Publications (40)373.73 Total impact
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Article: GBD 2010: design, definitions, and metrics.
The Lancet 12/2013; 380(9859):2063-6. · 38.28 Impact Factor -
Article: GBD 2010: a multi-investigator collaboration for global comparative descriptive epidemiology.
The Lancet 12/2013; 380(9859):2055-8. · 38.28 Impact Factor -
Article: Improving the quality of road injury statistics by using regression models to redistribute ill-defined events.
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ABSTRACT: OBJECTIVE: To test the predictive ability of multinomial regression method in obtaining category of death distribution for cases with unknown/ill-defined mortality codes. METHODS: The authors evaluated the performance of the multinomial regression model by fitting the model to trial datasets from 2004 Mexican vital registration data. To predict category of death, the regression method makes use of explanatory variables, such as gender, age, place of crash, place of residence, education and insurance type. The authors compared the results of a full model regression with those of a reduced model that only contained gender and age as explanatory variables. For this comparison, the authors constructed two forms of data: dummy variable adjustment method and case-wise deleted method. The comparison was made through estimated area under the curve (AUC) for each outcome variable. RESULTS: The full model significantly outperformed the gender-age (reduced) model using both datasets. In the case-wise deleted method, the AUC was increased from 0.55 to 0.7 for the reduced model and from 0.64 to 0.84 for the full model. Improvement in AUC using the dummy variable adjustment method was less significant. CONCLUSIONS: To predict ill-defined categories of death, adding relevant explanatory variables to gender and age is recommended. Multiple imputations may perform even better than this model especially when significant portion of the data are missing.Injury Prevention 04/2012; · 1.39 Impact Factor -
Article: Global malaria mortality between 1980 and 2010: a systematic analysis.
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ABSTRACT: During the past decade, renewed global and national efforts to combat malaria have led to ambitious goals. We aimed to provide an accurate assessment of the levels and time trends in malaria mortality to aid assessment of progress towards these goals and the focusing of future efforts. We systematically collected all available data for malaria mortality for the period 1980-2010, correcting for misclassification bias. We developed a range of predictive models, including ensemble models, to estimate malaria mortality with uncertainty by age, sex, country, and year. We used key predictors of malaria mortality such as Plasmodium falciparum parasite prevalence, first-line antimalarial drug resistance, and vector control. We used out-of-sample predictive validity to select the final model. Global malaria deaths increased from 995,000 (95% uncertainty interval 711,000-1,412,000) in 1980 to a peak of 1,817,000 (1,430,000-2,366,000) in 2004, decreasing to 1,238,000 (929,000-1,685,000) in 2010. In Africa, malaria deaths increased from 493,000 (290,000-747,000) in 1980 to 1,613,000 (1,243,000-2,145,000) in 2004, decreasing by about 30% to 1,133,000 (848,000-1,591,000) in 2010. Outside of Africa, malaria deaths have steadily decreased from 502,000 (322,000-833,000) in 1980 to 104,000 (45,000-191,000) in 2010. We estimated more deaths in individuals aged 5 years or older than has been estimated in previous studies: 435,000 (307,000-658,000) deaths in Africa and 89,000 (33,000-177,000) deaths outside of Africa in 2010. Our findings show that the malaria mortality burden is larger than previously estimated, especially in adults. There has been a rapid decrease in malaria mortality in Africa because of the scaling up of control activities supported by international donors. Donor support, however, needs to be increased if malaria elimination and eradication and broader health and development goals are to be met. The Bill & Melinda Gates Foundation.The Lancet 02/2012; 379(9814):413-31. · 38.28 Impact Factor -
Article: Modeling causes of death: an integrated approach using CODEm.
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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.Population Health Metrics 01/2012; 10:1. · 2.11 Impact Factor -
Article: Progress towards Millennium Development Goals 4 and 5 on maternal and child mortality: an updated systematic analysis.
