Vital Registration Research Articles

Updates to Spectrum's case surveillance and vital registration tool for HIV estimates and projections.

IntroductionThe Case Surveillance and Vital Registration (CSAVR) model within Spectrum estimates HIV incidence trends from surveillance data on numbers of new HIV diagnoses and HIV‐related deaths. This article describes developments of the CSAVR tool to more flexibly model diagnosis rates over time, estimate incidence patterns by sex and age group and by key population group.MethodsWe modelled HIV diagnosis rate trends as a mixture of three factors, including temporal and opportunistic infection components. The tool was expanded to estimate incidence rate ratios by sex and age for countries with disaggregated reporting of new HIV diagnoses and AIDS deaths, and to account for information on key populations such as men who have sex with men (MSM), males who inject drugs (MWID), female sex workers (FSW) and females who inject drugs (FWID). We used a Bayesian framework to calibrate the tool in 71 high‐income or low‐HIV burden countries.ResultsAcross countries, an estimated median 89% (interquartile range [IQR]: 78%–96%) of HIV‐positive adults knew their status in 2019. Mean CD4 counts at diagnosis were stable over time, with a median of 456 cells/μl (IQR: 391–508) across countries in 2019. In European countries reporting new HIV diagnoses among key populations, median estimated proportions of males that are MSM and MWID was 1.3% (IQR: 0.9%–2.0%) and 0.56% (IQR: 0.51%–0.64%), respectively. The median estimated proportions of females that are FSW and FWID were 0.36% (IQR: 0.27%–0.45%) and 0.14 (IQR: 0.13%–0.15%), respectively. HIV incidence per 100 person‐years increased among MSM, with median estimates reaching 0.43 (IQR: 0.29–1.73) in 2019, but remained stable in MWID, FSW and FWID, at around 0.12 (IQR: 0.04–1.9), 0.09 (IQR: 0.06–0.69) and 0.13% (IQR: 0.08%–0.91%) in 2019, respectively. Knowledge of HIV status among HIV‐positive adults gradually increased since the early 1990s to exceed 75% in more than 75% of countries in 2019 among each key population.ConclusionsCSAVR offers an approach to using routine surveillance and vital registration data to estimate and project trends in both HIV incidence and knowledge of HIV status.

Who dies where? Estimating the percentage of deaths that occur at home

IntroductionThe majority of low-income and middle-income countries (LMICs) have incomplete death registration systems and so the proportion of deaths that occur at home (ie, home death percentage) is generally unknown....

Accounting for misclassified and unknown cause of death data in vital registration systems for estimating trends in HIV mortality.

IntroductionMisclassification of HIV deaths can substantially diminish the usefulness of cause of death data for decision‐making. In this study, we describe the methods developed by the Global Burden of Disease Study to account for the misclassified cause of death data from vital registration systems for estimating HIV mortality in 132 countries and territories.MethodsThe cause of death data were obtained from the World Health Organization Mortality Database and official country‐specific mortality databases. We implemented two steps to adjust the raw cause of death data: (1) redistributing garbage codes to underlying causes of death, including HIV/AIDS by applying methods, such as analysis of multiple cause data and proportional redistribution, and (2) reassigning HIV deaths misclassified as other causes to HIV/AIDS by examining the age patterns of underlying causes in location and years with and without HIV epidemics.ResultsIn 132 countries, during the period from 1990 to 2018, 1,848,761 deaths were reported as caused by HIV/AIDS. After garbage code redistribution in these 132 countries, this number increased to 4,165,015 deaths. An additional 1,944,291 deaths were added through correction of HIV deaths misclassified as other causes in 44 countries. The proportion of HIV deaths derived from garbage code redistribution decreased over time, from 0.4 in 1990 to 0.1 in 2018. The proportion of deaths derived from HIV misclassification correction peaked at 0.4 in 2006 and declined afterwards to 0.08 in 2018. The greatest contributors to garbage code redistribution were “immunodeficiency antibody” (ICD 9: 279‐279.1; ICD 10: D80‐D80.9) and “immunodeficiency other” (ICD 9: 279, 279.5‐279.9; ICD 10: D83‐D84.9, D89, D89.8‐D89.9), which together contributed 77% of all redistributed deaths at their peak in 1995. Respiratory tuberculosis (ICD 9: 010–012.9; ICD 10: A10‐A14, A15‐A16.9) contributed the greatest proportion of all HIV misclassified deaths (25–62% per year) over the most years.ConclusionsCorrecting for miscoding and misclassification of cause of death data can enhance the utility of the data for analyzing trends in HIV mortality and tracking progress toward the Sustainable Development Goal targets.

