Next Article in Journal
Changes in Metabolic Syndrome Status and Risk of Dementia
Next Article in Special Issue
Postprandial Hypotension as a Risk Factor for the Development of New Cardiovascular Disease: A Prospective Cohort Study with 36 Month Follow-Up in Community-Dwelling Elderly People
Previous Article in Journal
Design and Measurement Properties of the Online Gambling Disorder Questionnaire (OGD-Q) in Spanish Adolescents
Previous Article in Special Issue
Decision Support for the Optimization of Provider Staffing for Hospital Emergency Departments with a Queue-Based Approach
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Relationship between Morbidity and Health Behavior in Chronic Diseases

1
Research Institute for Future Medicine, Samsung Medical Center, Seoul 06351, Korea
2
Department of Medical Device Management and Research, SAIHST, Sungkyunkwan University, Seoul 06355, Korea
3
Department of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
*
Author to whom correspondence should be addressed.
J. Clin. Med. 2020, 9(1), 121; https://doi.org/10.3390/jcm9010121
Submission received: 15 November 2019 / Revised: 25 December 2019 / Accepted: 26 December 2019 / Published: 2 January 2020
(This article belongs to the Special Issue Clinical Medicine for Healthcare and Sustainability)

Abstract

:
This study aimed to analyze the demographic characteristics and health behaviors related to chronic diseases and to identify factors that may affect chronic diseases. Data from the Seventh Korea National Health and Nutrition Examination Survey were used, and 3795 adults aged above 40 years were included. The following demographic variables were obtained: sex, age, education, income, type of health insurance, and private insurance. The following health behavior factors were also analyzed: medical checkup, drinking, smoking, exercise, obesity, and hypercholesterolemia. Participants with lower socioeconomic status had a higher risk of developing chronic diseases. Meanwhile, those with private health insurance had a lower risk of developing chronic diseases. In addition, participants who underwent medical checkups and performed exercises had a lower risk, while those with obesity and hypercholesterolemia had a higher risk of developing chronic diseases. It is necessary to manage chronic diseases through comprehensive programs, rather than managing these diseases individually, and through community primary care institutions to improve health behaviors.

1. Introduction

An individual’s behavior related to health may have an effect on their physical health or ability to recover from illness. In particular, health-related behavior, such as a lack of exercise, smoking, and drinking, are some of the main factors that can contribute to morbidity and mortality [1,2,3]. Health behavior affects 40% of premature deaths; in order to reduce premature mortality, improving health behaviors is more cost-effective than improving the social and physical environments or health-care systems [4]. These health behaviors are important in maintaining good health, which is influenced by biological and socioeconomic factors, among others [5,6]. Rapid economic growth, high health-care costs, lifestyle changes, and population aging have been associated with an increased prevalence of chronic diseases worldwide. Chronic diseases may cause complications, and thus, require continuous care and are among the types of diseases with high health-care costs due to their long disease duration [7,8,9].
Chronic diseases, one of the leading causes of death worldwide, especially cardiocerebrovascular diseases, diabetes, and hypertension, have a high mortality rate. However, the mortality rate of chronic diseases can be reduced through prevention [10,11,12]. Chronic disease is closely related to changes in health behaviors; the main health behaviors affecting the development of chronic diseases include health risk behavioral factors, such as smoking, drinking, and physical activities, and clinicopathologic factors, including obesity, hypertension, and hypercholesterolemia [13,14]. In particular, since health-related lifestyles have increased the risk of mortality, the significance of managing health risk behavioral factors has also been increasing. Thus, it is necessary to prevent chronic diseases and delay the aggravation of symptoms by improving individual lifestyles [15,16,17]. In addition, individual health behaviors may differ according to sociodemographic characteristics including age and sex [18]. In the identification of the individual physical condition, sociodemographic and socioeconomic factors are known to act as important factors, and prevalence rates vary in accordance with the individual’s income level, education level, and socioeconomic factors [19].
Previous studies have analyzed the relationship between chronic diseases and health promotion behaviors, but were only conducted in predetermined age groups, such as in older patients, or examined the relationship between chronic diseases and health behaviors while only targeting certain chronic diseases [20,21,22,23,24]. As the number of polychronic patients has increased, a comprehensive analysis of chronic diseases is required. To date, the number of studies evaluating patients with chronic diseases is limited. Accordingly, in this study, we aimed to analyze the sociodemographic characteristics and health behaviors related to the development of chronic diseases and to identify factors that may have an effect on the morbidity of chronic diseases. Through this and by suggesting measures to contribute to the effective management and prevention of chronic diseases, we intend to promote the health of the people.

