TY  - JOUR
PY  - 2020//
TI  - Temporal trends and demographic risk factors for hospital admissions due to carbon monoxide poisoning in England
JO  - Preventive medicine
A1  - Roca-Barceló, Aina
A1  - Crabbe, Helen
A1  - Ghosh, Rebecca
A1  - Freni-Sterrantino, Anna
A1  - Fletcher, Tony
A1  - Leonardi, Giovanni
A1  - Hoge, Courtney
A1  - Hansell, Anna L.
A1  - Piel, Frédéric B.
SP  - ePub
EP  - ePub
VL  - ePub
IS  - ePub
N2  - 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.<br><br>Copyright © 2020. Published by Elsevier Inc.<p />  <p>Language: en</p>
LA  - en
SN  - 0091-7435
UR  - http://dx.doi.org/10.1016/j.ypmed.2020.106104
ID  - ref1
ER  -