Healthcare costs associated with overweight and obesity at an individual versus a population level - a HUNT study. / Helsetjenestekostnader ved overvekt og fedme på individnivå versus populasjonsnivå ­ en HUNT-studie.

BACKGROUND: The interpretation of research results is affected by how results are presented. We show the importance of presenting the association between body mass index (BMI) and healthcare costs from both the individual perspective and the population perspective. MATERIAL AND METHOD: Using measurements of height and weight from the Nord-Trøndelag Health Study (HUNT Study) linked to register data on specialist healthcare costs and demographics, we estimated the association between BMI and specialist healthcare costs by means of regression analyses. RESULTS: From an individual perspective, the association between BMI and specialist healthcare costs was strongest in people in obesity classes 2 and 3 (BMI ≥ 35 kg/m2). In contrast, from a population perspective, the association was strongest in the case of overweight (BMI ≥ 25 kg/m2) or obesity class 1 (BMI ≥ 30 kg/m2), as there are more people in this BMI range. INTERPRETATION: The study emphasises the importance of including the population perspective in research studies and policy decision-making processes. People with severe obesity have a high individual risk, but their use of health services has less significance for the overall costs of health care since they are fewer people in this group.

Body mass index and healthcare costs: using genetic variants from the HUNT study as instrumental variables.

BACKGROUND: Past studies have found associations between obesity and healthcare costs, however, these studies have suffered from bias due to omitted variables, reverse causality, and measurement error. METHODS: We used genetic variants related to body mass index (BMI) as instruments for BMI; thereby exploiting the natural randomization of genetic variants that occurs at conception. We used data on measured height and weight, genetic information, and sociodemographic factors from the Nord-Trøndelag Health Studies (HUNT), and individual-level registry data on healthcare costs, educational level, registration status, and biological relatives. We studied associations between BMI and general practitioner (GP)-, specialist-, and total healthcare costs in the Norwegian setting using instrumental variable (IV) regressions, and compared our findings with effect estimates from ordinary least squares (OLS) regressions. The sensitivity of our findings to underlying IV-assumptions was explored using two-sample Mendelian randomization methods, non-linear analyses, sex-, healthcare provider-, and age-specific analyses, within-family analyses, and outlier removal. We also conducted power calculations to assess the likelihood of detecting an effect given our sample 60,786 individuals. RESULTS: We found that increased BMI resulted in significantly higher GP costs; however, the IV-based effect estimate was smaller than the OLS-based estimate. We found no evidence of an association between BMI and specialist or total healthcare costs. CONCLUSIONS: Elevated BMI leads to higher GP costs, and more studies are needed to understand the causal mechanisms between BMI and specialist costs.

The relationship between body mass index and income: Using genetic variants from HUNT as instrumental variables.

Several studies have estimated effects of body mass index (BMI) on labour market outcomes, and these studies have mixed findings. A significant challenge has been to adequately control for omitted variables, selection, reverse causality, and measurement error. We examine the impact of BMI on income using genetic variants as instrumental variables for BMI. Individual-level pre-tax income from tax records was merged with health survey data containing measured height and weight, and data on genetic variants. The analyses were stratified by sex and a variety of methods were used to explore the sensitivity and validity of the instrumental variable (IV) strategy. For females we found that BMI had a negative effect on the logarithm of income. The effect estimated from the IV models (-0.02) was larger than the effect estimated from naïve ordinary least squares regressions (-0.01). For males, the coefficients for the effect of BMI on income were imprecise, and both positive and negative coefficients were estimated depending on the estimation method. Our results suggest that females are susceptible to reduced income levels following increased BMI.

Body mass index and lifetime healthcare utilization.

