Your privacy, your choice

We use essential cookies to make sure the site can function. We also use optional cookies for advertising, personalisation of content, usage analysis, and social media.

By accepting optional cookies, you consent to the processing of your personal data - including transfers to third parties. Some third parties are outside of the European Economic Area, with varying standards of data protection.

See our privacy policy for more information on the use of your personal data.

for further information and to change your choices.

Skip to main content
Fig. 3 | Health Economics Review

Fig. 3

From: The healthcare costs of increased body mass index–evidence from The Trøndelag Health Study

Fig. 3

Effect and 95% confidence intervals of BMI on healthcare costs using different analytical approaches, for females, with adjustment for age (top panel), and fully-adjusted models (bottom panel). In the fully adjusted analyses the OLS, GLM, 2PM, lagged IV-analyses, and the offspring IV-analyses, estimates were adjusted for age, education, smoking status, marital status, resident in rural or urban area, income and country of birth. In the offspring IV-analyses we also adjusted for offspring age and sex, and in the GRS based IV-analyses we only adjusted for age (since a prerequisite for these models is that there is no need for further adjustment because our genes are randomly assigned at conception, and therefore assumed to be uncorrelated with confounding factors)

Back to article page