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1.  A composite metric for assessing data on mortality and causes of death: the vital statistics performance index 
Timely and reliable data on causes of death are fundamental for informed decision-making in the health sector as well as public health research. An in-depth understanding of the quality of data from vital statistics (VS) is therefore indispensable for health policymakers and researchers. We propose a summary index to objectively measure the performance of VS systems in generating reliable mortality data and apply it to the comprehensive cause of death database assembled for the Global Burden of Disease (GBD) 2013 Study.
We created a Vital Statistics Performance Index, a composite of six dimensions of VS strength, each assessed by a separate empirical indicator. The six dimensions include: quality of cause of death reporting, quality of age and sex reporting, internal consistency, completeness of death reporting, level of cause-specific detail, and data availability/timeliness. A simulation procedure was developed to combine indicators into a single index. This index was computed for all country-years of VS in the GBD 2013 cause of death database, yielding annual estimates of overall VS system performance for 148 countries or territories.
The six dimensions impacted the accuracy of data to varying extents. VS performance declines more steeply with declining simulated completeness than for any other indicator. The amount of detail in the cause list reported has a concave relationship with overall data accuracy, but is an important driver of observed VS performance. Indicators of cause of death data quality and age/sex reporting have more linear relationships with simulated VS performance, but poor cause of death reporting influences observed VS performance more strongly. VS performance is steadily improving at an average rate of 2.10% per year among the 148 countries that have available data, but only 19.0% of global deaths post-2000 occurred in countries with well-performing VS systems.
Objective and comparable information about the performance of VS systems and the utility of the data that they report will help to focus efforts to strengthen VS systems. Countries and the global health community alike need better intelligence about the accuracy of VS that are widely and often uncritically used in population health research and monitoring.
PMCID: PMC4060759  PMID: 24982595
Mortality; Causes of death; Vital statistics; Civil registration; Vital registration; Data quality; Health information systems
2.  Transcriptional and hormonal regulation of petal and stamen development by STAMENLESS, the tomato (Solanum lycopersicum L.) orthologue to the B-class APETALA3 gene 
Journal of Experimental Botany  2014;65(9):2243-2256.
Characterization of stamenless mutants reveals that petal and stamen identity in tomato depends on gene–hormone interactions, as mediated by the tomato APETALA3 orthologue STAMENLESS gene (SL, syn. TAP3, SlDEF, LeAP3).
Four B-class MADS box genes specify petal and stamen organ identities in tomato. Several homeotic mutants affected in petal and stamen development were described in this model species, although the causal mutations have not been identified for most of them. In this study we characterized a strong stamenless mutant in the tomato Primabel cultivar (sl-Pr), which exhibited homeotic conversion of petals into sepals and stamens into carpels and we compared it with the stamenless mutant in the LA0269 accession (sl-LA0269). Genetic complementation analysis proved that both sl mutants were allelic. Sequencing revealed point mutations in the coding sequence of the Tomato APETALA3 (TAP3) gene of the sl-Pr genome, which lead to a truncated protein, whereas a chromosomal rearrangement in the TAP3 promoter was detected in the sl-LA0269 allele. Moreover, the floral phenotype of TAP3 antisense plants exhibited identical homeotic changes to sl mutants. These results demonstrate that SL is the tomato AP3 orthologue and that the mutant phenotype correlated to the SL silencing level. Expression analyses showed that the sl-Pr mutation does not affect the expression of other tomato B-class genes, although SL may repress the A-class gene MACROCALYX. A partial reversion of the sl phenotype by gibberellins, gene expression analysis, and hormone quantification in sl flowers revealed a role of phytohormones in flower development downstream of the SL gene. Together, our results indicated that petal and stamen identity in tomato depends on gene–hormone interactions, as mediated by the SL gene.
PMCID: PMC4036497  PMID: 24659487
APETALA3; B-class gene; flower morphogenesis; hormone regulation; Solanum lycopersicum; STAMENLESS; tomato.
3.  Using verbal autopsy to measure causes of death: the comparative performance of existing methods 
BMC Medicine  2014;12:5.
Monitoring progress with disease and injury reduction in many populations will require widespread use of verbal autopsy (VA). Multiple methods have been developed for assigning cause of death from a VA but their application is restricted by uncertainty about their reliability.
