Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2021 Jun 1.
Published in final edited form as: Soc Sci Med. 2020 Apr 25;255:113010. doi: 10.1016/j.socscimed.2020.113010

Neighborhood Disadvantage, Parent-Adolescent Relationship Quality, and Type 1 Diabetes in Late Adolescents Transitioning to Early Emerging Adulthood

Daniel Mello 1, Deborah Wiebe 1, Ashley C Baker 1, Jonathan Butner 2, Cynthia Berg 2
PMCID: PMC7268169  NIHMSID: NIHMS1588593  PMID: 32353651

Introduction

Type 1 diabetes (T1D) is a chronic disease that requires complex daily self-management behaviors to maintain healthy blood glucose levels (Chiang et al., 2018). Managing T1D is particularly challenging during late adolescence and early emerging adulthood (ages 18 to 25; Arnett, 2016). In this stage of life, youth are becoming increasingly independent from parents and are facing life changes, uncertainty about their future, and risks to their well-being (e.g., leaving home, entering college or the work force, experimenting with alcohol; Monaghan, Helgeson, & Wiebe, 2015). Late adolescents with T1D take on greater responsibility for managing their illness (Wiebe et al., 2014) and are tasked with continual diabetes care while navigating these life transitions. T1D management steadily deteriorates across adolescence (e.g., poorer adherence and glycemic control), reaching a nadir in the late adolescence–early emerging adulthood period (Clements et al., 2016; Miller et al., 2015). This decline is concerning because poor glycemic control is associated with short- (e.g., diabetic ketoacidosis, hypoglycemia; Levine et al., 2001) and long-term health complications (e.g., nephropathy; White, 2015). Because patterns of diabetes management in adolescence may set the stage for management across emerging adulthood (Helgeson et al., 2017), it is imperative to understand factors that might contribute to lower adherence and higher HbA1c (i.e., poorer glycemic control) at this time of development.

Lower socioeconomic status (SES) is a risk factor for adverse T1D outcomes. Among adolescents, lower SES is cross-sectionally associated with lower adherence behaviors (Duke et al., 2008), a less-intensive insulin administration regimen, less overall knowledge of diabetes, and fewer daily blood glucose checks (Powell, Chen, Kumar, Streisand, & Holmes, 2013), as well as higher HbA1c (Borschuk & Everhart, 2015; Duke et al., 2008; Powell et al., 2013; Redondo et al., 2014). Only two studies have examined longitudinal associations between SES and subsequent T1D outcomes. Helgeson et al. (2017) found that early adolescents from lower social status homes (as indicated by the Hollingshead Index) had poorer latent trajectories of HbA1c across adolescence and emerging adulthood, while Secrest et al. (2011) found that lower income in early adulthood predicted the development of long-term complications later in life (e.g., neuropathy). Thus, there is a consistent link between lower SES and poorer T1D outcomes, but most work is cross-sectional, and we have a limited understanding of associations at the high-risk time of late adolescence and early emerging adulthood.

Neighborhood-level SES is a unique context linked to the health of developing youth. US census tract indicators of socioeconomic disadvantage (e.g., percent who are unemployed) have been used to create a “neighborhood disadvantage” construct suggestive of the environmental conditions within which families live, work, play, and survive. Cross-sectional work revealed that neighborhood disadvantage associated with dysregulated cortisol during childhood (Dulin-Keita, Casazza, Fernandez, Goran, & Gower, 2012) and late adolescence, over-and-above other family SES indicators (e.g., parental education, occupation, or income; Chen & Paterson, 2006). Research with pediatric T1D similarly revealed that adolescents from disadvantaged neighborhoods showed higher HbA1c (Main et al., 2014; Wang, Wiebe, & White, 2011), with some evidence that these associations occur independent of family SES and markers of health care access (Clarke, Daneman, Curtis, & Mahmud, 2017; Queen et al., 2017).

Neighborhood disadvantage may place those with T1D at risk partially by undermining parent-adolescent relationship quality. Evidence from a recent meta-analysis suggests that neighborhood disadvantage affects health outcomes primarily through psychosocial mechanisms (O’Brien, Farrell, & Welsh, 2019). The Family Investment Model theorizes that socioeconomic limitations, including the neighborhood environment (e.g., inadequate housing), hinder parents’ abilities to devote resources to their adolescent’s development (e.g., less time or space for parent–adolescent bonding that may facilitate social competence; Conger & Donnellan, 2007). Relatedly, the Family Stress Model posits that persistent socioeconomic distress can undermine family functioning by creating marital relationship strain, a less accepting and nurturing caregiving environment, and more harsh, inconsistent parenting (Conger & Donnellan, 2007). SES-related distress may thus overtax parents’ abilities to effectively parent and strain relationships with their adolescent, potentially placing their adolescent’s health at risk. Indeed, lower household SES is linked to poorer affective involvement within families experiencing pediatric chronic illnesses (Herzer et al., 2010), and neighborhood-level risk is linked to poorer parent-adolescent relationship quality (Kotchick & Forehand, 2002; Simons et al., 2016), underscoring the importance of neighborhood disadvantage during adolescence.

