Journal of Preventive Medicine and Public Health

The Korean Society for Preventive Medicine (대한예방의학회)
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A Multi-level Analysis of Factors Affecting Participation in Health Screenings in Korea: A Focus on Household and Regional Factors

  • Park, So Yoon (Institute of Public Health, Hanyang University) ;
  • Shin, Young-jeon (Department of Preventive Medicine, Hanyang University College of Medicine)
  • Received : 2021.05.18
  • Accepted : 2021.10.25
  • Published : 2022.03.31
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Abstract

Objectives: This study divided the factors that affect participation in health screenings into individual, household, and regional levels and conducted a multi-level analysis to identify the factors related to participation in health screenings. Methods: Participants from the 2017 Community Health Survey were classified into 2 groups (under 40 and 40 or older). A multi-level logistic regression analysis was conducted to identify the factors that affected participation in health screenings. Results: The screening rate of the participants was 69.7%, and it was higher among participants aged 40 and older (80.3%) than it was among participants younger than 40 (49.8%). At the individual level, the factors that influenced participation in health screenings included age, economic activity, smoking status, physician-diagnosed hypertension, and a moderate or high physical activity level. At the household level, the odds ratio of participation in health screenings was high for participants who lived in single-person households, lived with a spouse, earned a high monthly household income, and were not beneficiaries of national basic livelihood security. At the regional level, the odds ratio at the 95% confidence interval level of participation in health screenings was high for participants who had trust in the local community and lived in an area with a proportionally high social welfare budget. Conclusions: This study analyzed nationalwide data and confirmed that individual, household, and regional characteristics affected participation in health screenings. Therefore, policies that prioritize the improvement of regional level factors and especially household level factors are likely to be the most effective for improving the screening rate.

