Evidence map›Paper›PMID 36744377›Full record

ArticleChronic illness2023

Morbidity and utilisation of healthcare services among people with cardiometabolic disease in three diverse regions of rural India.

Sojib Bin Zaman, Roger G Evans, Clara K Chow, Rohina Joshi, Kavumpurathu R Thankappan, Brian Oldenburg, Ajay S Mahal, Kartik Kalyanram, Kamakshi Kartik, Michaela A Riddell and 6 more

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In one paragraph

Article in Chronic illness, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Sojib Bin ZamanDepartment of Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia.ORCID 0000-0002-3043-7954
Roger G EvansCardiovascular Disease Program, Biomedicine Discovery Institute and Department of Physiology, Monash University, Melbourne, Australia.ORCID 0000-0002-9241-0757
Clara K ChowGeorge Institute for Global Health, University of New South Wales, Sydney, Australia.
Rohina JoshiGeorge Institute for Global Health, University of New South Wales, Sydney, Australia.
Kavumpurathu R ThankappanPublic Health and Community Medicine, Central University of Kerala, Kasaragod, India.ORCID 0000-0002-4536-2684
Brian OldenburgNon-Communicable Diseases and Implementation Science, Baker Heart and Diabetes Institute, Melbourne, Australia.
Ajay S MahalNossal Institute for Global Health, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.
Kartik KalyanramRishi Valley Rural Health Centre, Chittoor District, India.
Kamakshi KartikRishi Valley Rural Health Centre, Chittoor District, India.
Michaela A RiddellDepartment of Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia.
Oduru SureshDepartment of Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia.
Nihal ThomasDepartment of Endocrinology, Diabetes & Metabolism, Christian Medical College, Vellore, India.
Gomathyamma K MiniGlobal Institute of Public Health, Ananthapuri Hospitals and Research Institute, Trivandrum, India.ORCID 0000-0003-2775-629X
Pallab K MaulikGeorge Institute for Global Health, University of New South Wales, Sydney, Australia.
Velandai K SrikanthDepartment of Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia.
Amanda G ThriftDepartment of Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia.ORCID 0000-0001-8533-4170

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo assess the prevalence and determinants of cardiometabolic disease (CMD), and the factors associated with healthcare utilisation, among people with CMD.

methodsUsing a cross-sectional design, 11,657 participants were recruited from randomly selected villages in 3 regions located in Kerala and Andhra Pradesh from 2014 to 2016. Multivariable logistic regression was used to identify factors independently associated with CMD and healthcare utilisation (public or private).

resultsThirty-four per cent (n = 3629) of participants reported having ≥1 CMD, including hypertension (21.6%), diabetes (11.6%), heart disease (5.0%) or chronic kidney disease (CKD) (1.6%). The prevalence of CMD was progressively greater in regions of greater socio-economic position (SEP), ranging from 19.1% to 40.9%. Among those with CMD 41% had sought any medical advice in the last month, with only 19% utilising public health facilities. Among people with CMD, those with health insurance utilised more healthcare (age-gender adjusted odds ratio (AOR) (95% confidence interval (CI)): 1.31 (1.13, 1.51)) as did those who reported accessing private rather than public health services (1.43 (1.23, 1.66)). DISCUSSION: The prevalence of CMD is high in these regions of rural India and is positively associated with indices of SEP. The utilisation of outpatient health services, particularly public services, among those with CMD is low.

Indexed as

Cardiovascular DiseasesHealth ServicesCross-Sectional StudiesHumansPatient Acceptance of Health CarePrevalenceCardiometabolic diseaseshealthcare disparitieshealth insuranceIndiaprivate facilities

Identifiers

PMID36744377
PMCPMC10655594

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.