TY - JOUR
T1 - Obesity as a risk factor for developing functional limitation among older adults
T2 - A conditional inference tree analysis
AU - Cheng, Feon W.
AU - Gao, Xiang
AU - Bao, Le
AU - Mitchell, Diane C.
AU - Wood, Craig
AU - Sliwinski, Martin J.
AU - Smiciklas-Wright, Helen
AU - Still, Christopher D.
AU - Rolston, David D.K.
AU - Jensen, Gordon L.
N1 - Publisher Copyright:
© 2017 The Obesity Society
PY - 2017/7
Y1 - 2017/7
N2 - Objective: To examine the risk factors of developing functional decline and make probabilistic predictions by using a tree-based method that allows higher order polynomials and interactions of the risk factors. Methods: The conditional inference tree analysis, a data mining approach, was used to construct a risk stratification algorithm for developing functional limitation based on BMI and other potential risk factors for disability in 1,951 older adults without functional limitations at baseline (baseline age 73.1 ± 4.2 y). We also analyzed the data with multivariate stepwise logistic regression and compared the two approaches (e.g., cross-validation). Over a mean of 9.2 ± 1.7 years of follow-up, 221 individuals developed functional limitation. Results: Higher BMI, age, and comorbidity were consistently identified as significant risk factors for functional decline using both methods. Based on these factors, individuals were stratified into four risk groups via the conditional inference tree analysis. Compared to the low-risk group, all other groups had a significantly higher risk of developing functional limitation. The odds ratio comparing two extreme categories was 9.09 (95% confidence interval: 4.68, 17.6). Conclusions: Higher BMI, age, and comorbid disease were consistently identified as significant risk factors for functional decline among older individuals across all approaches and analyses.
AB - Objective: To examine the risk factors of developing functional decline and make probabilistic predictions by using a tree-based method that allows higher order polynomials and interactions of the risk factors. Methods: The conditional inference tree analysis, a data mining approach, was used to construct a risk stratification algorithm for developing functional limitation based on BMI and other potential risk factors for disability in 1,951 older adults without functional limitations at baseline (baseline age 73.1 ± 4.2 y). We also analyzed the data with multivariate stepwise logistic regression and compared the two approaches (e.g., cross-validation). Over a mean of 9.2 ± 1.7 years of follow-up, 221 individuals developed functional limitation. Results: Higher BMI, age, and comorbidity were consistently identified as significant risk factors for functional decline using both methods. Based on these factors, individuals were stratified into four risk groups via the conditional inference tree analysis. Compared to the low-risk group, all other groups had a significantly higher risk of developing functional limitation. The odds ratio comparing two extreme categories was 9.09 (95% confidence interval: 4.68, 17.6). Conclusions: Higher BMI, age, and comorbid disease were consistently identified as significant risk factors for functional decline among older individuals across all approaches and analyses.
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U2 - 10.1002/oby.21861
DO - 10.1002/oby.21861
M3 - Article
C2 - 28544480
AN - SCOPUS:85019711032
SN - 1930-7381
VL - 25
SP - 1263
EP - 1269
JO - Obesity
JF - Obesity
IS - 7
ER -