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The Health Behavior and Status according to Household Income Level in Korean Women Aged 35 Years or Older: the 2013 National Health and Nutrition Examination Survey


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The Health Behavior and Status according to Household Income Level in Korean Women Aged 35 Years or Older: the 2013 National Health and Nutrition Examination Survey

Article information

Korean J Health Promot. 2017;17(1):20-30
Publication date (electronic) : 2017 March 31
doi : https://doi.org/10.15384/kjhp.2017.17.1.20
Min-Jeong Oh1, Yun-Jin Kim2, Jeong-Gyu Lee2, Yu-Hyeon Yi1, Young-Jin Tak1, Hye-Rim Hwang1, Seung-Hoon Lee1
1Department of Family Medicine, Pusan National University Hospital, Busan, Korea.
2Department of Family Medicine, Pusan National University School of Medicine, Yangsan, Korea.
Corresponding author: Yun-Jin Kim, MD, PhD. Department of Family Medicine, Pusan National University School of Medicine, 49 Busandaehak-ro, Mulgeum-eup, Yangsan 50612, Korea. Tel: +82-51-240-7834, Fax: +82-51-242-8671, yujkim@pusan.ac.kr
Received 2016 December 07; Accepted 2017 March 20.

Abstract

Background

Income is a major socioeconomic index, and low household income is known to negatively affect health. Nevertheless, there is a lack of research on the health status and health behavior of middle-aged and older women with low-income. This study aims to provide basic information on the health status and health behavior of low-income women, using data representative of South Koreans.

Methods

This cross-sectional study used data from the 6th Korea National Health and Nutrition Examination Survey. Among the total of 8,018 respondents, 2,713 women aged 35 years or older were enrolled in the study. The subjects were classified by income status based on standard household income quartiles.

Results

The low-income group showed the lowest education levels and the highest unemployment rate (P<0.001). The percentage of smokers was the highest, while the frequency of exercise was the lowest in this group (P<0.001). The incidence of hyperlipidemia was highest (P=0.028), and they showed the highest body mass index, waist circumference (P<0.001), blood pressure, fasting blood glucose (P=0.018), and triglyceride level (P=0.03), as well as the lowest high density lipoprotein level (P=0.039), and the highest risk of cardiovascular diseases (P=0.002). Additionally, perceived health status was negative and quality of life was lowest among the groups (P<0.001). Although the enrollment rate for free health check-up services was highest (P=0.007), subscription to private health insurance, adult health check-ups, cancer screening rate were all lowest of the groups.

Conclusions

This study confirmed a health gap among middle-aged and elderly women of low income, compared to higher income groups.

Keywords: Income; Female; Health behavior; Health status

Notes

This study was supported by the clinical research fund of Pusan National University Hospital in 2016.

