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Background@#Low-density lipoprotein cholesterol is an important marker highly associated with cardiovascular disease. Since the direct measurement of it is inefficient in terms of cost and time, it is common to estimate through the Friedewald equation developed about 50 years ago. However, various limitations exist since the Friedewald equation was not designed for Koreans. This study proposes a new low-density lipoprotein cholesterol estimation equation for South Koreans using nationally approved statistical data. @*Methods@#This study used data from the Korean National Health and Nutrition Examination Survey from 2009 to 2019. The 18,837 subjects were used to develop the equation for estimating low-density lipoprotein cholesterol. The subjects included individuals with low-density lipoprotein cholesterol levels directly measured among those with high-density lipoprotein cholesterol, triglycerides, and total cholesterol measured. We compared twelve equations developed in the previous studies and the newly proposed equation (model 1) developed in this study with the actual low-density lipoprotein cholesterol value in various ways. @*Results@#The low-density lipoprotein cholesterol value estimated using the estimation formula and the actual low-density lipoprotein cholesterol value were compared using the root mean squared error. When the triglyceride level was less than 400 mg/dL, the root mean squared of the model 1 was 7.96, the lowest compared to other equations, and the model 2 was 7.82. The degree of misclassification was checked according to the NECP ATP III 6 categories. As a result, the misclassification rate of the model 1 was the lowest at 18.9%, and Weighted Kappa was the highest at 0.919 (0.003), which means it significantly reduced the underestimation rate shown in other existing estimation equations. Root mean square error was also compared according to the change in triglycerides level. As the triglycerides level increased, the root mean square error showed an increasing trend in all equations, but it was confirmed that the model 1 was the lowest compared to other equations. @*Conclusion@#The newly proposed low-density lipoprotein cholesterol estimation equation showed significantly improved performance compared to the 12 existing estimation equations. The use of representative samples and external verification is required for more sophisticated estimates in the future.
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Background@#This study purposed to examine the difference in the prevalence of obesity at each stage among people with and without disabilities considering the severity and type of disability. @*Methods@#The study targeted a total of 1,315,967 people, including 68,418 disabled and 1,247,549 non-disabled, who completed the national health screenings. Logistic analysis and average marginal effect analysis were conducted in three stages (pre-obesity, obesity, severe obesity). Those analyses were conducted considering the severity and type of disabilities. @*Results@#People with disabilities were more likely to be at all stages of obesity than non-disabled people. In severely disabled people, the probability of obesity was higher than non-disabled people at all stages of obesity, but mildly disabled people had a higher only in the severe obesity stage, no difference in obesity stage, and a low in the pre-obesity stage. In physical and mental disabilities, the probability of obesity was higher than non-disabled people at all stages of obesity, but external physical function and internal organs disabled had a lower in the obesity and pre-obesity stage, and no difference in severe obesity stage. @*Conclusion@#This study found that people with disabilities had a higher relationship with obesity than people without disabilities. In addition, severity and types of disabilities have different effects on the stage of obesity. Therefore, it is necessary to care about the health inequality and health of disabled people considering their severity and types of disabilities.
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Background@#The purpose of this study is to explain the factors influencing the incurrence of catastrophic health expenditure of national health insurance households using panel data observed over a long period. @*Methods@#The study targeted 3,652 households who had no censoring during the 11-year survey period (2007–2017) and householders whose insurance type was consistently maintained as national health insurance. Generalized estimating equations were adopted to identify factors affecting the occurrence of catastrophic health expenditure at 20%, 30%, and 40% threshold levels. A subgroup analysis was conducted by categorizing groups depending on the existence of the elderly in the household. @*Results@#For the last 11 years, the incidence of catastrophic health expenditure in the households without the elderly decreased slightly at all threshold levels, but the households with the elderly seemed to be increased. At baseline, household type showed a statistically significant relationship with all other variables. The results of generalized estimating equations analyses show that household income was not significant at all threshold levels in the households without elderly. On the other hand, in the households with the elderly, the 2nd (odds ratio [OR], 1.33–2.05) and 3rd quintile groups (OR, 1.25–2.55) were more likely to have catastrophic health expenditure compared to the 1st quintile of household income group. @*Conclusion@#As the amount of health expenditures relative to the ability to pay is increasing in households with the elderly, the application of an intervention followed by consistent monitoring is needed. This study found that there were differences in influencing factors according to the presence of the elderly in the households. In particular, in households with the elderly, interesting results have been drawn regarding the occurrence of catastrophic health expenditure in the near-poor, so additional research is required.
RESUMEN
Background@#The purpose of this study is to explain the factors influencing the incurrence of catastrophic health expenditure of national health insurance households using panel data observed over a long period. @*Methods@#The study targeted 3,652 households who had no censoring during the 11-year survey period (2007–2017) and householders whose insurance type was consistently maintained as national health insurance. Generalized estimating equations were adopted to identify factors affecting the occurrence of catastrophic health expenditure at 20%, 30%, and 40% threshold levels. A subgroup analysis was conducted by categorizing groups depending on the existence of the elderly in the household. @*Results@#For the last 11 years, the incidence of catastrophic health expenditure in the households without the elderly decreased slightly at all threshold levels, but the households with the elderly seemed to be increased. At baseline, household type showed a statistically significant relationship with all other variables. The results of generalized estimating equations analyses show that household income was not significant at all threshold levels in the households without elderly. On the other hand, in the households with the elderly, the 2nd (odds ratio [OR], 1.33–2.05) and 3rd quintile groups (OR, 1.25–2.55) were more likely to have catastrophic health expenditure compared to the 1st quintile of household income group. @*Conclusion@#As the amount of health expenditures relative to the ability to pay is increasing in households with the elderly, the application of an intervention followed by consistent monitoring is needed. This study found that there were differences in influencing factors according to the presence of the elderly in the households. In particular, in households with the elderly, interesting results have been drawn regarding the occurrence of catastrophic health expenditure in the near-poor, so additional research is required.