Mariana Staut Zukeran1, João Valentini Neto1, Carla Vasconcelos Romanini2, Silvana Vieira Bandeira Mingardi2, Gabriela Cabett Cipolli3, Ivan Aprahamian2, Sandra Maria Lima Ribeiro4. 1. School of Public Health, University of Sao Paulo, Av. Dr. Arnaldo, 715, SP, Brazil. 2. Department of Internal Medicine and Division of Geriatrics, Group of Investigation on Multimorbidity and Mental Health in Aging (GIMMA), Jundiaí Medical School, Rua Francisco Telle, 222, Jundiaí, SP, Brazil. 3. School of Arts, Sciences and Humanities, University of Sao Paulo, Rua Arlindo Béttio, 1000, São Paulo, SP, Brazil. 4. School of Public Health, University of Sao Paulo, Av. Dr. Arnaldo, 715, SP, Brazil; Department of Internal Medicine and Division of Geriatrics, Group of Investigation on Multimorbidity and Mental Health in Aging (GIMMA), Jundiaí Medical School, Rua Francisco Telle, 222, Jundiaí, SP, Brazil. Electronic address: smlribeiro@usp.br.
Abstract
BACKGROUND: Appetite loss (AL) in older adults can reduce energy and nutrient intake, increasing the risk of weight loss, sarcopenia, frailty, and ultimately, mortality. The identification of associated factors to AL is important to plan different interventions. AIMS: To identify the association between appetite loss, frailty, and psychosocial factors in community-dwelling older adults. METHODS: Cross-sectional analysis of the cohort study MiMiCS-FRAIL based in Jundiai City, São Paulo, Brazil. Patients 60+ years old were evaluated from January 2019 to August 2020. The AL (dependent variable) was evaluated through the SNAQ questionnaire; the independent variables were: frailty (identified by frailty index-36; FI-36) which is based on the accumulation of deficits; depressive symptoms (GDS scale); ethnicity, and years of formal schooling, both used as proxies of socioeconomic status. The associations were investigated using logistic regression models (crude and multiple). MAIN RESULTS: The final sample included 122 older adults, 58.2% of women, mean age of 71.7 years, 80.3% White, and low educational level (5.8 ± 4.3 years of formal schooling). We found 19.6% of the sample presenting AL. The final regression models showed independent and significant association between AL and age (OR = 1.11; 95%IC = 1.03-1.20; p < 0.01), being non-White (OR = 6.47; 95%IC = 1.63-25.58; p < 0.01), and presence of depressive symptoms (OR = 8.38; 95%IC = 2.31-30.47; p < 0.01). However, years of formal schooling, gender, and FI-36 remained statistically non-significant in the model. CONCLUSION: Our data pointed to the presence of depressive symptoms and social variables as significant factors associated with AL. Further studies with more robust samples or longitudinal design will clarify some unanswered questions of our study.
BACKGROUND: Appetite loss (AL) in older adults can reduce energy and nutrient intake, increasing the risk of weight loss, sarcopenia, frailty, and ultimately, mortality. The identification of associated factors to AL is important to plan different interventions. AIMS: To identify the association between appetite loss, frailty, and psychosocial factors in community-dwelling older adults. METHODS: Cross-sectional analysis of the cohort study MiMiCS-FRAIL based in Jundiai City, São Paulo, Brazil. Patients 60+ years old were evaluated from January 2019 to August 2020. The AL (dependent variable) was evaluated through the SNAQ questionnaire; the independent variables were: frailty (identified by frailty index-36; FI-36) which is based on the accumulation of deficits; depressive symptoms (GDS scale); ethnicity, and years of formal schooling, both used as proxies of socioeconomic status. The associations were investigated using logistic regression models (crude and multiple). MAIN RESULTS: The final sample included 122 older adults, 58.2% of women, mean age of 71.7 years, 80.3% White, and low educational level (5.8 ± 4.3 years of formal schooling). We found 19.6% of the sample presenting AL. The final regression models showed independent and significant association between AL and age (OR = 1.11; 95%IC = 1.03-1.20; p < 0.01), being non-White (OR = 6.47; 95%IC = 1.63-25.58; p < 0.01), and presence of depressive symptoms (OR = 8.38; 95%IC = 2.31-30.47; p < 0.01). However, years of formal schooling, gender, and FI-36 remained statistically non-significant in the model. CONCLUSION: Our data pointed to the presence of depressive symptoms and social variables as significant factors associated with AL. Further studies with more robust samples or longitudinal design will clarify some unanswered questions of our study.
Authors: Neshat Chareh; Eva Kiesswetter; Robert Kob; Anne Hannink; Beate Brandl; Thomas Skurk; Hans Hauner; Cornel C Sieber; Dorothee Volkert Journal: Front Aging Date: 2022-03-18