Abraham D. Flaxman

Bio: Abraham D. Flaxman is an academic researcher from Institute for Health Metrics and Evaluation. The author has contributed to research in topics: Population & Verbal autopsy. The author has an hindex of 66, co-authored 195 publications receiving 88582 citations. Previous affiliations of Abraham D. Flaxman include Microsoft & University of Queensland.

Injuries, Death, and Disability Associated with 11 Years of Conflict in Baghdad, Iraq: A Randomized Household Cluster Survey.

Abstract: BACKGROUND: The objective of this study was to characterize injuries, deaths, and disabilities arising during 11 years of conflict in Baghdad. METHODS: Using satellite imagery and administrative population estimated size for Baghdad, 30 clusters were selected, proportionate to population size estimates. Interviews were conducted during April and May 2014 in 900 households containing 5148 persons. Details about injuries and disabilities occurring from 2003 through May 2014 and resultant disabilities were recorded. FINDINGS: There were 553 injuries reported by Baghdad residents, 225 of which were intentional, and 328 unintentional. For intentional injuries, the fatality rate was 39.1% and the disability rate 56.0%. Gunshots where the major cause of injury through 2006 when blasts/explosions became the most common cause and remained so through 2014. Among unintentional injuries, the fatality rate was 7.3% and the disability rate 77.1%. The major cause of unintentional injuries was falls (131) which have increased dramatically since 2008, followed by traffic related injuries (81), which have steadily increased. The proportion of injuries ending in disabilities remained fairly constant through the survey period. INTERPRETATION: Intentional injuries added substantially to the burden of unintentional injuries for the population. For Baghdad, the phases of the Iraqi conflict are reflected in the patterns of injuries and consequent deaths reported. The scale of injuries during conflict is most certainly under-reported. Difficulties recalling injuries in a survey covering 11 years is a limitation, but it is likely that minor injuries were under-reported more than severe injuries. The in- and out-migration of Baghdad populations likely had effects on the events reported which we could not measure or estimate. Damage to the health infrastructure and the flight of health workers may have contributed to mortality and morbidity. Civilian injuries as well as mortality should be measured during conflicts, though not currently done. Language: en

Variation in life expectancy and mortality by cause among neighbourhoods in King County, WA, USA, 1990–2014: a census tract-level analysis for the Global Burden of Disease Study 2015

Abstract: Summary Background Health outcomes are known to vary at both the country and local levels, but trends in mortality across a detailed and comprehensive set of causes have not been previously described at a very local level. Life expectancy in King County, WA, USA, is in the 95th percentile among all counties in the USA. However, little is known about how life expectancy and mortality from different causes of death vary at a local, neighbourhood level within this county. In this analysis, we estimated life expectancy and cause-specific mortality within King County to describe spatial trends, quantify disparities in mortality, and assess the contribution of each cause of death to overall disparities in all-cause mortality. Methods We applied established so-called garbage code redistribution algorithms and small area estimation methods to death registration data for King County to estimate life expectancy, cause-specific mortality rates, and years of life lost (YLL) rates from 152 causes of death for 397 census tracts from Jan 1, 1990, to Dec 31, 2014. We used the cause list developed for the Global Burden of Disease 2015 study for this analysis. Deaths were tabulated by age group, sex, census tract, and cause of death. We used Bayesian mixed-effects regression models to estimate mortality overall and from each cause. Findings Between 1990 and 2014, life expectancy in King County increased by 5·4 years (95% uncertainty interval [UI] 5·0–5·7) among men (from 74·0 years [73·7–74·3] to 79·3 years [79·1–79·6]) and by 3·4 years (3·0–3·7) among women (from 80·0 years [79·7–80·2] to 83·3 years [83·1–83·5]). In 2014, life expectancy ranged from 68·4 years (95% UI 66·9–70·1) to 86·7 years (85·0–88·2) for men and from 73·6 years (71·6–75·5) to 88·4 years (86·9–89·9) for women among census tracts within King County. Rates of YLL by cause also varied substantially among census tracts for each cause of death. Geographical areas with relatively high and relatively low YLL rates differed by cause. In general, causes of death responsible for more YLLs overall also contributed more significantly to geographical inequality within King County. However, certain causes contributed more to inequality than to overall YLLs. Interpretation This census tract-level analysis of life expectancy and cause-specific YLL rates highlights important differences in health among neighbourhoods in King County that are masked by county-level estimates. Efforts to improve population health in King County should focus on reducing geographical inequality, by targeting those health conditions that contribute the most to overall YLLs and to inequality. This analysis should be replicated in other locations to more fully describe fine-grained local-level variation in population health and contribute to efforts to improve health while reducing inequalities. Funding John W Stanton and Theresa E Gillespie.

Prevalence of Visual Acuity Loss or Blindness in the US: A Bayesian Meta-analysis.

Abstract: Importance Globally, more than 250 million people live with visual acuity loss or blindness, and people in the US fear losing vision more than memory, hearing, or speech. But it appears there are no recent empirical estimates of visual acuity loss or blindness for the US. Objective To produce estimates of visual acuity loss and blindness by age, sex, race/ethnicity, and US state. Data Sources Data from the American Community Survey (2017), National Health and Nutrition Examination Survey (1999-2008), and National Survey of Children’s Health (2017), as well as population-based studies (2000-2013), were included. Study Selection All relevant data from the US Centers for Disease Control and Prevention’s Vision and Eye Health Surveillance System were included. Data Extraction and Synthesis The prevalence of visual acuity loss or blindness was estimated, stratified when possible by factors including US state, age group, sex, race/ethnicity, and community-dwelling or group-quarters status. Data analysis occurred from March 2018 to March 2020. Main Outcomes or Measures The prevalence of visual acuity loss (defined as a best-corrected visual acuity greater than or equal to 0.3 logMAR) and blindness (defined as a logMAR of 1.0 or greater) in the better-seeing eye. Results For 2017, this meta-analysis generated an estimated US prevalence of 7.08 (95% uncertainty interval, 6.32-7.89) million people living with visual acuity loss, of whom 1.08 (95% uncertainty interval, 0.82-1.30) million people were living with blindness. Of this, 1.62 (95% uncertainty interval, 1.32-1.92) million persons with visual acuity loss are younger than 40 years, and 141 000 (95% uncertainty interval, 95 000-187 000) persons with blindness are younger than 40 years. Conclusions and Relevance This analysis of all available data with modern methods produced estimates substantially higher than those previously published.

Standards of Medical Care in Diabetes

Abstract: XI. STRATEGIES FOR IMPROVING DIABETES CARE D iabetes is a chronic illness that requires continuing medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires that many issues, beyond glycemic control, be addressed. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes. These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care. While individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. These standards are not intended to preclude more extensive evaluation and management of the patient by other specialists as needed. For more detailed information, refer to Bode (Ed.): Medical Management of Type 1 Diabetes (1), Burant (Ed): Medical Management of Type 2 Diabetes (2), and Klingensmith (Ed): Intensive Diabetes Management (3). The recommendations included are diagnostic and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A grading system (Table 1), developed by the American Diabetes Association (ADA) and modeled after existing methods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E.