Sandeep C. Kulkarni

The reversal of fortunes: trends in county mortality and cross-county mortality disparities in the United States.

Background Counties 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 Findings We 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 countys 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. Conclusions There 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.

The promise of prevention: the effects of four preventable risk factors on national life expectancy and life expectancy disparities by race and county in the United States.

Majid Ezzati and colleagues examine the contribution of a set of risk factors (smoking, high blood pressure, elevated blood glucose, and adiposity) to socioeconomic disparities in life expectancy in the US population.

Priority setting for health interventions in Mexico's System of Social Protection in Health

Explicit priority setting presents Mexico with the opportunity to match the pressure and complexity of an advancing epidemiological transition with evidence-based policies driven by a fundamental concern for how to make the best use of scarce resources to improve population health. The Mexican priority-setting experience describes how standardised analytical approaches to decision making, mainly burden of disease and cost-effectiveness analyses, combine with other criteria--eg, being responsive to the legitimate non-health expectations of patients and ensuring fair financing across households--to design and implement a set of three differentiated health intervention packages. This process is a key element of a wider set of reform components aimed at extending health insurance, especially to the poor. The most relevant policy implications include lessons on the use of available and proven analytical tools to set national health priorities, the usefulness of priority-setting results to guide long-term capacity development, the importance of favouring an institutionalised approach to cost-effectiveness analysis, and the need for local technical capacity strengthening as an essential step to balance health-maximising arguments and other non-health criteria in a transparent and systematic process.

Falling behind: life expectancy in US counties from 2000 to 2007 in an international context

BackgroundThe United States health care debate has focused on the nations uniquely high rates of lack of insurance and poor health outcomes relative to other high-income countries. Large disparities in health outcomes are well-documented in the US, but the most recent assessment of county disparities in mortality is from 1999. It is critical to tracking progress of health reform legislation to have an up-to-date assessment of disparities in life expectancy across counties. US disparities can be seen more clearly in the context of how progress in each county compares to international trends.MethodsWe use newly released mortality data by age, sex, and county for the US from 2000 to 2007 to compute life tables separately for each sex, for all races combined, for whites, and for blacks. We propose, validate, and apply novel methods to estimate recent life tables for small areas to generate up-to-date estimates. Life expectancy rates and changes in life expectancy for counties are compared to the life expectancies across nations in 2000 and 2007. We calculate the number of calendar years behind each county is in 2000 and 2007 compared to an international life expectancy time series.ResultsAcross US counties, life expectancy in 2007 ranged from 65.9 to 81.1 years for men and 73.5 to 86.0 years for women. When compared against a time series of life expectancy in the 10 nations with the lowest mortality, US counties range from being 15 calendar years ahead to over 50 calendar years behind for men and 16 calendar years ahead to over 50 calendar years behind for women. County life expectancy for black men ranges from 59.4 to 77.2 years, with counties ranging from seven to over 50 calendar years behind the international frontier; for black women, the range is 69.6 to 82.6 years, with counties ranging from eight to over 50 calendar years behind. Between 2000 and 2007, 80% (men) and 91% (women) of American counties fell in standing against this international life expectancy standard.ConclusionsThe US has extremely large geographic and racial disparities, with some communities having life expectancies already well behind those of the best-performing nations. At the same time, relative performance for most communities continues to drop. Efforts to address these issues will need to tackle the leading preventable causes of death.

Understanding the Coronary Heart Disease Versus Total Cardiovascular Mortality Paradox A Method to Enhance the Comparability of Cardiovascular Death Statistics in the United States

Background— Coronary heart disease (CHD) represents the largest share of cardiovascular disease in the United States, but there are conspicuous discrepancies between CHD and total cardiovascular death rates across the states, possibly due in part to variations in physician assignment of causes of death. Our aim was to identify exogenous individual- and community-level predictors of cause-of-death assignment and variability and to use these predictors to improve the comparability of CHD mortality estimates across states. Methods and Results— We performed a multinomial logistic regression analysis to estimate the effect of individual- and community-level factors on the likelihood of a death being certified as 1 of 3 ill-defined clusters (general atherosclerosis and unspecified heart disease, heart failure, and cardiac arrest) relative to being certified as CHD. The individual-level variables were the decedent’s race, sex, age, education, and place of death; the community-level variable was the number of cardiologists per capita. We used the model to estimate state-level CHD rates that are standardized with regard to the levels of individual- and community-level determinants of cause-of-death assignment. Decedents who died in hospitals and in counties with more cardiologists per capita were more likely to be assigned to CHD than to the ill-defined categories, as were white males relative to other race-sex combinations. Adjustment for these factors resulted in substantially improved correlation between death rates for CHD and all cardiovascular causes. Increases in CHD death rates across states after adjustment for external predictors of cause-of-death assignment ranged from 2% (North Dakota) to 72% (Washington, DC); New York had a decrease (1%) in CHD death rates after adjustment. Nationally, CHD death rates increased 10% for males and 15% for females. The total number of deaths in 2001 attributed to CHD in patients over 30 years of age rose from 433 625 to 489 836 after adjustment. Conclusions— Greater presence of medical knowledge at the time of death, reflected by place of death and cardiologists per capita, reduces the use of the ill-defined cardiovascular clusters. Racial and gender effects on CHD assignment may reflect disparities in access to care and quality of care. By adjusting for differentials in these parameters, a comparable and consistent set of CHD mortality estimates can be created. The role of the exogenous predictors in validity and comparability of cause-of-death statistics should be confirmed in carefully designed validation autopsy studies.

Definición de prioridades para las intervenciones de salud en el Sistema de Protección Social en Salud de México

La definicion explicita de prioridades en intervenciones de salud representa una oportunidad para Mexico de equilibrar la presion y la complejidad de una transicion epidemiologica avanzada, con politicas basadas en evidencias generadas por la inquietud de como optimizar el uso de los recursos escasos para mejorar la salud de la poblacion. La experiencia mexicana en la definicion de prioridades describe como los enfoques analiticos estandarizados en la toma de decisiones, principalmente los de analisis de la carga de la enfermedad y de costo-efectividad, se combinan con otros criterios -tales como dar respuesta a las expectativas legitimas no medicas de los pacientes y asegurar un financiamiento justo para los hogares-, para disenar e implementar un grupo de tres paquetes diferenciados de intervenciones de salud. Este es un proceso clave dentro de un conjunto mas amplio de elementos de reforma dirigidos a extender el aseguramiento en salud, especialmente a los pobres. Las implicaciones mas relevantes en el ambito de politicas publicas incluyen lecciones sobre el uso de las herramientas analiticas disponibles y probadas para definir prioridades nacionales de salud; la utilidad de resultados que definan prioridades para guiar el desarrollo de capacidades a largo plazo; la importancia de favorecer un enfoque para institucionalizar el analisis ex-ante de costo-efectividad; y la necesidad del fortalecimiento de la capacidad tecnica local como un elemento esencial para equilibrar los argumentos sobre maximizacion de la salud con criterios no relacionados con la salud en el marco de un ejercicio sistematico y transparente.