DOI QR코드

DOI QR Code

Classification of Clusters, Characteristics and Related Factors according to Drinking, Smoking, Exercising and Nutrition among Korean Adults

한국 성인의 음주, 흡연, 운동 및 영양행태에 대한 군집별 특성 및 관련요인

  • 김꽃별 (충남대학교 간호대학 간호학과) ;
  • 은상준 (충남대학교 의과대학 예방의학교실)
  • Received : 2019.02.08
  • Accepted : 2019.05.03
  • Published : 2019.05.31

Abstract

The purpose of this study was to identify the type of health behaviors in Korean adults and to identify related factors. The data used in the analysis was the Korea Health and Nutrition Examination Survey 2014., which was representative of the Korean population. Cluster analysis was used to find the pattern of clustering of smoking, drinking, exercising and nutrition. Differences in the pattern of clustering was examined, first by bivariate chi-square test, and then by multinomial logit regression. Lastly, the association between the clusters of health behaviors and other behavioral risk factors was tested by chi-square test and logistic regression. The distribution of the clusters varied not only across socioeconomic characteristics and local size, but also between individuals with certain chronic diseases and those without. The results of this study can be used as a basis for the usefulness of approaching the cluster rather than individually approaching the health behavior.

본 연구의 목적은 한국 성인의 건강행태군집 유형을 확인하고 이와 관련된 요인들을 파악하는 것이다. 이를 위해 2014년도 국민건강영양조사 자료를 이차분석 하였다. 음주, 흡연, 운동 및 영양 변수를 이용하여 19세 이상 성인을 대상으로 군집분석하였고, 이 유형들과 인구사회학적 특성 및 건강상태의 연관성을 확인하기 위해 SPSS WIN 22 복합표본 설계 모듈을 이용하여 카이제곱 검정과 다항로지스틱 분석을 실시하였다. 한국 성인의 건강행태군집 유형은 흡연군, 식습관군, 건강 관심군, 수동적 태도군 그리고 음주군의 총 6개 유형으로 분류되었고 수동적 태도군의 빈도가 26.0%로 가장 높았다. 건강행태 군집의 타당성을 검증하기 위해 분류된 군집과 건강행태변수를 이용해 판별분석한 결과 타당한 것으로 나타났다. 건강행태 군집은 성, 연령, 교육 수준, 직업, 소득 수준, 결혼 상태 및 지역 규모등 인구 사회학적 특성별로 분포가 달랐으며, 고혈압 및 당뇨와 같은 일부 만성질환의 유무별로도 다른 것으로 나타났다. 인구사회학적 특성, 지역, 고혈압 및 당뇨는 수동적 태도군 보다는 나머지 건강행태군집에 속하는 것과 유의한 연관을 보이는 변수였다. 본 연구 결과는 건강행태를 개별적으로 접근하기 보다는 군집으로 접근하는 것의 유용성에 대한 근거 자료로 활용할 수 있을 것이다.

Keywords

Table 1. Characteristics of the study subjects

SHGSCZ_2019_v20n5_252_t0001.png 이미지

Table 2. Selecting number of clusters based on Akaike Information Criterion (AIC)