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ABSTRACT: With 4 years until 2015, it is essential to monitor progress towards Millennium Development Goals (MDGs) 4 and 5. Although estimates of maternal and child mortality were published in 2010, an update of estimates is timely in view of additional data sources that have become available and new methods developed. Our aim was to update previous estimates of maternal and child mortality using better data and more robust methods to provide the best available evidence for tracking progress on MDGs 4 and 5. We update the analyses of the progress towards MDGs 4 and 5 from 2010 with additional surveys, censuses, vital registration, and verbal autopsy data. For children, we estimate early neonatal (0-6 days), late neonatal (7-28 days), postneonatal (29-364 days), childhood (ages 1-4 years), and under-5 mortality. We use an improved model for estimating mortality by age under 5 years. For maternal mortality, our updated analysis includes greater than 1000 additional site-years of data. We tested a large set of alternative models for maternal mortality; we used an ensemble model based on the models with the best out-of-sample predictive validity to generate new estimates from 1990 to 2011. Under-5 deaths have continued to decline, reaching 7·2 million in 2011 of which 2·2 million were early neonatal, 0·7 million late neonatal, 2·1 million postneonatal, and 2·2 million during childhood (ages 1-4 years). Comparing rates of decline from 1990 to 2000 with 2000 to 2011 shows that 106 countries have accelerated declines in the child mortality rate in the past decade. Maternal mortality has also continued to decline from 409,100 (uncertainty interval 382,900-437,900) in 1990 to 273,500 (256,300-291,700) deaths in 2011. We estimate that 56,100 maternal deaths in 2011 were HIV-related deaths during pregnancy. Based on recent trends in developing countries, 31 countries will achieve MDG 4, 13 countries MDG 5, and nine countries will achieve both. Even though progress on reducing maternal and child mortality in most countries is accelerating, most developing countries will take many years past 2015 to achieve the targets of the MDGs 4 and 5. Similarly, although there continues to be progress on maternal mortality the pace is slow, without any overall evidence of acceleration. Immediate concerted action is needed for a large number of countries to achieve MDG 4 and MDG 5. Bill & Melinda Gates Foundation.The Lancet 09/2011; 378(9797):1139-65. · 38.28 Impact Factor -
Article: Breast and cervical cancer in 187 countries between 1980 and 2010: a systematic analysis.
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ABSTRACT: Breast and cervical cancer are important causes of mortality in women aged ≥15 years. We undertook annual age-specific assessments of breast and cervical cancer in 187 countries. We systematically collected cancer registry data on mortality and incidence, vital registration, and verbal autopsy data for the period 1980-2010. We modelled the mortality-to-incidence (MI) ratio using a hierarchical model. Vital registration and verbal autopsy were supplemented with incidence multiplied by the MI ratio to yield a comprehensive database of mortality rates. We used Gaussian process regression to develop estimates of mortality with uncertainty by age, sex, country, and year. We used out-of-sample predictive validity to select the final model. Estimates of incidence with uncertainty were also generated with mortality and MI ratios. Global breast cancer incidence increased from 641,000 (95% uncertainty intervals 610,000-750,000) cases in 1980 to 1,643,000 (1,421,000-1,782,000) cases in 2010, an annual rate of increase of 3·1%. Global cervical cancer incidence increased from 378,000 (256,000-489,000) cases per year in 1980 to 454,000 (318,000-620,000) cases per year in 2010-a 0·6% annual rate of increase. Breast cancer killed 425,000 (359,000-453,000) women in 2010, of whom 68,000 (62,000-74,000) were aged 15-49 years in developing countries. Cervical cancer death rates have been decreasing but the disease still killed 200,000 (139,000-276,000) women in 2010, of whom 46,000 (33,000-64,000) were aged 15-49 years in developing countries. We recorded pronounced variation in the trend in breast cancer mortality across regions and countries. More policy attention is needed to strengthen established health-system responses to reduce breast and cervical cancer, especially in developing countries. Susan G Komen for the Cure and the Bill & Melinda Gates Foundation.The Lancet 09/2011; 378(9801):1461-84. · 38.28 Impact Factor -
Article: Exposing misclassified HIV/AIDS deaths in South Africa.
