Objectives The world is witnessing a sharp increase in its elderly population, accelerated by longer life expectancy and lower birth rates, which in turn imposes enormous medical burden on society. Although numerous studies have predicted medical expenses based on region, gender, and chronological age (CA), any attempt has rarely been made to utilize biological age (BA)—an indicator of health and aging—to ascertain and predict factors related to medical expenses and medical care use. Thus, this study employs BA to predict factors that affect medical expenses and medical care use. Materials and methods Referring to the health screening cohort database of the National Health Insurance Service (NHIS), this study targeted 276,723 adults who underwent health check-ups in 2009−2010 and kept track of the data on their medical expenses and medical care use up to 2019. The average follow-up period is 9.12 years. Twelve clinical indicators were used to measure BA, while the total annual medical expenses, total annual number of outpatient days, total annual number of days in hospital, and average annual increases in medical expenses were used as the variables for medical expenses and medical care use. For statistical analysis, this study employed Pearson correlation analysis and multiple regression analysis. Results Regression analysis of the differences between corrected biological age (cBA) and CA exhibited statistically significant increases (p<0.05) in all the variables of the total annual medical expenses, total annual number of outpatient days, total annual number of days in hospital, and average annual increases in medical expenses. Conclusions This study quantified decreases in the variables for medical expenses and medical care use based on improved BA, thereby motivating people to become more health-conscious. In particular, this study is significant in that it is the first of its kind to predict medical expenses and medical care use through BA.
Background Untact cultures have rapidly spread around the world as a result of the prolongation of the COVID-19 pandemic, leading to various types of research and technological developments in the fields of medicine and health care, where digital health care refers to health care services provided in a digital environment. Previous studies relating to digital health care demonstrated its effectiveness in managing chronic diseases such as hypertension and diabetes. While many studies have applied digital health care to various diseases, daily health care is needed for healthy individuals before they are diagnosed with a disease. Accordingly, research on individuals who have not been diagnosed with a disease is also necessary. Objective This study aimed to identify the effects of using a customized digital health care service (CDHCS) on risk factors for metabolic syndrome (MS) and lifestyle improvement. Methods The population consisted of 63 adults who underwent a health checkup at the National Health Insurance Service Ilsan (NHIS) Hospital in 2020. Measured variables include basic clinical indicators, MS-related variables, and lifestyle variables. All items were measured at NHIS Ilsan Hospital before the use of the CDHCS and 3 months thereafter. The CDHCS used in this study is a mobile app that analyzes the health condition of the user by identifying their risk factors and provides appropriate health care content. For comparison between before and after CDHCS use (pre-post comparison), paired t test was used for continuous variables, and a chi-square test was used for nominal variables. Results The study population included 30 (47.6%) male and 33 (52.4%) female participants, and the mean age was 47.61 (SD 13.93) years. The changes in clinical indicators before and after intervention results showed a decrease in weight, waist circumference, triglyceride, and high-density lipoprotein cholesterol and increases in systolic blood pressure and diastolic blood pressure. The distribution of the risk group increased from 32 (50.8%) to 34 (54%) and that of the MS group decreased from 18 (28.6%) to 16 (25.4%). The mean metabolic syndrome age–chronological age before the CDHCS was 2.20 years, which decreased to 1.72 years after CDHCS, showing a decrease of 0.48 years in the mean metabolic syndrome age–chronological age after the intervention. While all lifestyle variables, except alcohol consumption, showed a tendency toward improvement, the differences were not statistically significant. Conclusions Although there was no statistical significance in the variables under study, this pilot study will provide a foundation for more accurate verification of CDHCS in future research.
BACKGROUND Untact cultures have rapidly spread around the world as a result of the prolongation of the COVID-19 pandemic, leading to various types of research and technological developments in the fields of medicine and healthcare, where digital healthcare refers to healthcare services provided in a digital environment. OBJECTIVE This study aimed to identify the effects of using a customized digital healthcare service (CDHCS) on risk factors for metabolic syndrome (MS) and lifestyle improvement. METHODS The population consisted of 63 adults who underwent a health checkup at the National Health Insurance Service Ilsan Hospital in 2020. Measured variables include basic clinical indicators, MS-related variables, and lifestyle variables. The CDHCS used in this study is a mobile application that analyzes the health condition of the user by identifying their risk factors and provides appropriate healthcare content. RESULTS All measured variables, except drinking status, showed a tendency towards improvement, but the differences were not statistically significant. CONCLUSIONS Although there was no statistical significance in the variables under study, this pilot study will provide a foundation for more accurate verification of CDHCS in future research. CLINICALTRIAL All participants received verbal explanations regarding the study and submitted their prior written consent. This study was approved by the Institutional Review Board (IRB) of NHIS Ilsan Hospital (NHIMC 2020-02-002).
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