Digital Health Inequalities Among Immigrants in the United States: An Intersectional Analysis Using Nationally Representative Survey Data

Abstract

The rapid expansion of digital health during COVID-19 transformed healthcare delivery, offering new opportunities for remote care. However, health access remains inequitable, with barriers such as technology access, language barriers, and financial constraints disproportionately affecting immigrants and marginalized populations. This study applied an intersectional approach to examine digital health utilization trends by immigration status and key sociodemographic factors. This study analyzed nationally representative data from the 2021–2023 National Health Interview Survey (NHIS) for adults (N = 83,116). Immigration status was cross-classified with race/ethnicity, gender, marital status, education, income, health insurance, chronic conditions, and rural residency. Weighted logistic regression models examined disparities and moderation effects. While digital health utilization generally declined post-pandemic with increased access to in-person care, disparities across populations persisted. While naturalized immigrants had similar odds of digital health use compared to U.S.-born individuals, noncitizen immigrants had significantly lower odds. The findings also reveal noncitizen immigrants, particularly those with lower income, no insurance, and living in rural areas, face significant barriers in accessing digital health services. These disparities highlight the need for targeted policies to ensure equitable access to digital health resources for immigrant populations.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1007/s10903-026-01875-2.

Background

The rapid advancement of digital health technologies is transforming healthcare delivery worldwide. Digital health encompasses a broad range of interventions, including telemedicine, mobile health (mHealth) applications, electronic health records (EHRs), wearable health devices, and more recently, artificial intelligence–driven diagnostics [1, 2]. Among these innovations, telehealth, defined as the delivery of clinical care through video or telephone-based encounters, has become an increasingly prominent mode of healthcare access, with the potential to improve access to care and empower patients in managing their health [3]. The dramatic expansion of telehealth during the COVID-19 pandemic, in particular, highlighted its utility and adaptability in healthcare delivery, with approximately one in four U.S. adults using telehealth during the pandemic compared to single-digit percentages prior to this period [4].

While digital health presents significant opportunities to improve health outcomes, it also risks exacerbating existing health disparities. The digital divide, often described as digital exclusion, refers to inequalities in access to, and effective use of, digital technologies, including differences in skills, patterns of use, and material access [5–8]. These disparities are well-documented among populations with lower incomes, racial and ethnic minorities, rural residents, and older adults [9]. Structural barriers, such as limited broadband infrastructure and financial constraints, and individual-level challenges, such as lower digital literacy and concerns regarding data privacy, can hinder these groups from fully benefiting from digital health innovations [10]. Although a growing body of research has examined digital health disparities in the general population, less is known about how immigrants engage with telehealth and navigate through the specific challenges they may face in using digitally mediated healthcare services.

Immigrants represent a large and diverse segment of the U.S. population, yet their engagement with telehealth remains understudied. Existing research indicates that immigrants face numerous barriers to healthcare access, including language barriers, lower health literacy, limited insurance coverage, and fear of interacting with healthcare institutions due to immigration-related concerns [11–13]. These barriers may extend to digital health services, potentially limiting immigrants’ ability to participate in telehealth visits or communicate electronically with healthcare providers. Differences in cultural perceptions of healthcare, trust in digital platforms, and familiarity with U.S. healthcare technologies may further contribute to disparities in telehealth utilization among immigrant populations [14].

Despite the increasing reliance on telehealth to improve healthcare access, few studies have examined how intersectional social positions, such as immigration status, race/ethnicity, gender, and socioeconomic position, jointly shape digital health inequities. Existing research often relies on single-axis explanations of healthcare disparities, overlooking the compounded effects of multiple forms of marginalization [15]. Without a clearer understanding of how immigrants navigate telehealth systems, digital innovations risk excluding already marginalized communities and reproducing broader healthcare inequalities rather than reducing them. This study seeks to address this gap by employing an intersectional lens to examine how immigration status interacts with sociodemographic factors to influence telehealth utilization among immigrants in the U.S.

