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. Author manuscript; available in PMC: 2022 Dec 1.
Published in final edited form as: J Cancer Educ. 2020 Oct 27;36(6):1155–1162. doi: 10.1007/s13187-020-01879-y

Adherence to Mammography and Pap Screening Guidelines Among Medically Underserved Women: The Role of Family Structures and Network-Level Behaviors

Caitlin G Allen 1, David Todem 2, Karen Patricia Williams 3
PMCID: PMC8076331  NIHMSID: NIHMS1641317  PMID: 33107009

Abstract

Purpose:

Poor adherence to screening recommendations is an important contributing factor to disparities in breast and cervical cancer outcomes among women in the United States. Screening behaviors are multifactorial but there has been limited focus on how family network beliefs and behaviors influence individual’s likelihood to complete screening. This research aims to fill this gap by evaluating the role of family network composition and screening behaviors on women’s likelihood to adhere to mammogram and pap screening recommendations.

Methods:

We used an ego network approach to analyze data from 137 families and their networks. Primary outcomes were whether an individual had received a mammogram in the past year and whether she had received a pap smear in the past three years. Network level predictors included network composition (size of network, average age of network members, satisfaction with family communication) and network screening behaviors. We conducted multivariable logistic regressions to assess the influence of network level variables on both mammogram and pap smears, adjusting for potential individual level confounders.

Results:

Each network had an average age of 47.8 years, and an average size of 3.05 women, with the majority of members being sisters (37.8%). We found differences in network screening behaviors by race, with Arab networks being less likely to have completed self-breast exams (OR=0.207, 95%CI=0.057–0.757, p=0.0173), ever a gotten pap screen (OR=0.105, 95%CI=0.013–0.849, p=0.0345), and gotten pap screening in the last three years (OR=0.307, 95%CI=0.095–0.992, p=0.048) compared to African American networks. Network screening behaviors also strongly influenced the likelihood of an individual completing a similar screening behavior.

Conclusions:

This analysis sheds light on family network characteristics that influence screening behaviors among medically underserved women. These findings support the development and dissemination of screening interventions among female’s family networks.

Keywords: cancer screening, mammograms, cervical cancer, social networks

Precis:

This analysis sheds light on family network characteristics that influence screening behaviors among underrepresented women. These findings support the development and dissemination of screening interventions among female’s family networks.

BACKGROUND

Despite declines in breast and cervical cancer deaths, there are still persistent racial and ethnic disparities in cancer outcomes among women in the United States (American Cancer Society, 2018; Centers for Disease Control Prevention, 2015; DeSantis, Siegel, et al., 2016). For example, African American women have the highest rate of death from cervical and breast cancer. Recent data also show that gaps are widening between white women and African American women in breast cancer mortality with African American women being 1.4 times more likely to die from breast cancer than white women (American Cancer Society, 2015; DeSantis, Fedewa, et al., 2016; Yoo et al., 2017). Similar patterns are also found among other US minority groups. For example, Hispanic women, despite having lower incidences and death rates of many common forms of cancer, are more likely than non-Hispanic women to be diagnosed at a later stage (American Cancer Society, 2016). Data also suggests that while Arab-American women have similar distribution of breast cancer histology compared to European-American women the stage, age, and hormone receptor status at diagnosis were more similar to African American women.(Hensley Alford et al., 2009)

