Reducing Acute Hospitalizations at High-Performing CPC+ Primary Care Practice Sites: Strategies, Activities, and Facilitators.

PURPOSE: Despite evidence suggesting that high-quality primary care can prevent unnecessary hospitalizations, many primary care practices face challenges in achieving this goal, and there is little guidance identifying effective strategies for reducing hospitalization rates. We aimed to understand how practices in the Comprehensive Primary Care Plus (CPC+) program substantially reduced their acute hospitalization rate (AHR) over 2 years. METHODS: We used Bayesian analyses to identify the CPC+ practice sites having the highest probability of achieving a substantial reduction in the adjusted Medicare AHR between 2016 and 2018 (referred to here as AHR high performers). We then conducted telephone interviews with 64 respondents at 14 AHR high-performer sites and undertook within- and cross-case comparative analysis. RESULTS: The 14 AHR high performers experienced a 6% average decrease (range, 4% to 11%) in their Medicare AHR over the 2-year period. They credited various care delivery activities aligned with 3 strategies for reducing AHR: (1) improving and promoting prompt access to primary care, (2) identifying patients at high risk for hospitalization and addressing their needs with enhanced care management, and (3) expanding the breadth and depth of services offered at the practice site. They also identified facilitators of these strategies: enhanced payments through CPC+, prior primary care practice transformation experience, use of data to identify high-value activities for patient subgroups, teamwork, and organizational support for innovation. CONCLUSIONS: The AHR high performers observed that strengthening the local primary care infrastructure through practice-driven, targeted changes in access, care management, and comprehensiveness of care can meaningfully reduce acute hospitalizations. Other primary care practices taking on the challenging work of reducing hospitalizations can learn from CPC+ practices and may consider similar strategies, selecting activities that fit their context, personnel, patient population, and available resources.

Speaking on Data's Behalf: What Researchers Say and How Audiences Choose.

BACKGROUND: Bayesian statistics have become popular in the social sciences, in part because they are thought to present more useful information than traditional frequentist statistics. Unfortunately, little is known about whether or how interpretations of frequentist and Bayesian results differ. OBJECTIVES: We test whether presenting Bayesian or frequentist results based on the same underlying data influences the decisions people made. RESEARCH DESIGN: Participants were randomly assigned to read Bayesian and frequentist interpretations of hypothetical evaluations of new education technologies of various degrees of uncertainty, ranging from posterior probabilities of 99.8% to 52.9%, which have equivalent frequentist p values of .001 and .65, respectively. SUBJECTS: Across three studies, 933 U.S. adults were recruited from Amazon Mechanical Turk. MEASURES: The primary outcome was the proportion of participants who recommended adopting the new technology. We also measured respondents' certainty in their choice and (in Study 3) how easy it was to understand the results. RESULTS: When presented with Bayesian results, participants were more likely to recommend switching to the new technology. This finding held across all degrees of uncertainty, but especially when the frequentist results reported a p value >.05. Those who recommended change based on Bayesian results were more certain about their choice. All respondents reported that the Bayesian display was easier to understand. CONCLUSIONS: Presenting the same data in either frequentist or Bayesian terms can influence the decisions that people make. This finding highlights the importance of understanding the impact of the statistical results on how audiences interpret evaluation results.

Beyond "Treatment Versus Control": How Bayesian Analysis Makes Factorial Experiments Feasible in Education Research.

BACKGROUND: Researchers often wish to test a large set of related interventions or approaches to implementation. A factorial experiment accomplishes this by examining not only basic treatment-control comparisons but also the effects of multiple implementation "factors" such as different dosages or implementation strategies and the interactions between these factor levels. However, traditional methods of statistical inference may require prohibitively large sample sizes to perform complex factorial experiments. OBJECTIVES: We present a Bayesian approach to factorial design. Through the use of hierarchical priors and partial pooling, we show how Bayesian analysis substantially increases the precision of estimates in complex experiments with many factors and factor levels, while controlling the risk of false positives from multiple comparisons. RESEARCH DESIGN: Using an experiment we performed for the U.S. Department of Education as a motivating example, we perform power calculations for both classical and Bayesian methods. We repeatedly simulate factorial experiments with a variety of sample sizes and numbers of treatment arms to estimate the minimum detectable effect (MDE) for each combination. RESULTS: The Bayesian approach yields substantially lower MDEs when compared with classical methods for complex factorial experiments. For example, to test 72 treatment arms (five factors with two or three levels each), a classical experiment requires nearly twice the sample size as a Bayesian experiment to obtain a given MDE. CONCLUSIONS: Bayesian methods are a valuable tool for researchers interested in studying complex interventions. They make factorial experiments with many treatment arms vastly more feasible.

