UK Small Area Health Statistics Unit (SAHSU), Department of Epidemiology & Biostatistics, School of Public Health, Imperial College London, London, UK.
Environmental Epidemiology Group, Centre for Radiation, Chemical and Environmental Hazards, Public Health England, Chilton, UK; National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Health Impact of Environmental Hazards, UK.
Prev Med. 2020 Jul;136:106104. doi: 10.1016/j.ypmed.2020.106104. Epub 2020 Apr 27.
Unintentional non-fire related (UNFR) carbon monoxide (CO) poisoning is a preventable cause of morbidity and mortality. Epidemiological data on UNFR CO poisoning can help monitor changes in the magnitude of this burden, particularly through comparisons of multiple countries, and to identify vulnerable sub-groups of the population which may be more at risk. Here, we collected data on age- and sex- specific number of hospital admissions with a primary diagnosis of UNFR CO poisoning in England (2002-2016), aggregated to small areas, alongside area-level characteristics (i.e. deprivation, rurality and ethnicity). We analysed temporal trends using piecewise log-linear models and compared them to analogous data obtained for Canada, France, Spain and the US. We estimated age-standardized rates per 100,000 inhabitants by area-level characteristics using the WHO standard population (2000-2025). We then fitted the Besag York Mollie (BYM) model, a Bayesian hierarchical spatial model, to assess the independent effect of each area-level characteristic on the standardized risk of hospitalization. Temporal trends showed significant decreases after 2010. Decreasing trends were also observed across all countries studied, yet France had a 5-fold higher risk. Based on 3399 UNFR CO poisoning hospitalizations, we found an increased risk in areas classified as rural (0.69, 95% CrI: 0.67; 0.80), highly deprived (1.77, 95% CrI: 1.66; 2.10) or with the largest proportion of Asian (1.15, 95% CrI: 1.03; 1.49) or Black population (1.35, 95% CrI: 1.20; 1.80). Our multivariate approach provides strong evidence for the identification of vulnerable populations which can inform prevention policies and targeted interventions.
非火灾相关(UNFR)一氧化碳(CO)中毒是一种可预防的发病率和死亡率原因。UNFR CO 中毒的流行病学数据可以帮助监测这种负担的变化幅度,特别是通过比较多个国家,并确定可能面临更大风险的脆弱人群亚组。在这里,我们收集了英格兰(2002-2016 年)因 UNFR CO 中毒住院的年龄和性别特定人数的数据,按小地区汇总,并与地区水平特征(即贫困、农村和种族)相关联。我们使用分段对数线性模型分析了时间趋势,并将其与加拿大、法国、西班牙和美国获得的类似数据进行了比较。我们根据世界卫生组织标准人口(2000-2025 年),按地区水平特征估计了每 10 万人标准化发病率。然后,我们拟合了 Besag York Mollie(BYM)模型,这是一种贝叶斯层次空间模型,以评估每个地区水平特征对住院标准化风险的独立影响。时间趋势显示,2010 年后显著下降。所有研究国家也观察到下降趋势,但法国的风险高 5 倍。根据 3399 例非火灾相关 CO 中毒住院病例,我们发现农村地区(0.69,95% CrI:0.67;0.80)、高度贫困地区(1.77,95% CrI:1.66;2.10)或亚洲人口比例最大的地区(1.15,95% CrI:1.03;1.49)或黑人人口比例最大的地区(1.35,95% CrI:1.20;1.80)的风险增加。我们的多变量方法为识别脆弱人群提供了有力证据,这可以为预防政策和有针对性的干预措施提供信息。