Association between cancer screenings uptake and genetic testing for cancer risk among US adults: findings from HINTS 2017–2020

Abstract

Genetic testing for cancer risk is a vital tool for preventive care, yet its association with the uptake of evidence-based cancer screening remains unclear. This study examined the association between cancer-risk genetic testing and cancer screening uptake using data from the Health Information National Trends Survey (2017 and 2020), a nationally representative sample of US adults. We focused on the United States Preventive Services Task Force (USPSTF)-recommended screening tests for colorectal (CRC), breast, and cervical cancers. Multivariable logistic regression models, adjusted for sociodemographic and clinical factors, were used to assess the relationship between cancer screening uptake and cancer-risk genetic testing. The analysis included 6,629 respondents (mean age 48.5 years; 50.7% female; 61.1% non-Hispanic White). Of the respondents, 3.3% had undergone genetic testing for cancer risk. Among eligible populations, screening uptake was 85.2% for Pap tests, 80.8% for mammograms, and 81.3% for CRC. Unadjusted analysis showed a significant association between breast cancer screening and genetic testing (p = 0.005), which lost significance after covariate adjustment. Most respondents who underwent genetic testing received result interpretation assistance from healthcare providers and genetic counselors. Among those who received genetic testing, all respondents who received assistance from genetic counselors were adherent to cancer screening recommendations. Our results suggest that while genetic testing was associated with breast cancer screening in unadjusted analyses, this association was not maintained after adjusting for covariates. No significant associations were found between genetic testing and cervical cancer or CRC screening. Further research using prospective designs is needed to examine the effectiveness of genetic testing in enhancing cancer prevention and screening efforts.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12687-025-00797-0.

Introduction

Cancer remains a significant public health concern as it is the second leading cause of death in the United States (US), resulting in 609,360 deaths in 2022 nationally (Siegel et al. 2023). Cancer screening plays a pivotal role in early detection and intervention, thereby reducing cancer-related deaths and improving overall survival and quality of life (Siu 2016; Bibbins-Domingo et al. 2016; Curry et al. 2018). The US Preventive Services Task Force (USPSTF) and American Cancer Society develop clinical guidelines to enhance screening efforts and curb cancer incidence and mortality (Siu 2016; Bibbins-Domingo et al. 2016; Curry et al. 2018; American Cancer Society 2023). Cancer screening initiatives such as those for colorectal and breast cancer have demonstrated significant reductions in cancer mortality and adverse clinical outcomes (Bibbins-Domingo et al. 2016; Lin and Gostin 2016). However, the current screening rates fall short of the Healthy People 2030 targets, (U.S. Department of Health and Human Services 2023) with significant disparities among subgroups (Xie et al. 2023; Bauer et al. 2022; Liu et al. 2021; Benavidez et al. 2021). There is a pressing need for increased public health initiatives and research to improve cancer screening uptake in the population at risk and to reduce disparities in cancer outcomes (Liu et al. 2021; Benavidez et al. 2021).

Genetic testing for cancer risk is an underutilized tool in cancer prevention and screening (Whitaker et al. 2021; Alkhatib et al. 2024; Hong et al. 2024; Yadav and Couch 2019). BRCA1/2-related Breast and Ovarian Cancer (HBOC) syndrome and Lynch syndrome are the most common hereditary cancer syndromes, contributing to increased risk for breast, colorectal, and other cancers (e.g., endometrial, pancreatic cancers) (Mars et al. 2024; Imyanitov et al. 2023). These syndromes, which involve multiple genes and numerous possible mutations, are part of a broader spectrum of inherited cancer risk factors, with prevalence rates varying across populations (Mars et al. 2024; Imyanitov et al. 2023; Obeagu and Obeagu 2024). While these hereditary conditions are relatively rare, they contribute to a significant proportion of cancer cases in the population (Imyanitov et al. 2023; Obeagu and Obeagu 2024). The availability of genetic testing for inherited mutations provides individuals with valuable information on their risk, particularly concerning hereditary cancers of the breast, ovaries, and colorectal origins (Whitaker et al. 2021; Yadav and Couch 2019; Mars et al. 2024). Integrating genetic counseling into the cancer prevention agenda is of paramount importance to enhance cancer risk assessment in the population (U.S. Department of Health and Human Services 2023).

This study aims to address two primary research questions: (1) Does undergoing genetic testing for cancer risk influence an individual's adherence to recommended cancer screening guidelines for breast, cervical, and colorectal cancers? (2) How does assistance in interpreting genetic test results affect cancer screening uptake?