Estimation of all-cause excess mortality by age-specific mortality patterns for countries with incomplete vital statistics: a population-based study of the case of Peru during the first wave of the COVID-19 pandemic

SummaryBackgroundAll-cause excess mortality is a comprehensive measure of the combined direct and indirect effects of COVID-19 on mortality. Estimates are usually derived from Civil Registration and Vital Statistics (CRVS) systems, but these do not include non-registered deaths, which may be affected by changes in vital registration coverage over time.MethodsOur analytical framework and empirical strategy account for registered mortality and under-registration. This provides a better estimate of the actual mortality impact of the first wave of the COVID-19 pandemic in Peru. We use population and crude mortality rate projections from Peru's National Institute of Statistics and Information (INEI, in Spanish), individual-level registered COVID-19 deaths from the Ministry of Health (MoH), and individual-level registered deaths by region and age since 2017 from the National Electronic Deaths Register (SINADEF, in Spanish).We develop a novel framework combining different estimates and using quasi-Poisson models to estimate total excess mortality across regions and age groups. Also, we use logistic mixed-effects models to estimate the coverage of the new SINADEF system.FindingsWe estimate that registered mortality underestimates national mortality by 37•1% (95% CI 23% - 48•5%) across 26 regions and nine age groups. We estimate total all-cause excess mortality during the period of analysis at 173,099 (95% CI 153,669 - 187,488) of which 108,943 (95% CI 96,507 - 118,261) were captured by the vital registration system. Deaths at age 60 and over accounted for 74•1% (95% CI 73•9% - 74•7%) of total excess deaths, and there were fewer deaths than expected in younger age groups. Lima region, on the Pacific coast and including the national capital, accounts for the highest share of excess deaths, 87,781 (95% CI 82,294 - 92,504), while in the opposite side regions of Apurimac and Huancavelica account for less than 300 excess deaths.InterpretationEstimating excess mortality in low- and middle-income countries (LMICs) such as Peru must take under-registration of mortality into account. Combining demographic trends with data from administrative registries reduces uncertainty and measurement errors. In countries like Peru, this is likely to produce significantly higher estimates of excess mortality than studies that do not take these effects into account.FundingNone.

How reliable are COVID-19 burden estimates for India?

How reliable are COVID-19 burden estimates for India?

Validity of an algorithm to identify cardiovascular deaths from administrative health records: a multi-database population-based cohort study

BackgroundCardiovascular death is a common outcome in population-based studies about new healthcare interventions or treatments, such as new prescription medications. Vital statistics registration systems are often the preferred source of information about cause-specific mortality because they capture verified information about the deceased, but they may not always be accessible for linkage with other sources of population-based data. We assessed the validity of an algorithm applied to administrative health records for identifying cardiovascular deaths in population-based data.MethodsAdministrative health records were from an existing multi-database cohort study about sodium-glucose cotransporter-2 (SGLT2) inhibitors, a new class of antidiabetic medications. Data were from 2013 to 2018 for five Canadian provinces (Alberta, British Columbia, Manitoba, Ontario, Quebec) and the United Kingdom (UK) Clinical Practice Research Datalink (CPRD). The cardiovascular mortality algorithm was based on in-hospital cardiovascular deaths identified from diagnosis codes and select out-of-hospital deaths. Sensitivity, specificity, and positive and negative predictive values (PPV, NPV) were calculated for the cardiovascular mortality algorithm using vital statistics registrations as the reference standard. Overall and stratified estimates and 95% confidence intervals (CIs) were computed; the latter were produced by site, location of death, sex, and age.ResultsThe cohort included 20,607 individuals (58.3% male; 77.2% ≥70 years). When compared to vital statistics registrations, the cardiovascular mortality algorithm had overall sensitivity of 64.8% (95% CI 63.6, 66.0); site-specific estimates ranged from 54.8 to 87.3%. Overall specificity was 74.9% (95% CI 74.1, 75.6) and overall PPV was 54.5% (95% CI 53.7, 55.3), while site-specific PPV ranged from 33.9 to 72.8%. The cardiovascular mortality algorithm had sensitivity of 57.1% (95% CI 55.4, 58.8) for in-hospital deaths and 72.3% (95% CI 70.8, 73.9) for out-of-hospital deaths; specificity was 88.8% (95% CI 88.1, 89.5) for in-hospital deaths and 58.5% (95% CI 57.3, 59.7) for out-of-hospital deaths.ConclusionsA cardiovascular mortality algorithm applied to administrative health records had moderate validity when compared to vital statistics data. Substantial variation existed across study sites representing different geographic locations and two healthcare systems. These variations may reflect different diagnostic coding practices and healthcare utilization patterns.

