ArticleNature communications2020
A cross-sectional study of cardiovascular disease risk clustering at different socio-geographic levels in India.
Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Cardiovascular Diseases and Metabolic Medications in the Lebanese Population: A Post Hoc Analysis from a Nationwide Cross-Sectional Study.Pharmacy (Basel, Switzerland) · 2024Article
- Associations of blood pressure in the third trimester and risk of venous thromboembolism postpartum.MedComm · 2024Article
- Odisha tribal family health survey: methods, tools, and protocols for a comprehensive health assessment survey.Frontiers in public health · 2023Article
- Article
- On willingness to pay for Covid-19 vaccines: a case study from India.Human vaccines & immunotherapeutics · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Despite its importance for the targeting of interventions, little is known about the degree to which cardiovascular disease (CVD) risk factors cluster within different socio-geographic levels in South Asia. Using two jointly nationally representative household surveys, which sampled 1,082,100 adults across India, we compute the intra-cluster correlation coefficients (ICCs) of five major CVD risk factors (raised blood glucose, raised blood pressure, smoking, overweight, and obesity) at the household, community, district, and state level. Here we show that except for smoking, the level of clustering is generally highest for households, followed by communities, districts, and then states. On average, more economically developed districts have a higher household ICC in rural areas. These findings provide critical information for sample size calculations of cluster-randomized trials and household surveys, and inform the targeting of policies and prevention programming aimed at reducing CVD in India.
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