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J Pediatr Psychol. 2011 March; 36(2): 196–205.
Published online 2010 August 24. doi:  10.1093/jpepsy/jsq071
PMCID: PMC3042599

From Caregiver Psychological Distress to Adolescent Glycemic Control: The Mediating Role of Perceived Burden around Diabetes Management

Abstract

Objective To examine whether perceived caregiver burden around diabetes management mediated the relationship between caregivers’ psychological distress and adolescents’ glycemic control. Methods Across three visits spanning 9 months, caregivers of 147 adolescents with type 1 diabetes completed measures of anxiety and depressive symptoms and a measure of perceived burden specific to diabetes management. Adolescents’ glycemic control was also measured. Results Perceived burden mediated the relationship between caregiver depressive symptoms and adolescents’ glycemic control. The overall model was significant, F(10,132) = 5.0, p < .001, R2 = 0.27. Fifty percent of the relationship was explained by diabetes-specific burden. The relationship between caregiver anxiety symptoms and adolescent glycemic control was partially mediated by diabetes-specific burden, F(10,133) = 5.7, p < .001, R2 = 0.30, explaining 26% of this relationship. Discussion A variable linking caregiver psychological distress to adolescent glycemic control is perceived caregiver burden around diabetes management. Implications for clinical practice include targeting caregiver psychological functioning and reducing global and diabetes-specific distress.

Keywords: adolescents, diabetes, parents, health care services

Type 1 diabetes is a common chronic disease, affecting one in 500 youth (SEARCH for Diabetes in Youth Study Group, 2006; The National Institute of Diabetes and Digestive and Kidney Diseases, 2005) with approximately 15,000 new diagnoses annually in the United States (Dabelea et al., 2007). Treatment of type 1 diabetes includes insulin administration, blood glucose monitoring (BGM), and close attention to dietary intake and physical activity. Although significant advancements in treatment approaches and technologies have been made (Tamborlane et al., 2008), adolescents with type 1 diabetes continue to exhibit suboptimal glycemic control (Danne et al., 2001; Springer et al., 2006). A number of individual (e.g., growth, psychological functioning) and family factors contribute to suboptimal control (Amiel, Sherwin, Simonson, Lauritano, & Tamborlane, 1986; Moreland et al., 2004). However, few investigations have examined the role of caregiver psychological factors in relation to adolescent glycemic control (Anderson, Ho, Brackett, Finkelstein, & Laffel, 1997; La Greca et al., 1995).

A wealth of empirical evidence in the literature has linked caregiver psychological factors to poor child outcomes. The child outcomes cut across academic, behavioral, and emotional domains (Cicchetti, Rogosch, & Toth, 1998; Cytryn et al., 1984; Hay, Pawlby, Angold, Harold, & Sharp, 2003; Lyons-Ruth, Connell, Grunebaum, & Botein, 1990; Orvaschel, Weissman, & Kidd, 1980; Radke-Yarrow, Zahn-Waxler, Richardson, Susman, & Martinez, 1994; Silverstein, Augustyn, Cabral, & Zuckerman, 2006; Walker et al., 2007). For example, Larson and colleagues (2008) found that multiple social risks, including “low maternal mental health,” predicted poor child health in the 2003 National Survey of Children’s Health. In addition, caregiver depressive symptoms have been linked with negative health outcomes in adolescents. In a large sample of inner-city adolescents with asthma, there was a twofold increase in child hospitalization in the presence of caregiver depressive symptoms (Weil et al., 1999). Furthermore, while not specifically examining health outcomes in a younger age group with type 1 diabetes, maternal depressive symptoms were related negatively to child quality of life and other indicators of family functioning (Jaser, Whittemore, Ambrosino, Lindemann, & Grey, 2008). Additionally, Cameron, Young, and Weibe (2007) found that elevated levels of caregiver anxiety symptoms were related to suboptimal glycemic control in adolescents with type 1 diabetes. Specifically, maternal trait anxiety was associated with higher A1c levels and greater absenteeism from school and social activities due to diabetes during the subsequent 3 months in younger adolescents. Considered together, both maternal anxiety and depressive symptoms were shown to be associated with negative child health outcomes, although data have been limited in adolescents with type 1 diabetes.