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ABSTRACT: To quantify the deaths from human immunodeficiency virus (HIV) infection or acquired immunodeficiency syndrome (AIDS) that are misattributed to other causes in South Africa's death registration data and to adjust for this bias. Deaths in the World Health Organization's mortality database were distributed among 48 mutually exclusive causes. For each cause, age- and sex-specific global death rates were compared with the average rate among people aged 65-69, 70-74 and 75-79 years to generate "relative" global death rates. Relative rates were also computed for South Africa alone. Differences between global and South African relative death rates were used to identify the causes to which deaths from HIV/AIDS were misattributed in South Africa and quantify the HIV/AIDS deaths misattributed to each. These deaths were then reattributed to HIV/AIDS. In South Africa, deaths from HIV/AIDS are often misclassified as being caused by 14 other conditions. Whereas in 1996-2006 deaths attributed to HIV/AIDS accounted for 2.0-2.5% of all registered deaths in South Africa, our analysis shows that the true cause-specific mortality fraction rose from 19% (uncertainty range: 7-28%) to 48% (uncertainty range: 38-50%) over that period. More than 90% of HIV/AIDS deaths were found to have been misattributed to other causes during 1996-2006. Adjusting for cause of death misclassification, a simple procedure that can be carried out in any country, can improve death registration data and provide empirical estimates of HIV/AIDS deaths that may be useful in assessing estimates from demographic models.Bulletin of the World Health Organisation 04/2011; 89(4):278-85. · 4.64 Impact Factor -
Article: Management of diabetes and associated cardiovascular risk factors in seven countries: a comparison of data from national health examination surveys.
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ABSTRACT: To examine the effectiveness of the health system response to the challenge of diabetes across different settings and explore the inequalities in diabetes care that are attributable to socioeconomic factors. We used nationally representative health examination surveys from Colombia, England, the Islamic Republic of Iran, Mexico, Scotland, Thailand and the United States of America to obtain data on diagnosis, treatment and control of hyperglycaemia, arterial hypertension and hypercholesterolaemia among individuals with diabetes. Using logistic regression, we explored the socioeconomic determinants of diagnosis and effective case management. A substantial proportion of individuals with diabetes remain undiagnosed and untreated, both in developed and developing countries. The figures range from 24% of the women in Scotland and the USA to 62% of the men in Thailand. The proportion of individuals with diabetes reaching treatment targets for blood glucose, arterial blood pressure and serum cholesterol was very low, ranging from 1% of male patients in Mexico to about 12% in the United States. Income and education were not found to be significantly related to the rates of diagnosis and treatment anywhere except in Thailand, but in the three countries with available data insurance status was a strong predictor of diagnosis and effective management, especially in the United States. There are many missed opportunities to reduce the burden of diabetes through improved control of blood glucose levels and improved diagnosis and treatment of arterial hypertension and hypercholesterolaemia. While no large socioeconomic inequalities were noted in the management of individuals with diabetes, financial access to care was a strong predictor of diagnosis and management.Bulletin of the World Health Organisation 03/2011; 89(3):172-83. · 4.64 Impact Factor -
Article: Improving the public health utility of global cardiovascular mortality data: the rise of ischemic heart disease.
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ABSTRACT: High-quality, cause-specific mortality data are critical for effective health policy. Yet vague cause of death codes, such as heart failure, are highly prevalent in global mortality data. We propose an empirical method correcting mortality data for the use of heart failure as an underlying cause of death. We performed a regression analysis stratified by sex, age, and country development status on all available ICD-10 mortality data, consisting of 142 million deaths across 838 country-years. The analysis yielded predicted fractions with which to redistribute heart failure-attributed deaths to the appropriate underlying causes of death. Age-adjusted death rates and rank causes of death before and after correction were calculated. Heart failure accounts for 3.1% of all deaths in the dataset. Ischemic heart disease has the highest redistribution proportion for ages 15-49 and 50+ in both sexes and country development levels, causing gains in age-adjusted death rates in both developed and developing countries. COPD and hypertensive heart disease also make significant rank gains. Reproductive-aged women in developing country-years yield the most diverse range of heart failure causes. Ischemic heart disease becomes the No. 1 cause of death in several developed countries, including France and Japan, underscoring the cardiovascular epidemic in high-income countries. Age-adjusted death rate increases for ischemic heart disease in low- and middle-income countries, such as Argentina and South Africa, highlight the rise of the cardiovascular epidemic in regions where public health efforts have historically focused on infectious diseases. This method maximizes the use of available data, providing better evidence on major causes of death to inform policymakers in allocating finite resources.Population Health Metrics 03/2011; 9:8. · 2.11 Impact Factor -
Article: Verbal autopsy: advancing science, facilitating application.
