Family Health History Communication Networks of Older Adults

Abstract

Older individuals play a critical role in disseminating family health history (FHH) information that can facilitate disease prevention among younger family members. This study evaluated the characteristics of older adults and their familial networks associated with two types of communication (have shared and intend to share new FHH information with family members) to inform public health efforts to facilitate FHH dissemination. Information on 970 social network members enumerated by 99 seniors (aged 57 years and older) at 3 senior centers in Memphis, Tennessee, through face-to-face interviews was analyzed. Participants shared FHH information with 27.5% of the network members; 54.7% of children and 24.4% of siblings. Two-level logistic regression models showed that participants had shared FHH with those to whom they provided emotional support (odds ratio [OR] = 1.836) and felt close to (OR = 1.757). Network-members were more likely to have received FHH from participants with a cancer diagnosis (OR = 2.617) and higher familiarity with (OR = 1.380) and importance of sharing FHH with family (OR = 1.474). Participants intended to share new FHH with those who provide tangible support to (OR = 1.804) and were very close to them (OR = 2.112). Members with whom participants intend to share new FHH were more likely to belong to the network of participants with higher perceived severity if family members encountered heart disease (OR = 1.329). Many first-degree relatives were not informed of FHH. Perceptions about FHH and disease risk as well as quality of social relationships may play roles in whether seniors communicate FHH with their families. Future studies may consider influencing these perceptions and relationships.

Keywords

common diseases communication networks family health history older adults social relationships

Public health professionals continue to face challenges in reducing the detrimental impacts of common chronic diseases such as cancer and heart disease. As part of these efforts, health professionals are now increasingly focusing attention on the influence of both genetic and environmental factors associated with chronic conditions (Scheuner, Wang, Raffel, Larabell, & Rotter, 1997). Although family health history (FHH) information has been criticized by some for confounding the effects of inherited and noninherited factors, this incorporation of both factors makes FHH an ideal risk assessment tool for chronic conditions that are influenced by determinants at multiple levels (Claassen et al., 2010; Valdez, Coates, St Pierre, Grossniklaus, & Khoury, 2011). Reports indicate that awareness about one’s own FHH is associated with engagement in exercise, healthy diet, participation in screenings, and losing weight (Baptiste-Roberts et al., 2007). However, inadequate knowledge of FHH among the general public hinders its usefulness for chronic disease prevention. A review of studies showed low sensitivity in a person’s self-reported FHH across various diseases (Qureshi et al., 2009). Although most Americans acknowledge the importance of knowing FHH, only 29% have actively collected such information (Yoon et al., 2004). At the 2009 NIH State-of-the-Science Conference on Family History, the expert panel called for more research to facilitate the use of FHH in public health and clinical practice (Qureshi et al., 2009).

FHH assessment can only be conducted within the familial social context and the dissemination of FHH information heavily relies on family communication. Older individuals know more FHH than younger individuals (Foster, Watson, Moynihan, Ardern-Jones, & Eeles, 2002), suggesting the benefit of facilitating FHH dissemination from older to younger generations to increase FHH knowledge among the population. Older Americans, many of whom are retiring in their early 60s (Blau, 2008), are able to provide more support and resources to family members than younger (Baker, Silverstein, & Putney, 2008; Bengtson, 2001), making them ideal targets for family-based interventions to facilitate FHH dissemination within families. A recent report showed that only 10% of those interviewed at community health centers, who have at least one child, were willing to communicate FHH to their children (Ashida, Goodman, Stafford, Lachance, & Kaphingst, 2012). It is therefore important to understand older adults’ FHH communication patterns with their family members and identify associated modifiable factors.

The decision to communicate private information about health conditions is influenced by social and psychological factors, and an individual’s evaluation of the benefits of disclosing such information (Petronio, 2002). Communication about disease risks among family members has been associated with the levels of support individuals receive (Hughes et al., 2002; van Oostrom et al., 2007). This suggests that the characteristics of social relationships (e.g., support exchange, closeness, frequency of contact) may determine whether FHH information is exchanged among family members. Furthermore, in health behavior theories such as the health belief model and protection motivation theory, perception of disease risk is postulated to influence an individual’s health-related behaviors (Champion & Skinner, 2008; Rogers, 1975). Thus, individuals who perceive that they or their family members are at increased risk for developing diseases and believe that sharing FHH is beneficial in reducing these risks, may be more motivated to share this information. It is also possible that individuals who perceive very high levels of risk may develop fear and avoid communicating FHH if their perception of efficacy to reduce risk is not sufficient (Roskos-Ewoldsen, Yu, & Rhodes, 2004; Witte, 1992). Previous research has also shown that perceptions regarding genomic information may determine the extent to which individuals use this information to address health concerns (McBride et al., 2009). In one study, a higher perceived familiarity with one’s own FHH was associated with a wider health communication reach within the family (the extent to which individuals communicated with family members of different relationship categories, including parents, siblings, children, and aunts/uncles), independent of participants’ education levels (Ashida et al., 2012). Therefore, older adults’ perceived familiarity with and importance of FHH may be associated with whether they share it with other family members.

