Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015 : a systematic analysis for the Global Burden of Disease Study 2015

Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography-year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61.7 years (95% uncertainty interval 61.4-61.9) in 1980 to 71.8 years (71.5-72.2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11.3 years (3.7-17.4), to 62.6 years (56.5-70.2). Total deaths increased by 4.1% (2.6-5.6) from 2005 to 2015, rising to 55.8 million (54.9 million to 56.6 million) in 2015, but age-standardised death rates fell by 17.0% (15.8-18.1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14.1% (12.6-16.0) to 39.8 million (39.2 million to 40.5 million) in 2015, whereas age-standardised rates decreased by 13.1% (11.9-14.3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42.1%, 39.1-44.6), malaria (43.1%, 34.7-51.8), neonatal preterm birth complications (29.8%, 24.8-34.9), and maternal disorders (29.1%, 19.3-37.1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000-183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000-532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Copyright (C) The Author(s). Published by Elsevier Ltd.Peer reviewe

Correction: Coupled effects of oil spill and hurricane on saltmarsh terrestrial arthropods.

[This corrects the article DOI: 10.1371/journal.pone.0194941.]

Weathering of Oil Spilled in the Marine Environment

Crude oil is a complex mixture of many thousands of mostly hydrocarbon and nitrogen-, sulfur-, and oxygen-containing compounds with molecular weights ranging from below 70 Da to well over 2,000 Da. When this complex mixture enters the environment from spills, ruptures, blowouts, or seeps, it undergoes a continuous series of compositional changes that result from a process known as weathering. Spills of petroleum involving human activity generally result in more rapid input of crude oil or refined products (diesel, gasoline, heavy fuel oil, and diluted bitumens) to the marine system than do natural processes and urban runoffs. The primary physicochemical processes involved in weathering include evaporation, dissolution, emulsification, dispersion, sedimentation/flocculation, microbial degradation, and photooxidation

Weathering of Oil Spilled in the Marine Environment

Crude oil is a complex mixture of many thousands of mostly hydrocarbon and nitrogen-, sulfur-, and oxygen-containing compounds with molecular weights ranging from below 70 Da to well over 2,000 Da. When this complex mixture enters the environment from spills, ruptures, blowouts, or seeps, it undergoes a continuous series of compositional changes that result from a process known as weathering. Spills of petroleum involving human activity generally result in more rapid input of crude oil or refined products (diesel, gasoline, heavy fuel oil, and diluted bitumens) to the marine system than do natural processes and urban runoffs. The primary physicochemical processes involved in weathering include evaporation, dissolution, emulsification, dispersion, sedimentation/flocculation, microbial degradation, and photooxidation

Coupled effects of oil spill and hurricane on saltmarsh terrestrial arthropods

<div><p>Terrestrial arthropods play an important role in saltmarsh ecosystems, mainly affecting the saltmarsh’s primary production as the main consumers of terrestrial primary production and decomposition. Some of these arthropods, including selected insects and spiders, can be used as ecological indicators of overall marsh environmental health, as they are differentially sensitive to ecological stressors, such as land loss, erosion, oil spills, and tropical storms. In the present study, we used terrestrial arthropods collected from seven (three lightly-oiled, four heavily-oiled) sites in Barataria Bay and from three unoiled reference sites in Delacroix, Louisiana, to determine the impacts of the distribution and re-distribution of <i>Deepwater Horizon</i> (DWH) oil on these saltmarsh ecosystems. A total of 9,476 and 12,256 insects were collected in 2013 and 2014, respectively. The results show that the terrestrial arthropods were negatively affected by the re-distribution of DWH oil by Hurricane Isaac in 2012, although the level of impacts varied among the arthropod groups. Moreover, the mean diversity index was higher (>1.5) in 2014 than in 2013 (<1.5) for all sites, suggesting a recovery trajectory of the saltmarsh arthropod population. The higher taxonomic richness observed in the reference sites compared to the oiled sites for both years also indicated long-term impacts of DWH oil to the saltmarsh arthropod community. Whereas a slow recovery of certain terrestrial arthropods was observed, long-term monitoring of arthropod communities would help better understand the recovery and succession of the marsh ecosystems.</p></div

Occurrence of Echinococcusgranulosussensulato and other Taeniids in Bhutan

The present research shows the results of a national study documenting the occurrence and genetic diversity of Echinococcus and Taenia species across Bhutan. Environmental dog faecal samples (n = 953) were collected from 2016 to 2018 in all 20 Bhutanese districts, mainly in urbanised areas. Cystic echinococcosis cysts were isolated from 13 humans and one mithun (Bos frontalis). Isolation of taeniid eggs from faeces was performed by sieving/flotation technique, followed by DNA isolation, PCR and sequence analyses for species identification (gene target: small subunit of ribosomal RNA). Genetic diversity of E. granulosuss.s. was based on the sequence (1609 bp) of the cox1 gene. A total of 67 out of 953 (7%) dog faecal samples were positive for at least one taeniid species. From the 670 free-roaming dog faecal samples, 40 (5.9%) were positive for taeniid DNA, 22 (3.2%) of them were identified as E. granulosuss.s. and four (0.5%) as E. ortleppi (G5). From the 283 faecal samples originating from yak-grazing areas, 27 (9.5%) were taeniid positive, including eight (2.8%) infected with E. granulosuss.s. and four (1.4%) with E. ortleppi. E. granulosuss.s. was identified in all isolates from human and the cyst from mithun. A haplotype network (cox1 gene) from E. granulosuss.s, including isolates from 12 dogs, two human and one mithun, revealed eight different haplotypes. The most common cox1 haplotype was the globally distributed Eg01, followed by Eg40 and Eg37 (previously described in China). Five new cox1 haplotypes (EgBhu1–5) originated from human, dogs, and a mithun were identified. The study indicated the contamination of urban areas and pastures with Echinococcus eggs in seven districts in Bhutan. The molecular characterisation of E. granulosuss.l. revealed different E. granulosuss.s. haplotypes as well as E. ortleppi. The transmission of T. multiceps was documented only in the western part of the country. Considering the zoonotic feature of E. granulosus s.s. and E. ortleppi and the economic impact of coenurosis caused by T. multiceps (also known as gid) in Bhutan, the findings of this study represent a significant contribution towards an epidemiological baseline for the establishment of a national control programme

Mean (±SE) abundance of individual group of arthropods collected per sweep net sample in reference, light oiled and heavily oiled sites in 2013 (blue) and 2014 (orange).

<p>Mean (±SE) abundance of individual group of arthropods collected per sweep net sample in reference, light oiled and heavily oiled sites in 2013 (blue) and 2014 (orange).</p

Effect of treatment (heavily oil, lightly oiled, and reference), year (2013 and 2014) and their interaction (treatment*year) on the insects and spider (p values).

<p>The degree of freedom for treatment (df = 7), year (df = 47) and treatment*year interaction (df = 47) is same for all the arthropods.</p

Geographic coordinates for the treatment sites: heavily oiled, lightly oiled and reference sites.

<p>Geographic coordinates for the treatment sites: heavily oiled, lightly oiled and reference sites.</p