Health has improved markedly in Mesoamerica, the region consisting of southern Mexico and Central America, over the past decade. Despite this progress, there remain substantial inequalities in health outcomes, access, and quality of medical care between and within countries. Poor, indigenous, and rural populations have considerably worse health indicators than national or regional averages. In an effort to address these health inequalities, the Salud Mesoamérica 2015 Initiative (SM2015), a results-based financing initiative, was established.
For each of the eight participating countries, health targets were set to measure the progress of improvements in maternal and child health produced by the Initiative. To establish a baseline, we conducted censuses of 90,000 households, completed 20,225 household interviews, and surveyed 479 health facilities in the poorest areas of Mesoamerica. Pairing health facility and household surveys allows us to link barriers to care and health outcomes with health system infrastructure components and quality of health services.
Indicators varied significantly within and between countries. Anemia was most prevalent in Panama and least prevalent in Honduras. Anemia varied by age, with the highest levels observed among children aged 0 to 11 months in all settings. Belize had the highest proportion of institutional deliveries (99%), while Guatemala had the lowest (24%). The proportion of women with four antenatal care visits with a skilled attendant was highest in El Salvador (90%) and the lowest in Guatemala (20%). Availability of contraceptives also varied. The availability of condoms ranged from 83% in Nicaragua to 97% in Honduras. Oral contraceptive pills and injectable contraceptives were available in just 75% of facilities in Panama. IUDs were observed in only 21.5% of facilities surveyed in El Salvador.
These data provide a baseline of much-needed information for evidence-based action on health throughout Mesoamerica. Our baseline estimates reflect large disparities in health indicators within and between countries and will facilitate the evaluation of interventions and investments deployed in the region over the next three to five years. SM2015’s innovative monitoring and evaluation framework will allow health officials with limited resources to identify and target areas of greatest need.
Electronic supplementary material
The online version of this article (doi:10.1186/s12963-015-0034-4) contains supplementary material, which is available to authorized users.
Results-based financing; Salud Mesoamerica 2015; Vaccination; Contraceptives; Skilled birth attendance; Antenatal care; Anemia; Wasting; Health facilities
Easy-to-collect epidemiological information is critical for the more accurate estimation of the prevalence and burden of different non-communicable diseases around the world. Current measurement is restricted by limitations in existing measurement systems in the developing world and the lack of biometry tests for non-communicable diseases. Diagnosis based on self-reported signs and symptoms (“Symptomatic Diagnosis,” or SD) analyzed with computer-based algorithms may be a promising method for collecting timely and reliable information on non-communicable disease prevalence. The objective of this study was to develop and assess the performance of a symptom-based questionnaire to estimate prevalence of non-communicable diseases in low-resource areas.
As part of the Population Health Metrics Research Consortium study, we collected 1,379 questionnaires in Mexico from individuals who suffered from a non-communicable disease that had been diagnosed with gold standard diagnostic criteria or individuals who did not suffer from any of the 10 target conditions. To make the diagnosis of non-communicable diseases, we selected the Tariff method, a technique developed for verbal autopsy cause of death calculation. We assessed the performance of this instrument and analytical techniques at the individual and population levels.
The questionnaire revealed that the information on health care experience retrieved achieved 66.1% (95% uncertainty interval [UI], 65.6–66.5%) chance corrected concordance with true diagnosis of non-communicable diseases using health care experience and 0.826 (95% UI, 0.818–0.834) accuracy in its ability to calculate fractions of different causes. SD is also capable of outperforming the current estimation techniques for conditions estimated by questionnaire-based methods.
SD is a viable method for producing estimates of the prevalence of non-communicable diseases in areas with low health information infrastructure. This technology can provide higher-resolution prevalence data, more flexible data collection, and potentially individual diagnoses for certain conditions.
Electronic supplementary material
The online version of this article (doi:10.1186/s12916-014-0245-8) contains supplementary material, which is available to authorized users.
Automated methods; Mexico; Non-communicable diseases; Non-communicable diseases prevalence; Questionnaire
The fifth Millennium Development Goal (MDG 5) established the goal of a 75% reduction in the maternal mortality ratio (MMR; number of maternal deaths per 100 000 livebirths) between 1990 and 2015. We aimed to measure levels and track trends in maternal mortality, the key causes contributing to maternal death, and timing of maternal death with respect to delivery.
We used robust statistical methods including the Cause of Death Ensemble model (CODEm) to analyse a database of data for 7065 site-years and estimate the number of maternal deaths from all causes in 188 countries between 1990 and 2013. We estimated the number of pregnancy-related deaths caused by HIV on the basis of a systematic review of the relative risk of dying during pregnancy for HIV-positive women compared with HIV-negative women. We also estimated the fraction of these deaths aggravated by pregnancy on the basis of a systematic review. To estimate the numbers of maternal deaths due to nine different causes, we identified 61 sources from a systematic review and 943 site-years of vital registration data. We also did a systematic review of reports about the timing of maternal death, identifying 142 sources to use in our analysis. We developed estimates for each country for 1990–2013 using Bayesian meta-regression. We estimated 95% uncertainty intervals (UIs) for all values.
