Dataset Information

Urbanicity and lifestyle risk factors for cardiometabolic diseases in rural Uganda: a cross-sectional study.

ABSTRACT:

Background

Urban living is associated with unhealthy lifestyles that can increase the risk of cardiometabolic diseases. In sub-Saharan Africa (SSA), where the majority of people live in rural areas, it is still unclear if there is a corresponding increase in unhealthy lifestyles as rural areas adopt urban characteristics. This study examines the distribution of urban characteristics across rural communities in Uganda and their associations with lifestyle risk factors for chronic diseases.

Methods and findings

Using data collected in 2011, we examined cross-sectional associations between urbanicity and lifestyle risk factors in rural communities in Uganda, with 7,340 participants aged 13 y and above across 25 villages. Urbanicity was defined according to a multi-component scale, and Poisson regression models were used to examine associations between urbanicity and lifestyle risk factors by quartile of urbanicity. Despite all of the villages not having paved roads and running water, there was marked variation in levels of urbanicity across the villages, largely attributable to differences in economic activity, civil infrastructure, and availability of educational and healthcare services. In regression models, after adjustment for clustering and potential confounders including socioeconomic status, increasing urbanicity was associated with an increase in lifestyle risk factors such as physical inactivity (risk ratio [RR]: 1.19; 95% CI: 1.14, 1.24), low fruit and vegetable consumption (RR: 1.17; 95% CI: 1.10, 1.23), and high body mass index (RR: 1.48; 95% CI: 1.24, 1.77).

Conclusions

This study indicates that even across rural communities in SSA, increasing urbanicity is associated with a higher prevalence of lifestyle risk factors for cardiometabolic diseases. This finding highlights the need to consider the health impact of urbanization in rural areas across SSA. Please see later in the article for the Editors' Summary.

SUBMITTER: Riha J

PROVIDER: S-EPMC4114555 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature

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Publications

Urbanicity and lifestyle risk factors for cardiometabolic diseases in rural Uganda: a cross-sectional study.

Riha Johanna J Karabarinde Alex A Ssenyomo Gerald G Allender Steven S Asiki Gershim G Kamali Anatoli A Young Elizabeth H EH Sandhu Manjinder S MS Seeley Janet J

PLoS medicine 20140729 7

<h4>Background</h4>Urban living is associated with unhealthy lifestyles that can increase the risk of cardiometabolic diseases. In sub-Saharan Africa (SSA), where the majority of people live in rural areas, it is still unclear if there is a corresponding increase in unhealthy lifestyles as rural areas adopt urban characteristics. This study examines the distribution of urban characteristics across rural communities in Uganda and their associations with lifestyle risk factors for chronic diseases ...[more]

PMID: 25072243

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Project description:BackgroundAlong with a nutritional transition in Sub-Saharan Africa, the prevalence of non-communicable diseases is increasing rapidly. We assess the association between food intake and cardiometabolic risk factors in a rural population in Uganda.MethodsThe present study was based on data from a household-based case-control study of diabetic and non-diabetic households in Southwestern Uganda, 2012-2013. We analysed food intake in 359 individuals age ≥ 13 years from 87 households, using a household food frequency questionnaire, and measures of glycated haemoglobin (HbA1c), height and weight. We used multinomial logistic regression to model abnormal HbA1c (≥5.7%) and weight status (underweight, normal weight and overweight) as an outcome of total food intake and by nine food groups. Results were reported as odds ratios (OR) with 95% confidence intervals (CI). Models were adjusted for three nested sets of covariates.ResultsThe diet primarily consisted of staple food (cassava and plantain). High-Glycaemic Index staple food was the most consumed food group (median = 14 servings/week, p25-p75: 11-17). Milk, meat, fish and vegetables were the least consumed food groups (medians: 0-3 servings/week). Median intake of sugary food was 6 servings/week (p25-p75: 2-9). The OR of having abnormal HbA1c or being overweight increased with every weekly serving of food (1.02, 95% CI: 1.00-1.04 and 1.01 95% CI: 1.00-1.03, respectively). Of specific food groups, each weekly serving of meat increased the OR of being overweight with 33% (95% CI: 1.08-1.64), and fruit intake decreased the OR of abnormal HbA1c (0.94, 95% CI: 0.88-1.00), though this latter association was attenuated after adjustment for weight status, aerobic capacity, and socioeconomic status.ConclusionDiet was monotonous, mainly consisting of cassava and plantain, and increasing food intake was associated with abnormal HbA1c and overweight. To prevent non-communicable diseases a diet with higher intake of fish and vegetables, and less sugary food is recommended.