Theoretical Framework

To understand digital health disparities among immigrants, this study is grounded in an intersectional framework that examines how multiple dimensions of social position combine to shape healthcare experiences. Originating from critical legal scholarship, intersectionality emphasizes that social inequalities are not the result of single-axis factors but rather the product of overlapping and interdependent systems of power and exclusion [16–18]. In the context of digital health, immigrants who experience multiple marginalized identities may face compounded barriers to accessing and utilizing digital health technologies. Additionally, we draw upon the digital health equity framework (DHEF), which identifies key structural, systemic, and individual-level factors that influence digital health engagement [10]. The DHEF highlights that digital health disparities arise from the interaction of predisposing factors (e.g., demographic characteristics and cultural norms), enabling factors (e.g., health insurance coverage and access to broadband internet), and need-based factors (e.g., healthcare needs and chronic conditions) [19]. This framework provides a useful structure for examining how social and institutional conditions shape immigrants’ opportunities to engage with digital health. By integrating these theoretical perspectives, this study provides a more comprehensive understanding of the barriers and facilitators of digital health utilization, ultimately informing strategies to promote more equitable digital healthcare systems.

Methods

Data

This study used data from the National Health Interview Survey (NHIS) 2021–2023, a nationally representative survey of U.S. households that collects information on health status, healthcare access, and healthcare services including digital health. NHIS also collects demographic and socioeconomic characteristics. The analysis focuses on the sample adult population, which includes respondents aged 18 and older. The final analytical sample consists of 83,116 adults after excluding observations with missing data. Since NHIS data are publicly available and de-identified, this study was exempt from Institutional Review Board (IRB) approval.

Measures

Outcome Variable

The outcome variable was digital health utilization, measured by the question, “in the past 12 months, have you had an appointment with a doctor, nurse, or other health professional by video or by phone?” The variable was coded into a binary outcome indicating if the respondents used digital health (0 = no, 1 = yes).

Independent Variables

Immigration status. This primary independent variable was operationalized using NHIS items on place of birth and citizenship. Respondents were categorized as U.S.-born citizens, naturalized citizens (foreign-born individuals who reported having obtained U.S. citizenship), or noncitizen immigrants. The noncitizen category reflects citizenship status as measured by the NHIS and does not distinguish among different types of legal documentation.

Demographic and socioeconomic variables. Age, sex (female or male; respondents who selected “refused” or “don’t know” were excluded), race/ethnicity (non-Hispanic Asian [Asian], non-Hispanic Black [Black], Hispanic, or non-Hispanic White [White]), marital status (married or cohabitated, single, or previously married [widowed, divorced, or separated]), educational attainment (less than high school, high school, college degree, or graduate school), income level status (below federal poverty level [FPL], 100%−200% FPL, or above 200% FPL), having any chronic conditions (no or yes), health insurance (no insurance, private, or public), and living in rural areas (no or yes).

Analysis

We first presented weighted descriptive statistics to summarize sample characteristics, and digital health utilization rates were examined across immigration status groups from 2021 to 2023. Data from the 2021–2023 NHIS were pooled for analysis, with person-level sampling weights adjusted by dividing annual final weights by the number of survey years. Cross-classifications of immigration status with sociodemographic variables (e.g., race/ethnicity, education, income) were conducted to examine potential moderation effects. A series of weighted logistic regression models were estimated to assess the association between immigration status, sociodemographic factors, and digital health utilization. To ensure robustness, all analyses applied survey weights to account for the complex survey design and improve population-level generalizability.

Observations with missing data (3%) were excluded using listwise deletion. Statistical significance was assessed at the 95% confidence level, and results are reported as adjusted odds ratios (AORs) with 95% confidence intervals (CIs). All analyses were conducted using Stata 18 to account for the NHIS survey design.

Results

Descriptive Statistics

Table 1 presents weighted characteristics of the analytical sample. Overall, approximately one-third of adults reported using digital health services in the past 12 months. Most respondents were U.S.-born citizens, with smaller proportions of naturalized citizens and noncitizen immigrants. The sample was racially and ethnically diverse, with White adults comprising the largest group, followed by Hispanic, Black, and Asian respondents. The mean age was 48.22 years, and the sample was evenly distributed by sex. Socioeconomically, nearly half of respondents held a college degree or higher, and the majority had incomes above 200% FPL. Most respondents had private health insurance, while approximately one-third reported having at least one chronic condition.

Table 1.

