Evidence map›Paper›PMID 23967317›Full record

ArticlePloS one2013

Diabetes and pre-diabetes among persons aged 35 to 60 years in eastern Uganda: prevalence and associated factors.

Roy William Mayega, David Guwatudde, Fredrick Makumbi, Frederick Nelson Nakwagala, Stefan Peterson, Goran Tomson, Claes-Goran Ostenson

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In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed, 4 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

59 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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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

7 authors.

Roy William MayegaDivision of Global Health-IHCAR, Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden. wromay2000@yahoo.co.uk
David Guwatudde
Fredrick Makumbi
Frederick Nelson Nakwagala
Stefan Peterson
Goran Tomson
Claes-Goran Ostenson

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOur aim was to estimate the prevalence of abnormal glucose regulation (AGR) (i.e. diabetes and pre-diabetes) and its associated factors among people aged 35-60 years so as to clarify the relevance of targeted screening in rural Africa.

methodsA population-based survey of 1,497 people (786 women and 711 men) aged 35-60 years was conducted in a predominantly rural Demographic Surveillance Site in eastern Uganda. Participants responded to a lifestyle questionnaire, following which their Body Mass Index (BMI) and Blood Pressure (BP) were measured. Fasting plasma glucose (FPG) was measured from capillary blood using On-Call® Plus (Acon) rapid glucose meters, following overnight fasting. AGR was defined as FPG ≥6.1 mmol L⁻¹ (World Health Organization (WHO) criteria or ≥5.6 mmol L⁻¹ (American Diabetes Association (ADA) criteria. Diabetes was defined as FPG >6.9 mmol L⁻¹, or being on diabetes treatment.

resultsThe mean age of participants was 45 years for men and 44 for women. Prevalence of diabetes was 7.4% (95%CI 6.1-8.8), while prevalence of pre-diabetes was 8.6% (95%CI 7.3-10.2) using WHO criteria and 20.2% (95%CI 17.5-22.9) with ADA criteria. Using WHO cut-offs, the prevalence of AGR was 2 times higher among obese persons compared with normal BMI persons (Adjusted Prevalence Rate Ratio (APRR) 1.9, 95%CI 1.3-2.8). Occupation as a mechanic, achieving the WHO recommended physical activity threshold, and higher dietary diversity were associated with lower likelihood of AGR (APRR 0.6, 95%CI 0.4-0.9; APRR 0.6, 95%CI 0.4-0.8; APRR 0.5, 95%CI 0.3-0.9 respectively). The direct medical cost of detecting one person with AGR was two US dollars with ADA and three point seven dollars with WHO cut-offs.

conclusionsThere is a high prevalence of AGR among people aged 35-60 years in this setting. Screening for high risk persons and targeted health education to address obesity, insufficient physical activity and non-diverse diets are necessary.

Indexed as

AdultBehaviorBlood GlucoseDiabetes Mellitus, Type 2FemaleHealth Knowledge, Attitudes, PracticeHumansIncomeMaleMass ScreeningMiddle AgedPrediabetic StatePrevalenceRiskRural PopulationUgandaBlood Glucose

Identifiers

PMID23967317
PMCPMC3743823

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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.