The relationship between genetic testing and screening behaviors is complex and likely mediated by multiple factors, including individual risk perception. While the Health Belief Model suggests that increased perceived susceptibility to a health threat (such as cancer) should motivate preventive behaviors, (Glanz et al. 2008) existing evidence indicates a more nuanced relationship (Ferrer and Klein 2015; Peterson et al. 2018; Mittendorf et al. 2021; Laza et al. 2022). For those receiving genetic testing, the impact on screening behaviors may vary based on test results—a positive result might increase perceived risk and motivate enhanced screening adherence, while a negative result could potentially reduce perceived susceptibility and affect future screening patterns (Mars et al. 2024; Ferrer and Klein 2015; Laza et al. 2022; Johnson et al. 2002). Additionally, individuals who pursue genetic testing may already have heightened health awareness and different baseline risk perceptions that influence both their decision to undergo testing and their screening behaviors (Ferrer and Klein 2015; Peterson et al. 2018). Understanding this bidirectional relationship is crucial as healthcare systems work to integrate genetic risk assessment into preventive care strategies.

Previous studies have shown that genetic counseling and testing can improve adherence to recommended cancer screening through mechanisms raising awareness of risk and perceived susceptibility to cancer, particularly in individuals with positive genetic test results (Ferrer and Klein 2015; Peterson et al. 2018). However, synthesized evidence suggests that despite the potential benefits, genetic counseling for hereditary cancer syndromes does not consistently translate into increased protective health behaviors, such as screening services (Mittendorf et al. 2021; Laza et al. 2022). A recent international review of personalized breast cancer screening programs utilizing genetic risk assessment found mixed behavioral responses, with some women's screening behaviors remaining unchanged or even counterintuitive to their assessed risk level (Laza et al. 2022). Various barriers may explain these inconsistent findings, including inadequate clinical communication, low health literacy, financial constraints, geographical disparities, and inequitable access to healthcare services (Alkhatib et al. 2024; Hong et al. 2024; Mittendorf et al. 2021). These conflicting results underscore the need for further exploration to elucidate the complex interplay between genetic testing, risk perception, and subsequent protective health behaviors, such as adhering to recommended screening guidelines.

We know of no studies that have explored the relationship between genetic testing for inherited cancer risk and cancer screening uptake among US adults who meet age-specific USPSTF screening guidelines. Identifying cancer risk is important to tailoring clinical recommendations and improving patient outcomes (U.S. Department of Health and Human Services 2023; Yadav and Couch 2019; Cragun and Pal 2013). As precision medicine continues to shape cancer prevention strategies, it becomes imperative to comprehend the extent to which genetic testing can facilitate early detection of the most common hereditary cancers at the population level (Yadav and Couch 2019; Rulten et al. 2023). Therefore, we conducted an exploratory investigation using a nationally representative sample to examine whether the uptake of cancer screening for breast, cervical, and colorectal cancers varies by cancer genetic testing history. Additionally, we examined whether individuals received assistance with interpreting the results of their genetic test (e.g., assistance from a healthcare provider) and whether assistance was associated with cancer screening uptake. The findings from this study will contribute to a better understanding of the potential impact of genetic testing on the uptake of cancer screening behavior, which is an important mechanism for early detection and treatment, thereby informing the development of targeted interventions to enhance cancer prevention and early detection efforts.

Methods

Data and study population

This study utilized data from two cycles of the Health Information National Trends Survey (HINTS 5) conducted in 2017 (Cycle 1) and 2020 (Cycle 4) (National Cancer Institute 2020). HINTS is a national health communication monitoring program that employs a multistage probability sampling technique to select a representative sample of the noninstitutionalized civilian US population across all 50 states in the U.S. Web-based interviews were conducted to capture data on a wide range of health communication behaviors and attitudes (National Cancer Institute 2020). Detailed information on data sampling and survey instruments is available at http://hints.cancer.gov. The study sample consisted of adults aged 18 years and older who had complete data on cancer genetic testing utilization (n = 6,629). Respondents under 18 and those with missing data on cancer genetic testing were excluded from the analyses. For each cancer screening, we limited the sample to respondents within the age range recommended by the USPSTF who reported no prior diagnosis of that cancer (Siu 2016; Bibbins-Domingo et al. 2016; Curry et al. 2018). A flow chart of sample selection is provided in Fig. 1. Participants were questioned about their experience with cancer genetic tests, cancer screening behaviors, chronic conditions, and socio-demographic characteristics. The University of Florida institutional review board review granted an exemption for this secondary data analysis as it involved the use of publicly available and de-identified data sets. The study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines to ensure clarity and quality in reporting the survey's results (von Elm et al. 2008).

Fig. 1.

