Ana Catarina Queiroga 1,2,3,4 , Rui Seabra 3,5,6 , Richard Charles Franklin 3,7,8 , Amy E Peden 3,4,7,8,9 Show Affiliations »
Abstract
INTRODUCTION: Imprecise data systems hinder understanding of drowning burden, even in high-income countries like Portugal, that have a well-implemented death certificate system. Consequently, national studies on drowning mortality are scarce. We aimed to explore drowning mortality in Portugal using national data and to compare these to Global Burden of Disease (GBD) estimates. METHODS: Data were obtained from the National Institute of Statistics (INE) for 1992-2019, using International Classification of Diseases (ICD)-9 and ICD-10 codes, by sex, age group and cause (unintentional; water transport and intentional). GBD unintentional drowning data were obtained online. Age-standardised drowning rates were calculated and compared. RESULTS: INE data showed 6057 drowning deaths, 4327 classified as unintentional (75.2% male; 36.7% 35-64 years; 31.5% 65+years; 15.2% 0-19 years). Following 2001, an increase in accidental drowning mortality and corresponding decrease in undetermined intent was observed, coincident with Portugal's ICD-10 implementation. GBD modelled estimates followed a downward trend at an overall rate of decrease of -0.41/decade (95% CI (-0.45 to -0.37); R2 adj=0.94; p<0.05). Conversely, INE data showed an increase in the rate of drowning deaths over the last decade (0.35/decade; 95% CI (-0.18 to 0.89)). GBD estimates were significantly different from the INE dataset (alpha=0.05), either underestimating as much as 0.567*INE in 1996 or overestimating as much as 1.473*INE in 2011. CONCLUSIONS: While GBD mortality data estimates are valuable in the absence of routinely collected data, they smooth variations, concealing key advocacy opportunities. Investment in country-level drowning registries enables in-depth analysis of incident circumstances. Such data are essential to informing National Water Safety Plans. © Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.
INTRODUCTION: Imprecise data systems hinder understanding of drowning burden, even in high-income countries like Portugal, that have a well-implemented death certificate system. Consequently, national studies on drowning mortality are scarce. We aimed to explore drowning mortality in Portugal using national data and to compare these to Global Burden of Disease (GBD) estimates. METHODS: Data were obtained from the National Institute of Statistics (INE) for 1992-2019, using International Classification of Diseases (ICD)-9 and ICD-10 codes, by sex, age group and cause (unintentional; water transport and intentional). GBD unintentional drowning data were obtained online. Age-standardised drowning rates were calculated and compared. RESULTS: INE data showed 6057 drowning deaths, 4327 classified as unintentional (75.2% male; 36.7% 35-64 years; 31.5% 65+years; 15.2% 0-19 years). Following 2001, an increase in accidental drowning mortality and corresponding decrease in undetermined intent was observed, coincident with Portugal's ICD-10 implementation. GBD modelled estimates followed a downward trend at an overall rate of decrease of -0.41/decade (95% CI (-0.45 to -0.37); R2 adj=0.94; p<0.05). Conversely, INE data showed an increase in the rate of drowning deaths over the last decade (0.35/decade; 95% CI (-0.18 to 0.89)). GBD estimates were significantly different from the INE dataset (alpha=0.05), either underestimating as much as 0.567*INE in 1996 or overestimating as much as 1.473*INE in 2011. CONCLUSIONS: While GBD mortality data estimates are valuable in the absence of routinely collected data, they smooth variations, concealing key advocacy opportunities. Investment in country-level drowning registries enables in-depth analysis of incident circumstances. Such data are essential to informing National Water Safety Plans. © Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.
Entities: Chemical
Keywords:
epidemiology; mortality; policy; surveillance
Mesh： See more »
Substances： See more »
Year: 2021
PMID： 34972682 DOI： 10.1136/injuryprev-2021-044415
Source DB: PubMed Journal: Inj Prev ISSN： 1353-8047 Impact factor: 3.770