Title of article :
Changes in Obesity Odds Ratio among Iranian Adults, since 2000: Quadratic Inference Functions Method
Author/Authors :
Bakhshi, Enayatollah Department of Biostatistics - University of Social Welfare and Rehabilitation Sciences - Tehran, Iran , Etemad, Koorosh Ministry of Health and Medical Education - Tehran, Iran , Seifi, Behjat Department of Physiology - Medicine School - Tehran University of Medical Sciences - Tehran, Iran , Mohammad, Kazem Department of Biostatistics - School of Public Health and Institute of Public Health Research - Tehran University of Medical Sciences - Tehran, Iran , Biglarian, Akbar Department of Biostatistics - University of Social Welfare and Rehabilitation Sciences - Tehran, Iran , Koohpayehzadeh, Jalil Ministry of Health and Medical Education - Tehran, Iran
Abstract :
Background. Monitoring changes in obesity prevalence by risk factors is relevant to public health programs that focus on reducing
or preventing obesity. The purpose of this paper was to study trends in obesity odds ratios (ORs) for individuals aged 20 years and
older in Iran by using a new statistical methodology. Methods. Data collected by the National Surveys in Iran, from 2000 through
2011. Since responses of the member of each cluster are correlated, the quadratic inference functions (QIF) method was used to
model the relationship between the odds of obesity and risk factors. Results. During the study period, the prevalence rate of obesity
increased from 12% to 22%. By using QIF method and a model selection criterion for performing stepwise regression analysis, we
found that while obesity prevalence generally increased in both sexes, all ages, all employment, residence, and smoking levels, it
seems to have changes in obesity ORs since 2000. Conclusions. Because obesity is one of the main risk factors for many diseases,
awareness of the differences by factors allows development of targets for prevention and early intervention.
Keywords :
Iranian , Quadratic , QIF , Method
Journal title :
Computational and Mathematical Methods in Medicine