Revolutionizing Estimation and Inference for Program Evaluation Using Bayesian Methods.

BACKGROUND: Policy makers seek to replace the "thumbs up-thumbs down" of conventional hypothesis testing with statements about the probability that program effects on key outcomes exceed policy-relevant thresholds. OBJECTIVE: We develop a Bayesian model that addresses the shortcomings of a typical frequentist approach to estimating the effects of the Comprehensive Primary Care (CPC) initiative, a Centers for Medicare and Medicaid Services demonstration. We compare findings from the two approaches to illustrate the relative merits of introducing additional assumptions through Bayesian methods. RESEARCH DESIGN: We apply Bayesian and frequentist methods to estimate the effects of CPC on total Medicare expenditures per beneficiary per month for Medicare beneficiaries attributed to participating practices. Under both paradigms, we estimated program effects using difference-in-differences regressions comparing the change in Medicare expenditures between baseline and follow-up for Medicare patients attributed to 497 primary care practices participating in CPC to Medicare patients attributed to 908 propensity score-matched comparison practices. RESULTS: Results from the Bayesian and frequentist models are comparable for the overall sample, but in regional subsamples, the Bayesian model produces more precise etimates that exhibit less variation over time. The Bayesian results also permit probabilistic inference about the magnitudes of effects, offering policy makers the ability to draw conclusions about practically meaningful thresholds. CONCLUSIONS: Carefully developed Bayesian models can enhance precision and plausibility and offer a more nuanced understanding of where and when program effects occur, without imposing undue assumptions. At the same time, these methods frame conclusions in flexible, intuitive terms that respond directly to policy makers' needs.

Nrf2 mitigates LRRK2- and α-synuclein-induced neurodegeneration by modulating proteostasis.

Mutations in leucine-rich repeat kinase 2 (LRRK2) and α-synuclein lead to Parkinson's disease (PD). Disruption of protein homeostasis is an emerging theme in PD pathogenesis, making mechanisms to reduce the accumulation of misfolded proteins an attractive therapeutic strategy. We determined if activating nuclear factor erythroid 2-related factor (Nrf2), a potential therapeutic target for neurodegeneration, could reduce PD-associated neuron toxicity by modulating the protein homeostasis network. Using a longitudinal imaging platform, we visualized the metabolism and location of mutant LRRK2 and α-synuclein in living neurons at the single-cell level. Nrf2 reduced PD-associated protein toxicity by a cell-autonomous mechanism that was time-dependent. Furthermore, Nrf2 activated distinct mechanisms to handle different misfolded proteins. Nrf2 decreased steady-state levels of α-synuclein in part by increasing α-synuclein degradation. In contrast, Nrf2 sequestered misfolded diffuse LRRK2 into more insoluble and homogeneous inclusion bodies. By identifying the stress response strategies activated by Nrf2, we also highlight endogenous coping responses that might be therapeutically bolstered to treat PD.

Estimating the prevalence of transmitted HIV drug resistance using pooled samples.

In many resource-poor countries, hiv-infected patients receive a standardized antiretroviral cocktail. In these settings, population-level surveillance of drug resistance is needed to characterize the prevalence of resistance mutations and to enable antiretroviral therapy programs to select the optimal regimen for their local population. The surveillance strategy currently recommended by the World Health Organization is prohibitively expensive in some settings and may not provide a sufficiently precise rendering of the emergence of drug resistance. By using a novel assay on pooled sera samples, we decrease surveillance costs while simultaneously increasing the accuracy of drug resistance prevalence estimates for an important mutation that impacts first-line antiretroviral therapy. We present a Bayesian model for pooled-testing data that garners more information from each resistance assay conducted, compared with individual testing. We expand on previous pooling methods to account for uncertainty about the population distribution of within-subject resistance levels. In addition, our model accounts for measurement error of the resistance assay, and this added uncertainty naturally propagates through the Bayesian model to our inference on the prevalence parameter. We conduct a simulation study that informs our pool size recommendations and that shows that this model renders the prevalence parameter identifiable in instances when an existing non-model-based estimator fails.

