Dataset Information

Contextual Factors Associated With County-Level Suicide Rates in the United States, 1999 to 2016.

ABSTRACT:

Importance

Understanding geographic and community-level factors associated with suicide can inform targeted suicide prevention efforts.

Objectives

To estimate suicide rates and trajectories, assess associated county-level contextual factors, and explore variation across the rural-urban continuum.

Design, setting, and participants

This cross-sectional study included all individuals aged 25 to 64 years who died by suicide from January 1, 1999, to December 31, 2016, in the United States. Spatial analysis was used to map excess risk of suicide, and longitudinal random-effects models using negative binomial regression tested associations of contextual variables with suicide rates as well as interactions among county-level contextual variables. Data analyses were conducted between January 2019 and July 2019.

Exposure

County of residence.

Main outcomes and measures

Three-year county suicide rates during an 18-year period stratified by rural-urban location.

Results

Between 1999 and 2016, 453?577 individuals aged 25 to 64 years died by suicide in the United States. Decedents were primarily male (349?082 [77.0%]) with 101?312 (22.3%) aged 25 to 34 years, 120?157 (26.5%) aged 35 to 44 years, 136?377 (30.1%) aged 45 to 54 years, and 95?771 (21.1%) aged 55 to 64 years. Suicide rates were higher and increased more rapidly in rural than in large metropolitan counties. The highest deprivation quartile was associated with higher suicide rates compared with the lowest deprivation quartile, especially in rural areas, although this association declined during the period studied (rural, 1999-2001: incidence rate ratio [IRR], 1.438; 95% CI, 1.319-1.568; P?Conclusions and relevanceThis study found that suicide rates have increased across the nation and most rapidly in rural counties, which may be more sensitive to the impact of social deprivation than more metropolitan counties. Improving social connectedness, civic opportunities, and health insurance coverage as well as limiting access to lethal means have the potential to reduce suicide rates across the rural-urban continuum.

SUBMITTER: Steelesmith DL

PROVIDER: S-EPMC6735416 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Contextual Factors Associated With County-Level Suicide Rates in the United States, 1999 to 2016.

Steelesmith Danielle L DL Fontanella Cynthia A CA Campo John V JV Bridge Jeffrey A JA Warren Keith L KL Root Elisabeth D ED

JAMA network open 20190904 9

<h4>Importance</h4>Understanding geographic and community-level factors associated with suicide can inform targeted suicide prevention efforts.<h4>Objectives</h4>To estimate suicide rates and trajectories, assess associated county-level contextual factors, and explore variation across the rural-urban continuum.<h4>Design, setting, and participants</h4>This cross-sectional study included all individuals aged 25 to 64 years who died by suicide from January 1, 1999, to December 31, 2016, in the Uni ...[more]

PMID: 31490540

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Project description:ImportanceSuicide is the second leading cause of death among youths aged 10 to 19 years in the United States, with rates nearly doubling during the past decade. Youths in impoverished communities are at increased risk for negative health outcomes; however, the association between pediatric suicide and poverty is not well understood.ObjectiveTo assess the association between pediatric suicide rates and county-level poverty concentration.Design, setting, and participantsThis retrospective, cross-sectional study examined suicides among US youths aged 5 to 19 years from January 1, 2007, to December 31, 2016. Suicides were identified using International Statistical Classification of Diseases, Tenth Revision, Clinical Modification codes from the Centers for Disease Control and Prevention's Compressed Mortality File. Data analysis was performed from February 1, 2019, to September 10, 2019.ExposuresCounty poverty concentration and the percentage of the population living below the federal poverty level. Counties were divided into 5 poverty concentration categories: 0% to 4.9%, 5.0% to 9.9%, 10.0% to 14.9%, 15.0% to 19.9%, and 20.0% or more of the population living below the federal poverty level.Main outcomes and measuresThe study used a multivariable negative binomial regression model to analyze the association between pediatric suicide rates and county poverty concentration, reporting adjusted incidence rate ratios (aIRRs) with 95% CIs. The study controlled for year, demographic characteristics of the children who died (age, sex, and race/ethnicity), county urbanicity, and county demographic features (age, sex, and racial composition). Subgroup analyses were stratified by method.ResultsFrom 2007 to 2016, a total of 20 982 youths aged 5 to 19 years died by suicide (17 760 [84.6%] were aged 15-19 years, 15 982 [76.2%] male, and 14 387 [68.6%] white non-Hispanic). The annual suicide rate was 3.35 per 100 000 youths aged 5 to 19 years. In the multivariable model, compared with counties with the lowest poverty concentration (0%-4.9%), counties with poverty concentrations of 10% or greater had higher suicide rates in a stepwise manner (10.0%-14.9%: aIRR, 1.25 [95% CI, 1.06-1.47]; 15.0%-19.9%: aIRR, 1.30 [95% CI, 1.10-1.54]; and 20.0% or more: aIRR, 1.37 [95% CI, 1.15-1.64]). When stratified by method, firearm suicides had the strongest association with county poverty concentration (aIRR, 1.87; 95% CI, 1.41-2.49) in counties with 20% or higher poverty concentration compared with counties with 0% to 4.9% poverty concentration.Conclusions and relevanceThe findings suggest that higher county-level poverty concentration is associated with increased suicide rates among youths aged 5 to 19 years. These findings may guide research into upstream risk factors associated with pediatric suicide to inform suicide prevention efforts.

