Childhood exposure to ambient air pollution and predicting individual risk of depression onset in UK adolescents.
Childhood exposure to ambient air pollution and predicting individual risk of depression onset in UK adolescents.
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DOI：
10.1016/j.jpsychires.2021.03.042
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发表时间：
2021-06
影响因子：
4.8
通讯作者：
Fisher HL
中科院分区：
文献类型：
--
作者：
Latham RM;Kieling C;Arseneault L;Botter-Maio Rocha T;Beddows A;Beevers SD;Danese A;De Oliveira K;Kohrt BA;Moffitt TE;Mondelli V;Newbury JB;Reuben A;Fisher HL
了解重度抑郁症（MDD）的早期风险因素对于识别高危人群至关重要。最近开发了一个多变量模型来预测青少年未来患抑郁症的个人风险，但其在英国样本中的表现远非完美。考虑到空气污染在抑郁症病因学中的潜在作用，我们调查了是否将儿童暴露于空气污染作为风险预测模型中的额外预测因子，以提高对英国青少年发展MDD风险最大的识别。我们使用了来自环境风险（E-Risk）纵向双胞胎研究的数据，这是一项具有全国代表性的英国出生队列，共有2，232名儿童，随访至18岁，保留率为93%。儿童10岁时每年接触四种污染物--二氧化氮（NO2）、氮氧化物（NOX）、<2.5μm的颗粒物（PM2.5）和<10μm的颗粒物（PM10）。MDD在18岁时通过访谈进行评估。NOX（调整后OR=1.43，95%CI =0.96-2.13）和PM2.5（调整后OR =1.35，95%CI =0.95-1.92）年暴露水平最高（前四分位数）的参与者发生MDD的风险升高最多。将这些环境污染估计数单独纳入风险预测模型提高了模型的特异性，但降低了模型的敏感性-导致模型性能的净改善微乎其微。研究结果表明，儿童环境空气污染暴露在青少年抑郁症的发展中的潜在作用，但建议，包括风险因素以外的其他可能是重要的，以提高风险预测模型的性能。
Knowledge about early risk factors for major depressive disorder (MDD) is critical to identify those who are at high risk. A multivariable model to predict adolescents’ individual risk of future MDD has recently been developed however its performance in a UK sample was far from perfect. Given the potential role of air pollution in the aetiology of depression, we investigate whether including childhood exposure to air pollution as an additional predictor in the risk prediction model improves the identification of UK adolescents who are at greatest risk for developing MDD. We used data from the Environmental Risk (E-Risk) Longitudinal Twin Study, a nationally representative UK birth cohort of 2,232 children followed to age 18 with 93% retention. Annual exposure to four pollutants – nitrogen dioxide (NO2), nitrogen oxides (NOX), particulate matter <2.5μm (PM2.5) and <10μm (PM10) – were estimated at address-level when children were aged 10. MDD was assessed via interviews at age 18. The risk of developing MDD was elevated most for participants with the highest (top quartile) level of annual exposure to NOX (adjusted OR=1.43, 95% CI=0.96-2.13) and PM2.5 (adjusted OR=1.35, 95% CI=0.95-1.92). The separate inclusion of these ambient pollution estimates into the risk prediction model improved model specificity but reduced model sensitivity – resulting in minimal net improvement in model performance. Findings indicate a potential role for childhood ambient air pollution exposure in the development of adolescent MDD but suggest that inclusion of risk factors other than this may be important for improving the performance of the risk prediction model.
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影响因子：
10.6
作者：
Miller, Andrew H.;Maletic, Vladimir;Raison, Charles L.
通讯作者：
Raison, Charles L.
影响因子：
4.4
作者：
Bakolis I;Hammoud R;Stewart R;Beevers S;Dajnak D;MacCrimmon S;Broadbent M;Pritchard M;Shiode N;Fecht D;Gulliver J;Hotopf M;Hatch SL;Mudway IS
通讯作者：
Mudway IS
影响因子：
4.9
作者：
Kelly, FJ
通讯作者：
Kelly, FJ
影响因子：
7.6
作者：
Moffitt, TE
通讯作者：
Moffitt, TE
影响因子：
15.9
作者：
Block, Michelle L.;Calderon-Garciduenas, Lilian
通讯作者：
Calderon-Garciduenas, Lilian