Asian American/Pacific Islander and Hispanic Ethnic Enclaves, Neighborhood Socioeconomic Status, and Hepatocellular Carcinoma Incidence in California: An Update

Hepatocellular carcinoma (HCC) is the dominant histologic type of liver cancer in the United States (1). Nationally, HCC incidence is three times higher in males than females and highest among the American Indian/Alaska Native population, followed by Asian American/Pacific Islander (AAPI) and Hispanic populations (2, 3). HCC incidence had been steadily increasing for decades (4, 5), until around 2006, when HCC incidence trends began to stabilize and eventually decrease, especially for AAPI and Hispanic populations (3, 6).

While individual-level etiologic differences can explain some variation in HCC incidence across different racial/ethnic groups (7), neighborhood contextual factors have emerged as important risk factors for racial/ethnic disparities (8, 9). Ethnic enclaves and various measures of neighborhood socioeconomic status (nSES) such as poverty level, household educational attainment, and unemployment rate, have been linked to increased risk of HCC in different regions of the United States (10–12). Enclaves are neighborhoods that are more ethnically distinct, often defined by high concentrations of specific racial/ethnic groups, foreign-born residents, and households with limited English proficiency or that are linguistically isolated. Enclaves tend to have businesses and social institutions that reflect the linguistic and cultural values of their residents, allowing greater opportunities to disseminate information that is linguistically and culturally relevant. Moreover, ethnic enclaves offer residents social integration and social support and/or collective efficacy from coethnic residents, which are important factors that can positively impact health (8, 13). At the same time, ethnic enclaves tend to be underserved and of lower socioeconomic status, therefore lacking resources for education, employment, health care, housing, and lifestyle behaviors such as physical activity and adequate nutrition leading to poorer health (13). Similarly, nSES has been shown to be an independent risk factor for health, beyond individual-level socioeconomic status, and residence in higher nSES areas may provide better access to resources such as parks and recreational opportunities, healthy food environments, and health care; all factors that can have a cumulative positive impact on health (8).

Two of the fastest-growing racial/ethnic groups in the United States are AAPI and Hispanic and California has the largest AAPI and Hispanic populations in the country (14). To our knowledge, only two studies have investigated the associations between ethnic enclaves and/or nSES on the risk of HCC among AAPI and Hispanic populations living in California. These previous studies found that AAPI and Hispanic enclaves and areas of low nSES were at increased risk of HCC (15, 16), although patterns differed by sex (15). Given changing patterns of HCC incidence and the ethno-demographic and socioeconomic landscape both in California and nationwide, we seek to build upon this work by incorporating the most currently available state cancer registry and decennial census data and provide an update on the disparities in HCC incidence by statewide distributions of ethnic enclave and nSES among AAPI and Hispanic populations in California, separately by race/ethnicity and sex.

The fundamentals of the study population, data extraction, and analysis have been reported in detail before (6, 15). Briefly, we obtained data for all primary, invasive HCC [International Classification of Diseases for Oncology, Third Edition (ICDO-3) site code 22.0, histology codes 8170–8175] from January 1, 1988, through December 31, 2012 from the California Cancer Registry (CCR), which comprises three of the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) program registries (17).

The analysis included 13,160 HCC cases (1,780 AAPI females, 4,753 AAPI males, 1,744 Hispanic females, and 4,883 Hispanic males) diagnosed within three 5-year intervals around decennial census years, 1990, 2000, and 2010 yielding diagnoses from 1988 to 1992, 1998 to 2002, 2008 to 2012, respectively. All cases were assigned to census tracts by CCR based on address information at diagnosis. In this analysis, 96% of Hispanic cases and 98% of AAPI cases were assigned to a census tract based on valid street address or zip+4/+2; for the remaining cases, census tracts were assigned based on zip code centroids. AAPI and Hispanic ethnicity were categorized using methods and algorithms described previously (15, 18, 19). We chose to use “Hispanic” in lieu of terms containing the word “Latin” because the registry defines this racial/ethnic group as origin from any Spanish-speaking country, and therefore includes the European country of Spain, but excludes origin from non-Spanish speaking Latin American countries such as Brazil (20). That being said, the Pew Research Center estimates that 84% of Hispanic Americans in California are of Mexican ancestry (21). We were not able to disaggregate data into specific AAPI ethnic groups for these analyses due to the lack of subgroup-specific population estimates for census tracts; therefore, AAPI populations are presented as an aggregate group. Furthermore, a high proportion of Hispanic cases with unspecified ethnicity precluded our ability to disaggregate Hispanic data into more granular ethnic groups. We used 2000 U.S. Census population estimates by race/ethnicity and sex at the census tract level. Case data was appended to census tract level neighborhood data.

