The Sustainable Development Goals (SDGs) mandate systematic monitoring of the health and wellbeing of all children to achieve optimal early childhood development. However, global epidemiological data ...on children with developmental disabilities are scarce. The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 provides a comprehensive assessment of prevalence and years lived with disability (YLDs) for development disabilities among children younger than 5 years in 195 countries and territories from 1990 to 2016.
We estimated prevalence and YLDs for epilepsy, intellectual disability, hearing loss, vision loss, autism spectrum disorder, and attention deficit hyperactivity disorder. YLDs were estimated as the product of the prevalence estimate and the disability weight for each mutually exclusive disorder, corrected for comorbidity. We used DisMod-MR 2.1, a Bayesian meta-regression tool, on a pool of primary data derived from systematic reviews of the literature, health surveys, hospital and claims databases, cohort studies, and disease-specific registries.
Globally, 52·9 million (95% uncertainty interval UI 48·7–57·3; or 8·4% 7·7–9·1) children younger than 5 years (54% males) had developmental disabilities in 2016 compared with 53·0 million (49·0–57·1; or 8·9% 8·2–9·5) in 1990. About 95% of these children lived in low-income and middle-income countries. YLDs among these children increased from 3·8 million (95% UI 2·8–4·9) in 1990 to 3·9 million (2·9–5·2) in 2016. These disabilities accounted for 13·3% of the 29·3 million YLDs for all health conditions among children younger than 5 years in 2016. Vision loss was the most prevalent disability, followed by hearing loss, intellectual disability, and autism spectrum disorder. However, intellectual disability was the largest contributor to YLDs in both 1990 and 2016. Although the prevalence of developmental disabilities among children younger than 5 years decreased in all countries (except for North America) between 1990 and 2016, the number of children with developmental disabilities increased significantly in sub-Saharan Africa (71·3%) and in North Africa and the Middle East (7·6%). South Asia had the highest prevalence of children with developmental disabilities in 2016 and North America had the lowest.
The global burden of developmental disabilities has not significantly improved since 1990, suggesting inadequate global attention on the developmental potential of children who survived childhood as a result of child survival programmes, particularly in sub-Saharan Africa and south Asia. The SDGs provide a framework for policy and action to address the needs of children with or at risk of developmental disabilities, particularly in resource-poor countries.
The Bill & Melinda Gates Foundation.
BACKGROUND: Estimates of children and adolescents with disabilities worldwide are needed to inform global intervention under the disability-inclusive provisions of the Sustainable Development Goals. ...We sought to update the most widely reported estimate of 93 million children <15 years with disabilities from the Global Burden of Disease Study 2004. METHODS: We analyzed Global Burden of Disease Study 2017 data on the prevalence of childhood epilepsy, intellectual disability, and vision or hearing loss and on years lived with disability (YLD) derived from systematic reviews, health surveys, hospital and claims databases, cohort studies, and disease-specific registries. Point estimates of the prevalence and YLD and the 95% uncertainty intervals (UIs) around the estimates were assessed. RESULTS: Globally, 291.2 million (11.2%) of the 2.6 billion children and adolescents (95% UI: 249.9–335.4 million) were estimated to have 1 of the 4 specified disabilities in 2017. The prevalence of these disabilities increased with age from 6.1% among children aged <1 year to 13.9% among adolescents aged 15 to 19 years. A total of 275.2 million (94.5%) lived in low- and middle-income countries, predominantly in South Asia and sub-Saharan Africa. The top 10 countries accounted for 62.3% of all children and adolescents with disabilities. These disabilities accounted for 28.9 million YLD or 19.9% of the overall 145.3 million (95% UI: 106.9–189.7) YLD from all causes among children and adolescents. CONCLUSIONS: The number of children and adolescents with these 4 disabilities is far higher than the 2004 estimate, increases from infancy to adolescence, and accounts for a substantial proportion of all-cause YLD.
Pandemics often precipitate declines in essential health service utilisation, which can ultimately kill more people than the disease outbreak itself. There is some evidence, however, that the ...presence of adequately supported community health workers (CHWs), that is, financially remunerated, trained, supplied and supervised in line with WHO guidelines, may blunt the impact of health system shocks. Yet, adequate support for CHWs is often missing or uneven across countries. This study assesses whether adequately supported CHWs can maintain the continuity of essential community-based health service provision during the COVID-19 pandemic.
Interrupted time series analysis. Monthly routine data from 27 districts across four countries in sub-Saharan Africa were extracted from CHW and facility reports for the period January 2018-June 2021. Descriptive analysis, null hypothesis testing, and segmented regression analysis were used to assess the presence and magnitude of a possible disruption in care utilisation after the earliest reported cases of COVID-19.
