The healthcare costs of increased body mass index-evidence from The Trøndelag Health Study.

BACKGROUND: Earlier studies have estimated the impact of increased body mass index (BMI) on healthcare costs. Various methods have been used to avoid potential biases and inconsistencies. Each of these methods measure different local effects and have different strengths and weaknesses. METHODS: In the current study we estimate the impact of increased BMI on healthcare costs using nine common methods from the literature: multivariable regression analyses (ordinary least squares, generalized linear models, and two-part models), and instrumental variable models (using previously measured BMI, offspring BMI, and three different weighted genetic risk scores as instruments for BMI). We stratified by sex, investigated the implications of confounder adjustment, and modelled both linear and non-linear associations. RESULTS: There was a positive effect of increased BMI in both males and females in each approach. The cost of elevated BMI was higher in models that, to a greater extent, account for endogenous relations. CONCLUSION: The study provides solid evidence that there is an association between BMI and healthcare costs, and demonstrates the importance of triangulation.

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.

Alcohol-attributed disease burden in four Nordic countries: a comparison using the Global Burden of Disease, Injuries and Risk Factors 2013 study.

AIMS: (1) To compare alcohol-attributed disease burden in four Nordic countries 1990-2013, by overall disability-adjusted life years (DALYs) and separated by premature mortality [years of life lost (YLL)] and health loss to non-fatal conditions [years lived with disability (YLD)]; (2) to examine whether changes in alcohol consumption informs alcohol-attributed disease burden; and (3) to compare the distribution of disease burden separated by causes. DESIGN: A comparative risk assessment approach. SETTING: Sweden, Norway, Denmark and Finland. PARTICIPANTS: Male and female populations of each country. MEASUREMENTS: Age-standardized DALYs, YLLs and YLDs per 100 000 with 95% uncertainty intervals (UIs). FINDINGS: In Finland, with the highest burden over the study period, overall alcohol-attributed DALYs were 1616 per 100 000 in 2013, while in Norway, with the lowest burden, corresponding estimates were 634. DALYs in Denmark were 1246 and in Sweden 788. In Denmark and Finland, changes in consumption generally corresponded to changes in disease burden, but not to the same extent in Sweden and Norway. All countries had a similar disease pattern and the majority of DALYs were due to YLLs (62-76%), mainly from alcohol use disorder, cirrhosis, transport injuries, self-harm and violence. YLDs from alcohol use disorder accounted for 41% and 49% of DALYs in Denmark and Finland compared to 63 and 64% in Norway and Sweden 2013, respectively. CONCLUSIONS: Finland and Denmark has a higher alcohol-attributed disease burden than Sweden and Norway in the period 1990-2013. Changes in consumption levels in general corresponded to changes in harm in Finland and Denmark, but not in Sweden and Norway for some years. All countries followed a similar pattern. The majority of disability-adjusted life years were due to premature mortality. Alcohol use disorder by non-fatal conditions accounted for a higher proportion of disability-adjusted life years in Norway and Sweden, compared with Finland and Denmark.

Socioeconomic variation in the impact of obesity on health-related quality of life.

There is evidence that obesity has a negative impact on health-related quality of life (HRQL). However, little attention has been paid to variations in this impact between population groups. This study investigates the relationship between HRQL and obesity, and whether or not this relationship varies by socioeconomic status (SES). Data were taken from four rounds of the Health Survey for England (2003-2006; n = 33,716) for persons aged 16 and above. Banded total annual household income is regressed against a comprehensive set of SES indicators using interval regression. We use the equivalised predicted values from this model, categorised into quartiles, as our measure of SES. We regress EQ-5D scores against interactions between body mass index and SES categories. Obesity is negatively correlated with HRQL. The negative impact of obesity is greater in people from lower SES groups. Overweight and obese people in lower SES groups have lower HRQL than those of normal weight in the same SES group, and have lower HRQL than those in higher SES groups of the same weight. This trend is also observed after controlling for individual and household characteristics, although the statistical significance and magnitude of effects is diminished.