2. Experimental Section

2.1. Data Source and Research Participants

In this study, we utilized the source data from the 2nd year (2017) of the 7th period of the Korea National Health and Nutrition Examination Survey, performed by the Korea Centers for Disease Control and Prevention. The Korea National Health and Nutrition Examination Survey (KNHANES) is a nationwide national survey, conducted to determine health-related parameters including the prevalence of chronic diseases and health behaviors based on Article 16 of the National Health Promotion Act. A total of 10,430 individuals from 3580 households were surveyed, but only 8127 participated in the study. Of them, 5159 aged above 40 years were extracted. In addition, 658 individuals whose answers were not related to chronic diseases were excluded; hence, only 3795 participants were analyzed, after further excluding 706 who did not respond to the questions related to health behaviors. The KNHANES is approved by the ethical committee of the Korea Centers for Disease Control and Prevention. The requirement for informed consent was waived because data in the KNHANE database are anonymized in adherence to strict confidentiality guidelines. The flowchart is shown in Figure 1.

2.2. Description of Variables

In this study, questions related to sociodemographic characteristics, morbidity, and presence of chronic diseases, and health behaviors were utilized. Sex, age, education level, level of income, type of health insurance, and private insurance policy were used as sociodemographic variables. In terms of age, participants aged 19 years or older were divided into two groups: adults and older adults (aged 65 years and above). The education level was stratified into middle school graduates or less and high school graduates or more. Income status was determined by the monthly mean household gross income and was classified based on 3 million won as the cut-off point. The patients with health insurance were classified as health insurance subscribers and medical care beneficiaries [23,25,26,27,28].
Hypertension and diabetes are the main causes of cardiovascular disease, and the number of patients continues to rise due to the increase in obesity rate. In addition, the cost of medical care is proliferating more rapidly than the number of patients. Therefore, it is significant to prevent it by analyzing the factors influencing chronic diseases. Hitherto, chronic disease was defined as hypertension, dyslipidemia, stroke, myocardial infarction, and diabetes. The presence of chronic disease was determined based on a response of “Yes” to the question related to a doctor’s diagnosis. Health behaviors included health checkups, drinking, smoking, exercise, obesity, and hypercholesterolemia [28,29,30,31]. Health checkup status was classified as patients who underwent health checkups and those who did not undergo health checkups. Drinking status was classified as non-drinkers and drinkers based on the monthly drinking rate; smoking status was classified as non-smokers and smokers using the current smoking rate. Exercise history was stratified as those who performed exercises and those who did not perform exercises based on the aerobic physical activity practice rate [32,33]. Furthermore, the prevalence of obesity was determined and obesity was stratified based on the following indices: a body mass index of 18.5 kg/m2 or higher or a body mass index of 23 kg/m2 or lower indicates normal weight, while a body mass index of 25 kg/m2 or higher indicates obesity [34,35,36]. Hypercholesterolemia was stratified based on its prevalence (Table 1).

2.3. Statistical Analysis

In order to analyze the relationship among sociodemographic characteristics, health behaviors, and the presence of chronic diseases, statistical analyses were conducted using the SPSS (version 25.0, https://www.ibm.com/kr-ko/analytics/spss-statistics-software).
First, cross-analysis was performed to analyze the relationship between chronic diseases and sociodemographic characteristics and between health behaviors and chronic diseases. In order to determine the relationship between sociodemographic characteristics and health behaviors and the risk for developing chronic diseases, a logistic regression analysis was performed.

3. Results

3.1. Participants’ Demographic Characteristics

Of the total participants, 56% were women and the proportion of women was higher than that of men; older adults aged 65 years or higher accounted for 33% of the total study population. Most of the participants were middle school graduates or had obtained higher education (2269 persons, 59.8%) and had an income of more than 3 million won (2107 persons, 55.5%). With regard to the type of health insurance, national health insurance subscribers accounted for 95.7% of the total participants according to the characteristics of health insurance in Korea. Meanwhile, private insurance subscribers accounted for 74.2%, even though the proportion of health insurance subscribers corresponded to a majority; this finding indicates that most of the patients took a private medical insurance policy due to the lack of coverage by the national health insurance. A total of 857 patients (22.6%) underwent medical checkups, which suggests that only a few patients were able to undergo medical checkups. A total of 1762 patients (46.4%) developed chronic diseases, of whom 21.4% had two or more chronic diseases (Table 2).

3.2. Relationship between Demographic Characteristics and Chronic Diseases

In this study, we intended to analyze the relationship between sociodemographic characteristics and chronic diseases, and the results are shown in Table 3. Among chronic disease patients, 955 (44.9%) were women, this proportion being higher than that of men. Meanwhile, 807 (48.4%) of 862 male participants had chronic diseases, which indicates that men had a higher rate of chronic disease morbidity. Approximately 71.3% of the participants aged 65 years or higher had chronic diseases. In addition, most of the patients with a lower educational level and lower-income level had chronic diseases (981 patients (64.3%)and 1008 patients (59.7%), respectively). A total of 1648 (45.4%) health insurance subscribers were chronic disease patients, while 114 (69.9%) medical care recipients were chronic disease patients. Furthermore, 1128 (40.1%) chronic disease patients were private insurance subscribers.

