The social determinants of multimorbidity in South Africa

Alaba, Olufunke A.; Chola, Lumbwe

doi:10.1186/1475-9276-12-63

Cited by 106 publications

(172 citation statements)

References 46 publications

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“…Despite difficulties that have been mentioned in systematic reviews regarding comparisons of the prevalences of multimorbidity in different countries, 7,38 the prevalence of multimorbidity of 33.1% that we observed in our study was close to the prevalences found in developed countries such as the Netherlands, 39 Canada 13 and Australia, 40 but it was considerably higher than in other LMIC countries. [19][20][21] As expected, the prevalence of multimorbidity increased with age and was higher among women than among men, across educational levels. Both obesity and smoking status showed high prevalence in the study population and these had significant relationships with the outcome, albeit in different ways.…”

Section: Discussionsupporting

confidence: 69%

“…For example, the prevalence of multimorbidity was found to be only 4% among South African adults and 70% of them were women. 19 For this reason, considering that the construct of multimorbidity measures not only the current health status of a population but also the health inequalities inherent to the healthcare system, it is crucial to understand the complexity of this phenomenon. Moreover, beyond these absolute inequalities, there is a relative difference among people relating to the way in which they interact with healthcare services, and this relates both to healthcare professionals and to patients.…”

Section: Women Menmentioning

confidence: 99%

“…association between low socioeconomic position and multimorbidity, [19][20][21] but the determinants of multimorbidity are still insufficiently studied in LMIC. 22,23 The few studies conducted in Brazil were restricted to specific populations.…”

mentioning

confidence: 99%

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Educational inequality in Rio de Janeiro and its impact on multimorbidity: evidence from the Pró-Saúde study. A cross-sectional analysis

2018

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BACKGROUND: Information about multimorbidity is scarce in developing countries. This study aimed to estimate the association of educational attainment with occurrences of multimorbidity in a population of public employees on university campuses in Rio de Janeiro. DESIGN AND SETTING: We conducted cross-sectional analyses on baseline data (1999-2001) from 3,253 participants in the Pró-Saúde study, conducted in Brazil. METHODS: The prevalence of multimorbidity, defined as a self-reported history of medical diagnoses of two or more chronic conditions, was estimated according to sex, age, smoking, obesity and educational level. The association between education and multimorbidity was estimated using odds ratios (OR) and the relative and slope indices of inequality, in order to quantify the degree of educational inequality among individuals with multimorbidity in this population. RESULTS: Greater age, female sex, smoking and obesity had direct associations with multimorbidity; and tobacco exposure and obesity also showed direct relationships with poorer educational level. There was a monotonic inverse linear trend between educational level and the presence of multimorbidity among women, with twice the odds (OR 2.47; 95% confidence interval, CI: 1.42-4.40) between extremities of schooling categories. There was excess multimorbidity of 22% at the lowest extremity of schooling, thus showing that women with worse educational status were more affected by the outcome. No trend and no excess multimorbidity was seen among men. CONCLUSIONS: Educational inequality is an important determinant for development of multimorbidity. Men and women experience its effect differently. Researchers need to consider that sex may be an effect modifier in multimorbidity studies.

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Section: Discussionsupporting

confidence: 69%

Section: Women Menmentioning

confidence: 99%

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Educational inequality in Rio de Janeiro and its impact on multimorbidity: evidence from the Pró-Saúde study. A cross-sectional analysis

2018

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“…Individuals with multimorbidity, especially the elderly, tend to experience a greater number of hospitalizations, use multiple medications simultaneously and thereby increase their susceptibility to adverse effects. Thus, the presence of multimorbidity increases the risk of mortality, generates physical and mental problems [3][4][5] and negatively influences quality of life [7][8][9] . It therefore results in greater demands on health care, representing a major challenge for health systems around the world 10,11 , especially as the care involved is more complex 12 .…”

Section: Introductionmentioning

confidence: 99%

“…The prevalence of multimorbidity among elderly persons is high (50 to 98%) 10,11 and its occurrence is associated with advanced age, the female gender, a low socioeconomic level and an unhealthy lifestyle 14,15 . In addition, studies indicate that self-perception of health is often described as negative, due to the occurrence of social, physical or mental disabilities, thus impairing quality of life 8,9,16,17 . The topic is highly relevant, as clinical studies of the elderly often include comorbidity 11 and information on multimorbidity provides support for the improvement of therapeutic strategies.…”

Section: Introductionmentioning

confidence: 99%

Multimorbidity associated with polypharmacy and negative self-perception of health

Cavalcanti

Doring

Portella

et al. 2017

Rev. bras. geriatr. gerontol.

