Last data update: Jun 11, 2024. (Total: 46992 publications since 2009)
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Estimating causes of death where there is no medical certification: evolution and state of the art of verbal autopsy
Chandramohan D , Fottrell E , Leitao J , Nichols E , Clark SJ , Alsokhn C , Cobos Munoz D , AbouZahr C , Di Pasquale A , Mswia R , Choi E , Baiden F , Thomas J , Lyatuu I , Li Z , Larbi-Debrah P , Chu Y , Cheburet S , Sankoh O , Mohamed Badr A , Fat DM , Setel P , Jakob R , de Savigny D . Glob Health Action 12/28/2021 14 1982486 Over the past 70 years, significant advances have been made in determining the causes of death in populations not served by official medical certification of cause at the time of death using a technique known as Verbal Autopsy (VA). VA involves an interview of the family or caregivers of the deceased after a suitable bereavement interval about the circumstances, signs and symptoms of the deceased in the period leading to death. The VA interview data are then interpreted by physicians or, more recently, computer algorithms, to assign a probable cause of death. VA was originally developed and applied in field research settings. This paper traces the evolution of VA methods with special emphasis on the World Health Organization's (WHO)'s efforts to standardize VA instruments and methods for expanded use in routine health information and vital statistics systems in low- and middle-income countries (LMICs). These advances in VA methods are culminating this year with the release of the 2022 WHO Standard Verbal Autopsy (VA) Toolkit. This paper highlights the many contributions the late Professor Peter Byass made to the current VA standards and methods, most notably, the development of InterVA, the most commonly used automated computer algorithm for interpreting data collected in the WHO standard instruments, and the capacity building in low- and middle-income countries (LMICs) that he promoted. This paper also provides an overview of the methods used to improve the current WHO VA standards, a catalogue of the changes and improvements in the instruments, and a mapping of current applications of the WHO VA standard approach in LMICs. It also provides access to tools and guidance needed for VA implementation in Civil Registration and Vital Statistics Systems at scale. |
Tobacco-specific nitrosamines (NNAL, NNN, NAT, and NAB) exposures in the US Population Assessment of Tobacco and Health (PATH) Study Wave 1 (2013-2014)
Xia B , Blount BC , Guillot T , Brosius C , Li Y , Van Bemmel DM , Kimmel HL , Chang CM , Borek N , Edwards KC , Lawrence C , Hyland A , Goniewicz ML , Pine BN , Xia Y , Bernert JT , De Castro BR , Lee J , Brown JL , Arnstein S , Choi D , Wade EL , Hatsukami D , Ervies G , Cobos A , Nicodemus K , Freeman D , Hecht SS , Conway K , Wang L . Nicotine Tob Res 2020 23 (3) 573-583 INTRODUCTION: The tobacco-specific nitrosamines (TSNAs) are an important group of carcinogens found in tobacco and tobacco smoke. To describe and characterize the levels of TSNAs in the Population Assessment of Tobacco and Health (PATH) Study Wave 1 (2013-2014), we present four biomarkers of TSNA exposure: N'-nitrosonornicotine, N'-nitrosoanabasine, N'-nitrosoanatabine, and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) which is the primary urinary metabolite of 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone. METHODS: We measured total TSNAs in 11 522 adults who provided urine using automated solid-phase extraction coupled to isotope dilution liquid chromatography-tandem mass spectrometry. After exclusions in this current analysis, we selected 11 004 NNAL results, 10 753 N'-nitrosonornicotine results, 10 919 N'-nitrosoanatabine results, and 10 996 N'-nitrosoanabasine results for data analysis. Geometric means and correlations were calculated using SAS and SUDAAN. RESULTS: TSNA concentrations were associated with choice of tobacco product and frequency of use. Among established, every day, exclusive tobacco product users, the geometric mean urinary NNAL concentration was highest for smokeless tobacco users (993.3; 95% confidence interval [CI: 839.2, 1147.3] ng/g creatinine), followed by all types of combustible tobacco product users (285.4; 95% CI: [267.9, 303.0] ng/g creatinine), poly tobacco users (278.6; 95% CI: [254.9, 302.2] ng/g creatinine), and e-cigarette product users (6.3; 95% CI: [4.7, 7.9] ng/g creatinine). TSNA concentrations were higher in every day users than in intermittent users for all the tobacco product groups. Among single product users, exposure to TSNAs differed by sex, age, race/ethnicity, and education. Urinary TSNAs and nicotine metabolite biomarkers were also highly correlated. CONCLUSIONS: We have provided PATH Study estimates of TSNA exposure among US adult users of a variety of tobacco products. These data can inform future tobacco product and human exposure evaluations and related regulatory activities. |
Integrating community-based verbal autopsy into civil registration and vital statistics (CRVS): system-level considerations
de Savigny D , Riley I , Chandramohan D , Odhiambo F , Nichols E , Notzon S , AbouZahr C , Mitra R , Cobos Munoz D , Firth S , Maire N , Sankoh O , Bronson G , Setel P , Byass P , Jakob R , Boerma T , Lopez AD . Glob Health Action 2017 10 (1) 1272882 BACKGROUND: Reliable and representative cause of death (COD) statistics are essential to inform public health policy, respond to emerging health needs, and document progress towards Sustainable Development Goals. However, less than one-third of deaths worldwide are assigned a cause. Civil registration and vital statistics (CRVS) systems in low- and lower-middle-income countries are failing to provide timely, complete and accurate vital statistics, and it will still be some time before they can provide physician-certified COD for every death. Proposals: Verbal autopsy (VA) is a method to ascertain the probable COD and, although imperfect, it is the best alternative in the absence of medical certification. There is extensive experience with VA in research settings but only a few examples of its use on a large scale. Data collection using electronic questionnaires on mobile devices and computer algorithms to analyse responses and estimate probable COD have increased the potential for VA to be routinely applied in CRVS systems. However, a number of CRVS and health system integration issues should be considered in planning, piloting and implementing a system-wide intervention such as VA. These include addressing the multiplicity of stakeholders and sub-systems involved, integration with existing CRVS work processes and information flows, linking VA results to civil registration records, information technology requirements and data quality assurance. CONCLUSIONS: Integrating VA within CRVS systems is not simply a technical undertaking. It will have profound system-wide effects that should be carefully considered when planning for an effective implementation. This paper identifies and discusses the major system-level issues and emerging practices, provides a planning checklist of system-level considerations and proposes an overview for how VA can be integrated into routine CRVS systems. |
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