Cargando…
A cross-sectional study of cardiovascular disease risk clustering at different socio-geographic levels in India
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...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7674456/ https://www.ncbi.nlm.nih.gov/pubmed/33208739 http://dx.doi.org/10.1038/s41467-020-19647-3 |
_version_ | 1783611509890351104 |
---|---|
author | Bischops, Anne C. De Neve, Jan-Walter Awasthi, Ashish Vollmer, Sebastian Bärnighausen, Till Geldsetzer, Pascal |
author_facet | Bischops, Anne C. De Neve, Jan-Walter Awasthi, Ashish Vollmer, Sebastian Bärnighausen, Till Geldsetzer, Pascal |
author_sort | Bischops, Anne C. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7674456 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-76744562020-11-24 A cross-sectional study of cardiovascular disease risk clustering at different socio-geographic levels in India Bischops, Anne C. De Neve, Jan-Walter Awasthi, Ashish Vollmer, Sebastian Bärnighausen, Till Geldsetzer, Pascal Nat Commun Article 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. Nature Publishing Group UK 2020-11-18 /pmc/articles/PMC7674456/ /pubmed/33208739 http://dx.doi.org/10.1038/s41467-020-19647-3 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Bischops, Anne C. De Neve, Jan-Walter Awasthi, Ashish Vollmer, Sebastian Bärnighausen, Till Geldsetzer, Pascal A cross-sectional study of cardiovascular disease risk clustering at different socio-geographic levels in India |
title | A cross-sectional study of cardiovascular disease risk clustering at different socio-geographic levels in India |
title_full | A cross-sectional study of cardiovascular disease risk clustering at different socio-geographic levels in India |
title_fullStr | A cross-sectional study of cardiovascular disease risk clustering at different socio-geographic levels in India |
title_full_unstemmed | A cross-sectional study of cardiovascular disease risk clustering at different socio-geographic levels in India |
title_short | A cross-sectional study of cardiovascular disease risk clustering at different socio-geographic levels in India |
title_sort | cross-sectional study of cardiovascular disease risk clustering at different socio-geographic levels in india |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7674456/ https://www.ncbi.nlm.nih.gov/pubmed/33208739 http://dx.doi.org/10.1038/s41467-020-19647-3 |
work_keys_str_mv | AT bischopsannec acrosssectionalstudyofcardiovasculardiseaseriskclusteringatdifferentsociogeographiclevelsinindia AT denevejanwalter acrosssectionalstudyofcardiovasculardiseaseriskclusteringatdifferentsociogeographiclevelsinindia AT awasthiashish acrosssectionalstudyofcardiovasculardiseaseriskclusteringatdifferentsociogeographiclevelsinindia AT vollmersebastian acrosssectionalstudyofcardiovasculardiseaseriskclusteringatdifferentsociogeographiclevelsinindia AT barnighausentill acrosssectionalstudyofcardiovasculardiseaseriskclusteringatdifferentsociogeographiclevelsinindia AT geldsetzerpascal acrosssectionalstudyofcardiovasculardiseaseriskclusteringatdifferentsociogeographiclevelsinindia AT bischopsannec crosssectionalstudyofcardiovasculardiseaseriskclusteringatdifferentsociogeographiclevelsinindia AT denevejanwalter crosssectionalstudyofcardiovasculardiseaseriskclusteringatdifferentsociogeographiclevelsinindia AT awasthiashish crosssectionalstudyofcardiovasculardiseaseriskclusteringatdifferentsociogeographiclevelsinindia AT vollmersebastian crosssectionalstudyofcardiovasculardiseaseriskclusteringatdifferentsociogeographiclevelsinindia AT barnighausentill crosssectionalstudyofcardiovasculardiseaseriskclusteringatdifferentsociogeographiclevelsinindia AT geldsetzerpascal crosssectionalstudyofcardiovasculardiseaseriskclusteringatdifferentsociogeographiclevelsinindia |