Project description:BACKGROUND:Non-communicable diseases (NCDs) are rapidly becoming leading causes of morbidity and mortality in low- and middle-income countries, including those in sub-Saharan Africa. In contrast to high-income countries, the sociodemographic distribution, including socioeconomic inequalities, of NCDs and their risk factors is unclear in sub-Saharan Africa, particularly among rural populations. METHODS:We undertook a cross-sectional population-based survey of 7809 residents aged 13 years or older in the General Population Cohort in south-western rural Uganda. Information on behavioural, physiological and biochemical risk factors was obtained using standardized methods as recommended by the WHO STEPwise Approach to Surveillance. Socioeconomic status (SES) was determined by principal component analysis including household features, ownership, and occupation and education of the head of household. RESULTS:SES was found to be associated with NCD risk factors in this rural population. Smoking, alcohol consumption (men only) and low high-density lipoprotein (HDL) cholesterol were more common among those of lower SES. For example, the prevalence of smoking decreased 4-fold from the lowest to the highest SES groups, from 22.0% to 5.7% for men and 2.2% to 0.4% for women, respectively. In contrast, overweight, raised blood pressure, raised HbA1c (women only) and raised cholesterol were more common among those of higher SES. For example, the prevalence of overweight increased 5-fold from 2.1% to 10.1% for men, and 2-fold from 12.0% to 23.4% for women, from the lowest to highest SES groups respectively. However, neither low physical activity nor fruit, vegetable or staples consumption was associated with SES. Furthermore, associations between NCD risk factors and SES were modified by age and sex. CONCLUSIONS:Within this rural population, NCD risk factors are common and vary both inversely and positively across the SES gradient. A better understanding of the determinants of the sociodemographic distribution of NCDs and their risk factors in rural sub-Saharan African populations will help identify populations at most risk of developing NCDs and help plan interventions to reduce their burden.

Project description:BACKGROUND:Sex-based differences in cardiovascular disease (CVD) burden are widely acknowledged, with male sex considered a risk factor in high-income settings. However, these relationships have not been examined in sub-Saharan Africa (SSA). We aimed to apply the American Heart Association (AHA) ideal cardiovascular health (CVH) tool modified by the addition of C-reactive protein (CRP) to examine potential sex-based differences in the prevalence of CVD risk in rural Uganda. METHODS:In a cross-sectional study nested within a population-wide census, 857 community-living adults completed physical and laboratory-based assessments to calculate individual ideal CVH metrics including an eight category for CRP levels. We summarized sex-specific ideal CVH indices, fitting ordinal logistic regression models to identify correlates of improving CVH. As secondary outcomes, we assessed subscales of ideal CVH behaviours and factors. Models included inverse probability of sampling weights to determine population-level estimates. RESULTS:The weighted-population mean age was 39.2 (1.2) years with 52.0 (3.7) % females. Women had ideal scores in smoking (80.4% vs. 68.0%; p < 0.001) and dietary intake (26.7% vs. 16.8%; p = 0.037) versus men, but the opposite in body mass index (47.3% vs. 84.4%; p < 0.001), glycated hemoglobin (87.4% vs. 95.2%; p = 0.001), total cholesterol (80.2% vs. 85.0%; p = 0.039) and CRP (30.8% vs. 49.7%; p = 0.009). Overall, significantly more men than women were classified as having optimal cardiovascular health (6-8 metrics attaining ideal level) (39.7% vs. 29.0%; p = 0.025). In adjusted models, female sex was correlated with lower CVH health factors sub-scales but higher ideal CVH behaviors. CONCLUSIONS:Contrary to findings in much of the world, female sex in rural SSA is associated with worse ideal CVH profiles, despite women having better indices for ideal CVH behaviors. Future work should assess the potential role of socio-behavioural sex-specific risk factors for ideal CVH in SSA, and better define the downstream consequences of these differences.