We investigated the validity of five automated VA methods for assigning cause of death: InterVA-4, Random Forest (RF), Simplified Symptom Pattern (SSP), Tariff method (Tariff), and King-Lu (KL), in addition to physician review of VA forms (PCVA), based on 12,535 cases from diverse populations for which the true cause of death had been reliably established. For adults, children, neonates and stillbirths, performance was assessed separately for individuals using sensitivity, specificity, Kappa, and chance-corrected concordance (CCC) and for populations using cause specific mortality fraction (CSMF) accuracy, with and without additional diagnostic information from prior contact with health services. A total of 500 train-test splits were used to ensure that results are robust to variation in the underlying cause of death distribution.
Three automated diagnostic methods, Tariff, SSP, and RF, but not InterVA-4, performed better than physician review in all age groups, study sites, and for the majority of causes of death studied. For adults, CSMF accuracy ranged from 0.764 to 0.770, compared with 0.680 for PCVA and 0.625 for InterVA; CCC varied from 49.2% to 54.1%, compared with 42.2% for PCVA, and 23.8% for InterVA. For children, CSMF accuracy was 0.783 for Tariff, 0.678 for PCVA, and 0.520 for InterVA; CCC was 52.5% for Tariff, 44.5% for PCVA, and 30.3% for InterVA. For neonates, CSMF accuracy was 0.817 for Tariff, 0.719 for PCVA, and 0.629 for InterVA; CCC varied from 47.3% to 50.3% for the three automated methods, 29.3% for PCVA, and 19.4% for InterVA. The method with the highest sensitivity for a specific cause varied by cause.
Physician review of verbal autopsy questionnaires is less accurate than automated methods in determining both individual and population causes of death. Overall, Tariff performs as well or better than other methods and should be widely applied in routine mortality surveillance systems with poor cause of death certification practices.
PMCID: PMC3891983  PMID: 24405531
Verbal autopsy; VA; Validation; Cause of death; Symptom pattern; Random forests; InterVA; King-Lu; Tariff
4.  Chlorpyrifos-, Diisopropylphosphorofluoridate-, and Parathion-Induced Behavioral and Oxidative Stress Effects: Are They Mediated by Analogous Mechanisms of Action? 
Toxicological Sciences  2012;131(1):206-216.
Exposure to organophosphates (OPs) can lead to cognitive deficits and oxidative damage. Little is known about the relationship between behavioral deficits and oxidative stress within the context of such exposures. Accordingly, the first experiment was carried out to address this issue. Male Wistar rats were administered 250mg/kg of chlorpyrifos (CPF), 1.5mg/kg of diisopropylphosphorofluoridate (DFP), or 15mg/kg of parathion (PTN). Spatial learning in the water maze task was evaluated, and F2-isoprostanes (F2-IsoPs) and prostaglandin (PGE2) were analyzed in the hippocampus. A second experiment was designed to determine the degree of inhibition of brain acetylcholinesterase (AChE) activity, both the soluble and particulate forms of the enzyme, and to assess changes in AChE gene expression given evidence on alternative splicing of the gene in response to OP exposures. In addition, brain acylpeptide hydrolase (APH) activity was evaluated as a second target for OP-mediated effects. In both experiments, rats were sacrificed at various points to determine the time course of OPs toxicity in relation to their mechanism of action. Results from the first experiment suggest cognitive and emotional deficits after OPs exposure, which could be due to, at least in part, increased F2-IsoPs levels. Results from the second experiment revealed inhibition of brain AChE and APH activity at various time points post OP exposure. In addition, we observed increased brain read-through splice variant AChE (AChE-R) mRNA levels after 48h PTN exposure. In conclusion, this study provides novel data on the relationship between cognitive alterations and oxidative stress, and the diverse mechanisms of action along a temporal axis in response to OP exposures in the rat.
PMCID: PMC3537130  PMID: 22986948
organophosphates; spatial learning; oxidative stress; acetylcholinesterase; acylpeptide hydrolase; read-through AChE.
