Does Maintained Medical Aid Coverage Affect Healthy Lifestyle Factors, Metabolic Syndrome-Related Health Status, and Individuals’ Use of Healthcare Services?
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design
2.2. Study Sample
2.3. Data Collection and Ethical Considerations
2.4. Study Measures
2.4.1. Whether Medical Aid Eligibility Is Maintained: “Maintained” vs. “Changed”
2.4.2. Healthy Lifestyle
2.4.3. Metabolic Syndrome-Related Health Status
2.4.4. Healthcare Utilization
2.5. Statistical Analysis
3. Results
3.1. Baseline Characteristics
3.2. Changes in the Healthy Lifestyle and Metabolic Syndrome-Related Health Status
3.3. Differences in Metabolic Syndrome-Related Health Status and Medical Expenses
3.4. Relationship between Medical Aid Eligibility and Increase in Total Medical Expenses
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Watkins, D.A.; Jamison, D.T.; Mills, A.; Atun, R.; Danforth, K.; Glassman, A.; Horton, S.; Jha, P.; Kruk, M.E.; Norheim, O.F.; et al. Universal Health Coverage and Essential Packages of Care. In Disease Control Priorities, Third Edition (Volume 9): Improving Health and Reducing Poverty; Jamison, D.T., Gelband, H., Horton, S., Jha, P., Laxminarayan, R., Mock, C.N., Nugent, R., Eds.; World Bank: Washington, DC, USA, 2017. [Google Scholar]
- Signorelli, C.; Odone, A.; Oradini-Alacreu, A.; Pelissero, G. Universal Health Coverage in Italy: Lights and shades of the Italian National Health Service which celebrated its 40th anniversary. Health Policy 2019, 124, 69–74. [Google Scholar] [CrossRef] [PubMed]
- Friebel, R.; Molloy, A.; Leatherman, S.; Dixon, J.; Bauhoff, S.; Chalkidou, K. Achieving high-quality universal health coverage: A perspective from the National Health Service in England. BMJ Glob. Health 2018, 3, e000944. [Google Scholar] [CrossRef] [Green Version]
- Courtemanche, C.; Marton, J.; Ukert, B.; Yelowitz, A.; Zapata, D. Early Impacts of the Affordable Care Act on Health Insurance Coverage in Medicaid Expansion and Non-Expansion States. J. Policy Anal. Manag. 2017, 36, 178–210. [Google Scholar] [CrossRef]
- Selden, T.M.; Lipton, B.J.; Decker, S.L. Medicaid expansion and marketplace eligibility both increased coverage, with trade-offs in access, affordability. Health Aff. 2017, 36, 2069–2077. [Google Scholar] [CrossRef] [PubMed]
- Park, S. Medical service utilization and out-of-pocket spending among near-poor National Health Insurance members in South Korea. BMC Health Serv. Res. 2021, 21, 886. [Google Scholar] [CrossRef] [PubMed]
- Jeong, H.E.; Lee, J.; Shin, H.J.; Shin, J.-Y. Socioeconomic disparities in Korea by health insurance type during the COVID-19 pandemic: A nationwide study. Epidemiol. Health 2021, 43, e2021007. [Google Scholar] [CrossRef]
- Allen, H.; Gordon, S.H.; Lee, D.; Bhanja, A.; Sommers, B.D. Comparison of Utilization, Costs, and Quality of Medicaid vs Subsidized Private Health Insurance for Low-Income Adults. JAMA Netw. Open 2021, 4, e2032669. [Google Scholar] [CrossRef]
- Lee, D.W.; Jang, J.; Choi, D.-W.; Jang, S.-I.; Park, E.-C. The effect of shifting medical coverage from National Health Insurance to Medical Aid type I and type II on health care utilization and out-of-pocket spending in South Korea. BMC Health Serv. Res. 2020, 20, 979. [Google Scholar] [CrossRef]
- National Health Insurance. 2022 Medical Aid Statistics. 2023. Available online: https://www.nhis.or.kr/nhis/together/wbhaec06500m01.do?mode=view&articleNo=10834337 (accessed on 9 June 2023).