Sample Selection Flowchart

Study variables

Cancer genetic test

Cancer genetic testing aims to identify gene mutations that elevate the risk for certain cancers. We categorized respondents'cancer genetic testing status using HINTS question, "Have you ever had any of the following types of genetic tests?" Those who selected "High-risk cancer testing (for example, BRCA1/2 or Lynch Syndrome)" were classified as having had clinical cancer genetic testing, not including those who underwent ancestry testing to determine their geographic or ethnic ancestry (e.g., Ancestry.com or 23andMe). Among respondents who reported having genetic test, HINTS also asked "If you had a genetic test, who helped you understand the results?" Respondents could select healthcare professionals, genetic counselors, family/friend (spouse, parents, siblings, children, friends), other, or not shared with anyone (none). These categories were not mutually exclusive, as respondents could report receiving assistance from multiple sources.

Cancer screenings

Data on the uptake of screening tests for cervical and breast cancers were available in both HINTS survey cycles (2017 and 2020). Females were asked about their utilization of Pap tests for cervical cancer screening and mammograms for breast cancer screening, including the timing of their most recent screenings. Colorectal cancer (CRC) screening, data were only available in 2020. The survey asked respondents whether they had ever undergone any colorectal cancer screening test, including colonoscopy, sigmoidoscopy, or stool blood test, without distinguishing between these modalities. While BRCA1/2 and Lynch syndrome represent well-defined hereditary syndromes for breast and colorectal cancers, cervical cancer involves interactions between genetic factors such as immune response and DNA repair genes and HPV infection. We included cervical cancer screening to examine whether genetic testing uptake might indicate broader preventive health behaviors. Screening adherence (up-to-date status) was determined based on recommendations from the USPSTF (Siu 2016; Bibbins-Domingo et al. 2016; Curry et al. 2018). For females aged 21–65 years without prior cervical cancer, Pap tests are recommended every three years for those aged 21–29, and every five years for those aged 30–65 (Curry et al. 2018). Mammograms are recommended every 2 years for females aged 50–74 without prior breast cancer (Siu 2016). For CRC screening, both males and females aged 50–75 with no history of CRC who reported having had any screening modality were considered adherent (Bibbins-Domingo et al. 2016). For each cancer screening type, we limited our analysis to respondents within the USPSTF-recommended age ranges who reported no prior diagnosis of that specific cancer.

Other characteristics

Socio-demographic and health-related data were collected for analysis. Age was categorized into five groups: 18–34, 35–49, 50–64, 65–74, and 75 + years. Sex was recorded as male or female. Race and ethnicity were classified as non-Hispanic White, non-Hispanic Black, Hispanic, and non-Hispanic other (including American Indian, Alaskan Native, Asian, Pacific Islander, and multiracial). Educational attainment was grouped into high school or less, some college, and college graduate or higher. Household income was divided into three brackets: < $50,000, $50,000-$99,999, and > $100,000. Marital status was categorized as married/living with partner, divorced/widowed/separated, or single. Health insurance types were recorded as private, public, or uninsured. Self-reported chronic conditions (diabetes, high blood pressure, heart condition, and lung disease) were documented as binary (yes/no) variables. Family cancer history was also recorded as a binary variable. The urban/rural classification of respondents'residential areas was noted as metro or non-metro. All variables were treated as categorical in the analysis.

Statistical analysis

Descriptive statistics were presented for respondent characteristics of the overall sample and separately for each HINTS survey cycle. Bivariate associations between the uptake of cancer genetic tests and the three cancer screening tests (cervical, breast, and colorectal cancers) were analyzed with p-values derived from Chi-square. Multivariable logistic regressions were conducted to examine the association between the uptake of a cancer genetic test and each cancer screening behavior adjusting for the covariates described above. The model equation is follows:

$$logit\left(\pi ,\left(x\right)\right)=log\left(\frac{\pi \left(x\right)}{1-\pi \left(x\right)}\right)={\beta }_0+{\beta }_{1}GeneticTesting+{\beta }_2{\mathit{Covariate}}_1+{\beta }_3{\mathit{Covariate}}_2\cdots +{\beta }_k{\mathit{Covariate}}_n$$

Where π(x) is the probability of the cancer screening uptake (outcome variable). GeneticTesting is a binary predictor variable indicating whether the individual underwent cancer genetic testing (1) or not (0). Covariate₁, Covariate₂, …, and Covariate_n are the additional covariates or control variables that were adjusted for in the analysis (e.g., age, sex, socioeconomic status) (Peng and So 2002). All covariates were categorical, with specifications described above in Other characteristics section. We carried out a secondary analysis to determine the sources of assistance used to understand the results, stratified by cancer screening uptake history. All estimates were generated using jackknife replication weights as per HINTS analytic guidelines, which accounted for potential non-response biases and generated nationally representative estimates. Statistical analyses were carried out using Stata 17.0 (StataCorp, College Station, TX). Results are reported using adjusted odds ratios (OR) and 95% confidence intervals (95% CI).

