Abstract
Colorectal Cancer (CRC) is common in Lao Americans, but screening is suboptimal. To investigate CRC screening rates of Lao Americans in Minnesota, and how predisposing characteristics, enabling resources, and perceived need are associated with screening. We conducted a convenience-sample cross-sectional survey of 50–75-year-old Lao Americans, using stepwise multivariate logistic regression to identify factors associated with ever being screened. Of the 118 survey participants, 45% ever received CRC screening. In univariate regression, some enabling resources (having a primary care provider, higher self-efficacy in pursuing screening) and perceived needs (knowledge of who should be screened, higher number of chronic illnesses) were associated with screening. In multivariate logistic regression, the odds of ever being screened was 12.4 times higher for those with a primary care provider than for those without (p = 0.045). The findings reinforce a need for developing culturally tailored interventions focused on Lao-American immigrants to promote CRC screening.
Keywords: Colorectal cancer, Screening, Asian-American, Cancer prevention, Behavioral model
Introduction
Colorectal Cancer (CRC) incidence and mortality is directly related to screening [1]. CRC is the second leading cause of cancer deaths in the United States [2], and disparities in cancer screening and optimum utilization of available screening tools remain major public health issues. In the United States, screening participation remains suboptimal, particularly among underserved populations, including for racial/ethnic minorities and even more so for those with limited English proficiency [3]. Asian Americans are 15–20% less likely to have undergone CRC cancer screening than Non-Hispanic whites (NHWs) [4, 5], and rates differ by ethnic subgroup [6]. Interventions among Asian Americans also appear to have differential effects by ethnicity [7].
Various studies have examined the barriers that Asian Americans face related to CRC screening. Analysis of the 2001 California Health Interview Survey found that Asian Americans who were male, older, uninsured, a more recent immigrant, less educated, poor, or living with three or more people were less likely to be screened for CRC cancer [4, 5]. Low health literacy and limited English proficiency have also been correlated with low CRC screening among Asian-Americans [8]. However, barriers by ethnic subgroup may differ [9], may be gender-specific [10], and even the structure of the health care market can be influential [11]. Previous work has also identified specific facilitators among Asian-Americans [5, 9].
For Lao-American women and men, CRC is the second and third most common cancer, respectively, and is the most rapidly rising cancer in Laotians in the U.S [12]. Minnesota is home to the third largest population of Lao-Americans [13], many of whom sought asylum during a large influx of refugees during the 1970s [14]. Minnesota ranks, on average, among the healthiest states in the nation, yet it has some of the most significant and persistent disparities in health outcomes [15]. In 2017 in Minnesota, 65% of Asian Americans had received CRC screening compared to the state-wide average of 73% [16], but this differs by subgroup. Those from Laos had the lowest screening rate at 48%, compared to those from Burma (60%), Thailand (64%), Philippines (66%), Cambodia (71%), and Vietnam (75%). By spoken language, Lao speakers had a CRC screening rate of 59%, compared to 72% for Korean and Cambodian, and 74% for Vietnamese [16].
Though several factors have been correlated with CRC screening in Asian American subgroups, participation by Lao Americans in these studies has been small. Barriers by ethnic subgroup may account for differences seen in screening rates, but whether any previously studied facilitator or barrier is influential within the Lao-American community has not been investigated. Through a community-university partnership and use of the Behavior Model for Vulnerable Populations as a framework, we sought to investigate the rates of reported CRC screening in the Lao-American community in Minnesota, and to understand how predisposing characteristics, enabling resources, and perceived need were associated with screening.
Conceptual Framework
The behavioral model for vulnerable populations [17] is a revision of the behavioral model, a leading model used to explain the use of health care services [18]. This revision provides a framework with domains that may be especially relevant to understanding the health and health-seeking behavior of vulnerable populations. The model suggests that a person’s use of health services is a function of an individual or population’s characteristics, namely: (1) his or her predisposition to use services, (2) factors that enable or impede use, and (3) his or her perceived need for care. This, along with the environment (health care system, external environment) and personal health behaviors (personal health practices, use of health services), influences health service use.
Predisposing factors include demographics such as gender, age, and marital status; health beliefs such as attitudes toward health services and knowledge about disease; social structural characteristics including ethnicity, education, employment, acculturation, immigration status, and religion; sexual orientation; and childhood characteristics [17].
Enabling resources are those that would enhance or impede an individual’s ability to use healthcare services, should the need arise. These include personal and family resources such as having a regular source of care, insurance, income, competing needs, ability to negotiate the system which may be influenced by English fluency, self-help skills (e.g. self-efficacy), transportation, and social support; and community resources such as health and social services and crime rates [17].
