PT - JOURNAL ARTICLE AU - Ana Luiza G Soares AU - Louis Banda AU - Alemayehu Amberbir AU - Shabbar Jaffar AU - Crispin Musicha AU - Alison Price AU - Moffat J Nyirenda AU - Debbie A Lawlor AU - Amelia Crampin TI - Sex and area differences in the association between adiposity and lipid profile in Malawi AID - 10.1136/bmjgh-2019-001542 DP - 2019 Sep 01 TA - BMJ Global Health PG - e001542 VI - 4 IP - 5 4099 - http://gh.bmj.com/content/4/5/e001542.short 4100 - http://gh.bmj.com/content/4/5/e001542.full SO - BMJ Global Health2019 Sep 01; 4 AB - Background Evidence from high-income countries shows that higher adiposity results in an adverse lipid profile, but it is unclear whether this association is similar in Sub-Saharan African (SSA) populations. This study aimed to assess the association between total and central adiposity measures and lipid profile in Malawi, exploring differences by sex and area of residence (rural/urban).Methods In this cross-sectional study, data from 12 096 rural and 12 847 urban Malawian residents were used. The associations of body mass index (BMI) and waist to hip ratio (WHR) with fasting lipids (total cholesterol (TC), low-density lipoprotein-cholesterol (LDL-C), high-density lipoprotein-cholesterol (HDL-C) and triglycerides (TG)) were assessed by area and sex.Results After adjusting for potential confounders, higher BMI and WHR were linearly associated with increased TC, LDL-C and TG and reduced HDL-C. BMI was more strongly related to fasting lipids than was WHR. The associations of adiposity with adverse lipid profile were stronger in rural compared with urban residents. For instance, one SD increase in BMI was associated with 0.23 mmol/L (95% CI 0.19 to 0.26) increase in TC in rural women and 0.13 mmol/L (95% CI 0.11 to 0.15) in urban women. Sex differences in the associations between adiposity and lipids were less evident.Conclusions The consistent associations observed of higher adiposity with adverse lipid profiles in men and women living in rural and urban areas of Malawi highlight the emerging adverse cardio-metabolic epidemic in this poor population. Our findings underline the potential utility of BMI in estimating cardiovascular risk and highlight the need for greater investment to understand the long-term health outcomes of obesity and adverse lipid profiles and the extent to which lifestyle changes and treatments effectively prevent and modify adverse cardio-metabolic outcomes.