Project description:Importance:Progress against premature death due to noncommunicable chronic disease (NCD) has stagnated. In the United States, county-level variation in NCD premature mortality has widened, which has impeded progress toward mortality reduction for the World Health Organization (WHO) 25 × 25 target. Objectives:To estimate variations in county-level NCD premature mortality, to investigate factors associated with mortality, and to present the progress toward achieving the WHO 25 × 25 target by analyzing the trends in mortality. Design, Setting, and Participants:This cross-sectional study focused on NCD premature mortality and its factors from 3109 counties using US mortality data for cause of death from the Centers for Disease Control and Prevention WONDER databases and county-level characteristics data from multiple databases. Data were collected from January 1, 1999, through December 31, 2017, and analyzed from April 1 through October 28, 2019. Exposures:County-level factors, including demographic composition, socioeconomic features, health care environment, and population health status. Main Outcomes and Measures:Variations in county-level, age-adjusted NCD mortality in the US residents aged 25 to 64 years and associations between mortality and the 4 sets of county-level factors. Results:A total of 6 794 434 deaths due to NCD were recorded during the study period (50.58% women; 16.49% aged 65 years or older). Mortality decreased by 4.30 (95% CI, -4.54 to -4.08) deaths per 100 000 person-years annually from 1999 to 2010 (P < .001) and decreased annually at a rate of 0.90 (95% CI, -1.13 to -0.73) deaths per 100 000 person-years annually from 2010 to 2017 (P < .001). Mortality in the county with the highest mortality was 10.40 times as high as that in the county with the lowest mortality (615.40 vs 59.20 per 100 000 population) in 2017. Geographic inequality was decomposed by between-state and within-state differences, and within-state differences accounted for most inequality (57.10% in 2017). County-level factors were associated with 71.83% variation in NCD mortality. Association with intercounty mortality was 19.51% for demographic features, 23.34% for socioeconomic composition, 16.40% for health care environment, and 40.75% for health-status characteristics. Conclusions and Relevance:Given the stagnated trend of decline and increasing variations in NCD premature mortality, these findings suggest that the WHO 25 × 25 target appears to be unattainable, which may be related to broad failure by United Nations members to follow through on commitments of reducing socioeconomic inequalities. The increasing inequalities in mortality are alarming and warrant expanded multisectoral efforts to ameliorate socioeconomic disparities.

Project description:ObjectiveTo determine which county-level social, economic, demographic, epidemiologic and access to care factors are associated with Latino/non-Latino White disparities in prevalence of diagnosed HIV infection.Methods and findingsWe used 2016 county-level prevalence rates of diagnosed HIV infection rates for Latinos and non-Latino Whites obtained from the National HIV Surveillance System and factors obtained from multiple publicly available datasets. We used mixed effects Poisson modeling of observed HIV prevalence at the county-level to identify county-level factors that explained homogeneous effects across race/ethnicity and differential effects for Latinos and NL-Whites. Overall, the median Latinos disparity in HIV prevalence is 2.4; 94% of the counties have higher rates for Latinos than non-Latinos, and one-quarter of the counties' disparities exceeded 10. Of the 41 county-level factors examined, 24 showed significant effect modification when examined individually. In multi-variable modeling, 11 county-level factors were found that significantly affected disparities. Factors that increased disparity with higher, compared to lower values included proportion of HIV diagnoses due to injection drug use, percent Latino living in poverty, percent not English proficient, and percent Puerto Rican. Latino disparities increased with decreasing percent severe housing, drug overdose mortality rate, percent rural, female prevalence rate, social association rate, percent change in Latino population, and Latino to NL-White proportion of the population. These factors while significant had minimal effects on diminishing disparity, but did substantially reduce the variance in disparity rates.ConclusionsLarge differences in HIV prevalence rates persist across almost all counties even after controlling for county-level factors. Counties that are more rural, have fewer Latinos, or have lower NL-White prevalence rates tend to have higher disparities. There is also higher disparity when community risk is low.

