To our knowledge, this is the first study to investigate whether and how the magnitude of absolute and relative educational inequalities in sporting inactivity has changed among adults in Germany since the early 2000s. The findings indicate that the overall prevalence of sporting inactivity declined between 2003 and 2012, but that this decline was solely due to a decrease in sporting inactivity among the better educated. In the low education group, the prevalence of sporting inactivity was consistently high throughout the study period. Hence, the sporting inactivity gap between adults with high and low educational attainment in Germany has widened significantly on both the absolute and relative scale within less than a decade. As our findings indicate, these trends were not sex-specific, but occurred similarly in both men and women. However, the increase in inequalities was larger in younger age groups under 50 than among the elderly population.
Strengths and limitations
The analyses in this study were based on large nationwide samples, which enabled separate analysis for men and women. Owing to the sample design and the weighting factors used to adjust for survey non-response, it is possible to draw conclusions for the adult population aged 25 to 69 years in Germany from our results. That the methods of data collection did not change across surveys assured adequate comparability of data over time. Recall bias should have been low, as the questions on education referred to the present and the recall period for sporting inactivity was only 3 months. The use of internationally established methods, such as the CASMIN classification, the ESP 2013, and the SII and RII as summary measures for the magnitude of inequality, can enable other researchers to use our results for between-study and cross-country comparisons, or future meta-analyses.
There are several limitations worth noting in this study. First, causality between education and sporting inactivity cannot be inferred because of the observational nature of the data. Second, the intervals between the surveys were not equal, which may have potentially biased the results for time trends. Third, it must be considered that the data on sporting inactivity were based on self-reports. Self-report measures of physical activity have only a low-to-moderate correlation with direct/objective activity measures [
25], which may be due to the relatively large amount of cognitive effort required to answer questions on physical activity [
26]. This, however, applies primarily to detailed questions on frequencies and durations of different activity types, whereas a simple yes/no question about any sports activity during the last 3 months should be less affected as it is less cognitively demanding. Furthermore, self-reports on sports activity can be subject to social desirability bias resulting in a potential under-reporting of sporting inactivity [
27,
28]. If better-educated participants were more likely to under-report their inactivity than less-educated participants, our results could potentially overestimate the extent of educational inequalities in sporting inactivity. If the perceived social unacceptability of sporting inactivity increased disproportionately in more highly-educated groups during the study period, a resulting increase in socially desirable responses from better-educated participants may have contributed to the observed widening of inequalities in sporting inactivity.
It must further be taken into account that the binary variable of sporting inactivity during the last 3 months (yes vs. no) used as the outcome measure in our study is a rather crude indicator for lack of health-enhancing physical activity. The results therefore do not allow conclusions to be drawn either on how inequalities in total sports activity levels have changed, or on trends in inequalities in the frequency and duration of activity. However, we performed a sensitivity analysis using a binary variable of up to 2 h vs. more than 2 h of sports activity per week as an outcome measure. Although the sensitivity analysis generally shows smaller inequalities in sports (in)activity, they are in line with the results from the main analysis in indicating significant increases in inequalities on both the absolute and relative scale for men and women. Another trend study in which the binary yes/no indicator of sporting inactivity during the last 3 months was used indicated that sporting inactivity has continuously decreased between the German Health Interview and Examination Surveys 1990–92, 1997–99, and 2008–11 [
29]. This is consistent with our findings, which indicates good reliability of the results produced by this indicator. Evidence supporting the convergent validity of our findings (e.g. co-occurring increasing obesity inequalities according to education, as a result of increasing sports inequalities) is, to our best knowledge, not available to date for the German adult population.
Moreover, it has to be acknowledged that the term “sport” was not precisely defined in the interview and/or no word list was provided. As a consequence, the definition of the term was up to each respondent’s subjective concept of sport. However, as mentioned in the
Methods section, in German the term “sport” is a very broad term; it is generally thought to include not only competitive club sports but also physical exercise to improve or maintain one’s physical fitness. From our knowledge, this is a wider understanding than is common in the English language, which must be borne in mind with regard to the results of our study.
Concerning the external validity and national representativeness of the samples, it must be mentioned that the response rate decreased across the surveys. However, the sample bias according to sex, age, education, and region, increased only slightly between 2003 and 2009 and remained constant thereafter, as indicated by the overall sample efficiency [see Additional file
1: Table S1]. To minimise the impact of potential selection bias from differential non-response across the surveys, we adjusted for non-response year-specifically by using weighting factors (see above). As the weighting procedure takes into account the age, sex, educational, and regional distribution of the samples, their national representativeness is limited to these characteristics.
