Educational differences in self-rated physical fitness among Finns

Socioeconomic position (SEP) reflects individual’s social and economic location in the structures of society. Karl Marx and Max Weber created the basics for the understanding of socioeconomic differences [1] and both traditions contributed to the modern research on health and socioeconomic circumstances. The aspects of wealth and working conditions can be seen largely of Marxian and the aspects of non-material resources and inequalities more of Weberian heritage. In this article the social stratification is described with SEP, since it reflects both Marxian and Weberian traditions [2].

Physical fitness (PF) is “a set of health or skill related attributes that people have or can achieve” [3]. A person with good PF integrates the use of the attributes effectively to reach an optimal performance. As a result PF enables “to carry out daily tasks with vigour and alertness without undue fatigue and ample energy to enjoy leisure-time pursuits and meet unforeseen emergencies” and “to achieve the optimal quality of life” [4] Physical activity (PA) is defined as “any bodily movement produced by skeletal muscles, that results in energy expenditure” [3].

Those in higher SEP have longer and healthier lives compared to those in lower SEP [1, 5, 6]. PA is a well-known contributor to good health [7‐9] and the main way to improve PF [3, 4, 8, 10], when performed regularly in adequate amounts and proper intensities [8, 11]. In addition to PA, PF is also influenced by energy balance, smoking, chronic diseases [10] as well as individual training effects and characteristics that includes genetic variability [12‐15]. PF enhancing health behavior is more common in higher than lower socioeconomic groups. For example, those in higher SEP have higher PA levels [16‐22], less obesity [23‐25], smoke less [24, 26, 27] and have less chronic diseases [28, 29] than those in lower SEP.

Health-related PF is a combination of cardiovascular endurance, body composition, muscular strength, muscular endurance and flexibility [3]. Good PF is inversely associated with mortality and chronic morbidity [10, 12]. It has associations also with better lipid and lipoprotein profile, lower blood pressure, better body composition, lower inflammation levels, improved autonomic nervous system [10] and improved insulin sensivity [10, 30]. To have an overall picture of health-related PF, all components should be measured [4]. The use of self-rated PF (SRPF) might be a useful option in population based studies, since measuring objectively all PF dimensions is time consuming and expensive. Studies support that SRPF correlates with objectively measured PF rather well [31‐33].

In this study, we used birth cohort adjusted years of education to indicate SEP. Education is widely used in health-related research because it reflects both material and immaterial resources such as skills, knowledge, attitudes and values [1, 2]. Education is also an important indicator of life course influences as childhood circumstances often influence adult education levels [2]. Furthermore, education is a strong determinant of occupational status, working conditions and income [1, 2, 34]. It is usually also more reliably reported than e.g. income levels [2].

While the educational differences in PA have been reported in detail [16, 20, 21], associations of education and PF have remained largely unexplored. Our purpose was to explore whether SRPF is associated with age and education and to examine whether PA, body mass index (BMI), history of chronic diseases and smoking contribute to the possible association of education and SRPF. We assumed that the young report more good PF levels than the elderly and that those with less education report more poor PF levels than those with longer educational career [35]. We assumed also that leisure-time PA (LTPA) and BMI would contribute to the educational differences in SRPF, because low LTPA levels [17‐19] as well high BMI [23] are more common in lower than higher educational groups, and both of them are known to correlate with SRPF [36].

Our purpose was to explore whether SRPF is associated with age and education and to examine whether PA, BMI, history of chronic diseases and smoking contribute to the possible association of education and SRPF. Our large population based data supported our hypotheses and suggested that age was inversely associated with SRPF. Education was directly associated with SRPF, and these educational differences were explained by health behavior related factors. LTPA, the strongest single contributor, explained fully and BMI partly the educational differences in SRPF among men. The combination of BMI, history of chronic diseases and smoking explained all educational differences in SRPF, except for the low educated women. The combination of age, three modes of PA, BMI, smoking status and history of chronic diseases explained all educational differences in SRPF among both genders. The strengths of this study are a representative population sample and education as the main indicator of SEP. The response rate of FINRISK 2007 study was 62.6%. The participation rate was acceptable, but those who do not participate are known to be more often less educated [41, 42]. If the participation rate would have been higher and thus the proportion of the less educated would have been higher, it is possible that the educational differences in SRPF would have been even more pronounced than reported.

