Estado nutricional antropométrico, desenvolvimento e validação de equações para a estimativa de peso e estatura em idosos institucionalizados
Nutritional deficits are related to the syndrome of frailty, multimorbidity and are associated with mortality in elderly residents in nursing homes. In order to identify the risk of deficits early, anthropometric measures such as weight, height, perimeter and skinfolds may be used. When it is not...
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| Formato: | doctoralThesis |
| Idioma: | pt_BR |
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Brasil
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| Endereço do item: | https://repositorio.ufrn.br/jspui/handle/123456789/28111 |
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| Resumo: | Nutritional deficits are related to the syndrome of frailty, multimorbidity and are
associated with mortality in elderly residents in nursing homes. In order to identify the risk of
deficits early, anthropometric measures such as weight, height, perimeter and skinfolds may be
used. When it is not possible to measure weight and height, they can be estimated by equations.
This study aimed to evaluate anthropometric nutritional status, develop and validate equations
for weight and height estimation in elderly residents in nursing homes. The study was conducted
with elderly living in nursing homes in Brazil. The anthropometric data collected were weight,
height, perimeters and skinfolds. For analyze the anthropometric nutritional status Principal
Component Analysis stratified by sex was performed and the factorial scores of the chosen
model were evaluated in relation to the age group, type of nursing home, racial/ethnic identity,
schooling, burden of disease and functional capacity. Methods of weight and height estimation
were elaborated by linear multiple regression. The regression models developed considered
statistical reliability criteria, such as the coefficient of determination (R²), the standard error of
the estimate and the Akaike Information Criterion (AIC). The prediction equations were
validated by concordance tests such as the Intraclass Correlation Coefficient (ICC) and its
respective confidence interval (95% CI). For all analyzes, p values <0.05 were considered
statistically significant. CPA identified two components: Anthropometric Nutritional Status
(ANS) and Stature (S), which together explained 80.8% of cumulative variance for men and
women. Regarding the development of weight estimation equations, five models with different
anthropometric measurements were developed: (1) using arm perimeter as discriminant
variable (Eq. Ia and Ib; ICC: 0.842), (2) with the best fit statistical analysis for men and women
(Eq. II; ICC: 0.874), (3) and stratified by sex (Eq. IIIa and IIIb; ICC: 0.876), (4) with easy
measures for men and women (Eq. IV; ICC: 0.842) and (5) stratified by sex (Eq. Va and Vb;
ICC: 0.828). Regarding height estimation, five equations were developed with different
anthropometric measurements, which take into account knee height (Eq. I; ICC: 0.863), ulna
length (Eq. II; ICC: 0.766), hemispan (Eq. III; ICC: 0.815), ulna length and hemispan (I Eq. V;
ICC: 0.834) and demispan (Eq. V; ICC: 0.794). The differences observed between the extracted
components occur especially between the mobility restriction variables, the type of nursing
home and the education level. The elderly with restricted mobility, residents in nonprofit
nursing homes and with less education have lower median factor loadings. Five applicable
models for weight estimation in institutionalized elderly and five equations for height estimation were developed and validated. The choice of using equations should take into
consideration the possibility of performing a certain measure. To nursing homes were sent
reports with the nutritional assessment of the elderly and a practical manual with the equations
developed by present study to contribute to the monitoring of the anthropometric nutritional
status. |
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