Reasons for these stark disparities in cancer outcomes are multifactorial, but include lower adherence to screening guidelines among medically underserved women (Cooper & Doug Kou, 2008; Demark-Wahnefried et al., 1995; Ko, Kreuter, & Baldwin, 2005; McBean & Yu, 2007; Rimer et al., 1996). Current American Cancer Society (ACS) recommendations indicate that women should undergo annual mammography beginning at age 45 years with the option of beginning annual screening between the ages of 40 and 44 years. Cervical cancer screening is suggested to begin at age 21 and take place every three years. Between the ages of 30–65 women should be screened every five years, and women over 65 with low risk can stop cervical cancer screening (Smith et al., 2018). However, minority women tend to have lower levels of participation in cancer screening (DeSantis, Siegel, et al., 2016; Kapp, Walker, Haneuse, & Yankaskas, 2011; Markossian & Hines, 2012) and are more likely to be diagnosed with late stage breast cancer, in part due to lower levels of participation in preventive screening efforts (Chatterjee, He, & Keating, 2013). Indeed, these low levels of screening and poor follow-up among minority women have been suggested to be substantially contributing to higher levels of mortality (O’Keefe, Meltzer, & Bethea, 2015).

Numerous efforts have been undertaken to better understand reasons for differences in levels of cancer screening among racial and ethnic minorities, including addressing intrapersonal beliefs about cancer such as lack of awareness and fear about screening procedures (Orom, Kiviniemi, Underwood, Ross, & Shavers, 2010; Sheppard et al., 2013). Often, interventions targeting screening behaviors are designed to focus on changing individual beliefs, knowledge, and attitudes. Such programs designed to promote early detection have been found successful, indicating that promoting screening for early diagnosis among minority women is an essential strategy to avert cancer disparities.

An understudied but promising area of research is the influence of interpersonal connections on cancer screening decisions. Indeed, screening may be a normative behavior among families and social networks (Kang & Bloom, 1993; Suarez, Lloyd, Weiss, Rainbolt, & Pulley, 1994; Suarez et al., 2000). Previous studies have indicated that psychosocial factors and social support from family members strongly influences minority women’s decisions to participate in cancer prevention practices (Brittain, Taylor, Loveland-Cherry, Northouse, & Caldwell, 2012; Madhivanan, Valderrama, Krupp, & Ibanez, 2016; Yang et al., 1994). Indeed, interventions that use peers or other community members have been shown to help increase the rates of screening among women (Allen, Sorensen, Stoddard, Peterson, & Colditz, 1999; Allen, Stoddard, & Sorensen, 2008; Kang, Bloom, & Romano, 1994; Seow, Huang, & Straughan, 2000; Suarez et al., 1994; Suarez et al., 2000; Taylor et al., 1998). Family networks tend to have a strong influence on these screening behaviors, as they provide encouragement, sharing of results and experiences with screening, and assistance in finding doctors or getting appointments. Previous studies have pointed to the role of subjective norms and encouragement by family and friends to help obtain screening adherence and follow-up (Allen et al., 2008). Social networks may influence the level of support and advice individuals receive about cancer screenings or provide examples of experiences in interacting with the health care system to complete screenings.

In this manuscript, we use data from the Kin KeeperSM Cancer prevention study to better understand the effects of family networks (female blood relatives including sister, mothers, grandmothers, aunts, and nieces) on individual’s cervical and breast cancer screening outcomes. The Kin KeeperSM model uses community-based participatory research approaches to help increase cancer prevention education and screening behaviors among minority women through family engagement (Williams, 2008). Our objective was to better understand the role of family network characteristics (composition and behaviors) on rates of mammography and pap screening among medically underserved women.

METHODS

Study Design

The Kin KeeperSM Cancer Prevention study is a randomized trial that sought to build from the natural ways female family members communicate in order to promote cancer screening behaviors. Detailed information about the study design and sample characteristics are described elsewhere (Williams, 2008; Williams, Mabiso, Jackson, Lawshe, & Maurer, 2009; Williams, Mullan, & Todem, 2009). All aspects of the study were approved by the Michigan State University IRB. Briefly, women between the ages of 21–70 from Detroit and Dearborn, Michigan, were recruited to participate in the study. Community health workers (CHWs) used community-based recruitment strategies to identify female participants. Once a women agreed to participate in the study she was considered the family’s kin keeper. Kin keepers were asked to recruit additional family members for inclusion in educational sessions. A total of 137 families were included in this sample, which included 137 Kin Keepers and 367 family members. All data used for this analysis are from surveys collected at during baseline data collection.