A key component of a nurturing home environment is higher-quality relationships with parents characterized by warmth and acceptance (Rohner, Khaleque, & Cournoyer, 2005), which play a central role in how T1D is managed during adolescence (Berg et al., 2008; Palmer et al., 2011), and may even set the stage for T1D management during the transition from late adolescence into early emerging adulthood (Wiebe, Helgeson, & Berg, 2016). As parental involvement in T1D management declines across adolescence (King, Berg, Butner, Butler, & Wiebe, 2014; Wiebe et al., 2014), parents often transition to being a backup system of “guiding agents” who are available to help in case of life and T1D difficulties (Hilliard et al., 2014; Sparud-Lundin, Öhrn, & Danielson, 2010). Yet, the emotional connection between parents and late adolescents remains important. Supportive parent-adolescent relationships during late adolescence are linked to better concurrent adherence and HbA1c (Helgeson et al., 2014; Main et al., 2015), and predict less deterioration in adherence from late adolescence into early emerging adulthood (Helgeson et al., 2014). Parents remain a trusted source of support into emerging adulthood (Sparud-Lundin et al., 2010), with some evidence that high quality relationships with parents are more strongly linked to T1D outcomes during emerging adulthood than at younger ages (Goethals et al., 2017). Taken together, these findings suggest that late adolescents’ experiences of high-quality relationships with parents may provide a familiar source of available support that predicts not only levels of T1D outcomes but also trajectories of outcomes across the transition into this high-risk developmental period. Examining longitudinal processes is important to understand whether neighborhood disadvantage has long-lasting effects on diabetes outcomes over time.

Relationship quality with mothers’ and fathers’ may have differential implications for late adolescent T1D outcomes (Wysocki & Gavin, 2004). Adolescents perceive mothers to be more accepting (Miranda, Affuso, Esposito, & Bacchini, 2016) and to display more emotional warmth than fathers (Worrall-Davies, Owens, Holland, & Haigh, 2002), but differential links to T1D outcomes are inconsistent. Perceptions of acceptance from both mothers and fathers have been related to better adherence and HbA1c among early adolescents (Drew et al., 2011; King et al., 2014) and late adolescents (Main et al., 2015). Yet, other findings show differential associations between mothers’ and fathers’ acceptance with T1D outcomes. Berg et al. (2008) found that early adolescents perceived mothers to be more accepting than fathers, and that greater mothers’ acceptance was associated with better adherence, while greater father’s acceptance was associated with better adherence and HbA1c. The limited and mixed literature makes it important to examine differential relational processes with mothers and fathers in the context of T1D.

Given evidence that neighborhood disadvantage is linked to parent-adolescent relationships, and that these relationships are associated with T1D outcomes, it is likely that neighborhood disadvantage associations with T1D outcomes may occur indirectly through parent-adolescent relationship processes. In cross-sectional studies of early adolescents, both Drew et al. (2011) and Thomas et al. (2018) found that lower family SES associated with poorer diabetes outcomes indirectly via poorer parent-adolescent relationship quality. Yet, the potential for this mediating process to set a foundation for managing T1D across the risky transitional period of early emerging adulthood has not been examined.

Summary and Hypotheses

The current study examined whether living within a socioeconomically-disadvantaged neighborhood during adolescence may hinder T1D outcomes across the transition from late adolescence into emerging adulthood through lower parent-adolescent relationship quality. We hypothesized that higher neighborhood disadvantage during adolescence would predict: 1) lower relationship quality with parents during late adolescence; 2) poorer subsequent levels of adherence and HbA1c; and 3) more rapid deterioration in adherence and HbA1c across a two-year transition. We further predicted that 4) links between neighborhood disadvantage and T1D outcomes would be partially mediated by relationship quality with mothers and/or fathers. The potential unique roles of mothers and fathers were tested, but limited and mixed findings in the previous literature prevented specific hypotheses.

Method

Participants

The current study used data from three annual assessments of a multi-site longitudinal study examining T1D management across the transition into early emerging adulthood. In a previous report based on an initial subset of this sample at baseline, we found higher neighborhood disadvantage was associated with higher HbA1c (Queen et al., 2017). High school seniors with T1D were recruited from outpatient endocrinology clinics in two southwestern cities. Of the qualifying 507 individuals, 247 (47%) were enrolled. Reasons for not participating included lack of interest (33%) or being too busy in their senior year (34%); 20% declined to give a reason. The larger multi-site study was approved by Institutional Review Boards at the University of Utah, the University of Texas Southwestern Medical Center (where half of the participants were recruited), and the University of California, Merced (where the Texas sample was followed across time). The Texas site provided IRB to extract medical records to compare participants and non-participants; there were no differences on illness variables such as HbA1c and time since diagnosis (ps > .05).

Eligibility criteria included being diagnosed with T1D for at least one year, English as the primary language, being in the final year of high school, living with a parent (82.1% lived in two-parent homes), being able to have regular contact with parents over the subsequent two years (consistent with objectives of the broader study), and having no condition that would prohibit study completion (e.g., severe intellectual disability, blindness) Adolescents who had dropped out of high school were eligible if they met other criteria.

At baseline, participants with valid surveys (N = 236) were 17.76 years old on average (SD = 0.39), 61% female, 73.9% non-Latino White, 14.3% Latino, 6.1% African American, and 5.7% either Asian/Pacific Islander, American Indian, or more than one race. Average time since diagnosis was 7.37 years (SD = 3.91); 44.4% reported using an insulin pump. At Time 2, 61.1% of our emerging adults reported attending a four-year college. Among parents, 12.9% of mothers and 18.2% of fathers had a high school education or less, 37.2% of mothers and 25.1% of fathers reported having some college or a vocational degree, and 34% of mothers and 46.3% of fathers had a bachelor’s degree or higher. Census tract data showed the median household income in the neighborhood to be approximately $68,300 (SD ≈ $30,500), distributed as < $20,000 (.9%), $20,000 to < $40,000 (9.7%), $40,000 to < $60,000 (24.1%), $60,000 to < $80,000 (32.9%), $80,000 to < $100,000 (17.1%), $100,000 to < $120,000 (6.9%), $120,000 to < $140,000 (5.1%), and $140,000+ (3.2%).

