Health Equity Blog Series: Using Data to Deploy the Right Care in the Right Place 

Health Equity Blog Series: Overcoming Historical Barriers to Neighborhood Health Equity

Health Equity Blog Series: The City Health Dashboard’s Commitment to Equity and Anti-Racism

<h3>This is the second blog in the Dashboard’s Health Equity Blog Series, a new, regular feature exploring issues impacting health and health equity across America’s cities and diverse communities. We want to acknowledge and thank the NYU Center for the Study of Asian American Health, specifically Dr. Stella Yi and Jennifer Wong, who contributed their time and expertise. This blog would not have been possible without their scholarship and support.</h3>

<hr /><p style="margin-bottom: 11px;">May is Asian American and Pacific Islander Heritage Month. Currently, Asian Americans are the <a href="https://nyulangone.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=a8b94169-c33a-4b8d-a3bf-acef012cd7ff">most understudied</a> racial/ethnic group in the United States, <a href="https://www.pewresearch.org/fact-tank/2021/04/09/asian-americans-are-the-fastest-growing-racial-or-ethnic-group-in-the-u-s/">despite the fact</a> that the Asian American population totals 18.9 million and is the fastest growing racial/ethnic group in the country. From 1992 to 2018, <a href="https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2738623">only 0.17%</a> of the total National Institutes for Health’s budget funded studies specifically focused on Asian American (AA) or Native Hawaiian &amp; Pacific Islander (NH&amp;PI) communities. In the ongoing fight against systemic racism, we recognize the importance of intersectional work towards racial equity and highlighting gaps in research for all people of color.</p>

<p>In health services research and data, AA and NH&amp;PI populations are often grouped together into one category and labeled “Asian” or “Other.” Aggregating these populations effectively erases distinct differences that exist across AA and NH&amp;PI ethnic groups, masking not only the geographic spread of culturally distinct ethnic groups but also minimizing the unique histories, socioeconomic experiences, and varied health disparities that exist across groups. Furthermore, showing AA and NH&amp;PI data in aggregate also works to perpetuate harmful biases, such as the <a href="https://www.washingtonpost.com/politics/2021/04/19/model-minority-myth-hurts-asian-americans-even-leads-violence/">model minority myth</a> and “perpetual foreigner” stereotype. These detrimental concepts have contributed to anti-Asian racism, including acts of violence, which have been even more prevalent in the news over the past year. In celebration of the diverse heritage and resilience of the AA and NH&amp;PI communities, especially in the current social climate, we are making the case – and a call to action – for more disaggregated data for all groups that are underrepresented in research, including the AA and NH&amp;PI populations.<br />
 </p>

<h2>Diving into AA and NH&amp;PI data on the City Health Dashboard</h2>

<p>The Dashboard takes this call to action seriously and aims to provide the most granular demographic data available. In partnership with the <a href="https://med.nyu.edu/departments-institutes/population-health/divisions-sections-centers/health-behavior/section-health-equity/research/center-the-study-asian-american-health">NYU Center for the Study of Asian American Health</a> (CSAAH), the Dashboard created <a href="/story/1484">demographic maps and tables</a> with neighborhood-level age, nativity, and racial/ethnic breakdowns for our 750+ cities, including data for specific racial/ethnic subgroups that are not commonly available (e.g. Chinese, Pakistani, Samoan). While we acknowledge that these demographic maps and tables are lacking for important groups, including Middle Eastern and African racial/ethnic subgroups, the <a href="/story/1484">information provided by these</a> maps can help users better understand the racial/ethnic makeup of their neighborhoods. They can provide critical cultural context to help design outreach strategies, whether that means translating a survey into different languages or working more intentionally with community organizations.</p>