- Liss, D.T.; Uchida, T.; Wilkes, C.L.; Radakrishnan, A.; Linder, J.A. General Health Checks in Adult Primary Care: A Review. JAMA 2021, 325, 2294–2306. [Google Scholar] [CrossRef]
- Bauer, U.E.; Briss, P.A.; Goodman, R.A.; Bowman, B.A. Prevention of chronic disease in the 21st century: Elimination of the leading preventable causes of premature death and disability in the USA. Lancet 2014, 384, 45–52. [Google Scholar] [CrossRef]
- Shin, D.W.; Cho, J.; Park, J.H.; Cho, B. National General Health Screening Program in Korea: History, current status, and future direction. Precis. Futur. Med. 2022, 6, 9–31. [Google Scholar] [CrossRef]
- Hill, S.C.; Abdus, S. The effects of Medicaid on access to care and adherence to recommended preventive services. Health Serv. Res. 2020, 56, 84–94. [Google Scholar] [CrossRef]
- Baicker, K.; Allen, H.L.; Wright, B.J.; Taubman, S.L.; Finkelstein, A.N. The Effect of Medicaid on Management of Depression: Evidence from the Oregon Health Insurance Experiment. Milbank Q. 2018, 96, 29–56. [Google Scholar] [CrossRef]
- Kim, J.-H.; Lee, K.-S.; Yoo, K.-B.; Park, E.-C. The differences in health care utilization between medical aid and health insurance: A longitudinal study using propensity score matching. PLoS ONE 2015, 10, e011993. [Google Scholar] [CrossRef]
- Taubman, S.L.; Allen, H.L.; Wright, B.J.; Baicker, K.; Finkelstein, A.N. Medicaid increases emergency-department use: Evidence from Oregon’s Health Insurance experiment. Science 2014, 343, 263–268. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sohn, M.; Jung, M. Effects of public and private health insurance on medical service utilization in the National Health Insurance System: National panel study in the Republic of Korea. BMC Health Serv. Res. 2016, 16, 503. [Google Scholar] [CrossRef] [Green Version]
- Li, Y.; Li, L.; Liu, J. The impact of health insurance on self-protection of Chinese rural residents. Front. Public Health 2022, 10, 1–14. [Google Scholar] [CrossRef] [PubMed]
- Einav, L.; Finkelstein, A. Moral hazard in health insurance: What we know and how we know it. J. Eur. Econ. Assoc. 2018, 16, 957–982. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Rezayatmand, R.; Pavlova, M.; Groot, W. The impact of out-of-pocket payments on prevention and health-related lifestyle: A systematic literature review. Eur. J. Public Health 2012, 23, 74–79. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Baicker, K.; Goldman, D. Patient cost-sharing and healthcare spending growth. J. Econ. Perspect. J. Am. Econ. Assoc. 2011, 25, 47–68. [Google Scholar] [CrossRef]
- Inoue, M.; Kachi, Y. Should co-payments for financially deprived patients be lowered? Primary care physicians’ perspectives using a mixed-methods approach in a survey study in Tokyo. Int. J. Equity Health 2017, 16, 38. [Google Scholar] [CrossRef] [Green Version]
- Kim, J.-H.; Lee, S.G.; Lee, K.-S.; Jang, S.-I.; Cho, K.-H.; Park, E.-C. Impact of health insurance status changes on healthcare utilisation patterns: A longitudinal cohort study in South Korea. BMJ Open 2016, 6, e009538. [Google Scholar] [CrossRef] [Green Version]
- Zimmerman, F.J.; Anderson, N.W. Trends in Health Equity in the United States by Race/Ethnicity, Sex, and Income, 1993–2017. JAMA Netw. Open 2019, 2, e196386. [Google Scholar] [CrossRef]