According to our study, the strongest single contributor for the educational differences in SRPF was LTPA. Also previous studies support that LTPA levels are higher among the high educated when compared to the low educated [16, 18, 21, 24]. Good PF is often due to high level of PA [3, 4, 10]. In addition to PA, material welfare and social influences may explain the educational differences in SRPF. Better material circumstances increase the possibility and variety to participate in LTPA among the high educated when compared to the low educated [1, 2, 34, 43]. Moreover, social appreciation and support possibly gained through high education is likely to increase the participation in LTPA [44, 45]. The low educated may also live in more deprived neighborhoods, where positive LTPA may be restricted by inadequate sports facilities, feelings of unsafe [43] or social control and norms [44].

Apart from LTPA, we found that other modes of PA could not explain the educational differences in SRPF. However, the questionnaire measured only the amount but not the intensity of CPA. It is therefore possible that all CPA reported was not contributing to PF. For example, CPA may be performed out of necessity instead of own motivation if other types of commuting are not possible. This is likely at least, if the household cannot afford to buy and maintain a car, and the public transportation services are inadequate in the neighborhood. If CPA is performed out of necessity, the fitness promoting intensities may even be avoided especially, if the working place lacks proper changing rooms and showering facilities. In this assumption the socioeconomic differences could exist if not in the amount but in the intensity of CPA.

In our study, BMI explained educational differences in SRPF only partly and only among men. It has been studied that BMI correlates with SRPF, but when adjusted with LTPA, the association between BMI and SRPF disappears [36]. This could indicate that LTPA would be a mediating factor between BMI and SRPF at least for middle-aged male employees. It is also established that LTPA would mediate the association of BMI and SEP for women, but not for men [46]. Thus it seems that LTPA mediates the health behavior related factors which BMI influence, but mediating pathways might be different among men and women. This difference may offer some explanations for the fact that we found partial mediating effects with BMI among men but not among women, and that LTPA explained educational differences in SRPF among men but not among women.

We did not expect that the explaining factors would differ between women and men. The gender difference in the explaining factors may arise either from the different views of SRPF among women and men or from the gender difference within the actual health behavior. To our knowledge, it is not known how individuals estimate their PF. However, it is likely that they compare their abilities with a reference group, which may consist of co-workers, friends, neighborhood inhabitants, own previous PF or others of the same gender. In this respect, individual SRPF may vary a great deal according to the reference group that has been chosen. For example, comparing PF with co-workers in physically straining work is likely to produce different estimations than if the reference groups would consist mainly of those in light work. Also previous severe illnesses of very high sport participation in past may affect individual estimates of individual PF.

We assume that conceptual differences may also contribute to PF estimations. For example, men may consider PF more as physical performance and women more as general well-being. If it is assumed that men consider PF more as physical performance and women as general well-being, it is also likely that men perform LTPA more often PF oriented and women just for having fun and enjoyment. Interestingly, according to our results, (slightly) a higher proportion of men than women considered their fitness level to be poor even when they reported high or medium LTPA levels (Table 2). Thus it is likely that some of the gender differences in our findings can be explained by conceptual differences in SRPF. It is most likely that the concept of SRPF vary also according to other attributes than gender, for example according to age or educational level.

For the future studies, more specific validation is needed to clarify the correspondence of self-rated and objectively measured PF. Also the associations of SRPF and other health measures such as self-rated health and functional ability need to be explored as well as the association of SRPF and other SEP indicators, such as income and occupation.

Educational differences in SRPF were found, but they could be explained by health behavior related factors. LTPA offered the strongest single explanation for the educational differences in SRPF. Enhancing LTPA among the low educated could improve public health and decrease the health inequalities between the educational groups.