<p>Let’s take a closer look at the demographics of two cities with similar total Asian and NH&amp;PI populations to illustrate the need for data disaggregated by racial/ethnic subgroups. As cities with around 300,000 residents, Stockton, CA and Plano, TX have total Asian populations of 25.9% and 22% respectively, and NH&amp;PI populations of 1.3% and 0.3%, respectively. Yet when data are broken down by subgroup, many differences emerge.</p>
<img alt="stockton" data-entity-type="file" data-entity-uuid="32490dd0-82b7-4039-b891-96304e88ae93" height="350" src="https://content.cityhealthdashboard.com/drupal/sites/default/files/inline-images/demo%20map_stockton.png" width="469" class="align-center" loading="lazy" /><p>Looking at Asian residents of both cities, Stockton has a larger Southeast Asian population, whereas Plano has a larger South Asian population. Overall, the top three Asian subgroups by percent for Stockton are Filipino (37.2% of Stockton’s Asian population), Cambodian (14.2%), and Chinese (9.2%). In contrast, the top three subgroups for Plano are Asian Indian (45.5%), Chinese (22.6%), and Pakistani (6.7%).</p>
<img alt="plano" data-entity-type="file" data-entity-uuid="3cae120d-3031-443b-be60-5106ee493332" height="357" src="https://content.cityhealthdashboard.com/drupal/sites/default/files/inline-images/demo%20map_plano.png" width="482" class="align-center" loading="lazy" /><p>When we break down the NH&amp;PI populations by subgroup for both cities, we again see differences. The top four NH&amp;PI subgroups in Stockton are Fijian (30.6%), Samoan (18.8%), Guamanian or Chamorro (16.4%), and Native Hawaiian (15.1%), while Plano’s NH&amp;PI residents are mostly Native Hawaiian (33.5%) and Samoan (21%). See the table below for more.</p>

<p><strong>Table: Asian and NH&amp;PI subgroup population breakdown ordered by largest subgroups (%) by total city population</strong></p>
<img alt="table" data-entity-type="file" data-entity-uuid="70935533-d75e-4d67-9a62-fa6530194563" height="307" src="https://content.cityhealthdashboard.com/drupal/sites/default/files/inline-images/table.PNG" width="763" class="align-center" loading="lazy" /><p>This example illustrates that looking at groups as a monolith tells an incomplete story. There is no ‘one size fits all’ approach to addressing the needs for AA and NH&amp;PI communities as a whole. For example, Stockton will have a different approach to addressing diabetes than Plano because the underlying systemic issues, cultural and historical context, etc. will differ significantly across residents of each city. Even within Stockton, city leaders will want to tailor their approaches to the Filipino community differently than they would to the Cambodian community because these population groups will have different needs and resources. Using these data, policymakers, funders and practitioners can tailor and better direct specific resources to improve program participation, community engagement and health outcomes through a more precise understanding of community context.<br />
 </p>

<h2>Spotlight on the CSAAH Health Atlas</h2>

<p>Developed in response to the same need for more disaggregated data, CSAAH created the <a href="https://med.nyu.edu/departments-institutes/population-health/divisions-sections-centers/health-behavior/sites/default/files/pdf/csaah-health-atlas.pdf">Health Atlas</a>, a visual tool that documents AA and NH&amp;PI health disparities in communities across the US and unmasks the heterogeneity of these culturally distinct groups. This visual resource makes plain where data exists – and where there are gaps. Though we recommend reading the <a href="https://med.nyu.edu/departments-institutes/population-health/divisions-sections-centers/health-behavior/sites/default/files/pdf/csaah-health-atlas.pdf">full report</a>, the Health Atlas provides these action steps to help you prioritize and look out for disaggregated data in your health survey research and data collection at local, state, and national levels:</p>

<ol><li>Consider data collection strategies (such as oversampling) when conducting research in underrepresented populations, particularly in new, emerging, or growing AA and NH&amp;PI subgroups.</li>
	<li>Collect health survey responses in-language, specifically in languages other than English and Spanish, in order to include and better represent the changing and diverse AA and NH&amp;PI subgroup landscape of the U.S.</li>
	<li>Ensure survey question wording and survey administration methods are culturally and linguistically tailored to AA and NH&amp;PI subgroups’ unique sociodemographic, cultural, and health needs.</li>
	<li>Correct the omission, aggregation, or extrapolation in the reporting of AA and NH&amp;PI data</li>
</ol><p>We also invite you to explore the Dashboard’s <a href="/take-action?resourceType=explore-strategies&amp;page=0">Take Action center</a>, which provides resources on how to more effectively engage with diverse communities and advance health equity.</p>

<p>America is only growing more diverse, and we are better for it. As community leaders and researchers, we can all do more to understand and support the needs of all our diverse and thriving communities for a healthier future for all.</p>


Health Equity Blog Series: Digging into data for Asian American and Native Hawaiian & Pacific Islander Communities

May 13, 2021

Peggy Hsieh & Samantha Breslin

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Health Equity Blog Series: Using Data to Deploy the Right Care in the Right Place

Health Equity Blog Series: Overcoming Historical Barriers to Neighborhood Health Equity

Health Equity Blog Series: The City Health Dashboard’s Commitment to Equity and Anti-Racism