Results

Our analytic sample included 6,629 respondents (mean age, 48.5 years [standard error, 0.20]; weighted population estimate of 472,963,168 for combined datasets from HINTS 2017 and 2020 data). Table 1 displays the unweighted frequencies and weighted population estimates for the sample by uptake of cancer genetic tests. Overall, 3.3% had undergone genetic testing for cancer risk (3.1% in 2017 and 3.5% in 2020). The overall sample consisted of group that was 51% female, 61% non-Hispanic White, 69% with an education level beyond high school, and 62% with an annual household income exceeding $50,000. Notably, 69% of the respondents reported a family history of cancer, and 85% resided in metropolitan areas. In the bivariate analysis, higher uptake rates of cancer genetic testing were observed among females, non-Hispanic whites, those with higher education levels, higher household incomes, private health insurance, and a family history of cancer. No significant differences in uptake rates were found for age, marital status, smoking status, chronic conditions, or rural–urban designation (Table 1).

Table 1.

Respondents Characteristics

	Total	Had Cancer Genetic Test	Never Had Cancer Genetic Test	p-value
Characteristics	n	n (weighted %)	n (weighted %)
Total, n	6629	248 (3.3)	6381 (96.7)
Age				0.400
18–34	841 (24.6)	28 (22.9)	813 (24.6)
35–49	1331 (27.3)	53 (27.5)	1278 (27.3)
50–64	2143 (28.9)	92 (32.8)	2051 (28.8)
65–74	1464 (11.2)	48 (10.6)	1416 (11.3)
75 +	850 (7.9)	27 (6.2)	823 (8.0)
Sex				< .001
Male	2710 (48.8)	51 (26.3)	2659 (49.5)
Female	3873 (50.7)	196 (73.3)	3677 (49.9)
Race/ethnicity				0.010
Non-Hispanic White	3829 (61.1)	166 (72.2)	3663 (60.7)
Non-Hispanic Black	835 (10.0)	22 (10.0)	813 (10.0)
Hispanic	957 (15.1)	23 (6.4)	934 (15.4)
Non-Hispanic Other	1008 (13.8)	37 (11.4)	971 (13.9)
Education				0.012
High school or less	1653 (30.1)	45 (23.3)	1608 (30.3)
Some college	1916 (35.6)	69 (36.4)	1847 (35.6)
College graduate or higher	2954 (33.2)	131 (40.0)	2823 (33.0)
Household Income (US$)				0.007
< 50,000	2669 (37.9)	85 (31.4)	2584 (38.1)
50,000–99,999	1820 (29.1)	64 (33.0)	1756 (29.0)
> 100,000	1565 (25.7)	79 (30.4)	1486 (25.5)
Marital Status				0.341
Married/living with partner	3560 (54.4)	137 (63.3)	3423 (54.1)
Divorced/widowed/separated	1852 (13.9)	74 (15.9)	1778 (13.8)
Never married	1102 (30.3)	33 (20.2)	1069 (30.7)
Health Insurance Type				0.007
Private	2924 (50.5)	131 (56.8)	2793 (50.2)
Public	3311 (39.8)	110 (33.1)	3201 (40.1)
Uninsured	268 (7.1)	< 10 (9.7)	264 (7.0)
Current Smoker				0.374
Yes	787 (14.2)	25 (14.5)	762 (14.2)
No	5788 (85.1)	221 (84.7)	5567 (85.1)
Diabetes				0.080
Yes	1351 (17.0)	40 (14.3)	1311 (17.1)
No	5200 (82.1)	207 (85.6)	4993 (82.0)
High Blood Pressure				0.432
Yes	2907 (35.7)	103 (33.5)	2804 (35.8)
No	3653 (63.4)	143 (66.1)	3510 (63.3)
Heart Condition				0.382
Yes	664 (7.6)	21 (9.0)	643 (7.5)
No	5905 (91.8)	227 (91.0)	5678 (91.8)
Lung Disease				0.511
Yes	917 (12.0)	31 (10.3)	886 (12.1)
No	5645 (87.1)	216 (89.5)	5429 (87.0)
Family History of Cancer				< .001
Yes	4705 (68.7)	209 (87.0)	4496 (68.1)
No	1411 (23.3)	26 (10.2)	1385 (23.8)
Rural–Urban Designation				0.742
Metro	5727 (85.4)	216 (84.2)	5511 (85.4)
Micropolitan/small town/rural area	902 (14.6)	32 (15.8)	870 (14.6)

