Dataset Information

A Multiple-Imputation "Forward Bridging" Approach to Address Changes in the Classification of Asian Race/Ethnicity on the US Death Certificate.

ABSTRACT: The incomparability of old and new classification systems for describing the same data can be seen as a missing-data problem, and, under certain assumptions, multiple imputation may be used to "bridge" 2 classification systems. One example of such a change is the introduction of detailed Asian-American race/ethnicity classifications on the 2003 version of the US national death certificate, which was adopted for use by 38 states between 2003 and 2011. Using county- and decedent-level data from 3 different national sources for pre- and postadoption years, we fitted within-state multiple-imputation models to impute ethnicities for decedents classified as "other Asian" during preadoption years. We present mortality rates derived using 3 different methods of calculation: 1) including all states but ignoring the gradual adoption of the new death certificate over time, 2) including only the 7 states with complete reporting of all ethnicities, and 3) including all states and applying multiple imputation. Estimates from our imputation model were consistently in the middle of the other 2 estimates, and trend results demonstrated that the year-by-year estimates of the imputation model were more similar to those of the 7-state model. This work demonstrates how multiple imputation can provide a "forward bridging" approach to make more accurate estimates over time in newly categorized populations.

SUBMITTER: Thompson CA

PROVIDER: S-EPMC5860289 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Multiple-Imputation "Forward Bridging" Approach to Address Changes in the Classification of Asian Race/Ethnicity on the US Death Certificate.

Thompson Caroline A CA Boothroyd Derek B DB Hastings Katherine G KG Cullen Mark R MR Palaniappan Latha P LP Rehkopf David H DH

American journal of epidemiology 20180201 2

The incomparability of old and new classification systems for describing the same data can be seen as a missing-data problem, and, under certain assumptions, multiple imputation may be used to "bridge" 2 classification systems. One example of such a change is the introduction of detailed Asian-American race/ethnicity classifications on the 2003 version of the US national death certificate, which was adopted for use by 38 states between 2003 and 2011. Using county- and decedent-level data from 3 ...[more]

PMID: 29401361

Similar Datasets

Project description:BACKGROUND:Reduction of premature mortality is a UN Sustainable Development Goal. Unlike other high-income countries, age-adjusted mortality in the USA plateaued in 2010 and increased slightly in 2015, possibly because of rising premature mortality. We aimed to analyse trends in mortality in the USA between 1999 and 2014 in people aged 25-64 years by age group, sex, and race and ethnicity, and to identify specific causes of death underlying the temporal trends. METHODS:For this analysis, we used cause-of-death and demographic data from death certificates from the US National Center for Health Statistics, and population estimates from the US Census Bureau. We estimated annual percentage changes in mortality using age-period-cohort models. Age-standardised excess deaths were estimated for 2000 to 2014 as observed deaths minus expected deaths (estimated from 1999 mortality rates). FINDINGS:Between 1999 and 2014, premature mortality increased in white individuals and in American Indians and Alaska Natives. Increases were highest in women and those aged 25-30 years. Among 30-year-olds, annual mortality increases were 2·3% (95% CI 2·1-2·4) for white women, 0·6% (0·5-0·7) for white men, and 4·3% (3·5-5·0) and 1·9% (1·3-2·5), respectively, for American Indian and Alaska Native women and men. These increases were mainly attributable to accidental deaths (primarily drug poisonings), chronic liver disease and cirrhosis, and suicide. Among individuals aged 25-49 years, an estimated 111?000 excess premature deaths occurred in white individuals and 6600 in American Indians and Alaska Natives during 2000-14. By contrast, premature mortality decreased substantially across all age groups in Hispanic individuals (up to 3·2% per year), black individuals (up to 3·9% per year), and Asians and Pacific Islanders (up to 2·6% per year), mainly because of declines in HIV, cancer, and heart disease deaths, resulting in an estimated 112?000 fewer deaths in Hispanic individuals, 311?000 fewer deaths in black individuals, and 34?000 fewer deaths in Asians and Pacific Islanders aged 25-64 years. During 2011-14, American Indians and Alaska Natives had the highest premature mortality, followed by black individuals. INTERPRETATION:Important public health successes, including HIV treatment and smoking cessation, have contributed to declining premature mortality in Hispanic individuals, black individuals, and Asians and Pacific Islanders. However, this progress has largely been negated in young and middle-aged (25-49 years) white individuals, and American Indians and Alaska Natives, primarily because of potentially avoidable causes such as drug poisonings, suicide, and chronic liver disease and cirrhosis. The magnitude of annual mortality increases in the USA is extremely unusual in high-income countries, and a rapid public health response is needed to avert further premature deaths. FUNDING:US National Cancer Institute Intramural Research Program.