5.  Marker-based linkage map of Andean common bean (Phaseolus vulgaris L.) and mapping of QTLs underlying popping ability traits 
BMC Plant Biology  2012;12:136.
Nuña bean is a type of ancient common bean (Phaseolus vulgaris L.) native to the Andean region of South America, whose seeds possess the unusual property of popping. The nutritional features of popped seeds make them a healthy low fat and high protein snack. However, flowering of nuña bean only takes place under short-day photoperiod conditions, which means a difficulty to extend production to areas where such conditions do not prevail. Therefore, breeding programs of adaptation traits will facilitate the diversification of the bean crops and the development of new varieties with enhanced healthy properties. Although the popping trait has been profusely studied in maize (popcorn), little is known about the biology and genetic basis of the popping ability in common bean. To obtain insights into the genetics of popping ability related traits of nuña bean, a comprehensive quantitative trait loci (QTL) analysis was performed to detect single-locus and epistatic QTLs responsible for the phenotypic variance observed in these traits.
A mapping population of 185 recombinant inbred lines (RILs) derived from a cross between two Andean common bean genotypes was evaluated for three popping related traits, popping dimension index (PDI), expansion coefficient (EC), and percentage of unpopped seeds (PUS), in five different environmental conditions. The genetic map constructed included 193 loci across 12 linkage groups (LGs), covering a genetic distance of 822.1 cM, with an average of 4.3 cM per marker. Individual and multi-environment QTL analyses detected a total of nineteen single-locus QTLs, highlighting among them the co-localized QTLs for the three popping ability traits placed on LGs 3, 5, 6, and 7, which together explained 24.9, 14.5, and 25.3% of the phenotypic variance for PDI, EC, and PUS, respectively. Interestingly, epistatic interactions among QTLs have been detected, which could have a key role in the genetic control of popping.
The QTLs here reported constitute useful tools for marker assisted selection breeding programs aimed at improving nuña bean cultivars, as well as for extending our knowledge of the genetic determinants and genotype x environment interaction involved in the popping ability traits of this bean crop.
PMCID: PMC3490973  PMID: 22873566
6.  Modeling causes of death: an integrated approach using CODEm 
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.
PMCID: PMC3315398  PMID: 22226226
cause of death; ensemble models; predictive validity; spatial-temporal models; maternal mortality; Global Burden of Disease
7.  Performance of InterVA for assigning causes of death to verbal autopsies: multisite validation study using clinical diagnostic gold standards 
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.
PMCID: PMC3160943  PMID: 21819580
Verbal autopsy; InterVA; validation
8.  Population Health Metrics Research Consortium gold standard verbal autopsy validation study: design, implementation, and development of analysis datasets 
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.
PMCID: PMC3160920  PMID: 21816095
Verbal autopsy; VA; validation; Philippines; Tanzania; India; Mexico; gold standard; cause of death
9.  Robust metrics for assessing the performance of different verbal autopsy cause assignment methods in validation studies 
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.
PMCID: PMC3160921  PMID: 21816106
Verbal autopsy; metrics; validation
10.  Simplified Symptom Pattern Method for verbal autopsy analysis: multisite validation study using clinical diagnostic gold standards 
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.
PMCID: PMC3160923  PMID: 21816099
Verbal autopsy; Symptom Pattern; validation; gold standard
11.  Performance of physician-certified verbal autopsies: multisite validation study using clinical diagnostic gold standards 
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.
PMCID: PMC3160925  PMID: 21816104
Verbal autopsy; cause of death certification; validation; physician review
12.  Assessing quality of medical death certification: Concordance between gold standard diagnosis and underlying cause of death in selected Mexican hospitals 
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.
PMCID: PMC3160931  PMID: 21816103
14.  An insertional mutagenesis programme with an enhancer trap for the identification and tagging of genes involved in abiotic stress tolerance in the tomato wild-related species Solanum pennellii 
Plant Cell Reports  2011;30(10):1865-1879.
