Summary Background Quantification of the disease burden caused by different risks informs prevention by providing an account of health loss different to that provided by a disease-by-disease analysis. No complete revision of global disease burden caused by risk factors has been done since a comparative risk assessment in 2000, and no previous analysis has assessed changes in burden attributable to risk factors over time. Methods We estimated deaths and disability-adjusted life years (DALYs; sum of years lived with disability [YLD] and years of life lost [YLL]) attributable to the independent effects of 67 risk factors and clusters of risk factors for 21 regions in 1990 and 2010. We estimated exposure distributions for each year, region, sex, and age group, and relative risks per unit of exposure by systematically reviewing and synthesising published and unpublished data. We used these estimates, together with estimates of cause-specific deaths and DALYs from the Global Burden of Disease Study 2010, to calculate the burden attributable to each risk factor exposure compared with the theoretical-minimum-risk exposure. We incorporated uncertainty in disease burden, relative risks, and exposures into our estimates of attributable burden. Findings In 2010, the three leading risk factors for global disease burden were high blood pressure (7·0% [95% uncertainty interval 6·2–7·7] of global DALYs), tobacco smoking including second-hand smoke (6·3% [5·5–7·0]), and alcohol use (5·5% [5·0–5·9]). In 1990, the leading risks were childhood underweight (7·9% [6·8–9·4]), household air pollution from solid fuels (HAP; 7·0% [5·6–8·3]), and tobacco smoking including second-hand smoke (6·1% [5·4–6·8]). Dietary risk factors and physical inactivity collectively accounted for 10·0% (95% UI 9·2–10·8) of global DALYs in 2010, with the most prominent dietary risks being diets low in fruits and those high in sodium. Several risks that primarily affect childhood communicable diseases, including unimproved water and sanitation and childhood micronutrient deficiencies, fell in rank between 1990 and 2010, with unimproved water we and sanitation accounting for 0·9% (0·4–1·6) of global DALYs in 2010. However, in most of sub-Saharan Africa childhood underweight, HAP, and non-exclusive and discontinued breastfeeding were the leading risks in 2010, while HAP was the leading risk in south Asia. The leading risk factor in Eastern Europe, most of Latin America, and southern sub-Saharan Africa in 2010 was alcohol use; in most of Asia, North Africa and Middle East, and central Europe it was high blood pressure. Despite declines, tobacco smoking including second-hand smoke remained the leading risk in high-income north America and western Europe. High body-mass index has increased globally and it is the leading risk in Australasia and southern Latin America, and also ranks high in other high-income regions, North Africa and Middle East, and Oceania. Interpretation Worldwide, the contribution of different risk factors to disease burden has changed s...

Summary Background As mortality rates decline, life expectancy increases, and populations age, non-fatal outcomes of diseases and injuries are becoming a larger component of the global burden of disease. The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016. Methods We estimated prevalence and incidence for 328 diseases and injuries and 2982 sequelae, their non-fatal consequences. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between incidence, prevalence, remission, and cause of death rates for each condition. For some causes, we used alternative modelling strategies if incidence or prevalence needed to be derived from other data. YLDs were estimated as the product of prevalence and a disability weight for all mutually exclusive sequelae, corrected for comorbidity and aggregated to cause level. We updated the Socio-demographic Index (SDI), a summary indicator of income per capita, years of schooling, and total fertility rate. GBD 2016 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, low back pain, migraine, age-related and other hearing loss, iron-deficiency anaemia, and major depressive disorder were the five leading causes of YLDs in 2016, contributing 57·6 million (95% uncertainty interval [UI] 40·8–75·9 million [7·2%, 6·0–8·3]), 45·1 million (29·0–62·8 million [5·6%, 4·0–7·2]), 36·3 million (25·3–50·9 million [4·5%, 3·8–5·3]), 34·7 million (23·0–49·6 million [4·3%, 3·5–5·2]), and 34·1 million (23·5–46·0 million [4·2%, 3·2–5·3]) of total YLDs, respectively. Age-standardised rates of YLDs for all causes combined decreased between 1990 and 2016 by 2·7% (95% UI 2·3–3·1). Despite mostly stagnant age-standardised rates, the absolute number of YLDs from non-communicable diseases has been growing rapidly across all SDI quintiles, partly because of population growth, but also the ageing of populations. The largest absolute increases in total numbers of YLDs globally were between the ages of 40 and 69 years. Age-standardised YLD rates for all conditions combined were 10·4% (95% UI 9·0–11·8) higher in women than in men. Iron-deficiency anaemia, migraine, Alzheimer’s disease and other dementias, major depressive disorder, anxiety, and all musculoskeletal disorders apart from gout were the main conditions contributing to higher YLD rates in women. Men had higher age-standardised rates of substance use disorders, diabetes, cardiovascular diseases, cancers, and all injuries apart from sexual violence. Globally, we noted much less geographical variation in disability than has been documented for premature mortality. In 2016, there was a less than two times difference in age-standardised YLD rates for all causes between the location with the lowest rate (China, 9201 YLDs per 100 000, 95% UI 6862–11943)...