3.3. Relationship between Health Behavior and Chronic Diseases

We analyzed the relationship between health behaviors and chronic diseases; the results are shown in Table 4. Of the total chronic disease patients, 944 (50.6%) were alcohol drinkers, 1503 (47%) were smokers, and 605 (40.1%) performed exercises, which is less than the number of patients who did not perform exercises (1157, 50.6%). Moreover, 1263 (52.7%) and 823 (73.9%) patients with obesity and hypercholesterolemia, respectively, had chronic diseases.

3.4. Factors Affecting Chronic Diseases

In order to determine the factors that may affect the development of chronic diseases, logistic regression analysis was performed, and the results are shown in Table 5. The factors with statistically significant effects in patients with chronic disease included sex, age, education, income, types of health insurance, decision to take a private insurance policy, health checkups, exercise, obesity, and hypercholesterolemia.
In men, the risk of developing chronic diseases was higher by 1.498 times. Further, as age increased, the risk of developing chronic diseases also increased by 3.145 times. In participants with a higher education level, the risk of developing chronic diseases increased by 0.535 times. In participants with higher income, the risk of developing chronic disease reduced by 0.773 times. With regard to the type of health insurance, the risk of developing chronic diseases increased by 1.727 times among medical care beneficiaries. In addition, for those who took a private insurance policy, the risk of developing chronic diseases increased by 0.782 times. Meanwhile, the risk of developing chronic diseases decreased by 0.782 times and 0.861 times among those who underwent medical checkups and who performed exercises, respectively. In normal-weight people, the risk of developing chronic diseases reduced by 0.544 times. In patients with hypercholesterolemia, the risk increased by 5.444 times.

4. Discussion

In this study, we analyzed the factors affecting the development of chronic diseases through logistic regression analysis using the data from the Korea National Health and Nutrition Examination Survey (2017). Of the sociodemographic characteristics, sex, age, education and income level, types of health insurance, and private insurance were found to have an effect on chronic diseases. In terms of sex, the proportion of women with chronic diseases was higher than that of men. Compared with women, men had a higher rate of chronic disease morbidity and the risk of developing chronic diseases. These results are inconsistent with those of previous studies, which reported that the prevalence of chronic diseases is higher among women than in men because men can maintain their economic level for longer than women. Women who have a lower income level than men have relatively low medical accessibility and find it difficult to manage their chronic diseases [37]. The number of chronic disease patients is increasing due to the lack of physical activity and the increasing prevalence of hypercholesterolemia and obesity, and considering that previous studies have shown that the prevalence of chronic disease was lower among men who received management, managing chronic diseases according to sex seems to be of utmost importance [38]. In addition, the number of patients aged 65 years or older who had chronic diseases was higher; therefore, the higher the age, the higher the risk of developing chronic diseases. This finding is consistent with those of a previous study, which reported that as age increases, the prevalence of chronic diseases also increases due to the decreased amount of physical activities and habit-based health risk behaviors [8,39].
It was also found that the higher the income and education levels, the lower the risk of chronic diseases. This finding is consistent with those of previous studies reporting that socioeconomic status, including income, education, and occupation levels, affects the health-related lifestyles and risk of chronic diseases [40]. Because of the low rates of physical activity and exercise practice and as the provision of medical services for managing chronic diseases has still not been ensured owing to lower educational levels or living standards, the prevalence of chronic diseases is increasing. Among medical care beneficiaries, the risk of developing chronic diseases was high, which was similar to the results of a previous study reporting that the incidence of chronic disease increased among individuals who belonged to the lower social class, like those in the low-income bracket. Social determinants, such as income, education, and social class, may cause health-related inequality but create an environment in which quality medical care can be provided for the treatment of chronic diseases. In addition, non-medical factors, such as social determinants, play a more substantial role in the management of chronic diseases than medical factors. It seems that medical care beneficiaries with low income may have more difficulty in managing chronic diseases [41,42,43]. There were many chronic disease patients who obtained a private medical insurance policy; the results showed that patients with private medical insurance had a lower risk of developing chronic diseases. These findings are similar to those of a previous study, which indicated that those who have private medical insurance policies tend to receive outpatient and inpatient treatments. In line with these findings, among patients with chronic diseases who require continuous health care, those with private medical insurance have a reduced burden in terms of medical expenses, leading to better health-care outcomes [44,45,46]. Considering these results, there are limitations in managing chronic diseases with national health insurance only. Furthermore, it is estimated that people obtain commercial medical insurance policies due to the burden of medical expenses caused by the recent increase in polychronic diseases. Therefore, since health-related inequalities in the low-income group patients, who find it difficult to pay the private medical insurance premiums, will become a serious problem if we only rely on private medical insurance for the management of chronic diseases, the coverage of the national health insurance should be reinforced for the management of chronic diseases.
Among health behaviors, the factors affecting the risk of developing chronic diseases included health checkups, exercise, obesity, and hypercholesterolemia. Those who underwent periodic health checkups had a risk of developing chronic diseases, which is similar to previous findings showing that periodic health checkups promote health and help prevent chronic diseases [8,47]. In addition, considering the results of previous studies reporting that those who benefit from health insurance are more likely to receive health checkups depending on the nature of the health insurance system in Korea, chronic diseases could be effectively managed through modifying the nature of the insurance provided. Previous studies have shown that health behavior factors related to chronic diseases include smoking, drinking, exercise, body mass index, and regular life and eating habits [7,29,36,48,49]. However, in this study, drinking and smoking did not have a statistically significant effect on the prevalence of chronic diseases, and these results are different from those of existing research. Furthermore, exercise, obesity, and hypercholesterolemia were associated with the risk of developing chronic diseases, consistent with existing research. Among those who performed exercises, the risk of developing chronic diseases was lower, while among those with obesity and hypercholesterolemia, the risk of developing chronic diseases was higher. Weight loss via exercise programs reduces the risk of developing chronic diseases. Maintaining a standard body weight can prevent chronic diseases by alleviating hypercholesterolemia. Management of chronic diseases should be comprehensively performed with weight management through exercise; however, there seems to be a limitation in this regard according to patients’ behavioral changes [50,51]. In order to overcome this limitation, wearable medical devices, which use ICT (Information & Communication Technology), have recently been developed for chronic disease management. Prevention and management of chronic diseases can be ensured through exercise [52,53,54,55]. The use of medical devices to promote physical activity leads to obesity and hypercholesterolemia management, and through the linkage between these medical devices and local clinic-centered, effective management of chronic diseases can be achieved through periodic monitoring. The results of this study also suggest that gender, age, education, and income levels have impacts on chronic disease, and it is significant to add these as risk factors and to continue monitoring in local clinic-centered facilities. Through this, a personalized chronic disease management system could be established.
This study has some limitations. First, chronic disease patients aged 40 years or below were not included. Recently, the number of younger chronic disease patients has increased owing to changes in lifestyle, therefore, further studies to analyze the factors influencing the risk of developing chronic diseases in this age group will be required, with the patients stratified as follows: youth, middle-aged, and older adults. Second, analyses according to the number of chronic diseases were not performed. In this study, only the presence or absence of chronic diseases in patients was assessed. Further studies to determine the influencing factors according to the number of chronic diseases are required. Third, there was no analysis of factors affecting chronic disease according to the residential area. Accessibility to medical services varies depending on where you live; therefore, chronic disease management may be different. Hence, it is necessary to analyze the factors affecting chronic diseases according to urban and rural areas. Despite these limitations, we comprehensively analyzed the factors influencing the prevalence of chronic diseases. Our study is significant as we were able to determine the risk factors for chronic diseases, which can be used as a basis for developing policies for the comprehensive management of chronic diseases, based on sex, age, and social factors.