Salinity and drought have a huge impact on agriculture since there are few areas free of these abiotic stresses and the problem continues to increase. In tomato, the most important horticultural crop worldwide, there are accessions of wild-related species with a high degree of tolerance to salinity and drought. Thus, the finding of insertional mutants with other tolerance levels could lead to the identification and tagging of key genes responsible for abiotic stress tolerance. To this end, we are performing an insertional mutagenesis programme with an enhancer trap in the tomato wild-related species Solanum pennellii. First, we developed an efficient transformation method which has allowed us to generate more than 2,000 T-DNA lines. Next, the collection of S. pennelli T0 lines has been screened in saline or drought conditions and several presumptive mutants have been selected for their salt and drought sensitivity. Moreover, T-DNA lines with expression of the reporter uidA gene in specific organs, such as vascular bundles, trichomes and stomata, which may play key roles in processes related to abiotic stress tolerance, have been identified. Finally, the growth of T-DNA lines in control conditions allowed us the identification of different development mutants. Taking into account that progenies from the lines are being obtained and that the collection of T-DNA lines is going to enlarge progressively due to the high transformation efficiency achieved, there are great possibilities for identifying key genes involved in different tolerance mechanisms to salinity and drought.
PMCID: PMC3172414  PMID: 21647638
Insertional mutagenesis; Solanum pennellii; Enhancer trap; Salinity; Drought; Gene tagging
15.  Improving the public health utility of global cardiovascular mortality data: the rise of ischemic heart disease 
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.
PMCID: PMC3064613  PMID: 21406100
16.  Functional Analysis of the Arlequin Mutant Corroborates the Essential Role of the ARLEQUIN/TAGL1 Gene during Reproductive Development of Tomato 
PLoS ONE  2010;5(12):e14427.
Reproductive development of higher plants comprises successive events of organ differentiation and growth which finally lead to the formation of a mature fruit. However, most of the genetic and molecular mechanisms which coordinate such developmental events are yet to be identified and characterized. Arlequin (Alq), a semi-dominant T-DNA tomato mutant showed developmental changes affecting flower and fruit ripening. Sepals were converted into fleshy organs which ripened as normal fruit organs and fruits displayed altered ripening features. Molecular characterization of the tagged gene demonstrated that it corresponded to the previously reported TOMATO AGAMOUS-LIKE 1 (TAGL1) gene, the tomato ortholog of SHATTERPROOF MADS-box genes of Arabidopsis thaliana, and that the Alq mutation promoted a gain-of-function phenotype caused by the ectopic expression of TAGL1. Ectopic overexpression of TAGL1 resulted in homeotic alterations affecting floral organ identity that were similar to but stronger than those observed in Alq mutant plants. Interestingly, TAGL1 RNAi plants yielded tomato fruits which were unable to ripen. They displayed a yellow-orange color and stiffness appearance which are in accordance with reduced lycopene and ethylene levels, respectively. Moreover, pericarp cells of TAGL1 RNAi fruits showed altered cellular and structural properties which correlated to both decreased expression of genes regulating cell division and lignin biosynthesis. Over-expression of TAGL1 is able to rescue the non-ripening phenotype of rin and nor mutants, which is mediated by the transcriptional activation of several ripening genes. Our results demonstrated that TAGL1 participates in the genetic control of flower and fruit development of tomato plants. Furthermore, gene silencing and over-expression experiments demonstrated that the fruit ripening process requires the regulatory activity of TAGL1. Therefore, TAGL1 could act as a linking factor connecting successive stages of reproductive development, from flower development to fruit maturation, allowing this complex process to be carried out successfully.
PMCID: PMC3009712  PMID: 21203447
17.  Algorithms for enhancing public health utility of national causes-of-death data 
Coverage and quality of cause-of-death (CoD) data varies across countries and time. Valid, reliable, and comparable assessments of trends in causes of death from even the best systems are limited by three problems: a) changes in the International Statistical Classification of Diseases and Related Health Problems (ICD) over time; b) the use of tabulation lists where substantial detail on causes of death is lost; and c) many deaths assigned to causes that cannot or should not be considered underlying causes of death, often called garbage codes (GCs). The Global Burden of Disease Study and the World Health Organization have developed various methods to enhance comparability of CoD data. In this study, we attempt to build on these approaches to enhance the utility of national cause-of-death data for public health analysis.