DNA repair factor BRCA1 depletion occurs in Alzheimer brains and impairs cognitive function in mice.

Maintaining DNA integrity is vital for all cells and organisms. Defective DNA repair may contribute to neurological disorders, including Alzheimer's disease (AD). We found reduced levels of BRCA1, but not of other DNA repair factors, in the brains of AD patients and human amyloid precursor protein (hAPP) transgenic mice. Amyloid-ß oligomers reduced BRCA1 levels in primary neuronal cultures. In wild-type mice, knocking down neuronal BRCA1 in the dentate gyrus caused increased DNA double-strand breaks, neuronal shrinkage, synaptic plasticity impairments, and learning and memory deficits, but not apoptosis. Low levels of hAPP/Amyloid-ß overexpression exacerbated these effects. Physiological neuronal activation increased BRCA1 levels, whereas stimulating predominantly extrasynaptic N-methyl-D-aspartate receptors promoted the proteasomal degradation of BRCA1. We conclude that BRCA1 is regulated by neuronal activity, protects the neuronal genome, and critically supports neuronal integrity and cognitive functions. Pathological accumulation of Aß depletes neuronal BRCA1, which may contribute to cognitive deficits in AD.

Trends and mortality effects of vitamin A deficiency in children in 138 low-income and middle-income countries between 1991 and 2013: a pooled analysis of population-based surveys.

BACKGROUND: Vitamin A deficiency is a risk factor for blindness and for mortality from measles and diarrhoea in children aged 6-59 months. We aimed to estimate trends in the prevalence of vitamin A deficiency between 1991 and 2013 and its mortality burden in low-income and middle-income countries. METHODS: We collated 134 population-representative data sources from 83 countries with measured serum retinol concentration data. We used a Bayesian hierarchical model to estimate the prevalence of vitamin A deficiency, defined as a serum retinol concentration lower than 0·70 µmol/L. We estimated the relative risks (RRs) for the effects of vitamin A deficiency on mortality from measles and diarrhoea by pooling effect sizes from randomised trials of vitamin A supplementation. We used information about prevalences of deficiency, RRs, and number of cause-specific child deaths to estimate deaths attributable to vitamin A deficiency. All analyses included a systematic quantification of uncertainty. FINDINGS: In 1991, 39% (95% credible interval 27-52) of children aged 6-59 months in low-income and middle-income countries were vitamin A deficient. In 2013, the prevalence of deficiency was 29% (17-42; posterior probability [PP] of being a true decline=0·81). Vitamin A deficiency significantly declined in east and southeast Asia and Oceania from 42% (19-70) to 6% (1-16; PP>0·99); a decline in Latin America and the Caribbean from 21% (11-33) to 11% (4-23; PP=0·89) also occurred. In 2013, the prevalence of deficiency was highest in sub-Saharan Africa (48%; 25-75) and south Asia (44%; 13-79). 94 500 (54 200-146 800) deaths from diarrhoea and 11 200 (4300-20 500) deaths from measles were attributable to vitamin A deficiency in 2013, which accounted for 1·7% (1·0-2·6) of all deaths in children younger than 5 years in low-income and middle-income countries. More than 95% of these deaths occurred in sub-Saharan Africa and south Asia. INTERPRETATION: Vitamin A deficiency remains prevalent in south Asia and sub-Saharan Africa. Deaths attributable to this deficiency have decreased over time worldwide, and have been almost eliminated in regions other than south Asia and sub-Saharan Africa. This new evidence for both prevalence and absolute burden of vitamin A deficiency should be used to reconsider, and possibly revise, the list of priority countries for high-dose vitamin A supplementation such that a country's priority status takes into account both the prevalence of deficiency and the expected mortality benefits of supplementation. FUNDIN: Bill & Melinda Gates Foundation, Grand Challenges Canada, UK Medical Research Council.

Regional functional connectivity predicts distinct cognitive impairments in Alzheimer's disease spectrum.

