배경: 우울에 영향을 미치는 요인과 특히 우울의 진단및 치료에 영향을 미치는 사회인구학적, 건강행태, 건강상태 요인을 규명하여 비교 분석하고자 하였다.
방법: 2010년 및 2011년 국민건강영양조사 원시자료를이용하여 만 19세 이상 성인 13,306명을 분석대상으로 하였다. 교차분석 및 다중 로지스틱 회귀분석을 실시하였다.
결과: 다중 로지스틱 회귀분석 결과, 여성(여 vs. 남, OR(odds ratio)=3.35), 50대 연령(50-59 vs. 60+, OR=1.45),낮은 소득수준(하 vs. 상, OR=1.35; 중하 vs. 상, OR=1.29),무직(무 vs. 유, OR=1.23), 낮은 교육수준(초졸 vs. 대졸,OR=1.26; 중졸 vs. 대졸, OR=1.27; 고졸 vs. 대졸, OR=1.18),흡연(유 vs. 무, OR=1.19), 고위험음주(유 vs. 무, OR=2.28),낮은 주관적 건강(중 vs. 상, OR=1.52; 하 vs. 상, OR=2.65),만성질환(유 vs. 무, OR=1.255), 활동제한(유 vs. 무, OR=1.744),와병(유 vs. 무, OR=1.69) 등이 우울경험에 영향을 미치는 요인들이었다. 우울진단에 영향을 미치는 변수로는 거주지(대도시 vs. 군지역, OR=1.40)가 유일하였고, 남자일수록(여vs. 남, OR=0.501), 만성질환이 있을수록(OR=1.73), 활동제한이 있을수록(OR=2.05), 와병이 있을수록(OR=1.88) 우울치료를 받은 것으로 나타났다.
결론: 정책결정자는 우울증 진단율의 지역적 차이를 줄이기 위해 대도시 이외 지역에서의 우울진단율을 높이는한편 여성의 치료율을 향상시킬 수 있도록 노력해야 할것이다.
Background: We compared factors associated with self‐reported depression and, in particular, diagnosis andtreatment of depressive symptoms in Korean adults.
Methods: The sample included 13,306 adults aged 19 years or older from the 2010 and 2011 Korea NationalHealth and Nutrition Examination Survey (KNHANES Ⅴ). Data were applied to the χ 2 test and multivariate logisticregression analysis.
Results: The following characteristics of individuals are significantly associated with self-reported depression:female (vs. male, OR [odds ratio]=3.35), ages 50-59 years (vs. 60+, OR=1.45), economic status (low vs. high,OR=1.35; middle-low vs. high OR=1.29), unemployed (vs. employed, OR=1.23), education (elementary vs.
college, OR=1.18; middle school vs. college, OR=1.27; vs. high school vs. college, OR=1.18), current smoking (vs.
no, OR=1.19), high-risk alcohol consumption (vs. no, OR=1.18), perceived health (good vs. very good/excellent,OR=1.156; poor/fair vs. very good/excellent, OR=2.65), chronic disease (vs. no, OR=1.26), activity limitation dueto health problems (vs. no, OR=1.74), and being in a sickbed during the past month (vs. not in a sickbed, OR=1.69).
Living in a metropolitan area (vs. rural, OR=1.40) is significantly associated with greater odds of being diagnosedwith depression. The odds of being treated for depression are lower for female (vs. male, OR=0.53). Greater oddsof being treated for depression was seen for those with chronic conditions (vs. no, OR=1.73) and activity limitationdue to health problems (vs. no, OR=2.05), as well as, those in a sickbed (vs. not, OR=1.88).
Conclusions: Applying our findings, policy makers should address the lower rates of depression diagnosed innon-metropolitan areas to reduce regional variations, and also promote treatment in females.