Based on careful consideration of 4,434 country-years of CoD data from 145 countries from 1901 to 2008, encompassing 743 million deaths in ICD versions 1 to 10 as well as country-specific cause lists, we have developed a public health-oriented cause-of-death list. These 56 causes are organized hierarchically and encompass all deaths. Each cause has been mapped from ICD-6 to ICD-10 and, where possible, they have also been mapped to the International List of Causes of Death 1-5. We developed a typology of different classes of GCs. In each ICD revision, GCs have been identified. Target causes to which these GCs should be redistributed have been identified based on certification practice and/or pathophysiology. Proportionate redistribution, statistical models, and expert algorithms have been developed to redistribute GCs to target codes for each age-sex group.
The fraction of all deaths assigned to GCs varies tremendously across countries and revisions of the ICD. In general, across all country-years of data available, GCs have declined from more than 43% in ICD-7 to 24% in ICD-10. In some regions, such as Australasia, GCs in 2005 are as low as 11%, while in some developing countries, such as Thailand, they are greater than 50%. Across different age groups, the composition of GCs varies tremendously - three classes of GCs steadily increase with age, but ambiguous codes within a particular disease chapter are also common for injuries at younger ages. The impact of redistribution is to change the number of deaths assigned to particular causes for a given age-sex group. These changes alter ranks across countries for any given year by a number of different causes, change time trends, and alter the rank order of causes within a country.
By mapping CoD through different ICD versions and redistributing GCs, we believe the public health utility of CoD data can be substantially enhanced, leading to an increased demand for higher quality CoD data from health sector decision-makers.
PMCID: PMC2873308  PMID: 20459720
18.  Estimating Population Cause-Specific Mortality Fractions from in-Hospital Mortality: Validation of a New Method 
PLoS Medicine  2007;4(11):e326.
Cause-of-death data for many developing countries are not available. Information on deaths in hospital by cause is available in many low- and middle-income countries but is not a representative sample of deaths in the population. We propose a method to estimate population cause-specific mortality fractions (CSMFs) using data already collected in many middle-income and some low-income developing nations, yet rarely used: in-hospital death records.
Methods and Findings
For a given cause of death, a community's hospital deaths are equal to total community deaths multiplied by the proportion of deaths occurring in hospital. If we can estimate the proportion dying in hospital, we can estimate the proportion dying in the population using deaths in hospital. We propose to estimate the proportion of deaths for an age, sex, and cause group that die in hospital from the subset of the population where vital registration systems function or from another population. We evaluated our method using nearly complete vital registration (VR) data from Mexico 1998–2005, which records whether a death occurred in a hospital. In this validation test, we used 45 disease categories. We validated our method in two ways: nationally and between communities. First, we investigated how the method's accuracy changes as we decrease the amount of Mexican VR used to estimate the proportion of each age, sex, and cause group dying in hospital. Decreasing VR data used for this first step from 100% to 9% produces only a 12% maximum relative error between estimated and true CSMFs. Even if Mexico collected full VR information only in its capital city with 9% of its population, our estimation method would produce an average relative error in CSMFs across the 45 causes of just over 10%. Second, we used VR data for the capital zone (Distrito Federal and Estado de Mexico) and estimated CSMFs for the three lowest-development states. Our estimation method gave an average relative error of 20%, 23%, and 31% for Guerrero, Chiapas, and Oaxaca, respectively.
Where accurate International Classification of Diseases (ICD)-coded cause-of-death data are available for deaths in hospital and for VR covering a subset of the population, we demonstrated that population CSMFs can be estimated with low average error. In addition, we showed in the case of Mexico that this method can substantially reduce error from biased hospital data, even when applied to areas with widely different levels of development. For countries with ICD-coded deaths in hospital, this method potentially allows the use of existing data to inform health policy.
Working in Mexico and using vital registration data, Chris Murray and colleagues achieved encouraging results with a new method to estimate population cause-specific mortality fractions.
Editors' Summary
Governments and international health agencies need accurate information on the leading causes of death in different populations to help them develop and monitor effective health policies and programs. It is pointless investing money in screening programs for a type of cancer in a country where that cancer is very rare, for example, or setting up treatment centers for an infectious disease in a region where the disease no longer occurs. In developed countries, most deaths are recorded in vital registration (VR) systems. These databases record the specific cause of death, which is assigned by doctors using the International Classification of Diseases (ICD), an internationally agreed-upon list of codes for hundreds of diseases. Across the developing world, however, only one death in four is recorded by VR systems; in some very poor countries, only one death in 20 is recorded accurately. With this paucity of cause-of-death data, developing countries cannot make good decisions about how to spend their limited resources.