Weighted characteristics of sampled adults in NHIS 2021–2023 (N = 83,116)

Variable	Mean (SE) or %
Digital health utilization
No	68.76%
Yes	31.24%
Immigration status
U.S.-born citizen	81.57%
Naturalized citizen	10.39%
Noncitizen immigrant	8.05%
Race/Ethnicity
non-Hispanic Asian [Asian]	6.10%
non-Hispanic Black [Black]	11.79%
Hispanic	17.23%
non-Hispanic White [White]	62.24%
Age	48.22 (0.12)
Sex
Female	51.41%
Male	48.59%
Marital status
Married or cohabitated	60.39%
Previously married	15.71%
Single	23.90%
Educational attainment
Less than high school	12.58%
High school	25.26%
College degree	49.48%
Graduate degree or above	12.69%
Income level
Below FPL	9.90%
100%−200% FPL	17.93%
Above 200% FPL	72.17%
Having chronic conditions
No	66.21%
Yes	33.79%
Health insurance status
No insurance	9.56%
Private insurance	67.11%
Public insurance	23.33%
Rural-Urban residency
Rural	13.62%
Urban	86.38%

Figure 1 shows digital health utilization across immigrant groups. While telehealth utilization has declined post-pandemic, persistent disparities present marginalization for immigrants. In 2021, U.S.-born and naturalized citizens had similar telehealth utilization rates of 38.2% (95% CI: 37.34–39.08) and 37.5% (95% CI: 35.35–39.70), respectively, compared to 24.25% (95% CI: 21.91–26.76) among noncitizen immigrants. By 2023, these disparities remained, with utilization dropping to 28% (95% CI: 27.17–28.84) for U.S.-born individuals, 28.3% (95% CI: 26.35–30.33) for naturalized citizens, and 14.42% (95% CI: 12.83–16.18) for noncitizen immigrants. While naturalized citizens have odds closer to U.S.-born citizens, noncitizen immigrants are the least likely to use telehealth compared to U.S.-born citizens.

Fig. 1.

Digital health utilization across immigration status, 2021–2023

Intersectionality Analyses

To explore the intersectional effects of immigration status and sociodemographic factors on digital health utilization, we conducted weighted logistic regression analyses. Figures 2, 3 and 4 present the odds ratios for digital health utilization across various intersectional groupings, using U.S.-born citizens as the reference category.

Fig. 2.

Immigration and sociodemographic factors in digital health utilization

Fig. 3.

Immigration and socioeconomic factors in digital health utilization

Fig. 4.

Immigration and health-related factors in digital health utilization

The effects of immigration and sociodemographic factors on digital health utilization are presented in Fig. 2. Compared to U.S.-born citizen & male, noncitizen immigrant & male had substantially lower odds of utilization (AOR = 0.48, 95% CI: 0.42–0.55), as did noncitizen immigrant & female (AOR = 0.78, 95% CI: 0.69–0.88). In contrast, naturalized citizen & female had higher odds of adoption (AOR = 1.36, 95% CI: 1.26–1.47). In terms of marital status, U.S.-born citizen & married or cohabitating individuals showed higher odds of utilization compared to their U.S.-born citizen & single counterparts. Naturalized citizen & married or cohabitating individuals had higher odds of use. Among noncitizen immigrants, utilization was consistently lower regardless of marital status, with particularly low odds among those who were single (AOR = 0.44, 95% CI: 0.36–0.54) compared to U.S.-born citizen & single adults. Noncitizen immigrant & Hispanic individuals had significantly lower odds of use (AOR = 0.39, 95% CI: 0.35–0.45), while naturalized citizens across race/ethnicity showed no significant differences compared to U.S.-born citizen & White. Notably, education moderated digital health adoption across immigration groups. Noncitizen immigrants & graduate degree had higher odds of utilization (AOR = 1.39, 95% CI: 1.16–1.66) compared to U.S.-born citizens & less than high school.

Figure 3 shows the intersection between immigration and socioeconomic factors. Digital health utilization also increased with income, with U.S.-born citizens in the highest income bracket (> 200% FPL) having the highest odds. However, noncitizen immigrant & below FPL had markedly lower odds of utilization (AOR = 0.50, 95% CI: 0.41–0.60) compared to U.S.-born citizens & below FPL, highlighting income-based disparities in access. Additionally, living in rural areas was associated with lower odds of utilization for both U.S.-born and immigrant populations. The lowest likelihood of utilization was observed among noncitizen immigrants living in rural areas (AOR = 0.41, 95% CI: 0.28–0.61) relative to U.S.-born citizens living in urban areas.

