Air pollution and its impacts on health in Vitoria, Espirito Santo, Brazil

ABSTRACT OBJECTIVE To analyze the impact of air pollution on respiratory and cardiovascular morbidity of children and adults in the city of Vitoria, state of Espirito Santo. METHODS A study was carried out using time-series models via Poisson regression from hospitalization and pollutant data in Vitoria, ES, Southeastern Brazil, from 2001 to 2006. Fine particulate matter (PM10), sulfur dioxide (SO2), and ozone (O3) were tested as independent variables in simple and cumulative lags of up to five days. Temperature, humidity and variables indicating weekdays and city holidays were added as control variables in the models. RESULTS For each increment of 10 µg/m3 of the pollutants PM10, SO2, and O3, the percentage of relative risk (%RR) for hospitalizations due to total respiratory diseases increased 9.67 (95%CI 11.84-7.54), 6.98 (95%CI 9.98-4.17) and 1.93 (95%CI 2.95-0.93), respectively. We found %RR = 6.60 (95%CI 9.53-3.75), %RR = 5.19 (95%CI 9.01-1.5), and %RR = 3.68 (95%CI 5.07-2.31) for respiratory diseases in children under the age of five years for PM10, SO2, and O3, respectively. Cardiovascular diseases showed a significant relationship with O3, with %RR = 2.11 (95%CI 3.18-1.06). CONCLUSIONS Respiratory diseases presented a stronger and more consistent relationship with the pollutants researched in Vitoria. A better dose-response relationship was observed when using cumulative lags in polynomial distributed lag models.

摘要
研究目的：分析巴西圣埃斯皮里图州维多利亚市的空气污染对儿童及成人呼吸与心血管疾病发病的影响。
研究方法：本研究采用时间序列模型结合泊松回归（Poisson regression），对巴西东南部圣埃斯皮里图州维多利亚市2001至2006年的住院数据与污染物监测数据开展分析。将细颗粒物（PM10）、二氧化硫（SO2）及臭氧（O3）作为自变量，分别以单日滞后及最长5天的累积滞后效应展开分析；模型中纳入气温、湿度以及代表工作日与城市节假日的变量作为控制变量。
研究结果：当PM10、SO2、O3浓度每升高10 µg/m³时，全人群因呼吸系统疾病住院的相对风险百分比（%RR）分别升高9.67（95%置信区间：11.84~7.54）、6.98（95%置信区间：9.98~4.17）及1.93（95%置信区间：2.95~0.93）。针对5岁以下儿童群体，PM10、SO2、O3对应的呼吸系统疾病住院%RR分别为6.60（95%置信区间：9.53~3.75）、5.19（95%置信区间：9.01~1.50）及3.68（95%置信区间：5.07~2.31）。心血管疾病与O3呈现显著关联，其%RR为2.11（95%置信区间：3.18~1.06）。
研究结论：本研究中，呼吸系统疾病与所纳入的空气污染物之间呈现出更强且更稳定的关联。采用多项式分布滞后模型（polynomial distributed lag models）的累积滞后分析时，可观察到更优的剂量-反应关系。