Population Health Metrics 01/2011; 9:18. · 2.11 Impact Factor -
Article: Simplified Symptom Pattern Method for verbal autopsy analysis: multisite validation study using clinical diagnostic gold standards.
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ABSTRACT: Verbal autopsy can be a useful tool for generating cause of death data in data-sparse regions around the world. The Symptom Pattern (SP) Method is one promising approach to analyzing verbal autopsy data, but it has not been tested rigorously with gold standard diagnostic criteria. We propose a simplified version of SP and evaluate its performance using verbal autopsy data with accompanying true cause of death. We investigated specific parameters in SP's Bayesian framework that allow for its optimal performance in both assigning individual cause of death and in determining cause-specific mortality fractions. We evaluated these outcomes of the method separately for adult, child, and neonatal verbal autopsies in 500 different population constructs of verbal autopsy data to analyze its ability in various settings. We determined that a modified, simpler version of Symptom Pattern (termed Simplified Symptom Pattern, or SSP) performs better than the previously-developed approach. Across 500 samples of verbal autopsy testing data, SSP achieves a median cause-specific mortality fraction accuracy of 0.710 for adults, 0.739 for children, and 0.751 for neonates. In individual cause of death assignment in the same testing environment, SSP achieves 45.8% chance-corrected concordance for adults, 51.5% for children, and 32.5% for neonates. The Simplified Symptom Pattern Method for verbal autopsy can yield reliable and reasonably accurate results for both individual cause of death assignment and for determining cause-specific mortality fractions. The method demonstrates that verbal autopsies coupled with SSP can be a useful tool for analyzing mortality patterns and determining individual cause of death from verbal autopsy data.Population Health Metrics 01/2011; 9:30. · 2.11 Impact Factor -
Article: Assessing quality of medical death certification: Concordance between gold standard diagnosis and underlying cause of death in selected Mexican hospitals.
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ABSTRACT: In Mexico, the vital registration system relies on information collected from death certificates to generate official mortality figures. Although the death certificate has high coverage across the country, there is little information regarding its validity. The objective of this study was to assess the concordance between the underlying cause of death in official statistics obtained from death certificates and a gold standard diagnosis of the same deaths derived from medical records of hospitals. The study sample consisted of 1,589 deaths that occurred in 34 public hospitals in the Federal District and the state of Morelos, Mexico in 2009. Neonatal, child, and adult cases were selected for causes of death that included infectious diseases, noncommunicable diseases, and injuries. We compared the underlying cause of death, obtained from medical death certificates, against a gold standard diagnosis derived from a review of medical records developed by the Population Health Metrics Research Consortium. We used chance-corrected concordance and accuracy as metrics to evaluate the quality of performance of the death certificate. Analysis considering only the underlying cause of death resulted in a median chance-corrected concordance between the cause of death in medical death certificates versus the gold standard of 54.3% (95% uncertainty interval [UI]: 52.2, 55.6) for neonates, 38.5% (37.0, 40.0) for children, and 66.5% (65.9, 66.9) for adults. The accuracy resulting from the same analysis was 0.756 (0.747, 0.769) for neonates, 0.683 (0.663, 0.701) for children, and 0.780 (0.774, 0.785) for adults. Median chance-corrected concordance and accuracy increased when considering the mention of any cause of death in the death certificate, not just the underlying cause. Concordance varied substantially depending on cause of death, and accuracy varied depending on the true cause-specific mortality fraction composition. Although we cannot generalize our conclusions to Mexico as a whole, the results demonstrate important problems with the quality of the main source of information for causes of death used by decision-makers in settings with highly technological vital registration systems. It is necessary to improve death certification procedures, especially in the case of child and neonatal deaths. This requires an important commitment from the health system and health institutions.Population Health Metrics 01/2011; 9:38. · 2.11 Impact Factor -
Article: Performance of physician-certified verbal autopsies: multisite validation study using clinical diagnostic gold standards.