Measures

Outcomes

Our two primary outcomes for this analysis were mammogram screening and pap screening. For mammogram screening, eligible participants were asked the following question, “In the last 12 months, have you had a mammogram,” (response options were yes and no). For pap smear screening, eligible participants were asked, “in the last three years have you had a pap smear?” (response options were yes and no). These outcomes accounted for age and appropriateness of screening guidelines.

Network-level Predictors

Network-level predictors included network composition: size of network, average age of network members, satisfaction with family communication, and network behavior characteristics. The size of the network was calculated based on the total number of family members (alters) for each kin keeper. The average age of network members was calculated based on the family members (alters) included and reported at the network level. The satisfaction with family communication score was calculated based on the question, “Family members are satisfied with how they communicate with each other” (5-point Likert scale from strongly disagree to strongly agree)(Olson, 2011). We also assessed the cancer density within the network, which was calculated based on the proportion of individuals who had cancer in a family. Finally, we included the proportion of network members who were sisters.

Network screening behavior characteristics included breast self-exams, “Have you ever done a breast self-exam?”; whether they have done clinical breast exam, “Have you ever had a clinical breast exam?”; ever have a mammogram, “Have you ever had a mammogram?”; pap smear behaviors, “Have you ever had a pap smear?”; mammogram in the past 12 months, “In the last 12 months, have you had a mammogram”; and recent pap smear screening, “in the last three years have you had a pap smear?” All items were assessed with yes/no response options. Network behaviors were reported as the proportion of the network with greater than 50% completing the behavior.

Socio-demographics

Kin keeper individual-level control variables included racial identity, marital status, age, education level, employment status, and health insurance. Racial identity was asked with the question, “how do you identify yourself?” (African-American/Black, Latino/Hispanic, and Arab American). Marital status options included: married, single/never married, and all other response options (separated, divorced, widowed). Age was generated based on the date of birth recorded at the time of recruitment. Education level was asked with the following question, “what is the highest education you have completed?” (graduate degree, college degree, some college, high school diploma, GED, above 9th grade, and below 9th grade), which was reported as high school and some college or greater. Employment status categories included: full time employee, part time employee, unemployed, and others (retired, not working). Insurance status was reported as no health insurance coverage and health coverage.

Statistical Analysis

Basic summary statistics were generated for the baseline socio-demographic characteristics of kin keepers and family members (alters), and the family network characteristics. These included the relationships between kin keepers and alters (percent of network members that were: mother, daughter, maternal grandmother, paternal grandmother, sister, niece (sister’s daughter), and niece (brother’s daughter)). In addition, we describe whole network characteristics, including: average size of network, the average age of network members, average level of satisfaction with family communication, density of cancer, and proportion of the sisters in the network. We also reported the mean proportion of network behaviors, which included: proportion of the network that had greater than 50% of network: completing self-breast exam, clinical breast exam, ever getting a pap screening, getting a mammogram in past 12 months, or getting a pap in last 3 years.

Bivariate associations between each of the two outcomes under study (the kin keeper screening behavior for had a mammogram in the past 12 months and pap in the last three years) and kin keepers’ and network characteristics were evaluated using chi-square tests of independence. We also assessed for racial differences in network screening behaviors (e.g., proportion of network that had greater than 50% completing self-breast exam).

We then conducted multivariable logistic regression to further assess the influence of network behaviors on an individual having a mammogram in the past 12 months or a pap in the past 3 years. Based on bivariate associations, we assessed whether network mammogram behaviors influenced kin keeper likelihood to have had mammogram in the past 12 months (controlling for socio-demographics), whether network clinical breast exams or network pap screening behaviors (ever gotten pap or gotten pap in last 3 years) influenced kin keeper likelihood to have gotten a pap in the last 3 years. P-values below 5% level were considered statistically significant. All analyses were performed with the use of SAS software, version 9.4.