Uncertainty in computerised analysis of maternal deaths

Maternal mortality continues to be a major concern for global public health despite commendable progress in reducing maternal deaths during the Millennium Development Goal era. Progress in reducing maternal mortality is largely dependent on the pace of achievements in the low-resource settings where the burden of maternal mortality is concentrated. To test the effectiveness of corrective actions, precise measurement of the appropriate indicator is essential. Vital registration systems in most low-resource settings are poor.

Causes and circumstances of maternal death: a secondary analysis of the Community-Level Interventions for Pre-eclampsia (CLIP) trials cohort

SummaryBackgroundIncomplete vital registration systems mean that causes of death during pregnancy and childbirth are poorly understood in low-income and middle-income countries. To inform global efforts to reduce maternal mortality, we compared physician review and computerised analysis of verbal autopsies (interpreting verbal autopsies [InterVA] software), to understand their agreement on maternal cause of death and circumstances of mortality categories (COMCATs) in the Community-Level Interventions for Pre-eclampsia (CLIP) cluster randomised trials.MethodsThe CLIP trials took place in India, Pakistan, and Mozambique, enrolling pregnant women aged 12–49 years between Nov 1, 2014, and Feb 28, 2017. 69 330 pregnant women were enrolled in 44 clusters (36 008 in the 22 intervention clusters and 33 322 in the 22 control clusters). In this secondary analysis of maternal deaths in CLIP, we included women who died in any of the 22 intervention clusters or 22 control clusters. Trained staff administered the WHO 2012 verbal autopsy after maternal deaths. Two physicians (and a third for consensus, if needed) reviewed trial surveillance data and verbal autopsies, and, in intervention clusters, community health worker-led visit data. They determined cause of death according to the WHO International Classification of Diseases-Maternal Mortality (ICD-MM). Verbal autopsies were also analysed by InterVA computer models (versions 4 and 5) to generate cause of death. COMCAT analysis was provided by InterVA-5 and, in India, by physician review of Maternal Newborn Health Registry data. Causes of death and COMCATs assigned by physician review, Inter-VA-4, and InterVA-5 were compared, with agreement assessed with Cohen's κ coefficient.FindingsOf 61 988 pregnancies with successful follow-up in the CLIP trials, 143 maternal deaths were reported (16 deaths in India, 105 in Pakistan, and 22 in Mozambique). The maternal death rate was 231 (95% CI 193–268) per 100 000 identified pregnancies. Most deaths were attributed to direct maternal causes (rather than indirect or undetermined causes as per ICD-MM classification), with fair to good agreement between physician review and InterVA-4 (κ=0·56 [95% CI 0·43–0·66]) or InterVA-5 (κ=0·44 [0·30–0·57]), and InterVA-4 and InterVA-5 (κ=0·72 [0·60–0·84]). The top three causes of death were the same by physician review, InterVA-4, and InterVA-5 (ICD-MM categories obstetric haemorrhage, non-obstetric complications, and hypertensive disorders); however, attribution of individual patient deaths to obstetric haemorrhage varied more between methods (physician review, 38 [27%] deaths; InterVA-4, 69 [48%] deaths; and InterVA-5, 82 [57%] deaths), than did attribution to non-obstetric causes (physician review, 39 [27%] deaths; InterVA-4, 37 [26%] deaths; and InterVA-5, 28 [20%] deaths) or hypertensive disorders (physician review, 23 [16%] deaths; InterVA-4, 25 [17%] deaths; and InterVA-5, 24 [17%] deaths). Agreement for all nine ICD-MM categories was fair for physician review versus InterVA-4 (κ=0·48 [0·38–0·58]), poor for physician review versus InterVA-5 (κ=0·36 [0·27–0·46]), and good for InterVA-4 versus InterVA-5 (κ=0·69 [0·59–0·79]). The most commonly assigned COMCATs by InterVA-5 were emergencies (68 [48%] of 143 deaths) and health systems (62 [43%] deaths), and by physician review (India only) were health systems (seven [44%] of 16 deaths) and inevitability (five [31%] deaths); agreement between InterVA-5 and physician review (India data only) was poor (κ=0·04 [0·00–0·15]).InterpretationOur findings indicate that InterVA-5 is less accurate than InterVA-4 at ascertaining causes and circumstances of maternal death, when compared with physician review. Our results suggest a need to improve the next iteration of InterVA, and for researchers and clinicians to preferentially use InterVA-4 when recording maternal deaths.FundingUniversity of British Columbia (grantee of the Bill & Melinda Gates Foundation).

