Evidence map›Paper›PMID 26406462›Full record

ArticlePloS one2015

The Epidemiology of Hypertension in Uganda: Findings from the National Non-Communicable Diseases Risk Factor Survey.

David Guwatudde, Gerald Mutungi, Ronald Wesonga, Richard Kajjura, Hafisa Kasule, James Muwonge, Vincent Ssenono, Silver K Bahendeka

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 147 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
147citing papers in PubMed, 7 pooled it
8.3field-weighted citation impact, top 2% 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

147 citing papers in PubMed, 7 syntheses or guidelines pooled it, 238 citations in OpenAlex.

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87 more citing papers are in PubMed but not listed here.

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

8 authors at 4 institutions in 1 country.

David GuwatuddeDepartment of Epidemiology & Biostatistics, School of Public Health, Makerere University College of Health Sciences, Kampala, Uganda.
Gerald MutungiControl of Non-Communicable Diseases Desk, Ministry of Health, Kampala, Uganda.
Ronald WesongaSchool of Statistics and Planning, Makerere University College of Business and Management Sciences, Kampala, Uganda.
Richard KajjuraDepartment of Community Health and Behavioral Sciences, School of Public Health, Makerere University College of Health Sciences, Kampala, Uganda.
Hafisa KasuleWorld Health Organization, Uganda Country Office, Kampala, Uganda.
James MuwongeDivision of Socioeconomic Surveys, Uganda Bureau of Statistics, Kampala, Uganda.
Vincent SsenonoDivision of Socioeconomic Surveys, Uganda Bureau of Statistics, Kampala, Uganda.
Silver K BahendekaDepartment of Internal Medicine, Nsambya Hospital, Kampala, Uganda.
Makerere University · UGMinistry of Health · UGNsambya Hospital · UGWorld Health Organization - Uganda · UG

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundHypertension is an important contributor to global burden of disease and mortality, and is a growing public health problem in sub-Saharan Africa. However, most sub-Saharan African countries lack detailed countrywide data on hypertension and other non-communicable diseases (NCD) risk factors that would provide benchmark information for design of appropriate interventions. We analyzed blood pressure data from Uganda's nationwide NCD risk factor survey conducted in 2014, to describe the prevalence and distribution of hypertension in the Ugandan population, and to identify the associated factors.

methodsThe NCD risk factor survey drew a countrywide sample stratified by the four regions of the country, and with separate estimates for rural and urban areas. The World Health Organization's STEPs tool was used to collect data on demographic and behavioral characteristics, and physical and biochemical measurements. Prevalence rate ratios (PRR) using modified Poison regression modelling was used to identify factors associated with hypertension.

resultsOf the 3906 participants, 1033 were classified as hypertensive, giving an overall prevalence of 26.4%. Prevalence was highest in the central region at 28.5%, followed by the eastern region at 26.4%, western region at 26.3%, and northern region at 23.3%. Prevalence in urban areas was 28.9%, and 25.8% in rural areas. The differences between regions, and between rural-urban areas were not statistically significant. Only 7.7% of participants with hypertension were aware of their high blood pressure. The prevalence of pre-hypertension was also high at 36.9%. The only modifiable factor found to be associated with hypertension was higher body mass index (BMI). Compared to participants with BMI less than 25 kg/m2, prevalence was significantly higher among participants with BMI between 25 to 29.9 kg/m2 with an adjusted PRR = 1.46 [95% CI = 1.25-1.71], and even higher among obese participants (BMI ≥ 30 kg/m2) with an adjusted PRR = 1.60 [95% CI = 1.29-1.99]. The un-modifiable factor found to be associated with hypertension was older age with an adjusted PRR of 1.02 [95% CI = 1.02-1.03] per yearly increase in age.

conclusionsThe prevalence of hypertension in Uganda is high, with no significant differences in distribution by geographical location. Only 7.7% of persons with hypertension were aware of their hypertension, indicating a high burden of undiagnosed and un-controlled high blood pressure. Thus a big percentage of persons with hypertension are at high risk of hypertension-related cardiovascular NCDs.

Indexed as

AdultBlood PressureBody Mass IndexCross-Sectional StudiesFemaleHealth SurveysHumansHypertensionMaleMiddle AgedPoisson DistributionPrevalenceRisk FactorsUgandaYoung Adult

Identifiers

PMID26406462
PMCPMC4583385
OpenAlexW2208270677

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.