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Obesity and Sickness Absence: Results from a Longitudinal Nationally Representative Sample from Germany

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Obesity and Sickness Absence: Results from a Longitudinal Nationally Representative Sample from Germany Open Access Research BMJ Open: first published as 10.1136/bmjopen-2017-019839 on 6 June 2018. Downloaded from Obesity and sickness absence: results from a longitudinal nationally representative sample from Germany Katrin Christiane Reber, Hans-Helmut König, André Hajek To cite: Reber KC, König H-H, ABSTRACT Strengths and limitations of this study Hajek A. Obesity and Objectives The current study aimed at investigating the sickness absence: results longitudinal association between obesity and sickness ► Data came from a large nationally representative from a longitudinal nationally absence in women and men in Germany. representative sample sample of German individuals. Methods Data were derived from the German from Germany. BMJ Open ► Panel regression models were used, diminishing the Socio-Economic Panel (GSOEP) which is a nationally 2018;8:e019839. doi:10.1136/ problem of unobserved heterogeneity. representative, longitudinal study of private households in bmjopen-2017-019839 ► The possibility of reverse causality cannot be Germany. We draw on data from 2002 to 2012. Information dismissed. ► Prepublication history and on self-rated body mass index has been collected every ► The self-rated body mass index was used to classify additional material for this second wave since 2002. Sick leave days (total number paper are available online. To obesity. of working days missed due to illness in the past calendar view these files, please visit the journal online (http:// dx. doi. year) and sick from work for more than 6 weeks in the org/ 10. 1136/ bmjopen- 2017- preceding 12 months (yes/no) were used as outcome 019839). measures. Fixed-effects (FE) regression models were between 16.5% and 23.9% in women and used for the total sample and stratified by sex. Gender between 17.3% and 23.3% in men.2 3 Obesity Received 9 October 2017 differences were examined using interaction terms (sex × and its related adverse health effects pose a Revised 17 April 2018 weight category). considerable burden to the healthcare system Accepted 27 April 2018 Results Controlling for several potential confounders, because of both its direct costs incurred by Poisson FE regression analysis showed that transitions increased health service utilisation and indi- from normal weight to obesity were associated with an rect costs arising from reduced or lost work- increase in sick leave days in women (incidence rate 4 5 ratio (IRR) 1.27, 95% CI 1.02 to 1.57) but not in men (IRR force productivity. Several studies found http://bmjopen.bmj.com/ 0.85, 95 % CI 0.68 to 1.06)—with significant gender that indirect costs of overweight and obesity differences (sex × obesity, p<0.01). Moreover, conditional make up the majority (51%–59%) of total 6 FE logistic regressions showed that transitions from costs, thus exceeding direct costs. Unsurpris- normal weight to overweight were associated with an ingly, the impact of obesity on the workplace increase in the probability of long-term absenteeism in in terms of absence from work due to excess women (overweight, OR 1.41, 95% CI 1.08 to 1.85) but not weight-related illnesses or other factors in men (overweight, OR 0.84, 95% CI 0.65 to 1.09). Gender continues to be of primary interest to health differences were significant (sex × overweight, p<0.01). policy-makers and employers. Conclusions Our findings stress the longitudinal The association between obesity and sick- on October 4, 2021 by guest. Protected copyright. association between excess weight and increased ness absence has been well documented likelihood of sick leave days as well as long-term absenteeism in women. cross-sectionally. Studies found a tendency for obese individuals to have a higher number of sick leave events and also have longer spells of individual sick leave compared with their INTRODUCTION normal-weight counterparts.4 7 8 As regards Obesity remains a major health concern in preobesity/overweight, inconsistent results Western societies.1 Behind the Americas, have been reported in literature for the asso- Europe ranks second regarding the propor- ciation with sickness absence. While some tion of overweight (25 kg/m²≤ body mass index studies found evidence of an elevated risk Department of Health Economics (BMI) <30 kg/m²) or obese (BMI ≥30 kg/ of sick leave for preobese subjects, others and Health Services Research, m²) people, according to WHO statistics. reported no significant association when University Medical Center The share of men and women being 18 years compared with normal-weight subjects.7 8 Hamburg-Eppendorf, Hamburg, and over having a BMI ≥25 kg/m² amounts However, in general, there tended to be a posi- Germany to 59.1% and 44.7%, respectively, and in the tive relationship between higher levels of Correspondence to EU-28. For Germany, the prevalence of adult BMI and sick leave, although available results Dr André Hajek; a. hajek@ uke. de obesity has recently been estimated to range pertaining to short-term spells were less clear, Reber KC, et al. BMJ Open 2018;8:e019839. doi:10.1136/bmjopen-2017-019839 1 Open Access which may be due to discrepant definitions of short-term from your doctor.’). Individuals reported the frequency BMJ Open: first published as 10.1136/bmjopen-2017-019839 on 6 June 2018. Downloaded from sick leave.7–9 Findings further suggested gender differ- of days of absence (‘none’, ‘a total of X days’). Long-term ences regarding the association between sickness absence absenteeism is based on a question that assessed whether and both preobesity and obesity. Women showed higher a person was sick from work for more than 6 weeks at rates of sickness absence and also stronger associations one time in the previous calendar year (‘Were you sick were observed for female employees.4 10 11 from work for more than 6 weeks at one time last year?’). Many studies that have been conducted so far employ Employees who reported not being sick from work for cross-sectional designs which do not allow drawing more than 6 weeks were coded as zero, while employees conclusions about causal mechanisms. So far, there is yet with a positive answer (‘yes, once’ and ‘yes, several times’) limited longitudinal research investigating the associa- were coded as one. tion between excess weight and sickness absence. While most of the longitudinal studies have been carried out in Independent variables the USA or the Scandinavian countries, evidence is still BMI was based on self-reported values of height and lacking for Germany. Therefore, the aim of this study weight and calculated as weight divided by squared height was to assess the association between obesity and sickness (kg/m²). We categorised BMI into four groups according absence using a representative sample of the German to WHO classification as underweight (BMI ≤18.5 kg/ labour force in a longitudinal setting. m²), normal weight (18.5 kg/m²≤BMI<25 kg/m²), preo- bese/overweight (25 kg/m²≤BMI<30 kg/m²) and obese (BMI ≥30 kg/m²).17 18 STUDY POPULATION AND METHODS Several sociodemographic, health-related and subjec- Sample tive well-being factors that have been identified by prior We used data from the German Socio-Economic Panel research to be associated with both excess weight and Study (GSOEP), a representative longitudinal survey productivity loss, or proposed to influence the relation- of the German population conducted on an annual ship between obesity and sickness absence were entered 9 10 19 20 basis since 1984.12 The GSOEP is located at the German as potential confounders in the analyses. As regards Institute for Economic Research (Deutsches Institut für sociodemographic characteristics, we considered age Wirtschaftsforschun, Berlin). It is a household panel like and marital status, the latter being dichotomised with the Panel Study of Income Dynamics in the USA or the married, living together coded as one and zero otherwise British Household Panel Study. Every year, approximately (ie, married, but living separated from spouse; divorced; 11 000 households and more than 20 000 individuals widowed; single are coded as zero). Concerning health-re- were interviewed. All adult household members (aged 17 lated and subjective well-being factors, we included subjec- and over) are interviewed. Topics include, for example, tive health, which was based on individuals’ self-rated domain satisfaction (eg, satisfaction with leisure time), health (5-point Likert scale: 1=‘bad’ and 5=‘very good’) http://bmjopen.bmj.com/ health or occupational status. Very high reinterview and disability assessed by a single item asking whether response rates were observed in the GSOEP.13 In addition, they were ‘legally classified as handicapped or capable it was found that survey attrition is low in the GSOEP (in of gainful employment only to a reduced extent due to most years and subsamples, attrition was less than 10%.14 medical reasons’ (no/yes). The disability variable served as 21 22 15 Further details regarding the sampling frame as well a proxy measure for objective morbidity. In accordance 23 as the survey design of the GSOEP are given elsewhere.16 with prior research, the continuous variable satisfaction In the current study, the analyses were based on data with life evaluated by the question ‘How satisfied are you from six waves (2002–2012, biannually), because BMI with your life, all things considered?’ (11-point rating scale on October 4, 2021 by guest. Protected copyright. was assessed only biannually. We restricted our sample ranging from 0 ‘completely dissatisfied’ to 10 ‘completely to individuals aged 17–65 years who were in the labour satisfied’) was included. Moreover, the time-invariant vari- force and employed at all waves. Thus, while regression able sex was used for descriptive purposes. analysis with sick leave days as outcome measure is based on 48 865 observations, the regression analysis with long- Statistical analysis term absenteeism as outcome measure is based on 9564 We used fixed-effects (FE) regression models to estimate observations.
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