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AlzRisk Paper Detail

Reference: Gustafson, 2003
Cohort: The H-70 Gerontological and Geriatric Population Studies
Risk Factor: Obesity

Average Follow-up Time Detail
Only females (n=226) were included in the analyses due to small numbers for men. The researches examined the association of AD with BMI at three separate ages, 70,75, and 79, each representing a row in this tables. One hundred and thirty-one women were used in this particular analysis of BMI at age 79.

Exposure Detail
The authors evaluated the associations between BMI at ages 70, 75 and 79 and AD, separately. This row of results correspond to the association between BMI at age 79 and AD.

Method of BMI ascertainment: technician measurement

"Anthropometric measurements were standardized during all follow-up years and were conducted in the morning with the participants wearing light clothing. Body weight was recorded to the nearest 0.1 kg, and body height was measured to the nearest centimeter. Body mass Index is a weight-per-height measurement and was calculated as kilogram per meter squared."

Ethnicity Detail
All participants were residents of Goteborg, Sweden. No other information on ethnicity or race was reported.

Age Detail
For this analysis, the BMI of the participants were measured at age 79.

Screening and Diagnosis Detail
Screening Method:
DSM IIIR - dementiaDiagnostic and Statistical Manual III - Revised - dementia

AD Diagnosis:
NINCDS ADRDA National Institute of Neurological and Communicative Diseases and Stroke/Alzheimer's Disease and Related Disorders Association Criteria (McKhann 1984)

Total Dementia Definition: Dementia via DSM-III-R clinical criteria

Covariates & Analysis Detail
Analysis Type:
Cox proportional hazards regression

"Cox proportional hazards regression analyses were used to calculate the hazard ratios for factors related to incident dementia, AD, and VaD among women at 70 to 79 years and 79 to 88 years of age. Time at risk was calculated to age 88 years, death, or diagnosis of dementia. Men were not included in regression analyses because of low participant numbers in our sample. Univariate regression analyses were used to evaluate the following potential confounders of the BMI-dementia relationship: apolipoprotein E4 phenotype, DBP, cardiovascular disease, stroke, diabetes mellitus, cancer, late-life depression, education, socioeconomic status, cigarette smoking, alcohol intake, and use of antihypertensive medications. The relationship between these factors and BMI was also assessed by means of analysis of variance and 2 analysis, and the interaction between DBP and BMI was tested in regression models. Variables were included in multivariate regression models if they met the criterion of P<.05 in univariate analyses. Thus, final regression models included measurements of BMI and DBP at ages 70, 75, and 79 years; cardiovascular disease; cigarette smoking; socioeconomic status; and treatment for hypertension. The BMI and DBP were modeled as continuous variables. Two levels of socioeconomic status, middle or upper vs working class (working class was the referent group), were entered into each model. Cardiovascular disease and treatment for hypertension were considered as dichotomous variables."

"Covariates were entered into Cox proportional hazards regression models by a single-step approach. In all analyses, concurrent (during 1 examination year) measures of BMI, DBP, smoking, and cardiovascular disease were included in individual models. Risk of dementia was calculated per 1.0 increment of BMI, as well as per 1-SD increment of BMI. Two-tailed tests were used in all analyses at a significance level of P<.05."

AD Covariates:
CVDcardiovascular disease
DBPdiastolic blood pressure
SMsmoking status
SESsocioeconomic status
THTtreatment for hypertension

TD Covariates:
CVDcardiovascular disease
DBPdiastolic blood pressure
SMsmoking status
SESsocioeconomic status
THTtreatment for hypertension