via Flickr Creative Commons by Michael 1952
By Rashmika Prakash
As of April 7th , 2020, 85 Bangladeshi New Yorkers had died due to COVID-19, as per extensive health worker and Bangladeshi community networks in New York City.
Yet, on the morning of April 8th when the NYC Health Department released COVID-19 related data, a mere 112 deaths for the entirety of the Asian American community were shown. Upon a closer look, it could be seen that a whopping 917 deaths were categorized as unknown or of other race/ethnicity. Clearly, in a country where diversity is said to be celebrated, the identities of multitudes of Bangladeshis were essentially erased, and in every sense of the word “othered”.
We must ensure data disaggregation to bring to light deep disparities in Asian Americans and Pacific Islanders (AAPI) health, enabling data to correctly represent the heterogeneous communities it attempts to encompass and leave no space for rendering racial and ethnic identities unknown.
Those identifying as AAPI are rarely given opportunities to specifically identify themselves as one of about 100 different ethnic groups that speak over 250 different languages and dialects. Such is the diversity of these communities that are pigeonholed into a homogeneous AAPI checkbox or relegated to “Other/Unknown” for race/ethnicity identification in most forms used in the United States.
Obviously, health risks differ widely between these racial/ethnic groups, yet healthcare workers are often left with gaps in knowledge of the diverse health needs among AAPI populations.
Without disaggregation, it is hard to get at any discrepancies in data – for example, among all racial and ethnic categories, Vietnamese women are among those with the highest rates of cervical cancer. Yet, if they are grouped along with the other scores of AAPI categories, the significance of this data gets lost.
Similarly, incidence of type 2 diabetes mellitus among American Indians rivals that of Hispanics, the second highest race/ethnic group to be diagnosed. However, when grouped under Asian Americans, they fall to become the fourth most diagnosed racial group. Clearly, the implications extend beyond numbers and not only affect the way those belonging to AAPI perceive their tolerance to risk (therefore promoting unhealth behavior), but also to fund allocations targeting these groups – the US National Institutes of Health’s funding, for example, amounted to a mere 0.2% of their budget from 1992 to 2018 for clinical research that focused on AAPI participants.
There exists further complexity in aggregating Pacific Islanders with Asian Americans. Formally, the two groups were to be separated in data collection from as far back as 1997, but during the current COVID-19 pandemic, disaggregated data is almost non-existent.
Where they are disaggregated, the disparities are wholly evident, such as in Colorado where Pacific Islanders make up 1.6% of deaths even though they represent just 0.1% of the state’s population. Additionally, individuals with comorbidities are known to be at high risk for COVID-19. This is important when noting that about 20% of Native Hawaiians and Pacific Islanders have heart disease, and South Asians also recognized as being high risk, yet those identifying as AAPI are less likely to have received care for chronic conditions than other groups.
To address the disparities among AAPI folks, interventions at all stages are required. Policy makers must take into consideration these severe health inequalities. Healthcare providers must turn their attention to understanding implications of different ethnic groups and prevalent diseases each faces.
Without disaggregating data, none of this can occur. There is no more impactful example than the current situation with the COVID-19 pandemic; when we are already struggling with lack of data to handle this crisis, it seems absurd that the data we do have regarding the AAPI community are almost useless, and doctors are flying blind in both issues with lack of COVID-19 data and irrelevant AAPI health data.
It can only be when data is collected at a subgroup level that existing gaping disparities become apparent. To achieve this, changing the standards of data collection must occur by adding in the nuanced race/ethnicities on all governmental and medical forms, while also disaggregating in terms of understanding AAPI as separate groups when considering funding and policymaking.
In order to provide adequate attention to the health of AAPI communities in need, we must advocate for disaggregating data to represent the various ethnic categories that are currently lumped into one entirely misrepresentative checkbox. It is only through this that we can hope to begin reaching the most underserved communities, ultimately including them in discussions for better health outcomes where they have thus far been ignored.
(About the Author: Rashmika Prakash is a graduate student at Columbia University’s Mailman School of Public Health)
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