Predictors of short-term mortality, cognitive and physical decline in older adults in northwest Russia: a population-based prospective cohort study
Aged, 80 and over
Male
2. Zero hunger
Frailty
Nutritional Status
Comorbidity
Russia
3. Good health
03 medical and health sciences
Sex Factors
0302 clinical medicine
Risk Factors
Forced Expiratory Volume
Physical Endurance
Humans
Cognitive Dysfunction
Female
Prospective Studies
Mortality
Aged
Proportional Hazards Models
DOI:
10.1007/s40520-016-0613-7
Publication Date:
2016-08-05T02:17:10Z
AUTHORS (4)
ABSTRACT
The classical phenotype, accumulated deficit model and self-report approach of frailty were found not useful in older adults in northwest Russia. More research is needed to identify predictors of adverse outcomes in this population.The aim of this study is to identify predictors of mortality, autonomy and cognitive decline in a population that is characterized by a high cardiovascular morbidity and mortality rate.A population-based prospective cohort study of 611 community-dwelling individuals 65+. Anthropometry, medical history nutritional status were recorded. An evaluation of cognitive, physical and autonomy function, spirometry, and laboratory tests were performed. The total follow-up was 5 years. Multiple imputation, backward stepwise Cox regression analysis, C-statistic, risk reclassification analysis and the bootstrapping techniques were used to analyze the data.We found that the combination of increasing age, male sex, low physical function, low mid-arm muscle area, low forced expiratory volume in 1 s and anemia was associated with mortality for people 65+. The substitution of anemia with anemia + high level of C-reactive protein (hCRP) and the addition of high brain natriuretic peptide (hBNP) levels improved the classification of older persons at risk for mortality.The combination of low physical function, low mid-arm muscle area, low forced expiratory volume in 1 s, anemia with hCRP levels and hBNP identified older persons at a higher risk for mortality. These predictors may be used for the development of a prediction model to detect older people who are at risk for adverse health outcomes in northwest Russia.
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