Global reporting of pulmonary embolism–related deaths in the World Health Organization mortality database: Vital registration data from 123 countries

IntroductionPulmonary embolism (PE) has not been accounted for as a cause of death contributing to cause‐specific mortality in global reports. MethodsWe analyzed global PE‐related mortality by focusing on the latest year available for each member state in the World Health Organization (WHO) mortality database, which provides age‐sex–specific aggregated mortality data transmitted by national authorities for each underlying cause of death. PE‐related deaths were defined by International Classification of Diseases, Tenth Revision codes for acute PE or nonfatal manifestations of venous thromboembolism (VTE). The 2001 WHO standard population served for standardization. ResultsWe obtained data from 123 countries covering a total population of 2 602 561 422. Overall, 50 (40.6%) were European, 39 (31.7%) American, 13 (10.6%) Eastern Mediterranean, 13 (10.6%) Western Pacific, 3 (2.4%) Southeast Asian, and 2 (1.6%) African. Of 116 countries classifiable according to population income, 57 (49.1%) were high income, 42 (36.2%) upper‐middle income, 14 (12.1%) lower‐middle income, and 3 (2.6%) low income. A total of 18 726 382 deaths were recorded, of which 86 930 (0.46%) were attributed to PE. PE‐related mortality rate increased with age in most countries. The reporting of PE‐related deaths was heterogeneous, with an age‐standardized mortality rate ranging from 0 to 24 deaths per 100 000 population‐years. Income status only partially explained this heterogeneity. ConclusionsReporting of PE‐related mortality in official national vital registration was characterized by extreme heterogeneity across countries. These findings mandate enhanced efforts toward systematic and uniform coverage of PE‐related mortality and provides a case for full recognition of PE and VTE as a primary cause of death.

Excess Mortality During the COVID-19 Pandemic in Philadelphia.

Objectives. To estimate excess all-cause mortality in Philadelphia, Pennsylvania, during the COVID-19 pandemic and understand the distribution of excess mortality in the population. Methods. With a Poisson model trained on recent historical data from the Pennsylvania vital registration system, we estimated expected weekly mortality in 2020. We compared these estimates with observed mortality to estimate excess mortality. We further examined the distribution of excess mortality by age, sex, and race/ethnicity. Results. There were an estimated 3550 excess deaths between March 22, 2020, and January 2, 2021, a 32% increase above expectations. Only 77% of excess deaths (n = 2725) were attributed to COVID-19 on the death certificate. Excess mortality was disproportionately high among older adults and people of color. Sex differences varied by race/ethnicity. Conclusions. Excess deaths during the pandemic were not fully explained by COVID-19 mortality; official counts significantly undercount the true death toll. Far from being a great equalizer, the COVID-19 pandemic has exacerbated preexisting disparities in mortality by race/ethnicity. Public Health Implications. Mortality data must be disaggregated by age, sex, and race/ethnicity to accurately understand disparities among groups.

