Prevalence of Multimorbidity of Chronic Noncommunicable Diseases in Brazil: Population-Based Study

Shi, Xin; Lima, Simone Maria da Silva; Mota, Caroline Maria de Miranda; Lü, Ying; Stafford, Randall S.; Pereira, Corintho Viana

doi:10.2196/29693

Cited by 14 publications

(13 citation statements)

References 26 publications

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“…No significant associations were observed in men. Conversely, women living in the South and Midwest regions had a higher multimorbidity prevalence than the others, corroborating a study conducted with a similar population ( 71 ). These outcomes probably reflect socioeconomic disparities in access to health services between sexes and regions.…”

Section: Discussionsupporting

confidence: 87%

Prevalence and factors associated with multimorbidity in adults in Brazil, according to sex: a population-based cross-sectional survey

Pereira

Pedroso

Batista

et al. 2023

Front. Public Health

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IntroductionMultimorbidity, defined as the coexistence of two or more chronic diseases in the same individual, represents a significant health challenge. However, there is limited evidence on its prevalence and associated factors in developing countries, such as Brazil, especially stratified by sex. Thus, this study aims to estimate the prevalence and analyze the factors associated with multimorbidity in Brazilian adults according to sex.MethodsCross-sectional population-based household survey carried out with Brazilian adults aged 18 years or older. The sampling strategy consisted of a three-stage conglomerate plan. The three stages were performed through simple random sampling. Data were collected through individual interviews. Multimorbidity was classified based on a list of 14 self-reported chronic diseases/conditions. Poisson regression analysis was performed to estimate the magnitude of the association between sociodemographic and lifestyle factors with the prevalence of multimorbidity stratified by sex.ResultsA total of 88,531 individuals were included. In absolute terms, the prevalence of multimorbidity was 29.4%. The frequency in men and women was 22.7 and 35.4%, respectively. Overall, multimorbidity was more prevalent among women, the older people, residents of the South and Southeast regions, urban area residents, former smokers, current smokers, physically inactive, overweight, and obese adults. Individuals with complete high school/incomplete higher education had a lower prevalence of multimorbidity than those with higher educational level. The associations between education and multimorbidity differed between sexes. In men, multimorbidity was inversely associated with the strata of complete middle school/incomplete high school and complete high school/incomplete higher education, while in women, the association between these variables was not observed. Physical inactivity was positively associated with a higher prevalence of multimorbidity only in men. An inverse association was verified between the recommended fruit and vegetable consumption and multimorbidity for the total sample and both sexes.ConclusionOne in four adults had multimorbidity. Prevalence increased with increasing age, among women, and was associated with some lifestyles. Multimorbidity was significantly associated with educational level and physical inactivity only in men. The results suggest the need to adopt integrated strategies to reduce the magnitude of multimorbidity, specific by gender, including actions for health promotion, disease prevention, health surveillance and comprehensive health care in Brazil.

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Section: Discussionsupporting

confidence: 87%

Prevalence and factors associated with multimorbidity in adults in Brazil, according to sex: a population-based cross-sectional survey

Pereira

Pedroso

Batista

et al. 2023

Front. Public Health

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“…This study examined the effect of educational attainment on multimorbidity, suggesting that illiterate adults had a higher prevalence of multimorbidity. Along with Brazil, this is the case in other countries, including India, South Africa, and Spain [ 33 ].…”

Section: Discussionmentioning

confidence: 99%

Prediction of Multimorbidity in Brazil: Latest Fifth of a Century Population Study

