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Measurements of health indicators are rarely available for every population and period of interest, and available data may not be comparable. The Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER) define best reporting practices for studies that calculate health estimates for multiple populations (in time or space) using multiple information sources. Health estimates that fall within the scope of GATHER include all quantitative population-level estimates (including global, regional, national, or subnational estimates) of health indicators, including indicators of health status, incidence and prevalence of diseases, injuries, and disability and functioning; and indicators of health determinants, including health behaviours and health exposures. GATHER comprises a checklist of 18 items that are essential for best reporting practice. A more detailed explanation and elaboration document, describing the interpretation and rationale of each reporting item along with examples of good reporting, is available on the GATHER website (http://gather-statement.org).

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BACKGROUND: Trends in food availability and metabolic risk factors in Brazil suggest a shift toward unhealthy dietary patterns and increased cardiometabolic disease risk, yet little is known about the impact of dietary and metabolic risk factors on cardiometabolic mortality in Brazil. METHODS: Based on data from Global Burden of Disease (GBD) Study, we used comparative risk assessment to estimate the burden of 11 dietary and 4 metabolic risk factors on mortality due to cardiovascular diseases and diabetes in Brazil in 2010. Information on national diets and metabolic risks were obtained from the Brazilian Household Budget Survey, the Food and Agriculture Organization database, and large observational studies including Brazilian adults. Relative risks for each risk factor were obtained from meta-analyses of randomized trials or prospective cohort studies; and disease-specific mortality from the GBD 2010 database. We quantified uncertainty using probabilistic simulation analyses, incorporating uncertainty in dietary and metabolic data and relative risks by age and sex. Robustness of findings was evaluated by sensitivity to varying feasible optimal levels of each risk factor. RESULTS: In 2010, high systolic blood pressure (SBP) and suboptimal diet were the largest contributors to cardiometabolic deaths in Brazil, responsible for 214,263 deaths (95% uncertainty interval [UI]: 195,073 to 233,936) and 202,949 deaths (95% UI: 194,322 to 211,747), respectively. Among individual dietary factors, low intakes of fruits and whole grains and high intakes of sodium were the largest contributors to cardiometabolic deaths. For premature cardiometabolic deaths (before age 70 years, representing 40% of cardiometabolic deaths), the leading risk factors were suboptimal diet (104,169 deaths; 95% UI: 99,964 to 108,002), high SBP (98,923 deaths; 95%UI: 92,912 to 104,609) and high body-mass index (BMI) (42,643 deaths; 95%UI: 40,161 to 45,111). CONCLUSION: suboptimal diet, high SBP, and high BMI are major causes of cardiometabolic death in Brazil, informing priorities for policy initiatives.

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BACKGROUND: Babies with low birthweight (<2500 g) are at increased risk of early mortality. However, low birthweight includes babies born preterm and with fetal growth restriction, and not all these infants have a birthweight less than 2500 g. We estimated the neonatal and infant mortality associated with these two characteristics in low-income and middle-income countries. METHODS: For this pooled analysis, we searched all available studies and identified 20 cohorts (providing data for 2,015,019 livebirths) from Asia, Africa, and Latin America that recorded data for birthweight, gestational age, and vital statistics through 28 days of life. Study dates ranged from 1982 through to 2010. We calculated relative risks (RR) and risk differences (RD) for mortality associated with preterm birth (<32 weeks, 32 weeks to <34 weeks, 34 weeks to <37 weeks), small-for-gestational-age (SGA; babies with birthweight in the lowest third percentile and between the third and tenth percentile of a US reference population), and preterm and SGA combinations. FINDINGS: Pooled overall RRs for preterm were 6·82 (95% CI 3·56-13·07) for neonatal mortality and 2·50 (1·48-4·22) for post-neonatal mortality. Pooled RRs for babies who were SGA (with birthweight in the lowest tenth percentile of the reference population) were 1·83 (95% CI 1·34-2·50) for neonatal mortality and 1·90 (1·32-2·73) for post-neonatal mortality. The neonatal mortality risk of babies who were both preterm and SGA was higher than that of babies with either characteristic alone (15·42; 9·11-26·12). INTERPRETATION: Many babies in low-income and middle-income countries are SGA. Preterm birth affects a smaller number of neonates than does SGA, but is associated with a higher mortality risk. The mortality risks associated with both characteristics extend beyond the neonatal period. Differentiation of the burden and risk of babies born preterm and SGA rather than with low birthweight could guide prevention and management strategies to speed progress towards Millennium Development Goal 4--the reduction of child mortality. FUNDING: Bill & Melinda Gates Foundation.

