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...

The burden of cardiovascular diseases (CVDs) remains unclear in many regions of the world. The GBD (Global Burden of Disease) 2015 study integrated data on disease incidence, prevalence, and mortality to produce consistent, up-to-date estimates for cardiovascular burden. CVD mortality was estimated from vital registration and verbal autopsy data. CVD prevalence was estimated using modeling software and data from health surveys, prospective cohorts, health system administrative data, and registries. Years lived with disability (YLD) were estimated by multiplying prevalence by disability weights. Years of life lost (YLL) were estimated by multiplying age-specific CVD deaths by a reference life expectancy. A sociodemographic index (SDI) was created for each location based on income per capita, educational attainment, and fertility. In 2015, there were an estimated 422.7 million cases of CVD (95% uncertainty interval: 415.53 to 427.87 million cases) and 17.92 million CVD deaths (95% uncertainty interval: 17.59 to 18.28 million CVD deaths). Declines in the age-standardized CVD death rate occurred between 1990 and 2015 in all high-income and some middle-income countries. Ischemic heart disease was the leading cause of CVD health lost globally, as well as in each world region, followed by stroke. As SDI increased beyond 0.25, the highest CVD mortality shifted from women to men. CVD mortality decreased sharply for both sexes in countries with an SDI >0.75. CVDs remain a major cause of health loss for all regions of the world. Sociodemographic change over the past 25 years has been associated with dramatic declines in CVD in regions with very high SDI, but only a gradual decrease or no change in most regions. Future updates of the GBD study can be used to guide policymakers who are focused on reducing the overall burden of noncommunicable disease and achieving specific global health targets for CVD.

National levels of personal health-care access and quality can be approximated by measuring mortality rates from causes that should not be fatal in the presence of effective medical care (ie, amenable mortality). Previous analyses of mortality amenable to health care only focused on high-income countries and faced several methodological challenges. In the present analysis, we use the highly standardised cause of death and risk factor estimates generated through the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) to improve and expand the quantification of personal health-care access and quality for 195 countries and territories from 1990 to 2015. We mapped the most widely used list of causes amenable to personal health care developed by Nolte and McKee to 32 GBD causes. We accounted for variations in cause of death certification and misclassifications through the extensive data standardisation processes and redistribution algorithms developed for GBD. To isolate the effects of personal health-care access and quality, we risk-standardised cause-specific mortality rates for each geography-year by removing the joint effects of local environmental and behavioural risks, and adding back the global levels of risk exposure as estimated for GBD 2015. We employed principal component analysis to create a single, interpretable summary measure-the Healthcare Quality and Access (HAQ) Index-on a scale of 0 to 100. The HAQ Index showed strong convergence validity as compared with other health-system indicators, including health expenditure per capita (r=0·88), an index of 11 universal health coverage interventions (r=0·83), and human resources for health per 1000 (r=0·77). We used free disposal hull analysis with bootstrapping to produce a frontier based on the relationship between the HAQ Index and the Socio-demographic Index (SDI), a measure of overall development consisting of income per capita, average years of education, and total fertility rates. This frontier allowed us to better quantify the maximum levels of personal health-care access and quality achieved across the development spectrum, and pinpoint geographies where gaps between observed and potential levels have narrowed or widened over time. Between 1990 and 2015, nearly all countries and territories saw their HAQ Index values improve; nonetheless, the difference between the highest and lowest observed HAQ Index was larger in 2015 than in 1990, ranging from 28·6 to 94·6. Of 195 geographies, 167 had statistically significant increases in HAQ Index levels since 1990, with South Korea, Turkey, Peru, China, and the Maldives recording among the largest gains by 2015. Performance on the HAQ Index and individual causes showed distinct patterns by region and level of development, yet substantial heterogeneities emerged for several causes, including cancers in highest-SDI countries; chronic kidney disease, diabetes, diarrhoeal diseases, and lower respiratory infections among middle-SDI countries; and measles and tetanus among lowest-SDI countries. While the global HAQ Index average rose from 40·7 (95% uncertainty interval, 39·0-42·8) in 1990 to 53·7 (52·2-55·4) in 2015, far less progress occurred in narrowing the gap between observed HAQ Index values and maximum levels achieved; at the global level, the difference between the observed and frontier HAQ Index only decreased from 21·2 in 1990 to 20·1 in 2015. If every country and territory had achieved the highest observed HAQ Index by their corresponding level of SDI, the global average would have been 73·8 in 2015. Several countries, particularly in eastern and western sub-Saharan Africa, reached HAQ Index values similar to or beyond their development levels, whereas others, namely in southern sub-Saharan Africa, the Middle East, and south Asia, lagged behind what geographies of similar development attained between 1990 and 2015. This novel extension of the GBD Study shows the untapped potential for personal health-care access and quality improvement across the development spectrum. Amid substantive advances in personal health care at the national level, heterogeneous patterns for individual causes in given countries or territories suggest that few places have consistently achieved optimal health-care access and quality across health-system functions and therapeutic areas. This is especially evident in middle-SDI countries, many of which have recently undergone or are currently experiencing epidemiological transitions. The HAQ Index, if paired with other measures of health-system characteristics such as intervention coverage, could provide a robust avenue for tracking progress on universal health coverage and identifying local priorities for strengthening personal health-care quality and access throughout the world. Bill & Melinda Gates Foundation.

