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Association of adiposity status and changes in early to mid-adulthood with incidence of Alzheimer's disease.


ABSTRACT: Adiposity status and change are potential risk factors for Alzheimer's disease (AD). The authors used data on 2,322 participants in the Baltimore Longitudinal Study of Aging to analyze the relation between AD incidence and adiposity in Cox proportional hazards models, with adjustment for sociodemographic factors and smoking status. Body mass index (BMI; weight (kg)/height (m)(2)) and waist circumference at specific ages were predicted by empirical Bayes estimators from mixed-effects regression models. After a median of 23.4 years of follow-up between 1958 and 2006, 187 participants developed AD. Among men, being underweight (BMI or=30) at age 30, 40, or 45 years and jointly centrally obese (waist circumference >or=80th percentile) at age 30, 35, or 50 years increased AD risk (HR = 6.57, 95% CI: 1.96, 22.02). Women who lost weight (BMI change <10th percentile) between ages 30 and 45 years were also at increased risk (HR = 2.02, 95% CI: 1.06, 3.85). Weight gain among men (BMI change >90th percentile) between ages 30 and 50 years increased AD risk (HR = 3.70, 95% CI: 1.43, 9.56). Future studies should identify age- and gender-specific optimal weights and weight-loss strategies for preventing AD and investigate potential mechanisms.

SUBMITTER: Beydoun MA 

PROVIDER: S-EPMC2582058 | biostudies-literature | 2008 Nov

REPOSITORIES: biostudies-literature

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Association of adiposity status and changes in early to mid-adulthood with incidence of Alzheimer's disease.

Beydoun May A MA   Lhotsky April A   Wang Youfa Y   Dal Forno Gloria G   An Yang Y   Metter E Jeffrey EJ   Ferrucci Luigi L   O'Brien Richard R   Zonderman Alan B AB  

American journal of epidemiology 20081003 10


Adiposity status and change are potential risk factors for Alzheimer's disease (AD). The authors used data on 2,322 participants in the Baltimore Longitudinal Study of Aging to analyze the relation between AD incidence and adiposity in Cox proportional hazards models, with adjustment for sociodemographic factors and smoking status. Body mass index (BMI; weight (kg)/height (m)(2)) and waist circumference at specific ages were predicted by empirical Bayes estimators from mixed-effects regression m  ...[more]

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