Effects of increased body mass index on employment status: a Mendelian randomisation study

Causal effect of obesity on the probability of employment in women in Turkey

This study aims to investigate the causal effect of obesity on the employment probability of women in Turkey via the instrumental variable approach by using data from the 2018 Turkey and Demographic Health Survey. Obesity prevalence in the area of living and the overweight status of the oldest child, which are the most common types of instruments seen in the literature, are used as instruments. Consistent with the OLS result, the 2SLS estimate indicates that obese women are statistically significantly less likely to be employed when the overweight status of the child is used as an instrument. On the other hand, the statistically significant effect of obesity disappears when the area level obesity prevalence is used as the instrument. In addition, obesity in women decreases the likelihood of employment in the services sector and full-time jobs and employment with social security. Although the results of this study do not indicate the source of the effect found, the presence of a causal relationship for women should not be ignored when the economic burden of obesity for Turkey is considered.

The association of obesity-related traits on COVID-19 severity and hospitalization is affected by socio-economic status: a multivariable Mendelian randomization study

BACKGROUND

Due to its large impact on human health, socio-economic status (SES) could at least partially influence the established association between obesity and coronavirus disease 2019 (COVID-19) severity. To estimate the independent effect of body size and SES on the clinical manifestations of COVID-19, we conducted a Mendelian randomization (MR) study.

METHODS

Applying two-sample MR approaches, we evaluated the effects of body mass index (BMI, n = 322 154), waist circumference (WC, n = 234 069), hip circumference (n = 213 019) and waist-hip ratio (n = 210 088) with respect to three COVID-19 outcomes: severe respiratory COVID-19 (cases = 8779, controls = 1 000 875), hospitalized COVID-19 (cases = 17 992, controls = 1 810 493) and COVID-19 infection (cases = 87 870, controls = 2 210 804). Applying a multivariable MR (MVMR) approach, we estimated the effect of these anthropometric traits on COVID-19 outcomes accounting for the effect of SES assessed as household income (n = 286 301).

RESULTS

BMI and WC were associated with severe respiratory COVID-19 [BMI: odds ratio (OR) = 1.51, CI = 1.24-1.84, P = 3.01e-05; WC: OR = 1.48, 95% CI = 1.15-1.91, P = 0.0019] and hospitalized COVID-19 (BMI: OR = 1.50, 95% CI = 1.32-1.72, P = 8.83e-10; WC: OR = 1.41, 95% CI = 1.20-1.67, P = 3.72e-05). Conversely, income was associated with lower odds of severe respiratory (OR = 0.70, 95% CI = 0.53-0.93, P = 0.015) and hospitalized COVID-19 (OR = 0.78, 95% CI = 0.66-0.92, P = 0.003). MVMR analyses showed that the effect of these obesity-related traits on increasing the odds of COVID-19 negative outcomes becomes null when accounting for income. Conversely, the association of income with lower odds of COVID-19 negative outcomes is not affected when including the anthropometric traits in the multivariable model.

CONCLUSION

Our findings indicate that SES contributes to the effect of obesity-related traits on COVID-19 severity and hospitalization.

Effects of depression on employment and social outcomes: a Mendelian randomisation study

BACKGROUND

Depression is associated with socioeconomic disadvantage. However, whether and how depression exerts a causal effect on employment remains unclear. We used Mendelian randomisation (MR) to investigate whether depression affects employment and related outcomes in the UK Biobank dataset.

METHODS

We selected 227 242 working-age participants (40-64 in men, 40-59 years for women) of white British ethnicity/ancestry with suitable genetic data in the UK Biobank study. We used 30 independent genetic variants associated with depression as instruments. We conducted observational and two-sample MR analyses. Outcomes were employment status (employed vs not, and employed vs sickness/disability, unemployment, retirement or caring for home/family); weekly hours worked (among employed); Townsend Deprivation Index; highest educational attainment; and household income.

RESULTS

People who had experienced depression had higher odds of non-employment, sickness/disability, unemployment, caring for home/family and early retirement. Depression was associated with reduced weekly hours worked, lower household income and lower educational attainment, and increased deprivation. MR analyses suggested depression liability caused increased non-employment (OR 1.16, 95% CI 1.06 to 1.26) and sickness/disability (OR 1.56, 95% CI 1.34 to 1.82), but was not causal for caring for home/family, early retirement or unemployment. There was little evidence from MR that depression affected weekly hours worked, educational attainment, household income or deprivation.

CONCLUSIONS

Depression liability appears to cause increased non-employment, particularly by increasing disability. There was little evidence of depression affecting early retirement, hours worked or household income, but power was low. Effective treatment of depression might have important economic benefits to individuals and society.

Obesity- attributable costs of absenteeism among working adults in Portugal

Background

Obesity leads to poor health outcomes and may adversely affect work productivity. This study, aimed to investigate the obesity- attributable costs of absenteeism among working adults in Portugal.

Methods

The study population included individuals actively working at baseline from the Epidemiology of Chronic Diseases Cohort (EpiDoC), a large Portuguese population-based prospective study. Body mass index was measured at baseline and in two follow-up interviews. Absenteeism in each wave of the EpiDoC was assessed by the question “Did you have a sick leave in the previous 12 months? yes/no”, followed by “How many days did you miss work due to sickness in the previous twelve months?”. Body mass index (BMI) was classified into underweight, normal weight, overweight, and obese, based on the standard World Health Organization definition.

Association between obesity and absenteeism was estimated with the negative binomial regression model adjusted for BMI, chronic diseases, and lifestyle. Obesity- attributable costs were calculated using lost gross income during the time absent from work, through the human-capital approach.

Results

The EpiDoC included 4338 working adults at baseline. Of these, 15.2% were obese at the beginning of the study and 22.7% of the population had been absent from work in the last 12 months. Participants with obesity missed 66% more days at work (IRR: 1.66; CI 95%:1.13–2.44; (p = 0.009.) than those with normal weight. The odds of having been absent from work were 1.4 times higher in obese compared to non-obese individuals (CI 95%: 1.18–1.67; p < 0.01) adjusted to sex and type of work. Obese individuals missed 3.8 more days per year than those with normal weight (95%CI: 3.1–4.5). Extrapolating to the entire Portuguese working population, absenteeism due to obesity incurred an additional cost of €238 million per year.

Conclusion

Obesity imposes a financial burden due to absenteeism in Portugal. Employers and national health regulators should seek effective ways to reduce these costs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13337-z.