292 982 (95% UI 261 017–327 792) maternal deaths occurred in 2013, compared with 376 034 (343 483–407 574) in 1990. The global annual rate of change in the MMR was −0·3% (−1·1 to 0·6) from 1990 to 2003, and −2·7% (−3·9 to −1·5) from 2003 to 2013, with evidence of continued acceleration. MMRs reduced consistently in south, east, and southeast Asia between 1990 and 2013, but maternal deaths increased in much of sub-Saharan Africa during the 1990s. 2070 (1290–2866) maternal deaths were related to HIV in 2013, 0·4% (0·2–0·6) of the global total. MMR was highest in the oldest age groups in both 1990 and 2013. In 2013, most deaths occurred intrapartum or postpartum. Causes varied by region and between 1990 and 2013. We recorded substantial variation in the MMR by country in 2013, from 956·8 (685·1–1262·8) in South Sudan to 2·4 (1·6–3·6) in Iceland.
Global rates of change suggest that only 16 countries will achieve the MDG 5 target by 2015. Accelerated reductions since the Millennium Declaration in 2000 coincide with increased development assistance for maternal, newborn, and child health. Setting of targets and associated interventions for after 2015 will need careful consideration of regions that are making slow progress, such as west and central Africa.
Bill & Melinda Gates Foundation.
Liver cirrhosis is a major yet largely preventable and underappreciated cause of global health loss. Variations in cirrhosis mortality at the country level reflect differences in prevalence of risk factors such as alcohol use and hepatitis B and C infection. We estimated annual age-specific mortality from liver cirrhosis in 187 countries between 1980 and 2010.
We systematically collected vital registration and verbal autopsy data on liver cirrhosis mortality for the period 1980 to 2010. We corrected for misclassification of deaths, which included deaths attributed to improbable or nonfatal causes. We used ensemble models to estimate liver cirrhosis mortality with uncertainty by age, sex, country and year. We used out-of-sample predictive validity to select the optimal model.
Global liver cirrhosis deaths increased from around 676,000 (95% uncertainty interval: 452,863 to 1,004,530) in 1980 to over 1 million (1,029,042; 670,216 to 1,554,530) in 2010 (about 2% of the global total). Over the same period, the age-standardized cirrhosis mortality rate decreased by 22%. This was largely driven by decreasing cirrhosis mortality rates in China, the US and countries in Western Europe. In 2010, Egypt, followed by Moldova, had the highest age-standardized cirrhosis mortality rates, 72.7 and 71.2 deaths per 100,000, respectively, while Iceland had the lowest. In Egypt, almost one-fifth (18.1%) of all deaths in males 45- to 54-years old were due to liver cirrhosis. Liver cirrhosis mortality in Mexico is the highest in Latin America. In France and Italy, liver cirrhosis mortality fell by 50% to 60%; conversely, in the United Kingdom, mortality increased by about one-third. Mortality from liver cirrhosis was also comparatively high in Central Asia countries, particularly Mongolia, Uzbekistan and Kyrgyzstan, and in parts of sub-Saharan Africa, notably Gabon.
Liver cirrhosis is a significant cause of global health burden, with more than one million deaths in 2010. Our study identifies areas with high and/or rapidly increasing mortality where preventive measures to control and reduce liver cirrhosis risk factors should be urgently strengthened.
Please see related commentary: http://www.biomedcentral.com/1741-7015/12/159/abstract.
Electronic supplementary material
The online version of this article (doi:10.1186/s12916-014-0145-y) contains supplementary material, which is available to authorized users.
Liver cirrhosis; Mortality; Global; Alcohol; Hepatitis
Quantification of the disease burden caused by different risks informs prevention by providing an account of health loss different to that provided by a disease-by-disease analysis. No complete revision of global disease burden caused by risk factors has been done since a comparative risk assessment in 2000, and no previous analysis has assessed changes in burden attributable to risk factors over time.
We estimated deaths and disability-adjusted life years (DALYs; sum of years lived with disability [YLD] and years of life lost [YLL]) attributable to the independent effects of 67 risk factors and clusters of risk factors for 21 regions in 1990 and 2010. We estimated exposure distributions for each year, region, sex, and age group, and relative risks per unit of exposure by systematically reviewing and synthesising published and unpublished data. We used these estimates, together with estimates of cause-specific deaths and DALYs from the Global Burden of Disease Study 2010, to calculate the burden attributable to each risk factor exposure compared with the theoretical-minimum-risk exposure. We incorporated uncertainty in disease burden, relative risks, and exposures into our estimates of attributable burden.
