According to a new groundbreaking study published in the Journal of the American Medical Association, official US records dramatically underestimate the disparity between mortality and life expectancy among Native Americans. The study, led by the Boston University School of Public Health, provides compelling evidence of a deep inconsistency between actual and officially reported statistics regarding health outcomes in American Indians and native Alaska (AI/AN) populations in the United States.
This study, a novel of this approach, tracks mortality outcomes over time among a nationally representative cohort of self-identified AI/individuals known as mortality disparities in American communities. Researchers linked official death certificates from the Centers for the National Statistical Systems at the Centers for the Centers for Disease Control and Prevention from 2008 to 2019 with data from the US Census Bureau’s 2008 American Community Survey, finding that the average life expectancy for the AI/AN population was 6.5 years lower than the national average. We then compared this to data from the CDC’s Wonder database and found that it was almost three times the number of gaps reported by the CDC.
In fact, this study found that the average life expectancy of AI/AN individuals is only 72.7 years, comparable to that of developing countries.
The researchers also revealed widespread racial misclassifications. The study reports that approximately 41% of AI/AN deaths were misclassified in the CDC Wonder database and were mainly misrepresented as “white.” These systemic misclassifications significantly distorted official statistics and presented AI/AN mortality rates as only 5% higher than the national average. When adjusting the data to account for these misclassifications, the researchers found that the actual rate was 42% higher than initially reported.
The issue of racial misclassification is “not something entirely new to us,” said Nanette Starr, director of policy and planning for the California Consortium for Health in California and India. The recent trend of journalists and politicians using umbrella terms like “Indigenous people” rather than more accurate “American Indians and Alaskan natives” could obscure the unique needs, history and political identities of the AI/AN community, focusing on both the stars and contributing to erasure in both data and public discourse. “That’s the word we use, it erases it — and it really brings that invisibility in our health statistics,” she said.
Issues related to racial misclassification in public records continue throughout the AI/AN life course, from birth to early childhood interventions to chronic illness and death. Starr, particularly in urban areas like Los Angeles, native individuals are often misidentified as Latino or multi-ethnic in California, deeply distorting public health data and obscuring the extent of health disparities. “It really masks the true magnitude of premature mortality and health disparities among our communities,” Starr said.
Additionally, Starr said the lack of accurate data exacerbates health disparities. “It’s really a matter of public health and justice,” she said. “If we don’t have numbers to support a targeted response, we won’t be able to fund these interventions or precautions.”
According to US census data, California is home to the largest AI/A AN in the United States. This means there is a unique opportunity to guide the country in addressing these systematic issues. California can prioritize collecting and reporting jointly and accurate public health data with many federal and state perceived tribes and substantial urban AI/populations.
Star noted that current distortions are not necessarily malicious, but are often attributed to a lack of training. She suggested that California implement a targeted training program for people responsible for recording this data, including funeral directors, coroners, doctors, and law enforcement agents. Allocate dedicated resources to improve the accuracy of racial classification of important records. Strengthen partnerships with tribal leaders.
The study authors propose a similar approach, with many successful cases of Indigenously-led health partnerships found in Canada and the United States that helped to reduce health disparities in the AI/AN community that can be used as templates.
These efforts not only help us move towards rectifying historical inaccuracies, but also ensure that AI/communities attract the attention of equitable health resources and policies.
“When AI/people are misclassified in life and death, it distorts public health data and drives inequality even deeper,” Starr said. “Numbers aren’t the only accurate data. It’s about celebrating life, taking the system accountable, and ensuring that the community is seen and provided.”
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