This study addresses critical gaps in existing public health research that centers on using FHH information to improve health by investigating factors that may facilitate FHH communication by older adults. Previous studies evaluated FHH communication associated with highly penetrant cancer syndromes (Hughes et al., 2002; van Oostrom et al., 2007) rather than common complex diseases, or did not specifically evaluate communication among older individuals (Ashida et al., 2012). The objectives of this current study are (a) to assess the extent of older adults’ FHH communication with their familial network members and (b) to identify individual (i.e., perceptions about FHH, disease risks) and relational characteristics (i.e., frequency of contact, support exchange, feelings of closeness) associated with such communication using a network approach to consider these factors within familial social contexts. Additionally, based on the findings of previous studies (Berkman et al., 2004; Henneman, Timmermans, & Van Der Wal, 2004; Ishiyama et al., 2008; Kaphingst et al., 2012) and recommendations from the NIH State-of-the-Science Conference on Family History (Qureshi et al., 2009), sociodemographic characteristics of older adults and their social network members that may be associated with health communication (i.e., gender, educational attainment, age, personal health history) were considered. Understanding key psychological and social relationship factors associated with FHH communication within familial social contexts is critical in developing effective public health interventions to enhance FHH communication.

Method

Procedure

Face-to-face interviews were conducted with 110 community-dwelling older adults from three senior centers in Memphis, Tennessee, between June and August, 2011. Graduate students in public health underwent approximately 40 hours of interviewer training on topics that included ethics and understanding the priority population, interviewing skills with older adults, and mock interviews with experienced interviewers and individuals similar to the study participants. Age 60 was used as a recruitment cutoff because a majority of Americans retire in their early 60s (Blau, 2008), and those retired are more likely to have time and resources to provide to younger family members, making them potential targets for interventions. Study flyers were posted at the centers and also included in the newsletters mailed to center members. Interested seniors contacted the staff at each center who maintained sign-up sheets. Each participant provided written consent before the interview and received a $10 gift card for a local grocery store after completion. This study was approved by the Institutional Review Board of the University of Memphis.

Measures

Family health history communication networks

Participants’ familial network members were enumerated by first listing their “biological family members including [their] parents, siblings, children, and grandchildren.” Participants then listed “other people, like spouse, other relatives, and close friends, whom [they] may talk to about [their or their family’s] health.” For each of the enumerated members, respondents provided information regarding their relationship to them, gender, age, whether currently living, and frequency of contact (talk or e-mail: once a year or less (1) to everyday (6)). Social network size was determined by the number of enumerated individuals who were currently living. Each member was assigned to the category of older- (parents, aunts/uncles), same-generation (siblings, cousins), younger generation family (children, grandchildren, nieces/nephews), or spouse/friends/nonbiological family. Friends and nonbiological members were included because disease risk information has been found to be communicated to spouses and close family friends who, in turn, may communicate it to individuals to whom the information is pertinent (Koehly et al., 2003).

From the list of the network members, respondents selected individuals to whom they have ever told about their family member or members who were diagnosed with cancer and heart disease (had shared), and with whom they will share information “if [they] learn new health information about one of [their] family members” (intend to share new FHH). For each of these questions, if the participant selected the network member the variable was coded 1 and those not selected were coded 0, creating two dichotomous outcome variables. These two dichotomous network member-level variables served as outcomes. There were five social support questions: “[who provides you with/to whom do you provide] tangible support like giving you a ride and helping with shopping?”; “[who provides you with/to whom do you provide] emotional support?”; and “who is very close to you?” to evaluate participants’ social exchanges with each network member.

