Analysis on epidemiological characteristics of central obesity residents in Shandong Province in 2007
FU Zhen-ta
Abstract
FU Zhen-ta
Abstract
Objective To identify characteristics of central obesity and its influencing factors among residents aged between 15 and 69 in Shandong Province and provide evidence for intervention.Methods Subjects who were sampled by multi-stage stratified randomized sampling were investigated by questionnaire.The data were analyzed by SPSS 13.0.Results The sample size was 3 839.The average waist circumference(WC) was(82.77±10.43)cm,along with male(84.75±10.00)cm and female(81.05±10.50)cm.The central obesity prevalence was 49.20%(male 47.55%,and female 50.63%).The standard obesity prevalence was 42.75%(male 44.59%,female 41.26%).Logistic regression indicated that sex, age,habitation and diabetes were major risk factors of central obesity.Conclusions The waist circumference of residents in Shandong Province is big and the prevalence of central obesity is high.It is necessary to enhance policy and measurements for controlling central obesity.
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Objective To identify characteristics of central obesity and its influencing factors among residents aged between 15 and 69 in Shandong Province and provide evidence for intervention.Methods Subjects who were sampled by multi-stage stratified randomized sampling were investigated by questionnaire.The data were analyzed by SPSS 13.0.Results The sample size was 3 839.The average waist circumference(WC) was(82.77±10.43)cm,along with male(84.75±10.00)cm and female(81.05±10.50)cm.The central obesity prevalence was 49.20%(male 47.55%,and female 50.63%).The standard obesity prevalence was 42.75%(male 44.59%,female 41.26%).Logistic regression indicated that sex, age,habitation and diabetes were major risk factors of central obesity.Conclusions The waist circumference of residents in Shandong Province is big and the prevalence of central obesity is high.It is necessary to enhance policy and measurements for controlling central obesity.
Key concepts: Waist, Obesity, Medicine, Logistic regression, Circumference, Epidemiology, Demography, Stratified sampling