- Rippe, J.M. Lifestyle Medicine: The Health Promoting Power of Daily Habits and Practices. Am. J. Lifestyle Med. 2018, 12, 499–512. [Google Scholar] [CrossRef]
- Kaminsky, L.A.; German, C.; Imboden, M.; Ozemek, C.; Peterman, J.E.; Brubaker, P.H. The importance of healthy lifestyle behaviors in the prevention of cardiovascular disease. Prog. Cardiovasc. Dis. 2022, 70, 8–15. [Google Scholar] [CrossRef] [PubMed]
- Yim, E.; Lee, K.; Park, I.; Lee, S. The prevalence of metabolic syndrome and health-related behavior changes: The korea national health examination survey. Healthcare 2020, 8, 134. [Google Scholar] [CrossRef]
- Al Shehri, H.A.; Al Asmari, A.K.; Khan, H.A.; Al Omani, S.; Kadasah, S.G.; Horaib, G.B.; Al Buraidi, A.; Al Sharif, A.A.; Mohammed, F.S.; Abbasmanthiri, R.; et al. Association between preventable risk factors and metabolic syndrome. Open Med. 2022, 17, 341–352. [Google Scholar] [CrossRef] [PubMed]
- Kong, H.-S.; Lee, K.-S.; Yim, E.-S.; Lee, S.-Y.; Cho, H.-Y.; Na Lee, B.; Park, J.Y. Factors Associated with Metabolic Syndrome and Related Medical Costs by the Scale of Enterprise in Korea. Ann. Occup. Environ. Med. 2013, 25, 23. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Nichols, G.A.; Moler, E.J.; Schwartz, S.L.; Lai, Y.-L.; Xu, J.; Abby, S.L.; Misir, S.; Jones, M.R.; Nagendran, S.; Viscogliosi, G.; et al. Metabolic syndrome components are associated with future medical costs independent of cardiovascular hospitalization and incident diabetes. Metab. Syndr. Relat. Disord. 2011, 9, 127–133. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Pothiwala, P.; Jain, S.K.; Yaturu, S.; Shin, J.; Kim, M.-H.; Yoon, K.-H.; Kang, M.-I.; Cha, B.-Y.; Lim, D.-J.; Yu, A.P.; et al. Metabolic syndrome and cancer. Metab. Syndr. Relat. Disord. 2009, 7, 279–288. [Google Scholar] [CrossRef] [Green Version]
- Fahed, G.; Aoun, L.; Bou Zerdan, M.; Allam, S.; Bou Zerdan, M.; Bouferraa, Y.; Assi, H.I. Metabolic Syndrome: Updates on Pathophysiology and Management in 2021. Int. J. Mol. Sci. 2022, 23, 786. [Google Scholar] [CrossRef] [PubMed]
- Grundy, S.M.; Cleeman, J.I.; Daniels, S.R.; Donato, K.A.; Eckel, R.H.; Franklin, B.A.; Gordon, D.J.; Krauss, R.M.; Savage, P.J.; Smith, S.C., Jr.; et al. Diagnosis and management of the metabolic syndrome: An American Heart Association/National Heart, Lung, and Blood Institute scientific statement. Circulation 2005, 112, 2735–2752. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kim, M.K.; Lee, W.-Y.; Kang, J.-H.; Kang, J.-H.; Kim, B.T.; Kim, S.M.; Kim, E.M.; Suh, S.-H.; Shin, H.J.; Lee, K.R.; et al. 2014 Clinical practice guidelines for overweight and obesity in Korea. Endocrinol. Metab. 2014, 29, 405–409. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Yilma, Z.; van Kempen, L.; de Hoop, T. A perverse ‘net’ effect? Health insurance and ex-ante moral hazard in Ghana. Soc. Sci. Med. 2012, 75, 138–147. [Google Scholar] [CrossRef]
- Stanciole, A.E. Health insurance and lifestyle choices: Identifying ex ante moral hazard in the US market. Geneva Pap. Risk Insur.-Issues Pract. 2008, 33, 627–644. [Google Scholar] [CrossRef]