Perceptions about FHH

Perceived familiarity with one’s own FHH was measured using an item adapted from a previous study (McBride et al., 2009): “How familiar are you with your family’s health history?”: not at all familiar (1) to very familiar (5). Based on an item used in previous research (Yoon et al., 2004), two items were adapted to measure perceived importance of sharing FHH: “How important do you think sharing family health history is to your [personal/family’s] health?”: not at all important (1) to extremely important (5). These items were examined separately in the analyses. Perceived risk was measured using two sets of questions, perceived susceptibility and severity (Champion & Skinner, 2008): “How likely do you think it is that your [sibling(s)/child(ren)/grandchild(ren)] will develop [cancer/heart disease] in the future?” (perceived susceptibility); and “How severe would it be if your [sibling(s)/child(ren)/grandchild(ren)] developed [cancer/heart disease]?” (perceived severity). Responses were averaged across the three relationship categories for each health condition, resulting in four scores (perceived susceptibility and severity for family regarding cancer and heart disease).

Participant characteristics

The following demographic characteristics of the respondents were considered, gender, race (Black, White), marital status (currently married/living as married, widowed/divorced/separated/never married), educational levels (high school degree or less, some college or higher), and personal health history (diagnosis of cancer, heart disease).

Analyses

The characteristics of the participants’ FHH communication networks were evaluated by examining descriptive statistics using the Statistical Package for Social Sciences (SPSS 20). Factors associated with communication outcomes (whether participants had shared or intend to share new FHH) were examined using two-level logistic regression models with random intercepts to account for the nested nature of the data (social relationships within families; Snijders, Spreen, & Zwaagstra, 1995) using HLM 7.0 (Raudenbush, Bryk, Cheong, Congdon, & Toit, 2011). Both models included, as Level 1 covariates, network member characteristics (i.e., age, generational status, gender). Level 2 (participant-level) covariates included participants’ gender, race, marital status, educational attainment, and social network size. Two dummy variables were used to examine whether adjustments would be needed for participants coming from three centers; however, it was determined unnecessary. Significant explanatory variables at both Level 1 (dyadic characteristics: i.e., frequency of contact, social support, closeness) and Level 2 (participant characteristics: i.e., personal health history, perceptions) were identified through a backward elimination procedure and retained in the final models. Statistical significance of parameters was assessed using Wald statistics based on restricted maximum likelihood estimation that can produce unbiased estimates of the variance and covariance parameters and robust standard errors (Meyer, 1991), using a Type I error rate of 0.05.

Results

A total of 1,058 currently living network members were enumerated by 110 respondents. Two participants who reported “other” race and nine who did not answer perceived risk questions were excluded, thus, the analyses included 970 network members of 99 participants. The characteristics of the respondents and their network members are provided in Table 1. Network members with missing values for age, frequency of contact, or relationship (n = 23) were included in evaluating the first objective but were excluded from the final models, which included 947 members of 99 participants. The average age of the participants was 73.07 years (SD = 7.48). Although all participants indicated that they were aged 60 years or older at the time of the recruitment, one of the participants was 57 years old based on the birthdate information. The majority of the respondents were female (78.8%), Black (71.7%), and not currently married (79.8%). The majority of the network members were biological family members (90.6%); 29.6% (n = 287) were siblings, 24.3% (n = 236) were children, and 30.3% (n = 294) were grandchildren. More than half (57.3 %) were younger generation and one third (31.0%) were same-generation family members.

Table 1.

Characteristics of the Participants (N = 99) and Their Network Members (N = 970)

	Frequency (n)	Percentage
Participant-level variables (N = 99)
Age in years	Mean = 73.07 (SD = 7.48)	Range = 57-90
Female	78	78.8
Race
Black	71	71.7
White	28	28.3
Marital status
Married/living as married	20	20.2
Widowed	45	45.5
Divorced/separated	24	24.2
Never married	10	10.1
Education
High school diploma or lower	42	42.4
Vocational school/some college	57	57.6
College degree	33	33.3
Have health insurance	93	93.9
Have ever been diagnosed with cancer	19	19.2
Have ever been diagnosed with heart disease	23	23.2
Network member-level variables (N = 970)
Age in years	Mean = 45.71 (SD = 21.86)	Range = 1-97
Female	514	53.0
Older generation family (parent, aunt, uncle)	22	2.3
Same generation family (sibling, cousin)	301	31.0
Younger generation family (child, grandchild, niece/nephew)	556	57.3
Social kin (spouse, friend, neighbor)	73	7.5

