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天津地区不同年龄组人群代谢综合征患病情况及其影响因素分析 被引量:1
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作者 潘怡 薛晓丹 +2 位作者 李威 辛鹏 王德征 《中华健康管理学杂志》 CAS CSCD 2022年第12期833-839,共7页
目的探讨天津地区不同年龄组人群代谢综合征(MS)患病情况及其相关影响因素。方法本研究以2015年9—11月开展的中国成人慢性病与营养监测天津地区调查人群为研究对象,采用多阶段整群随机抽样方法抽取天津市7个区42个监测点中18岁及以上... 目的探讨天津地区不同年龄组人群代谢综合征(MS)患病情况及其相关影响因素。方法本研究以2015年9—11月开展的中国成人慢性病与营养监测天津地区调查人群为研究对象,采用多阶段整群随机抽样方法抽取天津市7个区42个监测点中18岁及以上常住居民1753例,对其进行MS与各影响因素关系的描述性流行病学分析,采用χ^(2)检验、单因素logistic回归和决策树模型进行分析。结果天津市MS患病率为30.6%,标化患病率为24.5%,MS患病率随年龄增长而升高,老年组(≥60岁)最高,为38.9%。决策树模型显示,青年组(18~44岁)MS影响因素为性别、吸烟、主观健康感觉、年收入、睡眠时间,标准化重要性分别为100%、95.59%、22.55%、20.94%、9.89%。中年组(45~59岁)MS影响因素为二手烟暴露、主观健康感觉、睡眠时间、膳食宝塔得分、地区,标准化重要性分别为100%、98.08%、91.04%、45.74%、20.15%。老年组(≥60岁)MS影响因素为睡眠时间、二手烟暴露、性别、膳食宝塔得分、地区,标准化重要性分别为100%、46.75%、41.87%、41.82%、7.60%。结论天津地区调查人群MS患病率较高,烟草危害(吸烟、二手烟暴露)和睡眠时间是各年龄组居民MS的共同影响因素,3个年龄组人群不同影响因素分布各有侧重,应采取针对性的干预措施。 展开更多
关键词 代谢综合征 患病率 影响因素 决策树 天津
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Exposure measurement, risk assessment and source identification for exposure of traffic assistants to particle-bound PAHs in Tianjin, China 被引量:2
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作者 xiaodan xue Yan You +4 位作者 Jianhui Wu Bin Han Zhipeng Bai Naijun Tang Liwen Zhang 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2014年第2期448-457,共10页
To investigate the levels of exposure to particulate-bound polycyclic aromatic hydrocarbon (PAH) and to estimate the risk these levels pose to traffic assistants (TAs) in Tianjin (a rnegacity in North China), a ... To investigate the levels of exposure to particulate-bound polycyclic aromatic hydrocarbon (PAH) and to estimate the risk these levels pose to traffic assistants (TAs) in Tianjin (a rnegacity in North China), a measurement campaign (33 all-day exposure samples, 25 occupational-exposure samples and 10 indoor samples) was conducted to characterize the TAs' exposure to PAHs, assess the cancer risk and identify the potential sources of exposure. The average total exposure concentration of 14 PAHs was approximately 2871 + 928 ng/rn3 (on-duty), and 1622 + 457 ng/m3 (all-day). The indoor PAHs level was 1257 + 107 ng/m3. After 8000 Monte Carlo simulations, the cancer risk resulting from exposure to PAHs was found to be approximately 1.05 x 10-4. A multivariate analysis was applied to identify the potential sources, and the results showed that, in addition to vehicle exhaust, coal combustion and cooking fumes were also another two important contributors to personal PAH exposure. The diagnostic ratios of PAH compounds agree with the source apportionment results derived from principal component analysis. 展开更多
关键词 polycyclic aromatic hydrocarbons exposure risk assessment traffic assistants source identification
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