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ABSTRACT: Physician review of a verbal autopsy (VA) and completion of a death certificate remains the most widely used approach for VA analysis. This study provides new evidence about the performance of physician-certified verbal autopsy (PCVA) using defined clinical diagnostic criteria as a gold standard for a multisite sample of 12,542 VAs. The study was also designed to analyze issues related to PCVA, such as the impact of a second physician reader on the cause of death assigned, the variation in performance with and without household recall of health care experience (HCE), and the importance of local information for physicians reading VAs. The certification was performed by 24 physicians. The assignment of VA was random and blinded. Each VA was certified by one physician. Half of the VAs were reviewed by a different physician with household recall of health care experience included. The completed death certificate was processed for automated ICD-10 coding of the underlying cause of death. PCVA was compared to gold standard cause of death assignment based on strictly defined clinical diagnostic criteria that are part of the Population Health Metrics Research Consortium (PHMRC) gold standard verbal autopsy study. For individual cause assignment, the overall chance-corrected concordance for PCVA against the gold standard cause of death is less than 50%, with substantial variability by cause and physician. Physicians assign the correct cause around 30% of the time without HCE, and addition of HCE improves performance in adults to 45% and slightly higher in children to 48%. Physicians estimate cause-specific mortality fractions (CSMFs) with considerable error for adults, children, and neonates. Only for neonates for a cause list of six causes with HCE is accuracy above 0.7. In all three age groups, CSMF accuracy improves when household recall of health care experience is available. Results show that physician coding for cause of death assignment may not be as robust as previously thought. The time and cost required to initially collect the verbal autopsies must be considered in addition to the analysis, as well as the impact of diverting physicians from servicing immediate health needs in a population to review VAs. All of these considerations highlight the importance and urgency of developing better methods to more reliably analyze past and future verbal autopsies to obtain the highest quality mortality data from populations without reliable death certification.Population Health Metrics 01/2011; 9:32. · 2.11 Impact Factor -
Article: Robust metrics for assessing the performance of different verbal autopsy cause assignment methods in validation studies.
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ABSTRACT: Verbal autopsy (VA) is an important method for obtaining cause of death information in settings without vital registration and medical certification of causes of death. An array of methods, including physician review and computer-automated methods, have been proposed and used. Choosing the best method for VA requires the appropriate metrics for assessing performance. Currently used metrics such as sensitivity, specificity, and cause-specific mortality fraction (CSMF) errors do not provide a robust basis for comparison. We use simple simulations of populations with three causes of death to demonstrate that most metrics used in VA validation studies are extremely sensitive to the CSMF composition of the test dataset. Simulations also demonstrate that an inferior method can appear to have better performance than an alternative due strictly to the CSMF composition of the test set. VA methods need to be evaluated across a set of test datasets with widely varying CSMF compositions. We propose two metrics for assessing the performance of a proposed VA method. For assessing how well a method does at individual cause of death assignment, we recommend the average chance-corrected concordance across causes. This metric is insensitive to the CSMF composition of the test sets and corrects for the degree to which a method will get the cause correct due strictly to chance. For the evaluation of CSMF estimation, we propose CSMF accuracy. CSMF accuracy is defined as one minus the sum of all absolute CSMF errors across causes divided by the maximum total error. It is scaled from zero to one and can generalize a method's CSMF estimation capability regardless of the number of causes. Performance of a VA method for CSMF estimation by cause can be assessed by examining the relationship across test datasets between the estimated CSMF and the true CSMF. With an increasing range of VA methods available, it will be critical to objectively assess their performance in assigning cause of death. Chance-corrected concordance and CSMF accuracy assessed across a large number of test datasets with widely varying CSMF composition provide a robust strategy for this assessment.Population Health Metrics 01/2011; 9:28. · 2.11 Impact Factor -
Article: Population Health Metrics Research Consortium gold standard verbal autopsy validation study: design, implementation, and development of analysis datasets.