Public health utility of cause of death data: applying empirical algorithms to improve data quality

BackgroundAccurate, comprehensive, cause-specific mortality estimates are crucial for informing public health decision making worldwide. Incorrectly or vaguely assigned deaths, defined as garbage-coded deaths, mask the true cause distribution. The Global Burden of Disease (GBD) study has developed methods to create comparable, timely, cause-specific mortality estimates; an impactful data processing method is the reallocation of garbage-coded deaths to a plausible underlying cause of death. We identify the pattern of garbage-coded deaths in the world and present the methods used to determine their redistribution to generate more plausible cause of death assignments.MethodsWe describe the methods developed for the GBD 2019 study and subsequent iterations to redistribute garbage-coded deaths in vital registration data to plausible underlying causes. These methods include analysis of multiple cause data, negative correlation, impairment, and proportional redistribution. We classify garbage codes into classes according to the level of specificity of the reported cause of death (CoD) and capture trends in the global pattern of proportion of garbage-coded deaths, disaggregated by these classes, and the relationship between this proportion and the Socio-Demographic Index. We examine the relative importance of the top four garbage codes by age and sex and demonstrate the impact of redistribution on the annual GBD CoD rankings.ResultsThe proportion of least-specific (class 1 and 2) garbage-coded deaths ranged from 3.7% of all vital registration deaths to 67.3% in 2015, and the age-standardized proportion had an overall negative association with the Socio-Demographic Index. When broken down by age and sex, the category for unspecified lower respiratory infections was responsible for nearly 30% of garbage-coded deaths in those under 1 year of age for both sexes, representing the largest proportion of garbage codes for that age group. We show how the cause distribution by number of deaths changes before and after redistribution for four countries: Brazil, the United States, Japan, and France, highlighting the necessity of accounting for garbage-coded deaths in the GBD.ConclusionsWe provide a detailed description of redistribution methods developed for CoD data in the GBD; these methods represent an overall improvement in empiricism compared to past reliance on a priori knowledge.

947-P: Racial/Ethnic Differences in Type 2 Diabetes Diagnosis among Women with Gestational Diabetes: Creation of a Diverse Population-Based Eight-Year Postpartum Diabetes Cohort

Background: Women with gestational diabetes (GDM) are at increased risk of developing type 2 diabetes, a leading cause of premature morality. While data suggest racial/ethnic minority women bear the disproportionate burden of gestational diabetes, current postpartum GDM cohorts lack adequate diversity to examine whether racial/ethnic disparities persist in the transition to type 2 diabetes. To address this gap, we make use of two NYC public health surveillance databases to construct a novel population-based cohort of women with gestational diabetes and their progression to diabetes diagnosis. Methods: We used a systematic matching process to identify unique cases of women who gave birth between 2009 and 2011 and diabetes diagnosis (two A1c results6.5%) in the following 8 years using linked NYC vital statistics and HbA1c registry data. Results: Of 16,231 women with gestational diabetes, the cumulative incidence of diabetes in 8 years of follow-up was 14.4% (N=2,333 cases) in the overall cohort, 21.1% among non-Hispanic Black women, 15.9% among Hispanic women, 12.3% among Asian women, and 6.1% among non-Hispanic white women. Using this diverse cohort, future analyses will examine racial/ethnic differences in disease progression (e.g., from diabetes to glycemic control) among women with gestational diabetes, which has not been well studied in prior cohorts. Conclusions: This study makes use of diverse public health surveillance data to construct a population-based postpartum cohort of pregnant women to produce pioneering evidence of diabetes disease progression (using HbA1c levels) following pregnancies complicated by GDM. Future research will leverage this novel cohort to investigate how social determinants influence lifecourse racial-ethnic disparities in diabetes. Disclosure T. Janevic: None. K. J. Mccarthy: None. J. J. Kennedy: None. H. Chan: None. G. Van wye: None. V. L. Mayer: None. S. H. Liu: None. M. Huynh: None. Funding National Institutes of Health (R21DK122266)

Bayesian hierarchical factor regression models to infer cause of death from verbal autopsy data.

In low-resource settings where vital registration of death is not routine it is often of critical interest to determine and study the cause of death (COD) for individuals and the cause-specific mortality fraction (CSMF) for populations. Post-mortem autopsies, considered the gold standard for COD assignment, are often difficult or impossible to implement due to deaths occurring outside the hospital, expense, and/or cultural norms. For this reason, Verbal Autopsies (VAs) are commonly conducted, consisting of a questionnaire administered to next of kin recording demographic information, known medical conditions, symptoms, and other factors for the decedent. This article proposes a novel class of hierarchical factor regression models that avoid restrictive assumptions of standard methods, allow both the mean and covariance to vary with COD category, and can include covariate information on the decedent, region, or events surrounding death. Taking a Bayesian approach to inference, this work develops an MCMC algorithm and validates the FActor Regression for Verbal Autopsy (FARVA) model in simulation experiments. An application of FARVA to real VA data shows improved goodness-of-fit and better predictive performance in inferring COD and CSMF over competing methods. Code and a user manual are made available at https://github.com/kelrenmor/farva.