Understanding neural network dysfunction in neurodegenerative disease is imperative to effectively develop network-modulating therapies. In Alzheimer's disease (AD), cognitive decline associates with deficits in resting-state functional connectivity of diffuse brain networks. The goal of the current study was to test whether specific cognitive impairments in AD spectrum correlate with reduced functional connectivity of distinct brain regions. We recorded resting-state functional connectivity of alpha-band activity in 27 patients with AD spectrum--22 patients with probable AD (5 logopenic variant primary progressive aphasia, 7 posterior cortical atrophy, and 10 early-onset amnestic/dysexecutive AD) and 5 patients with mild cognitive impairment due to AD. We used magnetoencephalographic imaging (MEGI) to perform an unbiased search for regions where patterns of functional connectivity correlated with disease severity and cognitive performance. Functional connectivity measured the strength of coherence between a given region and the rest of the brain. Decreased neural connectivity of multiple brain regions including the right posterior perisylvian region and left middle frontal cortex correlated with a higher degree of disease severity. Deficits in executive control and episodic memory correlated with reduced functional connectivity of the left frontal cortex, whereas visuospatial impairments correlated with reduced functional connectivity of the left inferior parietal cortex. Our findings indicate that reductions in region-specific alpha-band resting-state functional connectivity are strongly correlated with, and might contribute to, specific cognitive deficits in AD spectrum. In the future, MEGI functional connectivity could be an important biomarker to map and follow defective networks in the early stages of AD.

Tau reduction prevents disease in a mouse model of Dravet syndrome.

OBJECTIVE: Reducing levels of the microtubule-associated protein tau has shown promise as a potential treatment strategy for diseases with secondary epileptic features such as Alzheimer disease. We wanted to determine whether tau reduction may also be of benefit in intractable genetic epilepsies. METHODS: We studied a mouse model of Dravet syndrome, a severe childhood epilepsy caused by mutations in the human SCN1A gene encoding the voltage-gated sodium channel subunit Nav 1.1. We genetically deleted 1 or 2 Tau alleles in mice carrying an Nav 1.1 truncation mutation (R1407X) that causes Dravet syndrome in humans, and examined their survival, epileptic activity, related hippocampal alterations, and behavioral abnormalities using observation, electroencephalographic recordings, acute slice electrophysiology, immunohistochemistry, and behavioral assays. RESULTS: Tau ablation prevented the high mortality of Dravet mice and reduced the frequency of spontaneous and febrile seizures. It reduced interictal epileptic spikes in vivo and drug-induced epileptic activity in brain slices ex vivo. Tau ablation also prevented biochemical changes in the hippocampus indicative of epileptic activity and ameliorated abnormalities in learning and memory, nest building, and open field behaviors in Dravet mice. Deletion of only 1 Tau allele was sufficient to suppress epileptic activity and improve survival and nesting performance. INTERPRETATION: Tau reduction may be of therapeutic benefit in Dravet syndrome and other intractable genetic epilepsies.

A taxonomic signature of obesity in the microbiome? Getting to the guts of the matter.

Obesity is an important and intractable public health problem. In addition to the well-known risk factors of behavior, diet, and genetics, gut microbial communities were recently identified as another possible source of risk and a potential therapeutic target. However, human and animal-model studies have yielded conflicting results about the precise nature of associations between microbiome composition and obesity. In this paper, we use publicly available data from the Human Microbiome Project (HMP) and MetaHIT, both surveys of healthy adults that include obese individuals, plus two smaller studies that specifically examined lean versus obese adults. We find that inter-study variability in the taxonomic composition of stool microbiomes far exceeds differences between lean and obese individuals within studies. Our analyses further reveal a high degree of variability in stool microbiome composition and diversity across individuals. While we confirm the previously published small, but statistically significant, differences in phylum-level taxonomic composition between lean and obese individuals in several cohorts, we find no association between BMI and taxonomic composition of stool microbiomes in the larger HMP and MetaHIT datasets. We explore a range of different statistical techniques and show that this result is robust to the choice of methodology. Differences between studies are likely due to a combination of technical and clinical factors. We conclude that there is no simple taxonomic signature of obesity in the microbiota of the human gut.

The global cardiovascular risk transition: associations of four metabolic risk factors with national income, urbanization, and Western diet in 1980 and 2008.