Procedure

Adolescents who were 18 years or older provided signed informed consent, while adolescents younger than 18 provided signed assent, and a parent provided parental consent; those who assented provided signed informed consent after turning 18. During an in-person research session, adolescents were trained to complete an on-line survey and a dried blood-spot HbA1c assay kit. Participants were then sent a secure link to complete the confidential online survey at home during the senior year of high school (Time 1), and again one (Time 2) and two years later (Time 3). Upon survey completion, adolescents were sent the HbA1c assay kit to complete and send to a central lab for processing. Adolescents were paid $50 for the first two assessments (online survey and assay) and $75 for the third assessment.

Measures

Neighborhood disadvantage

Neighborhood level data were culled from 2013 five-year estimates from the American Community Survey (ACS). At Time 1, 83.5% of participants had been living in their current residence for five years or more. Because enrollment for Time 1 was completed in 2013, the 2013 five-year ACS estimates provided the most comprehensive index available of neighborhood experiences to which the participants had been exposed for some time. Home addresses were used to determine individuals’ census tracts, which were then linked to the ACS data. Census tracts are smaller, contiguous regions than zip codes, providing greater resolution with which to capture neighborhood-level characteristics. Consistent with previous work (Dulin-Keita et al., 2012; Queen et al., 2017), ACS indicators chosen to represent the SES of neighborhood residents, as well as the physical environment, included: a) percent of the population under 25 years old with less than a high school education; b) percent under 18 years old living in poverty; c) percent unemployed; d) percent receiving public assistance; and e) percent of vacant housing units. A neighborhood disadvantage composite variable was created by summing the standardized scores of these census indicators. Higher values denote living in a more disadvantaged neighborhood.

Parent-adolescent relationship quality

Relationship quality at Time 1 (baseline) was measured using the acceptance scale from the Mother-Father-Peer Scale (Epstein, 1983). Five items were rated on a 1 (strongly disagree) to 5 (strongly agree) Likert scale to assess perceptions of feeling emotionally close to and accepted by mothers and fathers. Participants reported on relationship quality separately for mother and father, responding to items such as “My [mother/father] gives me the feeling that s(he) likes me as I am.” This scale has acceptable reliability in parent-adolescent samples (e.g., α range: .69 – .83) and is associated longitudinally with T1D adherence across adolescence (King et al., 2014). In the current sample, α = .86 and .88 for mothers’ and fathers’ acceptance, respectively.

Glycemic control

Adolescent glycated hemoglobin (HbA1c) was obtained annually using dried blood spot HbA1c mail-in assay kits. HbA1c is a three- to four-month average of blood glucose levels, with higher values indicating poorer blood glucose levels. Assay kits were acquired from and processed by CoreMedica Laboratories, accredited by the College of American Pathologists (www.coremedica.net). At baseline, these HbA1c values were highly correlated with point-of-care assays in medical records (r = .74; p < .001). For all time points, participants had average HbA1c levels (M range: 8.26 – 9.27%) higher than clinical recommendations of < 7.5% (Chiang et al., 2018).

Adherence

Adherence was captured annually with the Diabetes Behavior Rating Scale (DBRS; Iannotti, Nansel, et al., 2006). This 37-item scale measures completion of recommended self-management behaviors (e.g., “Was your insulin taken at the time you were supposed to?”, “Out of the last five times when you had symptoms of being HIGH, how often was insulin dose changed based on the results of a blood sugar test?”) and is scored by calculating a proportion of the maximum possible score, ranging from 0 to 1; higher scores denote better adherence. This scale correlates highly with time-intensive interview measures (Iannotti, Schneider, et al., 2006). Reliability across all time points ranged from α = .84 – .91.

Statistical Analysis Plan

Across all study variables, 50.42% of cases had incomplete data, though missingness at the variable level was small (7.14%). To account for missing data, five imputations were created using the Markov-Chain Monte Carlo method in SPSS 23 (Graham, 2009). Other variables in the larger dataset were included in the imputation procedure to ensure a “missing-at-random” model. These additional variables reflected aspects of self-regulation (e.g., executive functioning) and social relationships (e.g., mother/father knowledge of adolescent T1D management).

Structural Equation Modeling (SEM) was employed to estimate the hypothesized direct and indirect pathways between neighborhood disadvantage and diabetes management outcomes. Previous latent growth curve analyses with this sample showed longitudinal deterioration in both adherence and HbA1c from late adolescence into emerging adulthood, with significant between-person variability at baseline and across time (Berg et al., 2018). With these trajectories of risk established, we tested three latent growth curve models. First, relationship quality with both parents was initially examined simultaneously to determine unique mother versus father relationship quality associations (Figure 1). We also examined relationship quality with mothers and with fathers in separate models to determine individual patterns.

Figure 1.

Figure 1.

Open in a new tab

SEM model for direct and indirect pathways between neighborhood disadvantage, adherence, and HbA1c via parent-adolescent relationship quality among late adolescents transitioning into emerging adulthood. Coefficients shown as unstandardized parameter (standard error). Bold* coefficients are significant at the p = .05 level. Bold lines denote significant indirect paths: Adherence: B(SE) = −.01 (.004)*; HbA1c: B(SE) = .09 (.05)*. Gender, race/ethnicity, pump status, parental education, and median household income were covaried (not shown), χ2 (48, N = 236) = 51.46, p = .340, CFI = .99, TLI = .99, RMSEA = .02, SRMR = .04.

Because adherence behaviors and HbA1c are related but conceptually distinct constructs (Asche, LaFleur, & Conner, 2011; Hood, Peterson, Rohan, & Drotar, 2009), these variables were modeled as correlated outcomes. HbA1c is a physiological indicator of average blood glucose levels over the past three to four months (Chiang et al., 2018), while adherence is a set of behaviors (e.g., checking blood glucose, counting carbohydrates, administering insulin) that patients are advised to follow to promote optimal blood glucose control (Hood et al., 2009). Accordingly, the residual errors for the latent intercepts of adherence and HbA1c, as well as for the latent slopes of adherence and HbA1c, were allowed to correlate. The residual errors for the latent intercepts and slopes within each outcome were also allowed to correlate (i.e., intercept and slope of adherence and of HbA1c were allowed to correlate).