Characteristics of Participants’ FHH Communication Networks

The average social network size was 9.8 persons, ranging from 3 to 30. The network characteristics are presented in Table 2. On average, participants had shared with 3.29 (SD = 3.24) and intended to share new FHH with 4.84 (SD = 5.56) persons in their networks: 267 members (27.5%) were identified as those participants had shared with and 408 members (42.1%) were identified as those participants intended to share new FHH information with. The majority of the communication partners were first-degree relatives (i.e., siblings, children; 75% and 70% for “had shared” and “intend to share,” respectively). Participants identified different network members for the two outcome variables. Of the 970 members, 171 (17.6%) were identified as those participants had both shared and intended to share new FHH with (55.0% of those were children and 24.0% were siblings) whereas 466 (48.0%) were not selected for either outcomes (45.6% of those were grandchildren and 28.2% were siblings). Furthermore, 237 (24.4%) were identified as those participants had not shared but intended to share new FHH with (37.3% of those were siblings, 26.3% were grandchildren, and 25.0% were children), and 96 (9.9%) were identified as those participants had shared but do not intend to share new FHH with (37.2% of those were children and 30.9% were siblings). On average, participants receive tangible (e.g., getting a ride, help with shopping) and emotional support from 1.60 (SD = 1.29) and 2.73 (SD = 3.27) network members, respectively and provided tangible and emotional support to 2.69 (SD = 4.16) and 5.51 (SD = 5.70) members, respectively; participants felt close to 2.91 (SD = 2.70) members.

Table 2.

Characteristics of the Participants’ Social Networks (N = 99)

	Mean (SD)	Median	Range
Network compositions
Social network size	9.80 (5.12)	9	3-30
Frequency of contact (e.g., talk, e-mail)	3.02 (1.69)	2.83	1-6
Communication (average numbers of network members who fits the description)
To whom have you ever told about your family member(s) who were diagnosed with these conditions (shared)	3.29 (3.24)	3	0-17
If you learn new health information about your family, with whom will you share this information? (would share)	4.84 (5.56)	3	0-29
Social support (average numbers of network members who fit the description)
Who provides you with tangible support such as giving you a ride and helping with shopping?	1.60 (1.29)	1	0-8
To whom do you provide tangible support?	2.69 (4.16)	1	0-21
Who provides you with emotional support?	2.73 (3.27)	2	0-22
To whom do you provide emotional support?	5.51 (5.70)	4	0-26
Who is very close to you?	2.91 (2.70)	2	0-15

FHH and Disease Risk Perceptions

As shown in Table 3, participants, on average, felt “mostly familiar” with their own FHH (M = 3.88) and that sharing FHH is “very important” for their own and their family’s health (M = 4.05 and 4.06, respectively). The average level of perceived susceptibility was low, “a little likely” with an average score of 2 for both cancer and heart disease, whereas the perceived severity was “somewhat severe” with average scores of 3 for both conditions. The ranges of responses were wide for all these variables indicating that some participants had very low levels of perceived risk whereas others reported high levels of perceived risk.

Table 3.

Participants’ Perceptions About Family Health History (FHH) and Disease Risks (N = 99)

	Mean (SD)	Median	Range
Familiarity with own FHH	3.88 (1.06)	4	1-5^a
Importance of sharing FHH for own health	4.05 (0.66)	4	1-5^b
Importance of sharing FHH for family’s health	4.06 (0.78)	4	1-5^b
Susceptibility for family members (cancer)	2.15 (0.95)	2	1-4.5^c
Susceptibility for family members (heart disease)	2.32 (0.98)	2.33	1-5^c
Severity for family members (cancer)	2.97 (1.15)	3	1-5^d
Severity for family members (heart disease)	3.05 (1.21)	3	1-5^d

Not at all familiar (1) to very familiar (5). ^bNot at all important (1) to “extremely important (5). ^cNot at all likely (1) to extremely likely (5). ^dNot at all severe (1) to extremely severe (5).

Factors Associated With FHH Communication

Models examining factors associated with FHH communication are shown in Table 4. Participants reported that they had shared family health information with those to whom they provide emotional support (odds ratio [OR] = 1.836, p = .035), feel close (OR = 1.757, p = .014), and come in contact more frequently (OR = 1.147, p = .036). Participants were more likely to have shared FHH with younger generation (OR = 2.848, p = .015) than same-generation members. Network members were more likely to have received FHH from participants with smaller networks (OR = 0.927, p = .005), a cancer diagnosis (OR = 2.617, p = .003), higher perceived familiarity with FHH (OR = 1.380, p = .021), and higher perceived importance of sharing FHH for family’s health (OR = 1.474, p = .020).

