title: Determinants of Obesity and Associated Population Attributability, South Africa: Empirical Evidence from a National Panel Survey, 2008-2012.
abstract: BACKGROUND
  Obesity is a major risk factor for emerging non-communicable diseases (NCDS) in middle income countries including South Africa (SA). Understanding the multiple and complex determinants of obesity and their true population attributable impact is critical for informing and developing effective prevention efforts using scientific based evidence. This study identified contextualised high impact factors associated with obesity in South Africa.
  
  
  METHODS
  Analysis of three national cross sectional (repeated panel) surveys, using a multilevel logistic regression and population attributable fraction estimation allowed for identification of contextualised high impact factors associated with obesity (BMI>30 kg/m2) among adults (15 years+).
  
  
  RESULTS
  Obesity prevalence increased significantly from 23.5% in 2008 to 27.2% in 2012, with a significantly (p-value<0.001) higher prevalence among females (37.9% in 2012) compared to males (13.3% in 2012). Living in formal urban areas, white ethnicity, being married, not exercising and/or in higher socio-economic category were significantly associated with male obesity. Females living in formal or informal urban areas, higher crime areas, African/White ethnicity, married, not exercising, in a higher socio-economic category and/or living in households with proportionate higher spending on food (and unhealthy food options) were significantly more likely to be obese. The identified determinants appeared to account for 75% and 43% of male and female obesity respectively. White males had the highest relative gain in obesity from 2008 to 2012.
  
  
  CONCLUSIONS
  The rising prevalence of obesity in South Africa is significant and over the past 5 years the rising prevalence of Type-2 diabetes has mirrored this pattern, especially among females. Targeting young adolescent girls should be a priority. Addressing determinants of obesity will involve a multifaceted strategy and requires at individual and population levels. With rising costs in the private and public sector to combat obesity related NCDS, this analysis can inform culturally sensitive mass communications and wellness campaigns. Knowledge of social determinants is critical to develop "best buys".
authors.affiliation: Discipline of Public Health Medicine, School of Nursing and Public Health, University of KwaZulu-Natal, Durban, South Africa.
authors.forename: Benn
authors.initials: B
authors.lastname: Sartorius
authors.affiliation: School of Population Health, University of Queensland, Brisbane, QLD, Australia.
authors.forename: Lennert J
authors.initials: LJ
authors.lastname: Veerman
authors.affiliation: School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; PRICELESS SA, MRC/Wits Rural Public, Health and Health Transitions Research Unit, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
authors.forename: Mercy
authors.initials: M
authors.lastname: Manyema
authors.affiliation: School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; PRICELESS SA, MRC/Wits Rural Public, Health and Health Transitions Research Unit, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
authors.forename: Lumbwe
authors.initials: L
authors.lastname: Chola
authors.affiliation: School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; PRICELESS SA, MRC/Wits Rural Public, Health and Health Transitions Research Unit, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; John Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, United States of America.
authors.forename: Karen
authors.initials: K
authors.lastname: Hofman
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000453:epidemiology* / Q000208:ethnology; D012959:Socioeconomic Factors; D013019:South Africa