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The social patterning of risk factors for noncommunicable diseases in five countries: evidence from the modeling the epidemiologic transition study (METS)

Overview of attention for article published in BMC Public Health, September 2016
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Title
The social patterning of risk factors for noncommunicable diseases in five countries: evidence from the modeling the epidemiologic transition study (METS)
Published in
BMC Public Health, September 2016
DOI 10.1186/s12889-016-3589-5
Pubmed ID
Authors

Silvia Stringhini, Terrence E. Forrester, Jacob Plange-Rhule, Estelle V. Lambert, Bharathi Viswanathan, Walter Riesen, Wolfgang Korte, Naomi Levitt, Liping Tong, Lara R. Dugas, David Shoham, Ramon A. Durazo-Arvizu, Amy Luke, Pascal Bovet

Abstract

Associations between socioeconomic status (SES) and risk factors for noncommunicable diseases (NCD-RFs) may differ in populations at different stages of the epidemiological transition. We assessed the social patterning of NCD-RFs in a study including populations with different levels of socioeconomic development. Data on SES, smoking, physical activity, body mass index, blood pressure, cholesterol and glucose were available from the Modeling the Epidemiologic Transition Study (METS), with about 500 participants aged 25-45 in each of five sites (Ghana, South Africa, Jamaica, Seychelles, United States). The prevalence of NCD-RFs differed between these populations from five countries (e.g., lower prevalence of smoking, obesity and hypertension in rural Ghana) and by sex (e.g., higher prevalence of smoking and physical activity in men and of obesity in women in most populations). Smoking and physical activity were associated with low SES in most populations. The associations of SES with obesity, hypertension, cholesterol and elevated blood glucose differed by population, sex, and SES indicator. For example, the prevalence of elevated blood glucose tended to be associated with low education, but not with wealth, in Seychelles and USA. The association of SES with obesity and cholesterol was direct in some populations but inverse in others. In conclusion, the distribution of NCD-RFs was socially patterned in these populations at different stages of the epidemiological transition, but associations between SES and NCD-RFs differed substantially according to risk factor, population, sex, and SES indicator. These findings emphasize the need to assess and integrate the social patterning of NCD-RFs in NCD prevention and control programs in LMICs.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 170 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 170 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 29 17%
Student > Ph. D. Student 17 10%
Student > Bachelor 15 9%
Researcher 13 8%
Other 11 6%
Other 30 18%
Unknown 55 32%
Readers by discipline Count As %
Medicine and Dentistry 34 20%
Nursing and Health Professions 27 16%
Social Sciences 12 7%
Agricultural and Biological Sciences 6 4%
Biochemistry, Genetics and Molecular Biology 4 2%
Other 20 12%
Unknown 67 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 18 October 2016.
All research outputs
#13,237,135
of 23,655,067 outputs
Outputs from BMC Public Health
#8,915
of 15,344 outputs
Outputs of similar age
#166,450
of 332,186 outputs
Outputs of similar age from BMC Public Health
#213
of 373 outputs
Altmetric has tracked 23,655,067 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 15,344 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.2. This one is in the 41st percentile – i.e., 41% 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 332,186 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 373 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.