CHWs across all sites were supported in line with the WHO Guideline and received COVID-19 adapted protocols, training and personal protective equipment within 45 days after the first case in each country. We found no disruptions to the coverage of proactive household visits or integrated community case management (iCCM) assessments provided by these prepared and protected CHWs, as well as no disruptions to the speed with which iCCM was received, pregnancies were registered or postnatal care received.
CHWs who were equipped and prepared for the pandemic were able to maintain speed and coverage of community-delivered care during the pandemic period. Given that the majority of CHWs globally remain unpaid and largely unsupported, this paper suggests that the opportunity cost of not professionalising CHWs may be larger than previously estimated, particularly in light of the inevitability of future pandemics.
Abstract Sequence-based genetic testing identifies causative variants in ~ 50% of individuals with developmental and epileptic encephalopathies (DEEs). Aberrant changes in DNA methylation are ...implicated in various neurodevelopmental disorders but remain unstudied in DEEs. We interrogate the diagnostic utility of genome-wide DNA methylation array analysis on peripheral blood samples from 582 individuals with genetically unsolved DEEs. We identify rare differentially methylated regions (DMRs) and explanatory episignatures to uncover causative and candidate genetic etiologies in 12 individuals. Using long-read sequencing, we identify DNA variants underlying rare DMRs, including one balanced translocation, three CG-rich repeat expansions, and four copy number variants. We also identify pathogenic variants associated with episignatures. Finally, we refine the CHD2 episignature using an 850 K methylation array and bisulfite sequencing to investigate potential insights into CHD2 pathophysiology. Our study demonstrates the diagnostic yield of genome-wide DNA methylation analysis to identify causal and candidate variants as 2% (12/582) for unsolved DEE cases.
ABSTRACTSimão, R, Spineti, J, de Salles, BF, Matta, T, Fernandes, L, Fleck, SJ, Rhea, MR, and Strom-Olsen, HE. Comparison between nonlinear and linear periodized resistance traininghypertrophic and ...strength effects. J Strength Cond Res 26(5)1389–1395, 2012—The aim of this study was to investigate the effects of nonlinear periodized (NLP) and linear periodized (LP) resistance training (RT) on muscle thickness (MT) and strength, measured by an ultrasound technique and 1 repetition maximum (1RM), respectively. Thirty untrained men were randomly assigned to 3 groupsNLP (n = 11, age30.2 ± 1.1 years, height173.6 ± 7.2 cm, weight79.5 ± 13.1 kg), LP (n = 10, age29.8 ± 1.9 years, height172.0 ± 6.8 cm, weight79.9 ± 10.6 kg), and control group (CG; n = 9, age25.9 ± 3.6 years, height171.2 ± 6.3 cm, weight73.9 ± 9.9 kg). The right biceps and triceps MT and 1RM strength for the exercises bench press (BP), lat-pull down, triceps extension, and biceps curl (BC) were assessed before and after 12 weeks of training. The NLP program varied training biweekly during weeks 1–6 and on a daily basis during weeks 7–12. The LP program followed a pattern of intensity and volume changes every 4 weeks. The CG did not engage in any RT. Posttraining, both trained groups presented significant 1RM strength gains in all exercises (with the exception of the BP in LP). The 1RM of the NLP group was significantly higher than LP for BP and BC posttraining. There were no significant differences in biceps and triceps MT between baseline and posttraining for any group; however, posttraining, there were significant differences in biceps and triceps MT between NLP and the CG. The effect sizes were higher in NLP for the majority of observed variables. In conclusion, both LP and NLP are effective, but NLP may lead to greater gains in 1RM and MT over a 12-week training period.
Following the economic crisis in Greece in 2010, the country's ongoing austerity measures include a substantial contraction of health-care expenditure, with reports of subsequent negative health ...consequences. A comprehensive evaluation of mortality and morbidity is required to understand the current challenges of public health in Greece.
We used the results of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 to describe the patterns of death and disability among those living in Greece from 2000 to 2010 (pre-austerity) and 2010 to 2016 (post-austerity), and compared trends in health outcomes and health expenditure to those in Cyprus and western Europe. We estimated all-cause mortality from vital registration data, and we calculated cause-specific deaths and years of life lost. Age-standardised mortality rates were compared using the annualised rate of change (ARC). Mortality risk factors were assessed using a comparative risk assessment framework for 84 risk factors and clusters to calculative summary exposure values and population attributable fraction statistics. We assessed the association between trends in total, government, out-of-pocket, and prepaid public health expenditure and all-cause mortality with a segmented correlation analysis.