Estimation of older-adult mortality from information distorted by systematic age misreporting

Testing theories about human senescence and longevity demands accurate information on older-adult mortality; this is rare in low- to middle-income countries where raw data may be distorted by defective completeness and systematic age misreporting. For this reason, such populations are frequently excluded from empirical tests of mortality and longevity theories, thus limiting their reach, as they reflect only a small and selected human mortality experience. In this paper we formulate an integrated method to compute estimates of older-adult mortality when vital registration and population counts are defective due to inaccurate coverage and/or systematic age misreporting. The procedure is validated with a simulation study that identifies a strategy to compute adjustments, which, under some assumptions, performs quite well. While the paper focuses on Latin American and Caribbean countries, the method is quite general and, with additional information and some model reformulation, could be applied to other populations with similar problems.

Changes in body mass index, obesity, and overweight in Southern Africa development countries, 1990 to 2019: Findings from the Global Burden of Disease, Injuries, and Risk Factors Study.

BackgroundHigh body mass index (BMI) is associated with stroke, ischemic heart disease (IHD), and type 2 diabetes mellitus (T2DM). An epidemiological analysis of the prevalence of high BMI, stroke, IHD, and T2DM was conducted for 16 Southern Africa Development Community (SADC) using Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study data.MethodsGBD obtained data from vital registration, verbal autopsy, and ICD codes. Prevalence of high BMI (≥25 kg/m2), stroke, IHD, and T2DM attributed to high BMI were calculated. Cause of Death Ensemble Model and Spatiotemporal Gaussian regression was used to estimate mortality due to stroke, IHD, and T2DM attributable to high BMI.ResultsObesity in adult females increased 1.54‐fold from 12.0% (uncertainty interval [UI]: 11.5–12.4) to 18.5% (17.9–19.0), whereas in adult males, obesity nearly doubled from 4.5 (4.3–4.8) to 8.8 (8.5–9.2). In children, obesity more than doubled in both sexes, and overweight increased by 27.4% in girls and by 37.4% in boys. Mean BMI increased by 0.7 from 22.4 (21.6–23.1) to 23.1 (22.3–24.0) in adult males, and by 1.0 from 23.8 (22.9–24.7) to 24.8 (23.8–25.8) in adult females. South Africa 44.7 (42.5–46.8), Swaziland 33.9 (31.7–36.0) and Lesotho 31.6 (29.8–33.5) had the highest prevalence of obesity in 2019. The corresponding prevalence in males for the three countries were 19.1 (17.5–20.7), 19.3 (17.7–20.8), and 9.2 (8.4–10.1), respectively. The DRC and Madagascar had the least prevalence of adult obesity, from 5.6 (4.8–6.4) and 7.0 (6.1–7.9), respectively in females in 2019, and in males from 4.9 (4.3–5.4) in the DRC to 3.9 (3.4–4.4) in Madagascar.ConclusionsThe prevalence of high BMI is high in SADC. Obesity more than doubled in adults and nearly doubled in children. The 2019 mean BMI for adult females in seven countries exceeded 25 kg/m2. SADC countries are unlikely to meet UN2030 SDG targets. Prevalence of high BMI should be studied locally to help reduce morbidity.

Trends in mortality related to pulmonary embolism in the DACH countries: data from the WHO Mortality Database

Abstract Funding Acknowledgements Type of funding sources: None. Background Little is known about the burden imposed by pulmonary embolism for Germany, Austria and Switzerland (DACH countries). Purpose We aimed to assess pulmonary embolism-related mortality and time trends for the DACH countries based on data from the WHO Mortality Database. Methods We analysed vital registration data from the WHO Mortality Database (2000–2016) covering subregions of the WHO European Region: Germany, Switzerland and Austria (DACH countries). Deaths were considered pulmonary embolism-related if International Classification of Disease-10 code for acute pulmonary embolism or any code for deep or superficial vein thrombosis was listed as the primary cause of death. Results Between 2000 and 2016, age-standardised annual pulmonary embolism-related mortality rates decreased linearly from 15.6 to 7.8 deaths per 1000 population. In the 5-year period between 2012 and 2016 an average of 9127 pulmonary embolism-related deaths occurred annually in the DACH countries with a population of 98 273 329. Interestingly, pulmonary embolism-related mortality rates were considerable higher among women aged 15-55 years compared to age-matched men. Between 2012 and 2016, Germany showed the highest age-adjusted mortality rate (9.2 to 10.8 per 100000 inhabitants) compared to Switzerland 4.9-5.3 per 100000 inhabitants) and Austria (5.2 to 6.0 per 100000 inhabitants). Moreover, this means that the age-adjusted mortality rate in Germany was higher than the West-European average. Conclusion The observed decreasing trends in pulmonary embolism-related mortality might reflect improved management of the disease including new treatment options as well as advances in imaging technologies. However, pulmonary embolism remains a substantial contributor to total mortality, especially among women aged 15–55 years. For this reason, campaigns to increase physician and public awareness are urgently required for further improvement of the management and treatment of this preventable thrombotic disorder, which still remains the leading preventable cause of death.