Summary Background The fifth Millennium Development Goal (MDG 5) established the goal of a 75% reduction in the maternal mortality ratio (MMR; number of maternal deaths per 100 000 livebirths) between 1990 and 2015. We aimed to measure levels and track trends in maternal mortality, the key causes contributing to maternal death, and timing of maternal death with respect to delivery. Methods We used robust statistical methods including the Cause of Death Ensemble model (CODEm) to analyse a database of data for 7065 site-years and estimate the number of maternal deaths from all causes in 188 countries between 1990 and 2013. We estimated the number of pregnancy-related deaths caused by HIV on the basis of a systematic review of the relative risk of dying during pregnancy for HIV-positive women compared with HIV-negative women. We also estimated the fraction of these deaths aggravated by pregnancy on the basis of a systematic review. To estimate the numbers of maternal deaths due to nine different causes, we identified 61 sources from a systematic review and 943 site-years of vital registration data. We also did a systematic review of reports about the timing of maternal death, identifying 142 sources to use in our analysis. We developed estimates for each country for 1990–2013 using Bayesian meta-regression. We estimated 95% uncertainty intervals (UIs) for all values. Findings 292 982 (95% UI 261 017–327 792) maternal deaths occurred in 2013, compared with 376 034 (343 483–407 574) in 1990. The global annual rate of change in the MMR was −0·3% (−1·1 to 0·6) from 1990 to 2003, and −2·7% (−3·9 to −1·5) from 2003 to 2013, with evidence of continued acceleration. MMRs reduced consistently in south, east, and southeast Asia between 1990 and 2013, but maternal deaths increased in much of sub-Saharan Africa during the 1990s. 2070 (1290–2866) maternal deaths were related to HIV in 2013, 0·4% (0·2–0·6) of the global total. MMR was highest in the oldest age groups in both 1990 and 2013. In 2013, most deaths occurred intrapartum or postpartum. Causes varied by region and between 1990 and 2013. We recorded substantial variation in the MMR by country in 2013, from 956·8 (685·1–1262·8) in South Sudan to 2·4 (1·6–3·6) in Iceland. Interpretation Global rates of change suggest that only 16 countries will achieve the MDG 5 target by 2015. Accelerated reductions since the Millennium Declaration in 2000 coincide with increased development assistance for maternal, newborn, and child health. Setting of targets and associated interventions for after 2015 will need careful consideration of regions that are making slow progress, such as west and central Africa. Funding Bill & Melinda Gates Foundation.

Background DNA methylation leaves a long-term signature of smoking exposure and is one potential mechanism by which tobacco exposure predisposes to adverse health outcomes, such as cancers, osteoporosis, lung, and cardiovascular disorders. Methods and Results To comprehensively determine the association between cigarette smoking and DNA methylation, we conducted a meta-analysis of genome-wide DNA methylation assessed using the Illumina BeadChip 450K array on 15,907 blood derived DNA samples from participants in 16 cohorts (including 2,433 current, 6,518 former, and 6,956 never smokers). Comparing current versus never smokers, 2,623 CpG sites (CpGs), annotated to 1,405 genes, were statistically significantly differentially methylated at Bonferroni threshold of p<1×10−7 (18,760 CpGs at False Discovery Rate (FDR)<0.05). Genes annotated to these CpGs were enriched for associations with several smoking-related traits in genome-wide studies including pulmonary function, cancers, inflammatory diseases and heart disease. Comparing former versus never smokers, 185 of the CpGs that differed between current and never smokers were significant p<1×10−7 (2,623 CpGs at FDR<0.05), indicating a pattern of persistent altered methylation, with attenuation, after smoking cessation. Transcriptomic integration identified effects on gene expression at many differentially methylated CpGs. Conclusions Cigarette smoking has a broad impact on genome-wide methylation that, at many loci, persists many years after smoking cessation. Many of the differentially methylated genes were novel genes with respect to biologic effects of smoking, and might represent therapeutic targets for prevention or treatment of tobacco-related diseases. Methylation at these sites could also serve as sensitive and stable biomarkers of lifetime exposure to tobacco smoke.

Epigenetic modifications, including DNA methylation, represent a potential mechanism for environmental impacts on human disease. Maternal smoking in pregnancy remains an important public health problem that impacts child health in a myriad of ways and has potential lifelong consequences. The mechanisms are largely unknown, but epigenetics most likely plays a role. We formed the Pregnancy And Childhood Epigenetics (PACE) consortium and meta-analyzed, across 13 cohorts (n = 6,685), the association between maternal smoking in pregnancy and newborn blood DNA methylation at over 450,000 CpG sites (CpGs) by using the Illumina 450K BeadChip. Over 6,000 CpGs were differentially methylated in relation to maternal smoking at genome-wide statistical significance (false discovery rate, 5%), including 2,965 CpGs corresponding to 2,017 genes not previously related to smoking and methylation in either newborns or adults. Several genes are relevant to diseases that can be caused by maternal smoking (e.g., orofacial clefts and asthma) or adult smoking (e.g., certain cancers). A number of differentially methylated CpGs were associated with gene expression. We observed enrichment in pathways and processes critical to development. In older children (5 cohorts, n = 3,187), 100% of CpGs gave at least nominal levels of significance, far more than expected by chance (p value < 2.2 × 10(-16)). Results were robust to different normalization methods used across studies and cell type adjustment. In this large scale meta-analysis of methylation data, we identified numerous loci involved in response to maternal smoking in pregnancy with persistence into later childhood and provide insights into mechanisms underlying effects of this important exposure.