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BACKGROUND: Child undernutrition affects millions of children globally. We investigated associations between suboptimal growth and mortality by pooling large studies. METHODS: Pooled analysis involving children 1 week to 59 months old in 10 prospective studies in Africa, Asia and South America. Utilizing most recent measurements, we calculated weight-for-age, height/length-for-age and weight-for-height/length Z scores, applying 2006 WHO Standards and the 1977 NCHS/WHO Reference. We estimated all-cause and cause-specific mortality hazard ratios (HR) using proportional hazards models comparing children with mild (-2≤Z<-1), moderate (-3≤Z<-2), or severe (Z<-3) anthropometric deficits with the reference category (Z≥-1). RESULTS: 53 809 children were eligible for this re-analysis and contributed a total of 55 359 person-years, during which 1315 deaths were observed. All degrees of underweight, stunting and wasting were associated with significantly higher mortality. The strength of association increased monotonically as Z scores decreased. Pooled mortality HR was 1.52 (95% Confidence Interval 1.28, 1.81) for mild underweight; 2.63 (2.20, 3.14) for moderate underweight; and 9.40 (8.02, 11.03) for severe underweight. Wasting was a stronger determinant of mortality than stunting or underweight. Mortality HR for severe wasting was 11.63 (9.84, 13.76) compared with 5.48 (4.62, 6.50) for severe stunting. Using older NCHS standards resulted in larger HRs compared with WHO standards. In cause-specific analyses, all degrees of anthropometric deficits increased the hazards of dying from respiratory tract infections and diarrheal diseases. The study had insufficient power to precisely estimate effects of undernutrition on malaria mortality. CONCLUSIONS: All degrees of anthropometric deficits are associated with increased risk of under-five mortality using the 2006 WHO Standards. Even mild deficits substantially increase mortality, especially from infectious diseases.

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

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Oportunidades, a conditional cash-transfer program instituted in Mexico in 1997, provides cash incentives to mothers to invest in the health and education of family members. Drawing from data gathered by Mexico's National Institute of Public Health, this study assesses the effect of the program on contraceptive use and birth spacing among titulares (female household heads) living in rural areas during the experimental period, 1998-2000, and during 2000-03, after incorporation of the control group. In 2000, titulares were more likely to use modern contraceptives than were women in the control group, although by 2003 all beneficiaries had the same probability of use. Change in autonomy was not a mediator, although baseline autonomy modified the program's influence on contraceptive use. Cox proportional hazard models produced estimates that birth spacing was similar between the beneficiaries and controls. Inconsistent findings may be the result of the way contraceptive use was defined in this study. Findings from this study may be useful for helping program planners better understand the role of conditional cash transfers in modifying family planning and fertility among poor rural women in Latin America.

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The disparities in the burden of ill health caused by environmental risks should be an important consideration beyond their aggregate population effects. We used comparative risk assessment methods to calculate the mortality effects of unsafe water and sanitation, indoor air pollution from household solid fuel use, and ambient urban particulate matter pollution in Mexico. We also estimated the disparities in mortality caused by each risk factor, across municipios (counties) of residence and by municipio socioeconomic status (SES). Data sources for the analysis were the national census, population-representative health surveys, and air quality monitoring for risk factor exposure; systematic reviews and meta-analyses of epidemiological studies for risk factor effects; and vital statistics for disease-specific mortality. During 2001-2005, unsafe water and sanitation, household solid fuel use, and urban particulate matter pollution were responsible for 3,000, 3,600, and 7,600 annual deaths, respectively. Annual child mortality rates would decrease by 0.2, 0.1, and 0.1 per 1,000 children, and life expectancy would increase by 1.0, 1.2, and 2.4 months, respectively, in the absence of these environmental exposures. Together, these risk factors caused 10.6% of child deaths in the lowest-SES communities (0.9 deaths per 1,000 children), but only 4.0% in communities in the highest-SES ones (0.1 per 1,000). In the 50 most-affected municipios, these 3 exposures were responsible for 3.2 deaths per 1,000 children and a 10-month loss of life expectancy. The large disparities in the mortality effects of these 3 environmental risks should form the basis of interventions and environmental monitoring programs.

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BACKGROUND: Rates of diseases and injuries and the effects of their risk factors can have substantial subnational heterogeneity, especially in middle-income countries like Mexico. Subnational analysis of the burden of diseases, injuries, and risk factors can improve characterization of the epidemiological transition and identify policy priorities. METHODS AND FINDINGS: We estimated deaths and loss of healthy life years (measured in disability-adjusted life years [DALYs]) in 2004 from a comprehensive list of diseases and injuries, and 16 major risk factors, by sex and age for Mexico and its states. Data sources included the vital statistics, national censuses, health examination surveys, and published epidemiological studies. Mortality statistics were adjusted for underreporting, misreporting of age at death, and for misclassification and incomparability of cause-of-death assignment. Nationally, noncommunicable diseases caused 75% of total deaths and 68% of total DALYs, with another 14% of deaths and 18% of DALYs caused by undernutrition and communicable, maternal, and perinatal diseases. The leading causes of death were ischemic heart disease, diabetes mellitus, cerebrovascular disease, liver cirrhosis, and road traffic injuries. High body mass index, high blood glucose, and alcohol use were the leading risk factors for disease burden, causing 5.1%, 5.0%, and 7.3% of total burden of disease, respectively. Mexico City had the lowest mortality rates (4.2 per 1,000) and the Southern region the highest (5.0 per 1,000); under-five mortality in the Southern region was nearly twice that of Mexico City. In the Southern region undernutrition and communicable, maternal, and perinatal diseases caused 23% of DALYs; in Chiapas, they caused 29% of DALYs. At the same time, the absolute rates of noncommunicable disease and injury burdens were highest in the Southern region (105 DALYs per 1,000 population versus 97 nationally for noncommunicable diseases; 22 versus 19 for injuries). CONCLUSIONS: Mexico is at an advanced stage in the epidemiologic transition, with the majority of the disease and injury burden from noncommunicable diseases. A unique characteristic of the epidemiological transition in Mexico is that overweight and obesity, high blood glucose, and alcohol use are responsible for larger burden of disease than other noncommunicable disease risks such as tobacco smoking. The Southern region is least advanced in the epidemiological transition and suffers from the largest burden of ill health in all disease and injury groups.

