Evidence map›Paper›PMID 33796165›Full record

ArticleThe Pan African medical journal2020

Socio-economic and demographic determinants of non-communicable diseases in Kenya: a secondary analysis of the Kenya stepwise survey.

Kibachio Joseph Mwangi, Valerian Mwenda, Gladwell Gathecha, David Beran, Idris Guessous, Oren Ombiro, Zachary Ndegwa, Peninnah Masibo

Abstract read
In one paragraph

Article in The Pan African medical journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

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

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

  1. Pooled it
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  7. Beyond Numbers: Decoding the Gendered Tapestry of Non-Communicable Diseases in India.International journal of environmental research and public health · 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

8 authors.

Kibachio Joseph MwangiFaculté de Médecine, Université de Genève, Genève, Suisse.
Valerian MwendaDivision of Non-communicable Disease, Ministry of Health, Nairobi, Kenya.
Gladwell GathechaDivision of Non-communicable Disease, Ministry of Health, Nairobi, Kenya.
David BeranDivision of Primary Care Medicine, Department of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland.
Idris GuessousFaculté de Médecine, Université de Genève, Genève, Suisse.
Oren OmbiroDivision of Non-communicable Disease, Ministry of Health, Nairobi, Kenya.
Zachary NdegwaDivision of Non-communicable Disease, Ministry of Health, Nairobi, Kenya.
Peninnah MasiboGlobal Programs for Research and Training, University of California, San Francisco, Nairobi, Kenya.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionnon-communicable diseases (NCDs) are projected to become the leading cause of death in Africa by 2030. Gender and socio-economic differences influence the prevalence of NCDs and their risk factors.

methodswe performed a secondary analysis of the STEPS 2015 data to determine prevalence and correlation between diabetes, hypertension, harmful alcohol use, smoking, obesity and injuries across age, gender, residence and socio-economic strata.

resultstobacco use prevalence was 13.5% (males 19.9%, females 0.9%, p<0.001); harmful alcohol use was 12.6% (males 18.1%, females 2.2%, p<0.001); central obesity was 27.9% (females 49.5%, males 32.9%, p=0.017); type 2 diabetes prevalence 3.1% (males 2.0%, females 2.8%, p=0.048); elevated blood pressure prevalence was 23.8% (males 25.1%, females 22.6%, p<0.001), non-use of helmets 72.8% (males 89.5%, females 56.0%, p=0.031) and seat belts non-use 67.9% (males 79.8%, females 56.0%, p=0.027). Respondents with <12 years of formal education had higher prevalence of non-use of helmets (81.7% versus 54.1%, p=0.03) and seat belts (73.0% versus 53.9%, p=0.039). Respondents in the highest wealth quintile had higher prevalence of type II diabetes compared with those in the lowest (5.2% versus 1.6%,p=0.008). Rural dwellers had 35% less odds of tobacco use (aOR 0.65, 95% CI 0.49, 0.86) compared with urban dwellers, those with ≥12 years of formal education had 89% less odds of tobacco use (aOR 0.11, 95% CI 0.07, 0.17) compared with <12 years, and those belonging to the wealthiest quintile had 64% higher odds of unhealthy diets (aOR 1.64, 95% CI 1.26, 2.14). Only 44% of respondents with type II diabetes and 16% with hypertension were aware of their diagnosis.

conclusionprevalence of NCD risk factors is high in Kenya and varies across socio-demographic attributes. Socio-demographic considerations should form part of multi-sectoral, integrated approach to reduce the NCD burden in Kenya.

Indexed as

AdolescentAdultAgedAlcohol DrinkingCross-Sectional StudiesDiabetes Mellitus, Type 2FemaleHumansHypertensionKenyaMaleMiddle AgedNoncommunicable DiseasesObesityPrevalenceRisk FactorsdeterminantsKenyaNon-communicable diseasesrisk factorssocio-demographic

Identifiers

PMID33796165
PMCPMC7992900

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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.