본문 바로가기
KERD
논문KCI 등재

Gender differences in the association between food costs and obesity in Korean adults: an analysis of a population-based cohort

0

조회

0

다운로드

0

인용

0

참고문헌

키워드

초록

BACKGROUND/OBJECTIVES: Prior studies, mostly conducted in Western countries, have suggested that the low cost of energy-dense foods is associated with an increased risk of obesity. This study aimed to investigate the association between food costs and obesity risk among Koreans who may have different food cost and dietar y patterns than those of Western populations. SUBJECTS/METHODS: We used baseline data from a cohort of 45,193 men and 83,172 women aged 40–79 years (in 2006–2013). Dietar y intake information was collected using a validated food frequency questionnaire. Prudent and Western dietar y patterns extracted via principal component analysis. Food cost was calculated based on Korean government data and market prices. Logistic regression analyses were performed to investigate the association of daily total, prudent, and Western food cost per calorie with obesity. RESULTS: Men in the highest total food cost quintile had 15% higher odds of obesity, after adjusting for demographic characteristics and lifestyle factors (adjusted odds ratio, 1.15; 95% confidence inter val, 1.08–1.22; P-trend < 0.001); however, this association was not clear in women (P-trend = 0.765). While both men and women showed positive associations between prudent food cost and obesity (P-trends < 0.001), the association between Western food cost and obesity was only significant in men (P-trend < 0.001). CONCLUSIONS: In countries in which consumption of Western foods is associated with higher food costs, higher food costs are associated with an increased risk of obesity; however, this association differs between men and women.

Abstract

BACKGROUND/OBJECTIVES: Prior studies, mostly conducted in Western countries, have suggested that the low cost of energy-dense foods is associated with an increased risk of obesity. This study aimed to investigate the association between food costs and obesity risk among Koreans who may have different food cost and dietar y patterns than those of Western populations. SUBJECTS/METHODS: We used baseline data from a cohort of 45,193 men and 83,172 women aged 40–79 years (in 2006–2013). Dietar y intake information was collected using a validated food frequency questionnaire. Prudent and Western dietar y patterns extracted via principal component analysis. Food cost was calculated based on Korean government data and market prices. Logistic regression analyses were performed to investigate the association of daily total, prudent, and Western food cost per calorie with obesity. RESULTS: Men in the highest total food cost quintile had 15% higher odds of obesity, after adjusting for demographic characteristics and lifestyle factors (adjusted odds ratio, 1.15; 95% confidence inter val, 1.08–1.22; P-trend < 0.001); however, this association was not clear in women (P-trend = 0.765). While both men and women showed positive associations between prudent food cost and obesity (P-trends < 0.001), the association between Western food cost and obesity was only significant in men (P-trend < 0.001). CONCLUSIONS: In countries in which consumption of Western foods is associated with higher food costs, higher food costs are associated with an increased risk of obesity; however, this association differs between men and women.

참고문헌 (38)