All-age mortality in Greece increased from 944·5 (95% uncertainty interval UI 923·1–964·5) deaths per 100 000 in 2000 to 997·8 (975·4–1018) in 2010 and 1174·9 (1107·4–1243·2) in 2016, with a higher ARC after 2010 and the introduction of austerity (2·72% 1·65 to 3·74 for 2010–16) than before (0·55% 0·24 to 0·85 for 2000–10) or in western Europe during the same period (0·86% 0·54 to 1·17). Age-standardised reduction in ARC approximately halved from 2000–10 (−1·61 95% UI −1·91 to −1·30) to 2010–16 (−0·87% –2·03 to 0·20), with post-2010 ARC similar to that in Cyprus (−0·86% –1·4 to −0·36) and lower than in western Europe (−1·14% –1·48 to −0·81). Mortality changes in Greece coincided with a rapid decrease in government health expenditure, but also with aggregate population ageing from 2010 to 2016 that was faster than observed in Cyprus. Causes of death that increased were largely those that are responsive to health care. Comparable temporal and age patterns were noted for non-fatal health outcomes, with a somewhat faster rise in years lived with disability since 2010 in Greece compared with Cyprus and western Europe. Risk factor exposures, especially high body-mass index, smoking, and alcohol use, explained much of the mortality increase in Greek adults aged 15–49 years, but only explained a minority of that in adults older than 70 years.
The findings of increases in total deaths and accelerated population ageing call for specific focus from health policy makers to ensure the health-care system is equipped to meet the needs of the people in Greece.
Bill & Melinda Gates Foundation.
INTRODUCTION: Several studies have measured health outcomes in the United States, but none have provided a comprehensive assessment of patterns of health by state. OBJECTIVE: To use the results of ...the Global Burden of Disease Study (GBD) to report trends in the burden of diseases, injuries, and risk factors at the state level from 1990 to 2016. DESIGN AND SETTING: A systematic analysis of published studies and available data sources estimates the burden of disease by age, sex, geography, and year. MAIN OUTCOMES AND MEASURES: Prevalence, incidence, mortality, life expectancy, healthy life expectancy (HALE), years of life lost (YLLs) due to premature mortality, years lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 333 causes and 84 risk factors with 95% uncertainty intervals (UIs) were computed. RESULTS: Between 1990 and 2016, overall death rates in the United States declined from 745.2 (95% UI, 740.6 to 749.8) per 100 000 persons to 578.0 (95% UI, 569.4 to 587.1) per 100 000 persons. The probability of death among adults aged 20 to 55 years declined in 31 states and Washington, DC from 1990 to 2016. In 2016, Hawaii had the highest life expectancy at birth (81.3 years) and Mississippi had the lowest (74.7 years), a 6.6-year difference. Minnesota had the highest HALE at birth (70.3 years), and West Virginia had the lowest (63.8 years), a 6.5-year difference. The leading causes of DALYs in the United States for 1990 and 2016 were ischemic heart disease and lung cancer, while the third leading cause in 1990 was low back pain, and the third leading cause in 2016 was chronic obstructive pulmonary disease. Opioid use disorders moved from the 11th leading cause of DALYs in 1990 to the 7th leading cause in 2016, representing a 74.5% (95% UI, 42.8% to 93.9%) change. In 2016, each of the following 6 risks individually accounted for more than 5% of risk-attributable DALYs: tobacco consumption, high body mass index (BMI), poor diet, alcohol and drug use, high fasting plasma glucose, and high blood pressure. Across all US states, the top risk factors in terms of attributable DALYs were due to 1 of the 3 following causes: tobacco consumption (32 states), high BMI (10 states), or alcohol and drug use (8 states). CONCLUSIONS AND RELEVANCE: There are wide differences in the burden of disease at the state level. Specific diseases and risk factors, such as drug use disorders, high BMI, poor diet, high fasting plasma glucose level, and alcohol use disorders are increasing and warrant increased attention. These data can be used to inform national health priorities for research, clinical care, and policy.
