Everything You Want to Know About Data Disaggregation
What is Data Disaggregation?
Data disaggregation is the collection of data of minority groups in the population. Historically, these minority groups have been excluded from data collection in the fields of health, education, labor and economics, to name a few. Data can be disaggregated by a variety of factors, such as race, ethnicity, gender, sexual orientation, ability (disability), language preferences, and more. Recently, data disaggregation has been argued as an utmost priority for achieving health equity, particularly for people of Asian, Pacific Islander, American Indian, Alaska Native, Latinx, and Black descent.
General Resources & White Papers
AAPI Data. “Ethnicity Data and AAPIs: Resources on Data Disaggregation” aapidata.com/ethnicitydata/
Asian & Pacific Islander Health Forum. “Policy Recommendations: Health Equity Cannot Be Achieved Without Complete and Transparent Data Collection and the Disaggregation of Data.” www.apiahf.org/resource/policy-recommendations-health-equity-cannot-be-achieved-without-complete-and-transparent-data-collection-and-the-disaggregation-of-data/
Association of Asian Pacific Community Health Organizations (AAPCHO). “Statement of Support for the Collection of Disaggregated Data on Asian Americans, Native Hawaiians and Pacific Islanders. www.aapcho.org/wp/wp-content/uploads/2017/08/Data-disaggregation-organizational-statement-final-AAPCHO.pdf
National Forum on Education Statistics. “Forum Guide to Collecting and Using Disaggregated Data on Racial/Ethnic Subgroups.” nces.ed.gov/forum/pub_2017017.asp
PolicyLink. “Making the Case for Data Disaggregation to Advance a Culture of Health.” www.policylink.org/our-work/community/health-equity/data-disaggregation
Ponce, Ninez, A. J. Scheitler, and Riti Shimkhada. "Understanding the culture of health for Asian American, Native Hawaiian and Pacific Islanders (AANHPIs): what do population-based health surveys across the nation tell us about the state of data disaggregation for AANHPIs? Robert Wood Johnson Foundation." Robert Wood Johnson Foundation (2018). https://healthsurveynetwork.org/wp-content/uploads/2020/06/AANHPI-Survey-Data-Disaggregation-Practices-Report-Final.pdf
Race Matters Institute. “The Essentials of Disaggregated Data for Advancing Racial Equity.” viablefuturescenter.org/racemattersinstitute/resources/disaggregated-data/
Robert Wood Johnson Foundation. “Charting a Course for an Equity-Centered Data System: Recommendations from the National Commission to Transform Public Health Data Systems.” www.rwjf.org/en/library/research/2021/10/charting-a-course-for-an-equity-centered-data-system.html
Southeast Asia Resource Action Center (SEARAC). “Data Disaggregation General Factsheet.” www.searac.org/education/data-disaggregation-general-factsheet/
Urban Institute. “Five Ethical Risks to Consider before Filling Missing Race and Ethnicity Data.” www.urban.org/research/publication/five-ethical-risks-consider-filling-missing-race-and-ethnicity-data
United States Indigenous Data Sovereignty Network (USIDSN). “Promoting Indigenous Data Sovereignty Through Decolonizing Data and Indigenous Data Governance.” usindigenousdata.org
University of California-Los Angeles Center for Health Policy Research. “Workshop Series: Addressing Health Equity through Data Disaggregation. events.r20.constantcontact.com/register/event?oeidk=a07eidciy2r74c9bc20&llr=6yxgr6cab
Select Peer-Reviewed Publications
2022
Bhakta, Seema. "Data disaggregation: the case of Asian and Pacific Islander data and the role of health sciences librarians." Journal of the Medical Library Association: JMLA110, no. 1 (2022): 133. www.ncbi.nlm.nih.gov/pmc/articles/pmc8830391/
Gee, Gilbert C., Brittany N. Morey, Adrian M. Bacong, Tran T. Doan, and Corina S. Penaia. "Considerations of Racism and Data Equity Among Asian Americans, Native Hawaiians, And Pacific Islanders in the Context of COVID-19." Current Epidemiology Reports (2022): 1-10. Link: link.springer.com/article/10.1007/s40471-022-00283-y