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Although epidemiologic studies have established the relationship between Helicobacter pylori and gastric cancer and promising results that H. pylori treatment can reduce cancer incidence among individuals without preexisting precancerous lesions, there is no consensus on whether screening for H. pylori should be conducted. Our objective was to synthesize the available data to develop and empirically calibrate a mathematical model of gastric cancer and H. pylori in China and Colombia that could be used to provide qualitative insight into the benefits and cost-effectiveness of primary and secondary gastric cancer prevention strategies. The model represents the natural history of noncardia intestinal type gastric adenocarcinomas as a sequence of transitions among health states (e.g., normal gastric mucosa, chronic nonatrophic gastritis, gastric atrophy, intestinal metaplasia, dysplasia, and gastric cancer) stratified by H. pylori status. Initial plausible ranges for each parameter were established using data from published literature. A likelihood-based empirical calibration approach was used to identify multiple good-fitting parameter sets that were consistent with epidemiologic data. We then used these parameter sets to estimate a range of likely outcomes associated with H. pylori screening. This modeling approach allows for parameter uncertainty surrounding the natural history of H. pylori and gastric cancer to be reflected in the results of comparative analyses of different gastric cancer prevention strategies. As better data become available, the model can be refined and recalibrated, and, as such, be used as an iterative tool to assess the likely health and economic outcomes associated with gastric cancer prevention strategies.

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OBJECTIVE: The aim of this study was to increase the cross-state comparability of diabetes mortality statistics related in the U.S. and Mexico. RESEARCH DESIGN AND METHODS: We used multinomial logistic regression to estimate the effects of individual and community factors on a death for which diabetes was recorded as one of the multiple contributing causes of death (MCD) being assigned to diabetes as the underlying cause of death (UCD) versus assignment to cardiovascular, other noncommunicable, or communicable diseases. We used the model to estimate state-level diabetes death rates that are standardized in the individual and community factors. RESULTS: Deaths with diabetes as one of the MCD were more likely to be assigned to cardiovascular causes as the UCD if they occurred in hospitals or if an autopsy was performed and if the decedents were from states with higher BMI and systolic blood pressure, were more educated, or had insurance. Adjusting for individual- and community-level factors substantially increased the cross-state correlation of diabetes as the UCD and diabetes as one of the MCD mortality rates. The adjustment also reduced the number of direct diabetes deaths by 10% in the U.S. and by 24% in Mexico. In the U.S., deaths with diabetes as the UCD declined most in Utah, New Mexico, New Jersey, and Louisiana and increased in California and Hawaii. In Mexico, the numbers of adjusted diabetes deaths were smaller than those observed in all states by 3-34%. An additional 126,300 deaths due to ischemic heart disease and stroke in the U.S. and 19,497 in Mexico were attributable to high blood glucose. CONCLUSIONS: There is a need to improve the comparability of diabetes cause-of-death assignment, especially in relation to cardiovascular diseases.

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

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La definición explícita de prioridades en intervenciones de salud representa una oportunidad para México de equilibrar la presión y la complejidad de una transición epidemiológica avanzada, con políticas basadas en evidencias generadas por la inquietud de cómo optimizar el uso de los recursos escasos para mejorar la salud de la población. La experiencia mexicana en la definición de prioridades describe cómo los enfoques analíticos estandarizados en la toma de decisiones, principalmente los de análisis de la carga de la enfermedad y de costo-efectividad, se combinan con otros criterios -tales como dar respuesta a las expectativas legítimas no médicas de los pacientes y asegurar un financiamiento justo para los hogares-, para diseñar e implementar un grupo de tres paquetes diferenciados de intervenciones de salud. Éste es un proceso clave dentro de un conjunto más amplio de elementos de reforma dirigidos a extender el aseguramiento en salud, especialmente a los pobres. Las implicaciones más relevantes en el ámbito de políticas públicas incluyen lecciones sobre el uso de las herramientas analíticas disponibles y probadas para definir prioridades nacionales de salud; la utilidad de resultados que definan prioridades para guiar el desarrollo de capacidades a largo plazo; la importancia de favorecer un enfoque para institucionalizar el análisis ex-ante de costo-efectividad; y la necesidad del fortalecimiento de la capacidad técnica local como un elemento esencial para equilibrar los argumentos sobre maximización de la salud con criterios no relacionados con la salud en el marco de un ejercicio sistemático y transparente.

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

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

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