5. Conclusions

In order to manage chronic diseases, the management approach should be based on patients’ socioeconomic characteristics to address the differences related to sex, education, income, and medical care. The management should also include approaches to improve health behaviors, including the use of wearable medical devices and digital healthcare products. Based on our findings, we presume that chronic diseases develop due to a combination of factors. Age, socioeconomic factors, obesity, and hypercholesterolemia are factors that can be controlled to prevent and manage chronic diseases through comprehensive programs rather than through individual management. Moreover, those who belong to the lower social class, are more likely to require chronic disease management via primary healthcare institutions in the community. In order to improve health behaviors, continuous observation is required, and local clinic-centered chronic disease management can help improve health behaviors. It is significant to establish a comprehensive management system and promote efficient medical delivery systems for chronic diseases focused on local clinic-centered facilities. However, Korea’s medical delivery system urgently needs reorganization due to the concentration of university hospitals and the weakening of a local clinic-centered structure. Therefore, in order to expand the role of local clinic-centered facilities and to efficiently manage chronic diseases, the integrated local clinic-centered care chronic disease management project is being implemented. Through this, medical treatment for chronic disease management and education for improving lifestyle, are applied to lower the patient’s copayment. If the burden reduction of chronic disease management is expanded, the dependency on private health insurance will be reduced, which will prevent excessive medical expenses for chronic patients. In addition, strengthening the role of local clinic-centered facilities will lead to strengthening medical access for low-income people, thereby relieving health inequalities. For older adults, when included in the community care project in line with community-based primary healthcare service, comprehensive management of chronic diseases, including health improvement and lifestyle modification, could be implemented. In particular, in Europe, where public health policies are in place, chronic diseases are effectively managed by strengthening the local clinic-centered services, such as the attending physician, to manage chronic diseases. For common goals such as chronic disease management, community care is implemented to ensure continuous health care. In view of this, chronic disease management through public health policy should be implemented prior to private medical insurance. Patients with private medical insurance have a lower risk of developing chronic diseases, but this can be seen as a problem of low insurance coverage for chronic diseases. This can be resolved through community care projects such as in Europe. Because of this, patient-centered chronic disease management will ultimately improve the health of chronic disease patients.

