Summaryobjectives Living in an urban area influences obesity. However, little is known about whether this relationship is truly independent of, or merely mediated through, the demographic, socio-economic and lifestyle characteristics of urban populations. We aimed to identify and quantify the magnitude of this relationship in a Sri Lankan population.methods Cross-sectional study of adults aged 20-64 years representing the urban (n = 770) and rural (n = 630) populations, in the district of Colombo in 2004. Obesity was measured as a continuous variable using body mass index (BMI). Demographic, socio-economic and lifestyle factors were assessed. Gender-specific multivariable regression models were developed to quantify the independent effect of urban ⁄ rural living and other variables on increased BMI. conclusions Urban living is associated with obesity independently of most other demographic, socioeconomic and lifestyle characteristics of the population. Targeting urban populations may be useful for consideration when developing strategies to reduce the prevalence of obesity.

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Background: The significance of anthropometric measures of obesity that determine coronary-heart-disease (CHD) risk varies among populations. This study compares waist circumference (WC) and body mass index (BMI) in identifying the ''obesity-related-CHD risk'' among Sri Lankan adults. Methods: A population-based cross-section of 515 adults aged 20-64 years, residing in the district of Colombo in 2004 was selected by a multi-stage, stratified, probability sampling method. WC, height and weight were measured. Demographic, socioeconomic and lifestyle characteristics, smoking and obesity-related-CHD risk factors (hypertension, dyslipidaemia, diabetes) were assessed by questionnaires, physical measurements and biochemical assessments. ''Obesity-related CHD risk'' was defined by the presence of P1 obesity-related-CHD risk factors. Results: Compared to BMI, WC was a stronger correlate of systolic and diastolic blood pressure, triglycerides among both sexes and of plasma glucose among males. It was also an independent predictor of obesity-related-CHD risk in both males (beta co-efficient = 0.046; standard error = 0.013) and females (0.024; 0.012) in contrast to BMI, which was significant only among males (0.138; 0.037) in the logistic regression models adjusted for confounders. At the same level of obesity-related-CHD risk

Cardiovascular diseases (CVDs) are the leading cause of mortality in South Asia. Although well-recognized as a major risk factor, dyslipidemia in such populations is not well-reviewed. To review the trends in dyslipidemia, phenotypes, underlying causes, treatment modalities, and management gaps in Sri Lanka. A narrative review was undertaken on published literature on dyslipidemia in Sri Lanka from 2000 to 2020, extracted using PubMed, Google Scholar, and locally published literature. Out of the 33 documents reviewed, only a limited number was available on large-scale population-based studies. High prevalence of metabolic syndrome along with moderately high low-density lipoprotein-cholesterol, low high-density lipoprotein-cholesterol, high triglycerides, and high ApoB and Lp(a) concentrations was seen. Familial hypercholesterolemia was an understudied area with a need for a national screening program. With dyslipidemia guidelines limited to the management of special disease groups, there is a chasm between guidelines and practice at present in Sri Lanka. Unlike in primary prevention, prescribing high-dose statins in secondary prevention of CVD has been satisfactory. Treatment gaps are identified, with room for improvements in lipid screening and achieving lipid goals. Considering the substantial burden identified, education of physicians, optimizing lipid testing, and aggressive treatment of lipids are key initiatives toward optimizing management of dyslipidemia.