BACKGROUND: The UN's Sustainable Development Goals (SDGs) are grounded in the global ambition of "leaving no one behind". Understanding today's gains and gaps for the health-related SDGs is essential ...for decision makers as they aim to improve the health of populations. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016), we measured 37 of the 50 health-related SDG indicators over the period 1990-2016 for 188 countries, and then on the basis of these past trends, we projected indicators to 2030. METHODS: We used standardised GBD 2016 methods to measure 37 health-related indicators from 1990 to 2016, an increase of four indicators since GBD 2015. We substantially revised the universal health coverage (UHC) measure, which focuses on coverage of essential health services, to also represent personal health-care access and quality for several non-communicable diseases. We transformed each indicator on a scale of 0-100, with 0 as the 2·5th percentile estimated between 1990 and 2030, and 100 as the 97·5th percentile during that time. An index representing all 37 health-related SDG indicators was constructed by taking the geometric mean of scaled indicators by target. On the basis of past trends, we produced projections of indicator values, using a weighted average of the indicator and country-specific annualised rates of change from 1990 to 2016 with weights for each annual rate of change based on out-of-sample validity. 24 of the currently measured health-related SDG indicators have defined SDG targets, against which we assessed attainment. FINDINGS: Globally, the median health-related SDG index was 56·7 (IQR 31·9-66·8) in 2016 and country-level performance markedly varied, with Singapore (86·8, 95% uncertainty interval 84·6-88·9), Iceland (86·0, 84·1-87·6), and Sweden (85·6, 81·8-87·8) having the highest levels in 2016 and Afghanistan (10·9, 9·6-11·9), the Central African Republic (11·0, 8·8-13·8), and Somalia (11·3, 9·5-13·1) recording the lowest. Between 2000 and 2016, notable improvements in the UHC index were achieved by several countries, including Cambodia, Rwanda, Equatorial Guinea, Laos, Turkey, and China; however, a number of countries, such as Lesotho and the Central African Republic, but also high-income countries, such as the USA, showed minimal gains. Based on projections of past trends, the median number of SDG targets attained in 2030 was five (IQR 2-8) of the 24 defined targets currently measured. Globally, projected target attainment considerably varied by SDG indicator, ranging from more than 60% of countries projected to reach targets for under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria, to less than 5% of countries projected to achieve targets linked to 11 indicator targets, including those for childhood overweight, tuberculosis, and road injury mortality. For several of the health-related SDGs, meeting defined targets hinges upon substantially faster progress than what most countries have achieved in the past. INTERPRETATION: GBD 2016 provides an updated and expanded evidence base on where the world currently stands in terms of the health-related SDGs. Our improved measure of UHC offers a basis to monitor the expansion of health services necessary to meet the SDGs. Based on past rates of progress, many places are facing challenges in meeting defined health-related SDG targets, particularly among countries that are the worst off. In view of the early stages of SDG implementation, however, opportunity remains to take actions to accelerate progress, as shown by the catalytic effects of adopting the Millennium Development Goals after 2000. With the SDGs' broader, bolder development agenda, multisectoral commitments and investments are vital to make the health-related SDGs within reach of all populations.
Malnutrition is a major contributor to disease burden in India. To inform subnational action, we aimed to assess the disease burden due to malnutrition and the trends in its indicators in every state ...of India in relation to Indian and global nutrition targets.
We analysed the disease burden attributable to child and maternal malnutrition, and the trends in the malnutrition indicators from 1990 to 2017 in every state of India using all accessible data from multiple sources, as part of Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017. The states were categorised into three groups using their Socio-demographic Index (SDI) calculated by GBD on the basis of per capita income, mean education, and fertility rate in women younger than 25 years. We projected the prevalence of malnutrition indicators for the states of India up to 2030 on the basis of the 1990–2017 trends for comparison with India National Nutrition Mission (NNM) 2022 and WHO and UNICEF 2030 targets.
Malnutrition was the predominant risk factor for death in children younger than 5 years of age in every state of India in 2017, accounting for 68·2% (95% UI 65·8–70·7) of the total under-5 deaths, and the leading risk factor for health loss for all ages, responsible for 17·3% (16·3–18·2) of the total disability-adjusted life years (DALYs). The malnutrition DALY rate was much higher in the low SDI than in the middle SDI and high SDI state groups. This rate varied 6·8 times between the states in 2017, and was highest in the states of Uttar Pradesh, Bihar, Assam, and Rajasthan. The prevalence of low birthweight in India in 2017 was 21·4% (20·8–21·9), child stunting 39·3% (38·7–40·1), child wasting 15·7% (15·6–15·9), child underweight 32·7% (32·3–33·1), anaemia in children 59·7% (56·2–63·8), anaemia in women 15–49 years of age 54·4% (53·7–55·2), exclusive breastfeeding 53·3% (51·5–54·9), and child overweight 11·5% (8·5–14·9). If the trends estimated up to 2017 for the indicators in the NNM 2022 continue in India, there would be 8·9% excess prevalence for low birthweight, 9·6% for stunting, 4·8% for underweight, 11·7% for anaemia in children, and 13·8% for anaemia in women relative to the 2022 targets. For the additional indicators in the WHO and UNICEF 2030 targets, the trends up to 2017 would lead to 10·4% excess prevalence for wasting, 14·5% excess prevalence for overweight, and 10·7% less exclusive breastfeeding in 2030. The prevalence of malnutrition indicators, their rates of improvement, and the gaps between projected prevalence and targets vary substantially between the states.
Malnutrition continues to be the leading risk factor for disease burden in India. It is encouraging that India has set ambitious targets to reduce malnutrition through NNM. The trends up to 2017 indicate that substantially higher rates of improvement will be needed for all malnutrition indicators in most states to achieve the Indian 2022 and the global 2030 targets. The state-specific findings in this report indicate the effort needed in each state, which will be useful in tracking and motivating further progress. Similar subnational analyses might be useful for other low-income and middle-income countries.
Bill & Melinda Gates Foundation; Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.
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