Project description:ImportanceHealth care disparities are well-documented among children based on race, ethnicity, and language for care. An agenda that outlines research priorities for disparities in pediatric emergency care (PEC) is lacking.ObjectiveTo investigate research priorities for disparities in PEC among medical personnel, researchers, and health care-affiliated community organizations.Design, setting, and participantsIn this survey study, a modified Delphi approach was used to investigate research priorities for disparities in PEC. An initial list of research priorities was developed by a group of experienced PEC investigators in 2021. Partners iteratively assessed the list through 2 rounds of electronic surveys using Likert-type responses in late 2021 and early 2022. Priorities were defined as achieving consensus if they received a score of highest priority or priority by at least 60% of respondents. Asynchronous engagement of participants via online web-conferencing platforms and email correspondence with electronic survey administration was used. Partners were individuals and groups involved in PEC. Participants represented interest groups, research and medical personnel organizations, health care partners, and laypersons with roles in community and family hospital advisory councils. Participants were largely from the US, with input from international PEC research networks.OutcomeConsensus agenda of research priorities to identify and address health care disparities in PEC.ResultsPEC investigators generated an initial list of 27 potential priorities. Surveys were completed by 38 of 47 partners (80.6%) and 30 of 38 partners (81.1%) in rounds 1 and 2, respectively. Among 30 respondents who completed both rounds, there were 7 family or community partners and 23 medical or research partners, including 4 international PEC research networks. A total of 12 research priorities achieved the predetermined consensus threshold: (1) systematic efforts to reduce disparities; (2) race, ethnicity, and language data collection and reporting; (3) recognizing and mitigating clinician implicit bias; (4) mental health disparities; (5) social determinants of health; (6) language and literacy; (7) acute pain-management disparities; (8) quality of care equity metrics; (9) shared decision-making; (10) patient experience; (11) triage and acuity score assignment; and (12) inclusive research participation.Conclusions and relevanceThese results suggest a research priority agenda that may be used as a guide for investigators, research networks, organizations, and funding agencies to engage in and support high-priority disparities research topics in PEC.

Project description:IntroductionInfant mortality rates are higher in nonmetropolitan areas versus large metropolitan areas. Variation by race/ethnicity and cause of death has not been assessed. Urban-rural infant mortality rate differences were quantified by race/ethnicity and cause of death.MethodsNational Vital Statistics System linked birth/infant death data (2014-2016) were analyzed in 2019 by 3 urban-rural county classifications: large metropolitan, medium/small metropolitan, and nonmetropolitan. Excess infant mortality rates (rate differences) by urban-rural classification were calculated relative to large metropolitan areas overall and for each racial/ethnic group. The number of excess deaths, population attributable fraction, and proportion of excess deaths attributable to underlying causes of death was calculated.ResultsNonmetropolitan areas had the highest excess infant mortality rate overall. Excess infant mortality rates were substantially lower for Hispanic infants than other races/ethnicities. Overall, 7.4% of infant deaths would be prevented if all areas had the infant mortality rate of large metropolitan areas. With more than half of births occurring outside of large metropolitan areas, the population attributable fraction was highest for American Indian/Alaska Natives (20.3%) and whites, non-Hispanic (14.3%). Excess infant mortality rates in both nonmetropolitan and medium/small metropolitan areas were primarily attributable to sudden unexpected infant deaths (42.3% and 31.9%) and congenital anomalies (30.1% and 26.8%). This pattern was consistent for all racial/ethnic groups except black, non-Hispanic infants, for whom preterm-related and sudden unexpected infant deaths accounted for the largest share of excess infant mortality rates.ConclusionsInfant mortality increases with rurality, and excess infant mortality rates are predominantly attributable to sudden unexpected infant deaths and congenital anomalies, with differences by race/ethnicity regarding magnitude and cause of death.

Dataset Information

A Multiple-Imputation "Forward Bridging" Approach to Address Changes in the Classification of Asian Race/Ethnicity on the US Death Certificate.

Publications

A Multiple-Imputation "Forward Bridging" Approach to Address Changes in the Classification of Asian Race/Ethnicity on the US Death Certificate.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets