poles pointed out the benefits of the influx of additional labour. The youngest age group was also the most sceptical about the new employees, perhaps because of the greatest risk of losing jobs in favour of refugees ( Fig 3 ). Consequently, they more often believed that migrants from Ukraine were undercutting the economy and taking jobs away from Poles.

Symbols as per Table 1 .

https://doi.org/10.1371/journal.pone.0306895.g003

The educational background of the respondents is a substantial differentiating factor regarding the attitude of Poles towards Ukrainians ( Table 2 ). People with university degrees whose jobs are not threatened so much more often pointed out that the refugee influx was beneficial for small business owners and provided a workforce for seasonal increases in labour demand. The lower the education, the greater the probability of belief that refugees had a detrimental impact on the Polish labour market.

https://doi.org/10.1371/journal.pone.0306895.t002

The regional background also played a role in the perception of the refugee impact on the economy. Respondents from North and Mazowieckie Voivodeship less often agreed with the notion that the refugees were destabilising the economy. The Central and East macro-regions had more affirmative responses.

Macroregion influenced also the opinion of respondents on whether refugees form long-term relationships with their employers. People from the North-Western and Central regions were particularly likely to notice this phenomenon. Additionally, people from the Central region were the least likely to have no opinion on this matter, whereas interviewees from the North-Western region were the least likely to disagree with the statement that such relationships are formed.

However, it is worth pointing out that none of the relations were strong despite their statistical significance. Strength of effects in statistically significant relations between variables varied between 0,109 in the weakest relation, which was between Macro-region and statement that “Ukrainians destabilise the Polish economy” and 0,169 in the strongest relation education and statement that “Ukrainians take jobs away from Poles” ( Table 2 ). These results show, that none of the relations was particularly strong, as V-Cramer value below 0,3 means weak strength of effect.

2. Characteristics of stay

Most of the respondents (84.1%) noticed an increase in the influx of migrants from Ukraine after the Russian invasion ( Fig 4 ). Notably, 64.7% of them emphasized that the Ukrainians were bringing their families along, which may be beneficial to the future of demographics in Poland. It may also be linked to the fact that over 41.5% of the respondents believed that the migrants would stay in Poland for longer.

https://doi.org/10.1371/journal.pone.0306895.g004

Nevertheless, it is worth noting that all of the relationships should be described as weak despite their statistical significance. The strength of effects in relationships assessed as statistically significant, with p-values, ranged from 0.141 in the weakest relationship (between sex and ‘Settlement of labor migrants with their families’) to 0.210 in the strongest relationship (between education and ‘Increase in the number of refugees since the invasion’) ( Table 3 ). Looking at this result, one can state that none of the relationships were particularly strong, as all Cramér’s V values below 0.3 indicate a weak strength of effect.

https://doi.org/10.1371/journal.pone.0306895.t003

The strongest differentiating factor for the answers given to these questions was the educational background. Higher education entailed affirmative answers to question about increased number of refugees since the outbreak of war, where people with higher education were much more prone to notice higher influx of migrants ( Fig 5 ). It might be related to the fact, that they are more likely to be engaged in organisations working with migrants from Ukraine.

https://doi.org/10.1371/journal.pone.0306895.g005

There were no factors significantly differentiating the respondents regarding the length of stay of the migrants ( Table 3 ). Sex affected the answer regarding the settlement of migrants with their families ( Table 3 ). Women were more likely to state that migrants settle with their families, whereas men twice almost twice as often had no opinion in this matter. Age and macro-region significantly affected none of the answers tested in this group.

3. Institutional support for Ukrainian migrants

Nearly half of the respondents (49%) agreed that the support system for Ukrainian migrants was a burden on municipal budgets ( Fig 5 ). This opinion was expressed more often by women (55%) than men (43.7%). As much as 63% of the respondents in the young age group (18–34) agreed with that statement. The older age group (35–54) agreed to a lesser extent (49%), while the oldest group agreed in 45%. The educational background had a statistically significant impact on the selected answer. More than half of people with basic and secondary education (54%) believed migrant support to be a burden on municipal budgets. This statement resonated most with residents of South-West.

