Underweight, overweight, and obesity in childhood and adolescence are associated with adverse health consequences throughout the life-course. Our aim was to estimate worldwide trends in mean body-mass index (BMI) and a comprehensive set of BMI categories that cover underweight to obesity in children and adolescents, and to compare trends with those of adults. We pooled 2416 population-based studies with measurements of height and weight on 128·9 million participants aged 5 years and older, including 31·5 million aged 5-19 years. We used a Bayesian hierarchical model to estimate trends from 1975 to 2016 in 200 countries for mean BMI and for prevalence of BMI in the following categories for children and adolescents aged 5-19 years: more than 2 SD below the median of the WHO growth reference for children and adolescents (referred to as moderate and severe underweight hereafter), 2 SD to more than 1 SD below the median (mild underweight), 1 SD below the median to 1 SD above the median (healthy weight), more than 1 SD to 2 SD above the median (overweight but not obese), and more than 2 SD above the median (obesity). Regional change in age-standardised mean BMI in girls from 1975 to 2016 ranged from virtually no change (-0·01 kg/m2 per decade; 95% credible interval -0·42 to 0·39, posterior probability [PP] of the observed decrease being a true decrease=0·5098) in eastern Europe to an increase of 1·00 kg/m2 per decade (0·69-1·35, PP>0·9999) in central Latin America and an increase of 0·95 kg/m2 per decade (0·64-1·25, PP>0·9999) in Polynesia and Micronesia. The range for boys was from a non-significant increase of 0·09 kg/m2 per decade (-0·33 to 0·49, PP=0·6926) in eastern Europe to an increase of 0·77 kg/m2 per decade (0·50-1·06, PP>0·9999) in Polynesia and Micronesia. Trends in mean BMI have recently flattened in northwestern Europe and the high-income English-speaking and Asia-Pacific regions for both sexes, southwestern Europe for boys, and central and Andean Latin America for girls. By contrast, the rise in BMI has accelerated in east and south Asia for both sexes, and southeast Asia for boys. Global age-standardised prevalence of obesity increased from 0·7% (0·4-1·2) in 1975 to 5·6% (4·8-6·5) in 2016 in girls, and from 0·9% (0·5-1·3) in 1975 to 7·8% (6·7-9·1) in 2016 in boys; the prevalence of moderate and severe underweight decreased from 9·2% (6·0-12·9) in 1975 to 8·4% (6·8-10·1) in 2016 in girls and from 14·8% (10·4-19·5) in 1975 to 12·4% (10·3-14·5) in 2016 in boys. Prevalence of moderate and severe underweight was highest in India, at 22·7% (16·7-29·6) among girls and 30·7% (23·5-38·0) among boys. Prevalence of obesity was more than 30% in girls in Nauru, the Cook Islands, and Palau; and boys in the Cook Islands, Nauru, Palau, Niue, and American Samoa in 2016. Prevalence of obesity was about 20% or more in several countries in Polynesia and Micronesia, the Middle East and north Africa, the Caribbean, and the USA. In 2016, 75 (44-117) million girls and 117 (70-178) million boys worldwide were moderately or severely underweight. In the same year, 50 (24-89) million girls and 74 (39-125) million boys worldwide were obese. The rising trends in children's and adolescents' BMI have plateaued in many high-income countries, albeit at high levels, but have accelerated in parts of Asia, with trends no longer correlated with those of adults. Wellcome Trust, AstraZeneca Young Health Programme.

Numerous population-based studies of age-related macular degeneration have been reported around the world, with the results of some studies suggesting racial or ethnic differences in disease prevalence. Integrating these resources to provide summarised data to establish worldwide prevalence and to project the number of people with age-related macular degeneration from 2020 to 2040 would be a useful guide for global strategies. We did a systematic literature review to identify all population-based studies of age-related macular degeneration published before May, 2013. Only studies using retinal photographs and standardised grading classifications (the Wisconsin age-related maculopathy grading system, the international classification for age-related macular degeneration, or the Rotterdam staging system) were included. Hierarchical Bayesian approaches were used to estimate the pooled prevalence, the 95% credible intervals (CrI), and to examine the difference in prevalence by ethnicity (European, African, Hispanic, Asian) and region (Africa, Asia, Europe, Latin America and the Caribbean, North America, and Oceania). UN World Population Prospects were used to project the number of people affected in 2014 and 2040. Bayes factor was calculated as a measure of statistical evidence, with a score above three indicating substantial evidence. Analysis of 129,664 individuals (aged 30-97 years), with 12,727 cases from 39 studies, showed the pooled prevalence (mapped to an age range of 45-85 years) of early, late, and any age-related macular degeneration to be 8.01% (95% CrI 3.98-15.49), 0.37% (0.18-0.77), and 8.69% (4.26-17.40), respectively. We found a higher prevalence of early and any age-related macular degeneration in Europeans than in Asians (early: 11.2% vs 6.8%, Bayes factor 3.9; any: 12.3% vs 7.4%, Bayes factor 4.3), and early, late, and any age-related macular degeneration to be more prevalent in Europeans than in Africans (early: 11.2% vs 7.1%, Bayes factor 12.2; late: 0.5% vs 0.3%, 3.7; any: 12.3% vs 7.5%, 31.3). There was no difference in prevalence between Asians and Africans (all Bayes factors <1). Europeans had a higher prevalence of geographic atrophy subtype (1.11%, 95% CrI 0.53-2.08) than Africans (0.14%, 0.04-0.45), Asians (0.21%, 0.04-0.87), and Hispanics (0.16%, 0.05-0.46). Between geographical regions, cases of early and any age-related macular degeneration were less prevalent in Asia than in Europe and North America (early: 6.3% vs 14.3% and 12.8% [Bayes factor 2.3 and 7.6]; any: 6.9% vs 18.3% and 14.3% [3.0 and 3.8]). No significant gender effect was noted in prevalence (Bayes factor <1.0). The projected number of people with age-related macular degeneration in 2020 is 196 million (95% CrI 140-261), increasing to 288 million in 2040 (205-399). These estimates indicate the substantial global burden of age-related macular degeneration. Summarised data provide information for understanding the effect of the condition and provide data towards designing eye-care strategies and health services around the world. National Medical Research Council, Singapore.

The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk-outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk-outcome pairs, and new data on risk exposure levels and risk-outcome associations. We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk-outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. In 2017, 34·1 million (95% uncertainty interval [UI] 33·3-35·0) deaths and 1·21 billion (1·14-1·28) DALYs were attributable to GBD risk factors. Globally, 61·0% (59·6-62·4) of deaths and 48·3% (46·3-50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39-11·5) deaths and 218 million (198-237) DALYs, followed by smoking (7·10 million [6·83-7·37] deaths and 182 million [173-193] DALYs), high fasting plasma glucose (6·53 million [5·23-8·23] deaths and 171 million [144-201] DALYs), high body-mass index (BMI; 4·72 million [2·99-6·70] deaths and 148 million [98·6-202] DALYs), and short gestation for birthweight (1·43 million [1·36-1·51] deaths and 139 million [131-147] DALYs). In total, risk-attributable DALYs declined by 4·9% (3·3-6·5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23·5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18·6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD...

By 2040, it is projected that approximately 600 million people will have diabetes, with one-third expected to have diabetic retinopathy.^1-3 Screening for diabetic retinopathy, coupled with timely referral and treatment, is a universally accepted strategy for blindness prevention.² However, programs for screening diabetic retinopathy are challenged by issues related to implementation, availability of human assessors, and long-term financial sustainability.^2,4-7