Given our interest in examining relationship quality with mothers and with fathers individually, we conducted preliminary analyses to discern whether the adolescent’s living arrangements may have influenced the findings. We were particularly concerned that relationship quality with fathers could appear to be less relevant to T1D management in cases when the adolescent did not live with their primary father figure. To examine this possibility, we first assessed how many late adolescents were living with their father, and then estimated if living with father moderated the direct link of father-adolescent relationship quality with T1D outcomes. The vast majority of participants were in two-parent households (82.6%) and living with the father of whom they were reporting. Not surprisingly, youth who were living with their father (i.e., in two-parent households) experienced less neighborhood disadvantage than those who were not (r = −.34, p < .001). Yet, living situation did not moderate associations between father relationship quality and any T1D outcome (concurrent or longitudinal; ps > .151). Given that different patterns of associations across mother and father relationship quality were unlikely to reflect living situation, this variable was dropped to maintain model parsimony.

In all models, gender, race/ethnicity, and insulin pump status were covaried with exogenous/endogenous intercepts and slopes if they were correlated with the T1D outcomes (see Table 1). Similar to prior work and recommendations (Leventhal & Brooks-Gunn, 2000; Queen et al., 2017), parental education and median household income were covaried to discern if neighborhood disadvantage had unique associations with relationship quality and T1D outcomes above-and-beyond other metrics of SES. Data were centered at Time 2 to establish the temporal ordering of indirect effects from neighborhood disadvantage during adolescence to relationship quality at Time 1 (late adolescence) to predicted levels of each diabetes outcome at Time 2 (i.e., latent intercepts centered at Time 2 denote levels of each outcome one year after baseline assessments). Analyses used α = .05 (two-tailed) and were estimated using Mplus (v8.0). Because bootstrapped confidence intervals are unavailable for imputed data in this version of Mplus, the default delta method estimated p-values for indirect effects. Model fit was evaluated using goodness-of-fit indices: the Comparative Fit Index (CFI), the Tucker-Lewis Index (TLI), and Root Mean Square Error of Approximation (RMSEA), and the Standardized Root Mean square of the Residuals (SRMR). A model with a CFI > 0.95, TLI > 0.95, RMSEA < 0.07, and SRMR < .08 was considered for good fit (Hooper, Coughlan, & Mullen, 2008).

Table 1.

Correlations Between Neighborhood Disadvantage, Maternal & Paternal Acceptance, and T1D Outcomes among Late Adolescents with Type 1 Diabetes (N = 236)

M (SD) 1 2 3 4 5 6 7 8 9 10 11 12 13
1. Neighborhood Disadvantage 0.00 (0.71) --
2. Maternal Acceptance 4.32 (0.89) −.18* --
3. Paternal Acceptance 4.28 (0.90) −.16* .53* --
4. Time 1 HbA1c 8.26 (1.63) .25* −.14* −.24* --
5. Time 2 HbA1c 8.94 (1.97) .18* −.09 −.25* .47* --
6. Time 3 HbA1c 9.23 (2.05) .16* −.03 −.17* .47* .63* --
7. Time 1 Adherence 0.61 (0.12) −.02 .21* .36* −.21* −.23* −.19* --
8. Time 2 Adherence 0.59 (0.13) −.05 .05 .29* −.17* −.25* −.20* .67* --
9. Time 3 Adherence 0.59 (0.15) .05 .07 .17* −.27* −.27* −.29* .56* .65* --
10. Gender (% Female) 61% (n = 144) −.11 −.04 −.03 .20* .08 .15* −.03 .06 −.11 --
11. Race/Ethnicity (% White) 73.9% (n = 170) .41* .10 −.02 .29* .26* .22* .06 −.11 .00 .03 --
12. Pump Status (% Insulin Pump) 44.4% (n = 104) −.31* .07 .04 −.35* −.24* −.23* −.03 .05 .16* −.09 −.28* --
13. Parental Education (% College Degree) 59.3% (n = 118) −.35* .09 .09 −.31* −.20* −.23* .07 .12 .01 .07 −.42* .19* --
14. Median Household Income $68,300 ($30,500) −.69* .11 .03 −.20* −.19* −.20 .01 .02 −.01 .08 −.43* .14* .26*
Open in a new tab

Note. Values averaged across five imputed datasets. Bold* values significant at or below p = .05 level.

Results

Descriptive statistics and correlations among all model variables (including covariates) are shown in Table 1. Greater neighborhood disadvantage was associated with lower mothers’ and fathers’ acceptance, and higher HbA1c at all time points. Neighborhood disadvantage was not correlated with adherence at any time point. Higher mothers’ acceptance was linked to higher concurrent adherence and lower HbA1c at Time 1, but not to subsequent T1D outcomes at Times 2 or 3. Higher fathers’ acceptance, however, was linked to higher adherence and lower HbA1c both concurrently at Time 1, and prospectively one and two years later.