Table 4.

Factors Associated With Family Health History (FHH) Communication and Willingness to Communicate

	To Whom Have You Ever Told?			Who Would You Tell?
	OR	CI	p	OR	CI	p
Intercept	0.002***	[0.000, 0.022]	<.001	0.043*	[0.010, 0.179]	<.001
Participant-level variables (N = 99)
Female	0.919	[0.488, 1.730]	.792	0.623	[0.293, 1.326]	.217
Black	0.675	[0.377, 1.211]	.186	0.626	[0.309, 1.266]	.191
Married	0.917	[0.459, 1.833]	.805	1.514	[0.738, 3.108]	.256
High school degree or less	0.756	[0.434, 1.318]	.321	0.585	[0.306, 1.119]	.105
Cancer diagnosis	2.617**	[1.404, 4.877]	.003	—	—	—
Perceived severity of heart disease in family	—	—	—	1.329*	[1.055, 1.672]	.017
Familiarity with FHH	1.380*	[1.051, 1.812]	.021	—	—	—
Perceived importance of sharing FHH	1.474*	[1.006, 2.039]	.020	—	—	—
Network size	0.927**	[0.880, 0.976]	.005	1.039	[0.976, 1.105]	.228
Network member-level variables (N = 947)
Age	1.038***	[1.021, 1.055]	<.001	1.028***	[1.015, 1.041]	<.001
Older generation family member	0.179*	[0.043, 0.750]	.019	0.248**	[0.090, 0.681]	.007
Younger generation family member	2.848*	[1.230, 6.596]	.015	1.941	[0.965, 3.904]	.063
Spouse/friend/neighbor	0.611	[0.249, 1.502]	.284	0.333***	[0.193, 0.573]	<.001
Female	1.167	[0.850, 1.603]	.340	1.032	[0.801, 1.329]	.807
Frequency of contact	1.147*	[1.009, 1.303]	.036	1.132**	[1.032, 1.243]	.009
Provide tangible support to participant	—	—	—	1.804*	[1.144, 2.845]	.012
Receive emotional support from participant	1.836*	[1.045, 3.227]	.035	—	—	—
Participant feels close to	1.757*	[1.126, 2.741]	.014	2.112***	[1.444, 3.088]	<.001

Note. Reference groups are White race, some college or higher education, and same-generation family member. OR = odds ratio; CI = confidence interval.

p < .05. **p < .01. ***p < .001.

Participants were more likely to intend to share new FHH information with those who provide tangible support to them (OR = 1.804, p = .012), they felt close to (OR = 2.112, p < .001), and they came in contact with more frequently (OR = 1.132, p = .009). Participants who perceived higher severity of heart disease for family members were more likely to intend to share FHH (OR = 1.329, p = .017). Perceived severity regarding participants themselves and perceived susceptibility for self and family were not associated with either outcome.

Discussion

The findings of this study showed that the FHH communication networks of older adults were rather small, and that there are social and psychological factors associated with their past and intended communication behavior. Although participants, on average, had about 10 members in their familial networks, they had shared FHH with only 27.5% and were willing to share with 42.1% of the network members. Considering that most of the network members (89.0%) were first- and second-degree relatives who could benefit greatly from this information, these findings highlight the importance of facilitating the communication processes of older adults to increase FHH knowledge among their family members. Of 237 members identified as those with whom participants had not shared but intended to share new FHH, 78% were participants’ siblings, children, or grandchildren. This suggests the potential for more first- and second-degree relatives to receive FHH information with effective interventions to help and motivate older individuals collect and disseminate FHH.

Higher frequency of contact (e.g., talking, e-mailing) and feeling of closeness were associated with higher likelihood of FHH communication among the participants. Furthermore, participants had shared FHH with those to whom they provided emotional support, and they were willing to share it with those who provide tangible support to them regardless of feeling of closeness. The finding related to tangible support may, in part, reflect older adults’ attempt to reciprocate the support they receive, a type of interaction that is very important for older adults’ well-being (Israel & Antonucci, 1987). As older adults’ opportunities to give tangible support decrease with age (Kahn, 1979), sharing health information with family members may provide an opportunity to reciprocate support. Although this result was only significant for one outcome, this finding may help us understand how individuals may be motivated to carry out their behavioral intentions. Future studies could evaluate whether informing older adults that they can reciprocate support by sharing FHH information with their family members may facilitate FHH communication.