Need characteristics are those that are most immediate to the use of healthcare services. They include perceived health status and evaluated health status. In the case of cancer, this might include having a family history of cancer and knowledge of cancer risk and screening guidelines (perceived health status). The number of chronic conditions may be both perceived (e.g. they cause symptoms and influence self-reported health status) and evaluated (e.g. clinically identified by a healthcare provider) [17].
Methods
Participants
The population studied included male and female adults aged 50–75 years who identified as Lao American and who spoke Laotian and/or English. Participants were recruited from the Lao Assistance Center of Minnesota (LACM), a community-based social service agency that supports members of the Lao-American community, and during a regional Lao community holiday celebration. The LACM offers health and well-being programming, civic engagement, and youth and elder programs, as well as employment and housing counseling. Most participants that utilize LACM services are from the urban and suburban areas of Minneapolis and St. Paul, which is where 78% of Minnesotan Lao Americans live [19]. Respondents were given food incentives (e.g. rice, fish sauce) that valued $10 for their participation.
Data Collection
We conducted a cross-sectional survey study using a non-random sample. The survey was developed using survey instruments validated in other populations and used among immigrant populations. Through a collaborative editing process, survey questions were discussed and tested for face validity among LACM research staff and two additional Lao speakers. The survey questions were edited and translated to Lao, and back-translated to English to create the pilot version of the survey, which was printed in both Lao and English [20]. Inconsistency was discussed among the three bilingual researchers to avoid misleading items and to reach the culturally accurate meaning of each item. After piloting 10 surveys, the study team, including LACM research staff, discussed issues that they noted regarding respondent interpretation of survey questions and question clarity. The survey was then edited to its final version which was used throughout the remainder of the study.
Paper surveys were administered in a private space at the LACM. LACM staff trained in research methods and ethics consented participants and offered support to answer questions and to help the participant complete the survey verbally if preferred. Survey responses were entered into a secure web-based database. Survey protocol and all procedures related to the survey were reviewed and approved by the University of Minnesota Institutional Review Board.
Measures
CRC Screening Outcome
The CRC screening outcome was defined as the proportion of respondents who had ever undergone CRC screening. Participants were asked in three yes/no questions whether they had ever taken an FOBT or a fecal immunohistochemical test (FIT), or had a colonoscopy or sigmoidoscopy.
Predisposing Factors
We measured eight predisposing factors in this study including the demographic characteristics of age, gender, marital status, level of education, employment status, and number of years lived in the U.S. We also measured fatalism, and English fluency. Our fatalism measure was one adopted previously by authors who assessed culturally relevant health beliefs among Chinese and Southeastern Asian immigrant populations [10] and consisted of a validated construct [21] that was assessed through two questions asking whether or not the participant agreed on a four-point scale (strongly disagree to strongly agree). The questions were, “Getting cancer is my fate so there is nothing I can do about it,” and, “There’s not much people can do to lower their chances of getting cancer.” Responses were dichotomized for analysis. English fluency was a self-assessment from a single question (“Since you speak a language other than English, we are interested in your own opinion of how well you speak English. Would you say that you speak English:”) with four response options ranging from “Very well,” to “Not at all.” These were dichotomized into “well” and “not well” for analyses.
Enabling Resources
We measured five enabling resources. These included two demographic questions: insurance status and type, and income. We also asked about having a primary care provider, and family support and self-efficacy related to screening. Having a primary care provider was assessed using the yes/no question, “Do you have a primary physician?”. We used the summary score from a previously validated three-item scale to measure family support [22]. Family support questions were measured on a four-item response scale from “strongly disagree” to “strongly agree,” and included, “My family or adult children have recommended that I get checked for cancer,” “My family or friends have advised me about the importance of getting checked for cancer,” and “I rely on my family to advise me about health matters.” Self- efficacy was calculated as a summary score created from four yes/no questions about whether the respondent felt confident to: (1) Discuss CRC screening with provider, (2) Schedule and keep a CRC screening appointment, (3) request a referral for CRC screening from a primary provider, and (4) Get CRC screening even if you had to pay for it. The self-efficacy measure had a Cronbach’s alpha of 0.89, indicating that the items in the score are closely related and consistent. All summary scores were calculated and used only if none of the individual scores was missing.