Knowledge, attitudes, and perceptions of Kenyan healthcare workers regarding pediatric discharge from hospital.

ObjectiveTo assess attitudes, perceptions, and practices of healthcare workers regarding hospital discharge and follow-up care for children under age five in Migori and Homa Bay, Kenya.MethodsThis mixed-methods study included surveys and semi-structured telephone interviews with healthcare workers delivering inpatient pediatric care at eight hospitals between November 2017 and December 2018.ResultsThe survey was completed by 111 (85%) eligible HCWs. Ninety-seven of the surveyed HCWs were invited for interviews and 39 (40%) participated. Discharge tasks were reported to be “very important” to patient outcomes by over 80% of respondents, but only 37 (33%) perceived their hospital to deliver this care “very well” and 23 (21%) believed their facility provides sufficient resources for its provision. The vast majority (97%) of participants underestimated the risk of pediatric post-discharge mortality. Inadequate training, understaffing, stock-outs of take-home therapeutics, and user fees were commonly reported health systems barriers to adequate discharge care while poverty was seen as limiting caregiver adherence to discharge and follow-up care. Respondents endorsed the importance of follow-up care, but reported supportive mechanisms to be lacking. They requested enhanced guidelines on discharge and follow-up care.ConclusionKenyan healthcare workers substantially underestimated the risk of pediatric post-discharge mortality. Pre- and in-service training should incorporate instruction on discharge and follow-up care. Improved post-discharge deaths tracking–e.g., through vital registry systems, child mortality surveillance studies, and community health worker feedback loops–is needed, alongside dissemination which could leverage platforms such as routine hospital-based mortality reports. Finally, further interventional trials are needed to assess the efficacy and cost-effectiveness of novel packages to improve discharge and follow-up care.

Burden of Tracheal, Bronchus, and Lung Cancer and Its Attributable Risk Factors in 204 Countries and Territories, 1990 to 2019

IntroductionUnderstanding trends in the annual incidence, mortality, and disability-adjusted life-years (DALYs) for tracheal, bronchus, and lung (TBL) cancer globally is important to enable appropriate targeting of resources for prevention, clinical practice improvement, and research. The aim of this study was to determine the global, regional, and national burdens of TBL cancer in 204 countries and territories from 1990 to 2019 by age, sex, and sociodemographic index. MethodsEstimates were produced through various data inputs including the following: cancer registries (nsite-years = 5318), vital registration (nsite-years = 22,553), vital registration-sample (nsite-years = 825), and verbal autopsies (nsite-years = 516). Annual incidence, mortality, and DALYs were estimated and presented as counts and age-standardized rates per 100,000 population. ResultsThere were 2.3 million (95% uncertainty interval [UI]: 2.1–2.5) incident cases of TBL cancer, with an age-standardized annual incidence rate of 27.7 (95% UI: 25.3–30), which decreased by 2.6% (95% UI: −12.4 to 6.5) between 1990 and 2019. TBL cancer was responsible for 2 million (95% UI: 1.9–2.2) deaths globally with an age-standardized death rate of 25.2 (95% UI: 23.2–27), a decrease of 7.8% (95% UI: −15.9 to 0.2) between 1990 and 2019. Moreover, TBL accounted for 45.9 million (95% UI: 42.3–49.3) DALYs at the global level, with an age-standardized rate of 551.6 (95% UI: 509–593.1) DALYs per 100,000 population. The standardized DALY rate declined by 16.2% (95% UI: −24 to −8.2) from 1990 to 2019. Greenland (77.7 [95% UI: 64.4–90.6]), Monaco (75.6 [95% UI: 61.4–90.8]), and Montenegro (56.7 [95% UI: 46.5–68.9]) had the three highest age-standardized annual incidence rates. The aforementioned three countries also had the three highest age-standardized death and DALY rates of TBL cancer. Honduras (68% [95% UI: 14.5–137.7]), Cabo Verde (62.2% [95% UI: 24.1–101.3]), and Monaco (58.2% [95% UI: 19.2–109.7]) had the largest increase in age-standardized annual incidence rates for TBL cancer during 1990 to 2019. The largest increases were found in age-standardized death rates of TBL cancer in Honduras (67.1% [95% UI: 14.7–133.1]), Cabo Verde (64.4% [95% UI: 25–103.4]), and Mozambique (49.9% [95% UI: 7.9 –101.3]). Age-standardized annual incidence and death rates were higher in male than female individuals and increased with population aging. There were nonlinear but generally positive associations between age-standardized DALY rates with corresponding sociodemographic index of countries. Globally, smoking (62.4%), ambient particulate matter (15.3%), and high fasting plasma glucose (9.9%) had the top three highest percent of attributable DALYs owing to TBL cancer in 2019 for both sexes. ConclusionsThis study found a decline in burden globally but with some countries having an increase. These results are crucial to set priorities for prevention and treatment of TBL cancer and would be beneficial for policymakers, government officials, clinicians, and researchers.

