Relationships of Antidepressant Medication With Its Various Factors Including Nitrogen Dioxides Seasonality: Machine Learning Analysis Using National Health Insurance Data

• 영문명: Relationships of Antidepressant Medication With Its Various Factors Including Nitrogen Dioxides Seasonality: Machine Learning Analysis Using National Health Insurance Data
• 발행기관: 대한신경정신의학회
• 저자명: Kwang-Sig Lee Hae-In Kim Byung-Joo Ham
• 간행물 정보: 『Psychiatry Investigation』제20권 제6호, 515~523쪽, 전체 9쪽
• 주제분류: 의약학 > 정신과학
• 파일형태: PDF
• 발행일자: 2023.06.30

영문 초록

Objective This study employs machine learning and population-based data to examine major factors of antidepressant medication including nitrogen dioxides (NO2) seasonality. Methods Retrospective cohort data came from Korea National Health Insurance Service claims data for 43,251 participants with the age of 15–79 years, residence in the same districts of Seoul and no history of antidepressant medication during 2002–2012. The dependent variable was antidepressant-free months during 2013–2015 and the 103 independent variables for 2012 or 2015 were considered, e.g., particulate matter less than 2.5 micrometer in diameter (PM2.5), PM10, NO2, ozone (O3), sulphur dioxide (SO2) and carbon monoxide (CO) in each of 12 months in 2015. Results It was found that the Cox hazard ratios of NO2 were statistically significant and registered values larger than 10 for every three months: March, June–July, October, and December. Based on random forest variable importance and Cox hazard ratios in brackets, indeed, the top 20 factors of antidepressant medication included age (0.0041 [1.69–2.25]), migraine and sleep disorder (0.0029 [1.82]), liver disease (0.0017 [1.33–1.34]), exercise (0.0014), thyroid disease (0.0013), cardiovascular disease (0.0013 [1.20]), asthma (0.0008 [1.19–1.20]), September NO2 (0.0008 [0.01]), alcohol consumption (0.0008 [1.31–1.32]), gender - woman (0.0007 [1.80–1.81]), July NO2 (0.0007 [14.93]), July PM10 (0.0007), the proportion of the married (0.0005), January PM2.5 (0.0004), September PM2.5 (0.0004), chronic obstructive pulmonary disease (0.0004), economic satisfaction (0.0004), January PM10 (0.0003), residents in welfare facilities per 1,000 (0.0003 [0.97]), and October NO2 (0.0003). Conclusion Antidepressant medication has strong associations with neighborhood conditions including NO2 seasonality and welfare support.

목차

INTRODUCTION

METHODS

RESULTS

DISCUSSION

REFERENCES

키워드

Antidepressive agents Particulate matter Nitrogen Machine learning