BACKGROUND: It is commonly assumed that cardiovascular disease risk factors are associated with affluence and Westernization. We investigated the associations of body mass index (BMI), fasting plasma glucose, systolic blood pressure, and serum total cholesterol with national income, Western diet, and, for BMI, urbanization in 1980 and 2008. METHODS AND RESULTS: Country-level risk factor estimates for 199 countries between 1980 and 2008 were from a previous systematic analysis of population-based data. We analyzed the associations between risk factors and per capita national income, a measure of Western diet, and, for BMI, the percentage of the population living in urban areas. In 1980, there was a positive association between national income and population mean BMI, systolic blood pressure, and total cholesterol. By 2008, the slope of the association between national income and systolic blood pressure became negative for women and zero for men. Total cholesterol was associated with national income and Western diet in both 1980 and 2008. In 1980, BMI rose with national income and then flattened at ≈Int$7000; by 2008, the relationship resembled an inverted U for women, peaking at middle-income levels. BMI had a positive relationship with the percentage of urban population in both 1980 and 2008. Fasting plasma glucose had weaker associations with these country macro characteristics, but it was positively associated with BMI. CONCLUSIONS: The changing associations of metabolic risk factors with macroeconomic variables indicate that there will be a global pandemic of hyperglycemia and diabetes mellitus, together with high blood pressure in low-income countries, unless effective lifestyle and pharmacological interventions are implemented.

Global marine bacterial diversity peaks at high latitudes in winter.

Genomic approaches to characterizing bacterial communities are revealing significant differences in diversity and composition between environments. But bacterial distributions have not been mapped at a global scale. Although current community surveys are way too sparse to map global diversity patterns directly, there is now sufficient data to fit accurate models of how bacterial distributions vary across different environments and to make global scale maps from these models. We apply this approach to map the global distributions of bacteria in marine surface waters. Our spatially and temporally explicit predictions suggest that bacterial diversity peaks in temperate latitudes across the world's oceans. These global peaks are seasonal, occurring 6 months apart in the two hemispheres, in the boreal and austral winters. This pattern is quite different from the tropical, seasonally consistent diversity patterns observed for most macroorganisms. However, like other marine organisms, surface water bacteria are particularly diverse in regions of high human environmental impacts on the oceans. Our maps provide the first picture of bacterial distributions at a global scale and suggest important differences between the diversity patterns of bacteria compared with other organisms.

Global and regional hearing impairment prevalence: an analysis of 42 studies in 29 countries.

BACKGROUND: Hearing impairment is a leading cause of disease burden, yet population-based studies that measure hearing impairment are rare. We estimate regional and global hearing impairment prevalence from sparse data and calculate corresponding uncertainty intervals. METHODS: We accessed papers from a published literature review and obtained additional detailed data tabulations from investigators. We estimated the prevalence of hearing impairment by region, sex, age and hearing level using a Bayesian hierarchical model, a method that is effective for sparse data. As the primary objective of modelling was to produce regional and global prevalence estimates, including for those regions with scarce to no data, models were evaluated using cross-validation. RESULTS: We used data from 42 studies, carried out between 1973 and 2010 in 29 countries. Hearing impairment was positively related to age, male sex and middle- and low-income regions. We estimated that the global prevalence of hearing impairment (defined as an average hearing level of 35 decibels or more in the better ear) in 2008 was 1.4% (95% uncertainty interval 1.0-2.2%) for children aged 5-14 years, 9.8% (7.7-13.2%) for females >15 years of age and 12.2% (9.7-16.2%) for males >15 years of age. The model exhibited good external validity in the cross-validation analysis, with 87% of survey estimates falling within our final model's 95% uncertainty intervals. CONCLUSION: Our results suggest that the prevalence of child and adult hearing impairment is substantially higher in middle- and low-income countries than in high-income countries, demonstrating the global need for attention to hearing impairment.

Global, regional, and national trends in haemoglobin concentration and prevalence of total and severe anaemia in children and pregnant and non-pregnant women for 1995-2011: a systematic analysis of population-representative data.

