目的: 对天津和上海35岁以上人群氮氧化物(nitrogen oxides，NO_X)与二氧化氮(nitrogen dioxide，NO₂)个体暴露水平进行测量，并探讨研究对象基线特征、居住环境情况及日常活动模式等因素对其影响。方法: 采用定组研究，在天津和上海招募91名年龄35岁以上的研究对象，分别在夏季和冬季各进行3次随访(上海冬季因新型冠状病毒肺炎疫情影响只进行了1次随访)，每两次随访之间间隔至少为2个星期，有27名研究对象参与了两个季节的研究。每次随访使用Ogawa被动式采样器测量个体24 h NO_X与NO₂暴露浓度，通过问卷和日志收集日常活动模式信息。采用混合线性效应模型分析不同因素对NO_X与NO₂个体暴露水平的影响。结果: 两地人群共完成349人次有效的24 h内NO₂与NO_X个体暴露监测，天津夏季NO₂与NO_X个体暴露日均值(体积分数)分别为18.0×10^-9和26.2×10^-9，天津冬季分别为31.0×10^-9和54.9×10^-9，上海夏季分别为38.7×10^-9和100.0×10^-9，上海冬季分别为45.5×10^-9和139.2×10^-9。单因素回归分析结果显示NO_X与NO₂个体暴露水平与城市、季节、性别、日均做饭次数以及监测站大气NO₂浓度显著相关。除以上因素外，NO_X个体暴露水平还与教育水平有显著关联，NO₂个体暴露水平还与是否被动吸烟、日均居家时间、烹饪燃料类型、住宅与交通主干道距离、是否使用抽油烟机存在显著关联。多因素回归分析显示，NO₂与NO_X个体暴露水平天津显著低于上海，夏季显著低于冬季，男性NO_X个体暴露水平显著高于女性。监测站NO₂浓度与NO₂和NO_X个体暴露水平呈显著正向关联；日均做饭次数与NO₂个体暴露水平之间呈显著正向关联，日均居家时间与NO₂个体暴露水平之间呈显著负向关联。大气NO₂浓度每升高1个四分位间距(interquartile range，IQR), 即12.7×10^-9，NO₂个体暴露水平上升27.5%[95%置信区间(confidence interval，CI)：17.0%~38.9%]，NO_X个体暴露水平上升16.1%(95%CI：7.1%~25.8%)。结论: 不同季节、城市和大气NO₂浓度均可以影响NO₂与NO_X的个体暴露水平，同时NO₂个体暴露水平还受到生活习惯等因素的影响。

Objective: To investigate personal exposures to nitrogen oxides (NO_X) and nitrogen di-oxide (NO₂) and the influence of baseline personal characteristics, living environment and daily activity patterns of the participants on the exposures among adults over 35 in Tianjin and Shanghai. Methods: In this panel study, 91 healthy nonsmoking adults aged over 35 from Tianjin and Shanghai participated in our study. The study was conducted in summer and winter. The participants were followed for three times with an interval of at least two weeks. Only participants in Shanghai were followed once in winter because of the COVID-19 pandemic. Twenty-seven participants completed follow-up visits in both seasons. We measured their 24 h personal exposures to NO_X and NO₂and collected their baseline and time-activity information through questionnaire/diary. The linear mixed model was used to analyze the associations between potential influencing factors and personal NO_X and NO₂ exposure levels. Results: There were 349 follow-up visits with valid 24 h personal NO₂ and NO_X exposure measurements in the two cities. The ave-rage 24 h personal exposures to NO₂ and NO_X (volume fraction) in Tianjin participants were 18.0×10^-9 and 26.2×10^-9 in summer, and 31.0×10^-9 and 54.9×10^-9 in winter, respectively; and the average 24 h personal exposures to NO₂ and NO_X in Shanghai participants were 38.7×10^-9 and 100.0×10^-9 in summer, and 45.5×10^-9 and 139.2×10^-9 in winter, respectively. The results of univariate regression analysis showed that their personal NO_X exposure levels were significantly associated with city, season, gender, average daily cooking times, and ambient NO₂ concentrations measured at fixed-site monitoring stations. In addition to the above factors, the personal NO_X exposure levels were also significantly associated with educational level and the personal NO₂ exposure levels were also significantly associated with passive smoking, average daily home time, cooking energy type, residential distance from main traffic road, and use of kitchen ventilators. Multivariate regression analysis showed that the personal exposure levels of NO₂ and NO_X were significantly lower in Tianjin than that in Shanghai, were significantly lower in summer than that in winter, and were significantly and positively associated with ambient NO₂ concentrations measured at fixed-site monitoring stations. In addition, personal NO_X exposure levels were significantly lower in females than in males, and personal NO₂ exposure levels were significantly positively associated with average daily cooking times and significantly inversely associated with average daily home time. For every interquartile range (IQR) increase (12.7×10^-9) in ambient NO₂, the personal NO₂ exposure levels increased by 27.5% (95%CI: 17.0%-38.9%), and personal NO_X exposure levels increased by 16.1% (95%CI: 7.1%-25.8%). Conclusion: Season, city and ambient NO₂ concentrations are significant influencing factors of personal exposure levels of NO₂and NO_X. At the same time, the personal exposures levels of NO₂are also affected by lifestyle factors. Our study provides scientific evidence for making precise air pollution control decisions and reducing the exposure levels of NO_X in the population.