Community-Based Family Health History Education: The Role of State Health Agencies in Engaging Medically Underserved Populations in Understanding Genomics and Risk of Chronic Disease

Understanding the Process of Family Cancer History Collection and Health Information Seeking

PROBLEM ADDRESSED

To better understand the factors associated with family cancer history (FCH) information and cancer information seeking, we model the process an individual undergoes when assessing whether to gather FCH and seek cancer information and compare models by sociodemographics and family history of cancer. We used cross-sectional data from the Health Information National Trends Survey (HINTS 5, Cycle 2) and variables (e.g., emotion and self-efficacy) associated with the Theory of Motivated Information Management to assess the process of FCH gathering and information seeking. We completed path analysis to assess the process of FCH gathering and stratified path models.

RESULTS

Those who felt they could lower their chances of getting cancer (emotion) were more confident in their ability to complete FCH on a medical form (self-efficacy; B = 0.11, p < .0001) and more likely to have discussed FCH with family members (B = 0.07, p < .0001). Those who were more confident in their ability to complete a summary of their family history on a medical form were more likely to have discussed FCH with family members (B = 0.34, p < .0001) and seek other health information (B = 0.24, p < .0001). Stratified models showed differences in this process by age, race/ethnicity, and family history of cancer.

IMPLICATIONS FOR PUBLIC HEALTH RESEARCH AND PRACTICE

Tailoring outreach and education strategies to address differences in perceived ability to lower chances of getting cancer (emotion) and confidence in the ability to complete FCH (self-efficacy) could help encourage less engaged individuals to learn about their FCH and gather cancer information.

Effects of family history of alcohol problems on alcohol consumption: Stronger for medically underserved men

Family history (FH), informed by genetics and family environment, can be used by practitioners for risk prediction. This study compares the associations of FH with alcohol outcomes for medically underserved (MUS) men and women with the associations for non-underserved individuals to assess the utility of FH as a screening tool for this high-priority group. Data were from 29,993 adult lifetime drinkers in the Wave 1 (2001-2002) and Wave 2 (2004-2005) National Epidemiologic Survey on Alcohol and Related Conditions. All variables except FH were measured at Wave 2. Dependent variables were 12-month alcohol consumption and alcohol use disorder (AUD). FH scores (FH-SCORE) measured the proportion of first- and second-degree biological relatives with alcohol problems. MUS status was defined by household income at or below 100% of the federal poverty line and participants reporting no usual source of health care. Multivariate linear and logistic regression models tested main and interaction effects. Models showed a significant interaction of FH-SCORE with MUS status (p < .01), with a stronger effect of FH on alcohol consumption for the MUS group. This moderating effect was weaker for women than for men (FH-SCORE x MUS x Sex three-way interaction: p < .01). AUD models showed a significant positive association with FH-SCORE (p < .001) but no association with MUS status and no significant interaction effects. In this sample of lifetime drinkers, FH was associated with higher alcohol consumption, especially for MUS men. These results encourage additional validation of FH scores to prioritize MUS adults at high risk for alcohol problems to receive preventive interventions.

The Role of Family Health History in Predicting Midlife Chronic Disease Outcomes

INTRODUCTION

The generational relevance for determining disease risk for the leading causes of morbidity and mortality for U.S. adults is a source of debate.

METHODS

Data on 12,300 adults (Add Health Study Members) participating in Wave V (2016-2018) of the National Longitudinal Study of Adolescent to Adult Health (also known as Add Health) were merged with data from respondents' parents (n=2,013) participating in the Add Health Parent Study (2015-2017). Analyses beginning in January 2020 examined the concordance in lifetime occurrence of chronic conditions across 4 generations, including cardiovascular disease, diabetes, hypertension, hyperlipidemia, obesity, cancer, and depression and examined the associations between individual disease history and ones' family health history for the same condition.

RESULTS

Mean ages were 37.4 years for Add Health Study Members and 62.9 years for Add Health Parent Study mothers. The histories of mothers from the Add Health Parent Study on hyperlipidemia (AOR=1.61, 95% CI=1.04, 2.48), obesity (AOR=1.77, 95% CI=1.27, 2.48), and depression (AOR=1.87, 95% CI=1.19, 2.95) were significantly associated with increased odds of Add Health Study Member report of these conditions. Maternal great grandparent hyperlipidemia history was significantly associated with the Add Health Study Member hyperlipidemia (AOR=2.81, 95% CI=1.51, 5.21). Histories of diabetes in maternal grandfather (AOR=2.41, 95% CI=1.24, 4.69) and maternal great grandparent (AOR=3.05, 95% CI=1.45, 6.43) were significantly associated with Add Health Study Member diabetes. Each additional point in the Add Health Parent Study mothers' cardiometabolic risk factor index was associated with an 11% increase (incidence rate ratio=1.11, 95% CI=1.04, 1.19) in the expected count of cardiometabolic risk conditions for the Add Health Study Members.

CONCLUSIONS

Multigenerational health histories have value for quantifying the probability of diabetes, obesity, depression, and hyperlipidemia in early mid-adulthood. Family health history knowledge is relevant for health promotion and disease prevention strategies.