Finally, Fig. 4 shows the intersection between immigration and health-related factors. Having public or private insurance was associated with significantly higher odds of utilization for all groups. For example, U.S.-born citizens with public insurance had more than three times the odds of digital health use compared to uninsured U.S.-born citizens (AOR = 3.31, 95% CI: 2.92–3.75). While U.S.-born and naturalized citizens with chronic conditions had higher odds of digital health use, noncitizen immigrants with chronic conditions did not experience a comparable benefit (AOR = 0.95, 95% CI: 0.81–1.11) relative to U.S.-born citizens without chronic conditions.

Discussion

Digital health has emerged as a critical component of modern healthcare systems [3]. However, growing evidence suggests that digital health solutions may unintentionally exacerbate existing health disparities, particularly among marginalized populations facing multiple structural barriers to care [4]. The findings highlight persistent disparities in digital health utilization among immigrants. While overall digital health usage has declined post-pandemic, noncitizen immigrants remain the least likely to engage with these services, consistent with documented barriers such as limited digital literacy, privacy concerns, and immigration-related fears [20, 21]. Notably, naturalized citizens demonstrate usage patterns closer to U.S.-born individuals, suggesting that legal and social integration may mitigate barriers to digital health adoption. This finding aligns with prior evidence linking naturalization to improved health outcomes [22, 23].

The intersectional analyses reveal that sociodemographic factors shape digital health disparities, defined as unequal access to and utilization of digital health tools due to structural, cultural, and economic barriers [10]. While noncitizen immigrant & male exhibit lower odds of digital health use, noncitizen immigrant & female show slightly higher utilization rates. This trend may reflect gendered patterns of healthcare-seeking behaviors, with women generally being more proactive in engaging with health services [24]. Furthermore, race and ethnicity also intersect with immigration status in shaping digital health access. U.S.-born Black individuals show lower digital health utilization despite citizen status, suggesting structural barriers related to digital access and healthcare trust [25]. Among noncitizen immigrants, Hispanic individuals experience the lowest utilization, reinforcing concerns related to racialized immigration experiences, language barriers, and digital literacy gaps [26]. Educational attainment reveals a nuanced pattern. Those with graduate-level education have higher odds of using digital health compared to U.S.-born citizen & less than a high school education, suggesting that education functions as a key enabling resource [27].

Economic factors remain a critical determinant of digital health use. Higher income levels are consistently associated with greater utilization across groups. However, noncitizen immigrants at all income levels have lower odds of digital health use compared to U.S.-born citizen & below FPL, reflecting longstanding financial barriers [28]. Geographic disparities also play a role in digital health access. Rural residence is associated with lower utilization compared to U.S.-born citizens & living in urban areas, with the strongest effects among noncitizens. These disparities reflect infrastructural constraints, such as broadband infrastructure, lower digital literacy, and constrained institutional capacity [29–31], paralleling rural-urban gaps in in-person healthcare access [32].

Health insurance coverage emerges as a key enabler of digital health use across all groups. Both public and private insurance significantly increase the likelihood of digital health engagement, yet noncitizen immigrant & no insurance remain the least likely to utilize these services. Even when insured, noncitizen immigrants show lowest utilization. While insurance coverage can mitigate barriers to digital healthcare access, expanding insurance coverage for immigrant populations, particularly undocumented individuals, may be a crucial strategy in reducing disparities [33]. Additionally, chronic health conditions are associated with greater digital health utilization across all groups. However, noncitizen immigrant & chronic conditions still exhibit slightly lower utilization suggesting that, despite medical necessity, noncitizens face additional barriers, potentially including lack of culturally tailored digital health services and concerns about healthcare costs [21, 34].

A recurring debate in the digital health literature concerns whether observed disparities reflect inequities introduced by digital modalities themselves or simply mirror longstanding inequalities in healthcare access more broadly [35]. Our findings suggest that digital health largely reproduces existing healthcare inequalities while adding new barriers. Digital health platforms may further exacerbate these vulnerabilities by imposing material barriers, including the cost of necessary devices and subscription fees [36]. Moreover, these tools often require levels of digital literacy, language proficiency, and institutional trust that marginalized populations may not possess, while also heightening concerns related to data use, surveillance, and enforcement [37, 38].