Response ‘I don’t know’ concerning the support measures used by migrants from Ukraine who stayed in the respondent’s municipality was given by 39.4% of the respondents ( Fig 6 ). The percentage varied across the macro-regions from 30.7% (Mazowieckie) to 43.9% (North).

https://doi.org/10.1371/journal.pone.0306895.g006

The respondents were the most aware of support benefits to cover maintenance, in particular food, clothing, footwear, personal hygiene products, and lodgings fees. Awareness of health insurance contributions covered by the state is slightly smaller.

The South-West and Mazowieckie Voivodeship macro-regions exhibited the highest level of awareness concerning support benefits for migrants from Ukraine (Figs 7 and 8 ). The least knowledgeable in this regard were residents of North and East.

https://doi.org/10.1371/journal.pone.0306895.g007

https://doi.org/10.1371/journal.pone.0306895.g008

It has been over a year since the largest exodus of Ukrainians fleeing the war in their country in the history of Poland and Europe. From 1.2 to 1.3 million of them settled in Poland in addition to those who lived there before. Researchers from the Faculty of Political Science and International Studies, University of Warsaw and University of Economics and Human Sciences in Warsaw probed the public perception of Ukrainian refugees for the second time in January 2023. The survey results show that the positive attitude of Poles towards Ukrainians and support for them—mainly military—have remained virtually the same since the invasion. Nevertheless, a quarter of the respondents gave the affirmative answer to an additional question: ‘Has your attitude towards migrants from Ukraine changed over the last six months from June 2022?’ Moreover, 68% of them declared the change was towards a negative perception, which meant a worse attitude. As the report reads, ‘the following are listed among the potential threats to Poland posed by migrants from Ukraine:

• an adverse impact on the Polish economy / state budget / inflation;
• an adverse impact on the labour market;

The impact of Ukrainian nationalism declined compared to April 2022, but the respondents mentioned entitlement mentality and different culture of Ukrainians more often [ 20 ].

According to Łodziński and Szonert [ 21 ], the migration policy is becoming a policy without politics: coherent efforts in various aspects of migration, such as the labour market, policy towards the international community of Poles, protection of borders, and refugee policy with no broader and official discussion concerning its long-term goals. In this policy without politics, priorities tend to congregate around the needs of the labour market, demographics, and migration, considering the actual political context instead of ideological and strategic presumptions.

The impact of stereotypes on the way to integration is an important social aspect [ 22 , 23 ]. The strength of negative stereotypes and negative narration of media [ 24 ] in both cultures (Polish and Ukrainian) stemming from past armed and social conflicts between the nations will most probably dwindle gradually as their coexistence continues [ 25 ]. Immigrants and refugees face the most significant challenges with transferring their skills and adapting to the host country’s labour market [ 26 ]. Economic immigrants, who base their decisions on how easily their human capital and other resources can be transferred to host countries, tend to be more favourably selected to enter the labour market [ 27 ]. Migrants tend to move to countries where their skills are relatively scarce, filling in gaps in the natives’ set of skills [ 28 ].

The Ukrainians’ continuing desire for their own homeland should be considered. So, finding one’s own place among the Polish community is a big challenge. More civic-oriented identity becomes the predominant approach to nation-building in Ukraine, citizenship will be a central part of the process [ 29 – 33 ].

As regards assistance to Ukrainians, the public is divided along another line as well. Nearly half of the respondents (48%) believed Poland should provide more support, but more than a third were against it. Some called for curbing welfare. The researchers with the University of Warsaw pointed out another trend that had been there all along and has deteriorated slightly recently. Approval for the Act on aid to Ukrainian nationals (which grants them benefits equal to those for EU citizens) has slightly declined by 4 pp. since April 2022. Although most Poles are in favour of aid to Ukrainians in the form of a single payment of PLN 300 (49%), access to a free healthcare system (62%), and admission of children of Ukrainian refugees to Polish schools (87%), there is no broad approval of family and parent benefits, like PLN 500 monthly per child or social welfare benefits. Five per cent more people perceive it negatively than in 2022. Up to 16 pp. more (36% today) of the respondents were not in favour of state-funded lodgings for Ukrainians. In February, the Polish government introduced partial payment for refugees who spent more than 120 days in Poland. The public is annoyed by the more widespread foreign language, mostly Russian, used by the refugees. It is perceived as a ‘language of the enemy’, and Poles become disoriented as to who they are [ 20 ].