RESULTS

Overview of the Sample and Characteristics of the Network

The majority of networks members were sisters (57.77%). The average size of each network was 3.05 (SD=0.25) individuals, with an average age of the network being 47.87 years. Reported levels of satisfaction with family communication were high (4.06, SD=0.93). Overall, the mean proportions of cancer density was 0.53, indicating that half of the networks had some history of cancer. The proportion of networks that reported greater than 50% of the network completing screening behaviors was high for all network behaviors: self-breast exams (0.82, SD=0.39), clinical breast exams (0.84, SD=0.37), ever pap smears (0.89, SD=0.31), mammogram in the past three years (0.51, SD=0.5), and three year pap smears (0.51, SD=0.5),. (Table 1).

Table 1.

Network Characteristics

Relationships between Kin Keepers and Alters N %
Mother 42 11.44
Daughter 57 15.53
Grandmother (maternal) 7 1.91
Grandmother (paternal) 3 0.82
Sister 212 57.77
Niece (sister daughter) 37 10.08
Niece (brother daughter) 9 2.45
Whole Networks Mean SD
Size of Network 3.05 0.25
Average Age of Network Members 47.87 6.63
Satisfaction with Family Communication 4.05 0.93
Density of Cancer 0.53 0.32
Proportion of Sisters in Network 0.35 0.24
Network Behaviors (N=137) Proportion of Network Reporting >50% Completion SD
Average Self Breast Exams 0.82 0.39
Average Clinical Breast Exams 0.84 0.37
Average Ever Pap Smear 0.89 0.31
Average 12 month mammogram 0.51 0.5
Average 3 year pap smear 0.82 0.39
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There were high screening rates of both cancers among kin keepers and alters. Sixty-one percent of kin keepers reported having a mammogram in the past 12 months and 58.95% of alters. Similarly, 77.27% of kin keepers reported having a pap smear in the past three years and 75.61% of alters. The majority of participants considered themselves to be Arab (49.64% of kin keepers and 44.06% of alters), most were married (57.14% of kin keepers and 51.5% of alters). The average age of kin keepers was 47.77 and 48.50 for alters. Most participants were unemployed (53.49% of kin keepers and 45.81% of alters). The majority of kin keepers (67.88%) and alters (66.02%) had health insurance. There were no significant demographic differences between kin keepers and family members (Table 2).

Table 2.

Sample Descriptives

Kin Kee pers (N=137) Alters (N=367)
Outcomes N (Mean) % (SD) N (Mean) % (SD)
Had mammogram past 12 months 61 61 168 58.95
Pap in last 3 years 102 77.27 279 75.61
Race
African American 50 36.5 166 43.8
Latina 19 13.87 46 12.14
Arab 68 49.64 167 44.06
Marital Status
Married 76 57.14 189 51.5
Single/Never Married 31 23.31 108 29.43
Other 26 19.55 70 29.43
Age 47.77 12.44 48.59 12.65
Highest Education
High School 87 63.5 214 58.79
Some College or Greater 50 36.5 150 41.21
Employment
Full time 30 23.26 93 25.98
Part time 18 13.96 65 17.6
Unemployed 69 53.49 164 45.81
Other 12 9.3 38 10.61
Health Insurance
No health coverage 44 32.12 123 33.98
Health Coverage 93 67.88 293 66.02
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*

Note: no significant differences between characte ristics of kin keepers or alters usin g one-way ANOVA tests

Racial Differences in Screening Behaviors

Networks of Arab women were less likely than African American networks to report greater than 50% of their network completing a self-breast exam (OR=0.207, 95%CI=0.057–0.757, p=0.0173), having ever gotten a pap smear (OR=0.106, 95%CI=0.013–0.849, p=0.0345), and having gotten a pap in the past three years (OR=0.307, 95%CI=0.095–0.992). Networks of Latina women were also less likely than African American networks to have greater than half of their network getting a pap screening in the past three years (OR=0.188, 95%CI=0.046–0.77, p=0.0201) (Supplemental Table 1).