Ethnic enclaves are well-established and widely used in cancer surveillance literature (8, 12). We operationalized ethnic enclaves as geographic units with higher concentrations of a specific race/ethnicity, foreign-born and/or recent immigrants, and non-English language use than other geographic units (22). Principal components analysis, a well-validated statistical method (23), was applied to develop these measures using 1990 and 2000 U.S. Census and 2008 to 2012 American Community Survey (ACS) variables at the census tract level. For AAPI enclaves, we included data on linguistic isolation, English fluency, AAPI race, and recent immigration. For Hispanic enclaves, we included data on linguistic isolation, English fluency, Hispanic ethnicity, recent immigration, and nativity. Each census tract was assigned to a quintile (Q) based on the statewide distribution of each enclave index for each decennial Census year (1990, 2000, 2010). We used enclave quintiles (Q5 = most ethnically distinct neighborhoods vs. Q1 = least ethnically distinct neighborhoods) as well as a dichotomous measure of enclave (Q4–Q5 = enclave vs. Q1–Q3 = nonenclave; ref. 15).

To measure nSES, we used an established index that incorporates Census and ACS data on education, occupation, employment, household income, poverty, rent, and house values using principal components analysis (24). Each census tract was assigned to an nSES quintile based on the statewide distribution of the index for each decennial Census year (1990, 2000, and 2010). We utilized both the full range of nSES quintiles (Q1 = lowest nSES vs. Q5 = highest nSES) as well as a dichotomous measure combining Q1–Q3 (low nSES) versus Q4–Q5 (high nSES; ref. 15).

We used SEER*Stat software (25) to compute age-adjusted incidence rates (IR; per 100,000 population; standardized to the 2000 U.S. standard million population) and IR ratios (IRR) for each strata of ethnic enclave and nSES by sex and race/ethnicity for three time periods: 1988 to 1992, 1998 to 2002, 2008 to 2012, and the combination of the three periods, which will be referred to henceforth as the “combined period.” Confidence intervals (CI) were calculated using Tiwari and colleagues, 2006 modification (26). Population counts for incidence calculations were estimated using 1990, 2000, and 2010 census counts multiplied by 5. We conducted tests for linear trend of IRs across ethnic enclave and nSES quintiles using weighted linear regression where weight was the inverse of the variance of rate. All statistical tests were two-sided with P < 0.05 indicating statistical significance and CIs set to 95%. Data sets used for this analysis can be made available upon reasonable request.

HCC cases in our study included approximately three times as many males than females, with little variation in sex distributions by time period or race/ethnicity (Table 1). More AAPI cases were diagnosed at a very young age (<40 years) compared with Hispanic cases. Cases with distant or unknown stage decreased over time, while the number of cases with localized or regional stage increased over time for both AAPI and Hispanic groups.

Among AAPI females (Table 2; Figs. 1–3), there was no association between HCC incidence and AAPI enclave. HCC risk increased with decreasing nSES in the combined time period (Q1 vs. Q5: IRR = 1.22; 95% CI, 1.04–1.44; P_trend = 0.03) with stronger associations in the latest time period (2008–2012; Q1 vs. Q5: IRR = 1.50; 95% CI, 1.18–1.91; P_trend < 0.01). When AAPI enclave and nSES were studied jointly, in the earliest time period (1988–1992), AAPI females in nonenclave/low SES areas had increased risk of HCC (IRR = 2.06; 95% CI, 1.17–3.80) compared with those in nonenclave/high nSES areas. This association was not observed in later time periods.