- Spenkuch, J.L. Moral hazard and selection among the poor: Evidence from a randomized experiment. J. Health Econ. 2012, 31, 72–85. [Google Scholar] [CrossRef]
- Cantarero-Prieto, D.; Pascual-Sáez, M.; Lera, J. Healthcare Utilization and Healthy Lifestyles among Elderly People Living in Southern Europe: Recent Evidence from the SHARE. Atl. Econ. J. 2020, 48, 53–66. [Google Scholar] [CrossRef]
- Chung, J.; Choi, H.-M.; Jung, J.-H.; Kong, M.G. Association between Socioeconomic Status and Metabolic Syndrome in Korean Adults: Data from the Korean National Health and Nutrition Examination Survey. CardioMetabolic Syndr. J. 2021, 1, 168. [Google Scholar] [CrossRef]
- Kolasa, K.; Kowalczyk, M. Does cost sharing do more harm or more good?—A systematic literature review. BMC Public Health 2016, 16, 992. [Google Scholar] [CrossRef] [Green Version]
- Lee, I.-C.; Chang, C.-S.; Du, P.-L. Do healthier lifestyles lead to less utilization of healthcare resources? BMC Health Serv. Res. 2017, 17, 243. [Google Scholar] [CrossRef] [Green Version]
Div. | Total | 2012–2014 Medical Aid Recipients (“Maintained”) | 2012 Medical Aid->2014 NHI (“Changed”) | X2/t (p-Value) | ||||
---|---|---|---|---|---|---|---|---|
n | (%) | n | (%) | n | (%) | |||
Total | 2366 | (100.0) | 1606 | (67.9) | 760 | (32.1) | - | |
gender | Male | 767 | (32.4) | 533 | (33.2) | 234 | (30.8) | 1.355 (0.132) |
Female | 1599 | (67.6) | 1073 | (66.8) | 526 | (69.2) | ||
age | 40–49 | 1571 | (66.4) | 1221 | (76.0) | 350 | (46.1) | 208.57 (<0.001) |
50–59 | 567 | (24.0) | 280 | (17.4) | 287 | (37.8) | ||
60 or older | 228 | (9.6) | 105 | (6.5) | 123 | (16.2) | ||
mean ± SD | 47.53 ± 7.42 | 45.29 ± 6.94 | 51.63 ± 7.69 | 8.028 (<0.001) | ||||
healthy lifestyle | ||||||||
smoking | non-smoking | 1964 | (83.0) | 1327 | (82.6) | 637 | (83.8) | 0.516 (0.482) |
smoking | 402 | (17.0) | 279 | (17.4) | 123 | (16.2) | ||
drinking | moderate drinking | 2145 | (90.7) | 1478 | (92.0) | 667 | (87.8) | 11.090 (0.001) |
binge drinking | 221 | (9.3) | 128 | (8.0) | 93 | (12.2) | ||
exercise | PA | 659 | (27.9) | 433 | (27.0) | 226 | (29.7) | 1.978 (0.088) |
non-PA | 1707 | (72.1) | 1173 | (73.0) | 534 | (70.3) | ||
health status | ||||||||
blood pressure | normal | 1300 | (54.9) | 938 | (58.4) | 362 | (47.6) | 24.191 (<0.0001) |
risk | 1066 | (45.1) | 668 | (41.6) | 398 | (52.4) | ||
blood glucose | normal | 1442 | (60.9) | 1013 | (63.1) | 429 | (56.4) | 9.523 (0.001) |
risk | 924 | (39.1) | 593 | (36.9) | 331 | (43.6) | ||
triglycerides | normal | 1716 | (72.5) | 1193 | (74.3) | 523 | (68.8) | 7.741 (0.003) |
risk | 650 | (27.5) | 413 | (25.7) | 237 | (31.2) | ||
HDL | normal | 1732 | (73.2) | 1161 | (72.3) | 571 | (75.1) | 2.121 (0.079) |
risk | 634 | (26.8) | 445 | (27.7) | 189 | (24.9) | ||
waist circumference | normal | 1806 | (76.3) | 1230 | (76.6) | 576 | (75.8) | 0.182 (0.353) |
risk | 560 | (23.7) | 376 | (23.4) | 184 | (24.2) | ||
metabolic syndrome No. of risk factors | 0 | 558 | (23.6) | 404 | (25.2) | 154 | (20.3) | 16.240 (0.006) |
1 | 668 | (28.2) | 460 | (28.6) | 208 | (27.4) | ||
2 | 548 | (23.2) | 374 | (23.3) | 174 | (22.9) | ||
3 | 351 | (14.8) | 215 | (13.4) | 136 | (17.9) | ||
4 | 188 | (7.9) | 123 | (7.7) | 65 | (8.6) | ||