Sample sizes for all subgroups do not equal to total sample size except for age and race/ethnicity because of missing data. p-values are results from the chi-square test for all variables except for health insurance, where Fisher's exact test was used due to a small sample size

Table 2 presents the unadjusted prevalence of cancer screening uptake in the eligible population and its bivariate association with cancer genetic testing utilization. In the eligible population, 85.2% (95% CI: 82.9–87.2) of females aged 21–65 had undergone a Pap test for cervical cancer screening within the recommended time frame. For mammogram uptake, the prevalence was 80.8% (95% CI: 77.9–83.4) among females aged 50–74. Among both males and females aged 50–75, the prevalence of colorectal cancer screening uptake was 81.3% (95% CI: 78.3–84.0). Notably, without adjusting for other variables, a significant association was observed only between mammogram uptake and previous use of cancer genetic tests (p = 0.005).

Table 2.

Bivariate association between cancer genetic tests and cancer screening uptake among eligible population in the U.S

	Had Cancer Genetic Test
	Total Weighted % (95 CI)	Yes Weighted % (95 CI)	No Weighted % (95 CI)	p-valued
Pap test (n = 2,547)a				0.118
Yes	85.2 (82.9–87.2)	92.5 (80.8–97.3)	84.9 (82.6–86.9)
No	14.8 (12.8–17.1)	7.5 (2.7–19.2)	15.1 (13.1–17.4)
Mammogram (n = 1,855)b				0.005
Yes	80.8 (77.9–83.4)	93.6 (82.3–97.9)	80.5 (77.5–83.2)
No	19.2 (16.6–22.2)	6.4 (2.13–17.7)	19.5 (16.8–22.5)
Colorectal cancer tests (n = 1,903)c				0.612
Yes	81.3 (78.3–84.0)	85.1 (63.1–95.0)	81.1 (78.2–83.8)
No	18.7 (16.0–21.8)	14.9 (5.0–36.9)	18.9 (16.3–21.9)

^a Eligible population: females aged 21–65 years old and had no cervical cancer. Yes: aged 21–29 had pap test within three years; aged 30–65 had pap test within five years

^b Eligible population: females who aged 50–74 years old and had no breast cancer. Yes: Had mammogram within two years

^c Eligible population: males and females aged 50–75 years old and had no colorectal cancer. Yes: Ever had a colonoscopy, a sigmoidoscopy, or a stool blood test. Data on colorectal cancer tests are only available in HINTS 5 Cycle 4

^d Of Chi-Square tests

Upon adjusting for respondent characteristics, the association between cancer genetic testing and cancer screenings became non-significant (Table 3). Among the Pap test-eligible population, those who were never married (Odds Ratio [OR]: 0.53, 95% CI: 0.31–0.89) and uninsured (OR: 0.38, 95% CI: 0.16–0.87) were less likely to undergo screening within the recommended time frame. Among the mammogram-eligible population, Hispanic individuals (OR: 6.56, 95% CI: 2.12–20.23) and those with a college degree (OR: 2.06, 95% CI: 1.08–3.96) were more likely to be screened, while uninsured individuals were less likely. Among the eligible population for colorectal cancer screening, non-Hispanic Blacks were more likely to be screened (OR: 2.19, 95% CI: 1.17–4.10), while current smokers were less likely (OR: 0.46, 95% CI: 0.25–0.83).

Table 3.

Multivariable adjusted regression models for cervical, breast and colorectal cancer screenings

