Evidence map›Paper›PMID 28760156›Full record

ArticleBMC geriatrics2017

Predictors of self-reported health among the elderly in Ghana: a cross sectional study.

Cynthia Lum Fonta, Justice Nonvignon, Moses Aikins, Emmanuel Nwosu, Genevieve Cecilia Aryeetey

Open access · goldAbstract read
In one paragraph

Article in BMC geriatrics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
5.6field-weighted citation impact, top 4% 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

28 citing papers in PubMed, 1 synthesis or guideline pooled it, 71 citations in OpenAlex.

  1. Pooled it
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  7. Poor Self-Rated Health and Associated Factors among Older Persons in Malaysia: A Population-Based Study.International journal of environmental research and public health · 2023
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  16. Can survey data facilitate local priority setting? Experience from the Igunga and Nzega districts in Tanzania.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 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

5 authors at 2 institutions in 2 countries.

Cynthia Lum FontaDepartment of Health Policy Planning and Management, School of Public Health, University of Ghana, Legon, Accra, LG 13, Ghana. cynfonta@gmail.com.
Justice NonvignonDepartment of Health Policy Planning and Management, School of Public Health, University of Ghana, Legon, Accra, LG 13, Ghana.
Moses AikinsDepartment of Health Policy Planning and Management, School of Public Health, University of Ghana, Legon, Accra, LG 13, Ghana.
Emmanuel NwosuDepartment of Economics, University of Nigeria Nsukka, Enugu State, Nigeria.
Genevieve Cecilia AryeeteyDepartment of Health Policy Planning and Management, School of Public Health, University of Ghana, Legon, Accra, LG 13, Ghana.
University of Ghana · GHUniversity of Nigeria · NG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSelf-reported health is a widely used measure of health status across individuals. As the ageing population increases, the health of the elderly also becomes of growing concern. The elderly go through life facing social, economic and financial hardships. These hardships are known to affect the health status of people as they age. The purpose of this study is to assess social and health related factors of self-reported health among the elderly in Ghana.

methodsA multivariate regression analysis in form of a binary and ordinal logistic regression were used to determine the association between socioeconomic, demographic and health related factors, on self-reported health. The data used for this study was drawn from the World Health Organization (WHO) Study on Global Ageing and Adult Health (SAGE) Wave 1.

resultsIn total, out of 2613 respondent, 579 (20.1%) rated their health status as poor and 2034 (79.9%) as good. The results showed that the odds of reporting poor health was 2.5 times higher among the old-old compared to the young old. The elderly with one or more than one chronic condition had the odds of 1.6 times and 2 times respectively, of reporting poor health. Engaging in mild to moderate exercise increased the chances of reporting poor health by 1.8 times. The elderly who had never worked in a lifetime were 2 times more likely to report poor health. In the same way, residents of Eastern and Western parts of Ghana were 2 times more likely to report poor health compared to those in the Upper West region. Respondents with functional limitations and disabilities were 3.6 times and 2.4 times respectively, more likely to report poor health. On the other hand, the odds of reporting poor health was 29, 36 and 27% less among respondents in the highest income quintiles, former users of tobacco and those satisfied with certain aspects of life respectively. Also, current alcohol users were 41% less likely to report poor health.

conclusionThe health status of the elderly is to an extent determined by the circumstances in which they are born, grow and live. The findings suggest that addressing social issues faced by individuals in youthful age will go a long way to achieving good health in the future. People with physical limitations and disabilities are most vulnerable to unmet healthcare needs and support system from government, policy makers and family.

Indexed as

Health StatusPatient Reported Outcome MeasuresSelf ReportSocial SupportAdultAgedAged, 80 and overCross-Sectional StudiesExerciseFamilyFemaleGhanaHealth SurveysHealthy AgingHumansMaleElderly populationGhanaSelf-reported healthWellbeing

Identifiers

PMID28760156
PMCPMC5537992
OpenAlexW2741191367

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.