ArticleBMJ open2020
Patterns and predictors of mortality in a semi-urban population-based cohort in Sri Lanka: findings from the Ragama Health Study.
Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 6 citations in OpenAlex.
- Trial
- Chronic Kidney Disease in Urban, Adult Sri Lankans: A Cohort Follow-Up Study.International journal of nephrology · 2026Article
- Risk prediction of cardiovascular disease in the Asia-Pacific region: the SCORE2 Asia-Pacific model.European heart journal · 2025Article
- Recalibration of the Framingham coronary heart disease risk score for a selected Sri Lankan population and its association with carotid artery intima-media thickness: A cross-sectional study.JRSM cardiovascular diseaseArticle
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Authors and funding
13 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo describe patterns and predictors of mortality in a semi-urban population in Sri Lanka.
designA prospective population-based cohort study.
settingRagama Medical Officer of Health area in the Gampaha district, Sri Lanka.
participantsAdults between 35 and 64 years of age were recruited using an age stratified random sampling technique in 2007. MEASURES: At baseline, we recorded socio-demographic, lifestyle, anthropometric, biochemical and clinical data of the participants. Over 10 years, we obtained the cause and date of death from the death registration documents of deceased participants. We determined the survival probability of the cohort over 10 years and estimated Hazard ratios (HRs) for all-cause mortality (ACM), cardiovascular mortality (CVM) and cancer-related mortality (CRM) using Cox's proportional hazards model. We also estimated the survival probabilities for men and women in each 10-year age group and standardised mortality ratio relative to the source population.
resultsThere were 169 deaths over 10 years with standardised mortality rates of 5.3 and 2.4 per 1000 years of follow-up for men and women, respectively. Independent predictors of: ACM were older age, lower income, smoking and diabetes mellitus while gender, education, occupation, harmful alcohol use, waist circumference and hypertension were not; CVM were older age, lower income, smoking, diabetes and hypertension while gender and harmful alcohol use were not; CRM was older age while gender, smoking and diabetes were not. Those engaged in clerical and technical occupations or unemployed had a lower risk of CRM as compared with those engaged in elementary occupations.
conclusionsOlder age, lower income, smoking, diabetes and hypertension strongly predict mortality in this cohort. Addressing the identified modifiable predictors through behavioural modification will improve longevity in similar populations.
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