Impact of nonoptimal intakes of saturated, polyunsaturated, and trans fat on global burdens of coronary heart disease

Background: Saturated fat (SFA), ω‐6 (n‐6) polyunsaturated fat (PUFA), and trans fat (TFA) influence risk of coronary heart disease (CHD), but attributable CHD mortalities by country, age, sex, and time are unclear. Methods and Results: National intakes of SFA, n‐6 PUFA, and TFA were estimated using a Bayesian hierarchical model based on country‐specific dietary surveys; food availability data; and, for TFA, industry reports on fats/oils and packaged foods. Etiologic effects of dietary fats on CHD mortality were derived from meta‐analyses of prospective cohorts and CHD mortality rates from the 2010 Global Burden of Diseases study. Absolute and proportional attributable CHD mortality were computed using a comparative risk assessment framework. In 2010, nonoptimal intakes of n‐6 PUFA, SFA, and TFA were estimated to result in 711 800 (95% uncertainty interval [UI] 680 700–745 000), 250 900 (95% UI 236 900–265 800), and 537 200 (95% UI 517 600–557 000) CHD deaths per year worldwide, accounting for 10.3% (95% UI 9.9%–10.6%), 3.6%, (95% UI 3.5%–3.6%) and 7.7% (95% UI 7.6%–7.9%) of global CHD mortality. Tropical oil–consuming countries were estimated to have the highest proportional n‐6 PUFA– and SFA‐attributable CHD mortality, whereas Egypt, Pakistan, and Canada were estimated to have the highest proportional TFA‐attributable CHD mortality. From 1990 to 2010 globally, the estimated proportional CHD mortality decreased by 9% for insufficient n‐6 PUFA and by 21% for higher SFA, whereas it increased by 4% for higher TFA, with the latter driven by increases in low‐ and middle‐income countries. Conclusions: Nonoptimal intakes of n‐6 PUFA, TFA, and SFA each contribute to significant estimated CHD mortality, with important heterogeneity across countries that informs nation‐specific clinical, public health, and policy priorities.peer-reviewe

ESPON 3.2 - Data Navigator 2 - Final Report: Handbook for Data Collection

This report is divided in four parts: 1. The Data circuit part describes briefly the system of data collectionset up in the first phase of the ESPON program by giving an global overview (1.1). We present the dual role of Transnational Project Groups which are, at the same time, users and producers of data and, consequently, both receive input data (1.2) from multiple sources and send output data (1.3) towards the ESPON DB. 2. The Rules for data collection part firstly gives some general principles for data collection which are summed up in the form of “10 commandments” (2.1). These commandments come from an analysis of the data circuit presented in section 1. They also enlighten the necessity of re-thinking the data circuit and the way data are stored and managed. We therefore propose a new data model, called Long Term Data Base, whose main aim is to guaranty the right application of the commandments (2.2). Then, we show that this model also serves as a support for both the estimation of missing values and the elaboration of practical rules for quality control (2.3). 3. The recommendations for ESPON 2013 concludes this first part and summarises our proposals for further research. 4. The Experiences part presents, in a separate part, a set of concrete examples built by the experts of our group and which deal with the thematic harmonization of data (4.1), the extensive use ofnational sources (4.2) and the integration of environmental and socio-economic data (4.3)

ESPON 3.2 - Data Navigator 2 - Final Report: Handbook for Data Collection

This report is divided in four parts: 1. The Data circuit part describes briefly the system of data collectionset up in the first phase of the ESPON program by giving an global overview (1.1). We present the dual role of Transnational Project Groups which are, at the same time, users and producers of data and, consequently, both receive input data (1.2) from multiple sources and send output data (1.3) towards the ESPON DB. 2. The Rules for data collection part firstly gives some general principles for data collection which are summed up in the form of “10 commandments” (2.1). These commandments come from an analysis of the data circuit presented in section 1. They also enlighten the necessity of re-thinking the data circuit and the way data are stored and managed. We therefore propose a new data model, called Long Term Data Base, whose main aim is to guaranty the right application of the commandments (2.2). Then, we show that this model also serves as a support for both the estimation of missing values and the elaboration of practical rules for quality control (2.3). 3. The recommendations for ESPON 2013 concludes this first part and summarises our proposals for further research. 4. The Experiences part presents, in a separate part, a set of concrete examples built by the experts of our group and which deal with the thematic harmonization of data (4.1), the extensive use ofnational sources (4.2) and the integration of environmental and socio-economic data (4.3)

Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990-2013: quantifying the epidemiological transition.