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ABSTRACT: Verbal autopsy methods are critically important for evaluating the leading causes of death in populations without adequate vital registration systems. With a myriad of analytical and data collection approaches, it is essential to create a high quality validation dataset from different populations to evaluate comparative method performance and make recommendations for future verbal autopsy implementation. This study was undertaken to compile a set of strictly defined gold standard deaths for which verbal autopsies were collected to validate the accuracy of different methods of verbal autopsy cause of death assignment. Data collection was implemented in six sites in four countries: Andhra Pradesh, India; Bohol, Philippines; Dar es Salaam, Tanzania; Mexico City, Mexico; Pemba Island, Tanzania; and Uttar Pradesh, India. The Population Health Metrics Research Consortium (PHMRC) developed stringent diagnostic criteria including laboratory, pathology, and medical imaging findings to identify gold standard deaths in health facilities as well as an enhanced verbal autopsy instrument based on World Health Organization (WHO) standards. A cause list was constructed based on the WHO Global Burden of Disease estimates of the leading causes of death, potential to identify unique signs and symptoms, and the likely existence of sufficient medical technology to ascertain gold standard cases. Blinded verbal autopsies were collected on all gold standard deaths. Over 12,000 verbal autopsies on deaths with gold standard diagnoses were collected (7,836 adults, 2,075 children, 1,629 neonates, and 1,002 stillbirths). Difficulties in finding sufficient cases to meet gold standard criteria as well as problems with misclassification for certain causes meant that the target list of causes for analysis was reduced to 34 for adults, 21 for children, and 10 for neonates, excluding stillbirths. To ensure strict independence for the validation of methods and assessment of comparative performance, 500 test-train datasets were created from the universe of cases, covering a range of cause-specific compositions. This unique, robust validation dataset will allow scholars to evaluate the performance of different verbal autopsy analytic methods as well as instrument design. This dataset can be used to inform the implementation of verbal autopsies to more reliably ascertain cause of death in national health information systems.Population Health Metrics 01/2011; 9:27. · 2.11 Impact Factor -
Article: Performance of InterVA for assigning causes of death to verbal autopsies: multisite validation study using clinical diagnostic gold standards.
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ABSTRACT: InterVA is a widely disseminated tool for cause of death attribution using information from verbal autopsies. Several studies have attempted to validate the concordance and accuracy of the tool, but the main limitation of these studies is that they compare cause of death as ascertained through hospital record review or hospital discharge diagnosis with the results of InterVA. This study provides a unique opportunity to assess the performance of InterVA compared to physician-certified verbal autopsies (PCVA) and alternative automated methods for analysis. Using clinical diagnostic gold standards to select 12,542 verbal autopsy cases, we assessed the performance of InterVA on both an individual and population level and compared the results to PCVA, conducting analyses separately for adults, children, and neonates. Following the recommendation of Murray et al., we randomly varied the cause composition over 500 test datasets to understand the performance of the tool in different settings. We also contrasted InterVA with an alternative Bayesian method, Simplified Symptom Pattern (SSP), to understand the strengths and weaknesses of the tool. Across all age groups, InterVA performs worse than PCVA, both on an individual and population level. On an individual level, InterVA achieved a chance-corrected concordance of 24.2% for adults, 24.9% for children, and 6.3% for neonates (excluding free text, considering one cause selection). On a population level, InterVA achieved a cause-specific mortality fraction accuracy of 0.546 for adults, 0.504 for children, and 0.404 for neonates. The comparison to SSP revealed four specific characteristics that lead to superior performance of SSP. Increases in chance-corrected concordance are attained by developing cause-by-cause models (2%), using all items as opposed to only the ones that mapped to InterVA items (7%), assigning probabilities to clusters of symptoms (6%), and using empirical as opposed to expert probabilities (up to 8%). Given the widespread use of verbal autopsy for understanding the burden of disease and for setting health intervention priorities in areas that lack reliable vital registrations systems, accurate analysis of verbal autopsies is essential. While InterVA is an affordable and available mechanism for assigning causes of death using verbal autopsies, users should be aware of its suboptimal performance relative to other methods.Population Health Metrics 01/2011; 9:50. · 2.11 Impact Factor -
Article: [Burden of disease in Latin America].
