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1.
Nat Hum Behav ; 8(5): 903-916, 2024 May.
Artigo em Inglês | MEDLINE | ID: mdl-38480824

RESUMO

Evidence on cardiovascular disease (CVD) risk factor prevalence among adults living below the World Bank's international line for extreme poverty (those with income <$1.90 per day) globally is sparse. Here we pooled individual-level data from 105 nationally representative household surveys across 78 countries, representing 85% of people living in extreme poverty globally, and sorted individuals by country-specific measures of household income or wealth to identify those in extreme poverty. CVD risk factors (hypertension, diabetes, smoking, obesity and dyslipidaemia) were present among 17.5% (95% confidence interval (CI) 16.7-18.3%), 4.0% (95% CI 3.6-4.5%), 10.6% (95% CI 9.0-12.3%), 3.1% (95% CI 2.8-3.3%) and 1.4% (95% CI 0.9-1.9%) of adults in extreme poverty, respectively. Most were not treated for CVD-related conditions (for example, among those with hypertension earning <$1.90 per day, 15.2% (95% CI 13.3-17.1%) reported taking blood pressure-lowering medication). The main limitation of the study is likely measurement error of poverty level and CVD risk factors that could have led to an overestimation of CVD risk factor prevalence among adults in extreme poverty. Nonetheless, our results could inform equity discussions for resource allocation and design of effective interventions.


Assuntos
Doenças Cardiovasculares , Pobreza , Humanos , Pobreza/estatística & dados numéricos , Doenças Cardiovasculares/epidemiologia , Doenças Cardiovasculares/economia , Adulto , Prevalência , Masculino , Pessoa de Meia-Idade , Feminino , Fatores de Risco , Hipertensão/epidemiologia , Fatores de Risco de Doenças Cardíacas , Saúde Global/estatística & dados numéricos , Obesidade/epidemiologia , Idoso , Fumar/epidemiologia , Adulto Jovem , Diabetes Mellitus/epidemiologia
2.
Pan Afr Med J ; 37: 351, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33796165

RESUMO

INTRODUCTION: non-communicable diseases (NCDs) are projected to become the leading cause of death in Africa by 2030. Gender and socio-economic differences influence the prevalence of NCDs and their risk factors. METHODS: we performed a secondary analysis of the STEPS 2015 data to determine prevalence and correlation between diabetes, hypertension, harmful alcohol use, smoking, obesity and injuries across age, gender, residence and socio-economic strata. RESULTS: tobacco use prevalence was 13.5% (males 19.9%, females 0.9%, p<0.001); harmful alcohol use was 12.6% (males 18.1%, females 2.2%, p<0.001); central obesity was 27.9% (females 49.5%, males 32.9%, p=0.017); type 2 diabetes prevalence 3.1% (males 2.0%, females 2.8%, p=0.048); elevated blood pressure prevalence was 23.8% (males 25.1%, females 22.6%, p<0.001), non-use of helmets 72.8% (males 89.5%, females 56.0%, p=0.031) and seat belts non-use 67.9% (males 79.8%, females 56.0%, p=0.027). Respondents with <12 years of formal education had higher prevalence of non-use of helmets (81.7% versus 54.1%, p=0.03) and seat belts (73.0% versus 53.9%, p=0.039). Respondents in the highest wealth quintile had higher prevalence of type II diabetes compared with those in the lowest (5.2% versus 1.6%,p=0.008). Rural dwellers had 35% less odds of tobacco use (aOR 0.65, 95% CI 0.49, 0.86) compared with urban dwellers, those with ≥12 years of formal education had 89% less odds of tobacco use (aOR 0.11, 95% CI 0.07, 0.17) compared with <12 years, and those belonging to the wealthiest quintile had 64% higher odds of unhealthy diets (aOR 1.64, 95% CI 1.26, 2.14). Only 44% of respondents with type II diabetes and 16% with hypertension were aware of their diagnosis. CONCLUSION: prevalence of NCD risk factors is high in Kenya and varies across socio-demographic attributes. Socio-demographic considerations should form part of multi-sectoral, integrated approach to reduce the NCD burden in Kenya.


Assuntos
Diabetes Mellitus Tipo 2/epidemiologia , Hipertensão/epidemiologia , Doenças não Transmissíveis/epidemiologia , Adolescente , Adulto , Idoso , Consumo de Bebidas Alcoólicas/epidemiologia , Estudos Transversais , Feminino , Humanos , Quênia/epidemiologia , Masculino , Pessoa de Meia-Idade , Obesidade/epidemiologia , Prevalência , Fatores de Risco , População Rural/estatística & dados numéricos , Fatores Sexuais , Fumar/epidemiologia , Fatores Socioeconômicos , Inquéritos e Questionários , População Urbana/estatística & dados numéricos , Adulto Jovem
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