BACKGROUND: Overweight and obesity is a major global public health challenge, and understanding the implications for healthcare systems is essential for policy planning. Past studies have typically found positive associations between obesity and healthcare utilization, but these studies have not taken into consideration that obesity is also associated with early mortality. We examined associations between body mass index (BMI, reported as kg/m2) and healthcare utilization with and without taking BMI-specific survival into consideration. METHODS: We used nationally representative data on 33 882 adults collected between 2002 and 2015. We computed BMI- and age-specific primary and secondary care utilization and multiplied the estimated values with gender-, age-, and BMI-specific probabilities of surviving to each age. Then, we summed the average BMI-specific utilization between 18 and 85 years. RESULTS: During a survival-adjusted lifetime, males with normal weight (BMI: 18.5-24.9) had, on average, 167 primary care, and 77 secondary care contacts. In comparison, males with overweight (BMI: 25.0-29.9), category I obesity (BMI: 30.0-34.9), and category II/III obesity (BMI ≥35.0) had 11%, 41%, and 102% more primary care, and 14%, 29%, and 78% more secondary care contacts, respectively. Females with normal weight had, on average, 210 primary care contacts and 91 secondary care contacts. Females with overweight, category I obesity, and category II/III obesity had 20%, 34%, and 81% more primary care contacts, and 26%, 16%, and 16% more secondary care contacts, respectively. CONCLUSION: The positive association between BMI and healthcare utilization was reduced, but not offset, when BMI-specific survival was taken into consideration. Our findings underpin previous research and suggest that interventions to offset the increasing prevalence of overweight, and especially obesity, are warranted.

Influenza in workplaces: transmission, workers' adherence to sick leave advice and European sick leave recommendations.

BACKGROUND: Knowledge about influenza transmission in the workplace and whether staying home from work when experiencing influenza-like illness can reduce the spread of influenza is crucial for the design of efficient public health initiatives. AIM: This review synthesizes current literature on sickness presenteeism and influenza transmission in the workplace and provides an overview of sick leave recommendations in Europe for influenza. METHODS: A search was performed on Medline, Embase, PsychINFO, Cinahl, Web of Science, Scopus and SweMed to identify studies related to workplace contacts, -transmission, -interventions and compliance with recommendations to take sick leave. A web-based survey on national recommendations and policies for sick leave during influenza was issued to 31 European countries. RESULTS: Twenty-two articles (9 surveys; 13 modelling articles) were eligible for this review. Results from social mixing studies suggest that 20-25% of weekly contacts are made in the workplace, while modelling studies suggest that on average 16% (range 9-33%) of influenza transmission occurs in the workplace. The effectiveness of interventions to reduce workplace presenteeism is largely unknown. Finally, estimates from studies reporting expected compliance with sick leave recommendations ranged from 71 to 95%. Overall, 18 countries participated in the survey of which nine (50%) had issued recommendations encouraging sick employees to stay at home during the 2009 A(H1N1) pandemic, while only one country had official recommendations for seasonal influenza. CONCLUSIONS: During the 2009 A(H1N1) pandemic, many European countries recommended ill employees to take sick leave. Further research is warranted to quantify the effect of reduced presenteeism during influenza illness.

Evaluating costs and health consequences of sick leave strategies against pandemic and seasonal influenza in Norway using a dynamic model.

OBJECTIVES: To quantify population-level health and economic consequences of sick leave among workers with influenza symptoms. INTERVENTIONS: Compared with current sick leave practice (baseline), we evaluated the health and cost consequences of: (1) increasing the proportion of workers on sick leave from 65% (baseline) to 80% or 90%; (2) shortening the maximum duration from symptom onset to sick leave from 4 days (baseline) to 2 days, 1.5 days, 1 day and 0.5 days; and (3) combinations of 1 and 2. METHODS: A dynamic compartmental influenza model was developed using Norwegian population data and survey data on employee sick leave practices. The sick leave interventions were simulated under 12 different seasonal epidemic and 36 different pandemic influenza scenarios. These scenarios varied in terms of transmissibility, the proportion of symptomatic cases and illness severity (risk of primary care consultations, hospitalisations and deaths). Using probabilistic sensitivity analyses, a net health benefit approach was adopted to assess the cost-effectiveness of the interventions from a societal perspective. RESULTS: Compared with current sick leave practice, sick leave interventions were cost-effective for 31 (65%) of the pandemic scenarios, and 11 (92%) of the seasonal scenarios. Economic benefits from sick leave interventions were greatest for scenarios with low transmissibility, high symptomatic proportions and high illness severity. Overall, the health and economic benefits were greatest for the intervention involving 90% of sick workers taking sick leave within one-half day of symptoms. Depending on the influenza scenario, this intervention resulted in a 44.4%-99.7% reduction in the attack rate. Interventions involving sick leave onset beginning 2 days or later, after the onset of symptoms, resulted in economic losses. CONCLUSIONS: Prompt sick leave onset and a high proportion of sick leave among workers with influenza symptoms may be cost-effective, particularly during influenza epidemics and pandemics with low transmissibility or high morbidity.