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References

  1. Ministry of Health and Welfare. 2019 Health screening project guide [cited 2020 Aug 1]. Available from: https://www.129.go.kr/info/info04_view.jsp?n=1481 (Korean).
  2. Broyles RW, Narine L, Brandt EN Jr, Biard-Holmes D. Health risks, ability to pay, and the use of primary care: is the distribution of service effective and equitable? Prev Med 2000;30(6):453-462. https://doi.org/10.1006/pmed.2000.0672
  3. Langlie JK. Social networks, health beliefs, and preventive health behavior. J Health Soc Behav 1977;18(3):244-260. https://doi.org/10.2307/2136352
  4. Ministry of Health and Welfare. Health and welfare statistics 2018; 2019 [cited 2020 Aug 1]. Available from: http://www.mohw.go.kr/react/jb/sjb030301vw.jsp?PAR_MENU_ID=03&MENU_ID=032901&CONT_SEQ=347082&page=1 (Korean).
  5. Choi S, Lee KS. A study on the relationship between the spatial cluster patterns of male suicide rate and the regional characteristics in South Korea. Health Policy Manag 2019;29(3):312-322 (Korean). https://doi.org/10.4332/KJHPA.2019.29.3.312
  6. Kang SJ, Kim YH, Park IK. Causal relationship among the social ecological variables to explain physical activity. Korean J Sport Psychol 2016;27(2):53-64 (Korean). https://doi.org/10.24985/kjss.2016.27.1.53
  7. Moon KS, Kim YK, Chang HJ. Determinants of the use and type of comprehensive medical examination services. Korean J Health Serv Manag 2016;10(2):83-97 (Korean). https://doi.org/10.12811/kshsm.2016.10.2.083
  8. Park JK. A study on the impact factors of health screening. In: Proceedings of the Korean Society of Local Government, 2018; 2018 Nov 9, Busan. 2018, p. 231-237 (Korean).
  9. Yeo JY, Jeong HS. Determinants of health screening and its effects on health behaviors. Health Policy Manag 2012;22(1):49-64 (Korean). https://doi.org/10.4332/KJHPA.2012.22.1.049
  10. Jee YJ, Kim YJ. The difference of health behavior between screening and non screening group by health examinations services. Asia Pac J Multimed Serv Convertg Art Humanit Sociol 2017;7(6):503-510 (Korean).
  11. Tae ES. Factors associated with intention to participate in health screening [dissertation]. Gimhae: Inje University; 2012 (Korean).
  12. Song SH. Determinant of gastric cancer screening in the Korean population using multi-level analysis: Korean national cancer screening survey 2011-2012 [dissertation]. Seoul: Yonsei University; 2014 (Korean).
  13. Yu I. Factors related cancer screening of Korean men and women's according to marital status using multi-level analysis [dissertation]. Seoul: Yonsei University; 2020 (Korean).
  14. Jung YK. Determinants of general health check-up among older adults in Korea: a longitudinal analysis using the 1st-5th waves of Korean Longitudinal Study of Ageing (KLoSA). Crisisonomy 2018;14(1):135-148 (Korean).
  15. Choi WM. Factors related to non-screening of cervical cancer screening for Korean married women [dissertation]. Seoul: Yonsei University; 2015 (Korean).
  16. Park IS, Han JT. Study of effect on the obesity status using multilevel logistic regression analysis. J Korean Data Inf Sci Soc 2019;30(1):205-217 (Korean). https://doi.org/10.7465/jkdi.2019.30.1.205
  17. Kim KK, JeKarl J, Kwon YM, Park MS. Effects of the community environmental characteristics on drinking problems of adults: a multilevel analysis. Korean J Health Educ Promot 2012;29(5):103-113 (Korean).
  18. Jeong BG, Hwang IK, Sohn HS, Koh KW, Yoon TH, Lim JH. The relationship between trust in healthcare system and health examination participation. J Agric Med Community Health 2010;35(4):395-404 (Korean). https://doi.org/10.5393/JAMCH.2010.35.4.395
  19. Jeong JY, Kim C, Shin M, Ryu SY, Hong J, Kim NH, et al. Factors related with regional variations of health behaviors and health status: based on Community Health Survey and regional characteristics data. Korea Public Health Res 2017;43(3):91-108 (Korean). https://doi.org/10.22900/KPHR.2017.43.3.008
  20. Korea Disease Control and Prevention Agency. 2008-2019 Regional health statistics at a glance _ volume 1 (summary) [cited 2020 Oct 26]. Available from: https://chs.kdca.go.kr/chs/stats/statsMain.do (Korean).
  21. Kim Y. Factors associated with thyroid cancer screening of Korea using a multi-level analysis: results from Community Health Survey 2012. Seoul: Yonsei University; 2015 (Korean).
  22. Singer JD. Using SAS PROC MIXED to fit multilevel models, hierarchical models, and individual growth models. J Educ Behav Stat 1998;23(4):323-355. https://doi.org/10.2307/1165280
  23. Pollack CE, Cubbin C, Ahn D, Winkleby M. Neighbourhood deprivation and alcohol consumption: does the availability of alcohol play a role? Int J Epidemiol 2005;34(4):772-780. https://doi.org/10.1093/ije/dyi026
  24. Heck RH, Thomas SL. An introduction to multilevel modeling techniques. 2nd ed. New York: Routledge; 2009, p. 36.
  25. Kang S, You CH, Kwon YD. The determinants of the use of opportunistic screening programs in Korea. J Prev Med Public Health 2009;42(3):177-182 (Korean). https://doi.org/10.3961/jpmph.2009.42.3.177
  26. Kim YT. Health insurance general health screening blind spot. Gend Rev 2010;18:51-57 (Korean).
  27. Shin MA. Comparative study on health behavior and mental health between one person and multi-person households: analysis of data from the National Health and Nutrition Examination Surveys (2013, 2015, 2017). J Korean Soc Wellness 2019;14(4):11-23 (Korean). https://doi.org/10.21097/ksw.2019.11.14.4.11
  28. Park M. The characteristics of late middle-aged one-person households: a comparison with those of multi-person households. Korean Acad Pract Hum Welf 2016;17:115-129 (Korean).
  29. Choi EJ, Yoo SH, Son CG, Oh IY, Yu JY. Social capital and its impact on health promoting behavior; 2012 [cited 2022 Mar 27]. Available from: https://repository.kihasa.re.kr/handle/201002/9810 (Korean).
  30. Shin SS, Woo KS, Shin YJ. A systematic review of studies on public health using multilevel analysis: focused on research trends and the assessment of risk of bias. Health Soc Welf Rev 2015;35(4):157-189 (Korean). https://doi.org/10.15709/hswr.2015.35.4.157
  31. Lee JH, Heo TY. A study of effect on the smoking status using multilevel logistic model. Korean J Appl Stat 2014;27(1):89-102 (Korean). https://doi.org/10.5351/KJAS.2014.27.1.089
  32. Lim JH. A study on the service utilization of national health screening: focusing on causal factors from supply and demand sides [dissertation]. Seoul: Yonsei University; 2012 (Korean).
  33. Lee MH, Kim SH. Breast cancer screening rates-related factors Korea women ever considering area environmental characteristics: the fourth Korea National Health and Nutrition Examination Survey (KNHANES IV). J Digit Converg 2014;12(11):437-449 (Korean). https://doi.org/10.14400/JDC.2014.12.11.437