Caregivers play critical roles in managing type 1 diabetes in their adolescents, setting up the potential for caregiver psychological status to affect diabetes-specific health outcomes (Anderson et al., 2009; Berg et al., 2008). For example, a caregiver with depressive symptoms may feel overwhelmed and be uninvolved in critical parts of management. Alternatively, a caregiver experiencing anxiety symptoms may be overly attentive (i.e., hypervigilant) to diabetes care and may engage in constant monitoring. These experiences can be captured as perceived burden specific to diabetes management (Butler et al., 2008; Polonsky et al., 1995). Increases in perceived diabetes-specific burden may subsequently transfer to the adolescent and result in poor health outcomes (i.e., suboptimal glycemic control). For example, a caregiver who had negative feelings about adolescents’ BGM was more likely to have higher levels of perceived diabetes-specific burden (Butler et al., 2008). Interestingly, this investigation also found that perceived burden specific to diabetes management, rather than general caregiver negative affect, was directly related to glycemic control, when controlling for other sociodemographic and diabetes-specific variables. Thus, Butler and colleagues (2008) highlight that a caregiver variable, perceived diabetes-specific burden, is linked to an adolescent’s diabetes-specific health outcome. Also, there is literature linking perceived caregiver burden to caregiver distress in youth with medical conditions, including type 1 diabetes (Canning, Harris, & Kelleher, 1996).

The purpose of the current study was to examine the role of diabetes-specific burden perceived by caregivers as a mediating variable between measures of caregiver psychological distress and adolescents’ glycemic control. Testing this mediation model in a longitudinal dataset provides an opportunity to more strongly infer predictive relationships in contrast to a cross-sectional design where measures are collected concurrently. Specifically, we hypothesized that higher levels of general caregiver distress (e.g., anxiety or depressive symptoms) would lead to higher levels of perceived diabetes-specific burden around diabetes management, which would ultimately lead to suboptimal glycemic control.

Methods

Participants and Procedures

The study population consisted of 147 adolescents (aged 13–18 years) with type 1 diabetes and their primary caregivers, who participated in three study visits. The average length of time between visit 1 and visit 2 was 7.0 months (SD = 1.7); and between visits 2 and 3, 3.4 months (SD = 1.3). Primary caregivers were the caregivers who self-identified as primarily responsible for diabetes management; 130 mothers, 13 fathers, 2 grandmothers, and 2 aunts. All adolescents had a diagnosis of type 1 diabetes according to the practice guidelines of the American Diabetes Association (ADA) (Silverstein et al., 2005) and were receiving care from a multidisciplinary team at a Midwestern pediatric diabetes center. Exclusion criteria included the presence of a major psychiatric or neurocognitive disorder that would inhibit ability to participate; a significant medical disease other than treated thyroid disorders or celiac disease; or the inability to read or understand English. These criteria were assessed during the consent procedure. The participants were drawn from a sample of 163 eligible adolescents and their caregivers who were approached as a convenience sample about participation (agreement rate of 90%). All study procedures were approved by the institutional review board. After obtaining written informed consent from caregivers and consent/assent from the adolescents, a research assistant administered questionnaires during visits 1 and 2. Questionnaires were completed in the diabetes clinic before or after the adolescent’s clinic visit. Then, at visit 3, the adolescent’s glycemic control was measured. A1c levels were measured 3 months after visit 2 because A1c levels are an estimate of glycemic control for the previous 12 weeks, depicted in Figure 1.

Figure 1.
Mediating role of diabetes-specific burden.

Measures of Caregiver Psychological Distress

The State-Trait Anxiety Inventory (STAI) (Spielberger, 1983) was used to measure anxiety symptoms at visit 1. The STAI has 40 items with half related to anxious feelings in general (trait scale). The trait scale was used as a measure of caregiver anxiety symptoms because the current investigation was most interested in capturing levels of general anxiety in caregivers. There was a high degree of internal consistency on the trait scale (coefficient α = .92).

The 20-item Center for Epidemiologic Studies-Depression (CES-D) (Radloff, 1977) scale was used to measure caregiver depressive symptoms at visit 1. This measure is widely used, and large sample normative data and clinical cut-off scores (≥16) are available for the CES-D. There was a high level of internal consistency in this sample (coefficient α = .91).

