Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010 : a systematic analysis for the Global Burden of Disease Study 2010

Background Non-fatal health outcomes from diseases and injuries are a crucial consideration in the promotion and monitoring of individual and population health. The Global Burden of Disease (GBD) studies done in 1990 and 2000 have been the only studies to quantify non-fatal health outcomes across an exhaustive set of disorders at the global and regional level. Neither effort quantified uncertainty in prevalence or years lived with disability (YLDs). Methods Of the 291 diseases and injuries in the GBD cause list, 289 cause disability. For 1160 sequelae of the 289 diseases and injuries, we undertook a systematic analysis of prevalence, incidence, remission, duration, and excess mortality. Sources included published studies, case notification, population-based cancer registries, other disease registries, antenatal clinic serosurveillance, hospital discharge data, ambulatory care data, household surveys, other surveys, and cohort studies. For most sequelae, we used a Bayesian meta-regression method, DisMod-MR, designed to address key limitations in descriptive epidemiological data, including missing data, inconsistency, and large methodological variation between data sources. For some disorders, we used natural history models, geospatial models, back-calculation models (models calculating incidence from population mortality rates and case fatality), or registration completeness models (models adjusting for incomplete registration with health-system access and other covariates). Disability weights for 220 unique health states were used to capture the severity of health loss. YLDs by cause at age, sex, country, and year levels were adjusted for comorbidity with simulation methods. We included uncertainty estimates at all stages of the analysis. Findings Global prevalence for all ages combined in 2010 across the 1160 sequelae ranged from fewer than one case per 1 million people to 350 000 cases per 1 million people. Prevalence and severity of health loss were weakly correlated (correlation coefficient −0·37). In 2010, there were 777 million YLDs from all causes, up from 583 million in 1990. The main contributors to global YLDs were mental and behavioural disorders, musculoskeletal disorders, and diabetes or endocrine diseases. The leading specific causes of YLDs were much the same in 2010 as they were in 1990: low back pain, major depressive disorder, iron-deficiency anaemia, neck pain, chronic obstructive pulmonary disease, anxiety disorders, migraine, diabetes, and falls. Age-specific prevalence of YLDs increased with age in all regions and has decreased slightly from 1990 to 2010. Regional patterns of the leading causes of YLDs were more similar compared with years of life lost due to premature mortality. Neglected tropical diseases, HIV/AIDS, tuberculosis, malaria, and anaemia were important causes of YLDs in sub-Saharan Africa. Interpretation Rates of YLDs per 100 000 people have remained largely constant over time but rise steadily with age. Population growth and ageing have increased YLD numbers and crude rates over the past two decades. Prevalences of the most common causes of YLDs, such as mental and behavioural disorders and musculoskeletal disorders, have not decreased. Health systems will need to address the needs of the rising numbers of individuals with a range of disorders that largely cause disability but not mortality. Quantification of the burden of non-fatal health outcomes will be crucial to understand how well health systems are responding to these challenges. Effective and affordable strategies to deal with this rising burden are an urgent priority for health systems in most parts of the world. Funding Bill & Melinda Gates Foundation.

Franklin Barley: Patent law and plant breeders’ rights

This paper considers the relationship between patent law and plant breeders' rights in light of modern developments in biotechnology. It examines how a number of superior courts have sought to manage the tensions and conflicts between these competing schemes of intellectual property protection. Part 1 considers the High Court of Australia case of Grain Pool of Western Australia v the Commonwealth dealing with Franklin barley. Part 2 examines the significance of the Supreme Court of the United States decision in JEM Ag Supply Inc v Pioneer Hi-Bred International Inc with respect to utility patents and hybrid seed. Part 3 considers the Supreme Court of Canada case of Harvard College v the Commissioner of Patents dealing with the transgenic animal, oncomouse, and discusses its implications for the forthcoming appeal from the Federal Court case of Percy Schmeiser v Monsanto.

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

Background The 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. Methods 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. Findings 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. Interpretation 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.

