A comparison of the associations between adiposity and lipids in Malawi and the United Kingdom

Background The prevalence of excess adiposity, as measured by elevated body mass index (BMI) and waist-hip ratio (WHR), is increasing in sub-Saharan African (SSA) populations. This could add a considerable burden of cardiovascular and metabolic diseases for which these populations are currently ill-prepared. Evidence from white, European origin populations shows that higher adiposity leads to an adverse lipid profile; whether these associations are similar in all SSA populations requires further exploration. This study compared the association of BMI and WHR with lipid profile in urban Malawi with a contemporary cohort with contrasting socioeconomic, demographic, and ethnic characteristics in the United Kingdom (UK). Methods We used data from 1248 adolescents (mean 18.7 years) and 2277 Malawian adults (mean 49.8 years), all urban-dwelling, and from 3201 adolescents (mean 17.8 years) and 6323 adults (mean 49.7 years) resident in the UK. Adiposity measures and fasting lipids were assessed in both settings, and the associations of BMI and WHR with total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglycerides (TG) were assessed by sex and age groups in both studies. Results Malawian female adults were more adipose and had more adverse lipid profiles than their UK counterparts. In contrast, Malawian adolescent and adult males were leaner and had more favourable lipid profiles than in the UK. Higher BMI and WHR were associated with increased TC, LDL-C and TG and reduced HDL-C in both settings. The magnitude of the associations of BMI and WHR with lipids was mostly similar or slightly weaker in the Malawian compared with the UK cohort in both adolescents and adults. One exception was the stronger association between increasing adiposity and elevated TC and LDL-C in Malawian compared to UK men. Conclusions Malawian adult women have greater adiposity and more adverse lipid profiles compared with their UK counterparts. Similar associations of adiposity with adverse lipid profiles were observed for Malawian and UK adults in most age and sex groups studied. Sustained efforts are urgently needed to address the excess adiposity and adverse lipid profiles in Malawi to mitigate a future epidemic of cardio-metabolic disease among the poorest populations.

activities achieving at least 3000 MET-minutes/week. Use of regular lipid-lowering medication was investigated among those who reported medical diagnosis of raised cholesterol, and it was then recategorised into no raised cholesterol, raised cholesterol not taking medication, and raised cholesterol taking medication. HIV status was also investigated (positive/negative).
In UK adolescents, family socioeconomic data was assessed from questionnaires completed by the mothers during pregnancy and in the first months after delivery. Family income was measured at 33 and 47 months after delivery; a mean family income was calculated, and quintiles were generated. Maternal education was assessed at 32 weeks of gestation in 5 categories (CSE -Certificate of secondary education; Vocational degree; O level ordinary level; A leveladvanced level; and University degree). To note, O level typically represents 11 years of study and marks the end of secondary education; A level is a preuniversity qualification requiring an additional 2 years of study and leading to a total of 13 years. Ethnicity was assessed at age 12 years in 5 categories (White, Mixed colour, Asian, Black and Other), and it was recategorised into White and Other because the vast majority (95%) were White. Smoking status and alcohol intake were assessed at the same time as adiposity and lipid measurements. Smoking status was classified into non-smoker, former smoker, and smoker (smoked in the last 30 days). Frequency of alcohol intake was assessed into never, monthly or less, 2-4 times a month, 2-3 times a week, and 4 or more times a week.
Use of lipid-lowering medication (yes/no) was investigated among those who reported using any regular medication.
In UK adults, family socioeconomic information was the same as that used for the offspring (see above). Ethnicity was self-reported by the woman and her partner during pregnancy in 7 categories (White, Black Caribbean, Black African, Black Other, Indian, Chinese and other ethnicity); it was recategorised into White/British and Others as 98% were White. All the other covariates were assessed at the same time as assessment of anthropometric and lipids. Marital status was assessed in 9 categories (never married, widowed, divorced, separated, married only once, married for second time, married for third time or more, living as married, and civil partnership), and recategorised into never married, widowed, divorced/separated and married. Parity (number of pregnancies the woman had) was categorised as 1, 2, 3 and 4 or more. Smoking status including cigarette or other smoked tobacco use was categorised into never, former or current smoker. The frequency of alcohol intake was categorised as never, monthly or less, 2-4 times a month, 2-3 times a week, and 4 or more times a week.

Statistical Analysis for dyslipidaemia analysis
Age-standardised prevalence of each dyslipidaemia was described in adolescents and adults in Malawi and the UK, stratified by sex.
Multiple logistic regression analyses were used to examine the association of both BMI and WHR (in standard deviations) with each dyslipidaemia, adjusted initially for age and then for other potential confounders. The same confounders used in the linear regression analyses were used for the logistic regressions. However, for Malawian adolescents, HIV status was removed from the model due to high collinearity, and for ALSPAC adolescents, ethnicity was removed for the same reason.
Differences between the age-standardised prevalence of each dyslipidaemia and the adjusted associations of anthropometric measurements with dyslipidaemias between Malawi and the UK were compared by examining the point estimates and their 95% confidence intervals.