Evidence map›Paper›PMID 40435190›Full record

ArticlePLOS global public health2025

Physical activity levels and its associated factors among adults in Vihiga county, Kenya.

Miriam Bosire, Doreen Mitaru, Joanna Olale, Schiller Mbuka, Melvine Obuya, Rodgers Ochieng, Boniface Oyugi, Erastus Muniu, Joseph Mutai, Divya Parmar and 2 more

Abstract read
In one paragraph

Article in PLOS global public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

12 authors.

Miriam BosireCenter for Public Health Research, Kenya Medical Research Institute, Nairobi, Kenya.ORCID https://orcid.org/0009-0009-8301-2210
Doreen MitaruCenter for Public Health Research, Kenya Medical Research Institute, Nairobi, Kenya.ORCID https://orcid.org/0009-0003-7440-9765
Joanna OlaleCenter for Clinical Research, Kenya Medical Research Institute, Nairobi, Kenya.ORCID https://orcid.org/0009-0006-2697-7516
Schiller MbukaCenter for Public Health Research, Kenya Medical Research Institute, Nairobi, Kenya.ORCID https://orcid.org/0009-0009-7487-5743
Melvine ObuyaCenter for Clinical Research, Kenya Medical Research Institute, Nairobi, Kenya.ORCID https://orcid.org/0009-0001-8636-896X
Rodgers OchiengCenter for Public Health Research, Kenya Medical Research Institute, Nairobi, Kenya.
Boniface OyugiFaculty of Health Sciences, University of Nairobi, Nairobi, Kenya.ORCID https://orcid.org/0000-0002-9550-9138
Erastus MuniuCenter for Public Health Research, Kenya Medical Research Institute, Nairobi, Kenya.
Joseph MutaiCenter for Public Health Research, Kenya Medical Research Institute, Nairobi, Kenya.
Divya ParmarSchool of Population Health Sciences and School of Life Course Sciences, King's College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-7979-3140
Lydia KadukaCenter for Public Health Research, Kenya Medical Research Institute, Nairobi, Kenya.ORCID https://orcid.org/0000-0001-8746-0533
Seeromanie HardingSchool of Population Health Sciences and School of Life Course Sciences, King's College London, London, United Kingdom.

Funding

Wellcome Trust
6 · The paper itself

Abstract

Sedentary lifestyle is a major risk factor for cardiovascular diseases (CVDs) which account for 8% of Kenya's non-communicable disease (NCD) burden. Prevalence of physical inactivity remains high globally. There is paucity of data on physical activity levels in rural Sub-Saharan Africa to inform effective interventions. This study sought to establish levels and factors associated with physical activity in a rural population in Kenya. This was a cross-sectional study in Vihiga, a predominantly rural County in Kenya. Participants were adults aged ≥18 years drawn from four community markets. Stratified sampling by ecological zones and rural/urban status was used to select the four markets and Sampling the Next Customer Exiting the Market method for the respondents. Researcher administered e-questionnaire adapted from International Physical Activity Questionnaire (IPAQ) was used to collect data. Physical activity was calculated as the sum of all Metabolic Equivalents (MET)-minutes/week. Multivariable binary logistic regression analysis was used to identify correlates of physical activity. Out of the total 375 (m: 49%; f: 51%) participants, 27% were physically inactive (m: 22%; f: 32%;) and 42% engaged in low level physical activity. Majority of the respondents (75.5%) engaged in transportation-related physical activity while 32% engaged in leisure physical activities. The odds of being physically inactive were 1.93 times higher for females, 2.62 higher for those aged ≥65 years, and 3.62 higher for those with high health literacy. 48% with high health literacy were in the early working age group (15-24 years). Majority (53%) received health information from healthcare workers, especially for the 60% physically inactive participants. This study highlights the need for targeted community interventions to address the observed physical inactivity especially among women and older adults in rural Kenya.

Identifiers

PMID40435190
PMCPMC12118921

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LicenceCC BY
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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.