Opposing socioeconomic gradients in overweight and obese adults

• Main Authors: Alison Markwick (Author), Loretta Vaughan (Author), Zahid Ansari (Author)
• Format: Book
• Published: Elsevier, 2013-02-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 1753-6405; 1326-0200; 10.1111/1753-6405.12007
• Keywords: Overweight, obesity, gender socioeconomic status; BMI; health inequalities; Public aspects of medicine; RA1-1270
• Source: Australian and New Zealand Journal of Public Health, Vol 37, Iss 1, Pp 32-38 (2013)

Abstract Objective: Investigate the relationship between socioeconomic status (SES) and prevalence of overweight and/or obesity, by sex, using total annual household income as the indicator of SES and the World Health Organization (WHO) recommended ranges of self‐reported Body Mass Index (BMI) as the indicator of overweight and/or obesity. Methods : Total annual household income and BMI data were obtained from the Victorian Population Health Survey (VPHS), an annual computer‐assisted telephone survey of the health and well‐being of Victorian adults aged 18 years and older. Statistical analysis was conducted using ordinary least squares linear regression on the logarithms of age‐standardised prevalence estimates of overweight (25.0-29.9 kg/m2), obesity (≥30.0 kg/m2), and overweight and obesity combined (≥25.0 kg/m2), by income category and sex. Results: Typical SES gradients were observed in obese males and females, where the prevalence of obesity decreased with increasing income. No SES gradient was observed in overweight females, however, a reverse SES gradient was observed in overweight males, where the prevalence of overweight increased with increasing income. Combining the overweight and obesity categories into a single group eliminated the typical SES gradients observed in males and females for obesity, and resulted in a statistically significant reverse SES gradient in males. Conclusions: Combining the BMI categories of overweight and obesity into a single category masks important SES differences, while combining the data for males and females masks important sex differences. BMI categories of overweight and obesity should be analysed and reported independently, as should BMI data by sex.