Observed annually from August 15 to 21, Asian American, Native Hawaiian, and Pacific Islander (AANHPI) Breastfeeding Week draws attention to the diverse lactation experiences, cultural contexts, and systemic barriers affecting families across AANHPI communities (Asian Pacific Islander Breastfeeding Task Force of LA County / USBC AANHPI Caucus, 2020–2026).
This year’s theme, “Better Data, Better Care for AANHPI Families,” calls attention to a persistent challenge in public health research, which is the aggregation of highly diverse populations into a single racial or ethnic category (AAPI Data, 2026). For South Asian mothers and other distinct AANHPI populations, broad categorization can obscure important differences in clinical needs, languages, cultural practices, migration experiences, and access to care (CDC, 2023). Furthermore, as a South Asian doula and researcher working across public health and clinical spaces, I have repeatedly seen how our postpartum experiences, linguistic diversity, family structures, and cultural practices can disappear within broad demographic categories. A single “Asian” data point cannot adequately represent the experiences of Indian, Pakistani, Bangladeshi, Nepali, Sri Lankan, Bhutanese, Maldivian, and other South Asian families, nor the considerable diversity that exists within each of these communities.
The Problem With Data Aggregation
In public health surveillance and clinical research, people of Asian descent are frequently analyzed as a single demographic category (CDC, 2023). Although aggregate statistics may suggest relatively high breastfeeding initiation or duration rates among the broad “Asian” population, these averages can conceal substantial differences between communities (CDC, 2023; Lang, 2021).
The AANHPI umbrella encompasses populations with roots in many countries and territories, speaking hundreds of languages and representing widely different socioeconomic circumstances, migration histories, and cultural traditions. These include East Asian, Southeast Asian, South Asian, Native Hawaiian, and Pacific Islander communities, among many others (AAPI Data, 2026). Treating these populations as interchangeable can produce an incomplete picture of maternal and infant health.
When data are not sufficiently disaggregated, several problems arise:
- Structural barriers remain hidden. Challenges affecting particular immigrant and refugee populations, such as navigating an unfamiliar healthcare system, adapting to U.S. workplace lactation policies, or obtaining linguistically appropriate healthcare, may be difficult to identify when outcomes are reported only for a broad racial category (Lang, 2021).
- Resources may not reach the communities that need them most. Public health programs depend on accurate needs assessments. If data do not identify which populations are experiencing early breastfeeding cessation, difficulties accessing lactation support, or other maternal health disparities, interventions may fail to reach the families most affected (AAPI Data, 2026).
- Clinical blind spots persist. Without more granular evidence, healthcare professionals have fewer tools for understanding population-specific barriers and developing culturally responsive approaches to maternal and lactation care (Lang, 2021).
South Asian Mothers: Navigating Migration, Tradition, and Modern Care
South Asian communities represent a significant and growing part of the U.S. population (AAPI Data, 2026). Breastfeeding is strongly valued in many South Asian cultures, but migration can reshape the social and cultural environment in which infant feeding takes place.
For many South Asian families, the postpartum period has traditionally involved support from an extended family network. Mothers may receive assistance from parents, in-laws, or other relatives who help with infant care, household responsibilities, culturally specific foods, physical recovery, and breastfeeding guidance.
Migration can disrupt these support systems. A mother who might otherwise have been surrounded by several generations of relatives may instead navigate postpartum recovery and infant feeding with a much smaller support network. At the same time, families may encounter differences between traditional postpartum practices and recommendations provided within the U.S. healthcare system.
These differences do not necessarily represent a conflict between “traditional” and “modern” care. Rather, they highlight the need for clinicians who can listen, understand the cultural meaning of postpartum practices, evaluate them through an evidence-based lens, and work collaboratively with families.
When South Asian populations are grouped with other Asian populations in health datasets, however, these migration- and culture-related experiences may be difficult to identify in standard clinical and public health metrics (CDC, 2023).
Why Better Data Can Lead to Better Clinical Care
Data collection is more than an administrative exercise. The categories health systems choose to measure influence which disparities become visible, which questions researchers ask, and where programs and resources are directed (Lang, 2021).
More detailed data collection, including specific ethnic or national origin, preferred language, and relevant migration or generational information, when appropriate and collected respectfully, can strengthen maternal and infant health efforts in several ways.
- Culturally responsive lactation support. Better population-specific evidence can help lactation consultants, nurses, physicians, and other healthcare professionals understand cultural postpartum and infant-feeding practices. Instead of automatically dismissing unfamiliar practices, clinicians can discuss their benefits and potential risks and incorporate safe practices into individualized care plans.
- More appropriate linguistic and educational resources. Disaggregated data can reveal which languages are spoken by the families a health system serves. Hospitals and community programs can then prioritize interpretation and translated resources related to breastfeeding, pumping, workplace lactation rights, postpartum warning signs, and infant health.
- More informed policy and community outreach. Local health departments and community organizations can use granular data to identify disparities that aggregate statistics might conceal. This information can guide culturally and linguistically tailored programs that respond to the barriers experienced by specific communities.
- Stronger partnerships with communities. Data disaggregation should not simply create smaller demographic boxes. Ideally, it should be accompanied by meaningful engagement with the communities represented in those data. Researchers and health systems should work with community organizations, families, and culturally knowledgeable professionals to determine which questions matter and how findings should be interpreted.
Moving Forward
Supporting AANHPI families requires moving beyond the assumption that a single racial category can adequately describe the health experiences of millions of people from profoundly different cultural, linguistic, and historical backgrounds (Asian Pacific Islander Breastfeeding Task Force of LA County / USBC AANHPI Caucus, 2020–2026).
For South Asian mothers, better data can make experiences visible that have too often been hidden within aggregate statistics. For other Asian American, Native Hawaiian, and Pacific Islander communities, disaggregation can similarly reveal needs and disparities that broad averages overlook.
Public health agencies, researchers, healthcare systems, and clinical providers should therefore prioritize meaningful data disaggregation while ensuring that data collection remains respectful, purposeful, and connected to improving care.
Better data alone will not eliminate maternal health inequities. However, better data can help us see whom our systems are serving well, whom they are overlooking, and where change is most urgently needed.
Better data creates better visibility. Better visibility makes more equitable, culturally responsive, and effective care possible.
References
AAPI Data. (2026). Data Disaggregation and Subgroup Analysis in Public Health. https://aapidata.com/
Asian Pacific Islander Breastfeeding Task Force of LA County / USBC AANHPI Caucus. (2020–2026). AANHPI Breastfeeding Week Framework and Community Guidelines.
Centers for Disease Control and Prevention. (2023). Disaggregation of Breastfeeding Initiation Rates by Race and Ethnicity. Morbidity and Mortality Weekly Report.
Lang, K. (2021). Incomplete Data Drives Flawed Conclusions About AANHPI Breastfeeding Rates. Journal of Human Lactation Research.