人群的自然和社会属性分类下PM2.5对心血管疾病的影响

为了研究人群在自然属性和社会属性分类下的效应修饰作用,利用2005~2011年北京市大气PM_2.5日均浓度、气象要素及循环系统疾病每日死亡人数数据,根据不同年龄、性别及学历将人群分组,采用时间序列的半参数广义相加模型（GAM）,定量评价大气PM_2.5对居民循环系统疾病死亡人数的影响.单污染物模型和多污染物模型结果表明,PM_2.5为影响循环系统疾病每日死亡人数的主要大气污染物.北京市空气中PM_2.5的浓度每增加10μg/m³,循环系统疾病总死亡人数增加0.50%（95% CI：0.36,0.63）.不同人群的易感程度不同,各人群死亡人数的增加范围为0.23~0.71%,女性、60~74岁人群、文盲人群的健康风险相对较高.在文盲人群中,老年（60+）女性占比为66.2%,为了分离社会属性人群分类中可能存在的自然属性因素干扰,本文去除其中老年、女性这两个混杂因素的影响,文盲人群健康风险仍然大于较高学历的人群.年龄和性别因素叠加在学历因素上,可能加大低学历人群的健康风险,对于这部分叠加了自然因素和社会因素双重敏感性的人群应给与重点关注.     

Are there higher pedestrian fatalities in larger cities?: A scaling analysis of 115 to 161 largest cities in the United States

Objective: In 2012, 4,743 pedestrians were killed in the United States, representing 14% of total traffic fatalities. The number of pedestrians injured was higher at 76,000. Therefore, 36 out of 52 of the largest cities in the United States have adopted a citywide target of reducing pedestrian fatalities. The number of cities adopting the reduction goal during 2011 and 2012 increased rapidly with 8 more cities. We examined the scaling relationship of pedestrian fatality counts as a function of the population size of 115 to 161 large U.S. cities during the period of 1994 to 2011. We also examined the scaling relationship of nonpedestrian and total traffic fatality counts as a function of the population size.

Methods: For the data source of fatality measures we used Traffic Safety Facts Fatality Analysis Reporting System/General Estimates System annual reports published each year from 1994 to 2011 by the NHTSA. Using the data source we conducted both annual cross-sectional and panel data bivariate and multivariate regression models. In the construction of the estimated functional relationship between traffic fatality measures and various factors, we used the simple power function for urban scaling used by Bettencourt et al. (2007 Bettencourt LMA, Lobo J, Helbing D, Kühnert C, West GB. Growth, innovation, scaling and the pace of life in cities. Proc Natl Acad Sci USA. 2007;104:7301–7306.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar], 2010 Bettencourt LMA, Lobo J, Strumsky D, West GB. Urban scaling and its deviations: revealing the structure of wealth, innovation and crime across cities. PLoS ONE. 2010;5:e13541.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) and the refined STIRPAT (stochastic impacts by regression on population, affluence, and technology) model used in Dietz and Rosa (1994 Dietz T, Rosa EA. Rethinking the environmental impacts of population, affluence and technology. Human Ecology Review. 1994;1:277–300. [Google Scholar], 1997 Dietz T, Rosa EA. Effects of population and affluence on CO₂ emissions. Proc Natl Acad Sci USA. 1997;94:175–179.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) and York et al. (2003 York R, Rosa EA, Dietz T. STIRPAT, IPAT and IMPACT: analytic tools for unpacking the driving forces of environmental impacts. Ecol Econ. 2003;46:351–365.[Crossref], [Web of Science ®] , [Google Scholar]).

Results: We found that the scaling relationship display diseconomies of scale or sublinear for pedestrian fatalities. However, the relationship displays a superlinear relationship in case of nonpedestrian fatalities. The scaling relationship for total traffic fatality counts display a nearly linear pattern. When the relationship was examined by the 4 subgroups of cities with different population sizes, the most pronounced sublinear scaling relationships for all 3 types of fatality counts was discovered for the subgroup of megacities with a population of more than 1 million.

Conclusions: The scaling patterns of traffic fatalities of subgroups of cities depend on population sizes of the cities in subgroups. In particular, 9 megacities with populations of more than 1 million are significantly different from the remaining cities and should be viewed as a totally separate group. Thus, analysis of the patterns of traffic fatalities needs to be conducted within the group of megacities separately from the other cities with smaller population sizes for devising prevention policies to reduce traffic fatalities in both megacities and smaller cities.