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2016 ; 11
(5
): e0153516
Nephropedia Template TP
gab.com Text
Twit Text FOAVip
Twit Text #
English Wikipedia
County Poverty Concentration and Disparities in Unintentional Injury Deaths: A
Fourteen-Year Analysis of 1 6 Million U S Fatalities
#MMPMID27144919
Karb RA
; Subramanian SV
; Fleegler EW
PLoS One
2016[]; 11
(5
): e0153516
PMID27144919
show ga
Unintentional injury is the fourth leading cause of death in the United States,
and mortality due to injury has risen over the past decade. The social
determinants behind these rising trends have not been well documented. This study
examines the relationship between county-level poverty and unintentional injury
mortality in the United States from 1999-2012. Complete annual compressed
mortality and population data for 1999-2012 were obtained from the National
Center for Health Statistics and linked with census yearly county poverty
measures. The outcomes examined were unintentional injury fatalities, overall and
by six specific mechanisms: motor vehicle collisions, falls, accidental discharge
of firearms, drowning, exposure to smoke or fire, and unintentional poisoning.
Age-adjusted mortality rates and time trends for county poverty categories were
calculated, and multivariate negative binomial regression was used to determine
changes over time in both the relative risk of living in high poverty
concentration areas and the population attributable fraction. Age-adjusted
mortality rates for counties with > 20% poverty were 66% higher mortality in 1999
compared with counties with < 5% poverty (45.25 vs. 27.24 per 100,000; 95% CI for
rate difference 15.57,20.46), and that gap widened in 2012 to 79% (44.54 vs.
24.93; 95% CI for rate difference 17.13,22.09). The relative risk of living in
the highest poverty counties has increased for all injury mechanisms with the
exception of accidental discharge of firearms. The population attributable
fraction for all unintentional injuries rose from 0.22 (95% CI 0.13,0.30) in 1999
to 0.35 (95% CI 0.22,0.45) in 2012. This is the first study that uses
comprehensive mortality data to document the associations between county poverty
and injury mortality rates for the entire US population over a 14 year period.
This study suggests that injury reduction interventions should focus on areas of
high or increasing poverty.
|*Cause of Death
[MESH]
|*Poverty
[MESH]
|Accidental Falls/mortality
[MESH]
|Accidents, Traffic/mortality
[MESH]
|Accidents/*mortality
[MESH]
|Adolescent
[MESH]
|Adult
[MESH]
|Aged
[MESH]
|Aged, 80 and over
[MESH]
|Child
[MESH]
|Child, Preschool
[MESH]
|Drowning
[MESH]
|Female
[MESH]
|Firearms
[MESH]
|Geography
[MESH]
|Health Status Disparities
[MESH]
|Humans
[MESH]
|Infant
[MESH]
|Infant, Newborn
[MESH]
|Male
[MESH]
|Middle Aged
[MESH]
|Multivariate Analysis
[MESH]
|Regression Analysis
[MESH]
|Risk
[MESH]
|Sex Distribution
[MESH]
|Social Class
[MESH]
|United States
[MESH]
|Wounds and Injuries/epidemiology/*mortality
[MESH]