Do sociodemographic, behavioral or health status variables affect longitudinal anthropometric changes in older adults? Population‐based cohort study in Southern Brazil

Goes, Vanessa Fernanda; Wazlawik, Elisabeth; d’Orsi, Eleonora; Navarro, Albert; González‐Chica, David Alejandro

doi:10.1111/ggi.13024

Cited by 2 publications

(2 citation statements)

References 24 publications

(37 reference statements)

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“…Many studies confirmed the role of socioeconomic factors in the determination of healthy ageing (Supplementary Material, Table 3). Interestingly there are studies which exclusively emphasised the role of childhood or early life background of individuals in the determination of healthy life in the old age (Carrillo-Vega et al, 2019; Castro-Costa et al, 2011; Gao et al, 2017; Goes et al, 2017; Grimard et al, 2010; Gu et al, 2011; Jiang et al, 2019; Mejia-Arango & Gutierrez, 2011; Sadeghi et al, 2015; Saenz & Wong, 2016; Sha et al, 2018; Shen & Zeng, 2014; Torres et al, 2018b). These studies accentuate why considering causality effects is relevant in healthy ageing studies as health in old age is an accumulation of multiple factors influenced over time.…”

Section: Resultsmentioning

confidence: 99%

Healthy Ageing in Low and Middle-Income Countries; A Systematic Scoping Review

Irshad

Dash

Muraleedharan

2022

Journal of Health Management

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Healthy ageing is a new paradigm that describes the possibility of better ageing experience in contrast to the traditional notion of ageing. The aim of this scoping review was to map literature on healthy ageing in the context of low and middle-income countries (LMICs). A five-step scoping review procedure was used to synthesise the conceptualisation of healthy ageing and its measurement approach and to summarise key evidences on healthy ageing. Our descriptive summary analysis shows that the majority of the studies conceptualised healthy ageing under physical capabilities, cognitive functions, metabolic and physiological health and psychological well-being domains with more of objective measurement approach. We identified a number of studies that can be relevant to consider for public health policy. Future research should also focus on neurobiological ageing aspects as such studies were found to be very rare in the review. Our review identified that there is limited number of studies conducted in some LMICs where the growth of population ageing is an emerging concern.

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Section: Resultsmentioning

confidence: 99%

Healthy Ageing in Low and Middle-Income Countries; A Systematic Scoping Review

Irshad

Dash

Muraleedharan

2022

Journal of Health Management

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“…A few studies associated nutritional risk and marital status, but other studies observed some association with weight loss and sarcopenia. Alexandre et al ( 40 ) described an association between absence of marital life and sarcopenia to older adults who participated of the Health, Well-being, and Aging study in 2010 (SABE study), while Góes et al ( 41 ) related that unmarried men lose weight at a higher rate, showing a higher risk of sarcopenia for older adults living in Southern Brazil (EpiFloripa Study).…”

Section: Discussionmentioning

confidence: 99%

Quality of life and socio-demographic factors associated with nutritional risk in Brazilian community-dwelling individuals aged 80 and over: cluster analysis and ensemble methods

Brech,

da Silva,

Alonso

et al. 2024

Front. Nutr.

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IntroductionThe aim of the present study was to use cluster analysis and ensemble methods to evaluate the association between quality of life, socio-demographic factors to predict nutritional risk in community-dwelling Brazilians aged 80 and over.MethodsThis cross-sectional study included 104 individuals, both sexes, from different community locations. Firstly, the participants answered the sociodemographic questionnaire, and were sampled for anthropometric data. Subsequently, the Mini-Mental State Examination (MMSE) was applied, and Mini Nutritional Assessment Questionnaire (MAN) was used to evaluate their nutritional status. Finally, quality of life (QoL) was assessed by a brief version of World Health Organizations’ Quality of Life (WHOQOL-BREF) questionnaire and its older adults’ version (WHOQOL-OLD).ResultsThe K-means algorithm was used to identify clusters of individuals regarding quality-of-life characteristics. In addition, Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) algorithms were used to predict nutritional risk. Four major clusters were derived. Although there was a higher proportion of individuals aged 80 and over with nutritional risk in cluster 2 and a lower proportion in cluster 3, there was no statistically significant association. Cluster 1 showed the highest scores for psychological, social, and environmental domains, while cluster 4 exhibited the worst scores for the social and environmental domains of WHOQOL-BREF and for autonomy, past, present, and future activities, and intimacy of WHOQOL-OLD.ConclusionHandgrip, household income, and MMSE were the most important predictors of nutritional. On the other hand, sex, self-reported health, and number of teeth showed the lowest levels of influence in the construction of models to evaluate nutritional risk. Taken together, there was no association between clusters based on quality-of-life domains and nutritional risk, however, predictive models can be used as a complementary tool to evaluate nutritional risk in individuals aged 80 and over.

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Do sociodemographic, behavioral or health status variables affect longitudinal anthropometric changes in older adults? Population‐based cohort study in Southern Brazil

Cited by 2 publications

References 24 publications

Healthy Ageing in Low and Middle-Income Countries; A Systematic Scoping Review

Healthy Ageing in Low and Middle-Income Countries; A Systematic Scoping Review

Quality of life and socio-demographic factors associated with nutritional risk in Brazilian community-dwelling individuals aged 80 and over: cluster analysis and ensemble methods

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