BACKGROUND: Low haemoglobin concentrations and anaemia are important risk factors for the health and development of women and children. We estimated trends in the distributions of haemoglobin concentration and in the prevalence of anaemia and severe anaemia in young children and pregnant and non-pregnant women between 1995 and 2011. METHODS: We obtained data about haemoglobin and anaemia for children aged 6-59 months and women of childbearing age (15-49 years) from 257 population-representative data sources from 107 countries worldwide. We used health, nutrition, and household surveys; summary statistics from WHO's Vitamin and Mineral Nutrition Information System; and summary statistics reported by other national and international agencies. We used a Bayesian hierarchical mixture model to estimate haemoglobin distributions and systematically addressed missing data, non-linear time trends, and representativeness of data sources. We quantified the uncertainty of our estimates. FINDINGS: Global mean haemoglobin improved slightly between 1995 and 2011, from 125 g/L (95% credibility interval 123-126) to 126 g/L (124-128) in non-pregnant women, from 112 g/L (111-113) to 114 g/L (112-116) in pregnant women, and from 109 g/L (107-111) to 111 g/L (110-113) in children. Anaemia prevalence decreased from 33% (29-37) to 29% (24-35) in non-pregnant women, from 43% (39-47) to 38% (34-43) in pregnant women, and from 47% (43-51) to 43% (38-47) in children. These prevalences translated to 496 million (409-595 million) non-pregnant women, 32 million (28-36 million) pregnant women, and 273 million (242-304 million) children with anaemia in 2011. In 2011, concentrations of mean haemoglobin were lowest and anaemia prevalence was highest in south Asia and central and west Africa. INTERPRETATION: Children's and women's haemoglobin statuses improved in some regions where concentrations had been low in the 1990s, leading to a modest global increase in mean haemoglobin and a reduction in anaemia prevalence. Further improvements are needed in some regions, particularly south Asia and central and west Africa, to improve the health of women and children and achieve global targets for reducing anaemia. FUNDING: Bill & Melinda Gates Foundation, Grand Challenges Canada, and the UK Medical Research Council.

Children's height and weight in rural and urban populations in low-income and middle-income countries: a systematic analysis of population-representative data.

BACKGROUND: Urban living affects children's nutrition and growth, which are determinants of their survival, cognitive development, and lifelong health. Little is known about urban-rural differences in children's height and weight, and how these differences have changed over time. We aimed to investigate trends in children's height and weight in rural and urban settings in low-income and middle-income countries, and to assess changes in the urban-rural differentials in height and weight over time. METHODS: We used comprehensive population-based data and a Bayesian hierarchical mixture model to estimate trends in children's height-for-age and weight-for-age Z scores by rural and urban place of residence, and changes in urban-rural differentials in height and weight Z scores, for 141 low-income and middle-income countries between 1985 and 2011. We also estimated the contribution of changes in rural and urban height and weight, and that of urbanisation, to the regional trends in these outcomes. FINDINGS: Urban children are taller and heavier than their rural counterparts in almost all low-income and middle-income countries. The urban-rural differential is largest in Andean and central Latin America (eg, Peru, Honduras, Bolivia, and Guatemala); in some African countries such as Niger, Burundi, and Burkina Faso; and in Vietnam and China. It is smallest in southern and tropical Latin America (eg, Chile and Brazil). Urban children in China, Chile, and Jamaica are the tallest in low-income and middle-income countries, and children in rural areas of Burundi, Guatemala, and Niger the shortest, with the tallest and shortest more than 10 cm apart at age 5 years. The heaviest children live in cities in Georgia, Chile, and China, and the most underweight in rural areas of Timor-Leste, India, Niger, and Bangladesh. Between 1985 and 2011, the urban advantage in height fell in southern and tropical Latin America and south Asia, but changed little or not at all in most other regions. The urban-rural weight differential also decreased in southern and tropical Latin America, but increased in east and southeast Asia and worldwide, because weight gain of urban children outpaced that of rural children. INTERPRETATION: Further improvement of child nutrition will require improved access to a stable and affordable food supply and health care for both rural and urban children, and closing of the the urban-rural gap in nutritional status. FUNDING: Bill & Melinda Gates Foundation, Grand Challenges Canada, UK Medical Research Council.

National, regional, and global trends in adult overweight and obesity prevalences.