The SEM model examining relationship quality with mothers and fathers simultaneously (Figure 1) showed excellent fit to the data, χ2 (48, N = 236) = 51.46, p = .340, CFI = .99, TLI = .99, RMSEA = .02, SRMR = .04. Neighborhood disadvantage was not directly associated with any T1D outcomes once other variables were in the model (ps > .480). As predicted, however, greater neighborhood disadvantage was associated with lower parent-adolescent relationship quality for both mothers and fathers, and lower father-adolescent relationship quality was linked to lower levels of adherence, and higher levels of HbA1c, at Time 2. Relationship quality with fathers also formed an indirect path linking neighborhood disadvantage to Time 2 levels of adherence (parameter(SF) = −.01 (.004). p = .040) and HbA1c (parameter(SF) = .09 (.05). p = .042). Relationship quality with mothers was not associated with levels of either T1D outcome at Time 2 (i.e., latent intercepts; ps > .342), and all other indirect paths were non-significant (p > .179). Relationship quality with parents was also not associated with the rate of deterioration in T1D outcomes across all three time points (i.e., latent slopes; ps > .101). Overall, this full model accounted for 3.6% of the variance in mother-adolescent relationship quality, 2.8% of the variance in father-adolescent relationship quality, 28.8% of the variance in the latent intercept of HbA1c, 5.4% of the variance in latent trajectories of HbA1c, 10.2% of the variance in the latent intercept of adherence, and 16.5% of the variance in latent trajectories of adherence.

We further examined whether these combined effects were seen in separate models for mothers and fathers. This additional step allowed us to discern whether the absence of an indirect effect through relationship quality with mothers may have occurred because the full model examined only unique mother and father variance, while ignoring the substantial shared variance between mothers’ and fathers’ acceptance (e.g., r = .53). SEM models examining relationship quality with mothers and with fathers were estimated individually, with each model showing excellent fit to the data. All the significant and non-significant direct and indirect associations between neighborhood disadvantage, relationship with mothers and fathers, and T1D outcomes remained unchanged (see online supplemental material). Thus, the absence of an indirect path through mother relationship quality remains when examined individually, providing more confidence in the unique role that fathers play in T1D outcomes at this time of development.

Discussion

Parent-adolescent relationship quality continues to be important for T1D outcomes among late adolescents on the cusp of emerging adulthood, but living within a socioeconomically-disadvantaged neighborhood may place the parent-adolescent relationship at risk. The present study extended prior cross-sectional research linking greater neighborhood disadvantage to poorer T1D outcomes among youth by examining whether neighborhood disadvantage during adolescence is associated with subsequent levels of adherence or HbA1c, as well as rates of deterioration in outcomes across a two-year transition into early emerging adulthood. We also examined whether such associations occur indirectly through the quality of relationships with mothers or fathers. Greater neighborhood disadvantage was linked to poorer adolescent relationship quality with each parent, and lower relationship quality with fathers formed an indirect path linking neighborhood disadvantage to poorer adherence and HbA1c one year later (see Figure 1). Such findings were not found for mothers, suggesting that mothers and fathers play unique roles in late adolescents’ T1D at this important developmental threshold.

Neighborhood disadvantage formed a unique risk for relationship quality with parents during late adolescence. Adolescents from socioeconomically-disadvantaged neighborhoods reported lower relationship quality with both mothers and fathers, even when both parents were simultaneously modeled. Importantly, these associations were independent of family-level SES markers, such as parental education and household income. Thus, corresponding with previous work (O’Brien et al., 2019), neighborhood disadvantage may represent a distressing socioenvironmental context that is straining family functioning, where parents and adolescents struggle to develop warm and accepting relationships (Conger & Donnellan, 2007). This risk to parenting has been studied in younger children and adolescents (Drew et al., 2011), and the present study extends these findings to the late adolescent context, when young people are spending increasing time away from parents.

Relationship quality with fathers appeared to be particularly important for understanding family processes linked to T1D outcomes. Positive relationship quality with parents is crucial for T1D during adolescence (King et al., 2014; Palmer et al., 2011), and relationships with parents may continue to play a key role during the transition into early emerging adulthood (Goethals et al., 2017; Sparud-Lundin et al., 2010; Wiebe et al., 2016). That said, some evidence suggests that mothers and fathers play different roles in T1D management, with mothers more involved in the daily aspects of T1D management, and fathers more involved with larger T1D problems (Berg et al., 2016; Butner et al., 2017). In the current study, lower relationship quality with fathers predicted poorer levels of adherence and HbA1c one year later, while relationship quality with mothers did not. As early emerging adults assume more of the daily responsibilities for T1D management, it may be that mothers’ role in daily management wanes, while fathers’ role with larger problems continues in a manner that predicts subsequent outcomes.

Previous work with early adolescents found that family income was indirectly linked to adherence via both mother- and father-adolescent relationship quality (Drew et al., 2011), but the current study found that only relationship quality with fathers formed an indirect path linking neighborhood disadvantage to T1D outcomes. Although research in this area is extremely limited, some work has suggested that fathers’ parenting practices may be less adaptive in the face of socioeconomic adversity compared to mothers’ parenting practices (Szepsenwol, Simpson, Griskevicius, & Raby, 2015). For example, fathers of impoverished families were less emotionally and behaviorally engaged with their child than fathers of higher SES families (Peters & Ehrenberg, 2009), a finding that did not appear among mothers (Harris & Marmer, 1996). More research is required to replicate and understand these processes, and to discern whether the present findings are unique to our focus on acceptance as the measure of relationship quality with fathers. Nevertheless, our findings suggest that acceptance from fathers is an especially important aspect of family management of T1D during early emerging adulthood, but it may be at risk among families living within socioeconomically-disadvantaged neighborhoods.

Although associations were found linking neighborhood disadvantage and relationship quality measured at Time 1 to levels of T1D outcomes at Time 2, these variables did not predict trajectories across the two-year transition into early emerging adulthood. This finding was surprising given prior research and theory indicating that a foundation of warm and accepting relationships with parents sets the stage for how adolescents transition (Berg et al., 2017), and that relationship quality with parents longitudinally predicts T1D outcomes across adolescence (King et al., 2014) and into emerging adulthood (Helgeson et al., 2014). There are notable differences between the current study and this prior work that may have contributed to these differences (e.g., different developmental periods, measures of parent-adolescent relationship, analytic approaches). Nevertheless, the findings of the current study emphasize that relationship quality may have more proximal associations with levels of T1D outcomes than neighborhood disadvantage, but that these earlier life risk factors may not set a person on particular T1D management trajectories. In additional work with the present sample, we found that relationship quality did not change linearly across the transition out of high school, but rather shifted from year-to-year after high school, and these within-person shifts were associated with changes in T1D outcomes (Berg et al., 2019). Taken together, parent-adolescent relationships may continue to transform into early emerging adulthood and may predict more proximal levels of T1D outcomes rather than determining a person’s trajectories across time.

