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Assessing cardiovascular disease risk factor screening inequalities in India using Lot Quality Assurance Sampling

BACKGROUND: Cardiovascular diseases (CVDs) are the leading cause of mortality in India. India has rolled out Comprehensive Primary Health Care (CPHC) reforms including population based screening for hypertension and diabetes, facilitated by frontline health workers. Our study assessed blood pressure...

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Autores principales: Nambiar, Devaki, Bhaumik, Soumyadeep, Pal, Anita, Ved, Rajani
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7687829/
https://www.ncbi.nlm.nih.gov/pubmed/33238995
http://dx.doi.org/10.1186/s12913-020-05914-y
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author Nambiar, Devaki
Bhaumik, Soumyadeep
Pal, Anita
Ved, Rajani
author_facet Nambiar, Devaki
Bhaumik, Soumyadeep
Pal, Anita
Ved, Rajani
author_sort Nambiar, Devaki
collection PubMed
description BACKGROUND: Cardiovascular diseases (CVDs) are the leading cause of mortality in India. India has rolled out Comprehensive Primary Health Care (CPHC) reforms including population based screening for hypertension and diabetes, facilitated by frontline health workers. Our study assessed blood pressure and blood sugar coverage achieved by frontline workers using Lot Quality Assurance Sampling (LQAS). METHODS: LQAS Supervision Areas were defined as catchments covered by frontline workers in primary health centres in two districts each of Uttar Pradesh and Delhi. In each Area, 19 households for each of four sampling universes (males, females, Above Poverty Line (APL) and Below Poverty Line (BPL)) were visited using probability proportional to size sampling. Following written informed consent procedures, a short questionnaire was administered to individuals aged 30 or older using tablets related to screening for diabetes and hypertension. Using the LQAS hand tally method, coverage across Supervision Areas was determined. RESULTS: A sample of 2052 individuals was surveyed, median ages ranging from 42 to 45 years. Caste affiliation, education levels, and occupation varied by location; the sample was largely married and Hindu. Awareness of and interaction with frontline health workers was reported in Uttar Pradesh and mixed in Delhi. Greater coverage of CVD risk factor screening (especially blood pressure) was seen among females, as compared to males. No clear pattern of inequality was seen by poverty status; some SAs did not have adequate BPL samples. Overall, blood pressure and blood sugar screening coverage by frontline health workers fell short of targeted coverage levels at the aggregate level, but in all sites, at least one area was crossing this threshold level. CONCLUSION: CVD screening coverage levels at this early stage are low. More emphasis may be needed on reaching males. Sex and poverty related inequalities must be addressed by more closely studying the local context and models of service delivery where the threshold of screening is being met. LQAS is a pragmatic method for measuring program inequalities, in resource-constrained settings, although possibly not for spatially segregated population sub-groups. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-020-05914-y.
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spelling pubmed-76878292020-11-30 Assessing cardiovascular disease risk factor screening inequalities in India using Lot Quality Assurance Sampling Nambiar, Devaki Bhaumik, Soumyadeep Pal, Anita Ved, Rajani BMC Health Serv Res Research Article BACKGROUND: Cardiovascular diseases (CVDs) are the leading cause of mortality in India. India has rolled out Comprehensive Primary Health Care (CPHC) reforms including population based screening for hypertension and diabetes, facilitated by frontline health workers. Our study assessed blood pressure and blood sugar coverage achieved by frontline workers using Lot Quality Assurance Sampling (LQAS). METHODS: LQAS Supervision Areas were defined as catchments covered by frontline workers in primary health centres in two districts each of Uttar Pradesh and Delhi. In each Area, 19 households for each of four sampling universes (males, females, Above Poverty Line (APL) and Below Poverty Line (BPL)) were visited using probability proportional to size sampling. Following written informed consent procedures, a short questionnaire was administered to individuals aged 30 or older using tablets related to screening for diabetes and hypertension. Using the LQAS hand tally method, coverage across Supervision Areas was determined. RESULTS: A sample of 2052 individuals was surveyed, median ages ranging from 42 to 45 years. Caste affiliation, education levels, and occupation varied by location; the sample was largely married and Hindu. Awareness of and interaction with frontline health workers was reported in Uttar Pradesh and mixed in Delhi. Greater coverage of CVD risk factor screening (especially blood pressure) was seen among females, as compared to males. No clear pattern of inequality was seen by poverty status; some SAs did not have adequate BPL samples. Overall, blood pressure and blood sugar screening coverage by frontline health workers fell short of targeted coverage levels at the aggregate level, but in all sites, at least one area was crossing this threshold level. CONCLUSION: CVD screening coverage levels at this early stage are low. More emphasis may be needed on reaching males. Sex and poverty related inequalities must be addressed by more closely studying the local context and models of service delivery where the threshold of screening is being met. LQAS is a pragmatic method for measuring program inequalities, in resource-constrained settings, although possibly not for spatially segregated population sub-groups. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-020-05914-y. BioMed Central 2020-11-25 /pmc/articles/PMC7687829/ /pubmed/33238995 http://dx.doi.org/10.1186/s12913-020-05914-y Text en © The Author(s) 2020 Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Nambiar, Devaki
Bhaumik, Soumyadeep
Pal, Anita
Ved, Rajani
Assessing cardiovascular disease risk factor screening inequalities in India using Lot Quality Assurance Sampling
title Assessing cardiovascular disease risk factor screening inequalities in India using Lot Quality Assurance Sampling
title_full Assessing cardiovascular disease risk factor screening inequalities in India using Lot Quality Assurance Sampling
title_fullStr Assessing cardiovascular disease risk factor screening inequalities in India using Lot Quality Assurance Sampling
title_full_unstemmed Assessing cardiovascular disease risk factor screening inequalities in India using Lot Quality Assurance Sampling
title_short Assessing cardiovascular disease risk factor screening inequalities in India using Lot Quality Assurance Sampling
title_sort assessing cardiovascular disease risk factor screening inequalities in india using lot quality assurance sampling
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7687829/
https://www.ncbi.nlm.nih.gov/pubmed/33238995
http://dx.doi.org/10.1186/s12913-020-05914-y
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