Perceived Need
We measured three need-for-care factors: family history of cancer, knowledge about CRC screening, and number of chronic conditions. We measured family history of cancer through a yes/no question, “Have any of your family members (only your blood relatives, including half brothers and sisters) ever had cancer of any kind?” Knowledge about CRC screening was assessed through the yes/no question, “Should men and women begin screening for colorectal cancer at age 50?” To measure number of chronic conditions, participants indicated whether they had experienced (yes/no/not sure) any of 12 common medical conditions in the past 12 months. They also had the option of including a condition in an additional “other” category. Total “yes” responses were summed into the number of chronic illnesses. All factors are outlined in Table 1.
Table 1.
Patient measures used
| Predisposing Characteristics | Enabling resources | Perceived need | |
|---|---|---|---|
| Age | Education | Insurance coverage | Family history of cancer |
| Sex | English fluency | Income | Screening knowledge |
| Marital status | Years in U.S. | Having a primary care provider | Number of chronic diseases |
| Employment | Fatalism | Family support | |
| Self-efficacya | |||
Self-efficacy measure: 4-question summary score. Cronbach’s alpha = 0.89
Analysis
We used descriptive statistics (frequencies and percentages, or mean and standard deviations, as appropriate) to describe our sample. We defined the rate of ever receiving CRC screening as the average of “yes” responses to any CRC screening type: FOTB, FIT, colonoscopy, or sigmoidoscopy. For comparison of subjects who ever had CRC screening and who never had, a p value was calculated from two-sample t-test or Fisher’s exact test. Cronbach’s alpha was calculated for self-efficacy to assess internal consistency.
We used step-wise logistic regression to investigate the associations between ever having CRC screening and its associated risk factors, using only the variables with p-values ≤ 0.05 from the two-sample t-tests or Fisher’s exact tests (described above) as the risk factor variables in the regression models. Each risk factor was examined individually in univariate regressions with adjustment for age, sex, education, and years in the U.S., and then added together into multivariate regression models to evaluate whether the association between each factor and ever being screened was independent of other factors. All analyses were carried out using the SAS system (v. 9.3; SAS Institute, Cary, NC, USA). P-values were two-sided, and ≤0.05 was considered statistically significant. Goodness-of-fit statistics, i.e. global Chi square, and generalized R-square from SAS LOGISTIC procedure were reported for the final model. The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.
Results
Participant Sociodemographic Characteristics
One hundred eighteen participants age 50 and above completed surveys. Table 2 shows participant characteristics. The mean age of the cohort was 60.8 years (SD 8.3) and 50% were female. Only 45% (53/118) reported ever receiving CRC screening. Those who had ever been screened were older (62.7 vs. 59.2 years), but otherwise did not differ from those never screened by other predisposing characteristics (gender, marital status, years in the U.S., education, employment, fatalism, and English fluency). Those ever screened more often had a primary care provider (92% vs. 59%), greater self-efficacy, more chronic conditions (2.6 vs. 0.9), and knowledge about who should be screened for CRC (85% vs. 66%). They otherwise did not differ from those never screened by the remaining enabling resources (income, insurance coverage, and social support) or by perceived need (family history of cancer).
Table 2.
Survey respondent demographics for those ≥ 50 years of age, total and by colorectal cancer screening status
| Variable | Total (n = 118) |
Ever screened? | |
|---|---|---|---|
| Yes (n = 53) | No (n = 65) | ||
| Age,a mean (± SD) | 60.8 + 8.3 | 62.7 ± 8.7 | 59.2 ± 7.8 |
| Female gender, n (%) | 58 (50) | 28 (54) | 30 (48) |
| Years in the U.S., mean ± SD | 30.1 + 6.3 | 31.2 ± 4.9 | 29.2 ± 7.3 |
| Education, n (%) | |||
| No schooling | 23 (20) | 13 (25) | 10 (16) |
| Did not complete high school | 60 (52) | 22 (42) | 38 (60) |
| Graduated high school or higher | 33 (28) | 18 (34) | 15 (24) |
| Employed, n (%) | 40 (37) | 17 (34) | 23 (39) |
| Total monthly household income, n (%) | |||
| Under $999 | 56 (49) | 24 (46) | 32 (52) |
