Nutr Res Pract.  2020 Feb;14(1):62-69. 10.4162/nrp.2020.14.1.62.

Dietary and modifiable factors contributing to hyper-LDL-cholesterolemia prevalence in nationwide time series data and the implications for primary prevention strategies

Affiliations
  • 1Department of Foods and Nutrition, College of Science and Technology, Kookmin University, 77, Jeongnung-ro, Seongbuk-gu, Seoul 02707, Korea. ibaik@kookmin.ac.kr

Abstract

BACKGROUND/OBJECTIVES
A number of studies examined secular trends in blood lipid profiles using time series data of national surveys whereas few studies investigated individual-level factors contributing to such trends. The present study aimed to examine secular trends in dietary and modifiable factors and hyper-LDL-cholesterolemia (HC) prevalence and evaluate their associations using time series data of nationwide surveys.
SUBJECTS/METHODS
The study included 41,073 Korean adults aged ≥ 30 years from the 2005, 2007-2009, 2010-2012, 2013-2015, and 2016 Korea National Health and Nutrition Examination Surveys. Stepwise logistic regression analysis was performed to select significant factors associated with HC, which was defined as serum LDL cholesterol levels ≥130 mg/dL.
RESULTS
The following factors showed a positive association with HC (P < 0.05): for men having higher body mass index (BMI), being married, having an office job, and consuming higher dairy and vegetable oil products; for women having higher age or BMI, having no job or a non-office job, not in a low-income household, and consuming higher dairy products. In the given model, the 2016 survey data showed that a 2 kg/m² reduction in BMI of obese persons resulted in a decreased HC prevalence from 30.8% to 29.3% among men and from 33.6% to 32.5% among women.
CONCLUSIONS
Based on these findings, it is suggested that primary prevention programs should advocate having proper BMI for Korean adults with a high-risk of HC. However, whether discouraging consumption of dairy and vegetable oil products can reduce HC prevalence warrants further studies with a prospective longitudinal design.

Keyword

Surveys; cholesterol; prevalence; body mass index

MeSH Terms

Adult
Body Mass Index
Cholesterol
Cholesterol, LDL
Dairy Products
Family Characteristics
Female
Humans
Korea
Logistic Models
Male
Prevalence*
Primary Prevention*
Prospective Studies
Vegetables
Cholesterol
Cholesterol, LDL

Figure

  • Fig. 1 Observed and predicted estimates of hyper-LDL-cholesterolemia prevalence calculated using the 2016 Korea National Health and Nutrition Examination Survey data. The ‘predicted prevalence A’ indicates an estimate calculated using the final models presented in Table 3. The ‘predicted prevalence B’ indicates an estimate obtained when considering a 2 kg/m2 reduction in the body mass index of obese persons in the given models. The vertical line on the bar indicates the 95% confidence interval. Logistic regression analysis was used.

  • Fig. 2 Association between % of calories from fat and hyper-LDL-cholesterolemia prevalence in 38394 adults aged 30 years or older. The multivariate odds ratios of hyper-LDL-cholesterolemia prevalence were estimated after adjustment of variables presented in Table 2, except for consumption of high-fat foods. The multivariate odds ratios (number of subjects) are shown inside the bars with the 95% confidence interval depicted as a vertical line on the bar. Logistic regression analysis was used and p-value for trend was obtained when median values of % of calories from fat for each category were fitted.