International audienceThe Global Burden of Disease Study 2013 (GBD 2013) aims to bring together all available epidemiological data using a coherent measurement framework, standardised estimation methods, and transparent data sources to enable comparisons of health loss over time and across causes, age-sex groups, and countries. The GBD can be used to generate summary measures such as disability-adjusted life-years (DALYs) and healthy life expectancy (HALE) that make possible comparative assessments of broad epidemiological patterns across countries and time. These summary measures can also be used to quantify the component of variation in epidemiology that is related to sociodemographic development. We used the published GBD 2013 data for age-specific mortality, years of life lost due to premature mortality (YLLs), and years lived with disability (YLDs) to calculate DALYs and HALE for 1990, 1995, 2000, 2005, 2010, and 2013 for 188 countries. We calculated HALE using the Sullivan method; 95% uncertainty intervals (UIs) represent uncertainty in age-specific death rates and YLDs per person for each country, age, sex, and year. We estimated DALYs for 306 causes for each country as the sum of YLLs and YLDs; 95% UIs represent uncertainty in YLL and YLD rates. We quantified patterns of the epidemiological transition with a composite indicator of sociodemographic status, which we constructed from income per person, average years of schooling after age 15 years, and the total fertility rate and mean age of the population. We applied hierarchical regression to DALY rates by cause across countries to decompose variance related to the sociodemographic status variable, country, and time. Worldwide, from 1990 to 2013, life expectancy at birth rose by 6·2 years (95% UI 5·6-6·6), from 65·3 years (65·0-65·6) in 1990 to 71·5 years (71·0-71·9) in 2013, HALE at birth rose by 5·4 years (4·9-5·8), from 56·9 years (54·5-59·1) to 62·3 years (59·7-64·8), total DALYs fell by 3·6% (0·3-7·4), and age-standardised DALY rates per 100 000 people fell by 26·7% (24·6-29·1). For communicable, maternal, neonatal, and nutritional disorders, global DALY numbers, crude rates, and age-standardised rates have all declined between 1990 and 2013, whereas for non-communicable diseases, global DALYs have been increasing, DALY rates have remained nearly constant, and age-standardised DALY rates declined during the same period. From 2005 to 2013, the number of DALYs increased for most specific non-communicable diseases, including cardiovascular diseases and neoplasms, in addition to dengue, food-borne trematodes, and leishmaniasis; DALYs decreased for nearly all other causes. By 2013, the five leading causes of DALYs were ischaemic heart disease, lower respiratory infections, cerebrovascular disease, low back and neck pain, and road injuries. Sociodemographic status explained more than 50% of the variance between countries and over time for diarrhoea, lower respiratory infections, and other common infectious diseases; maternal disorders; neonatal disorders; nutritional deficiencies; other communicable, maternal, neonatal, and nutritional diseases; musculoskeletal disorders; and other non-communicable diseases. However, sociodemographic status explained less than 10% of the variance in DALY rates for cardiovascular diseases; chronic respiratory diseases; cirrhosis; diabetes, urogenital, blood, and endocrine diseases; unintentional injuries; and self-harm and interpersonal violence. Predictably, increased sociodemographic status was associated with a shift in burden from YLLs to YLDs, driven by declines in YLLs and increases in YLDs from musculoskeletal disorders, neurological disorders, and mental and substance use disorders. In most country-specific estimates, the increase in life expectancy was greater than that in HALE. Leading causes of DALYs are highly variable across countries. Global health is improving. Population growth and ageing have driven up numbers of DALYs, but crude rates have remained relatively constant, showing that progress in health does not mean fewer demands on health systems. The notion of an epidemiological transition--in which increasing sociodemographic status brings structured change in disease burden--is useful, but there is tremendous variation in burden of disease that is not associated with sociodemographic status. This further underscores the need for country-specific assessments of DALYs and HALE to appropriately inform health policy decisions and attendant actions. Bill & Melinda Gates Foundation