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Objective: to verify the association between the multimorbidity of the elderly and sociodemographic variables, self-perception of health and polypharmacy. Method: a cross-sectional study was performed. The research data was collected using the Health, Well-Being and Aging questionnaire. The sample was composed of 676 people aged 60 years or more, who were residents of small towns in the north of the state of Rio Grande do Sul, Brazil. The dependent variable was multimorbidity, that is, the occurrence of two or more chronic non-communicable diseases in the same person. The independent variables were demographic, socioeconomic and health-related characteristics. Poisson's raw and robust regression model was used to analyze the effect of the independent variables in relation to the outcome and p was considered significant when <0.05. Result: among the elderly interviewed, 45% presented multimorbidity, 51.1% reported a selfperception of poor/very poor health and 37.1% used polypharmacy. After the analysis was adjusted to the occurrence of multimorbidity, association with the following variables was found: health perception (regular/poor/very poor) PR=1.15 (CI95%; 1.09 -1.22) and use of polypharmacy PR=1.29 (CI95%; 1.22 -1.35). Conclusion: Multimorbidity may interfere negatively in the self-perception of health of the elderly contributing to increased medicine consumption.

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Epidemiology and predictors of multimorbidity in Kharameh cohort study: A population‐based cross‐sectional study in southern Iran

Moftakhar

Rezaeianzadeh

Johari‬

et al. 2022

Health Science Reports

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Background and Aim Multimorbidity is one of the problems and concerns of public health. The aim of this study was to estimate the prevalence and identify the risk factors associated with multimorbidity based on the data of the Kherameh cohort study. Methods This cross‐sectional study was performed on 10,663 individuals aged 40–70 years in the south of Iran in 2015 to 2017. Demographic and behavioral characteristics were investigated. Multimorbidity was defined as the coexistence of two or more of two chronic diseases in a person. In this study, the prevalence of multimorbidity was calculated. Logistic regression was used to identify the predictors of multimorbidity. Results The prevalence of multimorbidity was 24.4%. The age‐standardized prevalence rate was 18.01% in males and 29.6% in females. The most common underlying diseases were gastroesophageal reflux disease with hypertension (33.5%). Multiple logistic regression results showed that the age of 45–55 years (adjusted odds ratio [OR adj] ] = 1.22, 95% confidence interval [CI], 1.07–1.38), age of over 55 years (OR adj = 1.21, 95% CI, 1.06–1.37), obesity (OR adj = 3.65, 95% CI, 2.55–5.24), and overweight (OR adj = 2.92, 95% CI, 2.05–4.14) were the risk factors of multimorbidity. Also, subjects with high socioeconomic status (OR adj = 1.27, 95% CI, 1.1–1.45) and very high level of socioeconomic status (OR adj = 1.53, 95% CI, 1.31–1.79) had a higher chance of having multimorbidity. The high level of education, alcohol consumption, having job, and high physical activity had a protective role against it. Conclusion The prevalence of multimorbidity was relatively high in the study area. According to the results of our study, age, obesity, and overweight had an important effect on multimorbidity. Therefore, determining interventional strategies for weight loss and control and treatment of chronic diseases, especially in the elderly, is very useful.

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The social determinants of multimorbidity in South Africa

Cited by 106 publications

References 46 publications

Educational inequality in Rio de Janeiro and its impact on multimorbidity: evidence from the Pró-Saúde study. A cross-sectional analysis

Educational inequality in Rio de Janeiro and its impact on multimorbidity: evidence from the Pró-Saúde study. A cross-sectional analysis

Multimorbidity associated with polypharmacy and negative self-perception of health

Epidemiology and predictors of multimorbidity in Kharameh cohort study: A population‐based cross‐sectional study in southern Iran

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