Strosnider Heather, Kennedy Caitlin, Monti Michele, Yip Fuyuen
Environmental Health Tracking Branch, Division of Environmental Hazards and Health Effects, National Center for Environmental Health, CDC.
MMWR Surveill Summ. 2017 Jun 23;66(13):1-10. doi: 10.15585/mmwr.ss6613a1.
PROBLEM/CONDITION: The places in which persons live, work, and play can contribute to the development of adverse health outcomes. Understanding the differences in risk factors in various environments can help to explain differences in the occurrence of these outcomes and can be used to develop public health programs, interventions, and policies. Efforts to characterize urban and rural differences have largely focused on social and demographic characteristics. A paucity of national standardized environmental data has hindered efforts to characterize differences in the physical aspects of urban and rural areas, such as air and water quality.
2008-2012 for air quality and 2010-2015 for water quality.
Since 2002, CDC's National Environmental Public Health Tracking Program has collaborated with federal, state, and local partners to gather standardized environmental data by creating national data standards, collecting available data, and disseminating data to be used in developing public health actions. The National Environmental Public Health Tracking Network (i.e., the tracking network) collects data provided by national, state, and local partners and includes 21 health outcomes, exposures, and environmental hazards. To assess environmental factors that affect health, CDC analyzed three air-quality measures from the tracking network for all counties in the contiguous United States during 2008-2012 and one water-quality measure for 26 states during 2010-2015. The three air-quality measures include 1) total number of days with fine particulate matter (PM) levels greater than the U.S. Environmental Protection Agency's (EPA's) National Ambient Air Quality Standards (NAAQS) for 24-hour average PM (PM days); 2) mean annual average ambient concentrations of PM in micrograms per cubic meter (mean PM); and 3) total number of days with maximum 8-hour average ozone concentrations greater than the NAAQS (ozone days). The water-quality measure compared the annual mean concentration for a community water system (CWS) to the maximum contaminant level (MCL) defined by EPA for 10 contaminants: arsenic, atrazine, di(2-ethylhexyl) phthalate (DEHP), haloacetic acids (HAA5), nitrate, perchloroethene (PCE), radium, trichloroethene (TCE), total trihalomethanes (TTHM), and uranium. Findings are presented by urban-rural classification scheme: four metropolitan (large central metropolitan, large fringe metropolitan, medium metropolitan, and small metropolitan) and two nonmetropolitan (micropolitan and noncore) categories. Regression modeling was used to determine whether differences in the measures by urban-rural categories were statistically significant.
Patterns for all three air-quality measures suggest that air quality improves as areas become more rural (or less urban). The mean total number of ozone days decreased from 47.54 days in large central metropolitan counties to 3.81 days in noncore counties, whereas the mean total number of PM days decreased from 11.21 in large central metropolitan counties to 0.95 in noncore counties. The mean average annual PM concentration decreased from 11.15 μg/m in large central metropolitan counties to 8.87 μg/m in noncore counties. Patterns for the water-quality measure suggest that water quality improves as areas become more urban (or less rural). Overall, 7% of CWSs reported at least one annual mean concentration greater than the MCL for all 10 contaminants combined. The percentage increased from 5.4% in large central metropolitan counties to 10% in noncore counties, a difference that was significant, adjusting for U.S. region, CWS size, water source, and potential spatial correlation. Similar results were found for two disinfection by-products, HAA5 and TTHM. Arsenic was the only other contaminant with a significant result. Medium metropolitan counties had 3.1% of CWSs reporting at least one annual mean greater than the MCL, compared with 2.4% in large central counties.
Noncore (rural) counties experienced fewer unhealthy air-quality days than large central metropolitan counties, likely because of fewer air pollution sources in the noncore counties. All categories of counties had a mean annual average PM concentration lower than the EPA standard. Among all CWSs analyzed, the number reporting one or more annual mean contaminant concentrations greater the MCL was small. The water-quality measure suggests that water quality worsens as counties become more rural, in regards to all contaminants combined and for the two disinfection by-products individually. Although significant differences were found for the water-quality measure, the odds ratios were very small, making it difficult to determine whether these differences have a meaningful effect on public health. These differences might be a result of variations in water treatment practices in rural versus urban counties.
