A cross-sectional study of cardiovascular disease risk clustering at different socio-geographic levels in India

• Verfasst von: Bischops, Anne Christine [VerfasserIn]
• Verfasst von: De Neve, Jan-Walter [VerfasserIn]
• Verfasst von: Awasthi, Ashish [VerfasserIn]
• Verfasst von: Vollmer, Sebastian [VerfasserIn]
• Verfasst von: Bärnighausen, Till [VerfasserIn]
• Verfasst von: Geldsetzer, Pascal [VerfasserIn]
• Titel: A cross-sectional study of cardiovascular disease risk clustering at different socio-geographic levels in India
• Verf.angabe: Anne C. Bischops, Jan-Walter De Neve, Ashish Awasthi, Sebastian Vollmer, Till Bärnighausen & Pascal Geldsetzer
• E-Jahr: 2020
• Jahr: 18 November 2020
• Umfang: 7 S.
• Fussnoten: Gesehen am 17.12.2020
• Titel Quelle: Enthalten in: Nature Communications
• Ort Quelle: [London] : Nature Publishing Group UK, 2010
• Jahr Quelle: 2020
• Band/Heft Quelle: 11(2020) Artikel-Nummer 5891, 7 Seiten
• ISSN Quelle: 2041-1723
• DOI: doi:10.1038/s41467-020-19647-3
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1743099029
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext

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.