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1.
Am J Public Health ; 111(10): 1865-1873, 2021 10.
Artículo en Inglés | MEDLINE | ID: mdl-34623882

RESUMEN

For nearly 2 decades, the Community Health Status Indicators tool reliably supplied communities with standardized, local health data and the capacity for peer-community comparisons. At the same time, it created a large community of users who shared learning in addressing local health needs. The tool survived a transition from the Health Resources and Services Administration to the Centers for Disease Control and Prevention before being shuttered in 2017. While new community data tools have come online, nothing has replaced Community Health Status Indicators, and many stakeholders continue to clamor for something new that will enable local health needs assessments, peer comparisons, and creation of a community of solutions. The National Committee on Vital and Health Statistics heard from many stakeholders that they still need a replacement data source. (Am J Public Health. 2021;111(10):1865-1873. https://doi.org/10.2105/AJPH.2021.306437).


Asunto(s)
Servicios de Salud Comunitaria/normas , Indicadores de Salud , Administración en Salud Pública/normas , Planificación en Salud/organización & administración , Apoyo a la Planificación en Salud/normas , Humanos , Estados Unidos
2.
Prev Chronic Dis ; 15: E11, 2018 01 25.
Artículo en Inglés | MEDLINE | ID: mdl-29369759

RESUMEN

Compared with people in other developed countries, Americans live shorter lives, have more disease and disability, and lag on most population health measures. Recent research suggests that this poor comparative performance is primarily driven by profound local place-based disparities. Several initiatives successfully used sub-county life expectancy estimates to identify geographic disparities, generate widespread interest, and catalyze multisector actions. To explore the feasibility of scaling these efforts, the Centers for Disease Control and Prevention and the Council of State and Territorial Epidemiologists initiated a multiphase project - the Sub-County Assessment of Life Expectancy. Phase I participants reviewed the literature, assessed and identified appropriate tools, calculated locally relevant estimates, and developed methodological guidance. Phase I results suggest that most state and local health departments will be able to calculate actionable sub-county life expectancy estimates despite varying resources, expertise, and population sizes, densities, and geographies. To accelerate widespread scaling, we describe several successful case examples, identify user-friendly validated tools, and provide practical tips that resulted from lessons learned.


Asunto(s)
Equidad en Salud , Esperanza de Vida , Femenino , Geografía Médica , Disparidades en el Estado de Salud , Humanos , Masculino , Distribución por Sexo , Estados Unidos/epidemiología
3.
Am J Prev Med ; 46(4): 413-22, 2014 Apr.
Artículo en Inglés | MEDLINE | ID: mdl-24650845

RESUMEN

CONTEXT: Exposure to elevated concentrations of traffic-related air pollutants in the near-road environment is associated with numerous adverse human health effects, including childhood cancer, which has been increasing since 1975. Results of individual epidemiologic studies have been inconsistent. Therefore, a meta-analysis was performed to examine the association between residential traffic exposure and childhood cancer. EVIDENCE ACQUISITION: Studies published between January 1980 and July 2011 were retrieved from a systematic search of 18 bibliographic databases. Nine studies meeting the inclusion criteria were identified. Weighted summary ORs were calculated using a random effects model for outcomes with four or more studies. Subgroup and sensitivity analyses were performed. EVIDENCE SYNTHESIS: Childhood leukemia was positively associated (summary OR=1.53, 95% CI=1.12, 2.10) with residential traffic exposure among seven studies using a postnatal exposure window (e.g., childhood period or diagnosis address) and there was no association (summary OR=0.92, 95% CI=0.78, 1.09) among four studies using a prenatal exposure window (e.g., pregnancy period or birth address). There were too few studies to analyze other childhood cancer outcomes. CONCLUSIONS: Current evidence suggests that childhood leukemia is associated with residential traffic exposure during the postnatal period, but not during the prenatal period. Additional well-designed epidemiologic studies that use complete residential history to estimate traffic exposure, examine leukemia subtypes, and control for potential confounding factors are needed to confirm these findings. As many people reside near busy roads, especially in urban areas, precautionary public health messages and interventions designed to reduce population exposure to traffic might be warranted.


Asunto(s)
Contaminantes Atmosféricos/toxicidad , Exposición a Riesgos Ambientales/efectos adversos , Leucemia/epidemiología , Vehículos a Motor , Adolescente , Niño , Preescolar , Femenino , Vivienda , Humanos , Lactante , Leucemia/inducido químicamente , Embarazo , Efectos Tardíos de la Exposición Prenatal/epidemiología , Medición de Riesgo
4.
J Environ Health ; 70(8): 33-41, 55-6, 2008 Apr.
Artículo en Inglés | MEDLINE | ID: mdl-18468221

RESUMEN

This review presents epidemiologic evidence of adverse health effects associated with residential proximity to traffic. Of the 29 peer-reviewed studies that met the authors' defined criteria, 25 reported statistically significant associations with at least one adverse health effect across a broad range of exposure metrics and diverse geographical locations. Specific pollutants contributing to the associated health effects could not, however, be identified, and uncertainties existed because of the lack of individual exposure assessments that could rule out confounding by other factors. Improved exposure assessments and future studies should be considered for better identification of contributing pollutants and mechanisms of action. In the meantime, additional policies, additional regulations, and improved land use and urban planning can better protect the public and limit exposure, especially for vulnerable populations such as pregnant women, children, and the elderly.


Asunto(s)
Contaminantes Atmosféricos/efectos adversos , Características de la Residencia , Enfermedades Respiratorias/epidemiología , Emisiones de Vehículos , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Niño , Preescolar , Monitoreo del Ambiente/métodos , Monitoreo Epidemiológico , Humanos , Recién Nacido de Bajo Peso , Recién Nacido , Persona de Mediana Edad , Mortalidad , Neoplasias/epidemiología , Política Pública
5.
Mil Med ; 168(11): 941-7, 2003 Nov.
Artículo en Inglés | MEDLINE | ID: mdl-14680052

RESUMEN

OBJECTIVE: This study evaluated the association between military service and health-related quality of life (HRQOL), using a large, population-based sample of U.S. adults. METHODS: Participants in the 2000 Behavioral Risk Factor Surveillance System were characterized as active duty personnel (N = 1,163), reserves (N = 1,055], veterans (N = 22,558), or no military service (N = 141,620). HRQOL was described by sex and military status. Logistic regression was used to calculate sex-specific adjusted odds ratios. RESULTS: Active duty men were more likely than men without military service to report 14 or more days of activity limitation, pain, and not enough rest in the past 30 days. Reserve personnel reported better overall HRQOL than nonmilitary participants, and no difference in HRQOL was observed between veterans and persons with no military service. CONCLUSIONS: Recommendations are made to monitor HRQOL of active duty and reserve personnel over time and to include HRQOL measures in military-based surveys of active duty troops.


Asunto(s)
Personal Militar/estadística & datos numéricos , Calidad de la Atención de Salud , Adolescente , Adulto , Distribución por Edad , Anciano , Anciano de 80 o más Años , Intervalos de Confianza , Escolaridad , Femenino , Estado de Salud , Humanos , Renta/estadística & datos numéricos , Modelos Logísticos , Masculino , Persona de Mediana Edad , Análisis Multivariante , Oportunidad Relativa , Grupos de Población , Factores de Riesgo , Fumar/epidemiología , Estados Unidos/epidemiología , Veteranos/estadística & datos numéricos
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