Strengths and Limitations

The findings of the current study should be interpreted in the context of both strengths and limitations. A strength of the mediation model is that the temporal ordering of the indirect effects was consistent with the theorized model. That is, neighborhood disadvantage was measured using addresses at which the vast majority of participants had been living for the past five or more years, relationship quality was measured at baseline, and the intercept for the T1D outcomes was centered one year later at Time 2. Such ordering makes it unlikely that lower relationship quality is a response to poor T1D management. In addition, variables were measured not only via self-report but also using objective census tract and physiological parameters, making associations unlikely to be heavily influenced by shared method variance. Nevertheless, there are limitations to this study. First, although acceptance is a major component of the parent-adolescent relationship (Rohner et al., 2005) and has been examined as an indirect pathway linking SES and T1D outcomes (Drew et al., 2011), other aspects of the parent-adolescent relationship may have different associations to neighborhood disadvantage and T1D outcomes. Second, neighborhood disadvantage showed unique associations beyond individual and family indices of SES, but it is not an exhaustive measure, and did not include other salient indicators of neighborhood-level SES (e.g., physical surroundings; Clarke et al., 2017). Third, while we used retrospective ACS data to examine neighborhood conditions, future work should consider tracking changes in neighborhood conditions across the transition into emerging adulthood to provide new insights into how these processes might play out across this developmental period. Fourth, a primary aim of the current study was to examine how socioenvironmental living conditions during adolescence shaped T1D management afterward. The study was not designed to examine how socioenvironmental conditions during emerging adulthood were related to T1D management. Because emerging adulthood is a unique developmental period full of flux (Arnett, 2016), future work examining how life circumstances after high school (e.g., college attendance, full-time employment) relate to trajectories of T1D management across the emerging adulthood years will be important. Fifth, although the sample was fairly representative of youth who develop T1D (Dabelea et al., 2014) and race/ethnicity was covaried in the analyses, the sample was mostly non-Latino White who lived in two-parent households. As such, the results of the current study may not generalize to more diverse samples or other family constellations. This area is important for future research, given evidence that SES (Cheng & Goodman, 2015; Wang et al., 2011) and relationship quality (Kotchick & Forehand, 2002) may be associated with different developmental outcomes across race/ethnicity groups during adolescence.

Conclusions

The current study has important research and clinical implications for disadvantaged youth with T1D at the high-risk transition into early emerging adulthood. This study informs currently effective family-based interventions (e.g., Hilliard, Powell, & Anderson, 2016; McBroom & Enriquez, 2009), highlighting the aspects of the parent-adolescent relationship that may be most strongly linked to late adolescent diabetes outcomes. Interventions focusing on communication and problem-solving skills among youth and their parents have shown promise in enhancing diabetes management during early adolescence (Nansel, Thomas, & Liu, 2015) and may also contribute to maintaining good T1D management practices among late adolescents on the cusp of emerging adulthood. Moreover, the unique direct and indirect pathways via relationship quality with fathers suggests future research is necessary to inform clinicians how to promote fathers’ involvement and relationship quality. The current study also advances extant research and interventions by highlighting the role of neighborhood disadvantage in parent-adolescent relationships. Given the possibility that parents’ coping may buffer the risk of low SES on T1D outcomes among older adolescents (Mello, Wiebe, & Berg, 2019), future work may want to examine the potential for parental coping and resilience processes among families living in disadvantaged neighborhoods. Overall, the current study may help researchers and clinicians be better equipped to design effective interventions that target important elements of the parent-adolescent relationship among at-risk youth transitioning into adulthood.

Supplementary Material

1

Highlights.

  • Examined links between neighborhood disadvantage and T1D outcomes.

  • Longitudinal models examined the high-risk transition to early emerging adulthood.

  • Relationship quality with mothers and fathers were examined as mediators.

  • Neighborhood disadvantage linked to poorer relationship quality with parents.

  • Links to T1D outcomes occurred through relationships with fathers, but not mothers.

Acknowledgments

We thank the READY research group for their invaluable assistance, staff and health care providers at the endocrinology clinics at University of Utah Health Care, Mountain Vista Medicine, and Children’s Medical Center Dallas, and the participants of this study. This study was funded by a grant from the National Institute of Diabetes and Digestive and Kidney Diseases at the National Institutes of Health (DK 092939).

Footnotes

The authors declare no conflicts of interest.

