Showing papers by "Christopher J L Murray published in 2012"

Modeling causes of death: an integrated approach using CODEm

Abstract: Data on causes of death by age and sex are a critical input into health decision-making Priority setting in public health should be informed not only by the current magnitude of health problems but by trends in them However, cause of death data are often not available or are subject to substantial problems of comparability We propose five general principles for cause of death model development, validation, and reporting We detail a specific implementation of these principles that is embodied in an analytical tool - the Cause of Death Ensemble model (CODEm) - which explores a large variety of possible models to estimate trends in causes of death Possible models are identified using a covariate selection algorithm that yields many plausible combinations of covariates, which are then run through four model classes The model classes include mixed effects linear models and spatial-temporal Gaussian Process Regression models for cause fractions and death rates All models for each cause of death are then assessed using out-of-sample predictive validity and combined into an ensemble with optimal out-of-sample predictive performance Ensemble models for cause of death estimation outperform any single component model in tests of root mean square error, frequency of predicting correct temporal trends, and achieving 95% coverage of the prediction interval We present detailed results for CODEm applied to maternal mortality and summary results for several other causes of death, including cardiovascular disease and several cancers CODEm produces better estimates of cause of death trends than previous methods and is less susceptible to bias in model specification We demonstrate the utility of CODEm for the estimation of several major causes of death

Common values in assessing health outcomes from disease and injury: Disability weights measurement study for the Global Burden of Disease Study 2010

Abstract: NOTE: This article is free to read on the journal website provided you register (which is free). BACKGROUND Measurement of the global burden of disease with disability-adjusted life-years (DALYs) requires disability weights that quantify health losses for all non-fatal consequences of disease and injury. There has been extensive debate about a range of conceptual and methodological issues concerning the definition and measurement of these weights. Our primary objective was a comprehensive re-estimation of disability weights for the Global Burden of Disease Study 2010 through a large-scale empirical investigation in which judgments about health losses associated with many causes of disease and injury were elicited from the general public in diverse communities through a new, standardised approach. METHODS We surveyed respondents in two ways: household surveys of adults aged 18 years or older (face-to-face interviews in Bangladesh, Indonesia, Peru, and Tanzania; telephone interviews in the USA) between Oct 28, 2009, and June 23, 2010; and an open-access web-based survey between July 26, 2010, and May 16, 2011. The surveys used paired comparison questions, in which respondents considered two hypothetical individuals with different, randomly selected health states and indicated which person they regarded as healthier. The web survey added questions about population health equivalence, which compared the overall health benefits of different life-saving or disease-prevention programmes. We analysed paired comparison responses with probit regression analysis on all 220 unique states in the study. We used results from the population health equivalence responses to anchor the results from the paired comparisons on the disability weight scale from 0 (implying no loss of health) to 1 (implying a health loss equivalent to death). Additionally, we compared new disability weights with those used in WHO's most recent update of the Global Burden of Disease Study for 2004. FINDINGS 13,902 individuals participated in household surveys and 16,328 in the web survey. Analysis of paired comparison responses indicated a high degree of consistency across surveys: correlations between individual survey results and results from analysis of the pooled dataset were 0·9 or higher in all surveys except in Bangladesh (r=0·75). Most of the 220 disability weights were located on the mild end of the severity scale, with 58 (26%) having weights below 0·05. Five (11%) states had weights below 0·01, such as mild anaemia, mild hearing or vision loss, and secondary infertility. The health states with the highest disability weights were acute schizophrenia (0·76) and severe multiple sclerosis (0·71). We identified a broad pattern of agreement between the old and new weights (r=0·70), particularly in the moderate-to-severe range. However, in the mild range below 0·2, many states had significantly lower weights in our study than previously. INTERPRETATION This study represents the most extensive empirical effort as yet to measure disability weights. By contrast with the popular hypothesis that disability assessments vary widely across samples with different cultural environments, we have reported strong evidence of highly consistent results.

The Global Financial Crisis Has Led To A Slowdown In Growth Of Funding To Improve Health In Many Developing Countries

Abstract: How has funding to developing countries for health improvement changed in the wake of the global financial crisis? The question is vital for policy making, planning, and advocacy purposes in donor and recipient countries alike We measured the total amount of financial and in-kind assistance that flowed from both public and private channels to improve health in developing countries during the period 1990–2011 The data for the years 1990–2009 reflect disbursements, while the numbers for 2010 and 2011 are preliminary estimates Development assistance for health continued to grow in 2011, but the rate of growth was low We estimate that assistance for health grew by 4 percent each year from 2009 to 2011, reaching a total of $2773 billion This growth was largely driven by the World Bank’s International Bank for Reconstruction and Development and appeared to be a deliberate strategy in response to the global economic crisis Assistance for health from bilateral agencies grew by only 4 percent, or $44408 mi

Developing a comprehensive time series of GDP per capita for 210 countries from 1950 to 2015

Abstract: Income has been extensively studied and utilized as a determinant of health. There are several sources of income expressed as gross domestic product (GDP) per capita, but there are no time series that are complete for the years between 1950 and 2015 for the 210 countries for which data exist. It is in the interest of population health research to establish a global time series that is complete from 1950 to 2015. We collected GDP per capita estimates expressed in either constant US dollar terms or international dollar terms (corrected for purchasing power parity) from seven sources. We applied several stages of models, including ordinary least-squares regressions and mixed effects models, to complete each of the seven source series from 1950 to 2015. The three US dollar and four international dollar series were each averaged to produce two new GDP per capita series. Nine complete series from 1950 to 2015 for 210 countries are available for use. These series can serve various analytical purposes and can illustrate myriad economic trends and features. The derivation of the two new series allows for researchers to avoid any series-specific biases that may exist. The modeling approach used is flexible and will allow for yearly updating as new estimates are produced by the source series. GDP per capita is a necessary tool in population health research, and our development and implementation of a new method has allowed for the most comprehensive known time series to date.