	Pap Testa	Mammogramb	Tests for colorectal cancerc
	OR (95% CI)	OR (95% CI)	OR (95% CI)
Ever Had Cancer Genetic Tests
No	[Reference]	[Reference]	[Reference]
Yes	2.13 (0.34–13.21)	3.06 (0.59–15.79)	1.50 (0.22–10.50)
Age
18–34	[Reference]	-	-
35–49	1.35 (0.76–2.41)	-	-
50–65	0.75 (0.44–1.26)	[Reference]	[Reference]
66–75		1.05 (0.57–1.94)	2.25 (0.98–5.14)
Sex
Male	-	-	[Reference]
Female	-	-	1.15 (0.67–1.98)
Race/ethnicity
Non-Hispanic White	[Reference]	[Reference]	[Reference]
Non-Hispanic Black	1.47 (0.68–3.21)	2.11 (0.88–5.10)	2.19 (1.17–4.10)
Hispanic	0.94 (0.47–1.90)	6.56 (2.12–20.23)	0.83 (0.43–1.61)
Non-Hispanic Other	0.75 (0.37–1.54)	1.34 (0.52–3.44)	2.25 (1.00–5.07)
Education
High school or less	[Reference]	[Reference]	[Reference]
Some college	0.81 (0.45–1.45)	1.16 (0.69–1.94)	1.35 (0.82–2.21)
College graduate or above	1.76 (0.88–3.49)	2.06 (1.08–3.96)	1.30 (0.70–2.43)
Household Income (US$)
< 50,000	[Reference]	[Reference]	[Reference]
50,000–99,999	0.93 (0.50–1.72)	1.39 (0.73–2.62)	1.65 (0.78–3.49)
> 100,000	1.50 (0.69–3.28)	1.67 (0.76–3.69)	1.64 (0.50–5.44)
Marital Status
Married/living with partner	[Reference]	[Reference]	[Reference]
Divorced/Widowed/Separated	0.99 (0.59–1.67)	1.06 (0.63–1.76)	0.69 (0.37–1.29)
Never married	0.53 (0.31–0.89)	0.83 (0.42–1.67)	1.05 (0.35–3.13)
Health Insurance Type
Private	[Reference]	[Reference]	[Reference]
Public	0.80 (0.44–1.45)	1.04 (0.57–1.90)	1.37 (0.64–2.94)
Uninsured	0.38 (0.16–0.87)	0.13 (0.05–0.36)	0.54 (0.18–1.65)
Current Smoker
No	[Reference]	[Reference]	[Reference]
Yes	0.89 (0.53–1.47)	0.70 (0.42–1.17)	0.46 (0.25–0.83)
Diabetes
No	[Reference]	[Reference]	[Reference]
Yes	1.11 (0.60–2.05)	1.41 (0.83–2.41)	1.34 (0.71–2.54)
Hypertension
No	[Reference]	[Reference]	[Reference]
Yes	1.18 (0.75–1.87)	1.25 (0.80–1.96)	1.47 (0.91–2.38)
Heart Disease
No	[Reference]	[Reference]	[Reference]
Yes	0.48 (0.20–1.18)	0.76 (0.33–1.78)	0.88 (0.25–3.10)
Lung Disease
No	[Reference]	[Reference]	[Reference]
Yes	1.01 (0.61–1.69)	1.35 (0.60–3.04)	1.47 (0.74–2.93)
Family History of Cancer
No	[Reference]	[Reference]	[Reference]
Yes	0.90 (0.52–1.59)	1.12 (0.67–1.85)	1.49 (0.78–2.86)
Rural–Urban Designation
Metro	[Reference]	[Reference]	[Reference]
Micropolitan	0.99 (0.49–2.01)	1.64 (0.73–3.69)	1.06 (0.43–2.62)
Small Town	1.07 (0.30–3.85)	1.23 (0.46–3.27)	2.17 (0.81–5.84)
Rural Area	0.40 (0.11–1.46)	1.53 (0.41–5.70)	1.34 (0.26–7.01)

^a Sample included females aged 21–65 years old and had no cervical cancer in HINTS 5 Cycle 1 and Cycle 4 (n = 2,128)

^b Sample included females aged 50–74 years old and had no breast cancer in HINTS 5 Cycle 1 and Cycle 4 (n = 1,480)

^cSample included males and females aged 50–75 years old and had no colorectal cancer in HINTS 5 Cycle 4 (n = 1,503)

Out of the respondents who took cancer genetic testing (n = 248), 145 respondents provided complete responses on cancer screening and whether they received assistance when understanding the genetic test results (Supplemental Table 1). Among these respondents, help in understanding genetic test results came from multiple sources: 54% of the respondents sought help in understanding the genetic test results from healthcare providers (excluding genetic counselors), 31% from genetic counselors specifically, 11% from family or friends, and 17% received no assistance (Fig. 2). Notably, among those who did not adhere to USPSTF-recommended screenings, none of them received assistance from genetic counselors. Healthcare providers are the primary source of assistance for understanding genetic test results, followed by genetic counselors and family and friends. Respondents who received assistance from a genetic counselor in understanding their genetic test results were more likely to undergo breast cancer screening (p = 0.017). Those who only received assistance from family or friends were more likely to miss the recommended window for breast cancer screening (p = 0.046). Respondents who had no help in understanding the results were less likely to undergo colorectal cancer tests (p = 0.043).

Fig. 2.

