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1. Measuring bereavement prevalence in a complex sampling survey: the 2019 Georgia Behavioral Risk Factor Surveillance System (BRFSS)

Author

Changle Li, Toni P. Miles, Ye Shen, Rana Bayakly, Moses Ido, and M. Mahmud Khan

Subjects
BRFSS, Bereavement, Grief, Aging, Population Surveillance, Weighting, Medicine (General), R5-920
Abstract

Abstract Background The Behavioral Risk Factor Surveillance System (BRFSS) is an annual survey designed to identify trends in the public’s health. In its 2019 field survey, the U.S. state of GA tested a new 3 – item module to measure the numbers of bereaved, resident adults aged 18 years and older. Participants were eligible if they answered ‘Yes’ to the item ‘Have you experienced the death of a family member or close friend in the years 2018 or 2019?’. This analysis explores two research questions. Can estimates for bereavement prevalence be derived without large sampling errors, low precision, and small subsamples? Can multiple imputation techniques be applied to overcome non-response and missing data to support multivariate modeling? Methods BRFSS is a non-institutionalized sample of adults aged 18 years and older living in the U.S. state of Georgia. Analyses in this study were conducted under two scenarios. Scenario 1 applies the complex sample weights created by the Centers for Disease Control and imputes values for missing responses. Scenario 2 treats the data as a panel – no weighting combined with removal of persons with missing data. Scenario 1 reflects the use of BRFSS data for public health and policy, while Scenario 2 reflects data as it is commonly used in social science research studies. Results The bereavement screening item has a response rate (RR) of 69.1% (5206 of 7534 persons). Demographic subgroups and categories of health have RR of 55% or more. Under Scenario 1, the estimated prevalence of bereavement is 45.38%, meaning that 3,739,120 adults reported bereaved in 2018 or 2019. The estimated prevalence is 46.02% with Scenario 2 which removes persons with any missing data (4,289 persons). Scenario 2 overestimates the bereavement prevalence by 1.39%. An illustrative logistic model is presented to show the performance of exposure to bereavement under the two data scenarios. Conclusions Recent bereavement can be ascertained in a surveillance survey accounting for biases in response. Estimating bereavement prevalence is needed for measuring population health. This survey is limited to one US state in a single year and excludes persons aged 17 years and younger.

Published
2023
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2. A New Measure of Population Health in a Complex Sampling Survey: The 2019 Georgia Behavioral Risk Factor Surveillance Survey – Unweighted, Weighted, and Imputed Weighted Data

Author

Moses Ido, Rana Bayakly, Changle Li, Toni Miles, M Mahmoud Khan, and Ye Shen

Subjects
Behavioral risk, Measure (data warehouse), Geography, Statistics, Sampling (statistics), Population health
Abstract

Background: Measuring population health requires a well-defined denominator. The Behavioral Risk Factor Surveillance Survey (BRFSS) is designed to provide one for state-level populations. In 2019, the U.S. state of Georgia tested a new module to study recent bereavement among its 8.1 million residents aged 18 years and older. This is the first population-level assessment of bereavement. In BRFSS, bereavement is defined as the fact of a death. The term grief is not used because it denotes emotions related to that death. There is evidence from cohort studies linking new bereavement to subsequent mortality and health care utilization. Methods: BRFSS data are obtained using list-assisted, random digit dialing from the non-institutionalized population aged 18 years and older within primary statistical units. Data came from both landline telephones and cellular phones. Three questions were added to the end of the latest BRFSS asking about death of family or friend in 2018 or 2019. To evaluate data from this new module, the report presents three statistical approaches - unweighted panel data, weighted data, and weighted data using multiple imputation of missing responses. The estimated prevalence of bereavement and its standard error under each data scenario is calculated. Results: The threat to the validity of data from this new module are bias due to small samples and missingness. The unweighted panel contains 5,206 persons (70.9 percent response). Among these, 2,396 persons (46.0 %) responded ‘Yes’ to ‘Have you experienced the death of a family member or close friend in the years 2018 or 2019? To estimate the size of the population, weights are applied. With weighted data and removal of missing responses yields a prevalence of 45.56 % (SE = 1.13) with a population estimate of 4,937,056 persons. Using multiple imputation to keep missing responses, the prevalence is 45.80 % (SE = 1.18) with a denominator of 8,164,018 persons. Conclusions: New bereavement can be ascertained in a surveillance survey without bias due to refusals. Multiple imputation provides a population size estimate that is comparable to U.S. Census bureau. More field testing is required to replicate these results in other states.

Published
2021
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