Evidence map›Paper›PMID 29703215›Full record

ArticleInternational journal for equity in health2018

Inequalities in health and health risk factors in the Southern African Development Community: evidence from World Health Surveys.

Stella M Umuhoza, John E Ataguba

Abstract read
In one paragraph

Article in International journal for equity in health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 2 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

25 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

2 authors.

Stella M UmuhozaDepartment of Health Policy, Economics and Management, School of Public Health, College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda.
John E AtagubaHealth Economics Unit, School of Public Health and Family Medicine, Faculty of Health Sciences, University of Cape Town, Anzio Road, Observatory, 7925, South Africa. John.Ataguba@uct.ac.za.ORCID 0000-0002-7746-3826

Funding

International Development Research Centre 106439
6 · The paper itself

Abstract

backgroundSocioeconomic inequalities in health have been documented in many countries including those in the Southern African Development Community (SADC). However, a comprehensive assessment of health inequalities and inequalities in the distribution of health risk factors is scarce. This study specifically investigates inequalities both in poor self-assessed health (SAH) and in the distribution of selected risk factors of ill-health among the adult populations in six SADC countries.

methodsData come from the 2002/04 World Health Survey (WHS) using six SADC countries (Malawi, Mauritius, South Africa, Swaziland, Zambia and Zimbabwe) where the WHS was conducted. Poor SAH is reporting bad or very bad health status. Risk factors such as smoking, heavy drinking, low fruit and vegetable consumption and physical inactivity were considered. Other environmental factors were also considered. Socioeconomic status was assessed using household expenditures. Standardised and normalised concentration indices (CIs) were used to assess socioeconomic inequalities. A positive (negative) concentration index means a pro-rich (pro-poor) distribution where the variable is reported more among the rich (poor).

resultsGenerally, a pro-poor socioeconomic inequality exists in poor SAH in the six countries. However, this is only significant for South Africa (CI = - 0.0573; p < 0.05), and marginally significant for Zambia (CI = - 0.0341; P < 0.1) and Zimbabwe (CI = - 0.0357; p < 0.1). Smoking and inadequate fruit and vegetable consumption were significantly concentrated among the poor. Similarly, the use of biomass energy, unimproved water and sanitation were significantly concentrated among the poor. However, inequalities in heavy drinking and physical inactivity are mixed. Overall, a positive relationship exists between inequalities in ill-health and inequalities in risk factors of ill-health.

conclusionThere is a need for concerted efforts to tackle the significant socioeconomic inequalities in ill-health and health risk factors in the region. Because some of the determinants of ill-health lie outside the health sector, inter-sectoral action is required.

Indexed as

Attitude to HealthHealth StatusAdolescentAdultBlack PeopleDeveloping CountriesFemaleHealth SurveysHumansIncomeMaleRisk FactorsSelf-AssessmentSocioeconomic FactorsSouth AfricaSurveys and QuestionnairesHealth inequalitySelf-assessed healthSouthern African development communityWorld Health Survey

Identifiers

PMID29703215
PMCPMC5921793

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.