  1. NHLBI Obesity Education Initiative Expert Panel on the Identification Evaluation and Treatment of Obesity in Adults, "Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults: The Evidence Report" (1998), National Institutes of Health, National Heart, Lung, and Blood Institute
  2. "Obesity and overweight" (2021)[URL]
  3. Organisation for Economic Co-operation and Development (OECD), "Overweight or Obese Population" (2021), OECD
  4. 김경배, "Males with Obesity and Overweight", Journal of Obesity & Metabolic Syndrome, 29(1), pp.18~25 (2020), 대한비만학회[DOI]
  5. Steenhuis IH, "Consumer food choices : the role of price and pricing strategies", Public Health Nutr, 14, pp.2220~2226 (2011)
  6. French SA, "Pricing effects on food choices", J Nutr, 133, pp.841S~843S (2003)[DOI]
  7. Darmon N, "A cost constraint alone has adverse effects on food selection and nutrient density : an analysis of human diets by linear programming", J Nutr, 132, pp.3764~3771 (2002)
  8. Powell LM, "Food prices and obesity : evidence and policy implications for taxes and subsidies", Milbank Q, 87, pp.229~257 (2009)
  9. Headey DD, "The relative caloric prices of healthy and unhealthy foods differ systematically across income levels and continents", J Nutr, 149, pp.2020~2033 (2019)
  10. Wardle J, "Gender differences in food choice : the contribution of health beliefs and dieting", Ann Behav Med, 27, pp.107~116 (2004)
  11. Bärebring L, "Gender differences in perceived food healthiness and food avoidance in a Swedish population-based survey : a cross sectional study", Nutr J, 19, pp.140~ (2020)
  12. Kim Y, "Cohort profile : the Korean Genome and Epidemiology Study(KoGES)consortium", Int J Epidemiol, 46, pp.e20~ (2017)
  13. "Cohort description: KoGES_health examinees (HEXA) study" (2023)[URL]
  14. "The Asia-Pacific perspective:redefining obesity and its treatment" (2000)[URL]
  15. Jolliffe IT, "Principal component analysis : a review and recent developments", Philos Trans A Math Phys Eng Sci, 374, pp.20150202~ (2016)
  16. The Korean Nutrition Society, "Recommended Dietary Allowances for Koreans" (2000), The Joongang Copy
  17. Rea LM, "Designing and Conducting Survey Research" (1992), Jossey-Bass
  18. Cramér H, "Mathematical Methods of Statistics", pp.260~290 (1946), Princeton University Press
  19. Field A, "Discovering Statistics Using IBM SPSS Statistics" (2013), SAGE Publications Ltd
  20. Cohen J, "Statistical Power Analysis for the Behavioral Sciences" (1988), Lawrence Erlbaum Associates
  21. Lakens D, "Calculating and reporting effect sizes to facilitate cumulative science : a practical primer for t-tests and ANOVAs", Front Psychol, 4, pp.863~ (2013)
  22. Schuster NA, "Modeling non-linear relationships in epidemiological data : the application and interpretation of spline models", Front Epidemiol, 2, pp.975380~ (2022)
  23. "Flexible multivariate imputation by MICE" (1999)[URL]
  24. Schafer JL, "Multiple imputation : a primer", Stat Methods Med Res, 8, pp.3~15 (1999)
  25. Goldman D, "Economic Aspects of Obesity", pp.65~90 (2008), University of Chicago Press
  26. Lopez CN, "Costs of Mediterranean and western dietary patterns in a Spanish cohort and their relationship with prospective weight change", J Epidemiol Community Health, 63, pp.920~927 (2009)
  27. Muñoz FL, "An empirically derived"prudent"dietary pattern is associated with lower obesity occurrence : modeling and mapping from a national nutrition survey", Nutr Res, 109, pp.26~34 (2023)
  28. Schulze MB, "Sugar-sweetened beverages, weight gain, and incidence of type 2 diabetes in young and middle-aged women", JAMA, 292, pp.927~934 (2004)
  29. Volpe R, "The effect of produce purchasing behavior on adult obesity and body weight : evidence from household-level scanner data", Agric Resour Econ Rev, 48, pp.253~273 (2019)
  30. Clonan A, "Socioeconomic and demographic drivers of red and processed meat consumption : implications for health and environmental sustainability", Proc Nutr Soc, 75, pp.367~373 (2016)
  31. Ritzel C, "The old man and the meat : on gender differences in meat consumption across stages of human life", Foods, 10, pp.2809~ (2021)
  32. 박어진, "동물성 식품의 건강 이미지가 기호 및 섭취빈도에 미치는 영향", 한국식생활문화학회지, 27(1), pp.1~11 (2012), 한국식생활문화학회
  33. Baek SH, "A cross-cultural comparison of fast food restaurant selection criteria between Korean and Filipino college students", Int J Hospit Manag, 25, pp.683~698 (2006)
  34. Smith GD, "Socio-economic differentials in health : the role of nutrition", Proc Nutr Soc, 56, pp.75~90 (1997)
  35. James WP, "Socioeconomic determinants of health. The contribution of nutrition to inequalities in health", BMJ, 314, pp.1545~1549 (1997)
  36. Pechey R, "Socioeconomic inequalities in the healthiness of food choices : exploring the contributions of food expenditures", Prev Med, 88, pp.203~209 (2016)
  37. Shim JS, "Socioeconomic characteristics and trends in the consumption of ultra-processed foods in Korea from 2010 to 2018", Nutrients, 13, pp.1120~ (2021)
  38. Lim H, "Trends in fast-food and sugar-sweetened beverage consumption and their association with social environmental status in South Korea", J Acad Nutr Diet, 118, pp.1228~1236 (2018)[DOI]

관련 논문AI추천

이 간행물의 다른 논문 (15건)