| $1000-$2999 | 37 (32) | 21 (40) | 16 (26) |
| $3000 or more | 21 (18) | 7 (13) | 14 (23) |
| Medically insured, n (%) | 100 (86) | 46 (88) | 54 (84) |
| Insurance type, n(%) | |||
| Medicare or medicaid | 67 (58) | 34 (65) | 33 (52) |
| Commercial | 32 (28) | 12 (23) | 20 (32) |
| Marital status, n (%) | |||
| Single | 53 (46) | 27 (51) | 26 (42) |
| Married or partnered | 62 (54) | 26 (49) | 36 (58) |
| English fluency, n (%) | |||
| Well | 40 (35) | 16 (31) | 24 (38) |
| Not well | 75 (65) | 36 (69) | 39 (62) |
| Fatalism, n (%) | 36 (31) | 16 (30) | 20 (32) |
| Identifies a primary physician,a n (%) | 86 (74) | 49 (92) | 37 (59) |
| Family history of cancer, n (%) | 17 (15) | 10 (19) | 7 (11) |
| Number chronic illnesses,a mean ± SD | 1.7 + 2.1 | 2.6 ± 2.3 | 0.9 ± 1.6 |
| Self-efficacy score,a,b mean ± SD | 2.2 + 1.7 | 2.8 ± 1.5 | 1.7 ± 1.8 |
| Screening knowledge,a n (%) | 85 (75) | 44 (85) | 41 (66) |
Statistical significance (p < 0.05) between the two groups
Self-efficacy score is the summary score of 4 yes/no questions about whether the respondent felt confident to: (1) discuss screening with provider, (2) schedule screening, (3) request a referral for screening, and (4) pay for screening if needed
Multivariate Logistic Regression Analysis
Using the above risk factors found to differ significantly between those ever screened and those never screened, we conducted regression analyses adjusted for age, sex, education, and years in the US. The enabling resources associated with ever being screened included having a primary care provider (OR 13.2 [CI 3.2, 54.1]) and having higher self-efficacy in pursuing screening (OR 1.5 [CI 1.1, 2.0]). Perceived needs associated with ever being screened included knowledge of screening age (OR 3.2 [CI 1.1, 9.3]) and having a higher number of chronic illnesses (OR 2.0 [CI 1.4, 2.7]). When having a primary care provider, self-efficacy score, and knowledge of screening age were added into a multivariate logistic regression model, having a primary care provider and higher self-efficacy were still associated with screening independent of other factors. However, after adding into the model the number of chronic illnesses, only primary care provider was still significant such that the odds of ever being screened for CRC was 12.4 times higher for those with a primary care provider compared to those without (p = 0.045, [CI 1.1, 145.9]). For this model, the proportion of the total variability of ever being screened that was accounted for by the model was 0.36 (R-square statistic), and the included variables improved the fit of the model (Wald Chi square = 18.2, p = 0.03). Analyses are summarized in Table 3.
Table 3.
Association between risk factors and ever being screened for CRC
| Risk factor | Comparison | OR (95% CI) | ||
|---|---|---|---|---|
| Univariate models | Model 1 | Model 2 | ||
| Primary physician | Yes vs. no | 13.15 (3.20, 54.05) | 11.51 (2.05, 64.54) | 12.42 (1.06, 145.9) |
| Self-efficacy score | One-unit incr. | 1.52 (1.14, 2.03) | 1.44 (1.03, 2.00) | 1.30 (0.92, 1.85) |
| Screening knowledge | Yes vs. no | 3.18 (1.09, 9.29) | 3.12 (0.68, 14.30) | 3.26 (0.59, 17.91) |
| No. chronic illnesses | One increase | 1.95 (1.40, 2.73) | 1.44 (0.94, 2.18) | |
Univariate models: univariate regressions. Each factor was examined individually in separate models. N = 108 for primary physician; N = 91 for self-efficacy score; N = 105 for screening knowledge; N = 107 for No. Chronic Illnesses
Model 1: multivariate regression. The first three listed factors (primary physician, self-efficacy score, screening knowledge) were examined together in the model. N = 88
Model 2: multivariate regression. Number of chronic illnesses was added to Model 2. N = 86
All models were adjusted for age, sex, education, and years in US
Discussion
This study provides an analysis of CRC screening behavior among Lao-Americans using the revised behavioral model for vulnerable populations. These results reinforce that Lao-Americans in the Minneapolis-St Paul metropolitan area have lower CRC screening rates than the state-wide average of 73% [16]. This is consistent with prior studies demonstrating that immigrant Asian populations have lower rates of colorectal cancer screening compared to NHWs [10, 23–27]. Our rate of 45% is lower than for Laotian-speaking Minnesotans (59%) [16], which may reflect socioeconomic influences. For example, in Minnesota, the CRC screening rate is only 55% for those with less than high school education [28].