For AAPI males (Table 2; Figs. 1–3), living in highest versus lowest quintile of AAPI enclave increased risk of HCC during the combined time period (Q5 vs. Q1: IRR = 1.25; 95% CI, 1.03–1.53) and the latest time period (2008–2012; Q5 vs. Q1: IRR = 1.39; 95% CI, 1.05–1.88). In every time period, HCC risk increased 46% to 64% for lowest versus highest nSES with strong ordinal trends in the later time periods. In the combined time period, compared with AAPI males in nonenclave/high nSES areas, AAPI males in enclave/low nSES areas experienced the greatest risk of HCC (IRR = 1.43; 95% CI, 1.28–1.60), followed by those living in nonenclave/low nSES areas (IRR = 1.17; 95% CI, 1.02–1.34). Similar associations were seen in the latest time period (2008–2012; IRR enclave/low nSES = 1.49; 95% CI, 1.28–1.75 and IRR nonenclave/low nSES = 1.24; 95% CI, 1.02–1.51).

Hispanic females (Table 3; Figs. 1–3) living in the highest versus lowest quintile of Hispanic enclave experienced an increased risk of HCC in the combined time period (Q5 vs. Q1: IRR = 1.42; 95% CI, 1.13–1.82). A stronger, ordinal association existed in the latest time period (2008–2012; Q5 vs. Q1: IRR = 1.72; 95% CI, 1.26–2.39; P_trend = 0.04). During the latest time period (2008–2012), Hispanic females with lowest versus highest nSES had increased risk of HCC (Q1 vs. Q5: IRR = 1.41; 95% CI, 1.09–1.86). However, this association was attenuated when the time periods were combined due to nonordinal inverse associations in the earliest time period (1988–2002). In the combined time period, compared with those in nonenclave/high nSES areas, those in low nSES areas, regardless of enclave status, had a 22% increased risk of HCC. In the latest time period (2008–2012) this risk ranged from 40% to 46%.

There were no ordinal associations with Hispanic enclave nor nSES and HCC incidence among Hispanic males (Table 3; Figs. 1–3). However, when Hispanic enclave and nSES were studied jointly, Hispanic males in nonenclave/low SES areas had a 19% (95% CI, 1.07–1.32) increased risk of HCC in the combined period and a 30% (95% CI, 1.14–1.47) increased risk in the latest time period (2008–2012), compared with those living in nonenclave/high SES areas. Risk was also elevated 35% (95% CI, 1.05–1.70) for those in enclave/high nSES versus nonenclave/high nSES areas during the latest time period (2008–2012).

In general, ordinal associations for ethnic enclave and nSES were stronger in the latest time period (2008–2012). However, time period patterns varied by race/ethnicity and sex. For AAPI females (Table 2; Figs. 1–3), there were no temporal trends in associations for AAPI enclave but associations of increased HCC incidence with decreasing nSES were limited to the latest time period (P_trend < 0.01). For the joint AAPI enclave/nSES variable, a two-fold increased risk of HCC in the earliest time period (1988–1992) for low versus high nSES among those in nonenclave neighborhoods (IRR = 2.06; 95% CI, 1.17–3.80) became attenuated towards the null in the latest time period. For AAPI males (Table 2; Figs. 1–3), trends for increased HCC incidence with increasing AAPI enclave were not significant in the earliest time period, but were significant in the middle (P_trend = 0.04) and marginally significant in the latest (P_trend = 0.08) time periods. Furthermore, positive associations between HCC incidence and nSES and joint AAPI enclave/nSES became stronger in successive time periods. For Hispanic females (Table 3; Figs. 1–3), positive associations for Hispanic enclave, nSES, and joint Hispanic enclave/nSES were limited to the latest time period. For Hispanic males (Table 3; Figs. 1–3), associations did not vary by time period for Hispanic enclave or nSES separately, however, positive associations for joint Hispanic enclave/nSES were only evident in the latest time period.

In this population-based study, we found differences in HCC IRs by two important neighborhood contextual factors: ethnic enclave and nSES. Among AAPI males, but not AAPI females, living in highest versus lowest quintile of AAPI enclave increased risk of HCC by 25% in the combined time period. For both AAPI females and males, there were ordinal trends of increasing HCC risk with decreasing nSES. Regardless of AAPI enclave status, living in low nSES areas increased risk of HCC in AAPI males by 17% and 43% compared with those living in a nonenclave/high nSES area in the combined time period. For Hispanic females and males in the combined time period, there were no ordinal trends to the associations found for Hispanic enclave or nSES when analyzed separately, although ordinal patterns were more apparent for Hispanic females in the later time period. When Hispanic enclave and nSES were considered jointly, the influence of lower nSES on HCC risk became evident, especially among Hispanic females for whom risk increased 22% for low versus high nSES, regardless of enclave status in the combined study period. These findings suggest that social, economic, and cultural characteristics of neighborhoods can influence incidence of HCC and differ over time between AAPI and Hispanic females and males in California.