Understanding the differences between rural and urban areas in air and water quality can help public health departments to identify, monitor, and prioritize potential environmental public health concerns and opportunities for action. These findings suggest a continued need to develop more geographically targeted, evidence-based interventions to prevent morbidity and mortality associated with poor air and water quality.
问题/状况:人们生活、工作和娱乐的场所可能会导致不良健康后果的产生。了解不同环境中风险因素的差异有助于解释这些后果发生情况的差异,并可用于制定公共卫生计划、干预措施和政策。以往对城乡差异的描述主要集中在社会和人口特征方面。缺乏全国标准化的环境数据阻碍了对城乡地区物理层面差异(如空气质量和水质)的描述工作。
空气质量为2008 - 2012年,水质为2010 - 2015年。
自2002年以来,美国疾病控制与预防中心(CDC)的国家环境公共卫生跟踪项目与联邦、州和地方合作伙伴合作,通过制定国家数据标准、收集现有数据以及传播用于制定公共卫生行动的数据,来收集标准化的环境数据。国家环境公共卫生跟踪网络(即跟踪网络)收集国家、州和地方合作伙伴提供的数据,涵盖21种健康结果、暴露因素和环境危害。为评估影响健康的环境因素,CDC分析了2008 - 2012年期间美国本土所有县跟踪网络中的三项空气质量指标,以及2010 - 2015年期间26个州的一项水质指标。三项空气质量指标包括:1)细颗粒物(PM)水平高于美国环境保护局(EPA)的24小时平均PM国家环境空气质量标准(NAAQS)的天数总和(PM天数);2)以每立方米微克数计的年均环境PM平均浓度(平均PM);3)8小时平均臭氧浓度高于NAAQS的天数总和(臭氧天数)。水质指标将社区供水系统(CWS)的年均浓度与EPA针对10种污染物定义的最大污染物水平(MCL)进行比较:砷、阿特拉津、邻苯二甲酸二(2 - 乙基己基)酯(DEHP)、卤乙酸(HAA5)、硝酸盐、全氯乙烯(PCE)、镭、三氯乙烯(TCE)、总三卤甲烷(TTHM)和铀。研究结果按城乡分类方案呈现:四类大都市地区(大型中心大都市、大型边缘大都市、中型大都市和小型大都市)和两类非大都市地区(微型大都市和非核心地区)。采用回归模型来确定城乡类别在各项指标上的差异是否具有统计学意义。
所有三项空气质量指标的模式表明,随着地区变得更加乡村化(或城市化程度降低),空气质量有所改善。臭氧天数的平均总数从大型中心大都市县的47.54天降至非核心县的3.81天,而PM天数的平均总数从大型中心大都市县的11.21天降至非核心县的0.95天。年均PM平均浓度从大型中心大都市县的11.15μg/m³降至非核心县的8.87μg/m³。水质指标的模式表明,随着地区变得更加城市化(或乡村化程度降低),水质有所改善。总体而言,7%的CWS报告称所有10种污染物的年均浓度至少有一项超过MCL。这一比例从大型中心大都市县的5.4%升至非核心县的10%,在对美国地区、CWS规模、水源和潜在空间相关性进行调整后,这一差异具有统计学意义。对于两种消毒副产物HAA5和TTHM也发现了类似结果。砷是唯一有显著结果的其他污染物。中型大都市县有3.1%的CWS报告称至少有一项年均浓度超过MCL,而大型中心县为2.4%。
非核心(农村)县的空气质量不良天数少于大型中心大都市县,可能是因为非核心县的空气污染源较少。所有县的年均PM平均浓度均低于EPA标准。在所有分析的CWS中,报告有一项或多项年均污染物浓度超过MCL的数量较少。水质指标表明,就所有污染物综合而言以及就两种消毒副产物单独而言,随着县变得更加乡村化,水质变差。尽管在水质指标上发现了显著差异,但优势比非常小,难以确定这些差异是否对公共卫生有有意义的影响。这些差异可能是城乡县水处理方式不同的结果。
了解城乡地区在空气质量和水质方面的差异有助于公共卫生部门识别、监测潜在的环境公共卫生问题,并确定行动的优先事项和机会。这些发现表明,持续需要制定更具地域针对性、基于证据的干预措施,以预防与不良空气质量和水质相关的发病和死亡情况。