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013

Background The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the first of a series of annual updates of the GBD. Risk factor quantification, particularly of modifiable risk factors, can help to identify emerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution. Methods Attributable deaths, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) have been estimated for 79 risks or clusters of risks using the GBD 2010 methods. Risk–outcome pairs meeting explicit evidence criteria were assessed for 188 countries for the period 1990–2013 by age and sex using three inputs: risk exposure, relative risks, and the theoretical minimum risk exposure level (TMREL). Risks are organised into a hierarchy with blocks of behavioural, environmental and occupational, and metabolic risks at the first level of the hierarchy. The next level in the hierarchy includes nine clusters of related risks and two individual risks, with more detail provided at levels 3 and 4 of the hierarchy. Compared with GBD 2010, six new risk factors have been added: handwashing practices, occupational exposure to trichloroethylene, childhood wasting, childhood stunting, unsafe sex, and low glomerular filtration rate. For most risks, data for exposure were synthesised with a Bayesian meta-regression method, DisMod-MR 2.0, or spatial-temporal Gaussian process regression. Relative risks were based on meta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all risks combined took into account evidence on the mediation of some risks such as high body-mass index (BMI) through other risks such as high systolic blood pressure and high cholesterol. Findings All risks combined account for 57·2% (95% uncertainty interval [UI] 55·8–58·5) of deaths and 41·6% (40·1–43·0) of DALYs. Risks quantified account for 87·9% (86·5–89·3) of cardiovascular disease DALYs, ranging to a low of 0% for neonatal disorders and neglected tropical diseases and malaria. In terms of global DALYs in 2013, six risks or clusters of risks each caused more than 5% of DALYs: dietary risks accounting for 11·3 million deaths and 241·4 million DALYs, high systolic blood pressure for 10·4 million deaths and 208·1 million DALYs, child and maternal malnutrition for 1·7 million deaths and 176·9 million DALYs, tobacco smoke for 6·1 million deaths and 143·5 million DALYs, air pollution for 5·5 million deaths and 141·5 million DALYs, and high BMI for 4·4 million deaths and 134·0 million DALYs. Risk factor patterns vary across regions and countries and with time. In sub-Saharan Africa, the leading risk factors are child and maternal malnutrition, unsafe sex, and unsafe water, sanitation, and handwashing. In women, in nearly all countries in the Americas, north Africa, and the Middle East, and in many other high-income countries, high BMI is the leading risk factor, with high systolic blood pressure as the leading risk in most of Central and Eastern Europe and south and east Asia. For men, high systolic blood pressure or tobacco use are the leading risks in nearly all high-income countries, in north Africa and the Middle East, Europe, and Asia. For men and women, unsafe sex is the leading risk in a corridor from Kenya to South Africa. Interpretation Behavioural, environmental and occupational, and metabolic risks can explain half of global mortality and more than one-third of global DALYs providing many opportunities for prevention. Of the larger risks, the attributable burden of high BMI has increased in the past 23 years. In view of the prominence of behavioural risk factors, behavioural and social science research on interventions for these risks should be strengthened. Many prevention and primary care policy options are available now to act on key risks.

En sjukdom af högst elakt släckte : Återfallsfebern på Sveaborg och i Karlskrona 1788-1790

Sommaren 1788 drabbades den svenska flottan av en svårartad febersjukdom. Febern, som senare definierats som febris recurrens el. återfallsfeber, hade sitt ursprung i den ryska flottan. Besättningen ombord skeppet Vladislav, krigsbytet från slaget vid Hogland, bar på ett stort antal smittade klädlöss. Efter flottans ankomst till Sveaborg spred sig sjukdomen snabbt bland manskapet, men även bland fästningens garnison. Förhållandena inom militären, både inom lantarmén och framför allt inom flottan, var gynnsamma för epidemiers spridning. De trånga utrymmena, den ensidiga kosten, det undermåliga dricksvattnet, den bristande hygienen: allt gynnade uppkomsten och spridningen av olika epidemier. Manskapets försämrade allmäntillstånd gjorde, att sjukdomarna blev mera förödande än vad de i andra förhållanden skulle ha varit. Bristen på manskap och material under Gustav III:s ryska krig var enormt, bl.a. var bristen på medicinsk personal och -utrustning skriande. Då flottan och armén drabbades av en epidemi av katastrofala dimensioner stod myndigheterna hjälplösa. Epidemin visaqr tydligt hur illa förberett hela kriget var och hur misskött flottans sjukvård var. På Sveaborg var förhållandena fruktansvärda. Halva garnisonen uppges ha avlidit, och det låg travar av lik överallt. Kaserner m.fl. byggnader adapterades till provisoriska lasarett och det rådde brist på allt. De medicinska myndigheterna representerades av den till fästningen skickade andra fältläkaren, som tillsammans med läkarna på fästningen gjorde sitt bästa i enlighet med tidens vårdmetoder. Då den svenska örlogsflottan i november seglat över tilll Karlskrona spred sig epidemin i staden. Sjukdomen grasserade också bland de civila. Då sjukdomens orsak och utbredningssätt var okända, kunde man varken hindra epidemin från att spridas eller genomföra adekvata vårdmetoder. Tvärtom, med de hemförlovade båtsmännen spred sig sjukdomen även till de övriga delarna av riket. Under 1789 var flottan p.g.a. de många sjukdomsfallen närmast operationsoduglig. Under vårvintern och våren 1790 avtog epidemin. Epidemin var ett svårt medicinskt problem. För att utreda situationen i Karlskrona skickade den tillförordnade regeringen, utredningskommissionen och Collegium medicum sina egna representanter till staden. De olika läkarnas sjukdomssyner grundade sig främst på tron om sjukdomars uppkomst genom miasma och förbättrandet av luftkvaliteten sågs som en väsentlig vårdform. I arbetet jämförs de olika myndigheternas och några av de på platsen varande läkarnas syn på sjukdomens art, dess orsaker och ursprung. De flesta härleder sjukdomen till den ryska flottan, och nämner någon form av smitta. Som främsta sjukdomsorsak nämns dock miasma och de rekommenderade vårdformerna representerade den humoralpatologiska synen. Förste amiralitetsläkaren Arvid Faxe representerar dock en annan åsikt, i det att han enbart tror på sjukdomens överföring via smitta. Epidemin var också ett politiskt problem. Epidemin var en lokal angelägenhet ända till dess att flottans operationer hämmades av manskapsbristen, varefter den blev ett ärende på högsta nivå. Kungen ingrep sommaren 1789 genom att grunda en kommision med rätt vidsträckta befogenheter. I Karlskrona verkar de militära myndigheterna och läkarna ha misstrott och skuldsatt varandra för katastrofen, och förhållandet mellan de till staden sända utredarna och militärerna var likaså inflammerat. Genom källorna återspeglas rivalitet, avund och inbördes konkurrens. Personalbristen var svår, och den skyldiga söktes utanför den egna kretsen. Den danskfödde apotekaren med sina påstott otjänliga mediciner blev en ypperlig syndabock. Örlogsflottan beräknas i sjukdomar ha förlorat omkring 10.000 man i döda, huvudsakligen i Karlskrona (civila inberäknade). Armén och Skärgårdsflottan uppges likadeles ha mist omkring 10.000 man, medan antalet i strid stupade armésoldater endast var ca 1500. Sammanlagt antas alltså ca 20.000 människor ha mist livet; både i återfallsfeber, men även i andra, samtidigt grasserande farsoter. I denna siffra är inte de övriga delarna av riket inberäknade. Epidemin i fråga kan alltså på goda grunder anses vara det svenska 1700-talets största medicinska katastrof.