Author Contributions

Conceptualization, M.L.; methodology, S.P.; software, S.P.; validation, M.L. and K.-S.L.; formal analysis, M.L.; writing—original draft preparation, S.P.; writing—review and editing, M.L.; supervision, K.-S.L.; project administration, M.L. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2019S1A5A2A03040304).

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Janowski, K.; Kurpas, D.; Kusz, J.; Mroczek, B.; Jedynak, T. Health-related behavior, profile of health locus of control and acceptance of illness in patients suffering from chronic somatic diseases. PLoS ONE 2013, 8, e63920. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Mullen, P.D.; Hersey, J.C.; Iverson, D.C. Health behavior models compared. Soc. Sci. Med. 1987, 24, 973–981. [Google Scholar] [CrossRef]
  3. Berrigan, D.; Dodd, K.; Troiano, R.P.; Krebs-Smith, S.M.; Barbash, R.B. Patterns of health behavior in U.S. adults. Prev. Med. 2003, 36, 615–623. [Google Scholar] [CrossRef]
  4. McGinnis, J.M.; Williams-Russo, P.; Knickman, J.R. The case for more active policy attention to health promotion. Health Aff. 2002, 21, 78–93. [Google Scholar] [CrossRef]
  5. Jarvandi, S.; Yan, Y.; Schootman, M. Income disparity and risk of death: The importance of health behaviors and other mediating factors. PLoS ONE 2012, 7, e49929. [Google Scholar] [CrossRef] [Green Version]
  6. Nettle, D. Why are there social gradients in preventative health behavior? A perspective from behavioral ecology. PLoS ONE 2010, 5, e13371. [Google Scholar] [CrossRef] [Green Version]
  7. Paudel, S.; Owen, A.J.; Owusu-Addo, E.; Smith, B.J. Physical activity participation and the risk of chronic diseases among South Asian adults: A systematic review and meta-analysis. Sci. Rep. 2019, 9, 9771. [Google Scholar] [CrossRef]
  8. Strong, K.; Mathers, C.; Leeder, S.; Beaglehole, R. Preventing chronic diseases: How many lives can we save? Lancet 2005, 366, 1578–1582. [Google Scholar] [CrossRef]
  9. Yach, D.; Hawkes, C.; Gould, C.L.; Hofman, K.J. The Global Burden of Chronic DiseasesOvercoming Impediments to Prevention and Control. JAMA 2004, 291, 2616–2622. [Google Scholar] [CrossRef]
  10. Bae, E.-J.; Park, N.-J.; Sohn, H.-S.; Kim, Y.-H. Handgrip strength and all-cause mortality in middle-aged and older Koreans. Int. J. Environ. Res. Public Health 2019, 16, 740. [Google Scholar] [CrossRef] [Green Version]
  11. Gansevoort, R.T.; Correa-Rotter, R.; Hemmelgarn, B.R.; Jafar, T.H.; Heerspink, H.J.L.; Mann, J.F.; Matsushita, K.; Wen, C.P. Chronic kidney disease and cardiovascular risk: Epidemiology, mechanisms, and prevention. Lancet 2013, 382, 339–352. [Google Scholar] [CrossRef]
  12. Halpin, H.A.; Morales-Suárez-Varela, M.M.; Martin-Moreno, J.M. Chronic Disease Prevention and the New Public Health. Public Health Rev. 2010, 32, 120–154. [Google Scholar] [CrossRef] [Green Version]
  13. Sturm, R. The effects of obesity, smoking, and drinking on medical problems and costs. Health Aff. 2002, 21, 245–253. [Google Scholar] [CrossRef] [PubMed]
  14. Strine, T.W.; Chapman, D.P.; Balluz, L.S.; Moriarty, D.G.; Mokdad, A.H. The associations between life satisfaction and health-related quality of life, chronic illness, and health behaviors among US community-dwelling adults. J. Community Health 2008, 33, 40–50. [Google Scholar] [CrossRef]
  15. Harris, M. The role of primary health care in preventing the onset of chronic disease, with a particular focus on the lifestyle risk factors of obesity, tobacco and alcohol. Canberra Natl. Prev. Health Taskforce 2008, 1, 21. [Google Scholar]
  16. Steyn, K.; Damasceno, A. Lifestyle and related risk factors for chronic diseases. Dis. Mortal. Sub-Sahar. Afr. 2006, 2, 247–265. [Google Scholar]
  17. Reeves, M.J.; Rafferty, A.P. Healthy lifestyle characteristics among adults in the United States, 2000. Arch. Intern. Med. 2005, 165, 854–857. [Google Scholar] [CrossRef] [Green Version]
  18. Kang, Y.J.; Kang, M.-Y. Chronic diseases, health behaviors, and demographic characteristics as predictors of ill health retirement: Findings from the Korea Health Panel Survey (2008–2012). PLoS ONE 2016, 11, e0166921. [Google Scholar] [CrossRef]
