Journal of Preventive Medicine and Public Health

Original Articles

Interactions of Behavioral Changes in Smoking, High-risk Drinking, and Weight Gain in a Population of 7.2 Million in Korea: Yeon-Yong Kim, Hee-Jin Kang, Seongjun Ha, Jong Heon Park; J Prev Med Public Health. 2019;52(4):234-241. Published online July 3, 2019; DOI: https://doi.org/10.3961/jpmph.18.290

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Objectives
To identify simultaneous behavioral changes in alcohol consumption, smoking, and weight using a fixed-effect model and to characterize their associations with disease status.
Methods
This study included 7 000 529 individuals who participated in the national biennial health-screening program every 2 years from 2009 to 2016 and were aged 40 or more. We reconstructed the data into an individual-level panel dataset with 4 waves. We used a fixed-effect model for smoking, heavy alcohol drinking, and overweight. The independent variables were sex, age, lifestyle factors, insurance contribution, employment status, and disease status.
Results
Becoming a high-risk drinker and losing weight were associated with initiation or resumption of smoking. Initiation or resumption of smoking and weight gain were associated with non-high-risk drinkers becoming high-risk drinkers. Smoking cessation and becoming a high-risk drinker were associated with normal-weight participants becoming overweight. Participants with newly acquired diabetes mellitus, ischemic heart disease, stroke, and cancer tended to stop smoking, discontinue high-risk drinking, and return to a normal weight.
Conclusions
These results obtained using a large-scale population-based database documented interactions among lifestyle factors over time.

Summary

Korean summary
이 분석은 흡연, 음주, 체중의 동시적 변화에 대해 패널분석방법론인 고정효과 모형을 이용하여 분석하였으며, 2009년부터 2016년까지 2년 주기로 4차례 모두 건강검진을 수검받은 720만 명을 대상으로 하였다. 흡연, 음주, 체중의 동시적 변화에 대한 방향성을 탐색하여 생활습관 관련 행태가 독자적이 아닌 유기적으로 변화하는 양상을 확인하였다, 또한 당뇨병, 뇌졸중, 암이 신규로 진단되었을 때 행태 변화가 나타나는 것을 확인하였다.

Citations

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Association between Body Mass Index and Risk of Gastric Cancer by Anatomic and Histologic Subtypes in Over 500,000 East and Southeast Asian Cohort Participants
Jieun Jang, Sangjun Lee, Kwang-Pil Ko, Sarah K. Abe, Md. Shafiur Rahman, Eiko Saito, Md. Rashedul Islam, Norie Sawada, Xiao-Ou Shu, Woon-Puay Koh, Atsuko Sadakane, Ichiro Tsuji, Jeongseon Kim, Isao Oze, Chisato Nagata, Shoichiro Tsugane, Hui Cai, Jian-Min
Cancer Epidemiology, Biomarkers & Prevention.2022; 31(9): 1727. CrossRef

Level of Agreement and Factors Associated With Discrepancies Between Nationwide Medical History Questionnaires and Hospital Claims Data: Yeon-Yong Kim, Jong Heon Park, Hee-Jin Kang, Eun Joo Lee, Seongjun Ha, Soon-Ae Shin; J Prev Med Public Health. 2017;50(5):294-302. Published online July 20, 2017; DOI: https://doi.org/10.3961/jpmph.17.024

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Abstract PDF

Objectives
The objectives of this study were to investigate the agreement between medical history questionnaire data and claims data and to identify the factors that were associated with discrepancies between these data types. Methods: Data from self-reported questionnaires that assessed an individual’s history of hypertension, diabetes mellitus, dyslipidemia, stroke, heart disease, and pulmonary tuberculosis were collected from a general health screening database for 2014. Data for these diseases were collected from a healthcare utilization claims database between 2009 and 2014. Overall agreement, sensitivity, specificity, and kappa values were calculated. Multiple logistic regression analysis was performed to identify factors associated with discrepancies and was adjusted for age, gender, insurance type, insurance contribution, residential area, and comorbidities. Results: Agreement was highest between questionnaire data and claims data based on primary codes up to 1 year before the completion of self-reported questionnaires and was lowest for claims data based on primary and secondary codes up to 5 years before the completion of self-reported questionnaires. When comparing data based on primary codes up to 1 year before the completion of self-reported questionnaires, the overall agreement, sensitivity, specificity, and kappa values ranged from 93.2 to 98.8%, 26.2 to 84.3%, 95.7 to 99.6%, and 0.09 to 0.78, respectively. Agreement was excellent for hypertension and diabetes, fair to good for stroke and heart disease, and poor for pulmonary tuberculosis and dyslipidemia. Women, younger individuals, and employed individuals were most likely to under-report disease. Conclusions: Detailed patient characteristics that had an impact on information bias were identified through the differing levels of agreement.