5 | 53 | (2.2) | 30 | (1.9) | 23 | (3.0) | ||
metabolic syndrome | No | 1774 | (75.0) | 1238 | (77.1) | 536 | (70.5) | 11.832 (<0.001) |
Yes | 592 | (25.0) | 368 | (22.9) | 224 | (29.5) |
Div. | 2012 → 2014 | Total | “Maintained” Group | “Changed” Group | X2 (p-Value) | |||
---|---|---|---|---|---|---|---|---|
n | (%) | n | (%) | n | (%) | |||
healthy lifestyle | ||||||||
smoking | non-smoking → non-smoking | 1903 | (80.4) | 1273 | (79.5) | 626 | (82.4) | 8.033 (0.045) |
smoking → non-smoking | 74 | (3.1) | 47 | (2.9) | 27 | (3.6) | ||
non-smoking → smoking | 61 | (2.6) | 50 | (3.1) | 11 | (1.4) | ||
smoking → smoking | 328 | (13.9) | 232 | (14.5) | 96 | (12.6) | ||
drinking | moderate → moderate | 2038 | (86.1) | 1406 | (87.5) | 632 | (83.2) | 15.636 (0.001) |
binge → moderate | 111 | (4.7) | 57 | (3.5) | 54 | (7.1) | ||
moderate → binge | 107 | (4.5) | 72 | (4.5) | 35 | (4.6) | ||
binge → binge | 110 | (4.6) | 71 | (4.4) | 39 | (5.1) | ||
exercise | PA * → PA | 294 | (12.4) | 197 | (12.3) | 97 | (12.8) | 2.470 (0.481) |
non-PA → PA | 370 | (15.6) | 252 | (15.7) | 118 | (15.5) | ||
PA → non-PA | 365 | (15.4) | 236 | (14.7) | 129 | (17.0) | ||
non-PA → non-PA | 1337 | (56.5) | 921 | (57.3) | 416 | (54.7) | ||
metabolic syndrome-related health status | ||||||||
blood pressure | normal → normal | 1032 | (43.6) | 757 | (47.1) | 275 | (36.2) | 32.112 (<0.001) |
risk → normal | 260 | (11.0) | 177 | (11.0) | 83 | (10.9) | ||
normal → risk | 268 | (11.3) | 181 | (11.3) | 87 | (11.4) | ||
risk → risk | 806 | (34.1) | 491 | (30.6) | 315 | (41.4) | ||
blood glucose | normal → normal | 1086 | (45.9) | 769 | (47.9) | 317 | (41.7) | 11.683 (0.009) |
risk → normal | 265 | (11.2) | 178 | (11.1) | 87 | (11.4) | ||
normal → risk | 356 | (15.0) | 244 | (15.2) | 112 | (14.7) | ||
risk → risk | 659 | (27.9) | 415 | (25.8) | 244 | (32.1) | ||
triglycerides | normal → normal | 1448 | (61.2) | 1012 | (63.0) | 436 | (57.4) | 13.765 (0.003) |
risk → normal | 275 | (11.6) | 161 | (10.0) | 114 | (15.0) | ||
normal → risk | 268 | (11.3) | 181 | (11.3) | 87 | (11.4) | ||
risk → risk | 375 | (15.8) | 252 | (15.7) | 123 | (16.2) | ||
HDL | normal → normal | 1421 | (60.1) | 949 | (59.1) | 472 | (62.1) | 4.108 (0.250) |
risk → normal | 266 | (11.2) | 179 | (11.1) | 87 | (11.4) | ||
normal → risk | 311 | (13.1) | 212 | (13.2) | 99 | (13.0) | ||
risk → risk | 368 | (15.6) | 266 | (16.6) | 102 | (13.4) | ||
waist circumference | normal → normal | 1602 | (67.7) | 1088 | (67.7) | 514 | (67.6) | 1.890 (0.596) |
risk → normal | 167 | (7.1) | 106 | (6.6) | 61 | (8.0) | ||
normal → risk | 204 | (8.6) | 142 | (8.8) | 62 | (8.2) | ||
risk → risk | 393 | (16.6) | 270 | (16.8) | 123 | (16.2) | ||
metabolic syndrome | No → No | 1515 | (64.0) | 1066 | (66.4) | 449 | (59.1) | 16.047 (0.001) |
Yes → No | 199 | (8.4) | 115 | (7.2) | 84 | (11.1) | ||
No → Yes | 259 | (10.9) | 172 | (10.7) | 87 | (11.4) | ||
Yes → Yes | 393 | (16.6) | 253 | (15.8) | 140 | (18.4) |
Div. | “Maintained” Group | “Changed” Group | t (p-Value) | |
---|---|---|---|---|
M ± SD | M ± SD | |||
Systolic blood pressure (mmHg) | 2012 | 118.81 ± 14.83 | 122.90 ± 15.07 | −6.228 (<0.001) |
2014 | 119.31 ± 14.65 | 121.70 ± 14.60 | −3.706 (<0.001) | |