SHGSCZ_2019_v20n5_252_t0002.png 이미지

Table 3. Comparison between clusters

SHGSCZ_2019_v20n5_252_t0003.png 이미지

Table 4. Discriminant analysis for Clusters

SHGSCZ_2019_v20n5_252_t0004.png 이미지

Table 5. Classification results for groups

SHGSCZ_2019_v20n5_252_t0005.png 이미지

Table 6. Comparison of demographic and social characteristics between groups

SHGSCZ_2019_v20n5_252_t0006.png 이미지

Table 7. Comparison of BMI and Subjective health state between groups

SHGSCZ_2019_v20n5_252_t0007.png 이미지

Table 8. Comparison of chronic disease between groups

SHGSCZ_2019_v20n5_252_t0008.png 이미지

Table 9. Factors effecting the classification of health-related behavior cluster

SHGSCZ_2019_v20n5_252_t0009.png 이미지

References

  1. SY. Lee, SW. Kim, JW. Park. Characteristics of health lifestyle patterns by the quantification method. Journal of Preventive Medicine and Public Health, vol 30, no. 1, pp. 181-193, 1997.
  2. R. Mistry, WJ McCarthy, AK. Yancey, Y. Lu, M Patel, Resilience and patterns of health risk behaviors in California adolescents. Journal of Preventive Medicine, vol 48, no. 3, pp. 291-297, 2009. DOI: https://doi.org/10.1016/j.ypmed.2008.12.013
  3. S. Keller, JE Maddock, W. Hannover, JR. Thyrian, HD. Basler. Multiple health risk behaviors in German first year university students. Journal of Preventive Medicine, vol 46, no. 3, pp. 189-195,2008. DOI: https://doi.org/10.1016/j.ypmed.2007.09.008
  4. KL. Chou. Prevalence and clustering of four major lifestyle risk factors in Hong Kong Chinease older adults. Journal of Aging Health, vol 20, no.7, pp. 788-803, 2008. DOI: https://doi.org/10.1177/0898264308321082
  5. KM. Emmons, BH. Marcus, L. Linnan, JS. Rossi, DB Abrams. Mechanisms in multiple risk factor Interventions:Smoking, physical activity, and dietary fat intake among manufacturing workers. Working Well Research Group. Journal of Preventive Medicine, vol 23, no. 4, pp. 481-489, 1994. DOI: https://doi.org/10.1006/pmed.1994.1066
  6. AJ. Schuit, AJ. van Loon, M. Tijhuis, M. Ocke. Clustering of lifestyle risk factors in a general adult population. Journal of Preventive Medicine, vol 35, no. 3, pp. 219-224, 2002. DOI: https://doi:10.1006/pmed.2002.1064
  7. W. Poortinga. Prevalence and clustering of four major lifestyle risk factors in an English adult population. Journal of Preventive Medicine, vol 44, no. 2, pp. 124-128, 2007. DOI: https://doi.org/10.1016/j.ypmed.2006.10.006
  8. LJ. Fine, GS. Philogene, R. Gramling, EJ. Coups, S. Sinha. Prevalence of multiple chronic disease risk factors: 2001 national health interview survey.American Journal of Preventive Medicine, vol 27, no. 2, pp. 18-24, 2004. DOI: https://doi.org/10.1016/j.amepre.2004.04.017
  9. D. Berrigan, K. Dodd, RP. Troiano, SM. Krebs- Smith, RB Barbash. Patterns of health behavior in U.S. adults. Journal of Preventive Medicine, vol 36, no. 5, pp. 788-803, 2003. DOI: https://doi.org/10.1016/S0091-7435(02)00067-1
  10. NP. Pronk, LH. Anderson, AL. Crain, BC. Martinson, PJ. O'Connor, NE. Sherwood. Meeting recommendations for multiple healthy lifestyle factors: Prevalence, clustering and predictors among adolescent, adult and senior health plan members. American Journal of Preventive Medicine, vol27, no. 2, pp. 25-33, 2005. DOI: https://doi.org/10.1016/j.amepre.2004.04.022
  11. EJ. Kang. Clustering of lifestyle behaviors of Korean adults using smoking, drinking, and physical activity. Korea Institute for Health and Social Affairs, vol 27, no. 2, pp. 44-66, 2007.
  12. EM. Durazo, MR. Jones, SP. Wallace, J. Van Arsdale, M. Aydin, C. Stewart. "The Health status and unique health challenges of rural older adults in California." Health Policy Brief., USA, June. 2011.
  13. JM. Lee, KS. Kwon, JH. Lee, GS. Jeon. A Study on Health Behavior of the Populations in Urban and Rural Area. Journal of agricultural medicine and community health, vol 30, no. 2, pp. 213-225, 2005.
  14. EO. Park. A comparative study of youth health risk behaviors by region: Focused on metropolit an areas, medium sized and small city areas, and rural areas. Journal of Korean Academy of Nursing, vol 40, no. 1, pp. 14-23, 2010. DOI: https://doi:10.4040/jkan.2010.40.1.14.
  15. JE. Paik, HK. Choi. Successful aging according to Korean elderly: The definition, types, and Predicting variables. Journal of Korean Home Mana gement, vol 23, no. 3, pp. 1-16, 2005.
  16. SM. Moon. Type of health behavior clusters and related factors among korean adults. The Society of Digital Policy & Management, vol 12, no. 8, pp. 1397-410, 2014. DOI: https://doi.org/10.14400/JDC.2014.12.8.397
  17. EJ. Kim, SS. Hwang, JM. Park, HI. Lee. A study on health promotion behaviors of a group of middle aged men in K-Ku, Incheon city. Journal of Korean Academy of community health Nursing, vol 15, no. 3, pp. 408-418, 2004.
  18. SH. Song, EH. Ha, DH. The psychosocial variables related to smoking status in male. Journal of Korean Health Psychology, vol 7, no.3, pp. 447-461, 2002.
  19. S. Moon, Physical activities and related factors among low-income middle-aged people. Journal of Korean Public Health Nursing, Vol. 26, no.1, pp. 39-51, 2012. DOI: https://doi.org/10.5932/JKPHN.2012.26.1.038
  20. D. Umberson. Gender, marital status and social control of health behavior. Social Science and Medicine, vol 34, no. 8, pp. 907-917, 1992. DOI: https://doi.org/10.1016/0277-9536(92)90259-S
  21. Y. S. Lee, Marital status, health behaviors and health status for middle-aged men and women in Korea. Korea Journal of Population Studies, vol. 35, no. 2, pp. 103-131, 2012. DOI: https://doi:10.4082/kjfm.2012.33.6.390
  22. JY. Kim. The relationship between socioeconomic status and health in Korea. Journal of Korean Social Science, vol 41, no. 3, pp. 127-153, 2007.
  23. JM. Lee, KS. Kwon, JH. Lee, GS. Jeon. A Study on Health Behavior of the Populations in Urb an and Rural Area. Journal of agricultural medicine and community health, vol 30, no. 2, pp. 213-225, 2005.
  24. JY. Kim. The relationship between socioeconomic status and health in Korea. Journal of Korean Social Science, vol 41, no. 3, pp. 127-153, 2007.
  25. JS. Choi. Effect of early detection of hypertension and diabetes on smoking and alcohol drinking. Korea Institute for Health and Social Affairs, vol 27, no. 1, pp. 103-130, 2007.