Despite these contributions, several limitations should be noted. First, the cross-sectional design precludes a causal relationship between immigration status and digital health utilization. Second, telehealth-only measurement likely underestimates the breadth and complexity of digital health engagement. Third, although the NHIS is administered in English and Spanish, language limitations may still underrepresent some immigrant populations. Finally, we did not capture more contextual factors such as digital literacy, language preferences, or trust in digital platforms, all of which are documented to shape digital health engagement [39, 40]. Healthcare systems often lack culturally and linguistically appropriate resources and impose structural barriers [14, 41]. Future research incorporating longitudinal, multilingual, and qualitative approaches is needed to address these gaps.

Policy & Practice Implications

The persistent disparities identified in this study have significant implications for healthcare equity. Federal and state-level policies promoting telehealth expansion have primarily focused on improving broadband access and provider reimbursement models, yet they have not adequately addressed barriers unique to immigrant communities. For instance, policies such as the CARES Act and the American Rescue Plan expanded digital health services but failed to address the exclusion of noncitizens from many federally funded healthcare programs [42]. Expanding Medicaid eligibility to include more immigrant groups, as well as increasing funding for community health initiatives that provide digital literacy training, could help bridge these gaps. More importantly, expanding inclusive digital health initiatives is not only a matter of equity but also of economic prudence. Research indicates that every $1 invested in public health programs can yield up to $2.50 to $5.60 in economic benefits, including reduced healthcare costs and improved productivity [43]. Therefore, extending digital health resources and access to immigrant populations rather than excluding them can strengthen the overall social welfare system and generate net economic gains.

Additionally, addressing digital health disparities requires targeted outreach efforts to build trust among immigrant populations. Community-based programs that provide culturally tailored telehealth services, multilingual digital health resources, and patient navigation support may help mitigate some of the challenges faced by immigrants. Furthermore, ensuring that digital health platforms are accessible to individuals with limited English proficiency and providing assistance with navigating online healthcare systems can enhance digital health adoption among immigrant communities. Future policies should prioritize inclusive telehealth initiatives, such as integrating immigrant-friendly healthcare navigation support, and expanding eligibility for federally funded digital health programs.

Although this study is situated within the U.S. healthcare system, similar digital health disparities have been observed in various countries. Canada’s experience shows that immigrants use telehealth services at roughly half the rate of long-term residents (11% vs. 22%), with language barriers identified as a major obstacle to access [44]. Substantial gaps in digital health usage among migrants have also been observed in Sweden, prompting policymakers to call for a national strategy to improve digital health literacy in minority populations [45]. The common thread is that without intentional inclusive strategies, telehealth expansion may replicate or even widen existing inequities. Simply introducing digital health technologies is not a panacea, and underlying social, linguistic, and policy barriers must be addressed for these tools to benefit everyone [38].

Conclusion

This study highlights the persistent disparities in digital health utilization among immigrant populations, with noncitizen immigrants facing the greatest barriers to access. Socioeconomic status, geographic location, insurance coverage, and chronic health conditions all influence digital health access, yet systemic barriers prevent noncitizens from fully benefiting from these services. Addressing these disparities requires targeted policy interventions, expanded insurance coverage, and culturally tailored digital health initiatives. As digital health continues to play an increasingly important role in healthcare delivery, ensuring equitable access for all populations regardless of immigration status will be essential in reducing health disparities and improving overall public health outcomes.

Supplementary Information

Below is the link to the electronic supplementary material.

Author Contributions

All authors contributed to the study’s conception and design. Conceptualization: C.C., J.P., and S.V.-G.; Methodology: C.C. and J.P.; Formal analysis and investigation: C.C.; Writing–original draft preparation: C.C.; Writing–review and editing: C.C., J.P., and S.V.-G.; Supervision: S.V.-G.

Funding

Funding is applicable for this study.

Data Availability

This study uses publicly available data from the National Health Interview Survey (NHIS), which can be accessed at https://www.cdc.gov/nchs/nhis/index.html. Further analyses or specific datasets generated during this study are available from the corresponding author upon reasonable request.

Declarations

Competing Interests

The authors declare no competing interests.