The objective of this study is to estimate the pooled uptake of cervical cancer screening and identify its predictors in Sub-Saharan Africa. Systematic review and meta-analysis. We searched PubMed, EMBASE, CINAHL, African Journals OnLine, Web of Science and Scopus electronic databases from January 2000 to 2019. All observational studies published in the English language that reported cervical cancer uptake and/or predictors in Sub-Saharan Africa were initially screened. We assessed methodological quality using the Newcastle-Ottawa Scale. An inverse variance-weighted random-effects model meta-analysis was performed to estimate the pooled uptake and odds ratio (OR) of predictors with a 95% confidence interval (CI). The I2 test statistic was used to check between-study heterogeneity, and the Egger's regression statistical test was used to check publication bias. We initially screened 3537 citations and subsequently 29 studies were selected for this review, which included a total of 36,374 women. The uptake of cervical cancer screening in Sub-Saharan Africa was 12.87% (95% CI: 10.20, 15.54; I2 = 98.5%). A meta-analysis of seven studies showed that knowledge about cervical cancer increased screening uptake by nearly five times (OR: 4.81; 95% CI: 3.06, 7.54). Other predictors of cervical screening uptake include educational level, age, Human Immune deficiency Virus (HIV) status, contraceptive use, perceived susceptibility and awareness about screening locations. Cervical screening uptake is low in Sub-Saharan Africa as a result of several factors. Health outreach and promotion programmes to target these identified predictors are required.

Objective: Low neighbourhood socioeconomic status (NSES) has been linked to a higher risk of overweight/obesity, irrespective of the individual’s own socioeconomic status. No meta-analysis study has been done on the association. Thus, this study was done to synthesise the existing evidence on the association of NSES with overweight, obesity and body mass index (BMI).Design: Systematic review and meta-analysis.Data sources: PubMed, Embase, Scopus, Cochrane Library, Web of Sciences and Google Scholar databases were searched for articles published until 25 September 2019.Eligibility criteria: Epidemiological studies, both longitudinal and cross-sectional ones, which examined the link of NSES to overweight, obesity or BMI, were included.Data extraction and synthesis: Data extraction was done by two reviewers, working independently. The methodological quality of included studies was assessed using the Newcastle-Ottawa Scale for the observational studies. The summary estimates of the relationships of NSES with overweight, obesity and BMI statuses were calculated with random-effects meta-analysis models. Heterogeneity was assessed by Cochran’s Q and I²statistics. Subgroup analyses were done by age categories, continents, study designs and NSES measures. Publication bias was assessed by visual inspection of funnel plots and Egger’s regression test.Result: A total of 21 observational studies, covering 1 244 438 individuals, were included in this meta-analysis. Low NSES, compared with high NSES, was found to be associated with a 31% higher odds of overweight (pooled OR 1.31, 95% CI 1.16 to 1.47, p<0.001), a 45% higher odds of obesity (pooled OR 1.45, 95% CI 1.21 to 1.74, p<0.001) and a 1.09 kg/m²increase in mean BMI (pooled beta=1.09, 95% CI 0.67 to 1.50, p<0.001).Conclusion: NSES disparity might be contributing to the burden of overweight/obesity. Further studies are warranted, including whether addressing NSES disparity could reduce the risk of overweight/obesity.PROSPERO registration number: CRD42017063889

The early initiation of breastfeeding (EIBF), or timely initiation of breastfeeding, is the proportion of children put to the breast within one hour of birth. It is an important strategy for reducing perinatal and infant morbidity and mortality, but it remains under practiced in Ethiopia. The aim of the study was to assess the prevalence and the predicting factors associated with EIBF. A community based cross-sectional study was conducted in 634 mothers in Dale Woreda, South Ethiopia. Multistage cluster sampling was used to select participating mothers. EIBF was outcome variable whereas sociodemographic characteristics and knowledge and practice of maternal health service were explanatory variables. A face-to-face interview using a pretested semi-structured questionnaire was done from September 2012 to March 2013. To investigate predicting factors, bivariate and multivariate logistic regression analysis was done. A total of 634 mothers of children under 24 months were interviewed. During the time of data collection, 94.3% of the mothers had breastfed. The prevalence of EIBF was 83.7%. Ownership of the house was a significant predicting factor for EIBF. Mothers who lived in rented houses were significantly less likely (60%) to initiate breastfeeding within one hour of birth compared to mothers who owned their own house: Adjusted odds ratio 0.40 (95% Confidence Interval 0.16, 0.97). More than three-fourths of mothers initiated breastfeeding within an hour. Findings from our study suggest that improving the mother's socioeconomic status as reflected by house ownership, being a significant predictor of EIBF, would have a central role in improving EIBF.