Difference | 0.51 ± 14.85 | −1.19 ± 15.29 | 2.576 (0.010) | |
t (p) | −1.366 (0.172) | 2.154 (0.032) | - | |
Diastolic blood pressure (mmHg) | 2012 | 74.99 ± 10.38 | 76.81 ± 10.11 | −4.026 (<0.001) |
2014 | 74.65 ± 9.88 | 76.06 ± 10.02 | −3.234 (0.001) | |
Difference | −0.34 ± 10.50 | −0.75 ± 11.07 | 0.858 (0.391) | |
t (p) | 1.302 (0.193) | 1.875 (0.061) | - | |
blood glucose (mg/dL) | 2012 | 98.88 ± 27.19 | 102.53 ± 27.40 | −3.046 (0.002) |
2014 | 101.30 ± 32.86 | 103.36 ± 29.20 | −1.474 (0.141) | |
Difference | 2.42 ± 27.72 | 0.82 ± 27.97 | 1.304 (0.192) | |
t (p) | −3.495 (<0.001) | −0.809 (0.419) | - | |
triglycerides (mg/dL) | 2012 | 130.46 ± 101.41 | 135.20 ± 94.27 | −1.085 (0.278) |
2014 | 130.78 ± 97.31 | 128.64 ± 87.00 | 0.516 (0.606) | |
Difference | 0.32 ± 96.35 | −6.56 ± 86.60 | 1.673 (0.094) | |
t (p) | −0.132 (0.895) | 2.088 (0.037) | - | |
HDL (mg/dL) | 2012 | 54.58 ± 21.32 | 56.17 ±25.18 | −1.599 (0.110) |
2014 | 54.49 ± 19.50 | 55.22 ± 13.34 | −0.941 (0.347) | |
Difference | −0.09 ± 24.02 | −0.95 ± 24.81 | 0.802 (0.422) | |
t (p) | 0.150 (0.881) | 1.053 (0.293) | - | |
waist circumference (cm) | 2012 | 79.54 ± 10.17 | 80.41 ± 9.44 | −2.003 (0.045) |
2014 | 80.16 ± 10.27 | 80.55 ± 9.38 | −0.884 (0.377) | |
Difference | 0.62 ± 6.21 | 0.14 ± 5.98 | 1.796 (0.073) | |
t (p) | −4.028 (<0.001) | −0.643 (0.521) | - | |
total medical expenses (USD) | 2012 | 1914.20 ± 2851.05 | 1446.77 ± 2215.20 | 3.986 (<0.001) |
2014 | 2103.46 ± 3152.64 | 1550.36 ± 2546.46 | 4.228 (<0.001) | |
Difference | 189.26 ± 2499.99 | 103.59 ± 2428.89 | 0.785 (0.432) | |
t (p) | −3.034 (0.002) | −1.176 (0.240) | - |
Variable | Level | Model 1 * | Model 2 ** | Model 3 *** | ||||||
---|---|---|---|---|---|---|---|---|---|---|
OR | 95% CI | p-Value | OR | 95% CI | p-Value | OR | 95% CI | p-Value | ||
medical aid eligibility | Changed | 1.000 | 1.000 | 1.000 | ||||||
Maintained | 1.368 | 1.141–1.641 | <0.001 | 1.400 | 1.165–1.683 | <0.001 | 1.421 | 1.180–1.710 | <0.001 | |
Fit Statistics | AIC **** | 3251.992 | 3256.328 | 3269.221 | ||||||
C-statistics | 0.543 | 0.565 | 0.579 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Park, I.; Lee, K.; Yim, E. Does Maintained Medical Aid Coverage Affect Healthy Lifestyle Factors, Metabolic Syndrome-Related Health Status, and Individuals’ Use of Healthcare Services? Healthcare 2023, 11, 1811. https://doi.org/10.3390/healthcare11131811
Park I, Lee K, Yim E. Does Maintained Medical Aid Coverage Affect Healthy Lifestyle Factors, Metabolic Syndrome-Related Health Status, and Individuals’ Use of Healthcare Services? Healthcare. 2023; 11(13):1811. https://doi.org/10.3390/healthcare11131811
Chicago/Turabian StylePark, Ilsu, Kyounga Lee, and Eunshil Yim. 2023. "Does Maintained Medical Aid Coverage Affect Healthy Lifestyle Factors, Metabolic Syndrome-Related Health Status, and Individuals’ Use of Healthcare Services?" Healthcare 11, no. 13: 1811. https://doi.org/10.3390/healthcare11131811
APA StylePark, I., Lee, K., & Yim, E. (2023). Does Maintained Medical Aid Coverage Affect Healthy Lifestyle Factors, Metabolic Syndrome-Related Health Status, and Individuals’ Use of Healthcare Services? Healthcare, 11(13), 1811. https://doi.org/10.3390/healthcare11131811