  19. Winkleby, M.A.; Cubbin, C. Changing patterns in health behaviors and risk factors related to chronic diseases, 1990–2000. Am. J. Health Promot. 2004, 19, 19–27. [Google Scholar] [CrossRef]
  20. Speake, D.L.; Cowart, M.E.; Pellet, K. Health perceptions and lifestyles of the elderly. Res. Nurs. Health 1989, 12, 93–100. [Google Scholar] [CrossRef]
  21. Cho, Y.I.; Lee, S.-Y.D.; Arozullah, A.M.; Crittenden, K.S. Effects of health literacy on health status and health service utilization amongst the elderly. Soc. Sci. Med. 2008, 66, 1809–1816. [Google Scholar] [CrossRef] [PubMed]
  22. Lee, T.W.; Ko, I.S.; Lee, K.J. Health promotion behaviors and quality of life among community-dwelling elderly in Korea: A cross-sectional survey. Int. J. Nurs. Stud. 2006, 43, 293–300. [Google Scholar] [CrossRef] [PubMed]
  23. Winkleby, M.A.; Jatulis, D.E.; Frank, E.; Fortmann, S.P. Socioeconomic status and health: How education, income, and occupation contribute to risk factors for cardiovascular disease. Am. J. Public Health 1992, 82, 816–820. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Innes, H.; McAuley, A.; Alavi, M.; Valerio, H.; Goldberg, D.; Hutchinson, S.J. The contribution of health risk behaviors to excess mortality in American adults with chronic hepatitis C: A population cohort-study. Hepatology 2018, 67, 97–107. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Lim, J.; Kim, S.; Ke, S.; Cho, B. The Association Chronic Liver Diseases with Health Related Behaviors in South Korea. Korean J. Fam. Med. 2010, 31, 302–307. [Google Scholar] [CrossRef]
  26. Caspersen, C.J.; Pereira, M.A.; Curran, K.M. Changes in physical activity patterns in the United States, by sex and cross-sectional age. Med. Sci. Sports Exerc. 2000, 32, 1601–1609. [Google Scholar] [CrossRef] [Green Version]
  27. Chang, O.; Choi, E.-K.; Kim, I.-R.; Nam, S.-J.; Lee, J.E.; Lee, S.K.; Im, Y.-H.; Park, Y.H.; Cho, J. Association between socioeconomic status and altered appearance distress, body image, and quality of life among breast cancer patients. Asian Pac. J. Cancer Prev. 2014, 15, 8607–8612. [Google Scholar] [CrossRef] [Green Version]
  28. Fine, L.J.; Philogene, G.S.; Gramling, R.; Coups, E.J.; Sinha, S. Prevalence of multiple chronic disease risk factors: 2001 National Health Interview Survey. Am. J. Prev. Med. 2004, 27, 18–24. [Google Scholar] [CrossRef]
  29. Lee, M.; Yoon, K. Catastrophic Health Expenditures and Its Inequality in Households with Cancer Patients: A Panel Study. Processes 2019, 7, 39. [Google Scholar] [CrossRef] [Green Version]
  30. McCann, B.A.; Ewing, R. Measuring the Health Effects of Sprawl: A National Analysis of Physical Activity, Obesity and Chronic Disease. Geography 2003. [Google Scholar] [CrossRef]
  31. Katzmarzyk, P.; Lear, S. Physical activity for obese individuals: A systematic review of effects on chronic disease risk factors. Obes. Rev. 2012, 13, 95–105. [Google Scholar] [CrossRef] [PubMed]
  32. Mukamal, K.J.; Ding, E.L.; Djoussé, L. Alcohol consumption, physical activity, and chronic disease risk factors: A population-based cross-sectional survey. BMC Public Health 2006, 6, 118. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Cho, E.R.; Shin, A.; Kim, J.; Jee, S.H.; Sung, J. Leisure-time physical activity is associated with a reduced risk for metabolic syndrome. Ann. Epidemiol. 2009, 19, 784–792. [Google Scholar] [CrossRef] [PubMed]
  34. Choban, P.; Flancbaum, L. Nourishing the obese patient. Clin. Nutr. 2000, 19, 305–311. [Google Scholar] [CrossRef]
  35. Chan, M.; Lim, Y.; Ernest, A.; Tan, T. Nutritional assessment in an Asian nursing home and its association with mortality. J. Nutr. Health Aging 2010, 14, 23–28. [Google Scholar] [CrossRef]
  36. Kim, Y.-H.; Kim, S.M.; Han, K.-D.; Jung, J.-H.; Lee, S.-S.; Oh, S.W.; Park, H.S.; Rhee, E.-J.; Lee, W.-Y.; Yoo, S.J. Waist Circumference and All-Cause Mortality Independent of Body Mass Index in Korean Population from the National Health Insurance Health Checkup 2009–2015. J. Clin. Med. 2019, 8, 72. [Google Scholar] [CrossRef] [Green Version]