Reference

1. Wilson PW. Established risk factors and coronary artery disease, the Framingham Study. Am J Hypertens. 1994; 7:7S–12S.
Article
2. Manson JE, Tosteson H, Ridker PM, Satterfield S, Hebert P, O'Connor GT, Buring JE, Hennekens CH. The primary prevention of myocardial infarction. N Engl J Med. 1992; 326:1406–1416.
Article
3. Gordon DJ, Probstfield JL, Garrison RJ, Neaton JD, Castelli WP, Knoke JD, Jacobs DR Jr, Bangdiwala S, Tyroler HA. High-density lipoprotein cholesterol and cardiovascular disease. Four prospective American studies. Circulation. 1989; 79:8–15.
Article
4. Lee SW, Kim HC, Lee HS, Suh I. Thirty-year trends in mortality from cardiovascular diseases in Korea. Korean Circ J. 2015; 45:202–209.
Article
5. Ministry of Health and Welfare. Korea Centers for Disease Control and Prevention. Korea Health Statistics 2016: Korea National Health and Nutrition Examination Survey (KNHANES VII-1. Sejong, Republic of Korea: Korea Centers for Disease Control and Prevention;2017.
6. Tran BT, Jeong BY, Oh JK. The prevalence trend of metabolic syndrome and its components and risk factors in Korean adults, results from the Korean National Health and Nutrition Examination Survey 2008-2013. BMC Public Health. 2017; 17:71.
Article
7. Committee for the Korean Guidelines for the Management of Dyslipidemia. 2015 Korean Guidelines for the Management of Dyslipidemia: Executive Summary (English Translation). Korean Circ J. 2016; 46:275–306.
8. Yun S, Kim HJ, Oh K. Trends in energy intake among Korean adults, 1998-2015: Results from the Korea National Health and Nutrition Examination Survey. Nutr Res Pract. 2017; 11:147–154.
Article
9. Micha R, Khatibzadeh S, Shi P, Fahimi S, Lim S, Andrews KG, Engell RE, Powles J, Ezzati M, Mozaffarian D. Global Burden of Diseases Nutrition and Chronic Diseases Expert Group NutriCoDE. Global, regional, and national consumption levels of dietary fats and oils in 1990 and 2010: a systematic analysis including 266 countryspecific nutrition surveys. BMJ. 2014; 348:g2272.
Article
10. Research Committee on Serum Lipid Level Survey 1990 in Japan. Current state of and recent trends in serum lipid levels in the general Japanese population. J Atheroscler Thromb. 1996; 2:122–132.
11. Cohen JD, Cziraky MJ, Cai Q, Wallace A, Wasser T, Crouse JR, Jacobson TA. 30-year trends in serum lipids among United States adults: results from the National Health and Nutrition Examination Surveys II, III, and 1999-2006. Am J Cardiol. 2010; 106:969–975.
Article
12. Hotchkiss JW, Davies CA, Gray L, Bromley C, Capewell S, Leyland A. Trends in cardiovascular disease biomarkers and their socioeconomic patterning among adults in the Scottish population 1995 to 2009: cross-sectional surveys. BMJ Open. 2012; 2:e000771.
Article
13. Johansson I, Nilsson LM, Stegmayr B, Boman K, Hallmans G, Winkvist A. Associations among 25-year trends in diet, cholesterol and BMI from 140,000 observations in men and women in Northern Sweden. Nutr J. 2012; 11:40.
Article
14. Nam GE, Han K, Park YG, Choi YS, Kim SM, Ju SY, Ko BJ, Kim YH, Kim EH, Cho KH, Kim DH. Trends in lipid profiles among South Korean adults: 2005, 2008 and 2010 Korea National Health and Nutrition Examination Survey. J Public Health (Oxf). 2015; 37:286–294.
Article
15. Kotseva K, De Bacquer D, Jennings C, Gyberg V, De Backer G, Rydén L, Amouyel P, Bruthans J, Cifkova R, Deckers JW, De Sutter J, Fraz Z, Graham I, Keber I, Lehto S, Moore D, Pajak A, Wood D. EUROASPIRE Investigators. Time Trends in Lifestyle, Risk Factor Control, and Use of Evidence-Based Medications in Patients With Coronary Heart Disease in Europe: Results From 3 EUROASPIRE Surveys, 1999-2013. Glob Heart. 2017; 12:315–322.
Article
16. Griffey S, Piccinino L, Gallivan J, Lotenberg LD, Tuncer D. Applying national survey results for strategic planning and program improvement: the National Diabetes Education Program. Eval Program Plann. 2015; 48:83–89.
