Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Importance: US cities have substantial, but varying, levels of racial mortality inequities, a consequence of structural racism. As committed partners increasingly pledge to eliminate health inequities, local data are required to focus and unify efforts.
Objective: To analyze the contributions of 26 cause-of-death categories to Black to White life expectancy gaps within 3 large US cities.
Design, Setting, And Participants: In this cross-sectional study, data were extracted from the 2018 and 2019 National Vital Statistics System Multiple Cause of Death Restricted Use data files for deaths by race, ethnicity, sex, age, place of residence, and underlying and contributing causes of death in Baltimore, Maryland; Houston, Texas; and Los Angeles, California. Life expectancy at birth was calculated for non-Hispanic Black and non-Hispanic White populations overall and by sex using abridged life tables with 5-year age intervals. Data analysis was performed from February to May 2022.
Main Outcomes And Measures: Using the Arriaga method, the proportion of the Black to White life expectancy gap was calculated overall and by sex for each city that was attributable to 26 cause-of-death categories defined using the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes for underlying and contributing causes of death.
Results: A total of 66 321 death records from 2018 to 2019 were analyzed, with 29 057 individuals (44%) were identified as Black, 34 745 (52%) as male, and 46 128 (70%) as aged 65 years and older. Black to White life expectancy gaps were 7.60 years for Baltimore, 8.06 years for Houston, and 9.57 years for Los Angeles. Circulatory diseases, cancer, injuries, and diabetes and endocrine disorders were top contributors to the gaps, although the order and magnitude varied by city. The contribution of circulatory diseases was 11.3 percentage points higher in Los Angeles than in Baltimore (3.76 years [39.3%] vs 2.12 years [28.0%]). The contribution of injuries to Baltimore's racial gap (2.22 years [29.3%]) was twice as large as in Houston (1.11 years [13.8%]) and Los Angeles (1.36 years [14.2%]).
Conclusions And Relevance: By assessing the composition of Black to White life expectancy gaps for 3 large US cities and categorizing deaths at a more granular level than past studies, this study provides insight into the differing underpinnings of urban inequities. This type of local data can support local resource allocation that more effectively addresses racial inequities.
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http://dx.doi.org/10.1001/jamanetworkopen.2023.3146 | DOI Listing |
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