  37. Virtanen, M.; Oksanen, T.; Batty, G.D.; Ala-Mursula, L.; Salo, P.; Elovainio, M.; Pentti, J.; Lybäck, K.; Vahtera, J.; Kivimäki, M. Extending employment beyond the pensionable age: A cohort study of the influence of chronic diseases, health risk factors, and working conditions. PLoS ONE 2014, 9, e88695. [Google Scholar] [CrossRef] [Green Version]
  38. Park, M.; Park, Y.; Kim, S.; Park, S.; Seol, H.; Woo, S.; Cho, S.; Lim, D.-S. Introduction and effectiveness of The Seoul Metabolic Syndrome Management. Public Health Aff. 2017, 1, 25–39. [Google Scholar] [CrossRef] [Green Version]
  39. Zhao, C.; Wong, L.; Zhu, Q.; Yang, H. Prevalence and correlates of chronic diseases in an elderly population: A community-based survey in Haikou. PLoS ONE 2018, 13, e0199006. [Google Scholar] [CrossRef] [Green Version]
  40. Cockerham, W.C.; Hamby, B.W.; Oates, G.R. The social determinants of chronic disease. Am. J. Prev. Med. 2017, 52, S5–S12. [Google Scholar] [CrossRef] [Green Version]
  41. Martínez-García, M.; Salinas-Ortega, M.; Estrada-Arriaga, I.; Hernández-Lemus, E.; García-Herrera, R.; Vallejo, M. A systematic approach to analyze the social determinants of cardiovascular disease. PLoS ONE 2018, 13, e0190960. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Taylor, L.A.; Tan, A.X.; Coyle, C.E.; Ndumele, C.; Rogan, E.; Canavan, M.; Curry, L.A.; Bradley, E.H. Leveraging the social determinants of health: What works? PLoS ONE 2016, 11, e0160217. [Google Scholar] [CrossRef] [PubMed]
  43. Nicholas, S.B.; Kalantar-Zadeh, K.; Norris, K.C. Socioeconomic disparities in chronic kidney disease. Adv. Chronic Kidney Dis. 2015, 22, 6–15. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Jeon, B.; Kwon, S. Effect of private health insurance on health care utilization in a universal public insurance system: A case of South Korea. Health Policy 2013, 113, 69–76. [Google Scholar] [CrossRef] [PubMed]
  45. Lee, M.; Yoon, K.; Choi, M. Private health insurance and catastrophic health expenditures of households with cancer patients in South Korea. Eur. J. Cancer Care 2018, 27, e12867. [Google Scholar] [CrossRef]
  46. Mulcahy, A.W.; Eibner, C.; Finegold, K. Gaining coverage through Medicaid or private insurance increased prescription use and lowered out-of-pocket spending. Health Aff. 2016, 35, 1725–1733. [Google Scholar] [CrossRef] [Green Version]
  47. Culica, D.; Rohrer, J.; Ward, M.; Hilsenrath, P.; Pomrehn, P. Medical checkups: Who does not get them? Am. J. Public Health 2002, 92, 88–91. [Google Scholar] [CrossRef]
  48. Liu, Y.; Croft, J.B.; Wheaton, A.G.; Kanny, D.; Cunningham, T.J.; Lu, H.; Onufrak, S.; Malarcher, A.M.; Greenlund, K.J.; Giles, W.H. Clustering of Five Health-Related Behaviors for Chronic Disease Prevention Among Adults, United States, 2013. Prev. Chronic Dis. 2016, 13, E70. [Google Scholar] [CrossRef] [Green Version]
  49. Campbell, D.J.; Ronksley, P.E.; Manns, B.J.; Tonelli, M.; Sanmartin, C.; Weaver, R.G.; Hennessy, D.; King-Shier, K.; Campbell, T.; Hemmelgarn, B.R. The association of income with health behavior change and disease monitoring among patients with chronic disease. PLoS ONE 2014, 9, e94007. [Google Scholar] [CrossRef] [Green Version]
  50. Thande, N.K.; Hurstak, E.E.; Sciacca, R.E.; Giardina, E.G.V. Management of obesity: A challenge for medical training and practice. Obesity 2009, 17, 107–113. [Google Scholar] [CrossRef]
  51. Lee, M.; Yoon, K.; Lee, K.-S. Subjective health status of multimorbidity: Verifying the mediating effects of medical and assistive devices. Int. J. Equity Health 2018, 17, 164. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  52. Zhu, X.; Cahan, A. Wearable technologies and telehealth in Care Management for Chronic Illness. In Healthcare Information Management Systems; Springer: Cham, Switzerland, 2016; pp. 375–398. [Google Scholar]
  53. Kang, S.Y. The ICT Technology for Geriatric Diseases Healthcare. In Information Science and Applications (ICISA) 2016; Springer: Singapore, 2016; pp. 1495–1500. [Google Scholar]