Why Was This Study Done?
The establishment of full VR systems in all developing countries will take time and may not always be possible, but many of these nations already collect ICD-coded data on in-hospital deaths. Unfortunately, this information does not accurately reflect the causes of death across whole populations. For example, the diseases that affect rich people differ from those that affect poor people, and rich people are more likely to die in hospital than poor people. Thus, although for each cause of death, the number of deaths in hospital equals the total number of deaths in the community multiplied by the proportion of deaths occurring in hospital, this proportion is different for each cause. If these proportions could be estimated, then in-hospital death records could be used to determine the fraction of the population that dies from each cause—the population's “cause-specific mortality fractions” (CSMFs). In this study, the researchers have devised a method that allows them to do this, and have used near-complete VR data collected between 1998 and 2005 in Mexico to test their method.
What Did the Researchers Do and Find?
The researchers developed a mathematical method that estimates the proportion of deaths occurring in hospitals for people grouped together by their age, sex, and cause of death (an “age–sex–cause group”) using VR data from a subset of the whole population. They tested their method for 45 nonoverlapping but all-encompassing diseases using the Mexican VR data (which records when a person has died in the hospital). They found that if they decreased the amount of VR data used to estimate the proportion of each age, sex, cause group dying in hospital from 100% to 9%, the maximum relative error between the true and estimated CSMFs was only 12%. When they just used the VR information from the capital city (9% of the population), the average relative error in CSMFs (a measure of how much the estimated and true CSMFs differ) across all 45 causes of death was only 10%. Finally, when they used VR data for the main urban area of Mexico (where access to hospitals is good) to estimate CSMFs for the three least developed states of Mexico, the average relative errors were 20%, 23%, and 31%.
What Do These Findings Mean?
These findings indicate that the researchers' method can provide accurate estimates of population CSMFs using ICD-coded cause-of-death data from deaths in hospital and VR data that cover part of the population. Even when the VR data from a developed area are used to calculate the CSMFs in a poorly developed area, the method produces a more accurate estimate than in-hospital death data used alone. Because the researchers have only tested their method for one country, additional “validation studies” need to be done using data from other countries with a good-quality VR system. If the method does work in these other settings, then existing data on in-hospital deaths could be used to determine the leading causes of death in countries with poor VR systems. Such information would be invaluable in establishing effective health policies.
Additional Information.
Please access these Web sites via the online version of this summary at
• An accompanying paper by the same authors describes an alternative approach to collecting accurate cause-of-death data in developing countries
• The World Health Organization provides information on health statistics and health information systems, on the International Classification of Diseases, and on the Health Metrics Network, a global collaboration focused on improving sources of vital statistics and cause-of-death data
• Grand Challenges in Global Health provides information on research into better ways for developing countries to measure their health status
PMCID: PMC2080647  PMID: 18031195
19.  Impact of insurance and supply of health professionals on coverage of treatment for hypertension in Mexico: population based study 
BMJ : British Medical Journal  2007;335(7625):875.
Objective To examine the independent and combined contributions of insurance status and supply of health professionals on coverage of antihypertensive treatment among adults in Mexico.
Design Population based study.
Setting Mexico.
Participants 4032 hypertensive adults (2967 uninsured and 1065 insured): 1065 uninsured adults matched with 1065 adults insured through Seguro Popular, a programme to expand health insurance coverage to uninsured people in Mexico.
Main outcome measures Coverage of antihypertensive treatment and coverage of antihypertensive treatment with control of blood pressure.
Results Rates of treatment for hypertension varied by insurance status and supply of health professionals. Hypertensive adults insured through Seguro Popular had a significantly higher probability of receiving antihypertensive treatment (odds ratio 1.50, 95% confidence interval 1.27 to 1.78) and receiving antihypertensive treatment with control of blood pressure (1.35, 1.00 to 1.82). Greater supply of health professionals in areas with coverage through Seguro Popular was a significant predictor of antihypertensive treatment after adjusting for covariates (1.49, 1.00 to 2.20).