Measure of Perceived Burden Specific to Diabetes Management

The Pediatric Assessment in Diabetes—Parent version (PAID-P) (Antisdel, 2001; Butler et al., 2008; Polonsky et al., 1995) was used to assess perceived burden related to diabetes management during visit 2. Caregivers rate their level of agreement with 20 statements related to their feelings of burden regarding their child’s diabetes management (e.g., “I feel ‘burned out’ by the constant effort to manage diabetes”) via a six-point Likert’s scale. The total score is computed by summing the total item responses and is considered an indicator of the caregiver’s perceived emotional distress surrounding diabetes management. The PAID-P was developed in the framework of an adult, diabetes-specific burden measure, the Problem Areas in Diabetes (PAID) scale (Polonsky et al., 1995). In a sample of 451 adult females with type 1 and type 2 diabetes, internal reliability of the PAID was high, with good item-to-total correlations Also, the PAID was positively associated with relevant psychosocial measures of distress, including general emotional distress, disordered eating, and fear of hypoglycemia. In addition, the PAID was positively associated with higher A1c levels and negatively associated with reported self-care behaviors. In our study sample, there was a high level of internal consistency for the PAID-P (coefficient α = .85).

Measures of Glycemic Control and Related Sociodemographic Variables

Adolescents’ glycemic control (i.e., A1c values) was measured by the DCA 2000+ during visits 1 and 3 (reference range 4.3–5.7%, Bayer Inc., Tarrytown, NY). Duration of diabetes and mode of insulin administration were obtained from chart review. Family sociodemographic data were obtained from a self-report questionnaire completed by the adolescent’s caregiver during visit 1.

Statistical Analyses

Prior to analysis, data were double entered and cross-checked for accuracy. Descriptive statistics, frequencies, and univariate comparisons were calculated for the sample. Bivariate correlations were run among sociodemographic characteristics and study variables of interest (e.g., anxiety symptoms, depressive symptoms, PAID-P scores). Next, multivariate analyses were run in the general linear model framework to determine if PAID-P scores mediated the relationship between caregiver psychological distress and glycemic control (see Figure 1). Separate models were run for caregiver anxiety and depressive symptoms. Mediator analyses were performed using the Baron and Kenny framework (1986). Presence of mediation was determined by testing whether: (1) the predictor is significantly associated with the mediator, (2) the mediator is related to the dependent variable, and (3) the addition of the mediator to the full model reduces the relationship between the predictor and the dependant variable. The Sobel test detected statistical significance of the mediator and we calculated the percentage of the caregiver psychological distress–glycemic control link accounted for by each psychological variable (Holmbeck, 2002). Covariates in all models included adolescent age, gender (1 = female, 0 = male), ethnicity (1 = identifies as ethnic minority/non-White, 0 = White, not of Hispanic origin), diabetes duration, mode of insulin delivery (1 = insulin pump, 0 = insulin injections); caregiver education level (1 = college degree or higher, 0 = less than a college degree) and marital status (1 = two caregivers in home; 0 = anything other than two caregivers in home); and family insurance status. These covariates have been shown to be related to A1c in previous literature (Lewin et al., 2006; Springer et al., 2006, Svoren et al., 2007); thus, they were included in all models. Post hoc analyses were conducted to examine significant covariates. All analyses were conducted in SASv9.2 (SAS Institute, Cary, NC).

Results

Baseline Participant Characteristics

The study population had a mean age of 15.5 years with a near equal proportion of males and females (see Table I for additional details). Approximately 87% of the sample was White, not of Hispanic origin. The participants had a mean duration of diabetes of 6.0 years at visit 1 (SD = 3.8, range 0.5–16.8 years). The 10 participants who had diabetes duration of <1 year at visit 1 were not excluded from the dataset for several reasons. First, the 10 participants did not differ from the rest of the sample on study variables of interest, including caregiver depressive symptoms caregiver anxiety, PAID-P scores, and A1c values (all p-values >.05). Secondly, all participants were diagnosed with type 1 diabetes for at least 1 year at visit 2 (when the PAID-P score was completed). Caregivers had a mean STAI trait score of 36.2 (SD = 9.1), similar to published norms for working adults (Spielberger, 1983). Caregivers had a mean CES-D score of 9.9 (SD = 8.7), similar to rates in community-based adult samples (Radloff, 1977). The mean PAID-P score at visit 2 was 49.4 (SD = 12.6), which was congruent to previously published rates of burden in caregivers of adolescents with diabetes (Butler et al., 2008).

