Evidence map›Paper›PMID 32489806›Full record

ArticleGlobal heart2020

Determinants of Mortality from Cardiovascular Disease in the Slums of Nairobi, Kenya.

Frederick M Wekesah, Kerstin Klipstein-Grobusch, Diederick E Grobbee, Damazo Kadengye, Gershim Asiki, Catherine K Kyobutungi

Abstract readMulticenter Study
In one paragraph

Article in Global heart, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–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

11 citing papers in PubMed.

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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

6 authors.

Frederick M WekesahAfrican Population and Health Research Center, 2 Floor APHRC Campus, Manga Close, Off Kirawa Road, Kitisuru, Nairobi, KE.
Kerstin Klipstein-GrobuschJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, NL.
Diederick E GrobbeeJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, NL.
Damazo KadengyeAfrican Population and Health Research Center, 2 Floor APHRC Campus, Manga Close, Off Kirawa Road, Kitisuru, Nairobi, KE.
Gershim AsikiAfrican Population and Health Research Center, 2 Floor APHRC Campus, Manga Close, Off Kirawa Road, Kitisuru, Nairobi, KE.
Catherine K KyobutungiAfrican Population and Health Research Center, 2 Floor APHRC Campus, Manga Close, Off Kirawa Road, Kitisuru, Nairobi, KE.

Funding

Wellcome TrustWellcome Trust WT092775MA
6 · The paper itself

Abstract

Background: Cardiovascular diseases (CVD) comprise eighty percent of non-communicable disease (NCD) burden in low- and middle-income countries and are increasingly impacting the poor inequitably. Traditional and socioeconomic factors were analyzed for their association with CVD mortality over 10 years of baseline assessment in an urban slum of Nairobi, Kenya. Methods and results: A 2008 survey on CVD risk factors was linked to cause of death data collected between 2008 and 2018. Cox proportional hazards on relative risk of dying from CVD over a 10-year period following the assessment of cardiovascular disease risk factors were computed. Population attributable fraction (PAF) of incident CVD death was estimated for key risk factors. In total, 4,290 individuals, 44.0% female, mean age 48.4 years in 2008 were included in the analysis. Diabetes and hypertension were 7.8% and 24.9% respectively in 2008. Of 385 deaths recorded between 2008 and 2018, 101 (26%) were caused by CVD. Age (hazard ratio (HR) 1.11; 95% confidence interval (CI) 1.03-1.20, p = 0.005) and hypertension (HR 2.19, 95% CI 1.44-3.33, p <0.001) were positively associated with CVD mortality. Primary school education and higher (HR 0.57, 95% CI 0.33-0.99, p = 0.044) and formal employment (HR 0.22, 95% CI 0.06-0.75, p = 0.015) were negatively associated with CVD mortality. Controlling hypertension would avert 27% (95% CI 9%-42%, p = 0.004) CVD deaths, while if every member of the community attained primary school education and unemployment was eradicated, 39% (95% CI 5% - 60%, p = 0.026), and 17% (95% CI 5%-27%, p = 0.030) of CVD deaths, would be averted respectively. Conclusions: A holistic approach in addressing socioeconomic factors in the broader context of social determinants of health at the policy, population and individual level will enhance prevention and treatment-adherence for CVD in underserved settings.

Indexed as

Cardiovascular DiseasesCross-Sectional StudiesEducational StatusFemaleFollow-Up StudiesHumansIncidenceIncomeKenyaMaleMiddle AgedPoverty AreasRetrospective StudiesRisk FactorsSocioeconomic FactorsSurvival RateCardiovascular riskeducationemploymentmortalitysocial determinants of health

Identifiers

PMID32489806
PMCPMC7218782

What OpenQuestion holds

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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.