In 2010, the three leading risk factors for global disease burden were high blood pressure (7·0% [95% uncertainty interval 6·2–7·7] of global DALYs), tobacco smoking including second-hand smoke (6·3% [5·5–7·0]), and alcohol use (5·5% [5·0–5·9]). In 1990, the leading risks were childhood underweight (7·9% [6·8–9·4]), household air pollution from solid fuels (HAP; 7·0% [5·6–8·3]), and tobacco smoking including second-hand smoke (6·1% [5·4–6·8]). Dietary risk factors and physical inactivity collectively accounted for 10·0% (95% UI 9·2–10·8) of global DALYs in 2010, with the most prominent dietary risks being diets low in fruits and those high in sodium. Several risks that primarily affect childhood communicable diseases, including unimproved water and sanitation and childhood micronutrient deficiencies, fell in rank between 1990 and 2010, with unimproved water we and sanitation accounting for 0·9% (0·4–1·6) of global DALYs in 2010. However, in most of sub-Saharan Africa childhood underweight, HAP, and non-exclusive and discontinued breastfeeding were the leading risks in 2010, while HAP was the leading risk in south Asia. The leading risk factor in Eastern Europe, most of Latin America, and southern sub-Saharan Africa in 2010 was alcohol use; in most of Asia, North Africa and Middle East, and central Europe it was high blood pressure. Despite declines, tobacco smoking including second-hand smoke remained the leading risk in high-income north America and western Europe. High body-mass index has increased globally and it is the leading risk in Australasia and southern Latin America, and also ranks high in other high-income regions, North Africa and Middle East, and Oceania.
Worldwide, the contribution of different risk factors to disease burden has changed substantially, with a shift away from risks for communicable diseases in children towards those for non-communicable diseases in adults. These changes are related to the ageing population, decreased mortality among children younger than 5 years, changes in cause-of-death composition, and changes in risk factor exposures. New evidence has led to changes in the magnitude of key risks including unimproved water and sanitation, vitamin A and zinc deficiencies, and ambient particulate matter pollution. The extent to which the epidemiological shift has occurred and what the leading risks currently are varies greatly across regions. In much of sub-Saharan Africa, the leading risks are still those associated with poverty and those that affect children.
Bill & Melinda Gates Foundation.
To identify the current clinical, socio-demographic and obstetric factors associated with the various types of delivery strategies in Mexico.
Materials and Methods
This is a cross-sectional study based on the 2012 National Health and Nutrition Survey (ENSANUT) of 6,736 women aged 12 to 49 years. Delivery types discussed in this paper include vaginal delivery, emergency cesarean section and planned cesarean section. Using bivariate analyses, sub-population group differences were identified. Logistic regression models were applied, including both binary and multinomial outcome variables from the survey. The logistic regression results identify those covariates associated with the type of delivery.
53.1% of institutional births in the period 2006 through 2012 were vaginal deliveries, 46.9% were either a planned or emergency cesarean sections. The highest rates of this procedure were among women who reported a complication during delivery (OR: 4.21; 95%CI: 3.66–4.84), between the ages of 35 and 49 at the time of their last child birth (OR: 2.54; 95%CI: 2.02–3.20) and women receiving care through private healthcare providers during delivery (OR: 2.36; 95%CI: 1.84–3.03).
The existence of different socio-demographic and obstetric profiles among women who receive care for vaginal or cesarean delivery, are supported by the findings of the present study. The frequency of vaginal delivery is higher in indigenous women, when the care provider is public and, in women with two or more children at time of the most recent child birth. Planned cesarean deliveries are positively associated with years of schooling, a higher socioeconomic level, and higher age. The occurrence of emergency cesarean sections is elevated in women with a diagnosis of a health issue during pregnancy or delivery, and it is reduced in highly marginalized settings.
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.
Mortality; Causes of death; Vital statistics; Civil registration; Vital registration; Data quality; Health information systems
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
APETALA3; B-class gene; flower morphogenesis; hormone regulation; Solanum lycopersicum; STAMENLESS; tomato.
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.
Verbal autopsy; VA; Validation; Cause of death; Symptom pattern; Random forests; InterVA; King-Lu; Tariff
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.
organophosphates; spatial learning; oxidative stress; acetylcholinesterase; acylpeptide hydrolase; read-through AChE.
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.
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.
cause of death; ensemble models; predictive validity; spatial-temporal models; maternal mortality; Global Burden of Disease
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.
Verbal autopsy; InterVA; validation
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.
Verbal autopsy; VA; validation; Philippines; Tanzania; India; Mexico; gold standard; cause of death
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.
Verbal autopsy; metrics; validation
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.
Verbal autopsy; Symptom Pattern; validation; gold standard
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.
Verbal autopsy; cause of death certification; validation; physician review
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.
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.
Insertional mutagenesis; Solanum pennellii; Enhancer trap; Salinity; Drought; Gene tagging
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.
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.
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.