Other important efforts include governmental, non-governmental, and business initiatives to help the refugees find employment, such as Polish language courses, vocational training (including IT), job board applications and websites for Ukrainians, including governmental pracawpolsce.gov.pl opened in summer 2022 [ 34 ].

Selected cash benefits available to Ukrainians after the invasion:

• PLN 300, a one-time livelihood benefit;
• PLN 500, a child benefit under the Rodzina 500+ scheme;
• family care capital for every child aged 12 to 35 months;
• PLN 95 to PLN 135 a month of a family benefit;
• PLN 1,000, parent benefit;
• PLN 215.84, nursing benefit;
• nursing pay;
• PLN 1,000 for childbirth;
• care benefit;
• up to PLN 400, subsidy for daycare centre, children’s club, or daycare provider;
• PLN 300, Dobry Start scheme for schoolchildren;
• PLN 90 to PLN 110, allowance for education and rehabilitation of a child with disabilities;
• rent allowance;
• welfare ticket;
• meals for children and students from Ukraine;
• reimbursable medicines;
• PLN 500, Health4Ukraine medicines allowance;
• benefits granted under specific conditions and for a specific time under the Act on aid to Ukrainian nationals related to the war in Ukraine of 12 March 2022.

The Polish government has provided substantial aid to the refugees, just like local governments, grassroots organizations, and the people. According to research by the Polish Economic Institute, the total (annual) public assistance and private aid (estimated for the first three months after the invasion) provided to the refugees is around PLN 25.4 billion, or 0.97 per cent of the Polish GDP for 2021 [ 7 ].

An additional mobility barrier concerns the large heterogeneity in social insurance rights across European countries. These rights, including old-age pensions, unemployment payments, and government-financed healthcare services, are determined at the national level, and programs differ strongly across countries [ 35 ].

Economic aspects of migration were also investigated in a survey among 808 employers from Małopolskie and Podkarpackie Voivodeships who employed migrants from Ukraine and had a business in one of the voivodeships between 2014 and 2018. The most represented sectors were construction (31.7%) and industry (15,8%). Employers representing services (15.5%) and trade (13.7%) were also rather numerous. The share of the other sectors did not exceed 10%. The survey results show that the main reason behind hiring Ukrainian employees is cost reduction through lower remuneration compared to Polish workers. This argument was provided by 57.3% of the surveyed employees. The result is not significantly varied across the population. The second most popular reason was permanent issues with finding employees with vocational profiles for specific existing vacancies in the local labour market. This reason was provided by 46.3% of the employers. The third reason was better efficiency, quality of work, availability, or work discipline of Ukrainian workers compared to their Polish colleagues. This factor was provided by 40.2% of the employers [ 36 ].

But, there is the distinct local character of the demands for foreign workers in the Mazovian region, and specifically in the direct surroundings of Warsaw. This is a region with relatively strong and market-oriented horticulture sector that has employed temporary migrant workers on a massive scale for over a decade [ 37 ].

Results of a 2022 survey on 1481 refugees from Ukraine who came to Opolskie Voivodeship (south-western Poland) revealed their relatively high competencies. An overwhelming majority of the refugees (62.7%) had both qualifications and professional experience. Moreover, nearly half of them (48%) had a university degree; they were mostly economists (18.9%) psychologists and educators (14.9%), engineers and technicians (10.8%), and physicians (8.4%) followed by representatives of humanities and law graduates (7.4%), personal services (7.5%), and management (6.1%). Trade, production, and transport professionals constituted a much smaller group: 4.2%, 4.6%, and 1.4%, respectively [ 38 ].