Participants were more likely to have told FHH to younger generation family members than same-generation family members. This is encouraging as we seek to facilitate the flow of FHH information from older- to younger generation family members. This may be partly because of social network size of older adults becoming smaller with age (Kahn, 1979), as 57.3% of the members were younger; whereas 33.3% were same- or older generation family members in our study. It should be noted, however, that in order for older adults to have accurate information for their younger generation family members, they need to exchange FHH information with their siblings, who are second-degree relatives of their biological children. Thus, we should facilitate FHH communication among all members and helping individuals of all ages understand how FHH information can be used to facilitate health may be most beneficial.

As previously found (Ashida et al., 2012), higher perceived familiarity with FHH was associated with FHH communication, potentially reflecting participants’ confidence in sharing this information. Perceived importance of sharing FHH for the health of family members was associated with whether older adults shared it, however, perceived importance for the participants’ own health was not associated. Furthermore, participants who perceived heart disease as severe for family members were more willing to share FHH, whereas severity perceptions regarding participants themselves were not associated. These findings suggest that informing older adults about the benefits of FHH information in preventing diseases among their family members may motivate them to share this information.

Older individuals tend to provide more social resources (e.g., health information, social support) to younger family members (Ashida et al., 2011; Bengtson, 2001). Thus, interventions can capitalize on these network characteristics and mobilize older adults to become FHH disseminators within families. Involving older individuals in such activities may also benefit them by enhancing their social engagement that, in turn, can facilitate optimal aging processes (Rowe & Kahn, 1998). Although older adults often have FHH knowledge that their younger family members do not have, they may be unaware of their role as information sources within the family. Some older adults may not feel confident that they have accurate FHH (Ford et al., 2002), therefore, interventions need to help them collect complete FHH and communicate this information effectively.

Our findings suggest the importance of both quantity and quality of social interactions in FHH communication. It is difficult to change the quality of social relationships (e.g., closeness); however, it may be possible to increase the quantity of interactions (e.g., frequency of contact, provision of tangible support). Although geographic distance may limit some family members’ ability to provide tangible support, our findings showed the potential benefits of frequent contact through talking or e-mailing. Efforts to enhance social interactions can focus on both older individuals and their family members (Heaney & Israel, 2008) who can be made aware of the resourcefulness of older individuals.

This study demonstrated the usefulness of using network approaches to understand FHH communication among older adults. However, a longitudinal study should be conducted to identify factors that precede FHH communication to better inform practices. Furthermore, in-depth qualitative interviews should be conducted to elucidate barriers for FHH communication. This study only considered cancer and heart disease, limiting our understanding regarding other disease contexts. Participants in this study were from senior centers in Memphis, TN, who were able to independently participate in social activities, limiting generalizability to older adults with different cultural backgrounds and characteristics. Our sample was similar to the 2000 U.S. Census data for the city of Memphis with a large proportion of Black participants. In prior research, non-Hispanic Whites were found to have higher FHH knowledge regarding type 2 diabetes than Blacks (Yoon et al., 2004). It is possible, that our population has limited FHH knowledge for chronic conditions, leading to the low levels of communication found in our study.

All measures were based on self-report, which may have been influenced by recall and social desirability biases, and question wordings may have caused the responses to center around the middle of the range (Streiner & Norman, 2008). Perceived familiarity does not indicate participants’ actual knowledge; however, perception may represent the underlying pathway through which FHH communication occurs. Two of the network members in the aunts/uncles category were younger than the participants who enumerated them. These individuals were included in the older generation category as they are considered one generation higher when analyzing family pedigree for familial risk. However, these individuals may have unique social roles in terms of FHH communication. Social networks were assessed only through the participants (ego centered); thus, the characteristics of social relationships were not verified by their network members. Future studies would benefit from interviewing their network members to identify strategies that could influence both the older adults and their family members to engage in FHH communication and to examine where same-generation family members are obtaining their FHH information.

Conclusions

Our results suggest the need to expand older adults’ FHH communication networks. Perceptions about the usefulness of FHH in preventing chronic diseases of family members and the characteristics of social relationships may play key roles in whether older adults communicate FHH. Future efforts may focus on gaining an in-depth understanding about the barriers for FHH communication, determining causal associations, and developing strategies to influence identified factors to enhance FHH dissemination.

