Evidence map›Paper›PMID 30400910›Full record

ArticleBMC public health2018

Prevalence and determinants of heavy episodic drinking among adults in Kenya: analysis of the STEPwise survey, 2015.

Anne Kendagor, Gladwell Gathecha, Melau W Ntakuka, Philip Nyakundi, Samuel Gathere, Dorcas Kiptui, Hussein Abubakar, Oren Ombiro, Pamela Juma, Christine Ngaruiya

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
2.8field-weighted citation impact, top 9% 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.

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  15. Mental Health Challenges and Needs among Sexual and Gender Minority People in Western Kenya.International journal of environmental research and public health · 2021
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  17. Alcohol consumption and alcohol policyTurkish journal of medical sciences · 2020
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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

10 authors at 4 institutions in 2 countries.

Anne KendagorDivision of Non-Communicable Diseases, Ministry of Health, Nairobi, Kenya. annekendagor@gmail.com.
Gladwell GathechaDivision of Non-Communicable Diseases, Ministry of Health, Nairobi, Kenya.
Melau W NtakukaAlcohol control focal point, Ministry of Health, Nairobi, Kenya.
Philip NyakundiDivision of Non-Communicable Diseases, Ministry of Health, Nairobi, Kenya.
Samuel GathereKenya Medical Research Institute (KEMRI), Nairobi, Kenya.
Dorcas KiptuiDivision of Non-Communicable Diseases, Ministry of Health, Nairobi, Kenya.
Hussein AbubakarDivision of Non-Communicable Diseases, Ministry of Health, Nairobi, Kenya.
Oren OmbiroDivision of Non-Communicable Diseases, Ministry of Health, Nairobi, Kenya.
Pamela JumaAfrican Population and Health Research Center, Nairobi, Kenya.
Christine NgaruiyaYale School of Medicine, New Haven, CT, USA. christine.ngaruiya@yale.edu.
Ministry of Health · KEAfrican Population and Health Research Center · KEKenya Medical Research Institute · KEYale University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGlobally, alcohol consumption contributes to 3.3 million deaths and 5.1% of Disability Adjusted Life Years (DALYs), and its use is linked with more than 200 disease and injury conditions. Our study assessed the frequency and patterns of Heavy Episodic Drinking (HED) in Kenya. HED is defined as consumption of 60 or more grams of pure alcohol (6+ standard drinks in most countries) on at least one single occasion per month. Understanding the burden and patterns of heavy episodic drinking will be helpful to inform strategies that would curb the problem in Kenya.

methodsUsing the WHO STEPwise approach to surveillance (STEPS) tool, a nationally representative household survey of 4203 adults aged 18-69 years was conducted in Kenya between April and June 2015. We used logistic regression analysis to assess factors associated with HED among both current and former alcohol drinkers. We included the following socio-demographic variables: age, sex, and marital status, level of education, socio-economic status, residence, and tobacco as an interaction factor.

resultsThe prevalence of HED was 12.6%. Men were more likely to engage in HED than women (unadjusted OR 9.9 95%, CI 5.5-18.8). The highest proportion of HED was reported in the 18-29-year age group (35.5%). Those currently married/ cohabiting had the highest prevalence of HED (60%). Respondents who were separated had three times higher odds of HED compared to married counterparts (OR 2.7, 95% CI 1.3-5.7). Approximately 16.0% of respondents reported cessation of alcohol use due to health reasons. Nearly two thirds reported drinking home-brewed beers or wines. Tobacco consumption was associated with higher odds of HED (unadjusted OR 6.9, 95% CI 4.4-10.8); those that smoke (34.4%) were more likely to engage in HED compared to their non-smoking counterparts.

conclusionOur findings highlight a significant prevalence of HED among alcohol drinkers in Kenya. Young males, those with less education, married people, and tobacco users were more likely to report heavy alcohol use, with male sex as the primary driving factor. These findings are novel to the country and region; they provide guidance to target alcohol control interventions for different groups in Kenya.

Indexed as

AdolescentAdultAgedAlcohol DrinkingFemaleHumansKenyaMaleMiddle AgedPrevalenceRisk FactorsSex DistributionSurveys and QuestionnairesYoung AdultAlcoholConsumptionControlEpisodic drinking

Identifiers

PMID30400910
PMCPMC6219062
OpenAlexW2899670871

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.