Family Health History-Based Interventions: A Systematic Review of the Literature

CONTEXT

National efforts have advocated for the need to deliver family health history-based interventions to the lay public for more than a decade. Yet, the numbers, characteristics, and outcomes of such interventions are unknown. This first-of-its-kind systematic literature review examines the characteristics and effectiveness of the existing family health history-based interventions.

EVIDENCE ACQUISITION

The research team systematically searched peer-reviewed articles published between January 2003 and July 2020 in MEDLINE, Embase, CINAHL, and Google Scholar.

EVIDENCE SYNTHESIS

A total of 35 articles met the inclusion criteria. These studies assessed various behaviors, including family health history collection/communication with family members, family health history communication with healthcare providers, healthy diet adoption, physical activity level, uptake of medical screenings and genetic tests, and being proactive in healthcare matters. The average methodologic quality score of the studies was 9.9 (SD=1.6) of a theoretical range from 2 to 16.

CONCLUSIONS

Many family health history-based interventions exist to examine a variety of behaviors. Yet, there is room for improvement in methodology because few studies used a randomized or quasi-experimental design. In addition, most included studies did not report objective or longer-term outcome data to examine the effectiveness of family health history-based interventions.

Implementing Cancer Genomics in State Health Agencies: Mapping Activities to an Implementation Science Outcome Framework

OBJECTIVE

To show how state health agencies can plan and evaluate activities to strengthen the evidence base for public health genomics, we mapped state cancer genomics activities to the Doyle et al. [Genet Med. 2018;20(9):995-1003] implementation science outcome framework.

METHODS

We identified state health agency activities addressing hereditary breast and ovarian cancer and Lynch syndrome by reviewing project narratives from Centers for Disease Control and Prevention Cancer Genomics Program funding recipients, leading discussions with state health agencies, and conducting an environmental scan.

RESULTS

State health agencies' cancer genomics activities included developing or adding to state surveillance systems, developing educational materials, bidirectional reporting, promoting health plan policy change, training providers, and promoting recommendations and standards. To address health disparities, programs have tracked group differences, developed culturally appropriate educational materials, and promoted access to services for underserved populations.

CONCLUSION

State health agencies can use the Doyle et al. [Genet Med. 2018;20(9):995-1003] performance objectives and outcome measures to evaluate proposed and ongoing activities. By demonstrating whether activities result in improved outcomes, state health agencies can build the evidence for the implementation of cancer genomics activities.

The enduring importance of family health history in the era of genomic medicine and risk assessment

Improving disease risk prediction and tailoring preventive interventions to patient risk factors is one of the primary goals of precision medicine. Family health history is the traditional approach to quickly gather genetic and environmental data relevant to the patient. While the utility of family health history is well-documented, its utilization is variable, in part due to lack of patient and provider knowledge and incomplete or inaccurate data. With the advances and reduced costs of sequencing technologies, comprehensive sequencing tests can be performed as a risk assessment tool. We provide an overview of each of these risk assessment approaches, the benefits and limitations and implementation challenges.

Blending Insights from Implementation Science and the Social Sciences to Mitigate Inequities in Screening for Hereditary Cancer Syndromes

Genomic screening to identify people at high risk for adult-onset hereditary conditions has potential to improve population health. However, if not equitably accessible, genomics-informed screening programs will exacerbate existing health inequities or give rise to new ones. To realize the disease prevention potential of these screening tools, we need strategies to broaden their reach. We propose a conceptual framework that merges insights from implementation science and sociological research on health inequities. Our framework does three things: first, it broadens the arenas of action beyond those typically addressed in implementation science frameworks; second, it argues for recruiting more diverse partners to share the work of implementation and dissemination; and third, it shows how implementation activities can be coordinated more effectively among those partners. We use screening for hereditary breast and ovarian cancers (HBOC) as a case to illustrate how this enhanced framework could guide implementation science and distribute the benefits of genomic medicine more equitably. Although our example is specific to genomics, this approach is more broadly applicable to the field of implementation science. Coordinated action among multiple stakeholders could translate a host of new technologies from the bench to the trench without creating new inequities or exacerbating existing ones.

Understanding the potential of state-based public health genomics programs to mitigate disparities in access to clinical genetic services

Purpose

State Health Agencies (SHAs) have developed public health genomics (PHG) programs that play an instrumental role in advancing precision public health, but there is limited research on their approaches. This study examines how PHG programs attempt to mitigate or forestall health disparities and inequities in the utilization of genomic medicine.

Methods

We compared PHG programs in three states: Connecticut, Michigan, and Utah. We analyzed 85 in-depth interviews with SHA internal and external collaborators and program documents. We employed a qualitative coding process to capture themes relating to health disparities and inequities.

Results

Each SHA implemented population-level approaches to identify individuals who carry genetic variants that increase risk of hereditary cancers. However, each SHA developed a unique strategy—which we label public health action repertoires—to reach specific subgroups who faced barriers in accessing genetic services. These strategies varied across states given demographics of the state population, state-level partnerships, and availability of healthcare services.

Conclusion

Our findings illustrate the imperative of tailoring PHG programs to local demographic characteristics and existing community resources. Furthermore, our study highlights how integrating genomics into precision public health will require multilevel, multisector collaboration to optimize efficacy and equity.