A summary of findings from two prior investigations of ethnic enclave, nSES, and liver cancer/HCC incidence in California, as well from the current study, are presented in Supplementary Table S1. The first analysis, led by Chang and colleagues (15), looked at liver cancer rates from 1998 to 2002 (sensitivity analyses restricting to HCC yielded similar results) while the second analysis, led by Yang and colleagues (16), examined ethnic enclave and HCC-specific incidence during 2008 to 2012. Our results for AAPI and Hispanic males are similar to Chang and colleagues, however, our findings of increasing HCC risk with decreasing nSES in AAPI females and no association between nSES and HCC in Hispanic females deviates from previous findings. We found strong positive associations with nSES among AAPI females in the latest time period (2008–2012), which drove findings of significant increased risk of HCC in the combined time period. For Hispanic females, strong inverse associations with nSES in the earliest time period (1988–1992) negated positive associations seen in the latest time period (2008–2012), resulting in no significant associations for the combined time period. Since the years included in our earliest and latest time period are outside the 1998 to 2002 time frame of the Chang and colleagues study, some differences are expected. For example, declines in neighborhood and individual economic status due to the 2008 global recession, especially among already marginalized populations, may have had negative effects on personal health, including communicable and noncommunicable disease risk (27). Our analysis supports such a pathway as risk of HCC increased with decreasing nSES over time for all groups except Hispanic males, which requires some additional investigation. Furthermore, although Chang and colleagues reported results for all liver cancers whereas we report on HCC-specific rates, sensitivity analyses restricting to HCC in their analysis yielded similar results. Finally, our finding of higher incidence of HCC for those living in the highest versus lowest quintile of ethnic enclave is in line with results from the HCC incidence analysis conducted by Yang and colleagues in 2008 to 2012, although this previous study did not present results by sex, as we did. Sex-specific IRs is an important strength of our study as we found that the associations between HCC and ethnic enclave were limited to Hispanic females and AAPI males.

The geographic distribution of characteristics of the neighborhood built environment (such as traffic density, businesses, parks and recreational facilities, and health care services) and high-risk health behaviors that are linked to liver diseases (such as alcohol consumption and tobacco smoking) can provide some rationale for the association between low nSES and high HCC incidence seen in Hispanic and AAPI populations (28). Alcohol consumption has been found to increase the risk of liver cancer by approximately 10% per drink per day (29). A recent nationwide geographic study of alcohol retail density found that greater density of alcohol retailers was associated with higher levels of neighborhood poverty (30). This suggests that our findings could be partially explained by the availability of harmful structural, built, and social attributes of lower nSES areas that can potentially increase the risk of liver disease and HCC. Additionally, HCC risk increases substantially with increasing BMI (31) and individuals living in lower nSES neighborhoods face more constraints to exercise (reduced access to parks and recreational facilities) and nutrition (lower prevalence or absence of retailers that offer whole and nutrient dense food) leading to higher BMI (32). Other factors to consider as pathways for how nSES can influence HCC risk include geographic differences in access to health prevention services, such as hepatitis vaccination and screening (33, 34) or high-quality health care (35).

Ethnic enclaves may influence cancer risk differently from nSES. Mortality (overall and cancer-specific) can be lower for Hispanic populations living in Hispanic enclaves, even though these same neighborhoods are also economically disadvantaged, which, as discussed above, is correlated with poorer health (36). Referred to as the Hispanic Paradox, the health benefit of Hispanic enclaves can be explained by a high level of social support and sense of community, consuming traditional and healthier diets, more employment, and more stable family structures and residential history (37). In our study, we found some evidence of higher risk of HCC incidence in more ethnically Hispanic neighborhoods but there was no linear trend in the combined time period. When paired with nSES, residence in a Hispanic enclave seemed to have a weaker influence over HCC risk than nSES, especially among Hispanic females. It is possible that for cancers that have a strong causal link with infections, ethnic enclaves may not be as influential as they are for cancers that have strong lifestyle risk factors (12). This may partially explain our findings for the weak relation between Hispanic enclaves and HCC risk as hepatitis C virus (HCV) infection is the most frequently reported etiologic factor for Hispanic HCC cases (1). Nevertheless, it is important to continue to track the influence of Hispanic enclaves on HCC risk as the increasing prevalence of obesity and nonalcoholic fatty liver disease/metabolic-associated fatty liver disease among Hispanic Americans (38), coupled with highly effective treatments for HCV (39), suggests that lifestyle risk factors will play a larger role in HCC etiology than viral infections in Hispanic populations.