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ABSTRACT: To describe the burden of disease studies made in the region, identify the main priorities in health from the indicator Disability Adjusted Life Years (DALYs). By the use of DALYs identify the burden of disease in the countries in the network. DALYs emphasize the emergency of mental disorders, diabetes mellitus in women and the disorders associated with alcohol consumption and injuries in men. Latin America is the region with more national studies of burden of disease, using a standardized methodology, that allows identifying new health priorities which are pressing to the health services; for that reason these results constitute an element to take into account in the establishment of public policies in each country.Salud publica de Mexico 01/2011; 53 Suppl 2:s72-7. · 0.94 Impact Factor -
Article: [Progress on the Millenium Development Goals 4 and 5 in Mesoamerica].
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ABSTRACT: To describe the advances made by countries in the Mesoamerican region towards reaching Millenium Development Goals (MDG) 4 and 5, and discuss the most useful tasks to help the region in accomplishing or keeping track of these objectives. The trend estimates of maternal and under 5 mortality from 1990 to 2008, the effective coverage of vaccination against diphteria, pertussis and tetanus (DPT), prenatal care and childbirth by qualified personnel were taken from the Institute of Health Metrics and Evaluation (IHME) and the causes of death for children under five were taken from the Children's Health Epidemiology Reference Group of WHO (CHERG). The regional trend in the rate of mortality for children under five (MDG-4) in the last 18 years shows an annual reduction of 4.2%, significantly above the global reduction of 2.1%. This suggests that countries of Mesoamerica will be able to fulfill this objective. In contrast, data for 2008 shows that the rate of reduction of maternal mortality is very heterogeneous and it is unlikely that any of the countries in the region will reach this goal. Efforts made by countries in Mesoamerica have been substantial in controlling mortality in children under five years but insufficient to achieve MDG-5. Although the tendency is in the right track the reduction rate will only partially fulfill the acquired commitments to eradicate poverty.Salud publica de Mexico 01/2011; 53 Suppl 3:S295-302. · 0.94 Impact Factor -
Article: Increased educational attainment and its effect on child mortality in 175 countries between 1970 and 2009: a systematic analysis.
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ABSTRACT: In addition to the inherent importance of education and its essential role in economic growth, education and health are strongly related. We updated previous systematic assessments of educational attainment, and estimated the contribution of improvements in women's education to reductions in child mortality in the past 40 years. We compiled 915 censuses and nationally representative surveys, and estimated mean number of years of education by age and sex. By use of a first-differences model, we investigated the association between child mortality and women's educational attainment, controlling for income per person and HIV seroprevalence. We then computed counterfactual estimates of child mortality for every country year between 1970 and 2009. The global mean number of years of education increased from 4·7 years (95% uncertainty interval 4·4-5·1) to 8·3 years (8·0-8·6) for men (aged ≥25 years) and from 3·5 years (3·2-3·9) to 7·1 years (6·7 -7·5) for women (aged ≥25 years). For women of reproductive age (15-44 years) in developing countries, the years of schooling increased from 2·2 years (2·0-2·4) to 7·2 years (6·8-7·6). By 2009, in 87 countries, women (aged 25-34 years) had higher educational attainment than had men (aged 25-34 years). Of 8·2 million fewer deaths in children younger than 5 years between 1970 and 2009, we estimated that 4·2 million (51·2%) could be attributed to increased educational attainment in women of reproductive age. The substantial increase in education, especially of women, and the reversal of the gender gap have important implications not only for health but also for the status and roles of women in society. The continued increase in educational attainment even in some of the poorest countries suggests that rapid progress in terms of Millennium Development Goal 4 might be possible. Bill & Melinda Gates Foundation.The Lancet 09/2010; 376(9745):959-74. · 38.28 Impact Factor
Top co-authors
Top Journals
Institutions
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2007–2013
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University of Washington Seattle
- Institute for Health Metrics and Evaluation
Seattle, WA, USA -
Secretaría de Salud
Mexico City, The Federal District, Mexico -
Johns Hopkins Bloomberg School of Public Health
Baltimore, MD, USA -
Harvard University
Boston, MA, USA
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2012
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Brandeis University
- Schneider Institute for Health Policy
Waltham, MA, USA
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2011
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Instituto Nacional de Salud Pública
Cuernavaca, Morelos, Mexico
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