References

1. Macintyre S. The Black Report and beyond: what are the issues? Soc Sci Med 1997;44(6):723–745.
2. Loucks EB, Magnusson KT, Cook S, Rehkopf DH, Ford ES, Berkman LF. Socioeconomic position and the metabolic syndrome in early, middle, and late life: evidence from NHANES 1999-2002. Ann Epidemiol 2007;17(10):782–790.
3. Kim HR. Implication of health behaviors in socioeconomic health inequalities and policy directions. Health Welf Policy Forum 2009;149:36–47.
4. Son M. The relationship of social class and health behaviors with morbidity in Korea. Korean J Prev Med 2002;35(1):57–64.
5. Lee SK. Social contextual effects on regional mortality and self-rated health status [dissertation] Seoul: The Graduate School, Yeonsei University; 2002. Korean.
6. Department of Social statistics, Korea National Statistical Office. 2012 life table [Internet] Daejeon: Korea National Statistical Office; 2013. Accessed Dec 5, 2013. Available form: http://kostat.go.kr/portal/korea/kor_nw/2/2/7/index.-board?bmode=read&aSeq=310490.
7. Kim JY. The relationship between socioeconomic status and health in Korea: focusing on age variations. Korean J Sociol 2007;41(3):127–153.
8. Kim YM, Jung-Choi KH. Socioeconomic inequalities in health risk factors in Korea. J Korean Med Assoc 2013;56(3):175–183.
9. Lee JM, KIm WJ, Sohn HS, Chun JH, Lee MJ, Park HS. Influences on health behaviors execution and self rated health as socioeconomic class by the age bracket. J Korea Contents Assoc 2012;16(9):317–327.
10. Kim M, Chung W, Lim S, Yoon S, Lee J, Kim E, et al. Socioeconomic inequity in self-rated health status and contribution of health behavioral factors in Korea. J Prev Med Public Health 2010;43(1):50–61.
11. Ham OK, Kim BJ, Lee YA. Cardiovascular Disease Risk according to Socioeconomic Factors among Low-income Midlife Women. J Korean Public Health Nurs 2008;22(1):27–38.
12. Kang HM, Kim DJ. Gender differences in the association of socioeconomic status with metabolic syndrome in middle-aged Koreans. Korean J Med 2012;82(5):569–575.
13. Adler NE, Boyce WT, Chesney MA, Folkman S, Syme SL. Socioeconomic inequalities in health. No easy solution. JAMA 1993;269(24):3140–3145.
14. Yoon TH, Moon OR, Lee SY, Jeong BG, Lee SJ, Kim NS, et al. Differences in health behaviors among the social strata in Korea. Korean J Prev Med 2000;33(4):469–476.
15. Kim HR. The relationship of socioeconomic position and health behaviors with morbidity in seoul, Korea. Health Soc Welf Rev 2005;25(2):3–35.
16. Kim YA, Oh KW. Public health weekly report Osong: Korea centers for disease control and prevention; 2015. p. 33–36.
17. Lahelma E, Valkonen T. Health and social inequitiesin Finlandand elsewhere. Soc Sci Med 1990;31(3):257–265.
18. Liu J, Grundy SM, Wang W, Smith SC Jr, Vega GL, Wu Z, et al. Ten-year risk of cardiovascular incidence related to diabetes, prediabetes and the metabolic syndrome. Am Heart J 2007;153(4):552–558.
19. Seo JM. Gender differences in association between socioeconomic status and incident metabolic syndrome in Korean adults [dissertation] Cheongju: Chungbuk National University; 2015. Korean.
20. Dallongeville J, Cottel D, Ferrières J, Arveiler D, Bingham A, Ruidavets JB, et al. Household income is associated with the risk of metabolic syndrome in a sex-specific manner. Diabetes Care 2005;28(2):409–415.
21. Marquezine GF, Oliveira CM, Pereira AC, Krieger JE, Mill JG. Metabolic syndrome determinants in an urban population from Brazil: social class and gender-specific interaction. Int J Cardiol 2008;129(2):259–265.
22. Brown AF, Ettner SL, Piette J, Weinberger M, Gregg E, Shapiro MF, et al. Socioeconomic position and health among persons with diabetes mellitus: a conceptual framework and review of the literature. Epidemiol Rev 2004;26:63–77.
23. Loucks EB, Rehkopf DH, Thurston RC, Kawachi I. Socioeconomic disparities in metabolic syndrome differ by gender: evidence from NHANES III. Ann Epidemiol 2007;17:19–26.
24. Kim MH, Cho YS, Uhm WS, Kim S, Bae SC. Cross-cultural adaptation and validation of the Korean version of the EQ-5D in patients with rheumatic diseases. Qual Life Res 2005;14(5):1401–1406.
25. Kim JH. The relationship among socioeconomic status, health behavior, and self-rated health status in employees: gender difference. Korean J Health Educ Promot 2011;28(1):57–67.
26. Kim YS. Equity in health status and health care utilization by income: analyzing different populations in old adults. Health Soc Sci 2012;31:55–81.
27. Lee YJ. A equity in health care utilization by health statuss. Korea Soc Policy Rev 2010;17(1):267–290.
28. Korea centers for disease control and prevention. The Third Korea National Health and Nutrition Examination Survey Guide Book. KNHANES III 2005 [Internet] Osong: Korea centers for disease control and prevention; 2006. Accessed Jan, 2014. Available form: https://knhanes.cdc.go.kr/knhanes/sub03/sub03_02_02.do.
29. House JS, Laritz PM, Herd P. Continuity and change in the social stratification of aging and health over the life course: Evidence from a Nationally Representative Longitudinal Study from 1986 to 2001/2002(American's Changing Lives Study). J Gerontol B Psychol Sci Soc Sci 2005;60(Special_Issue_2):S15–S26.

Article information Continued

Copyright © 2017 Korean Society for Health Promotion and Disease Prevention

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Funded by : Pusan National University Hospitalhttp://dx.doi.org/10.13039/501100008130

Table 1

General characteristics and health behaviors according to house hold income groups aged over 35 years women.

Table 1

Values are presented as unweighted number.

Continuous variables: estimated mean±SE, Categorical variables: % (SE).

P values are obtained by cross tabulation analysis (Rao-Scott chi-square test) in complex sample design.

aP values are obtained by general linear regression model in complex sample design.

bHigh risk drinking for women is defined as more than twice a week.

cExercise is defined as high intensity exercise 20 minutes more than 3 times per week or moderate intensity exercise 30 minutes more than 5 times per week or walking 30 minutes more than 5 times per week.

Table 2

Morbidity, health status, health care utilization according to house hold income groups aged over 35 years women.

Table 2

Values are presented as unweighted number (% SE).

P values are obtained by cross tabulation analysis (Rao-Scott chi-square test) in complex sample design.

aAssessed by logistic regression analysis.

bDiagnosed by a doctor.

Table 3

Anthropometric measurement and biochemical factors according to house hold income groups aged over 35 years women.

Table 3

Abbreviations: BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; GOT, glutamic oxalacetic transaminase; GTP, glutamic pyruvate transaminase; BUN, blood urea nitrogen; LDL-chol, low density lipoprotein cholesterol; HDL-chol, high density lipoprotein cholesterol; FBS, fasting blood sugar.

Values are presented as unweighted number (estimated mean±SE).

P values are obtained by general linear regression model in complex sample design.

aAssessed by logistic regression analysis.

Table 4

Number of cardiovascular disease risk according to house hold income groups aged over 35 years women.

Table 4

Abbreviation: HTN, hypertension; BMI, body mass index; HDL-chol, high density lipoprotein cholesterol.

Values are presented as unweighted number.

Continuous variables: estimated mean±SE, Categorical variables: % (SE).

P values are obtained by cross tabulation analysis (Rao-Scott chi-square test) in complex sample design.

aAssessed by logistic regression analysis

bP values are obtained by general linear regression model in complex sample design.

cLack of exercise is defined as not doing high intensity exercise 20 minutes more than 3 times per week or moderate intensity exercise 30 minutes more than 5 times per week or walking 30 minutes more than 5 times per week.

Table 5

Self-perceived health status and quality of life according to house hold income groups aged over 35 years women

Table 5

Values are presented as unweighted number (% SE).

P values are obtained by cross tabulation analysis (Rao-Scott chi-square test) in complex sample design.

aAssessed by logistic regression analysis.