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Background: Epigenetic modifications, such as DNA methylation, due to in utero exposures may play a critical role in early programming for childhood and adult illness. Maternal smoking is a major risk factor for multiple adverse health outcomes in children, but the underlying mechanisms are unclear.Objective: We investigated epigenome-wide methylation in cord blood of newborns in relation to maternal smoking during pregnancy.Methods: We examined maternal plasma cotinine (an objective biomarker of smoking) measured during pregnancy in relation to DNA methylation at 473,844 CpG sites (CpGs) in 1,062 newborn cord blood samples from the Norwegian Mother and Child Cohort Study (MoBa) using the Infinium HumanMethylation450 BeadChip (450K).Results: We found differential DNA methylation at epigenome-wide statistical significance (p-value < 1.06 × 10–7) for 26 CpGs mapped to 10 genes. We replicated findings for CpGs in AHRR, CYP1A1, and GFI1 at strict Bonferroni-corrected statistical significance in a U.S. birth cohort. AHRR and CYP1A1 play a key role in the aryl hydrocarbon receptor signaling pathway, which mediates the detoxification of the components of tobacco smoke. GFI1 is involved in diverse developmental processes but has not previously been implicated in responses to tobacco smoke.Conclusions: We identified a set of genes with methylation changes present at birth in children whose mothers smoked during pregnancy. This is the first study of differential methylation across the genome in relation to maternal smoking during pregnancy using the 450K platform. Our findings implicate epigenetic mechanisms in the pathogenesis of the adverse health outcomes associated with this important in utero exposure.

Pulmonary function is an easily measurable and reliable index of the physiological state of the lungs and airways 1 . Pulmonary function also predicts mortality in the general population, even among people who have never smoked (never-smokers) who have only modestly reduced pulmonary function and no respiratory symptoms 2,3 . The peak level of pulmonary function attained in early adulthood and its subsequent decline with age are likely influenced by genetic and environmental factors. Tobacco smoking is a major environmental cause of accelerated decline in pulmonary function with age. Other inhaled pollutants also appear to contribute. Familial aggregation studies suggest a genetic contribution to lung function, with heritability estimates exceeding 40% 4,5 , but little is known about the specific genetic factors involved. A relatively uncommon deficiency of α1-antitrypsin is the only established genetic risk factor for accelerated decline in pulmonary function and for development of chronic obstructive pulmonary disease (COPD), especially in smokers 4,6 . However, α1-antitrypsin accounts for little of the population variability in pulmonary function 4 . Candidate gene studies suggest that other genetic variants may influence the time course of pulmonary function and its decline in relation to smoking, but these putative genetic risk factors remain unknown 4 .Forced expiratory volume in the first second (FEV 1 ) and its ratio to forced vital capacity (FEV 1 /FVC) are two clinically relevant pulmonary function measures. Although both FEV 1 and FVC are influenced by lung size and can be reduced by restrictive lung diseases, obstructive lung disease leads to proportionately greater reduction in FEV 1 than FVC. Therefore, reduced FEV 1 /FVC, an indicator of airflow obstruction that is independent of lung size, is the primary criterion for defining an obstructive ventilatory defect 1 . Whereas low FEV 1 /FVC indicates the presence of airflow obstruction, FEV 1 is used to classify the severity and follow the progression of obstructive lung disease over time 5,7,8 .The first genome-wide association study (GWAS) for pulmonary function evaluating 70,987 SNPs in about 1,220 Framingham Heart Study (FHS) participants revealed no genome-wide significant loci 9 . Recently, a GWAS of FEV 1 /FVC using 2,540,223 SNPs in 7,691 FHS participants identified several SNPs on chromosome 4q31 near HHIP with genome-wide significance 10 . A GWAS of COPD 11 also implicated the HHIP region along with CHRNA3-CHRNA5 on chromosome 15, a region previously associated with nicotine dependence 12,13 .We conducted meta-analyses of GWAS results for a cross-sectional analysis of pulmonary function (FEV 1 /FVC and FEV 1 ) in 20,890 individuals of European ancestry from four Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium 14 studies: Atherosclerosis Risk in Communities (ARIC), Cardiovascular Health Study (CHS), FHS and Rotterdam Study (RS-I and RS-II). Given that cigarette smoking is a major risk factor for pulmonary fun...