Table I.
Participant Characteristics

Correlations between study variables, sociodemographic, and disease characteristics can be found in Table II. Pearson correlations are reported for relationships between continuous variables and point biserial correlations are reported for relationships between categorical variables. Caregiver anxiety symptoms were significantly related to caregiver depressive symptoms, PAID-P scores, and higher A1c values. Caregiver depressive symptoms were significantly related to PAID-P scores and higher A1c values. The relationship between caregiver distress, PAID-P scores, and A1c values partially satisfies the criteria purported by Baron and Kenny. PAID-P scores were also significantly related to higher A1c values. Adolescents of an ethnic minority were more likely to be on public insurance, have caregivers with higher levels of anxiety symptoms, and experience higher A1c values.

Table II.
Correlations of Study Variables

PAID-P scores as a Mediator of Caregiver Depressive Symptoms and A1c

The first step in our mediational analyses included caregiver depressive symptoms at visit 1 and covariates as independent variables and PAID-P scores at visit 2 as the dependent variable (see Table III). The overall model was significant F(9,133) = 2.2, p < .05, R2 = 0.13. Higher levels of caregiver depressive symptoms at visit 1 predicted higher levels of PAID-P scores at visit 2 ( p < .001). This model, with caregiver depressive symptoms as the only statistically significant variable, accounted for 13% of the variance in PAID-P scores. The second step included caregiver depressive symptoms at visit 1 and covariates as independent variables and A1c values at visit 3 as the dependent variable. The model was significant, F(9,136) = 3.9, p < .001, R2 = 0.21, with higher A1c values at visit 3 associated with more caregiver depressive symptoms at visit 1 ( p = .05), insulin delivery via injections versus continuous subcutaneous insulin (CSII) ( p = .01), and minority status ( p = .04). This model accounted for 21% of the variance in A1c values at visit 3.

Table III.
Mediation Models

The third step in the mediator analyses included caregiver depressive symptoms at visit 1, PAID-P scores at visit 2, and the covariates as the independent variables; A1c value at visit 3 was the dependent variable. The overall model was significant, F(10,132) = 5.0, p < .001, R2 = 0.27. Adding the mediator (PAID-P) explained an additional 6% of the variance in A1c values. The same covariates from the second step, insulin delivery via injections versus CSII ( p = .01) and minority status ( p = .03), were significant in the final model. In addition, older adolescents ( p = .04) and higher PAID-P scores ( p = .001) at visit 2 also predicted higher A1c values at visit 3, while the effect of caregiver depressive symptoms became non-significant ( p = .39) in the final model, thus satisfying the Baron and Kenny criteria. These findings suggest that PAID-P scores at visit 2 mediated the caregiver depressive symptoms-glycemic control link (Sobel = 2.5, p = .01). Examination of the indirect and direct effects showed that 50.0% of the relationship between caregiver depressive symptoms at visit 1 and A1c values at visit 3 was explained by PAID-P scores at visit 2.

PAID-P scores as a Mediator of Caregiver Anxiety Symptoms and A1c

The first step included caregiver anxiety symptoms at visit 1 and covariates as independent variables and PAID-P scores at visit 2 as the dependent variable (see Table III). The overall model was significant, F(9,134) = 4.9, p < .001, R2 = 0.25, with higher levels of caregiver anxiety symptoms at visit 1 predicting higher PAID-P scores at visit 2 ( p < .001). This model, with caregiver anxiety symptoms as the only statistically significant variable, accounted for 25% of the variance in PAID-P scores at visit 2. The second step included caregiver anxiety symptoms and covariates as independent variables and A1c value at visit 3 as the dependent variable. The model was significant, F(9,137) = 5.9, p < .001, R2 = 0.28. Higher A1c values at visit 3 were associated with caregiver anxiety symptoms at visit 1 ( p < .001), insulin delivery via injections versus CSII ( p = .02), and minority status ( p = .008). This model accounted for 28% of the variance in A1c values at visit 3.

The third step included caregiver anxiety symptoms, PAID-P scores, and the covariates, as the independent variables; A1c was the dependent variable. The overall model was significant, F(10,133) = 5.7, p < .001, R2 = 0.30. Thus, an additional 2% of the variance of A1c values can be explained by PAID-P scores. The same covariates from the second step, insulin mode ( p = .02) and minority status ( p = .0098), were significant. In addition, duration ( p = .03) and PAID-P scores at visit 2 ( p = .03) were associated with lower A1c values at visit 3 in this final model. Moreover, the significance level of the association between caregiver anxiety symptoms and A1c values dropped from p < .001 to p = .01 in this model. These findings suggest that PAID-P scores at visit 2 partially mediated the relationship between caregiver anxiety symptoms at visit 1 and A1c values at visit 3 (Sobel = 2.0, p = .04). Examination of the indirect and direct effects showed that 25.8% of the relationship between caregiver anxiety symptoms at visit 1 and A1c values at visit 3 is explained by PAID-P scores at visit 2.

Post hoc analyses

Due to the number of significant predictor variables in the model and documented associations with each other in univariate analyses, we ran post hoc analyses to clarify the nature of their associations. Specifically, for each model (anxiety and depressive symptoms), we entered only the significant variables from the planned analyses and their interactions. When we did this, there was no significant interaction in either model; however, adding the interaction term of insulin delivery mode (pump versus injections) and ethnicity changed the magnitude of the main effects, suggesting that these relationships may be worthy of further investigation. It may be that minority status serves as a proxy for another unknown variable relating to access to the insulin pump. Indeed, a chi-square analysis of insulin delivery mode by minority status revealed significance (χ2 = 7.96, p = .005) and indicated that a higher percentage of White, non-Hispanic youth in the study were on insulin pumps (67%) compared to the minority youth in the study (35%).

In addition, the relationship between BGM frequency at time 2 and adolescents’ A1c values at time 3 was examined. We did this because of the established relationship between BGM frequency and A1c (reviewed in Hood, Peterson, Rohan, & Drotar, 2009). These findings indicated BGM frequency and adolescents’ A1c values were highly correlated (r = −.43, p < .001).

Discussion

Data in this study establish an association between caregiver psychological functioning and adolescent glycemic control that is explained in part by the burden caregivers perceive regarding diabetes management. When caregivers experience psychological distress, it results in increased burden associated with diabetes management. The data demonstrate that the relationship between caregiver psychological distress and A1c values were stronger for symptoms of depression compared to symptoms of anxiety, suggesting that certain types of distress may be more closely tied to adolescent health outcomes. Overall, this finding extends previous research examining burden in youth with diabetes (e.g., Butler et al., 2008) by demonstrating that perceived diabetes-specific burden is related to caregiver psychological distress and A1c values in adolescents. We believe these findings have implications for both clinical practice and research.

The mediating effect of perceived diabetes-specific burden was more pronounced in the relationship between caregiver depressive symptoms and glycemic control than anxiety symptoms. One plausible explanation for these findings is the differential effect of caregiver anxiety and depressive symptoms on caregiver behavior. Specifically, there is a link documented between caregiver depressive symptoms and caregiver withdrawal (Langrock, Compas, Keller, Merchant, & Copeland, 2002). Alternatively, caregiver anxiety symptoms are linked to caregiver over-involvement (Woodruff-Borden, Morrow, Bourland, & Cambron, 2002). Thus, while caregiver depressive symptoms may lead a caregiver to feel overburdened and subsequently withdraw from diabetes management tasks and supervision, anxious caregivers may remain involved in diabetes management, but be overly extended. Upon visual inspection of the items that comprised the perceived diabetes-specific burden measure, several themes of burden relating to diabetes management emerged: lack of support, low self-efficacy, and high frustration. Frustration, perceived lack of support, and feeling ineffective with diabetes management may more accurately characterize results of depression rather than anxiety. In fact, a number of investigations suggest that lack of support and low self-efficacy may correspond closely to depressive symptoms (Bandura, Pastorelli, Barbaranelli, & Caprara, 1999; Hays et al., 1997; Kaslow, Rehm, & Siegel, 1984).

Overall, these findings suggest a relationship between caregiver psychological distress (particularly for depressive symptoms) to a health outcome in adolescents with type 1 diabetes. This relationship occurs via a general caregiver variable (psychological distress) to a diabetes-specific caregiver variable (perceived burden). These findings led us to consider how perceived burden impacts control. One potential mechanism is through the diabetes treatment regimen. Specifically, BGM frequency may be a predictor of glycemic control in adolescents with type 1 diabetes (see Hood et al., 2009, for a review). Additionally, family factors specific to diabetes may impact adherence, which in turn, may subsequently impact glycemic control (Duke et al., 2008). In the current study sample, BGM frequency and adolescents’ A1c values were highly correlated. Studies are underway to test the role of BGM frequency in predicting the relationship between caregiver burden and poor glycemic control as well as to examine multi-dimensional aspects of adherence rather than then uni-dimensional BGM frequency.

Alternatively, responsibility sharing around diabetes management may explain these findings. Higher collaborative involvement between caregivers and adolescents has been shown to be associated with improved glycemic control in adolescents with type 1 diabetes (Anderson, Auslander, Jung, Miller, & Santiago, 1990; Anderson et al., 2009; Berg et al., 2008). When a caregiver feels burdened by diabetes management, they may be more inclined to transfer responsibility to the adolescent or to be a less efficient partner in management. This could translate to poorer adherence and subsequently, poorer control.

Minority status significantly predicted A1c values in both models of caregiver depressive and anxiety symptoms. Post-hoc analyses indicate an interaction term of minority status and insulin delivery method approached significance. These findings suggest an indirect or interactive association for minority status with suboptimal control and are consistent with prior studies (Cortina, Repaske, & Hood, 2010; Harris, Greco, Wysocki, Elder-Danda, & White, 1999; Overstreet, Holmes, Dunlap, & Frentz, 1997). In general, prior work indicates disparities in health outcomes for youth with type 1 diabetes from ethnic minority groups (Overstreet et al., 1997). Further investigation of this finding is needed, particularly around perceived access and use of insulin pump.

Several limitations should be noted. First, we obtained data from the “primary caregiver” and this was predominantly the mother. Mothers may differ from fathers or other caregivers in their roles in diabetes management; however, this was not measured in the current investigation. It will be important in future investigations to obtain a larger proportion of other caregivers and their perspectives on distress and burden. Second, anxiety and depressive symptoms fluctuate over time. It may be that caregivers’ level of these symptoms changed between visits 1 and 2. In addition, it is also plausible that caregiver depressive symptoms and anxiety symptoms may result from concerns about the adolescents’ poor control. While the nature of these relations was not examined in the current investigation it will be important in future studies to determine if there is an additional impact on perceived diabetes-specific burden when these symptoms differ from their baseline levels. Third, this study’s sample is largely representative of the type 1 diabetes population in the United States; however, it is not a diverse sample. Thus, caution is warranted when generalizing these findings to other, more diverse samples. Lastly, we did not control for baseline A1c values in the current investigation, as A1c at visit 1 is highly correlated to A1c at visit 3. When such highly correlated variables are included within regression models, the variance remaining in the dependent variables is significantly decreased. When A1c values at visit 1 were entered into our models, no other study variables of interest predicted A1c at visit 3. In other words, we were unable to investigate relationships of interest in the model when baseline A1c was included.

The current study is the first to examine perceived diabetes-specific burden as a mechanism underlying the relationship between caregiver psychological distress and adolescents’ glycemic control via mediational analyses in a longitudinal sample. The current findings build on previous investigations that examined these variables via cross-sectional designs (e.g., Butler et al., 2008; Jaser et al., 2008). These findings also suggest multiple aspects of caregiver functioning (both general and diabetes-specific) impact youth health outcomes. Specifically, both caregiver distress and perceived diabetes-specific burden may contribute to the observed decrease in glycemic control across adolescence. Addressing caregiver psychological distress, particularly caregiver depressive symptoms, in family-based treatments of adherence in adolescents with type 1 diabetes may be valuable. Furthermore, addressing caregiver depressive symptoms may impact perceived burden relating to diabetes management, as well as perceived efficacy with management. Additionally, the inclusion of coping skills for the various facets of perceived diabetes-specific burden (e.g., social support, self-efficacy, and dealing with emotional distress specific to diabetes management) might improve family functioning, and may bolster health outcomes for adolescents with type 1 diabetes. Finally, examining additional mechanisms that may influence these relations (e.g., family responsibility sharing, multiple dimensions of adherence) may be valuable in future investigations.

Funding

National Institutes of Health (K23 DK-073340 to K.K.H.).

Conflict of interest: None declared.

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