Sources of Assistance in Understanding Genetic Test Results by Cancer Screening Uptake^a. ^aIn respondents who had genetic test for higher cancer risk. ^bEligible population: Females aged 21–65 years old and had no history of cervical cancer. ^cEligible population: Females who aged 50–74 years old and had no history of breast cancer. ^dEligible population: Both males and females aged 50–75 and had no history of colorectal cancer

Discussion

In this study, we investigated the relationship between genetic testing for cancer risk and the uptake of cancer screening for breast, cervical, and colorectal cancers. Initially, we observed a significant association between genetic testing and an increased uptake of mammograms for breast cancer. However, this association was no longer significant after adjusting for respondents’ sociodemographic and clinical characteristics. We anticipated that individuals undergoing genetic testing would adhere better to recommended cancer screening guidelines, driven by more accurate risk perception, communication with healthcare providers, and awareness of screening (Rantala et al. 2009). However, our findings did not support this expectation consistently across cancer screening types. The differential patterns observed in our results suggest that the interplay between genetic and environmental/behavioral risk factors may vary across breast, cervical, and colorectal cancers, influencing the relationship between genetic testing and screening behaviors (Xie et al. 2023; Liu et al. 2021; Benavidez et al. 2021; Whitaker et al. 2021; Mars et al. 2024). Additionally, socioeconomic-related disparities, which have been extensively investigated in prior studies, (Peterson et al. 2018; Mittendorf et al. 2021; Laza et al. 2022) could modulate the associations between genetic testing and screening uptake. Overall, our findings contribute to the evolving understanding of the complex relationships between cancer genetic testing and adherence to screening recommendations, highlighting the need for further research to elucidate the underlying mechanisms and potential moderating factors involved.

Understanding the factors that impact cancer screening uptake is crucial for promoting early detection and treatment through adherence to USPSTF guidelines (Xie et al. 2023; Benavidez et al. 2021). One important consideration is insurance coverage and cost-sharing, which can affect access to different types of screening tests (Jennings et al. 2021; Bhandari and Li 2019; Carlos et al. 2019; Hong et al. 2017). While the Affordable Care Act mandates coverage for breast, cervical, and colorectal cancer screenings, there are variations in how different insurance plans implement these requirements (Jennings et al. 2021; Bhandari and Li 2019; Carlos et al. 2019). While genetic testing is a relatively new preventative care approach, it has the potential to play an important role in identifying individuals at increased risk for certain types of cancers (National Cancer Institute 2024; Stadler and Schrag 2023). However, there may be variations in the correlation between cancer screening and genetic cancer testing from one healthcare provider to another due to differences in provider trust and knowledge of the screening process (Plourde et al. 2016; Hamilton et al. 2017). In addition, our finding that being uninsured was associated with lower uptake of cervical and breast cancer screening highlights the importance of insurance coverage in promoting cancer screening (Carlos et al. 2019). Addressing these complex factors is essential to improve cancer screening rates and reduce disparities in cancer outcomes.

An interesting finding from our further analysis was that most respondents who underwent the genetic testing sought help from healthcare providers in understanding test results, followed by genetic counselors and family or friends. Genetic test results can be complex necessitating expert assistance for interpretation (Turbitt et al. 2019). Many individuals may turn to their healthcare providers or genetic counselors for help in interpreting the results. However, some may not seek assistance at all, which could result in missed opportunities for cancer screening and prevention. Furthermore, it has been documented that there may be systematic barriers that prevent individuals from seeking assistance in interpreting genetic test results from healthcare providers. Primary care providers may feel uncomfortable discussing genetic testing results with their patients due to a lack of knowledge (Hamilton et al. 2017; Haga et al. 2019). Therefore, it is crucial for healthcare providers to receive proper training and support to ensure they can effectively communicate and interpret genetic test results for their patients. Collectively, these findings suggest that maintaining communication (e.g., testing follow-ups) with healthcare providers or genetic counselors could improve individuals'comprehension of their health status and their adherence to recommended health interventions (Turbitt et al. 2019; Taylor and Kelner 1996).

Although not the main focus of this study, we noted that the prevalence of cervical and colorectal cancer screening estimated (85.2% and 81.3%) was consistent with the estimates generated from the recent study using population-based data (Barlow et al. 2020; Richardson et al. 2022). However, the prevalence of breast cancer screening (80.8%) was slightly higher than estimated in previous studies using other nationally representative samples (Miller et al. 2022). This difference can be attributed, in part, to the low response rate of the HINTS survey (35%), which notes in its methodology that non-response is negatively correlated with access to care and health status (National Cancer Institute 2023). Surprisingly, despite previous research indicating the opposite historically, (Chlebowski et al. 2005; Goding Sauer et al. 2019) our findings indicated that Hispanic women have relatively higher rates of mammography screenings compared to non-Hispanic White women. Further research is needed to understand if this change was due to effective public health campaigns targeting this ethnic group (Miller et al. 2021). Additionally, our finding that non-Hispanic Blacks are more likely to receive a colorectal cancer screening than non-Hispanic Whites, aligns with the increasing trend in this subgroup since 2015 (Sokale et al. 2023; Tak et al. 2022). It is important to note that as of 2024, the USPSTF recommends beginning colorectal cancer screening at age 45 for average-risk adults (Davidson et al. 2021). For breast cancer, the USPSTF now recommends biennial screening mammography for women aged 40 to 74 years (Nicholson et al. 2024). These guidelines differ from those in place during the study period. Future research in this area should consider these updated recommendations when interpreting or building upon the findings of this study.

