↓ Skip to main content

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

Overview of attention for article published in International Journal for Equity in Health, April 2018
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
4 X users
facebook
1 Facebook page

Citations

dimensions_citation
28 Dimensions

Readers on

mendeley
124 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Inequalities in health and health risk factors in the Southern African Development Community: evidence from World Health Surveys
Published in
International Journal for Equity in Health, April 2018
DOI 10.1186/s12939-018-0762-8
Pubmed ID
Authors

Stella M. Umuhoza, John E. Ataguba

Abstract

Socioeconomic 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. Data 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). Generally, 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. There 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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 124 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 124 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 22 18%
Researcher 14 11%
Student > Ph. D. Student 11 9%
Student > Postgraduate 9 7%
Lecturer 7 6%
Other 15 12%
Unknown 46 37%
Readers by discipline Count As %
Medicine and Dentistry 14 11%
Nursing and Health Professions 14 11%
Economics, Econometrics and Finance 12 10%
Social Sciences 10 8%
Arts and Humanities 5 4%
Other 19 15%
Unknown 50 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 May 2018.
All research outputs
#15,293,119
of 24,716,872 outputs
Outputs from International Journal for Equity in Health
#1,549
of 2,144 outputs
Outputs of similar age
#184,358
of 331,554 outputs
Outputs of similar age from International Journal for Equity in Health
#39
of 43 outputs
Altmetric has tracked 24,716,872 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,144 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.3. This one is in the 26th percentile – i.e., 26% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 331,554 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.