Dataset Information

Prediction Model for Hypertension and Diabetes Mellitus Using Korean Public Health Examination Data (2002-2017).

ABSTRACT: Hypertension and diabetes mellitus are major chronic diseases that are important factors in the management of cardiovascular disease. In order to prevent the occurrence of chronic diseases, proper health management through periodic health check-ups is necessary. The purpose of this study is to determine the incidence of hypertension and diabetes mellitus according to the health check-up, and to develop a predictive model for hypertension and diabetes according to the health check-up. We used the National Health Insurance Corporation database of Korea and checked whether hypertension or diabetes occurred from that date according to the number of health check-ups over the past 10 years. Compared to those who underwent five health check-ups, those who participated in the first screening had hypertension (OR = 2.18, 95% CI = 2.14-2.22), diabetes mellitus (OR = 1.33, 95% CI = 1.30-1.35) and both diseases (OR = 2.46, 95% CI = 2.39-2.53); individuals who underwent 10 screenings had hypertension (OR = 0.86, 95% CI = 0.83-0.88), diabetes mellitus (OR = 0.83, 95% CI = 0.81-0.85) and both diseases (OR = 0.83, 95% CI = 0.79-0.87). Individuals who attended fewer than five screenings compared with individuals who attended five or more screenings had hypertension (OR = 1.61, 95% CI = 1.59-1.62; AUC = 0.66), diabetes mellitus (OR = 1.21, 95% CI = 1.20-1.22; AUC = 0.59) and both diseases (OR = 1.75, 95% CI = 1.72-1.78, AUC = 0.63). The machine learning-based prediction model using XGBoost showed higher performance in all datasets than the conventional logistic regression model in predicting hypertension (accuracy, 0.828 vs. 0.628; F1-score, 0.800 vs. 0.633; AUC, 828 vs. 0.630), diabetes mellitus (accuracy, 0.707 vs. 0.575; F1-score, 0.663 vs. 0.576; AUC, 0.710 vs. 0.575) and both diseases (accuracy, 0.950 vs. 0.612; F1-score, 0.950 vs. 0.614; AUC, 0.952 vs. 0.612). It was found that health check-up had a great influence on the occurrence of hypertension and diabetes, and screening frequency was more important than other factors in the variable importances.

SUBMITTER: Jeong YW

PROVIDER: S-EPMC9407141 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Prediction Model for Hypertension and Diabetes Mellitus Using Korean Public Health Examination Data (2002-2017).

Jeong Yong Whi YW Jung Yeojin Y Jeong Hoyeon H Huh Ji Hye JH Sung Ki-Chul KC Shin Jeong-Hun JH Kim Hyeon Chang HC Kim Jang Young JY Kang Dae Ryong DR

Diagnostics (Basel, Switzerland) 20220814 8

Hypertension and diabetes mellitus are major chronic diseases that are important factors in the management of cardiovascular disease. In order to prevent the occurrence of chronic diseases, proper health management through periodic health check-ups is necessary. The purpose of this study is to determine the incidence of hypertension and diabetes mellitus according to the health check-up, and to develop a predictive model for hypertension and diabetes according to the health check-up. We used the ...[more]

PMID: 36010317

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Project description:BackgroundSurveillance using coded administrative health data has shown that the prevalence of hypertension and diabetes in Canada increased substantially between 1998 to 2008. These findings require an assumption that the validity of hypertension and diabetes coding is stable over time. We tested this assumption by examining temporal trends in the validity of coding for hypertension and diabetes in the Canadian hospital Discharge Abstract Database.MethodsWe used the Alberta Provincial Project for Outcome Assessment in Coronary Heart Disease (APPROACH) database, a clinical registry, as the reference standard to evaluate the validity of the Discharge Abstract Database in recording hypertension and diabetes in Alberta. The APPROACH database contains data for all Alberta residents who have undergone cardiac catheterization and includes prospective ascertainment of comorbid conditions before each procedure. We linked patient data between the 2 databases for 2002 to 2013 using patient provincial health number. Temporal trends in sensitivity, specificity, positive predictive value, negative predictive value and Cohen κ were calculated for both hypertension and diabetes in the Discharge Abstract Database.ResultsWe matched 63 483 patients between the APPROACH database and the Discharge Abstract Database. The validity of the Discharge Abstract Database for hypertension and diabetes remained mostly consistent over time. Between 2002 and 2013, sensitivity, specificity, positive predictive value and negative predictive value ranged from 66% to 87% for hypertension and from 81% to 98% for diabetes; the corresponding κ scores ranged from 0.50 to 0.62 and from 0.80 to 0.89. No significant differences in the validity of coding were found across age, sex or hospital location subgroups.InterpretationThe validity of coding for hypertension and diabetes in the Discharge Abstract Database remained fairly consistent between 2002 and 2013. Our findings support the use of the Discharge Abstract Database for hypertension and diabetes surveillance in hospital settings.

Project description:BackgroundThe significance of high systolic and diastolic blood pressure remains controversial. We assessed the differences in prevalence of hypertension and its subtypes according to the different hypertension diagnostic criteria embodied by the 2017 American College of Cardiology/American Heart Association (2017 ACC/AHA) and 2018 Korean Society of Hypertension (2018 KSH) guidelines.MethodsWe used the 2007-2017 Korea National Health and Nutrition Examination Survey (KNHANES) data to calculate guideline-specific hypertension prevalence among untreated, adult participants. By the 2017 ACC/AHA guideline, a mean SBP ≥130 mmHg, DBP ≥80 mmHg, or currently using antihypertensive medications were considered to have hypertension. Isolated diastolic hypertension (IDH) was defined as DBP ≥80 mmHg and SBP <130 mmHg, isolated systolic hypertension (ISH) as SBP ≥130 mmHg and DBP <80 mmHg, and systolic diastolic hypertension (SDH) as SBP ≥130 mmHg and DBP ≥80 mmHg. In a similar manner, by the 2018 KSH guideline, all hypertension and its subtype prevalence were calculated using the 140/90 mmHg cutoff. The two versions of all hypertension and its corresponding subtype prevalence were calculated among all study participants and separately by sex and age then compared via analysis of variance.ResultsThe prevalence of all hypertension increased from 25.9% (95% confidence interval (CI) 25.4-26.5) defined by the 2018 KSH guideline to 46.3% (95% CI 45.6-46.9) classified by the 2017 ACC/AHA guideline. Such increase was primarily manifested through substantial increase in IDH prevalence, from 5.2% (95% CI 4.9-5.4) defined by the 2018 KSH guideline to 17.9% (95% CI 17.4-18.3) defined by the 2017 ACC/AHA guideline, and was most notably observed in young age groups, 30-49 years. ISH prevalence showed minimal differences. SDH prevalence moderately increased from 3.5% (95% CI 3.3-3.7) defined by the 2018 KSH guideline to 11.1% (95% CI 10.7-11.4) defined by the 2017 ACC/AHA guideline, achieved primarily among participants aged 50 years or above.ConclusionsChanges in each subtype prevalence made differential contribution to additionally classified hypertension cases by the 2017 ACC/AHA guideline. Future studies should investigate the diastolic-associated cardiovascular risks and benefits of its long-term primary prevention in the young population.

Dataset Information

Prediction Model for Hypertension and Diabetes Mellitus Using Korean Public Health Examination Data (2002-2017).

Publications

Prediction Model for Hypertension and Diabetes Mellitus Using Korean Public Health Examination Data (2002-2017).

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