In this study, we investigated the relationship between obesity and absenteeism and found that obesity increased the incidence rate ratio of absenteeism by 31% in our study cohort, independent of other risk factors, including chronic disease and unhealthy lifestyle choices. Obese women, in particular, are more likely to miss work, especially those with white-collar professions, and we estimate that absenteeism due to obesity imposes a considerable financial burden on states, totalling an additional €236 million per year in Portugal.
In previously published study, obesity was found to increase the absenteeism incidence rate ratio by approximately 27%, than normal weight peers.(23). Some authors, when applying a longitudinal methodology to understand the causal relationship between obesity and absenteeism, found that obesity could act both as a direct explanatory variable and as a mediator for other variables linked to loss of productivity, as obesity is also considered a risk factor for several chronic diseases(6, 23). These results are consistent with our findings showing similar degrees of obesity-associated effects on absenteeism, both when it is evaluated separately and when associated with other risk factors, such as chronic diseases and lifestyle habits. However, as has been recommended by other authors, prospective analyses are necessary to determine the time of occurrence, that is, whether diseases occur before or after an individual has become overweight or obese. Such studies would help to establish a clear causal framework for a meaningful attribution of the indirect costs of obesity(6).
Obese workers are more likely to report poor work ability or limitations in the amount, type, or quality of work they perform than their normal-weight counterparts (24). In the present study, we found that obese women were 68% (P < 0.01) more likely to miss work than normal-weight women, with significant increases in likelihood of absenteeism observed for women in both white- and blue-collar professions (82% and 48%, respectively). However, although similar trends were observed with men, the differences were not significant. Consistent with these results, a study from the United States found that the probability of missing work was significant across all professional categories for obese women, although among men, the results varied by occupation (4). This discrepancy with our findings for men may be due to the higher prevalence of obesity observed in the American study population, reported to be 23% among men; in contrast, male obesity rate in our study was 6.59%(25). Among women, similar rates of obesity were noted in both studies. This may be due to biological aspects related to the process of body fat accumulation, which begin at puberty and continue throughout life, as well as the complex interactions between genetic, epigenetic, and hormonal issues, and may explain the similar results reported in both studies [21, 23]
Numerous studies have shown that obesity is strongly associated with absenteeism. In one case, Finkelstein et al. reported that grade-I obese women (BMI, 30–34.9) in the United States miss 5.2 days per year due to illness or injury, which is 1.8 days more than normal-weight women, while grade-II (BMI, 35–39.9) and grade-III (BMI, ≥40) obese women miss 3.0 and 4.8 more days, respectively, than normal-weight women, with all increases statically significant (25). In contrast, grade-II and grade-III obese men miss approximately two more workdays per year than normal weight men, similar to what has been found in other studies(4, 25). Here, we found that obese individuals miss 10.2 workdays on average per year—3.8 more than their normal-weight peers. Obese women and men lose 12 and 8 working days per year, respectively, which is 4.6 and 3.5 days more, respectively, than their normal weight counterparts, with only results for women showing statistical significance. Similarly, a study conducted in London reported a loss of 9.5 workdays per year for obese workers. European countries have many common characteristics, relating to population distribution, sociodemographic characteristics, and prevalence of obesity itself. Thus, it makes sense that our results are more similar to those reported in London (26) than to findings from the United States(4, 24, 25). Regardless, all these studies report the key finding that obesity has a substantial impact on lost working days (4, 26). Adiposity and fat distribution are closely associated with whole body metabolism and long-term health, and consequently, obese individuals often have more chronic conditions associated with poor health status. Thus, we expect that this is the reason that people with obesity display greater absence from work due to sickness, as well as increased healthcare consumption, relative to their non-obese counterparts.
Critically, absenteeism due to obesity imposes a considerable financial burden on states. In this study, we estimated that obese workers incur an additional cost of €236 million per year when compared to non-obese workers. These costs range from to €297 to €467 per year for each obese employee and are higher for women than men (€398.6 vs. €361.5, respectively). A previous study by Pereira et al. estimated the total indirect cost of obesity in Portugal in 2002 at €199,8 million, indicating that obesity causes considerable economic losses for the country . Comparison with our findings reveals a difference of €37 million between the study by Pereira et al. and our estimate for obesity-associated costs due to absenteeism per year, despite that, it is important to say, that the methodology between the two studies is different, while Pereira et al used Attributable Risk to calculate the number of deaths attributable to obesity, taking into account the relative risk of obesity prevalence estimates, (27), in our study we used absenteeism as main outcome and estimated the costs through the HCA extrapolating to all population using the prevalence of obesity in the years of study.
In Europe, the estimated cost of absenteeism varies from €117 to €1873, depending on cost category or comparison group (11), and worldwide, this same trend is observed (6, 12, 13, 26, 28). Further, international studies have attributed increases in health sector spending ranging from 30–60% to absenteeism, with indirect costs reaching $8.65 billion per year in 2012(23, 25). Thus, the economic impact of obesity on both the health sector and society as a whole is undeniable, and numerous studies have reported this issue as a critical problem that is increasing in prevalence. We therefore expect that the implementation of strategies to prevent obesity could generate gains in productivity, as well as reduce the economic burden imposed by this disease.
We note, however, that this study has several limitations. First, the BMI values were based on self-reported weight and height, which could generate systematic bias, as people often underreport their weights and overestimate their heights (29). Second, our dependent variable, absenteeism, had a high number of zero observations, which substantially reduces the sample size of the study. However, by using appropriate statistical modelling and comparing different statistical approaches, we trust that our data are sufficiently robust to support our conclusions (21, 22). An additional challenge arises from the fact that, to the best of our knowledge, there is no standard methodology reported in the literature for evaluating the indirect cost of absenteeism due to obesity (7, 11, 12). Further, it is important to note that the salary values in this study were estimated based on the imputation of average worker wage data corresponding to the evaluation period of the EpiDoC and may therefore not be completely accurate. In addition, we assessed the cost of obesity with the HCA, which takes both an individual and societal perspective and has often been criticized for overestimating loss of productivity (19).
Despite these limitations, our study also has a number of key strengths. In particular, our data were obtained from a cohort representing the entire adult Portuguese population, and repeated measures can evaluate changes in outcomes over time. We also evaluated costs using obesity as the main predictor variable, whereas most other studies evaluated costs related to obesity-related diseases, and not just obesity. For this reason, we expect that our study is less prone to confounding bias and thus, better able to determine associations between obesity and absenteeism, as well as to estimate its costs. Furthermore, our dataset containing information relating to days absent, chronic diseases, and lifestyle factors is quite robust for indirect cost estimates and allows for a comprehensive analysis of obesity-associated factors.