Dataset Information

Trends in Mortality Due to Cancer in the United States by Age and County-Level Income, 1999-2015.

ABSTRACT: Disparities in cancer mortality by county-level income have increased. It is unclear whether these widening disparities have affected older and younger adults equally. National death certificate data were utilized to ascertain cancer deaths during 1999-2015. Average annual percent changes in mortality rates and mortality rate ratios (RRs) were estimated by county-level income quintile and age (25-64 vs ?65 years). Among 25- to 64-year-olds, cancer mortality rates were 30% higher (RR?=?1.30, 95% confidence interval [CI] = 1.29 to 1.31) in the lowest-vs the highest-income counties in 1999-2001 and 56% higher (RR?=?1.56, 95% CI = 1.55 to 1.57) in 2013-2015; the disparities among those 65 years and older were smaller but also widened over time (RR1999-2001 = 1.04, 95% CI = 1.03 to 1.05; RR2013-2015 = 1.14, 95% CI = 1.13 to 1.14). Widening disparities occurred across cancer sites. If all counties had the mortality rates of the highest-income counties, 21.5% of cancer deaths among 25- to 64-year-olds and 7.3% of cancer deaths in those 65 years and older would have been avoided in 2015. These results highlight an ongoing need for equity-focused interventions, particularly among younger adults.

SUBMITTER: Withrow DR

PROVIDER: S-EPMC6695317 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Publications

Trends in Mortality Due to Cancer in the United States by Age and County-Level Income, 1999-2015.

Withrow Diana R DR Berrington de González Amy A Spillane Susan S Freedman Neal D ND Best Ana F AF Chen Yingxi Y Shiels Meredith S MS

Journal of the National Cancer Institute 20190801 8

Disparities in cancer mortality by county-level income have increased. It is unclear whether these widening disparities have affected older and younger adults equally. National death certificate data were utilized to ascertain cancer deaths during 1999-2015. Average annual percent changes in mortality rates and mortality rate ratios (RRs) were estimated by county-level income quintile and age (25-64 vs ≥65 years). Among 25- to 64-year-olds, cancer mortality rates were 30% higher (RR = 1.30, 95% ...[more]

PMID: 31199459

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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:BackgroundCounties are the smallest unit for which mortality data are routinely available, allowing consistent and comparable long-term analysis of trends in health disparities. Average life expectancy has steadily increased in the United States but there is limited information on long-term mortality trends in the US counties This study aimed to investigate trends in county mortality and cross-county mortality disparities, including the contributions of specific diseases to county level mortality trends.Methods and findingsWe used mortality statistics (from the National Center for Health Statistics [NCHS]) and population (from the US Census) to estimate sex-specific life expectancy for US counties for every year between 1961 and 1999. Data for analyses in subsequent years were not provided to us by the NCHS. We calculated different metrics of cross-county mortality disparity, and also grouped counties on the basis of whether their mortality changed favorably or unfavorably relative to the national average. We estimated the probability of death from specific diseases for counties with above- or below-average mortality performance. We simulated the effect of cross-county migration on each county's life expectancy using a time-based simulation model. Between 1961 and 1999, the standard deviation (SD) of life expectancy across US counties was at its lowest in 1983, at 1.9 and 1.4 y for men and women, respectively. Cross-county life expectancy SD increased to 2.3 and 1.7 y in 1999. Between 1961 and 1983 no counties had a statistically significant increase in mortality; the major cause of mortality decline for both sexes was reduction in cardiovascular mortality. From 1983 to 1999, life expectancy declined significantly in 11 counties for men (by 1.3 y) and in 180 counties for women (by 1.3 y); another 48 (men) and 783 (women) counties had nonsignificant life expectancy decline. Life expectancy decline in both sexes was caused by increased mortality from lung cancer, chronic obstructive pulmonary disease (COPD), diabetes, and a range of other noncommunicable diseases, which were no longer compensated for by the decline in cardiovascular mortality. Higher HIV/AIDS and homicide deaths also contributed substantially to life expectancy decline for men, but not for women. Alternative specifications of the effects of migration showed that the rise in cross-county life expectancy SD was unlikely to be caused by migration.ConclusionsThere was a steady increase in mortality inequality across the US counties between 1983 and 1999, resulting from stagnation or increase in mortality among the worst-off segment of the population. Female mortality increased in a large number of counties, primarily because of chronic diseases related to smoking, overweight and obesity, and high blood pressure.

Project description:ImportanceUnderstanding geographic and community-level factors associated with suicide can inform targeted suicide prevention efforts.ObjectivesTo estimate suicide rates and trajectories, assess associated county-level contextual factors, and explore variation across the rural-urban continuum.Design, setting, and participantsThis 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.ExposureCounty of residence.Main outcomes and measuresThree-year county suicide rates during an 18-year period stratified by rural-urban location.ResultsBetween 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 < .001; large metropolitan, 1999-2001: 1.208; 95% CI, 1.149-1.270; P < .001; rural, 2014-2016: IRR, 1.121; 95% CI, 1.032-1.219; P = .01; large metropolitan, 2014-2016: IRR, 0.942; 95% CI, 0.887-1.001; P = .06). The presence of more gun shops was associated with an increase in county-level suicide rates in all county types except the most rural (rural: IRR, 1.001; 95% CI, 0.999-1.004; P = .40; micropolitan: IRR, 1.005; 95% CI, 1.002-1.007; P < .001; small metropolitan: IRR, 1.010; 95% CI, 1.006-1.014; P < .001; large metropolitan: IRR, 1.012; 95% CI, 1.006-1.018; P < .001). High social capital was associated with lower suicide rates than low social capital (IRR, 0.917; 95% CI, 0.891-0.943; P < .001). High social fragmentation, an increasing percentage of the population without health insurance, and an increasing percentage of veterans in a county were associated with higher suicide rates (high social fragmentation: IRR, 1.077; 95% CI, 1.050-1.103; P < .001; percentage of population without health insurance: IRR, 1.005; 95% CI, 1.004-1.006; P < .001; percentage of veterans: IRR, 1.025; 95% CI, 1.021-1.028; P < .001).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.

Dataset Information

Trends in Mortality Due to Cancer in the United States by Age and County-Level Income, 1999-2015.

Publications

Trends in Mortality Due to Cancer in the United States by Age and County-Level Income, 1999-2015.

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