Cardiovascular Health in India - a Report Card from Three Urban and Rural Surveys of 22,144 Adults.


Journal

Global heart
ISSN: 2211-8179
Titre abrégé: Glob Heart
Pays: England
ID NLM: 101584391

Informations de publication

Date de publication:
2022
Historique:
received: 08 02 2022
accepted: 12 07 2022
entrez: 2 9 2022
pubmed: 3 9 2022
medline: 9 9 2022
Statut: epublish

Résumé

Markers of ideal cardiovascular health (CVH) predict cardiovascular events. We estimated the prevalence of ideal CVH markers in two levels of cities and villages in India. We did pooled analysis of individual-level data from three cross sectional surveys of adults ≥ 30 years over 2010-14 (CARRS: Centre for cArdiometabolic Risk Reduction in South Asia; UDAY and Solan Surveillance Study) representing metropolitan cities; smaller cities and rural areas in diverse locations of India. We defined ideal CVH using modified American Heart Association recommendations: not smoking, ≥ 5 servings of fruits and vegetables (F&V), high physical activity (PA), body mass index (BMI) <25 Kg/m Of the total 22,144 participants, the prevalence of ideal CVH markers were: not smoking (76.7% [95% CI 76.1, 77.2]), consumed ≥5 F&V (4.2% [3.9, 4.5]), high PA (67.5% [66.8, 68.2]), optimum BMI (59.6% [58.9, 60.3]), ideal BP (34.5% [33.9, 35.2]), FPG (65.8% [65.1, 66.5]) and TC (65.4% [64.7, 66.1]). The mean number of ideal CVH metrics was 3.7(95% CI: 3.7, 3.8). Adjusted prevalence of good, moderate, and poor CVH, varied across settings: metropolitan (3.9%, 41.0%, and 55.1%), smaller cities (7.8%, 49.2%, and 43%), and rural (10.4%, 60.9%, and 28.7%) and across asset tertiles: Low (11.0%, 55.9%, 33.1%), Middle (6.3%, 52.2%, 41.5%), and High (5.0%, 46.4%, 48.7%), respectively. Achievement of ideal CVH varied, with higher prevalence in rural and lower asset tertiles. Multi-sectoral and targeted policy and program actions are needed to improve CVH in diverse contexts in India.

Sections du résumé

Background
Markers of ideal cardiovascular health (CVH) predict cardiovascular events. We estimated the prevalence of ideal CVH markers in two levels of cities and villages in India.
Methods
We did pooled analysis of individual-level data from three cross sectional surveys of adults ≥ 30 years over 2010-14 (CARRS: Centre for cArdiometabolic Risk Reduction in South Asia; UDAY and Solan Surveillance Study) representing metropolitan cities; smaller cities and rural areas in diverse locations of India. We defined ideal CVH using modified American Heart Association recommendations: not smoking, ≥ 5 servings of fruits and vegetables (F&V), high physical activity (PA), body mass index (BMI) <25 Kg/m
Results
Of the total 22,144 participants, the prevalence of ideal CVH markers were: not smoking (76.7% [95% CI 76.1, 77.2]), consumed ≥5 F&V (4.2% [3.9, 4.5]), high PA (67.5% [66.8, 68.2]), optimum BMI (59.6% [58.9, 60.3]), ideal BP (34.5% [33.9, 35.2]), FPG (65.8% [65.1, 66.5]) and TC (65.4% [64.7, 66.1]). The mean number of ideal CVH metrics was 3.7(95% CI: 3.7, 3.8). Adjusted prevalence of good, moderate, and poor CVH, varied across settings: metropolitan (3.9%, 41.0%, and 55.1%), smaller cities (7.8%, 49.2%, and 43%), and rural (10.4%, 60.9%, and 28.7%) and across asset tertiles: Low (11.0%, 55.9%, 33.1%), Middle (6.3%, 52.2%, 41.5%), and High (5.0%, 46.4%, 48.7%), respectively.
Conclusion
Achievement of ideal CVH varied, with higher prevalence in rural and lower asset tertiles. Multi-sectoral and targeted policy and program actions are needed to improve CVH in diverse contexts in India.

Identifiants

pubmed: 36051326
doi: 10.5334/gh.1137
pmc: PMC9354560
doi:

Substances chimiques

Biomarkers 0

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

52

Commentaires et corrections

Type : ErratumIn

Informations de copyright

Copyright: © 2022 The Author(s).

Déclaration de conflit d'intérêts

The authors have no competing interests to declare.

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Auteurs

Roopa Shivashankar (R)

Indian Council of Medical Research (ICMR), New Delhi, IN.
Centre for Chronic Disease Control (CCDC), New Delhi, IN.

Kalpana Singh (K)

Centre for Chronic Disease Control (CCDC), New Delhi, IN.
Hamad Medical Corporation, Doha, QA.

Dimple Kondal (D)

Centre for Chronic Disease Control (CCDC), New Delhi, IN.
Public Health Foundation of India (PHFI), New Delhi, IN.

Ruby Gupta (R)

Centre for Chronic Disease Control (CCDC), New Delhi, IN.
Public Health Foundation of India (PHFI), New Delhi, IN.

Pablo Perel (P)

London School of Hygiene and Tropical Medicine (LSHTM), London, UK.

Deksha Kapoor (D)

All India Institute of Medical Sciences (AIIMS), New Delhi, IN.
Global Academy of Agriculture and Food Systems, University of Edinburgh, Edinburgh, UK.

Devraj Jindal (D)

Centre for Chronic Disease Control (CCDC), New Delhi, IN.

Sailesh Mohan (S)

Centre for Chronic Disease Control (CCDC), New Delhi, IN.
Public Health Foundation of India (PHFI), New Delhi, IN.
Deakin University, Melbourne, AUS.

Rajendra Pradeepa (R)

Madras Diabetes Research Foundation (MDRF), Chennai, IN.

Prashant Jarhyan (P)

Public Health Foundation of India (PHFI), New Delhi, IN.

Nikhil Srinivasapura Venkateshmurthy (N)

Public Health Foundation of India (PHFI), New Delhi, IN.

Nikhil Tandon (N)

All India Institute of Medical Sciences (AIIMS), New Delhi, IN.

Viswanathan Mohan (V)

Madras Diabetes Research Foundation (MDRF), Chennai, IN.

K M Venkat Narayan (KMV)

Rollins School of Public Health & Emory Global Diabetes Research Center, Emory University, Atlanta, US.

Dorairaj Prabhakaran (D)

Centre for Chronic Disease Control (CCDC), New Delhi, IN.
Public Health Foundation of India (PHFI), New Delhi, IN.
Rollins School of Public Health, Emory University, Atlanta, US.

Mohammed K Ali (MK)

Rollins School of Public Health & Department of Family and Preventive Medicine, School of Medicine, Emory University, Atlanta, US.

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