Footnotes

Acknowledgements

We would like to thank the participants for sharing their stories with us and staff members at the senior centers for facilitating data collection processes. We also thank our interviewers: Doris Amoah, Andy Collins, and Larita Webb.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article:

This work was supported in full or in part by a grant from The University of Memphis Faculty Research Grant Fund. This support does not necessarily imply endorsement by the University of research conclusions. The work of Drs. Goodman and Kaphingst was supported by the Barnes-Jewish Hospital Foundation.

References

Ashida

Goodman

M. S.

Stafford

Lachance

Kaphingst

K. A.

(2012). Perceived familiarity with and importance of family health history among a medically underserved population. Journal of Community Genetics, 3, 285-295. doi:10.1007/s12687-012-0097-x

Ashida

Hadley

D. W.

Goergen

A. F.

Skapinsky

K. F.

Devlin

H. C.

Koehly

L. M.

(2011). The importance of older family members in providing social resources and promoting cancer screening in families with a hereditary cancer syndrome. The Gerontologist, 51, 833-842.

Baker

L. A.

Silverstein

Putney

N. M.

(2008). Grandparents raising grandchildren in the United States: Changing family forms, stagnant social policies. Journal of Societal and Social Policy, 7, 53-69.

Baptiste-Roberts

Gary

T. L.

Beckles

G. L.

Gregg

E. W.

Owens

Porterfield

Engelgau

M. M.

(2007). Family history of diabetes, awareness of risk factors, and health behaviors among African Americans. American Journal of Public Health, 97, 907-912.

Bengtson

V. L.

(2001). Beyond the nuclear family: The increasing importance of multigenerational relationships in American society. Journal of Marriage and Family, 63, 1-16.

Berkman

N. D.

DeWalt

D. A.

Pignone

M. P.

Sheridan

S. L.

Lohr

K. N.

Lux

Bonito

A. J.

(2004). Literacy and health outcome: Evidence report/technology assessment No. 87. Rockville, MD: U.S. Department of Health and Human Services.

Blau

D. M.

(2008). Retirement and consumption in a life cycle model. Journal of Labor Economics, 26, 35-71.

Champion

V. L.

Skinner

C. S.

(2008). The health belief model. In Glanz

D. K.

Rimer

B. K.

Viswanath

(Eds.), Health behavior and health education: Theory, research, and practice (4th ed., pp. 45-65). San Francisco, CA: Jossey-Bass.

Claassen

Henneman

Janssens

A. C.

Wijdenes-Pijl

Qureshi

Walter

F. M.

Timmermans

D. R. M.

(2010). Using family history information to promote healthy lifestyles and prevent diseases; a discussion of the evidence. BMC Public Health, 10(248), 1-7.

10.

Ford

M. E.

Hill

D. D.

Blount

Morrison

Worsham

Havstad

S. L.

Johnson

C. C.

(2002). Modifying a breast cancer risk factor survey for African American women. Oncology Nursing Forum, 29, 827-834.

11.

Foster

Watson

Moynihan

Ardern-Jones

Eeles

(2002). Genetic testing for breast and ovarian cancer predisposition: Cancer burden and responsibility. Journal of Health Psychology, 7, 469-484.

12.

Heaney

C. A.

Israel

B. A.

(2008). Social networks and social support. In Glanz

D. K.

Rimer

B. K.

Viswanath

(Eds.), Health behavior and health education: Theory, research, and practice (4th ed., pp. 189-210). San Francisco, CA: Jossey-Bass.

13.

Henneman

Timmermans

D. R. M.

Van Der Wal

(2004). Public experiences, knowledge and expectations about medical genetics and the use of genetic information. Community Genetics, 7, 33-43.

14.

Hughes

Lerman

Schwartz

Peshkin

B. N.

Wenzel

Narod

Main

(2002). All in the family: Evaluation of the process and content of sisters’ communication about BRCA1 and BRCA2 genetic test results. American Journal of Medical Genetics, 107, 143-150.

15.

Ishiyama

Nagai

Muto

Tamakoshi

Kokado

Mimura

Yamagata

(2008). Relationship between public attitudes toward genomic studies related to medicine and their level of genomic literacy in Japan. American Journal of Medical Genetics, Part A, 146, 1696-1706.