Genetic population structure of red snappers (Lutjanus malabaricus Bloch & Schneider, 1801 and Lutjanus erythropterus Bloch, 1790) in central and eastern Indonesia and northern Australia

The genetic population structure of red snapper Lutjanus malabaricus and Lutjanus erythropterus in eastern Indonesia and northern Australia was investigated by allozyme electrophoresis and sequence variation in the control region of mtDNA. Samples were collected from eight sites in Indonesia and four sites in northern Australia for both species. A total of 13 allozyme loci were scored. More variable loci were observed in L. malabaricus than in L. erythropterus. Sequence variation in the control region (left domain) of the mitochondrial genome was assessed by RFLP and direct sequencing. MtDNA haplotype diversity was high (L. erythropterus, 0.95 and L. malabaricus, 0.97), as was intraspecific sequence divergence, (L. erythropterus, 0.0-12.5% and L. malabaricus, 0.0-9.5%). The pattern of mtDNA haplotype frequencies grouped both species into two broad fisheries stocks with a genetic boundary either between Kupang and Sape (L. malabaricus) or between Kupang and Australian Timor Sea (L. erythropertus). The allozyme analyses revealed similar boundaries for L. erythropterus. Seven allozymes stocks compared to two mtDNA stocks of L. malabaricus including Ambon, which was not sampled with mtDNA, however, were reported. Possible reasons for differences in discrimination between the methods include: i) increased power of multiple allozyme loci over the single mtDNA locus, ii) insufficient gene sampling in the mtDNA control region and iii) relative evolutionary dynamics of nuclear (allozyme loci) and mitochondrial DNA in these taxa. Allozyme and haplotype data did not distinguish separate stocks among the four Australian locations nor the central Indonesian (Bali and Sape locations) for both L. malabaricus and L. erythropterus.

Elizabeth Engel nee Benjamin-Rasmussen in her home; Silver Springs, Maryland Portraits Women

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Elizabeth Engel nee Benjamin-Rasmussen with her daughter Dorel Hall nee Engel in Elizabeth's home; Silver Springs, Maryland Portraits Family

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Joseph Molling with wife Margarete "Gretchen" nee Benjamin and son Peter on a walk.

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Portrait of Hedwig and Ludwig Heinemann and Margarete nee Benjamin and Joseph Molling.

Elderly couple Hedwig and Ludwig Heinemann envolved with Adolph Molling Business. Younger couple is Margarete "Gretchen" Molling geb. Benjamin and Joseph Molling.

Portrait of Margarete "Gretchen" Molling nee Benjamin.

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Tombstone of Joseph Benjamin; Strangriede Cemetery, R83.8; Hannover Cemeteries Tombs

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Tombstone of Clara Meyer nee Benjamin; Strangriede Cemetery, Hannover Cemeteries; Tombs

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Tombstone of David Benjamin; Strangriede Cemetery (R 84.7); Hannover Cemeteries Tombs

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Tombstone of Frederike Benjamin nee Salamon; Strangriede Cemetery (R 83); Hannover Cemeteries Tombs

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