Evidence map›Paper›PMID 36000437›Full record

ArticleJournal of the American Heart Association2022

Inequalities by Income in the Prevalence of Cardiovascular Disease and Its Risk Factors in the Adult Population of Catalonia.

Pricila H Mullachery, Emili Vela, Montse Cleries, Josep Comin-Colet, Khurram Nasir, Ana V Diez Roux, Miguel Cainzos-Achirica, Josepa Mauri, Usama Bilal

Abstract read
In one paragraph

Article in Journal of the American Heart Association, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  8. Disparities in the access to atrial fibrillation ablation in Denmark: who gets ablated, who neglected?Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2024
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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

9 authors.

Pricila H MullacheryUrban Health Collaborative Drexel Dornsife School of Public Health Philadelphia PA.ORCID 0000-0003-4758-3875
Emili VelaHealthcare Information and Knowledge Unit Health Department of the Government of Catalonia Spain.ORCID 0000-0002-8736-5365
Montse CleriesHealthcare Information and Knowledge Unit Health Department of the Government of Catalonia Spain.
Josep Comin-ColetPla Director de Malalties de l'Aparell Circulatori, Health Department of the Government of Catalonia Spain.ORCID 0000-0001-8780-720X
Khurram NasirDivision of Cardiovascular Prevention and Wellness, Department of Cardiology Houston Methodist DeBakey Heart & Vascular Center Houston TX.ORCID 0000-0001-5376-2269
Ana V Diez RouxUrban Health Collaborative Drexel Dornsife School of Public Health Philadelphia PA.
Miguel Cainzos-AchiricaDivision of Cardiovascular Prevention and Wellness, Department of Cardiology Houston Methodist DeBakey Heart & Vascular Center Houston TX.ORCID 0000-0002-8073-2337
Josepa MauriPla Director de Malalties de l'Aparell Circulatori, Health Department of the Government of Catalonia Spain.ORCID 0000-0002-9638-7558
Usama BilalUrban Health Collaborative Drexel Dornsife School of Public Health Philadelphia PA.ORCID 0000-0002-9868-7773

Funding

The Health Consequences of Urban ScalingDP5OD026429 · OD · DREXEL UNIVERSITY · PI BILAL, USAMA · 2018 to 2022
$2.7M
NIH HHS DP5 OD026429
6 · The paper itself

Abstract

Background Understanding the magnitude of cardiovascular disease (CVD) inequalities is the first step toward addressing them. The linkage of socioeconomic and clinical data in universal health care settings provides critical information to characterize CVD inequalities. Methods and Results We employed a prospective cohort design using electronic health records data from all residents of Catalonia aged 18+ between January and December of 2019 (N=6 332 228). We calculated age-adjusted sex-specific prevalence of 5 CVD risk factors (diabetes, hypertension, hyperlipidemia, obesity, and smoking), and 4 CVDs (coronary heart disease, cerebrovascular disease, atrial fibrillation, and heart failure). We categorized income into high, moderate, low, and very low according to individual income (tied to prescription copayments) and receipt of welfare support. We found large inequalities in CVD and CVD risk factors among men and women. CVD risk factors with the largest inequalities were diabetes, smoking, and obesity, with prevalence rates 2- or 3-fold higher for those with very low (versus high) income. CVDs with the largest inequalities were cerebrovascular disease and heart failure, with prevalence rates 2 to 4 times higher for men and women with very low (versus high) income. Inequalities varied by age, peaking at midlife (30-50 years) for most diseases, while decreasing gradually with age for smoking. Conclusions We found wide and heterogeneous inequalities by income in 5 CVD risk factors and 4 CVD. Our findings in a region with a high-quality public health care system and universal coverage stress that strong equity-promoting policies are necessary to reduce disparities in CVD.

Indexed as

Cardiovascular DiseasesDiabetes MellitusHeart FailureAdultFemaleHumansIncomeMaleMiddle AgedObesityPrevalenceProspective StudiesRisk FactorsSocioeconomic FactorsSpaincardiovascular diseasehealth disparitieshealth equityincomesocioeconomic status

Identifiers

PMID36000437
PMCPMC9496415

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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.