Nutr Res Pract.  2018 Jun;12(3):251-257. 10.4162/nrp.2018.12.3.251.

Forecasting obesity prevalence in Korean adults for the years 2020 and 2030 by the analysis of contributing factors

• Baik I

• KMID: 2442299
• DOI: http://doi.org/10.4162/nrp.2018.12.3.251

Abstract

BACKGROUND/OBJECTIVES
There are few studies that forecast the future prevalence of obesity based on the predicted prevalence model including contributing factors. The present study aimed to identify factors associated with obesity and construct forecasting models including significant contributing factors to estimate the 2020 and 2030 prevalence of obesity and abdominal obesity.
SUBJECTS/METHODS
Panel data from the Korea National Health and Nutrition Examination Survey and national statistics from the Korean Statistical Information Service were used for the analysis. The study subjects were 17,685 male and 24,899 female adults aged 19 years or older. The outcome variables were the prevalence of obesity (body mass index ≥ 25 kg/m2) and abdominal obesity (waist circumference ≥ 90 cm for men and ≥ 85 cm for women). Stepwise logistic regression analysis was used to select significant variables from potential exposures.
RESULTS
The survey year, age, marital status, job status, income status, smoking, alcohol consumption, sleep duration, psychological factors, dietary intake, and fertility rate were found to contribute to the prevalence of obesity and abdominal obesity. Based on the forecasting models including these variables, the 2020 and 2030 estimates for obesity prevalence were 47% and 62% for men and 32% and 37% for women, respectively.
CONCLUSIONS
The present study suggested an increased prevalence of obesity and abdominal obesity in 2020 and 2030. Lifestyle factors were found to be significantly associated with the increasing trend in obesity prevalence and, therefore, they may require modification to prevent the rising trend.

Keyword

Obesity; abdominal fat; prevalence; risk factors; forecasting

MeSH Terms

Abdominal Fat
Adult*
Alcohol Drinking
Birth Rate
Female
Forecasting*
Humans
Information Services
Korea
Life Style
Logistic Models
Male
Marital Status
Nutrition Surveys
Obesity*
Obesity, Abdominal
Prevalence*
Psychology
Risk Factors
Smoke
Smoking
Smoke

Figure

• 

  Fig. 1 Forecasted prevalence of obesity and abdominal obesity among women and men in 2020 and 2030

Reference

1. Ministry of Health and Welfare, Korea Centers for Disease Control and Prevention. Korea Health Statistics 2015: Korea National Health and Nutrition Examination Survey (KNHANES VI-3). Cheongju: Korea Centers for Disease Control and Prevention;2016.

2. Lee SM, Yoon Y, Baek J, Hyun K, Gang H. Socio-economic Impacts of Major Health Risk Factors and Evaluation on Effects of Regulatory Policy. Seoul: Health Insurance Policy Institute of National Health Insurance Service;2015.

3. Egger G, Swinburn B. An “ecological” approach to the obesity pandemic. BMJ. 1997; 315:477–480.

4. Reidpath DD, Burns C, Garrard J, Mahoney M, Townsend M. An ecological study of the relationship between social and environmental determinants of obesity. Health Place. 2002; 8:141–145.

5. Finkelstein EA, Khavjou OA, Thompson H, Trogdon JG, Pan L, Sherry B, Dietz W. Obesity and severe obesity forecasts through 2030. Am J Prev Med. 2012; 42:563–570.

6. Wang Y, Beydoun MA, Liang L, Caballero B, Kumanyika SK. Will all Americans become overweight or obese? Estimating the progression and cost of the US obesity epidemic. Obesity (Silver Spring). 2008; 16:2323–2330.

7. Nacul LC, Soljak M, Meade T. Model for estimting the population prevalence of chronic obstructive pulmonary disease: cross sectional data from the Health Survey for England. Popul Health Metr. 2007; 5:8.

8. Statistics Korea. Population projections for Korea: 2010-2060 [Internet]. Daejeon: Statistics Korea;2011. cited 2014 October 28. Available from: http://kostat.go.kr/portal/eng/pressReleases/8/8/index.board.

9. Pan L, Freedman DS, Gillespie C, Park S, Sherry B. Incidences of obesity and extreme obesity among US adults: findings from the 2009 Behavioral Risk Factor Surveillance System. Popul Health Metr. 2011; 9:56.

10. Bonauto DK, Lu D, Fan ZJ. Obesity prevalence by occupation in Washington State, Behavioral Risk Factor Surveillance System. Prev Chronic Dis. 2014; 11:130219.

11. Baik I, Shin C. Prospective study of alcohol consumption and metabolic syndrome. Am J Clin Nutr. 2008; 87:1455–1463.

12. Gangwisch JE, Malaspina D, Boden-Albala B, Heymsfield SB. Inadequate sleep as a risk factor for obesity: analyses of the NHANES I. Sleep. 2005; 28:1289–1296.

13. Zhao G, Ford ES, Li C, Strine TW, Dhingra S, Berry JT, Mokdad AH. Serious psychological distress and its associations with body mass index: findings from the 2007 Behavioral Risk Factor Surveillance System. Int J Public Health. 2009; 54:Suppl 1. 30–36.

14. Shimokata H, Muller DC, Andres R. Studies in the distribution of body fat. III. Effects of cigarette smoking. JAMA. 1989; 261:1169–1173.

15. Seidell JC, Cigolini M, Deslypere JP, Charzewska J, Ellsinger BM, Cruz A. Body fat distribution in relation to physical activity and smoking habits in 38-year-old European men. The European Fat Distribution Study. Am J Epidemiol. 1991; 133:257–265.

16. Yun JE, Kimm H, Choi YJ, Jee SH, Huh KB. Smoking is associated with abdominal obesity, not overall obesity, in men with type 2 diabetes. J Prev Med Public Health. 2012; 45:316–322.

17. Gilbert DG, Meliska CJ, Williams CL, Jensen RA. Subjective correlates of cigarette-smoking-induced elevations of peripheral beta-endorphin and cortisol. Psychopharmacology (Berl). 1992; 106:275–281.

18. Björntorp P. Metabolic implications of body fat distribution. Diabetes Care. 1991; 14:1132–1143.

19. Dai WS, Gutai JP, Kuller LH, Cauley JA. Cigarette smoking and serum sex hormones in men. Am J Epidemiol. 1988; 128:796–805.

20. Barrett-Connor E, Khaw KT. Cigarette smoking and increased endogenous estrogen levels in men. Am J Epidemiol. 1987; 126:187–192.