Comparison with other research
The findings of this nationwide study are consistent with previous studies indicating that sporting inactivity and other types of physical inactivity have decreased in many developed countries over the last decades [
30‐
34]. However, the picture with regard to changes in social inequalities in inactivity habits is less coherent according to previous research from developed countries. While some studies have found indications of widening inequalities consistent with ours [
30,
32,
35], others have found inequalities during the last 2–3 decades to be constant [
31,
33,
36,
37]. A trend study from Canada examined absolute and relative inequalities in leisure-time physical inactivity and suggested that both kinds of inequalities have narrowed from 1981 to 1996, but widened from 1996 to 2005 [
38]. A study conducted in a US metropolitan population suggests a narrowing of inequalities during the 1980s [
39]. Scholes and colleagues [
40] have examined trends in area-level socioeconomic inequalities in physical activity levels (without work-based activity) in England from 1998 to 2008. In contrast to our findings, they found unchanged absolute and relative inequalities among younger groups and a widening of absolute inequalities among older women. The partial inconsistency in findings may be due to between-study differences in inactivity measures, study periods, countries/regions, and indicators of social position. Moreover, most studies have considered only either absolute or relative inequalities, which can have a significant impact on judgements about inequality trends [
17]. Mixed results on trends in inequalities in leisure-time physical inactivity, however, have also been found between different US states within the same study [
35]. Altogether, this suggests that trends in social inequalities in physical inactivity habits can be subject to strong contextual, period, cohort, sociocultural, and/or regional differences. A regional study conducted in northeast German rural communities indicated that the educational gradient in adult sporting inactivity evolved in this part of the former East Germany only in the course of social transformation after German reunification [
41]. Data from a retrospective survey of elderly residents in two German cities, similar to our nationwide findings, indicate a stronger increase in sports participation in the better-educated, particularly since the end of the 1990s [
34].
Our observation of widening educational inequalities in sporting inactivity can be regarded as another example of “diffusion of innovations” [
42]. According to this theory, persons of higher social position tend to adopt modern ideas (e.g. a health-conscious and physically active lifestyle) earlier or more quickly than those of a lower social position because, among other reasons, they can draw on more resources. For example, members of advantaged social groups may be able to adopt more healthy behaviours at a faster pace because they are more likely to live in supportive environments that place fewer constraints on individual choice than those faced by people in disadvantaged groups [
43]. Along with this idea from diffusion theory, the theory of fundamental causes [
44,
45] may help explain why social inequalities in sporting inactivity persist over time despite progressive public initiatives to promote physically active lifestyles in the population. Fundamental cause theory argues that the association between social position and health is time-persistent because the lack of material and non-material resources (e.g. money and knowledge) in lower social groups, which is regarded as the fundamental cause of the association, persists no matter how other factors and circumstances may change (e.g. public initiatives to promote physical activity, sports promotion strategies, or physical activity promoting environments). In addition to different resources for pursuing the goal of good health, the theory considers different preferences for health as one of the “metamechanisms” that may contribute to the durable association between social position and health [
46]. People in higher social groups may exhibit a stronger and more consistent preference for future good health than people in lower social groups, for example, because of different time horizons or as part of their cultural “habitus” [
46,
47]. Different preferences for health could also impact on the motivation to commence and maintain sports activity in adulthood and may explain why sporting inactivity declines faster or earlier in higher social groups.
Another explanation often given in the context of educational disparities in health behaviours is the unequal distribution of health-related knowledge. Smith et al. [
38] argue, however, that widening education-related inequalities in physical activity habits are unlikely to reflect unequal knowledge of the consequences of unhealthy behaviours because the basic relevant knowledge is widespread in all education groups today. They emphasize, instead, that widening gaps in health behaviours between groups with different education levels highlight some of the challenges faced by public health interventions. Population-level interventions that seek to improve the health of a population can have unequal effects across social groups and thereby lead to unintended exacerbations of health inequalities [
48]. With particular respect to population-based physical activity interventions, however, a systematic review shows that sufficient information on social group differences in their effectiveness is still lacking [
49]. Therefore, existing and future population-based interventions to promote physical and sports activity should be accompanied by scientific monitoring to ascertain whether they are more effective in some social groups than in others. The resulting findings could help identify effective strategies to promote sports activity in socially disadvantaged groups and thereby to reduce social inequalities in inactivity habits.
Furthermore, it needs to be borne in mind that sporting activity, as a subset of leisure-time physical activity, is only a small component of total physical activity level. Disadvantaged social groups are often more physically active at work and in everyday life, and have thus a higher total energy expenditure level compared with privileged social groups [
5]. This could also explain why they are less likely to participate in leisure sports activity and leisure physical activity interventions. However, participation in sports activities is still desirable because of the greater health benefits associated with these types of activity compared with work-related physical activity [
1].