Influence of Family Networks on Behaviors

Evaluations of bivariate associations are reported in Supplemental Table 2. Individuals with networks reporting greater than half of their network getting a mammogram in the past 12 months were more likely to have had a mammogram in the past 12 months (OR=6.41, p<0.0001). Network screening behaviors also influenced individuals’ likelihood to have had a pap smear in the past three years. Networks reporting greater than 50% of network having completed a clinical breast exam (OR=3.545, p=0.132), having ever gotten a pap (OR=14.184, p<0.0001), and having gotten a pap in the past 3 years (OR=27.636, p<0.0001) were more likely to have had a pap in the past three years.

Multivariable Models

Our final model for the outcome of the kin keeper having a mammogram in the past 12 months included the proportion of the network that had greater than 50% getting a mammogram in the past 12 months, controlling for socio-demographic characteristics. We found that the network level of mammogram screening in the past 12 months was associated with the likelihood of the kin keeper having receive a mammogram in the past 12 months (OR=8.52: 95%CI=2.86–25.31, p=0.0001).

We also assessed for the kin keeper’s likelihood to have had a pap in the past 3 years. We ran three separate multivariable models based on bivariate associations. First, we found that the proportion of the network that had completed clinical breast exams influenced the likelihood that kin keepers would receive a pap in the past 3 years, controlling for sociodemographics (OR=7.54; 95%CI=2.16–26.26, p=0.0015). We also found that the network level of having ever gotten a pap smear influenced likelihood of the kin keeper receiving a pap smear (OR=13.262, 95%CI=3.21–54.83, p=0.0004), and proportion of the network that have gotten a pap in the past three years (OR=39.92, 95%CI=10.66–149.573, p<0.0001).

DISCUSSION

In this analysis, we assessed the influence of various network structural and behavioral predictors on individual’s cancer screening adherence among minority women. Results from the present analysis align with previous literature that suggests social support and network behaviors play an important role in promoting cancer screening (Farhadifar, Taymoori, Bahrami, & Zarea, 2015; Jensen, Pedersen, Andersen, & Vedsted, 2016; C. A. Latkin & Knowlton, 2015). To the best of our knowledge, existing analyses have primarily focused on an individual’s or dyad’s perceived support; in contrast to our analysis which combines all network member’s perceptions of support. This approach relies on the hypothesis that bringing women together and increasing perceptions of social support across female family members could help improve screening rates over time, making for a more sustainable intervention effect.

Network behaviors were strong influencers of likelihood to have had a mammogram and pap smear. Our analyses revealed that network’s rates of mammogram had a positive influence on women’s likelihood to have had a mammogram in the past 12 months, but related behaviors (pap smears) did not positively influence mammogram screening levels. Similarly, kin keeper’s level of pap screening was positively influenced by network-level of having ever gotten a pap smear and pap smears in the past three years, as well as network receiving a clinical breast exam. The direct relationship between network- level behavior on a woman’s likelihood to complete the same behavior align with previous literature. Perceptions of network member’s behaviors tend to lead to social pressure to perform (or not perform) a certain behavior(Lawal, Murphy, Hogg, & Nightingale, 2017). Once established, social norms tend to be self-maintaining. Similar to findings about social support and social norms in previous literature, our results suggest that shared understanding at the family level is an important opportunity for intervention. While it would be possible to address individual-level perceptions, addressing normative beliefs and behaviors at the family level could potentially allow for more sustainable intervention effects. Indeed, networks are commonly sources for health information and normative influence, thus network based approaches could be used to help conceptualize how norms may be altered by key early adopters in a family and then subsequently maintained by the remaining majority of the network. (C. Latkin et al., 2009; C. A. Latkin & Knowlton, 2015; Reiter & Linnan, 2011; Tavasoli, Kane, Chiarelli, & Kupets, 2018).