16.

Israel

B. A.

Antonucci

T. C.

(1987). Social network characteristics and psychological well-being: A replication and extension. Health Education Quarterly, 14, 461-481.

17.

Kahn

R. L.

(1979). Aging and social support. In Riley

M. W.

(Ed.), Aging from birth to death: Interdisciplinary perspectives (pp. 77-92). Boulder, CO: Westview Press.

18.

Kaphingst

K. A.

Goodman

Pandya

Garg

Stafford

Lachance

(2012). Factors affecting frequency of communication about family health history with family members and doctors in a medically underserved population. Patient Education and Counseling, 88, 291-197. doi:10.1016/j.pec.2011.11.013

19.

Koehly

L. M.

Peterson

S. K.

Watts

B. G.

Kempf

K. K. G.

Vernon

S. W.

Gritz

E. R.

(2003). A social network analysis of communication about Hereditary Nonpolyposis Colorectal Cancer genetic testing and family functioning. Cancer Epidemiology, Biomarkers and Prevention, 12, 304-313.

20.

McBride

C. M.

Alford

S. H.

Reid

R. J.

Larson

E. B.

Baxevanis

A. D.

Brody

L. C.

(2009). Characteristics of users of online personalized genomic risk assessments: Implications for physician-patient interactions. Genetics in Medicine, 11, 582-587.

21.

Meyer

(1991). Estimating variance and covariances for multivariate animal models by restricted maximum likelihood. Genetics Selection Evolution, 23, 67-83.

22.

Petronio

(2002). Boundaries of privacy: Dialectics of disclosure. Albany: State University of New York Press.

23.

Qureshi

Wilson

B. J.

Santaguida

Little

Carroll

Allanson

Raina

(2009). NIH state-of-the-science conference: Family history and improving health (Evidence Report/Technology Assessment No. 186: Prepared by the McMaster University Evidence-based Practice Center, under Contract No. 290-2007-10060-I). Rockville, MD: Agency for Healthcare Research and Quality.

24.

Raudenbush

Bryk

Cheong

Y. F.

Congdon

R. T.

Toit

(2011). HLM 7: Hierarchical linear and nonlinear modeling for Windows (Version 7.0). Lincolrnwood, IL: Scientific Software International.

25.

Rogers

R. W.

(1975). A protection motivation theory of fear appeals and attitude change. Journal of Psychology, 35, 150-159.

26.

Roskos-Ewoldsen

D. R.

J. J.

Rhodes

(2004). Fear appeal messages affect accessibility of attitudes toward the threat and adaptive behaivors. Communication Monographs, 71, 49-69.

27.

Rowe

J. W.

Kahn

R. L.

(1998). Successful aging: The MacArthur Foundation study. New York, NY: Dell.

28.

Scheuner

M. T.

Wang

S. J.

Raffel

L. J.

Larabell

S. K.

Rotter

J. I.

(1997). Family history: A comprehensive genetic risk assessment method for the chronic conditions of adulthood. American Journal of Medical Genetics, 71, 315-324.

29.

Snijders

Spreen

Zwaagstra

(1995). The use of multilevel modeling for analysing personal networks: Networks of cocaine users in an urban area. Journal of Quantitative Anthropology, 5, 85-105.

30.

Streiner

D. L.

Norman

G. R.

(2008). Health measurement scales: A practical guide to their development and use (4th ed.). New York, NY: Oxford University Press.

31.

Valdez

Coates

R. J.

St Pierre

Grossniklaus

Khoury

M. J.

(2011). Knowledge gaps remain in the use of family health history in public health. Public Health Genomics, 14(2), 94-95.

32.

van Oostrom

Meijers-Heijboer

Duivenvoorden

H. J.

Brocker-Vriends

A. H.

van Asperen

C. J.

Sijmons

R. H.

Tibben

(2007). A prospective study of the impact of genetic susceptibility testing for BRCA1/2 or HNPCC on family relationships. Psychooncology, 16, 320-328.

33.

Witte

(1992). Putting the fear back into fear appeals: The extended parallel process model. Communication Monographs, 59, 329-349.

34.

Yoon

P. W.

Scheuner

M. T.

Gwinn

Khoury

M. J.

Jorgensen

Hariri

Lyn

(2004). Awareness of family health history as a risk factor for disease—United States, 2004. Morbidity and Mortality Weekly Report, 53, 1044-1047.