Conclusions Expansion of healthcare coverage to uninsured people in Mexico was associated with greater use of antihypertensive treatment and blood pressure control, particularly in areas with a greater supply of health professionals.
PMCID: PMC2043407  PMID: 17954519
20.  The burden of HIV: insights from the Global Burden of Disease Study 2010 
AIDS (London, England)  2013;27(13):2003-2017.
To evaluate the global and country-level burden of HIV/AIDS relative to 291 other causes of disease burden from 1980 to 2010 using the Global Burden of Disease Study 2010 (GBD 2010) as the vehicle for exploration.
HIV/AIDS burden estimates were derived elsewhere as a part of GBD 2010, a comprehensive assessment of the magnitude of 291 diseases and injuries from 1990 to 2010 for 187 countries. In GBD 2010, disability-adjusted life years (DALYs) are used as the measurement of disease burden. DALY estimates for HIV/AIDS come from UNAIDS’ 2012 prevalence and mortality estimates, GBD 2010 disability weights and mortality estimates derived from quality vital registration data.
Despite recent declines in global HIV/AIDS mortality, HIV/AIDS was still the fifth leading cause of global DALYs in 2010. The distribution of HIV/AIDS burden is not equal across demographics and regions. In 2010, HIV/AIDS was ranked as the leading DALY cause for ages 30–44 years in both sexes and for 21 countries that fall into four distinctive blocks: Eastern and Southern Africa, Central Africa, the Caribbean and Thailand. Although a majority of the DALYs caused by HIV/AIDS are in high-burden countries, 20% of the global HIV/AIDS burden in 2010 was in countries where HIV/AIDS did not make the top 10 leading causes of burden.
In the midst of a global economic recession, tracking the magnitude of the HIV/AIDS epidemic and its importance relative to other diseases and injuries is critical to effectively allocating limited resources and maintaining funding for effective HIV/AIDS interventions and treatments.
PMCID: PMC3748855  PMID: 23660576
burden; disability-adjusted life years; Global Burden of Disease Study; global trends; HIV/AIDS; mortality
21.  Estimates of neonatal morbidities and disabilities at regional and global levels for 2010: introduction, methods overview, and relevant findings from the Global Burden of Disease study 
Pediatric Research  2013;74(Suppl 1):4-16.
Neonatal mortality and morbidity are increasingly recognized as important globally, but detailed estimates of neonatal morbidity from conditions and long-term consequences are yet to be published.
We describe the general methods for systematic reviews, meta-analyses, and modeling used in this supplement, highlighting differences from the Global Burden of Disease (GBD2010) inputs and methods. For five conditions (preterm birth, retinopathy of prematurity, intrapartum-related conditions, neonatal infections, and neonatal jaundice), a standard three-step compartmental model was applied to estimate—by region, for 2010—the numbers of (i) affected births by sex, (ii) postneonatal survivors, and (iii) impaired postneonatal survivors. For conditions included in GBD2010 analyses (preterm birth and intrapartum-related conditions), impairment at all ages was estimated, and disability weights were applied to estimate years lived with disability (YLD) and summed with years of life lost (YLL) to calculate disability-adjusted life years (DALYs).
GBD2010 estimated neonatal conditions (preterm birth, intrapartum-related, neonatal sepsis, and “other neonatal”) to be responsible for 202 million DALYs or 8.1% (7.3–9.0%) of the worldwide total. Mortality contributed 95% of the DALYs, and the estimated 26% reduction in neonatal condition DALYs since 1990 is primarily due to a 44% reduction in neonatal mortality rate due to these conditions, counterbalanced by increased numbers of babies born (17%). Impairment following neonatal conditions remained stable globally and is therefore relatively more important, especially in high- and middle-income countries. Crucial data gaps were identified.
These results confirm neonatal conditions as a significant burden, reemphasizing the need to reduce deaths further, to count the linked 2.6 million stillbirths, and to better measure and address their long-term effects.
PMCID: PMC3873708  PMID: 24366460

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