Project description:BackgroundAlthough lifestyle factors have been studied in relation to individual non-communicable diseases (NCDs), their association with development of a subsequent NCD, defined as multimorbidity, has been scarcely investigated. The aim of this study was to investigate associations between five lifestyle factors and incident multimorbidity of cancer and cardiometabolic diseases.MethodsIn this prospective cohort study, 291,778 participants (64% women) from seven European countries, mostly aged 43 to 58 years and free of cancer, cardiovascular disease (CVD), and type 2 diabetes (T2D) at recruitment, were included. Incident multimorbidity of cancer and cardiometabolic diseases was defined as developing subsequently two diseases including first cancer at any site, CVD, and T2D in an individual. Multi-state modelling based on Cox regression was used to compute hazard ratios (HR) and 95% confidence intervals (95% CI) of developing cancer, CVD, or T2D, and subsequent transitions to multimorbidity, in relation to body mass index (BMI), smoking status, alcohol intake, physical activity, adherence to the Mediterranean diet, and their combination as a healthy lifestyle index (HLI) score. Cumulative incidence functions (CIFs) were estimated to compute 10-year absolute risks for transitions from healthy to cancer at any site, CVD (both fatal and non-fatal), or T2D, and to subsequent multimorbidity after each of the three NCDs.ResultsDuring a median follow-up of 11 years, 1910 men and 1334 women developed multimorbidity of cancer and cardiometabolic diseases. A higher HLI, reflecting healthy lifestyles, was strongly inversely associated with multimorbidity, with hazard ratios per 3-unit increment of 0.75 (95% CI, 0.71 to 0.81), 0.84 (0.79 to 0.90), and 0.82 (0.77 to 0.88) after cancer, CVD, and T2D, respectively. After T2D, the 10-year absolute risks of multimorbidity were 40% and 25% for men and women, respectively, with unhealthy lifestyle, and 30% and 18% for men and women with healthy lifestyles.ConclusionPre-diagnostic healthy lifestyle behaviours were strongly inversely associated with the risk of cancer and cardiometabolic diseases, and with the prognosis of these diseases by reducing risk of multimorbidity.

Project description:ObjectiveTo determine the patterns of cardiometabolic multimorbidity and associated risk factors in sub-Saharan Africa (SSA).DesignWe used data from the WHO STEPwise approach to non-communicable disease risk factor surveillance cross-sectional surveys conducted between 2014 and 2017.ParticipantsThe participants comprised 39, 658 respondents aged 15-69 years randomly selected from nine SSA countries using a multistage stratified sampling design.Primary outcome measureUsing latent class analysis and agglomerative hierarchical clustering algorithms, we analysed the clustering of cardiometabolic diseases (CMDs) including high blood sugar, hypercholesterolaemia, hypertension and cardiovascular diseases (CVDs) such as heart attack, angina and stroke. Clusters of lifestyle risk factors: harmful salt intake, physical inactivity, obesity, tobacco and alcohol use were also computed. Prevalence ratios (PR) from modified Poisson regression were used to assess the association of cardiometabolic multimorbidity with sociodemographic and lifestyle risk factors.ResultsTwo distinct classes of CMDs were identified: relatively healthy group with minimal CMDs (95.2%) and cardiometabolic multimorbidity class comprising participants with high blood sugar, hypercholesterolaemia, hypertension and CVDs (4.8%). The clusters of lifestyle risk factors included alcohol, tobacco and harmful salt consumption (27.0%), and physical inactivity and obesity (5.8%). The cardiometabolic multimorbidity cluster exhibited unique sociodemographic and lifestyle risk profiles. Being female (PR=1.7, 95% CI (1.5 to 2.0), middle-aged (35-54 years) (3.9 (95% CI 3.2 to 4.8)), compared with age 15-34 years, employed (1.2 (95% CI 1.1 to 1.4)), having tertiary education (2.5 (95% CI 2.0 to 3.3)), vs no formal education and clustering of physical inactivity and obesity (2.4 (95% CI 2.0 to 2.8)) were associated with a higher likelihood of cardiometabolic multimorbidity.ConclusionOur findings show that cardiometabolic multimorbidity and lifestyle risk factors cluster in distinct patterns with a disproportionate burden among women, middle-aged, persons in high socioeconomic positions, and those with sedentary lifestyles and obesity. These results provide insights for health systems response in SSA to focus on these clusters as potential targets for integrated care.

Dataset Information

Urbanicity and lifestyle risk factors for cardiometabolic diseases in rural Uganda: a cross-sectional study.

Background

Methods and findings

Conclusions

Publications

Urbanicity and lifestyle risk factors for cardiometabolic diseases in rural Uganda: a cross-sectional study.

Similar Datasets

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