Among AAPI females in our study, especially in the earlier years, more ethnically AAPI neighborhoods were protective against HCC. Although AAPI enclaves share some similarities with Hispanic enclaves in terms of social support and traditional lifestyle habits (12), AAPI populations, collectively, tend to report higher educational attainment and less poverty than Hispanic populations (40). It is important to note, however, that there is significant educational and income heterogeneity among different AAPI ethnicities (41). In our study, a very high proportion of Hispanic cases who lived in Hispanic enclaves also lived in low nSES areas compared with AAPI cases who lived in AAPI enclaves and this difference persisted over the study period (Supplementary Table S2). Therefore, AAPI enclaves may have characteristics associated with areas that have high individual-level and neighborhood-level socioeconomic status, such as greater access to healthcare resources, awareness about cancer prevention and screening (42), and, as it relates to HCC, adherence to hepatitis B virus (HBV) vaccination, screening, and treatment. HBV infection is the most frequently reported HCC risk factor among AAPI cases, especially those who are foreign-born (1). Differences between AAPI and Hispanic enclaves could explain why we saw differential associations for ethnic enclave among these two ethnically aggregate populations, however, a comparison of disaggregated AAPI and Hispanic ethnicities would yield more accurate and valid comparisons.

We detected temporal changes in associations of ethnic enclave and nSES with HCC incidence. Increased risk of HCC with ethnic enclave and low nSES was restricted to or stronger in the latest time period of 2008 to 2012. Furthermore, between the earliest (1988–1992) and latest (2008–2012) time periods, the proportion of AAPI cases residing in areas of low nSES decreased by 11% while the proportion of Hispanic cases residing in enclaves decreased by 6%. As mentioned earlier, the Great Recession of 2008 had immediate and far-reaching economic impacts on all Americans, but especially for those in marginalized and underserved communities, which may explain these trends. Changes in factors that affect individual-level risk for HCC, such as alcohol abuse and smoking (driven by increased stress and adverse mental health), reduced access to healthcare (driven by lower income and/or unemployment), and changes in factors that have an effect on neighborhood contextual risk factors such as immigration patterns, economic growth and recession, greater wealth gaps, as well as gentrification may have influenced some of these findings and warrants more in-depth analysis in future studies (27, 43).

Our study should be viewed in light of some limitations. First, the use of a registry-based population-level dataset limited our ability to control for potential individual-level confounders such as educational attainment, income, lifestyle risk factors, metabolic risk factors, infections, and health care access. Second, we assessed neighborhood characteristics at the time of diagnosis and were unable to assess lifetime residential history. Lifetime exposure to neighborhood contextual factors, and factors affecting duration of residence in a neighborhood and frequency of moves could prove important in predicting cancer risk. For example, long-term exposure to poverty is associated with known risk factors for HCC, such as obesity (44), early smoking initiation (45), and diabetes (46). Third, we were not able to assess associations between enclave and nSES by nativity or disaggregated race/ethnicity (especially for AAPI populations) due to the unavailability of census tract level population data by nativity or disaggregated race/ethnicity. Previous studies in California have found disparities in HCC incidence by specific AAPI groups and/or nativity (6, 15, 16, 47–49). Among AAPI populations, Vietnamese Americans had the highest HCC IRs (6, 16, 48) and IRs for all groups were generally higher for foreign-born than U.S.-born (6, 15). In Hispanic populations, U.S.-born males had higher HCC incidence than foreign-born males, whereas no relative differences by nativity in females were found (6, 47). Fourth, we used census tracts based on administrative boundaries to define geographic neighborhoods. Neighborhoods defined by individual-level self-reported measures may be more representative of the lived experience within those areas than geospatial measures (8), however, for population-based health studies such as ours, census tracts offer a useful approximation of neighborhoods (50). Fifth, our findings are specific to the sociodemographic, contextual, and economic environment in California and as such, may not be representative of findings in other geographic locations across the United States. Sixth, since there is no standard definition of ethnic enclave, our findings are specific to the measurement of enclaves in our study. However, while many prior studies have used a single measure of racial/ethnic density (12), our utilization of a multicomponent index measure to capture ethnic enclaves beyond racial/ethnic composition, accounting for immigration and linguistic proficiency and isolation, is a more comprehensive approach. Finally, although we had population data from the 2020 census, we did not have sufficient years of cancer registry data to create a 5-year assessment of HCC rates around the most recent census, as we did for previous census years. Therefore, continued examination of HCC risk in relation to ethnic enclaves and nSES in California is imperative as more data become available.

There are several strengths of our study. Our examination of ethnic enclaves, nSES, and HCC is the largest to date with a long assessment period spanning from 1988 to 2012. We were able to report stratified results highlighting differences by time period, race/ethnicity, and sex. Our cases were ascertained through high quality registry data, which are mandated by the state for reporting, therefore, it is unlikely that a significant number of HCC cases were missed. Furthermore, because separate data were used to operationalize the exposure and the outcome, any misclassification would have been independent and nondifferential, typically leading to more conservative estimates toward the null. Finally, because our findings are consistent with previous studies that have examined this same association with earlier waves of data (15, 16), it is unlikely that our analysis yielded spurious results.

In summary, we found persistent and significant variation in HCC incidence by ethnic enclave and nSES among AAPI and Hispanic populations living in California, consistent with patterns seen in earlier reports. Associations varied by time period and sex. Analysis of the joint effects of ethnic enclave and nSES demonstrated the interplay of these two important contextual factors and yielded findings that would not have otherwise been detected in separate analysis. Changing patterns in HCC incidence (6, 51) and the racial/ethnic milieu in California, a state with dynamic population growth and immigration patterns warrant further surveillance of HCC incidence. Future longitudinal studies are needed to further explore specific attributes of enclaves and nSES that impact HCC risk especially in subpopulations such as recent immigrants.

M. Sangaramoorthy reports grants from NCI during the conduct of the study. M.C. DeRouen reports grants from SEER during the conduct of the study. C.A. Thompson reports grants from NCI (via University of California, San Fransisco) during the conduct of the study. S.L. Gomez reports grants from NCI during the conduct of the study. S. Shariff-Marco reports other support from NCI and grants from California Department of Public Health during the conduct of the study. No disclosures were reported by the other authors.

M. Sangaramoorthy: Conceptualization, visualization, writing–original draft, writing–review and editing. J. Yang: Resources, data curation, software, formal analysis, validation, visualization, methodology, writing–original draft, writing–review and editing. A. Guan: Writing–original draft, writing–review and editing. M.C. DeRouen: Writing–review and editing. M.M. Tana: Writing–review and editing. M. Somsouk: Writing–review and editing. C.A. Thompson: Writing–review and editing. J. Gibbons: Resources, data curation, validation, writing–review and editing. C. Ho: Writing–review and editing. J.N. Chu: Writing–review and editing. I. Cheng: Funding acquisition, writing–review and editing. S.L. Gomez: Conceptualization, resources, data curation, supervision, funding acquisition, investigation, writing–review and editing. S. Shariff-Marco: Conceptualization, supervision, funding acquisition, investigation, methodology, writing–original draft, project administration, writing–review and editing.

This work was supported by the California Department of Public Health pursuant to California Health and Safety Code Section 103885; Centers for Disease Control and Prevention's National Program of Cancer Registries, under cooperative agreement 5NU58DP006344; the NCI's SEER Program under contract HHSN261201800032I awarded to the University of California (San Francisco, CA), contract HHSN261201800015I awarded to the University of Southern California (Los Angeles, CA), and contract HHSN261201800009I awarded to the Public Health Institute, Cancer Registry of Greater California. The ideas and opinions expressed herein are those of the author(s) and do not necessarily reflect the opinions of the State of California, Department of Public Health, the NCI, and the Centers for Disease Control and Prevention or their contractors and subcontractors.

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