Our study showed that Lao-Americans in Minnesota were much more likely to have been screened for CRC if they identified as having a primary care provider. Routinely visiting a doctor is a significant predictor of CRC screening among Asian-Americans [5, 9, 27, 29]. Does this mean that establishing care with a primary care provider is the only way to increase screening? Not necessarily. Recent studies have demonstrated increased cancer screening among Asian-American immigrants after community-based lay health worker programs delivering culturally tailored education [30, 31], including one focused on CRC screening among Hmong-Americans [32]. However, our finding could indicate that discussion of screening with a provider and other provider-focused elements could augment the efficacy of future interventions.
Self-efficacy was also an important factor associated with increased likelihood to have been screened for CRC. Self-efficacy, or one’s belief in one’s ability to succeed in specific situations or accomplish a task [33, 34], has been linked previously to successful completion of cancer screening [35, 36], though one review found its association inconsistent across studies [37]. “Self-efficacy” is a multifaceted, global concept. Applied to CRC screening, “self-efficacy” requires healthcare access either through health insurance or through Minnesota’s free Sage cancer screening program, which provides age-appropriate adults with no or inadequate insurance and who meet low-income criteria with free screening [38]. That 75% of the sample thought that people should be screened for CRC but only 45% had ever been screened suggests that limited access may be an important contributor. Screening also mandates an ability to navigate the health-care system, understand instructions in either preparation for endoscopy or proper stool collection for FOBT/FIT, and transportation to and from lab facilities or an endoscopy center. One could see that self-efficacy in an immigrant would be influenced by many things including insurance access, knowledge of free cancer screening programs, acculturation, health literacy, social support, and either English fluency or access to reliable translation. None of these measures in our study (insurance, number of years in the U.S., knowledge of CRC screening, social support, English fluency) were ultimately associated with ever being screened, though our small sample size may mask associations.
The strength of the study lies in the use of a conceptual framework to explore factors influencing CRC screening behavior among Lao Americans. However, limitations of this study include the limited sample size and the restriction of data collection to the Minneapolis-St. Paul metro area and a subsequent sample that is more socially vulnerable than the state average. Our respondent demographics reflect the Lao-American population in Minnesota by number of years in the U.S. (30% have been in the US 21 or more years), but appears to have less English fluency (40% state-wide do not speak English well) [19]; lower educational attainment (40% state-wide attained less than high school, which is lower than Cambodian (41%) and Vietnamese (30%) subgroups); lower median household income ($40,000 state-wide, the lowest among all Asian subgroups, with nearly one in three living below the poverty line); and higher uninsured (7% state-wide uninsured, the lowest among all Asian subgroups) compared to state averages for Lao Americans [14]. This likely reflects our recruitment from the LACM social service agency, and demonstrates that our findings represent a particularly vulnerable group. This could mask some additional important differences between groups and may limit generalizability of the findings. Finally, use of CRC screening was self-reported and may be subject to inaccurate recall, though we attempted to mitigate this bias through including descriptions of FOBT/FIT testing and colonoscopy/sigmoidoscopy.
New Contribution to the Literature
Our study highlights important factors that could potentially improve CRC screening among Lao Americans in Minnesota. Community-based educational interventions should focus education about the need for CRC screening and resources available to pursue it with the aim of promoting screening self-efficacy, as well as work to connect community members with primary care practices. Future research should explore whether community-based education and cancer screening referral resources improve screening rates and mitigate the disparities seen today in the Lao-American population. This research should incorporate consideration of predisposing characteristics, enabling resources, and perceived need to explore correlational factors for CRC screening, identifying which areas provide the largest impact.
Acknowledgements
This study was funded by a University of Minnesota Program in Health Disparities Research pilot grant. Dr. Rogers was supported through the University of Minnesota KL2 Scholars Career Development Program (National Center for Advancing Translational Sciences of the National Institutes of Health, Grants KL2TR002492 and UL1TR002494). The content is solely the responsibility of the authors and does not necessarily represent the official views of the funders. This research is the result of a close partnership between researchers at the University of Minnesota and the staff of the Lao Assistance Center of Minnesota, whose expertise, candid feedback, and hard work made this collaboration possible. We thank Qi Wang from the University of Minnesota CTSI’s Biostatistical Design and Analysis Center (BDAC) for help with verifying final data analyses. To the best of our knowledge, no conflict of interest, financial or other, exists. L. Anderson and L. Zhang participated in this work while an undergraduate student and while working for the CTSI’s BDAC at the University of Minnesota, respectively, but they are no longer affiliated with the institution.
Footnotes
Ethical Approval All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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