Altitude, life expectancy and mortality from ischaemic heart disease, stroke, COPD and cancers: national population-based analysis of US counties

Abstract: Background There is a substantial variation in life expectancy across US counties, primarily owing to differentials in chronic diseases. The authors9 aim was to examine the association of life expectancy and mortality from selected diseases with altitude. Methods The authors used data from the National Elevation Dataset, National Center for Heath Statistics and US Census. The authors analysed the crude association of mean county altitude with life expectancy and mortality from ischaemic heart disease (IHD), stroke, chronic obstructive pulmonary disease (COPD) and cancers, and adjusted the associations for socio-demographic factors, migration, average annual solar radiation and cumulative exposure to smoking in multivariable regressions. Results Counties above 1500 m had longer life expectancies than those within 100 m of sea level by 1.2–3.6 years for men and 0.5–2.5 years for women. The association between altitude and life expectancy became non-significant for women and non-significant or negative for men in multivariate analysis. After adjustment, altitude had a beneficial association with IHD mortality and harmful association with COPD, with a dose–response relationship. IHD mortality above 1000 m was 4–14 per 10 000 people lower than within 100 m of sea level; COPD mortality was higher by 3–4 per 10 000. The adjusted associations for stroke and cancers were not statistically significant. Conclusions Living at higher altitude may have a protective effect on IHD and a harmful effect on COPD. At least in part due to these two opposing effects, living at higher altitude appears to have no net effect on life expectancy.

Assessing the global burden of ischemic heart disease, part 2: analytic methods and estimates of the global epidemiology of ischemic heart disease in 2010.

Abstract: Background Ischemic heart disease (IHD) is the leading cause of death worldwide. The Global Burden of Diseases, Injuries and Risk Factors (GBD) 2010 Study estimated IHD mortality and disability burden for 21 world regions for the years 1990 to 2010. Methods Data sources for GBD IHD epidemiology estimates were mortality surveillance, verbal autopsy, and vital registration data (for IHD mortality) and systematic review of IHD epidemiology literature published from 1980 to 2008 (for nonfatal IHD outcomes). An estimation and validation process led to an ensemble model of IHD mortality by country for all 21 world regions, adjusted for country-level covariates. Disease models were developed for the nonfatal sequelae of IHD: myocardial infarction, stable angina pectoris, and ischemic heart failure. Results Country-level covariates including metabolic and nutritional risk factors, education, war, and annual income per capita contributed to the ensemble model for the analysis of IHD death. In the acute myocardial infarction model, inclusion of troponin in the diagnostic criteria of studies published after the year 2000 was associated with a 50% higher incidence. Self-reported diagnosis of angina significantly overestimated stable angina prevalence compared with "definite" angina elicited by the Rose angina questionnaire. For 2010, Eastern Europe and Central Asia had the highest rates of IHD death and the Asia Pacific High-Income, East Asia, Latin American Andean, and Sub-Saharan Africa regions had the lowest. Conclusions Global and regional IHD epidemiology estimates are needed for estimating the worldwide burden of IHD. Using descriptive meta-analysis tools, the GBD 2010 standardized and pooled international data by adjusting for region-level mortality and risk factor data, as well as study-level diagnostic method. Analyses maximized internal consistency, generalizability, and adjustment for known sources of bias. The GBD IHD analysis, nonetheless, highlights the need for improved IHD epidemiology surveillance in many regions and the need for uniform diagnostic standards.

Disentangling the effects of risk factors and clinical care on subnational variation in early neonatal mortality in the United States

Abstract: Objective Between 1990 and 2010, the U.S ranking in neonatal mortality slipped from 29th to 45th among countries globally. Substantial subnational variation in newborn mortality also exists. Our objective is to measure the extent to which trends and subnational variation in early neonatal mortality reflect differences in the prevalence of risk factors (gestational age and birth weight) compared to differences in clinical care. Methods Observational study using linked birth and death data for all births in the United States between 1996 and 2006. We examined health service area (HSA) level variation in the expected early neonatal mortality rate, based on gestational age (GA) and birth-weight (BW), and GA-BW adjusted mortality as a proxy for clinical care. We analyzed the relationship between selected health system indicators and GA-BW-adjusted mortality. Results The early neonatal death (ENND) rate declined 12% between 1996 and 2006 (2.39 to 2.10 per 1000 live births). This occurred despite increases in risk factor prevalence. There was significant HSA-level variation in the expected ENND rate (Rate Ratio: 0.73–1.47) and the GA-BW adjusted rate (Rate ratio: 0.63–1.68). Accounting for preterm volume (defined as <34 weeks), the number of neonatologist and NICU beds, 25.2% and 58.7% of the HSA-level variance in outcomes was explained among all births and very low birth weight babies, respectively. Conclusion Improvements in mortality could be realized through the expansion or reallocation of clinical neonatal resources, particularly in HSAs with a high volume of preterm births; however, prevention of preterm births and low-birth weight babies has a greater potential to improve newborn survival in the United States.