  54. Bodenheimer, T.; Lorig, K.; Holman, H.; Grumbach, K. Patient self-management of chronic disease in primary care. JAMA 2002, 288, 2469–2475. [Google Scholar] [CrossRef] [PubMed]
  55. Chiauzzi, E.; Rodarte, C.; DasMahapatra, P. Patient-centered activity monitoring in the self-management of chronic health conditions. BMC Med. 2015, 13, 77. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Figure 1. Flowchart of the study.
Figure 1. Flowchart of the study.
Jcm 09 00121 g001
Table 1. Classification and definition of variables.
Table 1. Classification and definition of variables.
VariableDefinition
Sex0 = Female
1 = Male
Age0 = Adult
1 = Senior
Education0 = ≤Middle school
1 = ≥Middle school
Income0 = <300
1 = ≥300
Type of insurance0 = National Health Insurance
1 = Assistance
Private insurance0 = No
1 = Yes
Chronic disease0 = No
1 = Yes
Medical checkup0 = No
1 = Yes
Drinking0 = Non-drinker
1 = Drinker
Smoking0 = Non-smoker
1 = Smoker
Exercise0 = No
1 = Yes
Obesity0 = Obesity
1 = Normal
Hypercholesterolemia0 = No
1 = Yes
Table 2. Demographic characteristics (n = 3795).
Table 2. Demographic characteristics (n = 3795).
CharacteristicTypeN%
SexFemale212656.0
Male166944.0
Age40–65254467.0
≥65125133.0
Education<Middle school152640.2
≥Middle school226959.8
Income<300168844.5
≥300210755.5
Type of insuranceNational health insurance363295.7
Assistance1634.3
Private insuranceY281474.2
N98125.8
Medical checkupY85722.6
N293877.4
Chronic disease0203353.6
195025.0
<281221.4
Table 3. Relationship between demographic characteristics and chronic diseases.
Table 3. Relationship between demographic characteristics and chronic diseases.
CharacteristicTypeChronic Diseasep-Value
N%Y%
Sex **Female117155.195544.90.019
Male86251.680748.4
Age ***40–65167465.887034.20.001
≥6535928.789271.3
Education ***<Middle school54535.798164.30.001
≥Middle school148865.678134.4
Income ***<30068040.3100859.70.001
≥300135364.275435.8
Type of insurance ***NHI198454.6164845.40.001
Assistance4930.111469.9
Private insurance ***Y168659.9112840.10.001
N34735.463464.6
** p < 0.05, *** p < 0.001.
Table 4. Relationship between health behavior and chronic diseases.
Table 4. Relationship between health behavior and chronic diseases.
CharacteristicTypeChronic Diseasep-Value
N%Y%
Medical checkupY45352.940447.10.331
N158053.8135846.2
Drinking ***Y92349.494450.60.001
N111057.681842.4
Smoking *Y169653.0150347.00.062
N33756.525943.5
Exercise ***Y90459.960540.10.001
N112949.4115750.6
Obesity ***Y113247.3126352.70.001
N90164.449935.6
Hypercholesterolemia ***Y29126.182373.90.001
N174265.093935.0
* p < 0.1, *** p < 0.001.
Table 5. Factors affecting the development of chronic diseases.
Table 5. Factors affecting the development of chronic diseases.
Dependent VariableIndependent VariableExp(B)p-Value
Chronic diseaseSex ***1.4980.001
Age ***3.1450.001
Education ***0.5350.001
Income **0.7730.004
Type of insurance **1.7270.008
Private insurance **0.8030.036
Medical checkup **0.7820.009
Drinking1.1010.252
Smoking1.0610.606
Exercise *0.8610.060
Obesity ***0.5440.001
Hypercholesterolemia ***5.4440.001
* p < 0.1, ** p < 0.05, *** p< 0.001.

Share and Cite

MDPI and ACS Style

Lee, M.; Park, S.; Lee, K.-S. Relationship between Morbidity and Health Behavior in Chronic Diseases. J. Clin. Med. 2020, 9, 121. https://doi.org/10.3390/jcm9010121

AMA Style

Lee M, Park S, Lee K-S. Relationship between Morbidity and Health Behavior in Chronic Diseases. Journal of Clinical Medicine. 2020; 9(1):121. https://doi.org/10.3390/jcm9010121

Chicago/Turabian Style

Lee, Munjae, Sewon Park, and Kyu-Sung Lee. 2020. "Relationship between Morbidity and Health Behavior in Chronic Diseases" Journal of Clinical Medicine 9, no. 1: 121. https://doi.org/10.3390/jcm9010121

APA Style

Lee, M., Park, S., & Lee, K. -S. (2020). Relationship between Morbidity and Health Behavior in Chronic Diseases. Journal of Clinical Medicine, 9(1), 121. https://doi.org/10.3390/jcm9010121

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop