Adverse Childhood Experiences and Diabetes: Testing Violence and Distress Mediational Pathways in Family Medicine Patients

Abstract

Type 2 diabetes mellitus (diabetes) is increasing in frequency and creating a significant burden on the United States healthcare system. Adverse childhood experiences (ACE) and interpersonal violence (IV) have been shown to have detrimental effects on mental and physical health. How ACE can influence IV as an adult and how this can influence the management of diabetes is not known. The purpose of the current study is to understand the relationship between violence and social determinants of health (SDoH), and its effect on patients with type 2 diabetes mellitus. A practiced-based research network (PBRN) of family medicine residency programs was utilized to collect cross-sectional data from seven family medicine residency program primary care clinics. In total, 581 participants with type 2 diabetes were recruited. A serial/parallel mediation model were analyzed. The majority of participants (58.3%) had a Hemoglobin A1c (HbA1c) that was not controlled. ACE was associated with an increase in Hurt-Insult-Threaten-Scream (HITS) scores, which in turn was positively associated with an increase in emotional burden, and finally, emotional burden decreased the likelihood that one’s HbA1c was controlled (Effect = −.054, SE = .026 CI [−.115, −.013]). This indirect pathway remained significant even after controlling for several SDoH and gender. The impact of ACE persists into adulthood by altering behaviors that make adults more prone to experiencing family/partner violence. This in turn makes one more emotionally distressed about their diabetes, which influences how people manage their chronic condition. Family physicians should consider screening for both ACE and family/partner violence in those patients with poorly controlled diabetes.

Keywords

Child abuse domestic violence mental health and violence diabetes

Introduction

Type 2 diabetes mellitus (diabetes) is a growing problem with over 415 million individuals living with diabetes worldwide (International Diabetes Federation, 2015). Diabetes affects over 34 million adults in the United States with 1.5 million new cases each year, and the disease was ranked seventh in causes of death in 2018, with over seven million adults remaining undiagnosed (American Diabetes Association, 2020).

In 2016, diabetes was the sixth most common primary diagnosis among all primary care visits (Rui & Okeyode, 2016). Management of diabetes presents a challenge for both physicians and patients. Diabetes self-management can be seen as a multifactorial endeavor that includes lifestyle changes and glycemic control to prevent microvascular complications (e.g., retinopathy, nephropathy, neuropathy), macrovascular complications (e.g., myocardial infarction, peripheral arterial disease, and stroke), and minimization of psychological and physical distress (Chatterjee et al., 2017). The potential barriers to successful diabetes management that physicians must consider include patients’ beliefs about their diabetes, culture, language, health literacy, financial resources, social support, and co-morbidities (Nam et al., 2011). Physicians must also be aware of their own biases regarding knowledge and perceptions about diabetes when it comes to treatment changes or patient adherence (Nam et al., 2011). This requires effective communication skills, a keen awareness of patient priorities, and a recognition of the role that diabetes management plays in their life (Greenfield et al., 2011).

Adverse childhood experiences (ACE) occur during the first 18 years of life and range from household dysfunction to child neglect and abuse, which in turn may cause trauma or toxic stress (Pantell et al., 2019). Multiple ACE are linked to increased risk for ischemic heart disease, cancer, chronic lung disease, skeletal fractures, and liver disease (Pantell et al., 2019). Individuals with the co-occurrence of ACE and diabetes have an increased risk of mortality as adults, suggesting that these factors together may compound poor diabetes outcomes (Campbell et al., 2019). High ACE scores are also strongly associated with violence victimization as an adult, suggesting a generational effect of ACE that locks families into cycles of adversity and poor health (Hughes et al., 2017). To this end, it is important to understand how interpersonal violence can exacerbate chronic health conditions.

Exposure to interpersonal violence (IV) in adulthood has been linked to an increased risk of developing diabetes (Caleyachetty et al., 2015; Pantell et al., 2019; Xu et al., 2018). Increased risk of diabetes onset has been associated with both physical and psychological IV (Mason et al., 2013), while IV has been linked to increases in BMI, especially for those who are depressed (Mason et al., 2017). While no studies have examined the relationship between violence and diabetes management, numerous studies have shown that the sequelae of violence, such as depression (Dirmaier et al., 2010) and post-traumatic stress disorder (Dutton et al., 2006), are associated with poor glycemic control (Gregory et al., 2016; Taggart Wasson et al., 2018). Research evaluating the effects of IV have noted adverse health outcomes as a result of psychological and physical IV (Coker et al., 2000). Specifically, psychological IV in women has been associated with disability, arthritis, chronic pain, among other health issues (Coker et al., 2000), and extended exposure to IV is associated with worse health outcomes (Bonomi et al., 2006). Vives-Cases and colleagues (Vives-Cases et al., 2011) have assessed severity of IV among women and found that poor self-perceived health and psychological distress were greater among those with high severity IV, indicating poorer health (Vives-Cases et al., 2011). Taken together, it is important to consider the relationship between IV and ACE, especially when considering health.

Recent studies have focused on multiple types of childhood maltreatment and have found that emotional abuse (Teicher et al., 2006), sexual abuse (Reckdenwald et al., 2013; Trabold et al., 2015), neglect (Teicher & Vitaliano, 2011), and witnessing sibling violence (Milaniak & Widom, 2015) are significantly associated with IV in adulthood. In college students, an increase in the number of ACE one experiences made them more likely to experience physical violence, sexual violence, psychological violence, and stalking in the last 12 months (Cprek et al., 2020). In their review, Montalvo-Liendo and colleagues (2015) noted that women who experienced ACE were more likely to experience intimate partner violence and were more likely to have poor mental and physical health. The causal pathways to which one who experiences ACE leads to IV in adulthood are not well understood, however, a large body of evidence suggest that individuals who are the victims of childhood abuse are more likely to be re-victimized as adults (Aakvaag et al., 2017; Montalvo-Liendo et al., 2015). It is important to note, social aspects (i.e., income, education, neighborhood safety) may play a role in poor management of diabetes and may interact with experiences of violence to exacerbate diabetes.

Social determinants of health (SDoH) are factors across the lifespan of an individual that are shaped by economic (i.e., socioeconomic status [SES]) and political elements at local and national levels (Hill-Briggs et al., 2021), and are a significant contributor to diabetes management and distress. Low SES has been shown to impact chronic disease development and contribute to an increase in mortality and morbidity (Adler & Newman, 2002). For instance, Agardh and colleagues (2011) found that individuals who had a low education, occupation, and income status were likely to develop diabetes. Individuals of low SES are less likely to have health insurance, which hinders them from accessing preventive care. Further, the quality of care received by individuals with low SES has been shown to be inferior to that of individuals of high SES (Brown et al., 2004). Neighborhood safety is another aspect of SDoH that has also been associated with diabetes. Gariepy and colleagues (2013) found that those who perceived their neighborhoods to have higher physical and social order were less distressed about their diabetes than those who had a low perception of the physical and social order of their neighborhoods.

The current study explored the relationship between ACE, IV (i.e., family/partner violence), and management of one’s diabetes. The Biological Embedding of Childhood Adversity Model (BECAM) has proposed that ACE leads to fundamental changes to the bodies of the victims by increasing inflammatory responses (Miller et al., 2011). The authors propose this is achieved by modifying cytokine responses and dysregulating hormonal signals to increase the inflammatory response, which may lead to the development of chronic diseases (e.g., diabetes) in adulthood (Huffhines et al., 2016; Miller et al., 2011). The authors further hypothesize that the pro-inflammatory response is further exacerbated by behavioral alterations (e.g., social rejection, evoking conflict, seeking immediate gratification, and inability to develop/maintain relationships in adulthood) as a result of ACE (Miller et al., 2011). Though not explicitly stated in the BECAM, it is possible that these altered behaviors, resulting from experiencing ACE, make one more prone to be a victim of IV as an adult, which may exacerbate diabetes distress and result in poor management. It is important to note that no study has explored the relationship between ACE and IV as it relates to being distressed about one’s diabetes, and as discussed above, the literature has primarily focused on the development and management of diabetes as it pertains to having experienced ACE and/or IV.

A violence-distress pathway was hypothesized for this study. We hypothesized that ACE would make one more prone to experience IV as an adult, which would make one more distressed about their diabetes, and would result in not having a controlled Hemoglobin A1c (HbA1c). We tested a mediational pathway (Figure 1) to explore if the type of diabetes distress (emotional burden, physician distress, and interpersonal distress) would be impacted more by ACE and family/partner violence. Our model included SDoH control variables (Gurrola & Ayón, 2018; NEJM Catalyst, 2017) to test if the hypothesized relationships would be maintained or if some other SDoH variable would account for this relationship.

Figure 1.

Indirect Pathway Effects and Confidence Intervals. Note. Bold pathways indicate significant specific indirect pathways. ACE = Adverse Childhood Experiences, HITS = Hit Insult Threaten Scream, HbA1c = Hemoglobin A1c.

Methods

A practiced-based research network (PBRN) of family medicine residency programs was utilized to collect data from multiple sites. A total of seven family medicine residency programs were used to collect data for this study within their primary care clinic sites. This project received approval by the Institutional Review Board (IRB) for Human Subjects Protection by one of the participating residency programs in the PBRN and served as the IRB of record that the other programs relied upon. Cross-sectional data was collected to explore how SDoH influence diabetes management in a sample of family medicine patients. Participants were included in this study if they had type 2 diabetes and if they were between the ages of 18–75. Participants who had cognitive deficits were excluded. Study participants were recruited at standard primary care clinic visits, and data collection lasted approximately 6 months. As part of the consenting process, participants gave the study team permission to access their electronic medical record to log their most recent HbA1c. A total of 581 participants were recruited for this study.

Measures

The ACE Survey (Felitti et al., 1998) is a 10-item survey where participants self-report childhood abuse that occurred before the age of 18. The ACE assesses several domains of child abuse such as neglect, physical, sexual, and verbal. Participants were asked to respond to these questions with a “Yes = 1” and “No = 0.” Items were summed to create an ACE score. The reliability of the ACE Survey was in the acceptable range (Cronbach’s α = .904; Table 1).

Table 1.

Correlations, Means, and Cronbach’s Alphas for Variables in Mediation Model.

Variables	1	2	3	4	5	6	7	8	9	10	11
1. HbA1c Controlled
2. Emotional diabetes distress	−.258***
3. Physician diabetes distress	−.097*	.292***
4. Interpersonal diabetes distress	−.086	.469***	.373***
5. ACE	−.046	.231***	.060	.250***
6. HITS	.069	.249***	.161**	.387***	.287***
7. Generational status	−009	−.028	−.085	.086	.198***	.122*
8. Income	.104*	−.245***	−.214***	−.143**	−.034	−.077	.078
9. Education	.002	−.098*	−.047	.031	−.033	.069	.153***	.366***
10. Neighborhood safety	−.005	.190***	.082	.235***	.211***	.242***	.024	−.154**	−.032
11. Gender	−.002	−.085	−.052	−.109*	−.028	−.066	−.005	.129**	.027	−.093*
Mean	.417	1.881	1.163	1.345	1.721	4.974	.803	.529	.505	.180	.393
SD	.494	.855	.430	.647	2.147	2.028	.398	.500	501	.385	.489
Cronbach’s α	—	.904	.838	.867	.781	.702	—	—	—	—	—

The Hurt-Insult-Threaten-Scream (HITS) (Shakil et al., 2005; Sherin et al., 1998) is a 4-item screening tool used in a primary care setting to assess IV. The participants used a 5-point Likert scale ranging from “1 = Never” to “5 = Frequently” to respond to questions asking how often anyone, including family has physically hurt, insulted, threatened, and/or screamed at them within the last 12 months. Items were summed to create a HITS score. The reliability of the HITS was an acceptable range (Cronbach’s α = 0.838; Table 1).

The Diabetes Distress Scale (DDS) is a 17-item scale that measures distress related to having diabetes (Polonsky et al., 2005). The total score and the score for the individual subscales is derived by adding the individual items and dividing them by the number of items. There are four subscales that measure emotional burden, physician-related distress, regimen-related distress, and interpersonal distress. Examples of items include, “Feeling that diabetes is taking up too much of my mental and physical energy every day” and “Feeling that diabetes controls my life” (Polonsky et al., 2005). For the purposes of this study, only emotional burden, physician-related distress, and interpersonal distress were considered. Reliability for all of the subscales was in acceptable ranges (Table 1).

Primary Outcome

Participants’ most recent HbA1c was used as the primary outcome for this analysis. HbA1c was pulled from the patient’s electronic medical record the day of their visit to the clinic. Only the most recent measure of HbA1c was used. HbA1c is measured twice a year and is an average of glycemia over 3 months (American Diabetes Association, 2021). The average number of days between the most recent HbA1c value and survey completion was 152.78 (N = 559, SD = 9.11) or approximately 5 months. An HbA1c less than 7.0 was considered controlled for those under the age of 65 and an HbA1c under 8.0 was considered controlled for those aged 65 and over (Kirkman et al., 2012). It was decided to dichotomize HbA1c as what constitutes a controlled value varies by age. Using guidelines described by Kirkman and colleagues (Kirkman et al., 2012), participants were dichotomized into HbA1c controlled group and HbA1c not controlled group. In total, 222 (41.7%) participants had a controlled HbA1c and 310 (58.3%) had an HbA1c that was not controlled.

Statistical Analysis

All statistical analyses were performed using SPSS version 26. A parallel/serial mediation model using cross-sectional data were carried out to examine the indirect effect on the HbA1c variable. In the mediation analyses, the SPSS macro, PROCESS (Hayes, 2017), was used to carry out the analyses. The PROCESS model 81 (parallel/serial mediation) was used, and 5000 bootstrapped samples were used to construct 95% bias corrected confidence intervals (CI) for the indirect effects. Significance of the effects is indicated by the 95% CI not containing a zero value. The SDoH variables were dichotomized and included in the model as control variables. The variables included: monthly income ($0 to $1750 vs. $1750 and higher), education (less than high school vs. high school and any post high school education), generational status (first generation vs. second/third generation), and concerns about neighborhood safety (Yes and No; Table 2). Considering that women are often the victims of IV, gender was added as a control variable in our model (Iverson et al., 2013; McGruder-Johnson et al., 2000; Mendenhall & Jacobs, 2012). The independent variable and the mediators were all transformed using a square-root transformation to avoid violations of normality. Individuals with missing data were removed from the analysis using the listwise deletion method.

Table 2.

Demographic and Social Determinants of Health.

Variables	N (SD or %)
Age	57.3 (11.1)
Race
White	258 (49.0)
African American	146 (27.8)
Other	96 (18.3)
Asian	17 (3.2)
American Indian/Alaskan Native	9 (1.7)
Ethnicity
Hispanic	273 (50.7)
Non-Hispanic	265 (49.3)
Gender
Male	202 (39.5)
Female	310 (60.4)
Education
Less than high school	90 (16.2)
High School/GED	172 (30.9)
Some college	128 (23.0)
Junior College/Associate	35 (6.3)
Technical/Vocational	31 (5.6)
Bachelor’s Degree	55 (9.9)
Graduate/Professional school	45 (8.1)
Income during the past month
$0–$500	24 (5.1)
$501–$750	53 (11.3)
$751–$1000	50 (10.6)
$1001–$1500	73 (15.5)
$1501–$1750	33 (7.0)
$1751–$2000	26 (5.5)
$2001–$2500	36 (7.6)
$2501–$3000	38 (8.1)
More than $3000	138 (29.3)
Generational status
First generation	92 (19.7)
Second generation	85 (18.2)
Third Generation/Later	290 (62.1)
Neighborhood safety concerns
Yes	99 (18.1)
No	448 (81.9)

Note. The Square-root transformed values were used in the correlation table; however, the means and SDs are the untransformed values. ACE = Adverse Childhood Experiences, HITS = Hit Insult Threaten Scream, HbA1c = Hemoglobin A1c.

Results

The average age of the sample was 57.3 years and over half (51%) identified as a race other than White (Table 2). Half (50.7%) of the total sample identified as Hispanic and most participants (70.1%) had an education level of “Some College” or less. Table 1 shows the correlations between the variables under analysis. Hemoglobin A1c correlated negatively with EB (r [1, 501] = −.258, p < .001) and PD (r [1, 493] = −.097, p = .032). This negative relationship was stronger for the EB variable. With the exception of PD, ACE correlated positively with EB (r [1, 516] = .231, p < .001) and ID (r [1, 510] = .250, p <.001). Hurt-Insult-Threaten-Scream correlated positively with all three diabetes distress subscales (Table 1).

Mediation Analysis

The results of the mediation analysis are presented in Table 3, and Figure 1 presents the pathways tested in the serial/parallel model along with regression coefficients and p-values. Model summaries are presented in the Online Appendix. There was a significant specific indirect effect of ACE → HITS → HbA1c (Effect = .037, SE = .023, CI [.004, .091]). When controlling for the other mediators in the model and the covariates, having a higher ACE score was associated with a higher HITS score, which made it more likely to have an HbA1c controlled. There was a significant indirect effect of ACE → EB → HbA1c (Effect = −.054, SE = .026 CI [−.115, −.013]). When controlling for the other mediators in the model and the covariates, a participant who had a higher ACE score increased one’s EB, which then made it less likely to have HbA1c controlled. A significant indirect effect was also found for ACE → HITS → EB → HbA1c (Effect = −.015, SE = .008 CI [−.034, −.003]). As ACE scores increased, the HITS score increased, HITS then increased EB, which made it less likely that HbA1c was controlled. No other specific indirect effects were significant and the direct and total indirect effect were both non-significant (Table 3).

Table 3.

Indirect Pathway Effects and Confidence Intervals.

Model 1 Specific Indirect Effects	Effect	SE	95% CI
ACES → HITS → HbA1c	.037	.023	[.004, .091]
ACE → emotional burden → HbA1c	−.054	.026	[−.115, -.013]
ACE → physician distress → HbA1c	−.003	.010	[−.033, .007]
ACE → interpersonal distress → HbA1c	−.005	.010	[−.029, .010]
ACE → HITS → emotional burden → HbA1c	−.015	.008	[−.034, -.003]
ACE → HITS → physician distress → HbA1c	−.002	.004	[−.014, .002]
ACE → HITS → interpersonal distress → HbA1c	−.004	.006	[−.019, .007]
Direct effect	−.041	.062	[−.162, .081]
Total indirect effect	−.046	.033	[−.122, .012]

Note. Bold 95% CI values indicate significance. ACE = adverse childhood experiences, HITS = hit insult threaten scream, HbA1c = hemoglobin A1c.

Discussion

The current study suggests that experiencing ACE in childhood makes one more likely to experience violence as an adult, which negatively affects health. For people with diabetes, as ACE increased so did the instances of IV. This led to an increase in emotional distress over their diabetes, which resulted in a lower likelihood that their HbA1c was controlled. Previous studies have linked ACE with the development of type 2 diabetes (Huffhines et al., 2016; Hughes et al., 2017) and other chronic diseases and IV to chronic diseases (El-Serag & Thurston, 2020; Mathew et al., 2013; Santaularia et al., 2014); but this is the first study that goes beyond an association of ACE and IV with diabetes to explore a possible pathway in which ACE and IV influence diabetes management in adulthood.

Previous research has linked the development of metabolic syndrome (Lee et al., 2014; Pedersen et al., 2016) and diabetes (Huang et al., 2015) to ACE, which may be due to physiological (Baumeister et al., 2016; Rosmond, 2005) and behavioral changes, and may be further exacerbated by abuse incurred as an adult as this study shows. Research in childhood trauma and ACE has shown that those who experience ACE or violence are more prone to be re-victimized as adults (Augsburger et al., 2019; Briere et al., 1997). Additionally, the health of victims of family/partner violence is adversely affected by violence (Black, 2011; Bonomi et al., 2006; Breiding et al., 2008; Coker et al., 2005), and may make one more prone to developing diabetes (Mason et al., 2013), which may be further exacerbated by having a history of ACE. As stated in the BECAM, ACE may alter immune inflammatory responses and behavioral responses to make one more prone to developing diabetes as an adult (Miller et al., 2011). Behavior alterations may result in a higher probability of re-victimization as an adult, which compounded with changes to the immune response that occurred as children may be more detrimental to the health of the adult. The current study provides evidence that diabetes may be further affected by family/partner violence, which made participants more emotionally distressed by diabetes and resulted in a decreased likelihood of having diabetes controlled. It is important to note that mental health factors (e.g., depression, anxiety, post-traumatic stress disorder) were not measured in this study and may serve as additional mediators in this model.

The link between ACE and family/partner violence highlights the need for screening in a primary care setting, especially for patients having difficulty managing their diabetes. Currently, the U.S. Preventive Services Taskforce recommends screening for IV in women of reproductive age, but gives no recommendations for screening of ACE (U.S. Preventive Services Task Force, 2018). It is important to note that screening for ACE is controversial, with some physicians noting potential harms to their patients and to their physician/patient relationship, but there is little or no evidence to support this notion (Campbell, 2020). Screening for either IV or ACE may present an incomplete picture of the patient’s history or cycle of violence. Adverse childhood experience and IV may be currently affecting patients’ mental health and knowing the severity of distress is vital. Understanding the extent of the trauma experienced by the patient may allow physicians to better understand their patients’ health and refer them to behavioral services as necessary. More research is needed to explore the link between ACE and HITS within a primary care setting, but it is possible that ACE could be a “first step” in assessing trauma, in that a positive screen for ACE could lead to further screening using the HITS screener to provide physicians with greater insight into the historical context of their patient.

Primary care has been labeled the “de facto” mental health service (Kessler & Stafford, 2008), but several barriers (e.g., clinical, administrative, financial) exist that prevent physicians from addressing mental and behavioral health issues, and many physicians may be resistant to screen for SDoH, ACE, and IV, which may prevent these issues from being addressed. In a survey of 258 clinicians, 84% showed support for SDoH screening in a clinical setting, but only a minority (41%) expressed confidence in the ability to address SDoH (Schickedanz et al., 2019). Two of the most significant barriers that have been identified include time constraints and lack of resources (Campbell, 2020). However, a feasibility study on screening for ACE in a family medicine setting found that it added five or less minutes to the length of the visit and physicians felt they gained new information about their patients (Glowa et al., 2016). A recent study examining intimate partner violence in primary care found that 92.1% of young men surveyed thought it was important for their health care clinicians to ask about victimization, however, only 13% reported being asked about victimization (Walsh et al., 2020). It could be argued that screening for DDS is sufficient to identify an underlying problem with diabetes that can later be addressed by a behavioral health specialist without the physician having to take time to screen for ACE or IV. However, considering the association between ACE and IV, as discussed above, with other chronic conditions, knowing a patient’s previous history with ACE and/or current experiences with IV may better inform the management of diabetes and other comorbid conditions the patient may have. It is to this end that an integrated medical-behavioral health model where physicians work closely with a behavioral health specialist who provides trauma-informed care and behavioral health resources may lead to better outcomes (Asarnow et al., 2015). More research is needed on screening historical abuse, present abuse, and targeted interventions in integrated primary care to address historical or present trauma.

There are several limitations in this study that are worth noting. The utilization of the PBRN network was an attempt to maximize the diversity of the sample and avoid bias that could occur from sampling a single site. However, 49% of our sample identified as White and the majority of participants had access to medical insurance. This may have biased the results of this study, in that our results may be unique to White individuals of a higher SES. It is important to note that despite this, our sample contained a large number of women, individuals who identified as Hispanic, and first and second generation immigrants, but future research should address how these relationships manifest in racially and economically diverse individuals. Additionally, participants were recalling traumatic events that in some instances occurred decades before they enrolled in the study and are subject to recall bias (Colman et al., 2016). Despite potential biases that occur with retrospective reports of ACE, research has shown agreement between prospective and retrospective reports on ACE, and the likelihood of an individual making a false account of ACE is low (Hardt & Rutter, 2004; Reuben et al., 2016). However, future research should explore this relationship with documented cases of ACE. Participants’ most recent HbA1c was taken from their electronic medical record, but to what extent the participants were aware of their most recent HbA1c is unknown. Additionally, HbA1c is not static. The index HbA1c may be controlled or uncontrolled, but the previous measurements may not have been categorized as such. It is possible that IV, measured by HITS over the course of 12 months, occurred after HbA1c was measured or that the IV had ceased by the time HbA1c was measured. Future research should explore the relationship between HbA1c and IV in real time. Further, it could be argued that not having one’s HbA1c controlled was the cause of the increased EB. Finally, the current study used cross-sectional data for the mediation analysis, which limits the causal inferences that can be made with the current model. Future research on this topic should explore these effects over time in order to ascertain the causal relationship between these variables, as well as diabetes control over years rather than at a single point in time.

Conclusion

The current study suggests that ACE continue to influence IV and physical health many years after it has occurred. Family medicine physicians should consider screening for both ACE and IV, especially in instances where patients are struggling to manage their diabetes despite appropriate interventions. Physicians may feel uncomfortable and/or unwilling to address ACE and IV in their patients, and an integrated medical-behavioral health model may be necessary when addressing these experiences. With an integrated model, physicians can identify ACE and IV and refer patients to a behavioral health specialist or consultant that works closely with the care team to begin to address the patient’s care needs using a holistic approach on a same-day basis. In general, gaining a greater understanding of our patients’ life context could help us better care for patients leading to improved health outcomes.

Supplemental Material

sj-pdf-1-jiv-10.1177_08862605221076536 – Supplemental Material for Adverse Childhood Experiences and Diabetes: Testing Violence and Distress Mediational Pathways in Family Medicine Patients

Supplemental Material, sj-pdf-1-jiv-10.1177_08862605221076536 for Adverse Childhood Experiences and Diabetes: Testing Violence and Distress Mediational Pathways in Family Medicine Patients by Chance R. Strenth, Albert Mo, Neelima J. Kale, Philip G. Day, Leo Gonzalez, Ronya Green, Inez I. Cruz, and Frank D. Schneider in Journal of Interpersonal Violence

Footnotes

Acknowledgments

Acknowledging contributions from 10 clinics in seven RRNeT residency programs and their accompanying medical students. With funding from the Texas Academy of Family Physicians Foundation (TAFP-F) and the Institute for Integration of Medicine and Science (IIMS), UT Health San Antonio, under the National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH) through Grant UL1 TR002645. The content is solely the responsibility of the authors and does not necessarily represent the official views of the TAFP-F or NIH. The first author would also like to acknowledge the support he received from Tenzin Tsewang and Norbu Tsewang during the writing of this manuscript.

Declaration of Conflicting Interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Financial Support: The Residency Research Network of Texas (RRNET) has support from the Texas Academy of Family Physicians Foundation (TAFP-F), the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health, through Grant UL1 TR002645. The content is solely the responsibility of the authors and does not necessarily represent the official views of the TAFP-F or NIH.

ORCID iD

Chance R. Strenth

Supplemental Material

Supplemental material for this article is available online.

Authors Biographies

Chance Strenth, PhD, is a Senior Research Associate in the Department of Family and Community Medicine at UT Southwestern Medical Center. His research focus has been in behavioral health where he has specifically focused on pain and behavioral endocrinology. Dr. Strenth has recently been focusing more on health disparities and their impact on health.

Albert Mo, MD, is a resident at Memorial Hermann Family Medicine Program in Sugar Land. He recently graduated from UT Southwestern Medical Center where he conducted research that examined the role that adverse childhood events and SDoH play in the management of chronic disease. He is interested in SDoH, behavioral health, as well as sports medicine.

Neelima Kale, PhD, MD, MBA, FAAFP is an Associate Professor and Vice Chair of Clinical Affairs in the Department of Family and Community Medicine at the University of Kentucky. Her research interests are primarily in chronic pain and the current Opioid Epidemic.

Philip Day, PhD is an Assistant Professor and Associate Director of Education at University of Massachusetts Chan Medical School. A trained philosopher, his work focuses on community-based participatory research, medical ethics, and healthcare for the underserved. He strives to identify and clarify ethical issues within primary care practice to better inform the training of the next generation of healthcare professionals.

Leo Gonzalez, MA, is a Research Associate in the Department of Family and Community Medicine at UT Southwestern Medical Center. His research has focused on the role of childhood poly-victimization on suicide ideation. He is interested in evaluating the role of ACE and its effects on physical and behavioral health.

Ronya Green, MD, MPH is the Program Director of the TriStar Family Medicine Residency Program in Nashville, TN. Dr. Green works daily to inspire the next generation of family physicians to provide comprehensive, compassionate medical care and to work towards diminishing health disparities among the disenfranchised and underrepresented. Her research focuses on the implications of social and moral determinants of health in the management of chronic disease and preventive medicine.

Inez I. Cruz, PhD, LMSW, serves as the Director of Professional Development for the Department of Family and Community Medicine at UT Health San Antonio. Dr. Cruz is a trained qualitative health services researcher in primary care, focusing on the development of compassionate healthcare delivery. Research conducted by Dr. Cruz strives to better understand how people make sense of their illnesses in their communities.

F. David Schneider, MD, MSPH is a family physician, Chair and Professor, and is the Perry E. Gross Distinguished Chair in Family and Community Medicine at UT Southwestern Medical Center. He has taught about and done research on the adverse effects of violence and toxic stress on health, and was the founding president of the Academy on Violence and Abuse.

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