Article
17. Zhou L, Zhao X, Heizhati M, Abulikemu S, Zhang D, Cheng Q, Ouyang W, Yao X, Hong J, Wu T, Xiamili Z, Li N. Trends in Lipids and Lipoproteins Among Adults in Northwestern Xinjiang, China, From 1998 Through 2015. J Epidemiol. 2018; [Epub ahead of print].
Article
18. Kweon S, Kim Y, Jang MJ, Kim Y, Kim K, Choi S, Chun C, Khang YH, Oh K. Data resource profile: the Korea National Health and Nutrition Examination Survey (KNHANES). Int J Epidemiol. 2014; 43:69–77.
Article
19. National Rural Living Science Institute. Food composition table. 6th ed. Suwon, Republic of Korea: 2001.
20. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem. 1972; 18:499–502.
Article
21. Rashad I. Associations of cycling with urban sprawl and the gasoline price. Am J Health Promot. 2009; 24:27–36.
Article
22. Baik I. Forecasting obesity prevalence in Korean adults for the years 2020 and 2030 by the analysis of contributing factors. Nutr Res Pract. 2018; 12:251–257.
Article
23. 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.
Article
24. Carroll MD, Fryar CD, Nguyen DT. Total and High-density Lipoprotein Cholesterol in Adults: United States, 2015-2016. NCHS Data Brief. 2017; 290:1–8.
25. Benatar JR, Sidhu K, Stewart RA. Effects of high and low fat dairy food on cardio-metabolic risk factors: a meta-analysis of randomized studies. PLoS One. 2013; 8:e76480.
Article
26. Livingstone KM, Lovegrove JA, Givens DI. The impact of substituting SFA in dairy products with MUFA or PUFA on CVD risk: evidence from human intervention studies. Nutr Res Rev. 2012; 25:193–206.
Article
27. Schwingshackl L, Bogensberger B, Benčič A, Knüppel S, Boeing H, Hoffmann G. Effects of oils and solid fats on blood lipids: a systematic review and network meta-analysis. J Lipid Res. 2018; 59:1771–1782.
Article
28. Narasimhamurthy K, Raina PL. Long term feeding effects of heated and fried oils on lipids and lipoproteins in rats. Mol Cell Biochem. 1999; 195:143–153.
29. Gadiraju TV, Patel Y, Gaziano JM, Djoussé L. Fried Food Consumption and Cardiovascular Health: A Review of Current Evidence. Nutrients. 2015; 7:8424–8430.
Article
30. Ministry of Health and Welfare. The Korean Nutrition Society. Dietary Reference Intakes for Koreans 2015. Seoul: Republic of Korea;2015.
31. The Korean Nutrition Society. Dietary Reference Intakes for Koreans 2010. Seoul, Republic of Korea: 2010.
32. Lamon-Fava S, Wilson PW, Schaefer EJ. Impact of body mass index on coronary heart disease risk factors in men and women. The Framingham Offspring Study. Arterioscler Thromb Vasc Biol. 1996; 16:1509–1515.
Article
33. Dattilo AM, Kris-Etherton PM. Effects of weight reduction on blood lipids and lipoproteins: a meta-analysis. Am J Clin Nutr. 1992; 56:320–328.
Article
34. Sharifi M, Futema M, Nair D, Humphries SE. Genetic Architecture of Familial Hypercholesterolaemia. Curr Cardiol Rep. 2017; 19:44.
Article
35. Dochi M, Suwazono Y, Sakata K, Okubo Y, Oishi M, Tanaka K, Kobayashi E, Nogawa K. Shift work is a risk factor for increased total cholesterol level, a 14-year prospective cohort study in 6886 male workers. Occup Environ Med. 2009; 66:592–597.
Article
36. Bouillon K, Singh-Manoux A, Jokela M, Shipley MJ, Batty GD, Brunner EJ, Sabia S, Tabák AG, Akbaraly T, Ferrie JE, Kivimäki M. Decline in low-density lipoprotein cholesterol concentration: lipid-lowering drugs, diet, or physical activity? Evidence from the Whitehall II study. Heart. 2011; 97:923–930.
Article
37. Fukuyama N, Homma K, Wakana N, Kudo K, Suyama A, Ohazama H, Tsuji C, Ishiwata K, Eguchi Y, Nakazawa H, Tanaka E. Validation of the Friedewald Equation for Evaluation of Plasma LDL-Cholesterol. J Clin Biochem Nutr. 2008; 43:1–5.
Article
Full Text Links
  • NRP
Actions
Cited
CITED
export Copy
Close
Share
  • Twitter
  • Facebook
Similar articles
Copyright © 2024 by Korean Association of Medical Journal Editors. All rights reserved.     E-mail: koreamed@kamje.or.kr