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

References

  1. Arnett JJ (2016). The oxford handbook of emerging adulthood. New York, NY: Oxford University Press. doi: 10.1093/oxfordhb/9780199795574.001.0001 [DOI] [Google Scholar]
  2. Asche C, LaFleur J, & Conner C (2011). A review of diabetes treatment adherence and the association with clinical and economic outcomes. Clinical Therapeutics, 33, 74–109. doi: 10.1016/j.clinthera.2011.01.019 [DOI] [PubMed] [Google Scholar]
  3. Berg CA, Butler JM, Osborn P, King G, Palmer DL, Butner JE, … Wiebe DJ (2008). Role of parental monitoring in understanding the benefits of parental acceptance on adolescent adherence and metabolic control of type 1 diabetes. Diabetes Care, 31, 678–683. doi: 10.2337/dc07-1678 [DOI] [PubMed] [Google Scholar]
  4. Berg CA, Butner JE, Turner SL, Lansing AH, King PS, & Wiebe DJ (2016). Adolescents’, mothers’, and fathers’ reports of adherence across adolescence and their relation to HbA1c and daily blood glucose. Journal of Behavioral Medicine, 39, 1009–1019. doi: 10.1007/s10865-016-9771-5 [DOI] [PubMed] [Google Scholar]
  5. Berg CA, Queen TL, Butner JE, Turner SL, Lansing AH, Main A, … Wiebe DJ (2017). Adolescent disclosure to parents and daily management of type 1 diabetes. Journal of Pediatric Psychology, 42, 75–84. doi: 10.1093/jpepsy/jsw056 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Berg CA, Wiebe DJ, Suchy Y, Turner SL, Butner J, Munion A, … Nutrition E (2018). Executive function predicting longitudinal change in type 1 diabetes management during the transition to emerging adulthood. Diabetes Care, 41, 1–8. doi: 10.2337/dc18-0351 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Berg CA, Wiebe DJ, Tracy EL, Kelly CS, Mello D, Turner SL, … Suchy Y (2019). Parental involvement and executive function in emerging adults with type 1 diabetes. Journal of Pediatric Psychology, 1–10. doi: 10.1093/jpepsy/jsz025 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Borschuk AP, & Everhart RS (2015). Health Disparities Among Youth With Type 1 Diabetes: A Systematic Review of the Current Literature. Families, Systems, & Health Systems and Health, 33, 297–313. doi: 10.1037/fsh0000134 [DOI] [PubMed] [Google Scholar]
  9. Butner JE, Berg CA, Munion AK, Turner SL, Hughes-Lansing A, Winnick JB, & Wiebe DJ (2017). Coordination of self- and parental-regulation surrounding type 1 diabetes management in late adolescence. Annals of Behavioral Medicine, 1–13. doi: 10.1007/s12160-017-9922-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Chen E, & Paterson LQ (2006). Neighborhood, family, and subjective socioeconomic status: How do they relate to adolescent health? Health Psychology, 25, 704–714. doi: 10.1037/0278-6133.25.6.704 [DOI] [PubMed] [Google Scholar]
  11. Cheng TL, & Goodman E (2015). Race, ethnicity, and socioeconomic status in research on child health. Pediatrics, 135, e225–37. doi: 10.1542/peds.2014-3109 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Chiang JL, Maahs DM, Garvey KC, Hood KK, Laffel LM, Weinzimer SA, … Schatz D (2018). Type 1 diabetes in children and adolescents: A position statement by the American Diabetes Association. Diabetes Care, 41, 1–19. doi: 10.2337/dci18-0023 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Clarke ABM, Daneman D, Curtis JR, & Mahmud FH (2017). Impact of neighbourhood-level inequity on paediatric diabetes care. Diabetic Medicine, 34, 794–799. doi: 10.1111/dme.13326 [DOI] [PubMed] [Google Scholar]
  14. Clements MA, Foster NC, Maahs DM, Schatz DA, Olson BA, Tsalikian E, … Network, T. E. C. (2016). Hemoglobin A1c (HbA1c) changes over time among adolescent and young adult participants in the T1D exchange clinic registry. Pediatric Diabetes, 17, 327–336. doi: 10.1111/pedi.12295 [DOI] [PubMed] [Google Scholar]
  15. Conger RD, & Donnellan MB (2007). An interactionist perspective on the socioeconomic context of human development. Annual Review of Psychology, 58, 175–199. doi: 10.1146/annurev.psych.58.110405.085551 [DOI] [PubMed] [Google Scholar]
  16. Dabelea D, Mayer-Davis EJ, Saydah S, Imperatore G, Linder B, Divers J, … Hamman RF (2014). Prevalence of type 1 and type 2 diabetes among children and adolescents from 2001 to 2009. Jama, 311, 1778–1786. doi: 10.1001/jama.2014.3201 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Drew LM, Berg CA, King P, Verdant C, Griffith K, Butler J, & Wiebe DJ (2011). Depleted parental psychological resources as mediators of the association of income with adherence and metabolic control. Journal of Family Psychology, 25, 751–758. doi: 10.1037/a0025259 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Duke DC, Geffken GR, Lewin AB, Williams LB, Storch EA, & Silverstein JH (2008). Glycemic control in youth with type 1 diabetes: Family predictors and mediators. Journal of Pediatric Psychology, 33, 719–727. doi: 10.1093/jpepsy/jsn012 [DOI] [PubMed] [Google Scholar]
  19. Dulin-Keita A, Casazza K, Fernandez JR, Goran MI, & Gower B (2012). Do neighbourhoods matter? Neighbourhood disorder and long-term trends in serum cortisol levels. Journal of Epidemiology & Community Health, 66, 24–29. doi: 10.1136/jech.2009.092676 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Epstein S (1983). Scoring and interpretation of the Mother-Father-Peer scale. Unpublished mansucript, University of Massachusetts; Amherst, Massachusetts. [Google Scholar]