Mexican mortality 1990‒2016: Comparison of unadjusted and adjusted estimates

Background: Vital statistics registration and census counts for Mexico may be incomplete, resulting in unreliable mortality indicators. Objective: We evaluate unadjusted mortality estimates for Mexico during 1990‒2016 and compare them with other published estimates for Mexico and with the historical mortality patterns observed among the 41 Human Mortality Database (HMD) populations. Finally, we investigate the effect of various adjustments on estimated life expectancy. Methods: We apply the HMD methodology to the official vital statistics and census counts to construct unadjusted life table series for Mexico. Then we make adjustments by substituting revised estimates for child mortality and by fitting a log-quadratic model. Results: Adjusted estimates of mortality below age 5 derived by the UN Inter-agency Group for Child Mortality Estimation (IGME) are up to 48% higher than our unadjusted estimates. Even in 2015, the IGME-adjusted estimates of child mortality remain at least 10% higher than our unadjusted estimates. Our analysis suggests that there may also be underestimation of mortality at both prime adult ages and the oldest ages. The log-quadratic model produced the lowest estimates of life expectancy at birth (3.8‒4.4 years lower than the unadjusted values in 1995). Conclusions: Unadjusted estimates are likely to underestimate mortality in Mexico, even in recent years. Adjustments may improve the accuracy of the mortality estimates, but we cannot adjudicate which set of adjusted estimates is closest to reality. Contribution: This is the first time the HMD methodology has been applied to the Mexican data.

A closer look at patterns and characteristics of suicide in Lebanon: A first nationwide report of cases from 2008 to 2018.

Suicide is a leading preventable cause of mortality worldwide. Suicide rates in Lebanon are unknown, as reported numbers are extrapolated and modeled over neighboring countries with poor quality of vital registration data. Numbers of death by suicide were obtained from the Internal Security Forces records from January 2008 through December 2018. Records from 2011 through 2018 specified the gender of the individual, the means of the suicide, the date and place of suicide. As of March 2014, nationality of the individual was recorded. The total recorded number of completed suicides over 11 years is 1366 with an annual rate ranging between 1.87 and 2.4 per 100,000 capita. The male to female ratio was 2:1. Death by firearms (41.4 %) was the most common means used, followed by hanging (26.5 %), jumping from a height (13.6 %), and poisoning (13.5 %). Males were more likely to use firearms while females were more likely to use hanging or jumping from a height (p < 0.001), the latter being a common finding in non-Lebanese nationals (Ethiopian). Suicides were most common in Mount Lebanon and least common in Nabatieh governates, while their distribution across seasons was similar. In Lebanon, like most of the Middle Eastern countries, suicide is a social and religious taboo. Our study shows a sizable prevalence of suicide rates, particularly after national efforts to improve awareness and reporting. Suicide means and vulnerable populations should be at the heart of targeted prevention strategies.