According to the portal Rynek Pracy [ 39 ], the number of foreign nationals, including Ukrainians, who get employment and social insurance is growing. In the first quarter of 2019, the Social Insurance Institution had 610,000 foreign nationals registered, including 455,000 Ukrainians. The number grew to 1,057,000 foreign nationals in the first quarter of 2023 with 738,000 Ukrainians. The number of Ukrainians with Polish social insurance grew significantly from 2019 to 2023.

In mid-February 2023, the EWL Migration Platform employment agency [ 40 ], Centre for East European Studies of the University of Warsaw [ 41 ], and the EWL Foundation for Support of Migrants on the Labour Market conducted a survey on 400 adult Ukrainians from across Poland. It demonstrated that 82% of adult refugees from Ukraine found employment in Poland, reaching 84% in the working-age group. The largest share (34%) started working within one to three months after arrival. This high level of employment within the first months of their stay reflects the determination of the refugees to find a job, the openness of Polish businesses to new employers, and the needs of the Polish market and economy.

Migrants from Ukraine fuelled a short-term spike in retail and private consumption in 2022, especially in Poland and Estonia. Moreover, as they grow more integrated, they will join the workforces of the host countries and improve production output in the medium and long term. Ukrainian migrants abroad drive private consumption in host countries, contributing to economic growth. According to National Bank of Ukraine data, Ukrainians abroad spent two billion dollars a month in 2022, over three times more than in the previous year. Estimates by the International Monetary Fund and study by the United Nations, controlled for all other conditions, forecast the contribution of Ukrainian migrants to improve production compared to a base scenario without migration by 2.2 per cent to 2.3 per cent in Estonia, Poland, and Czechia, and by 0.6 per cent to 0.65 per cent in Germany in 2026. Integration of migrants from Ukraine will affect labour markets in host countries [ 42 ].

The European Central Bank, in particular, expects the share of working-age Ukrainian migrants to reach 25% to 55% of the workforce in the Eurozone in the mid-term. Although in the short term, migrants pose additional challenges to the state budget, they will probably be beneficial to the finances and economy of host countries if they remain in the countries for more than several years and are active in the labour market [ 43 ].

Bird and Amaglobeli [ 44 ] estimated the short-term fiscal impact of migrants from Ukraine on the economies of EU states to reach EUR 30–37 billion, which is 0.19–0.23% of the EU’s GDP. Ukraine’s neighbours and Baltic states will spend the largest sums. According to the European Investment Bank [ 45 ], Latvia could spend 9% of its GDP on the adaptation of migrants, Estonia over 7%, and Hungary, Poland, and Czechia, 4–6%. Estimates by the International Monetary Fund expect the long-term net fiscal effect to be beneficial to Europe because Ukrainians actively integrate with the European labour market. Taxes paid by Ukrainian migrants in Poland are a particularly good example of their integration with the labour market.

Regarding Ukrainian nationals in the Polish labour market, 78% of respondents in a 2020 survey among 502 temporary workers from Ukraine working in Poland through OTTO Work Force companies were satisfied with working in Poland. It is 6 pp. more than in the previous year when the workers were more critical. The value for 2022 was virtually the same as for 2020 (79% and 78%, respectively). The percentage was the highest in 2017 (94%) which may be because June 2017 was the first time Ukrainian nationals could legally stay in Poland under the visa-free regime [ 46 ].

The Centre of Migration Research of the University of Warsaw estimated that Ukrainians paid PLN 10 billion in taxes in Poland (about USD 2.4 billion) [ 47 ].

In summary, the rebuilding of Ukraine after the war will probably offer an opportunity for Polish business [ 48 – 51 ]. The networks of enterprises that are being established today will be more effective in the new socioeconomic environment [ 52 – 54 ]. Demographics are an important determinant of the contribution of Ukrainian migrants to the economic growth of Poland [ 55 , 56 ]. Refugees coming to Poland are mainly women with children [ 57 ]. Their permanent settlement in Poland will improve demographic indicators (more children), which is of value in light of the ageing population. Migrants’ labour market integration is a topic of increasing public concern, particularly in the light of the recent refugee crisis faced by mainland Europe. However, non-economic migrants should not be seen as an inevitable burden but as further investments in the host country whose relevant skills can serve to close existing labour market gaps and improve their integration substantially [ 58 ]. Public opinion toward migrants is not positive and explicitly negative during economic downturns. However economic benefits of labour immigration overweight disadvantages. As the Brexit poses the first precedent since WWII when the economic and social ties in Europe loose [ 59 ].

