Exploring the relationship between urbanicity and risk factors for noncommunicable disease

Abstract

Abstract : Objectives: To create an 'urbanicity' scale adapted from a previously validated urbanicity scale and examine associations between urbanisation measured on this scale and chronic disease risk in Sri Lanka. Methods: Urbanisation was quantified using Allender et al., (2010) tool comprising a composite score based on seven components. This tool was administered to all 100 clusters covered by the Sri Lanka Diabetes and Cardiovascular study. Seven out of nine provinces were selected (North and East provinces excluded). Two stage random cluster sampling was used to select a sample of 5000 from 100 clusters. The area level score for each cluster was assigned to the 4485 individual participants. Results: The mean urbanicity score was 22.08 (SD= 8.4) on a range from 11 to 46. Clusters were allocated into 3 groups according to the urbanicity score low, middle and high. For dichotomous outcomes a significant difference between the levels of urbanisation and disease risk was observed in body mass index (BMI) of more than 23 kgm-2(OR1.3, p<0.05), diabetes mellitus (OR 1.4, p<0.05), physical inactivity (OR 1.7, p<0.05) and presence of ECG changes (OR 1.5, p<0.05).A difference between the levels of urbanisation and disease risk was observed for females in current drinking (OR 3.5, p<0.05), BMI > 23 kgm-2(OR 1.5, p<0.05), diabetes mellitus (OR1.4 p<0.05)and physical inactivity (OR 1.5, p<0.05). Conclusions: An increase in prevalence of several risk factors for noncommunicable diseases is associated with an increased level of urbanisation. Identifying possible strategies for intervention could benefit from an objective measure of urbanisation.