Prevalence and factors associated with sarcopenia among Brazilian older adults: An exploratory network analysis

OBJECTIVES

This study aimed to verify the prevalence of sarcopenia and its associations with sociodemographic, clinical and psychological factors in community-dwelling older adults.

STUDY DESIGN

A randomized cross-sectional study was extracted from a probabilistic cluster conducted on individuals aged 65 years or older residing in the community.

METHODS

Sarcopenia was defined according to the criteria of the European Working Group on Sarcopenia in Older People (EWGSOP2). Body composition was assessed using dual-energy X-ray absorptiometry (DXA). Associations were analyzed using networks based on mixed graphical models. Predictability indices of the estimated networks were assessed using the proportion of explained variance for numerical variables and the proportion of correct classification for categorical variables.

RESULTS

The study included 278 participants, with a majority being female (61 %). The prevalence of sarcopenia was 39.57 %. Among those with sarcopenia, 67 % were women and 33 % were men. In the network model, age, race, education, family income, bone mass, depression, cardiovascular disease, diabetes, total cholesterol levels and rheumatism were associated with sarcopenia. The covariates demonstrated a high accuracy (62.9 %) in predicting sarcopenia categories.

CONCLUSION

The prevalence of sarcopenia was high, especially in women. In addition, network analysis proved useful in visualizing complex relationships between sociodemographic and clinical factors with sarcopenia. The results suggest early screening of sarcopenia for appropriate treatment of this common geriatric syndrome in older adults in Brazil.

Machine Learning Models to Predict Future Frailty in Community-Dwelling Middle-Aged and Older Adults: The ELSA Cohort Study

BACKGROUND

Machine learning (ML) models can be used to predict future frailty in the community setting. However, outcome variables for epidemiologic data sets such as frailty usually have an imbalance between categories, that is, there are far fewer individuals classified as frail than as nonfrail, adversely affecting the performance of ML models when predicting the syndrome.

METHODS

A retrospective cohort study with participants (50 years or older) from the English Longitudinal Study of Ageing who were nonfrail at baseline (2008-2009) and reassessed for the frailty phenotype at 4-year follow-up (2012-2013). Social, clinical, and psychosocial baseline predictors were selected to predict frailty at follow-up in ML models (Logistic Regression, Random Forest [RF], Support Vector Machine, Neural Network, K-nearest neighbor, and Naive Bayes classifier).

RESULTS

Of all the 4 378 nonfrail participants at baseline, 347 became frail at follow-up. The proposed combined oversampling and undersampling method to adjust imbalanced data improved the performance of the models, and RF had the best performance, with areas under the receiver-operating characteristic curve and the precision-recall curve of 0.92 and 0.97, respectively, specificity of 0.83, sensitivity of 0.88, and balanced accuracy of 85.5% for balanced data. Age, chair-rise test, household wealth, balance problems, and self-rated health were the most important frailty predictors in most of the models trained with balanced data.

CONCLUSIONS

ML proved useful in identifying individuals who became frail over time, and this result was made possible by balancing the data set. This study highlighted factors that may be useful in the early detection of frailty.

COVID-19 infection rate and time spent at home: analysis of the beginning of the pandemic

Background and Objectives: Evidence suggests that the failure of epidemiological control impedes the resumption of socioeconomic activities.  Therefore, this study aimed to describe epidemiological aspects and the pattern of mobility on each continent and to verify the association between the COVID-19 infection rate and time spent at home. Methods: We analyzed reports from Global Positioning System of 97 countries and their epidemiological indicators until May 27, 2020. Results: Cases of COVID-19 ranged from 22 to 1,745,803, and deaths ranged from 0 to 102,107. The highest rates per 100,000 population were observed in Europe and America. Approximately 54% of COVID-19 cases occurred in America and 51% of deaths in Europe. Countries reduced mobility in retail and recreation (-43.45%±20.42%), grocery and pharmacy (-17.95%±20.82%), parks (-18.77%±37.34%), transit stations (-43.09%±20.31%), workplaces (-21.74%±19.92%), and increased time spent at home (13.00%±8.80%). Linear regression showed that European inhabitants stayed at home less when compared those on the American continent (β=-4.933, SE=0.976, p<.001). In addition, every unit increase in the infection rate per 100,000 population increased 0.005 points in the mean time spent at home (β=0.005, SE=0.001, p<.001). Conclusions: We provide evidence that increased infection rate of COVID-19 is associated with increased length of stay at home. As a main lesson, COVID-19 showed that in the absence of pharmacological resources, government authorities need to act quickly to contain the spread of infectious diseases.

How do the factors associated with frailty change with sex? An exploratory network analysis

BACKGROUND

It is important to study multiple social, physical and psychosocial factors associated with frailty in populations characterized by social and health disparities, such as men and women.

METHODS

This was a cross-sectional population-based study with older adults ≥65 years from the FIBRA (Frailty in Brazilian Older Adults) 2008-2009 study. We carried out a comparative analysis of the factors associated with the frailty phenotype in older men (N=706) and women (N=1.251) using networks based on mixed graphical models (MGM) according to sex.

