Evidence map›Paper›PMID 36757132›Full record

Observational studyJournal of global health2023

Multimorbidity, social determinants and intersectionality in chronic patients. Results from the EpiChron Cohort.

Aida Moreno-Juste, Antonio Gimeno-Miguel, Beatriz Poblador-Plou, Amaia Calderón-Larrañaga, Mabel Cano Del Pozo, Maria João Forjaz, Alexandra Prados-Torres, Luis A Gimeno-Feliú

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Journal of global health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 2 pooled it
6.7field-weighted citation impact, top 2% of its field
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

23 citing papers in PubMed, 2 syntheses or guidelines pooled it, 31 citations in OpenAlex.

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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

8 authors at 3 institutions in 2 countries.

Aida Moreno-Juste *EpiChron Research Group, Aragon Health Sciences Institute (IACS), IIS Aragón, Miguel Servet University Hospital, Zaragoza, Spain.
Antonio Gimeno-Miguel *EpiChron Research Group, Aragon Health Sciences Institute (IACS), IIS Aragón, Miguel Servet University Hospital, Zaragoza, Spain.
Beatriz Poblador-PlouEpiChron Research Group, Aragon Health Sciences Institute (IACS), IIS Aragón, Miguel Servet University Hospital, Zaragoza, Spain.
Amaia Calderón-LarrañagaNetwork for Research on Chronicity, Primary Care, and Health Promotion (RICAPPS), Research Network on Health Services in Chronic Diseases (REDISSEC), Institute of Health Carlos III (ISCIII), Madrid, Spain.
Mabel Cano Del PozoEpiChron Research Group, Aragon Health Sciences Institute (IACS), IIS Aragón, Miguel Servet University Hospital, Zaragoza, Spain.
Maria João ForjazNetwork for Research on Chronicity, Primary Care, and Health Promotion (RICAPPS), Research Network on Health Services in Chronic Diseases (REDISSEC), Institute of Health Carlos III (ISCIII), Madrid, Spain.
Alexandra Prados-TorresEpiChron Research Group, Aragon Health Sciences Institute (IACS), IIS Aragón, Miguel Servet University Hospital, Zaragoza, Spain.
Luis A Gimeno-FeliúEpiChron Research Group, Aragon Health Sciences Institute (IACS), IIS Aragón, Miguel Servet University Hospital, Zaragoza, Spain.
Red de Investigación en Actividades Preventivas y Promoción de la Salud · ESInstituto de Salud Carlos III · ESServicio Aragonés de Salud · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Multimorbidity is influenced in an interconnected way, both in extent and nature, by the social determinants of health. We aimed at implementing an intersectional approach to analyse the association of multimorbidity with five important axes of social inequality (i.e. gender, age, ethnicity, residence area and socioeconomic class). Methods: We conducted a cross-sectional observational study of all individuals who presented with at least one chronic disease in 2019 (n = 1 086 948) from the EpiChron Cohort (Aragon, Spain). Applying intersectional analysis, the age-adjusted likelihood of multimorbidity was investigated across 36 intersectional strata defined by gender, ethnicity, residence area and socioeconomic class. We calculated odds ratios (OR) 95% confidence interval (CI) using high-income urban non-migrant men as the reference category. The area under the receiver operator characteristics curve (AUC) was calculated to evaluate the discriminatory accuracy of multimorbidity. Results: The prevalence of multimorbidity increased with age, female gender and low income. Young and middle-aged low-income individuals showed rates of multimorbidity equivalent to those of high-income people aged about 20 years older. The intersectional analysis showed that low-income migrant women living in urban areas for >15 years were particularly disadvantaged in terms of multimorbidity risk OR = 3.16 (95% CI = 2.79-3.57). Being a migrant was a protective factor for multimorbidity, and newly arrived migrants had lower multimorbidity rates than those with >15 years of stay in Aragon, and even non-migrants. Living in rural vs. urban areas was slightly protective against multimorbidity. All models had a large discriminatory accuracy (AUC = 0.7884-0.7895); the largest AUC was obtained for the model including all intersectional strata. Conclusions: Our intersectional approach uncovered the large differences in the prevalence of multimorbidity that arise due to the synergies between the different socioeconomic and demographic exposures, beyond their expected additive effects.

Indexed as

Intersectional FrameworkMultimorbidityAgedCross-Sectional StudiesFemaleHumansMaleMiddle AgedSocial Determinants of HealthSocioeconomic Factors

Identifiers

PMID36757132
PMCPMC9893716
OpenAlexW4318995030

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.