Nguyen, Kevin H., Kaitlyn P. Lew, and Amal N. Trivedi. "Trends in Collection of Disaggregated Asian American, Native Hawaiian, and Pacific Islander Data: Opportunities in Federal Health Surveys." American Journal of Public Health 112.10 (2022): 1429-1435. Link: ajph.aphapublications.org/doi/pdf/10.2105/AJPH.2022.306969
Shimkhada, Riti, A. J. Scheitler, and Ninez A. Ponce. "Capturing racial/ethnic diversity in population-based surveys: data disaggregation of health data for Asian American, Native Hawaiian, and Pacific Islanders (AANHPIs)." Population Research and Policy Review 40, no. 1 (2021): 81-102. https://link.springer.com/article/10.1007/s11113-020-09634-3
Yi, Stella S., Simona C. Kwon, Rachel Suss, Lan N. Ðoàn, Iyanrick John, Nadia S. Islam, and Chau Trinh-Shevrin. "The Mutually Reinforcing Cycle Of Poor Data Quality And Racialized Stereotypes That Shapes Asian American Health: Study examines poor data quality and racialized stereotypes that shape Asian American health." Health Affairs 41, no. 2 (2022): 296-303. Link: www.healthaffairs.org/doi/full/10.1377/hlthaff.2021.01417
2021
Chao, Grace F., Jonel Emlaw, Alexander S. Chiu, Jie Yang, Jyothi Thumma, Alexandria Brackett, and Kevin Y. Pei. "Asian American Pacific Islander representation in outcomes research: NSQIP scoping review." Journal of the American College of Surgeons 232, no. 5 (2021): 682-689. https://www.sciencedirect.com/science/article/pii/S1072751521001277
Gigli, Kristin H. "Data Disaggregation: A Research Tool to Identify Health Inequities." Journal of Pediatric Health Care 35, no. 3 (2021): 332-336. www.sciencedirect.com/science/article/abs/pii/S0891524520303308
Kauh, Tina J., Jen’nan Ghazal Read, and A. J. Scheitler. "The critical role of racial/ethnic data disaggregation for health equity." Population Research and Policy Review 40, no. 1 (2021): 1-7. link.springer.com/article/10.1007/s11113-020-09631-6
Stella, S. Yi, Lan N. Ðoàn, Juliet K. Choi, Jennifer A. Wong, Rienna Russo, Matthew Chin, Nadia S. Islam, MD Taher, Laura Wyatt, Stella K. Chong, Chau Tring-Shevrin, and Simona C. Kwon. "With no data, there's no equity: addressing the lack of data on COVID-19 for Asian American communities." EClinicalMedicine 41 (2021). www.thelancet.com/journals/eclinm/article/PIIS2589-5370(21)00445-4/fulltext
Yom, Stephanie, and Maichou Lor. "Advancing health disparities research: The need to include Asian American Subgroup Populations." Journal of racial and ethnic health disparities (2021): 1-35. https://link.springer.com/article/10.1007/s40615-021-01164-8
2020
Wang, Daniel, Gilbert C. Gee, Ehete Bahiru, Eric H. Yang, and Jeffrey J. Hsu. "Asian-Americans and Pacific Islanders in COVID-19: emerging disparities amid discrimination." Journal of General Internal Medicine 35, no. 12 (2020): 3685-3688. link.springer.com/article/10.1007/s11606-020-06264-5
2019 & Prior
Sharpe, Rhonda Vonshay. "Disaggregating data by race allows for more accurate research." Nature Human Behaviour3, no. 12 (2019): 1240-1240. www.nature.com/articles/s41562-019-0696-1
Nguyen, Bach-Mai Dolly, Mike Hoa Nguyen, and Tu-Lien Kim Nguyen. "Advancing the Asian American and Pacific Islander data quality campaign: Data disaggregation practice and policy." Asian American Policy Review 24 (2013): 55. https://aapr.hkspublications.org/2014/06/04/advancing-the-asian-american-and-pacific-islander-data-quality-campaign-data-disaggregation-practice-and-policy/
Select Editoral Articles
2022
Kader, Farah, Lan N. Ðoàn, Matthew Lee, Matthew K. Chin, Simona C. Kwon, and Stella S. Yi. (March 25, 2022) “Disaggregating Race/Ethnicity Data Categories: Criticisms, Dangers, And Opposing Viewpoints.” Health Affairs Forefront. www.healthaffairs.org/do/10.1377/forefront.20220323.555023
2021
Kauh, Tina J. (November 29, 2021) “Racial Equity Will Not Be Achieved Without Investing In Data Disaggregation.” Health Affairs Forefront. www.healthaffairs.org/do/10.1377/forefront.20211123.426054
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