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Impact of Differential Privacy and Census Tract Data Source (Decennial Census Versus American Community Survey) for Monitoring Health Inequities
Journal article   Open access   Peer reviewed

Impact of Differential Privacy and Census Tract Data Source (Decennial Census Versus American Community Survey) for Monitoring Health Inequities

Nancy Krieger, Rachel C Nethery, Jarvis T Chen, Pamela D Waterman, Emily Wright, Tamara Rushovich and Brent A Coull
American journal of public health (1971), v 111(2), pp 265-268
Feb 2021
PMID: 33351654
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
https://www.ncbi.nlm.nih.gov/pmc/articles/7811099View
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Abstract

Aged Censuses Female Healthcare Disparities - statistics & numerical data Humans Male Massachusetts Middle Aged Mortality, Premature Population Groups - statistics & numerical data Privacy Socioeconomic Factors United States
To investigate how census tract (CT) estimates of mortality rates and inequities are affected by (1) differential privacy (DP), whereby the public decennial census (DC) data are injected with statistical "noise" to protect individual privacy, and (2) uncertainty arising from the small number of different persons surveyed each year in a given CT for the American Community Survey (ACS). We compared estimates of the 2008-2012 average annual premature mortality rate (death before age 65 years) in Massachusetts using CT data from the 2010 DC, 2010 DC with DP, and 2008-2012 ACS 5-year estimate data. For these 3 denominator sources, the age-standardized premature mortality rates (per 100 000) for the total population respectively equaled 166.4 (95% confidence interval [CI] = 162.2, 170.6), 166.4 (95% CI = 162.2, 170.6), and 166.3 (95% CI = 162.1, 170.5), and inequities in the range from best to worst quintile for CT racialized economic segregation were from 103.4 to 260.1, 102.9 to 258.7, and 102.8 to 262.4. Similarity of results across CT denominator sources held for analyses stratified by gender and race/ethnicity. Estimates of health inequities at the CT level may not be affected by use of 2020 DP data and uncertainty in the ACS data.

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UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#10 Reduced Inequalities
#3 Good Health and Well-Being

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Public, Environmental & Occupational Health
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