The labour market situation of migrants from Ukraine is changing month by month. It is shaped by several factors: 1. Pre-war migrants active in the agricultural and horticulture industries (the primary targets of seasonal migration in rural and town areas in Poland) are mainly men. Some of them, especially younger ones, no longer migrate due to the war. 2. Before the war, work in Polish agricultural and horticulture industries had been more financially beneficial than during the war, as the geographic reach of migration is growing (towards Western Europe).3. The perception of Ukrainians in Poland is changing because of the war, aid to the migrants, and the growing burden of cultural differences. Therefore, future research should focus on seasonal migrations in the context of broader demographic and social characteristics of the migrants, the profitability of seasonal work in Poland for Ukrainians, and relationships between Poles and Ukrainians in the context of their stay in Poland.

Conclusions

Most foreign nationals in the Polish labour market in 2021 were Ukrainians. The positive trend started in 2017 when they could enter Poland without a visa for the first time. The number of Ukrainian workers in the Polish labour market declined compared to other foreign nationals from 2021 to 2022. The change was not due to a smaller number of Ukrainian employees but the Act, which allows for employment without a permit. The number of permits issued by individual macro-regions varied from 2017 to 2022. The leading macro-region changed from Mazowieckie Voivodeship to North-West (closer to the German border).

The main research objective is to diagnose the conditions of seasonal labour migration, considering sex, age, education, and region of residence of the respondents. The respondents perceived the migration of Ukrainian nationals to Poland mostly positively, especially regarding seasonal work. The youngest respondents and those from the Central and East macro-regions were the most sceptical about the positive impact of Ukrainian migration on the Polish economy. Those with higher education, living in the North, and from Mazowieckie Voivodeship were more optimistic. They also emphasized that the Ukrainians performed work at variance with their qualifications. Only every fifth participant agreed that migrants took away jobs from Poles. Most of the respondents pointed out that small business owners benefited from employing Ukrainians.

A specific objective includes characteristic of stay. The overwhelming majority of the respondents noted an increase in migration from Ukraine after the full-scale invasion and that entire families of Ukrainians were coming to Poland. Less than half of the interviewees believed the migrants would stay in Poland for longer. People with university degrees pointed out the increased number of migrants following the full-scale invasion. It may be because they are more often involved in the efforts of organisations that help migrants from Ukraine. Women more often stated that the migrants settled together with families.

A last specific objective concerns an institutional support for Ukrainian migrants. Nearly half of them agreed that the support system for Ukrainian migrants was a burden on municipal budgets. Most in this group were women and people aged 18–34. At the same time, 40% of the survey population did not know what support means were used by migrants from Ukraine. The respondents were the most aware of support to cover maintenance, in particular food, clothing, footwear, personal hygiene products, and lodgings fees. Participants from the Central and East macro-regions were not inclined to perceive Ukrainians as a growth opportunity for the Polish economy. Residents of East and North had poor awareness of welfare benefits migrants from Ukraine were eligible for.

The study is limited by the systemic solutions presented in the article, which fail to include actions dedicated to the specific characteristics of regions in Poland. The results demonstrate varied acceptance for migrants depending on the residence, sex, and age of the respondents. The diagnosis of the labour market and work conditions of seasonal migrants was conducted considering the historical memory of Poles and stereotypes affecting the opinions on support for Ukrainians. This conclusion and others offered here may be useful when defining objectives for a regional policy regarding seasonal immigrant labour. Researchers investigating the problem of immigrants in the seasonal labour market face the challenge of factoring in applicable labour policies, work conditions, remuneration, and other quantities considering employers and migrant employees. Such a broader research perspective can juxtapose the results with the effectiveness of governmental programmes aimed at supporting seasonal migrant workers. The public opinion survey presented in the article has to be expanded with future research considering respondents’ experience and professional contacts with Ukrainians and how they are supported in the labour market.

Supporting information

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