Li¹,

Huang²,

Lü³

et al. 2023

JMIR Public Health Surveill

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Background Multimorbidity is characterized by the co-occurrence of 2 or more chronic diseases and has been a focus of the health care sector and health policy makers due to its severe adverse effects. Objective This paper aims to use the latest 2 decades of national health data in Brazil to analyze the effects of demographic factors and predict the impact of various risk factors on multimorbidity. Methods Data analysis methods include descriptive analysis, logistic regression, and nomogram prediction. The study makes use of a set of national cross-sectional data with a sample size of 877,032. The study used data from 1998, 2003, and 2008 from the Brazilian National Household Sample Survey, and from 2013 and 2019 from the Brazilian National Health Survey. We developed a logistic regression model to assess the influence of risk factors on multimorbidity and predict the influence of the key risk factors in the future, based on the prevalence of multimorbidity in Brazil. Results Overall, females were 1.7 times more likely to experience multimorbidity than males (odds ratio [OR] 1.72, 95% CI 1.69-1.74). The prevalence of multimorbidity among unemployed individuals was 1.5 times that of employed individuals (OR 1.51, 95% CI 1.49-1.53). Multimorbidity prevalence increased significantly with age. People over 60 years of age were about 20 times more likely to have multiple chronic diseases than those between 18 and 29 years of age (OR 19.6, 95% CI 19.15-20.07). The prevalence of multimorbidity in illiterate individuals was 1.2 times that in literate ones (OR 1.26, 95% CI 1.24-1.28). The subjective well-being of seniors without multimorbidity was 15 times that among people with multimorbidity (OR 15.29, 95% CI 14.97-15.63). Adults with multimorbidity were more than 1.5 times more likely to be hospitalized than those without (OR 1.53, 95% CI 1.50-1.56) and 1.9 times more likely need medical care (OR 1.94, 95% CI 1.91-1.97). These patterns were similar in all 5 cohort studies and remained stable for over 21 years. A nomogram model was used to predict multimorbidity prevalence under the influence of various risk factors. The prediction results were consistent with the effects of logistic regression; older age and poorer participant well-being had the strongest correlation with multimorbidity. Conclusions Our study shows that multimorbidity prevalence varied little in the past 2 decades but varies widely across social groups. Identifying populations with higher rates of multimorbidity prevalence may improve policy making around multimorbidity prevention and management. The Brazilian government can create public health policies targeting these groups, and provide more medical treatment and health services to support and protect the multimorbidity population.

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“…Therefore, tightening social distancing for the elderly and other measures, such as analyzing spatial accessibility and healthcare resources [ 75 ], to reduce the risks they face could positively affect the whole of society. Furthermore, comorbidities are associated with a higher risk of severe cases of COVID-19 that demand specialized clinical care [ 76 ], so Brazilians aged over 60 need to be taken into account since they have almost 12 times higher odds of developing multiple chronic diseases than young adults [ 77 ].…”

Section: Discussionmentioning

confidence: 99%

A spatial-temporal analysis at the early stages of the COVID-19 pandemic and its determinants: The case of Recife neighborhoods, Brazil

et al. 2022

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The outbreak of COVID-19 has led to there being a worldwide socio-economic crisis, with major impacts on developing countries. Understanding the dynamics of the disease and its driving factors, on a small spatial scale, might support strategies to control infections. This paper explores the impact of the COVID-19 on neighborhoods of Recife, Brazil, for which we examine a set of drivers that combines socio-economic factors and the presence of non-stop services. A three-stage methodology was conducted by conducting a statistical and spatial analysis, including clusters and regression models. COVID-19 data were investigated concerning ten dates between April and July 2020. Hotspots of the most affected regions and their determinant effects were highlighted. We have identified that clusters of confirmed cases were carried from a well-developed neighborhood to socially deprived areas, along with the emergence of hotspots of the case-fatality rate. The influence of age-groups, income, level of education, and the access to essential services on the spread of COVID-19 was also verified. The recognition of variables that influence the spatial spread of the disease becomes vital for pinpointing the most vulnerable areas. Consequently, specific prevention actions can be developed for these places, especially in heterogeneous cities.

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Prevalence of Multimorbidity of Chronic Noncommunicable Diseases in Brazil: Population-Based Study

Cited by 14 publications

References 26 publications

Prevalence and factors associated with multimorbidity in adults in Brazil, according to sex: a population-based cross-sectional survey

Prevalence and factors associated with multimorbidity in adults in Brazil, according to sex: a population-based cross-sectional survey

Prediction of Multimorbidity in Brazil: Latest Fifth of a Century Population Study

A spatial-temporal analysis at the early stages of the COVID-19 pandemic and its determinants: The case of Recife neighborhoods, Brazil

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