To our knowledge, this is the first study to examine the association between the uptake of cancer screening and genetic testing using a US nationally representative sample. Though the study is limited by the unavailability of actual genetic test results, this exploratory study provides initial population-level evidence linking interest in determining cancer risk through genetic testing with increased uptake of recommended cancer screening. Due to the cross-sectional nature of this study, we cannot determine whether genetic testing influences screening behavior, whether both reflect underlying health consciousness and risk perceptions or whether individuals underwent genetic testing due to family history, early-age cancer diagnosis, or other risk factors. Future research should also aim to assess adherence to risk-stratified screening recommendations. That is, many screening guidelines distinguish between general population and people with elevated genetic risk. As examples, colonoscopy rather than stool-based testing is recommended for people at elevated risk for colorectal cancer, and women at high risk for breast cancer are advised to add MRI to mammography. The HINTS data do not allow us to completely eliminate all factors that would influence screening eligibility such as prior hysterectomy (for any reason) and cervical cancer screening. Further research with alternate sources of data will be needed to understand whether individuals with clinical indications for genetic testing actually receive it, how genetic test results and family history jointly influence screening uptake, and how communication patterns about genetic test results affect screening behaviors, particularly among those with family history of cancer or early-age cancer diagnosis (Yadav and Couch 2019; Rulten et al. 2023; Kurian et al. 2023).

While our unadjusted analyses suggested a potential association between genetic testing and breast cancer screening uptake, this relationship was not maintained after adjusting for sociodemographic and clinical factors. This finding aligns with previous literature suggesting a complex relationship between genetic testing uptake and screening behaviors (Alkhatib et al. 2024; Hong et al. 2024; Mittendorf et al. 2021; Laza et al. 2022). It is important to note this study is exploratory in nature, given the data limitations and further investigation is required to tailor recommendations and interventions based on objective genetic risk. Another important limitation is the relatively small HINTS sample size, which impacted statistical power to detect effects and precision of estimates, as reflected by wide confidence intervals. Thus, results should be interpreted as exploratory, and confirmatory analyses with larger samples are needed. Therefore, further research with a prospective design with larger sample sizes and longer follow-up periods is necessary to explore the impact of genetic testing on cancer prevention and screening. Furthermore, the lack of information about the timing of cancer screenings and genetic testing in HINTS makes it impossible to establish a temporal relationship. Further assessments, particularly qualitative research to understand patient’s individual choice in screening and detailed information on family cancer history (e.g., cancer type, age of diagnosis), are necessary to establish any causal relationships.

Conclusions

Our analysis found that while genetic testing appeared to be associated with breast cancer screening in unadjusted analyses, this relationship did not persist after accounting for sociodemographic and clinical factors. No significant associations were observed between genetic testing and cervical or colorectal cancer screening. However, our examination of how individuals obtained assistance in understanding their genetic test results revealed important patterns: healthcare providers were the primary source of assistance, followed by genetic counselors. Notably, among those who underwent genetic testing, all individuals who received assistance from genetic counselors were adherent to screening recommendations, suggesting the potential value of professional guidance in promoting preventive care behaviors.

Our findings underscore the importance of understanding how genetic information and family history can be effectively integrated into regular care to optimize screening and prevention strategies. This integration becomes particularly important as healthcare systems work to identify both individuals with inherited genetic risk and the broader population with family history indicators warranting enhanced screening protocols. Healthcare providers play a crucial role in this integration by helping patients understand their genetic test results and appropriate screening recommendations. While our results suggest the potential value of investing in genetic counseling services and provider education, further research is needed to explore barriers to seeking guidance on genetic test results and to develop strategies that enhance collaborative decision-making between patients and healthcare providers.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

YR.H conceived and designed the study. A.C, R.W, and YR.H wrote the main manuscript text. R.W and YR.H conducted the statistical analyses. YR.H and D.B provided administrative, technical, and material support. All authors contributed to the acquisition, analysis, and interpretation of data, critically revised the manuscript for important intellectual content, and reviewed the final version. YR.H supervised the study.

Funding

This study was partly supported by the UF Health Cancer Center Pilot Grant (#CCPS202103; PI: Hong). The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Competing interests

The authors declare no competing interests.