We also found noteworthy racial differences in the ways networks engage with certain screening behaviors. Arab women were less likely than African American networks to have completed self-breast exams, ever gotten a pap screening, or a pap screening in the past three years. Latina networks were also less likely to have gotten a pap screening in the past three years as compared to African American networks. There were not racial differences in clinical breast exam or having gotten a mammogram in the past 12 months. Prior studies have suggested that key factors influencing pap screening among Arab women include knowledge of screening and prevention, immigration and acculturation, and attitudes and beliefs about screening. (Abboud et al., 2017; Donnelly et al., 2013) Our findings are unique, as they specifically compare networks of Arab women screening behaviors to other racial and ethnic minorities. Previous studies typically assess for differences in comparison to non-Hispanic white individuals and have suggested that minority screening rates are comparable. (Abboud et al., 2017) Our findings demonstrate that there are many noteworthy differences among minority populations that can be addressed to improve pap screening behaviors in particular.

There are several study limitations to note. First, all outcomes were self-reported by women. We were unable to link findings to clinical data, thus, our levels of compliance to screening behaviors may be over-estimated. Because this study was an egocentric network study and not a sociocentric network study, it was not possible to estimate the kin keeper position in the whole network or the structure of the whole network. We were only able to determine the network information based on the women who were recruited and participated in the family network intervention. Thus, these individuals may have stronger ties to the kin keeper than other women or family members who were not included as part of the intervention. In addition, the family network members who were included in the study may have had an interest in health and have been more likely to be compliant with screening recommendations. Definitions of family are important and may have influenced our findings. The present analysis focuses on blood relatives; however, other definitions of family exist (e.g., family based on kinship). These individuals who are not blood relatives but considered close to the family may also have a strong influence on health behaviors and decisions. Additionally, we were limited in statistical power to complete certain analyses. For example, we were unable to assess for racial differences in our final models due to limited sample size. Finally, our study focused on satisfaction with family communication and did not identify different types of social support (emotional, instrumental, informational) but future studies could consider ways that specific types of social support at the network level influence an individual’s likelihood to complete screening behaviors.

Despite these limitations, the present analysis sheds light on family network characteristics that influence women’s screening behaviors in a sample of medically underserved women. We focused on women’s central networks, that is, those who were close relatives and engaged consistently with family members. Future studies should consider ways that information from the interventions disseminated throughout female’s family networks to further assess the reach of interventions in family contexts.

Supplementary Material

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13187_2020_1879_MOESM2_ESM

Table 3.

Multivariable Models

Had mammogram past 12 months
OR LL UL p-value
Greater than 50% of Network Have Gotten Mammogram in Past 12 Months 8.522 2.858 25.414 0.0001
Pap in last 3 years
Greater than 50% of Network Have Completed Clinical Breast Exam 7.537 2.163 26.261 0.0015
Pap in last 3 years
OR LL UL p-value
Greater than 50% of Network Have Ever Gotten Pap 13.262 3.208 54.829 0.0004
Pap in last 3 years
OR LL UL p-value
Greater than 50% of Network Have Gotten Pap in Last 3 Years 39.922 10.655 149.574 <.0001
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*

all models control for socio-demographic differences

Footnotes

Publisher's Disclaimer: This Author Accepted Manuscript is a PDF file of a an unedited peer-reviewed manuscript that has been accepted for publication but has not been copyedited or corrected. The official version of record that is published in the journal is kept up to date and so may therefore differ from this version.

Conflict of Interest: None to report

Contributor Information

Caitlin G. Allen, Behavioral Sciences and Health Education, Rolling School of Public Health, Emory University, 1518 Clifton Road NE, Atlanta, GA 30308.

David Todem, Department of Epidemiology and Biostatistics, College of Human Medicine, Michigan State University.

Karen Patricia Williams, College of Nursing, The Ohio State University.

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