RESULTS

In the male network, frailty was most strongly associated with years of schooling, overall satisfaction with life and falls; in the female network, the syndrome was associated with satisfaction with problem solving, depression and diabetes in addition to years of schooling. Furthermore, permutation tests showed that the networks for males and females were statistically different in terms of their structure, the global strength of the relationships and the strength of the relationships between frailty and diabetes; frailty and falls; frailty and depression; frailty and overall satisfaction with life; and frailty and satisfaction with problem solving (p<0.05). The walktrap network cluster detection algorithm revealed that in men, frailty was in a physical and social dimension while in women the syndrome was in a cardiometabolic and psychosocial dimension.

CONCLUSIONS

Network analysis showed that different factors are associated with frailty for each sex. The findings suggest that different strategies for dealing with frailty should be adopted for men and women so that care and prevention efforts can be directed appropriately.

The use of Bayesian network models to identify factors related to frailty phenotype and health outcomes in middle-aged and older persons

BACKGROUND

Studies on frailty frequently only include older persons. The mapping of factors related to this syndrome and negative outcomes associated with it, also in middle age, may assist in health strategies to each age group.

OBJECTIVES

To investigate social and health factors related to the frailty phenotype and to analyze the probabilistic relationships between frailty, falls and hospitalization in middle-aged and older persons.

METHODS

This is a cross-sectional study using data for 4442 middle-aged (50-59 years) and older participants (60 years or older) from the Brazilian Longitudinal Study of Aging (ELSI-Brazil) 2015 and 2016. Bayesian network models were estimated with the score-based hill-climbing algorithm to identify factors associated with frailty, falls and hospitalization.

RESULTS

Mean age was 63.7 years, and prevalence of frailty was 8.5 % and 11.9 % among middle-aged and older participants, respectively. In the former, the probability of frailty increased when "poor" self-rated memory was considered in the model; and in the latter, the probability of frailty was greatest among individuals who did not participate socially and had the lowest level of education. In both age groups, frailty was an important factor that influenced the probability of negative health outcomes such as falls and hospitalization. However, this result depended on combinations of health factors in each sample.

CONCLUSIONS

This study has identified potential vulnerabilities that should be considered when undertaking a comprehensive assessment of middle-aged and older persons and developing suitable health strategies for each of these phases of life.

Falha no diagnóstico e no tratamento medicamentoso da hipertensão arterial em idosos brasileiros – Estudo FIBRA

Resumo O objetivo deste estudo foi investigar prevalências de falhas no diagnóstico, no uso de anti-hipertensivos e na eficácia do tratamento medicamentoso da hipertensão, e a associação destes parâmetros com variáveis sociodemográficas, de saúde e acesso ao serviço de saúde em idosos não institucionalizados. O estudo foi descritivo, transversal, com 3478 idosos, analisados separadamente em regiões Norte/Nordeste e Sul/Sudeste. Utilizou-se a regressão múltipla de Poisson para estimar razões de prevalência brutas e ajustadas pelo tipo de serviço de saúde utilizado. Do total, 29,6% dos idosos apresentaram falhas no diagnóstico, 4,6% no uso de anti-hipertensivos e 65,3% na eficácia medicamentosa. A falha no diagnóstico associou-se ao sexo masculino, menos morbidades, ter um companheiro, raça/cor branca, ter acesso ao convênio ou serviço privado de saúde, possuir renda pessoal inferior/média e ainda trabalhar. A falha no uso de anti-hipertensivos esteve associada à renda pessoal inferior/média e trabalhar. As falhas no manejo da hipertensão são prevalentes em idosos não institucionalizados. Há necessidade de ações que minimizem os impactos negativos destas insuficiências em saúde, em um país com diferenças sociais, econômicas e étnicas.

Survival of elderly outpatients: effects of frailty, multimorbidity and disability

This study aims to analyze the impact of frailty, multimorbidity and disability on the survival of elderly people attended in a geriatric outpatient facility, and identify the clinical risk factors associated with death. It is a longitudinal study, with 133 elderly people initially evaluated in relation to frailty, multimorbidity (simultaneous presence of three or more chronic diseases) and disability in Daily Life Activities. The Kaplan Meier method was used to analyze survival time, and the Cox regression was used for association of the clinical factors with death. In follow-up over six years, 21.2% of the participants died, survival being lowest among those who were fragile (p < 0.05). The variables frailty (HR = 2.26; CI95%: 1.03-4.93) and Chronic Renal Insufficiency (HR = 3.00; CI95%: 1.20-7.47) were the factors of highest risk for death in the multivariate analysis. Frailty had a negative effect on the survival of these patients, but no statistically significant association was found in relation to multimorbidity or disability. Tracking of vulnerabilities in the outpatient geriatric service is important, due to the significant number of elderly people with geriatric syndromes that use this type of service, and the taking of decisions on directions for care of these individuals.