Summary

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Factors Associated With Subjective Life Expectancy: Comparison With Actuarial Life Expectancy: Jaekyoung Bae, Yeon-Yong Kim, Jin-Seok Lee; J Prev Med Public Health. 2017;50(4):240-250. Published online June 27, 2017; DOI: https://doi.org/10.3961/jpmph.17.036

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Abstract PDF

Objectives
Subjective life expectancy (SLE) has been found to show a significant association with mortality. In this study, we aimed to investigate the major factors affecting SLE. We also examined whether any differences existed between SLE and actuarial life expectancy (LE) in Korea. Methods: A cross-sectional survey of 1000 individuals in Korea aged 20-59 was conducted. Participants were asked about SLE via a self-reported questionnaire. LE from the National Health Insurance database in Korea was used to evaluate differences between SLE and actuarial LE. Age-adjusted least-squares means, correlations, and regression analyses were used to test the relationship of SLE with four categories of predictors: demographic factors, socioeconomic factors, health behaviors, and psychosocial factors. Results: Among the 1000 participants, women (mean SLE, 83.43 years; 95% confidence interval, 82.41 to 84.46 years; 48% of the total sample) had an expected LE 1.59 years longer than that of men. The socioeconomic factors of household income and housing arrangements were related to SLE. Among the health behaviors, smoking status, alcohol status, and physical activity were associated with SLE. Among the psychosocial factors, stress, self-rated health, and social connectedness were related to SLE. SLE had a positive correlation with actuarial estimates (r=0.61, p<0.001). Gender, household income, history of smoking, and distress were related to the presence of a gap between SLE and actuarial LE. Conclusions: Demographic factors, socioeconomic factors, health behaviors, and psychosocial factors showed significant associations with SLE, in the expected directions. Further studies are needed to determine the reasons for these results.

Summary

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Interaction between self-perceived disease control and self-management behaviours among Chinese middle-aged and older hypertensive patients: the role of subjective life expectancy
Jiao Lu, Linhui Liu, Jiaming Zheng, Zhongliang Zhou
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Associations between existing and newly diagnosed chronic health conditions and change in subjective life expectancy: Results from a panel study
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Factors Affecting the Downward Mobility of Psychiatric Patients: A Korean Study of National Health Insurance Beneficiaries: Un-Na Kim, Yeon-Yong Kim, Jin-Seok Lee; J Prev Med Public Health. 2016;49(1):53-60. Published online December 22, 2015; DOI: https://doi.org/10.3961/jpmph.15.052

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Abstract PDF

Objectives
The purpose of this study is to examine the magnitude of and the factors associated with the downward mobility of first-episode psychiatric patients.
Methods
This study used the claims data from the Korean Health Insurance Review and Assessment Service. The study population included 19 293 first-episode psychiatric inpatients diagnosed with alcohol use disorder (International Classification of Diseases, 10th revision [ICD-10] code F10), schizophrenia and related disorders (ICD-10 codes F20-F29), and mood disorders (ICD-10 codes F30-F33) in the first half of 2005. This study included only National Health Insurance beneficiaries in 2005. The dependent variable was the occurrence of downward mobility, which was defined as a health insurance status change from National Health Insurance to Medical Aid. Logistic regression analysis was used to assess factors associated with downward drift of first-episode psychiatric patients.
Results
About 10% of the study population who were National Health Insurance beneficiaries in 2005 became Medical Aid recipients in 2007. The logistic regression analysis showed that age, gender, primary diagnosis, type of hospital at first admission, regular use of outpatient clinic, and long-term hospitalization are significant predictors in determining downward drift in newly diagnosed psychiatric patients.
Conclusions
This research showed that the downward mobility of psychiatric patients is affected by long-term hospitalization and medical care utilization. The findings suggest that early intensive intervention might reduce long-term hospitalization and the downward mobility of psychiatric patients.

Summary

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The Effect of Sleep Duration on the Risk of Unintentional Injury in Korean Adults: Yeon-Yong Kim, Un-Na Kim, Jin-Seok Lee, Jong-Heon Park; J Prev Med Public Health. 2014;47(3):150-157. Published online May 30, 2014; DOI: https://doi.org/10.3961/jpmph.2014.47.3.150

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Abstract PDF

Objectives

The decrease or increase in sleep duration has recently been recognized as a risk factor for several diseases, including hypertension and obesity. Many studies have explored the relationship of decreased sleep durations and injuries, but few have examined the relationship between increased sleep duration and injury. The objective of this research is to identify the risk for injury associated with both decreased and increased sleep durations.

Methods

Data from the 2010 Community Health Survey were used in this study. We conducted logistic regression with average sleep duration as the independent variable, injury as a dependent variable, and controlling for age, sex, occupation, education, region (cities and provinces), smoking, alcohol use, body mass index, hypertension, diabetes, arthritis, and depression. Seven categories of sleep duration were established: ≤4, 5, 6, 7, 8, 9, and ≥10 hours.

Results

Using 7 hours of sleep as the reference, the adjusted injury risk (odds ratio) for those sleeping a total of ≤4 h/d was 1.53; 1.28 for 5 hours, for 1.11 for 6 hours, 0.98 for 8 hours, 1.12 for 9 hours, and 1.48 for ≥10 hours. The difference in risk was statistically significant for each category except for the 8 and 9 hours. In this study, risk increased as the sleep duration decreased or increased, except for the 8 and 9 hours.

Conclusions

This research found that either a decrease or increase in sleep duration was associated with an increased risk for injury. The concept of proper sleep duration can be evaluated by its associated injury risk.

Summary

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