BACKGROUND: Overweight and obesity prevalence are commonly used for public and policy communication of the extent of the obesity epidemic, yet comparable estimates of trends in overweight and obesity prevalence by country are not available. METHODS: We estimated trends between 1980 and 2008 in overweight and obesity prevalence and their uncertainty for adults 20 years of age and older in 199 countries and territories. Data were from a previous study, which used a Bayesian hierarchical model to estimate mean body mass index (BMI) based on published and unpublished health examination surveys and epidemiologic studies. Here, we used the estimated mean BMIs in a regression model to predict overweight and obesity prevalence by age, country, year, and sex. The uncertainty of the estimates included both those of the Bayesian hierarchical model and the uncertainty due to cross-walking from mean BMI to overweight and obesity prevalence. RESULTS: The global age-standardized prevalence of obesity nearly doubled from 6.4% (95% uncertainty interval 5.7-7.2%) in 1980 to 12.0% (11.5-12.5%) in 2008. Half of this rise occurred in the 20 years between 1980 and 2000, and half occurred in the 8 years between 2000 and 2008. The age-standardized prevalence of overweight increased from 24.6% (22.7-26.7%) to 34.4% (33.2-35.5%) during the same 28-year period. In 2008, female obesity prevalence ranged from 1.4% (0.7-2.2%) in Bangladesh and 1.5% (0.9-2.4%) in Madagascar to 70.4% (61.9-78.9%) in Tonga and 74.8% (66.7-82.1%) in Nauru. Male obesity was below 1% in Bangladesh, Democratic Republic of the Congo, and Ethiopia, and was highest in Cook Islands (60.1%, 52.6-67.6%) and Nauru (67.9%, 60.5-75.0%). CONCLUSIONS: Globally, the prevalence of overweight and obesity has increased since 1980, and the increase has accelerated. Although obesity increased in most countries, levels and trends varied substantially. These data on trends in overweight and obesity may be used to set targets for obesity prevalence as requested at the United Nations high-level meeting on Prevention and Control of NCDs.

Trends in mild, moderate, and severe stunting and underweight, and progress towards MDG 1 in 141 developing countries: a systematic analysis of population representative data.

BACKGROUND: There is little information on country trends in the complete distributions of children's anthropometric status, which are needed to assess all levels of mild to severe undernutrition. We aimed to estimate trends in the distributions of children's anthropometric status and assess progress towards the Millennium Development Goal 1 (MDG 1) target of halving the prevalence of weight-for-age Z score (WAZ) below -2 between 1990 and 2015 or reaching a prevalence of 2·3% or lower. METHODS: We collated population-representative data on height-for-age Z score (HAZ) and WAZ calculated with the 2006 WHO child growth standards. Our data sources were health and nutrition surveys, summary statistics from the WHO Global Database on Child Growth and Malnutrition, and summary statistics from reports of other national and international agencies. We used a Bayesian hierarchical mixture model to estimate Z-score distributions. We quantified the uncertainty of our estimates, assessed their validity, compared their performance to alternative models, and assessed sensitivity to key modelling choices. FINDINGS: In developing countries, mean HAZ improved from -1·86 (95% uncertainty interval -2·01 to -1·72) in 1985 to -1·16 (-1·29 to -1·04) in 2011; mean WAZ improved from -1·31 (-1·41 to -1·20) to -0·84 (-0·93 to -0·74). Over this period, prevalences of moderate-and-severe stunting declined from 47·2% (44·0 to 50·3) to 29·9% (27·1 to 32·9) and underweight from 30·1% (26·7 to 33·3) to 19·4% (16·5 to 22·2). The largest absolute improvements were in Asia and the largest relative reductions in prevalence in southern and tropical Latin America. Anthropometric status worsened in sub-Saharan Africa until the late 1990s and improved thereafter. In 2011, 314 (296 to 331) million children younger than 5 years were mildly, moderately, or severely stunted and 258 (240 to 274) million were mildly, moderately, or severely underweight. Developing countries as a whole have less than a 5% chance of meeting the MDG 1 target; but 61 of these 141 countries have a 50-100% chance. INTERPRETATION: Macroeconomic shocks, structural adjustment, and trade policy reforms in the 1980s and 1990s might have been responsible for worsening child nutritional status in sub-Saharan Africa. Further progress in the improvement of children's growth and nutrition needs equitable economic growth and investment in pro-poor food and primary care programmes, especially relevant in the context of the global economic crisis. FUNDING: The Bill & Melinda Gates Foundation and the UK Medical Research Council.