背景：憂鬱症是常見的精神疾病，也是全球失能和疾病負擔的主要原因。根據WHO估計，2015年全球約有4.4%罹患憂鬱。憂鬱症不僅對健康造成負面影響，也可能導致自殺，其中社會和經濟環境為重要的影響因子。過去文獻顯示台灣的憂鬱症有增加的趨勢，然而，較少台灣研究探討社會和經濟環境與憂鬱之間的關係，如果能從中發現可改善之變項，也許能從不同的面向來預防憂鬱症。
目的：本研究目的旨在了解社會和經濟環境與個人憂鬱症狀分布情形，運用多層次分析方法探討兩者之間的關係，並進一步分層分析，探討性別和年齡與憂鬱症狀之間的關係。
方法：本研究採用2009年「國民健康訪問調查」資料，並串聯「高齡友善環境-縣市層級區位資料庫」中2009年之環境資料。樣本為20歲以上，排除住機構、代答、CES-D大於三題遺漏者，以及居住地遺漏者，最終樣本為6602位。研究之結果變項為憂鬱分數及有無憂鬱，以10題CES-D量表測量，總分為0至30分，越高分表示越嚴重，以10分為切點區分有無憂鬱。社會和經濟環境變項包含人口密度、離婚比率、刑案發生率、失業率、可支配所得和可得政府支出，依縣市平均分為低中高三組。個人變項包含社會人口學變項(性別、年齡、配偶、教育程度、工作、宗教信仰)、健康行為(抽菸、喝酒、運動)、健康狀態(自覺健康)。統計方法以ANOVA、t檢定等了解變項之分布和差異情形後；進一步以多層次分析(multilevel analysis)進行分析，探討社會和經濟環境與個人憂鬱症狀之間的關係，最後進行性別、年齡之分層分析。
結果：本研究6602位樣本中，女性占54.6%，平均年齡為53.94±19.29歲，憂鬱分數平均為5.11±4.32分，15.1%有憂鬱(憂鬱分數10以上)。環境變項中，僅失業率以低中高分組得到4、10、9個縣市，較不平均，其餘變項皆為7、8、7個縣市分三組。若將憂鬱以連續分數之模型，在控制個人變項後，可以發現整體而言僅人口密度中(β=0.76，p<.05)和失業率中(β=0.71，p<.05)顯著增加憂鬱分數。但將憂鬱以10分為切點區分有無時，可以發現人口密度為中組(OR=1.47，95% CI=1.11-1.94)、離婚比率為中和高組(中：OR=1.79，95% CI=1.18-2.74；高：OR=1.44，95% CI=1.04-2.00)、失業率為中和高組(中：OR=1.33，95% CI=1.02-1.73；高：OR=1.44，95% CI=1.06-1.95)、可得政府支出為高組(OR=1.35，95% CI=1.07-1.70)有關。
分性別後，在憂鬱分數之模型中，可以發現男性與失業率較有關(中β=0.804，p<.05；高β=0.922，p<.05)，女性則和人口密度較有關(中β=0.826，p<.05)。若分為有無憂鬱時，男性與失業率(中：OR=1.78，95% CI=1.13-2.81；高：OR=2.34，95% CI=1.42-3.86)和可得政府支出(高：OR=1.75，95% CI=1.21-2.53)較有關，女性則與人口密度(中：OR=1.54，95% CI=1.08-2.21)和離婚比率(中：OR=1.95，95% CI=1.14-3.36)有關。分年齡層後，在憂鬱分數之模型中，可以發現僅20-44歲與失業率(中β=1.146，p<.01；高β=0.988，p<.05)、可得政府支出(中β=0.909，p<.05；高β=0.626，p<.05)有關。但將憂鬱分為有無時，除了20-44歲與失業率(中：OR=1.70，95% CI=1.11-2.62；高：OR=1.73，95% CI=1.05-2.84)和可得政府支出(高：OR=1.57，95% CI=1.10-2.26)有關之外，45-64歲則與離婚比率(中：OR=3.27，95% CI=1.03-10.42)有關，65歲以上與人口密度(中：OR=1.87，95% CI=1.18-2.96)和離婚比率(中：OR=2.58，95% CI=1.27-5.24；高：OR=1.77，95% CI=1.02-3.06)有關。
結論：社會和經濟環境對不同性別和年齡層，其關係有所不同，男性和較年輕的族群(20-44歲)與經濟環境較有關，而女性和較年長的族群(45-64歲和65歲以上)則與社會環境較有關。本研究為橫斷性研究，故無法推論因果關係，建議未來研究可採用長期追蹤研究，以進一步檢視社經環境因子與憂鬱之關係。

The purpose of this study was to examine the relationship between social and economic environments and the depressive symptoms of Taiwanese adults. Data were retrieved from “2009 National Health Interview Survey (NHIS)”, a nationally representative survey, and combined with the dataset from “Age-Friendly Environment database- country/city levels”. Social and economic environments were divided into three levels: low, medium, and high. Depressive symptoms were measured by 10-items Chinese version of Center for Epidemiological Studies Depression Scale (CES-D).
After controlling for individual variables, compared with the low level, population density and unemployment rate were related to the increases and higher risk of depressive symptoms. Divorce rate was only associated with higher risk of depression. After stratifying by gender and age groups, man and younger group (20-44 years old) were associated with economic environments. Woman and elder groups (45-64, 65 or older) were associated with social environments. This study was a cross-sectional study and further longitudinal study is needed to re-examine the relationship between social and economic environments and depression.

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