Project description:Importance:Prior studies of dietary trends among US youth have evaluated major macronutrients or only a few foods or have used older data. Objective:To characterize trends in diet quality among US youth. Design, Setting, and Participants:Serial cross-sectional investigation using 24-hour dietary recalls from youth aged 2 to 19 years from 9 National Health and Nutrition Examination Survey (NHANES) cycles (1999-2016). Exposures:Calendar year and population sociodemographic characteristics. Main Outcomes and Measures:The primary outcomes were the survey-weighted, energy-adjusted mean consumption of dietary components and proportion meeting targets of the American Heart Association (AHA) 2020 continuous diet score (range, 0-50; based on total fruits and vegetables, whole grains, fish and shellfish, sugar-sweetened beverages, and sodium). Additional outcomes were the AHA secondary score (range, 0-80; adding nuts, seeds, and legumes; processed meat; and saturated fat) and Healthy Eating Index (HEI) 2015 score (range, 0-100). Poor diet was defined as less than 40% adherence (scores, <20 for primary and <32 for secondary AHA scores); intermediate as 40% to 79.9% adherence (scores, 20-39.9 and 32-63.9, respectively); and ideal, as at least 80% adherence (scores, ?40 and ?64, respectively). Higher diet scores indicate better diet quality; a minimal clinically important difference has not been quantified. Results:Of 31?420 youth aged 2 to 19 years included, the mean age was 10.6 years; 49.1% were female. From 1999 to 2016, the estimated AHA primary diet score significantly increased from 14.8 (95% CI, 14.1-15.4) to 18.8 (95% CI, 18.1-19.6) (27.0% improvement), the estimated AHA secondary diet score from 29.2 (95% CI, 28.1-30.4) to 33.0 (95% CI, 32.0-33.9) (13.0% improvement), and the estimated HEI-2015 score from 44.6 (95% CI, 43.5-45.8) to 49.6 (95% CI, 48.5-50.8) (11.2% improvement) (P?<?.001 for trend for each). Based on the AHA primary diet score, the estimated proportion of youth with poor diets significantly declined from 76.8% (95% CI, 72.9%-80.2%) to 56.1% (95% CI, 51.4%-60.7%) and with intermediate diets significantly increased from 23.2% (95% CI, 19.8%-26.9%) to 43.7% (95% CI, 39.1%-48.3%) (P?<?.001 for trend for each). The estimated proportion meeting ideal quality significantly increased but remained low, from 0.07% (95% CI, 0.01%-0.49%) to 0.25% (95% CI, 0.10%-0.62%) (P?=?.03 for trend). Persistent dietary variations were identified across multiple sociodemographic groups. The estimated proportion of youth with a poor diet in 2015-2016 was 39.8% (95% CI, 35.1%-44.5%) for ages 2 to 5 years (unweighted n?=?666), 52.5% (95% CI, 46.4%-58.5%) for ages 6 to 11 years (unweighted n?=?1040), and 66.6% (95% CI, 61.4%-71.4%) for ages 12 to 19 years (unweighted n?=?1195), with persistent differences across levels of parental education, household income, and household food security status. Conclusions and Relevance:Based on serial NHANES surveys from 1999 to 2016, the estimated overall diet quality of US youth showed modest improvement, but more than half of youth still had poor-quality diets.

Dataset Information

Contextual Factors Associated With County-Level Suicide Rates in the United States, 1999 to 2016.

Importance

Objectives

Design, setting, and participants

Exposure

Main outcomes and measures

Results

Publications

Contextual Factors Associated With County-Level Suicide Rates in the United States, 1999 to 2016.

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