  21. Goethals ER, Oris L, Soenens B, Berg CA, Prikken S, Van Broeck N, … Luyckx K (2017). Parenting and treatment adherence in type 1 diabetes throughout adolescence and emerging adulthood. Journal of Pediatric Psychology, 1–11. doi: 10.1093/jpepsy/jsx053 [DOI] [PubMed] [Google Scholar]
  22. Graham JW (2009). Missing data analysis: Making it work in the real world. Annual Review of Psychology, 60, 549–576. doi: 10.1146/annurev.psych.58.110405.085530 [DOI] [PubMed] [Google Scholar]
  23. Harris KM, & Marmer JK (1996). Poverty, paternal involvement, and adolescent well-being. Journal of Family Issues, 17, 614–640. doi: 10.1177/019251396017005003 [DOI] [Google Scholar]
  24. Helgeson VS, Palladino DK, Reynolds K. a, Becker DJ, Escobar O, & Siminerio L (2014). Relationships and health among emerging adults with and without type 1 diabetes. Health Psychology, 33, 1125–1133. doi: 10.1037/a0033511. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Helgeson VS, Vaughn AK, Seltman H, Orchard T, Libman I, Becker D, & Mbbc H (2017). Trajectories of glycemic control over adolescence and emerging adulthood: An 11-year longitudinal study of youth with type 1 diabetes. Journal of Pediatric Psychology, 1–11. doi: 10.1093/jpepsy/jsx083 [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Herzer M, Ph D, Godiwala N, Hommel K. a, Driscoll K, Mitchell M, … Modi AC (2010). Family functioning in the context of pediatric chronic conditions. Journal of Developmental & Behavioral Pediatrics, 31, 1–14. doi: 10.1097/DBP.0b013e3181c7226b.Family [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Hilliard ME, Perlus JG, Clark LM, Haynie DL, Plotnick LP, Guttmann-Bauman I, & Iannotti RJ (2014). Perspectives from before and after the pediatric to adult care transition: A mixed-methods study in type 1 diabetes. Diabetes Care, 37, 346–354. doi: 10.2337/dc13-1346 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Hilliard ME, Powell PW, & Anderson BJ (2016). Evidence-based behavioral interventions to promote diabetes management in children, adolescents, and families. American Psychologist, 71, 590–601. doi: 10.1037/a0040359 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Hood KK, Peterson CM, Rohan JM, & Drotar D (2009). Association between adherence and glycemic control in pediatric type 1 diabetes: A meta-analysis. Pediatrics, 124, 1171–1179. doi: 10.1542/peds.2009-0207 [DOI] [PubMed] [Google Scholar]
  30. Hooper D, Coughlan J, & Mullen MR (2008). Structural equation modelling: Guidelines for determining model fit. The Electronic Journal of Business Research Methods, 6, 53–60. doi: 10.1037/1082-989X.12.1.58 [DOI] [Google Scholar]
  31. Iannotti RJ, Nansel TR, Schneider S, Haynie DL, Simons-Morton B, Sobel DO, … Clark L (2006). Assessing regimen adherence of adolescents with type 1 diabetes. Diabetes Care, 29, 2263–2267. doi: 10.2337/dc06-0685 [DOI] [PubMed] [Google Scholar]
  32. Iannotti RJ, Schneider S, Nansel TR, Haynie DL, Plotnick LP, Clark LM, … Simons-Morton B (2006). Self-efficacy, outcome expectations, and diabetes self-management in adolescents with type 1 diabetes. Developmental and Behavioral Pediatrics, 27, 98–105. doi: 10.1097/00004703-200604000-00003 [DOI] [PubMed] [Google Scholar]
  33. King PS, Berg C. a., Butner JE, Butler JM, & Wiebe DJ (2014). Longitudinal trajectories of parental involvement in Type 1 diabetes and adolescents’ adherence. Health Psychology, 33, 424–432. doi: 10.1037/a0032804 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Kotchick BA, & Forehand R (2002). Putting parenting in perspective: A discussion of the contextual factors that shape parenting practices. Journal of Child and Family Studies, 11, 255–269. doi: 10.123/A:1016863921662 [DOI] [Google Scholar]
  35. Leventhal T, & Brooks-Gunn J (2000). The neighborhoods they live in: The effects of neighborhood residence on child and adolescent outcomes. Psychological Bulletin, 126, 309–337. doi: 10.1037//0033-2909.126.2.309 [DOI] [PubMed] [Google Scholar]
  36. Levine BS, Anderson BJ, Butler DA, Antisdel JE, Brackett J, & Laffel LMB (2001). Predictors of glycemic control and short-term adverse outcomes in youth with type 1 diabetes. Journal of Pediatrics, 139, 197–203. doi: 10.1067/mpd.2001.116283 [DOI] [PubMed] [Google Scholar]
  37. Main A, Wiebe DJ, Croom AR, Sardone K, Godbey E, Tucker C, & White PC (2014). Associations of parent-adolescent relationship quality with type 1 diabetes management and depressive symptoms in Latino and Caucasian youth. Journal of Pediatric Psychology, 39, 1104–1114. doi: 10.1093/jpepsy/jsu062 [DOI] [PubMed] [Google Scholar]
  38. Main A, Wiebe DJ, Van Bogart K, Turner SL, Tucker C, Butner JE, & Berg CA (2015). Secrecy from parents and type 1 diabetes management in late adolescence. Journal of Pediatric Psychology, 40, 1075–1084. doi: 10.1093/jpepsy/jsv060 [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. McBroom LA, & Enriquez M (2009). Review of family-centered interventions to enhance the health outcomes of children with type 1 diabetes. The Diabetes Educator, 35, 428–438. doi: 10.1177/0145721709332814 [DOI] [PubMed] [Google Scholar]
  40. Mello D, Wiebe DJ, & Berg CA (2019). Maternal shift and persist coping, SES, and adolescent type 1 diabetes management. Children’s Health Care. doi: 10.1080/02739615.2019.1570465 [DOI] [Google Scholar]
  41. Miller KM, Foster NC, Beck RW, Bergensta RM, DuBose SN, DiMeglio LA, … Tamborlane WV (2015). Current state of type 1 diabetes treatment in the U.S.: Updated data from the t1d exchange clinic registry. Diabetes Care, 38, 971–978. doi: 10.2337/dc15-0078 [DOI] [PubMed] [Google Scholar]
  42. Miranda MC, Affuso G, Esposito C, & Bacchini D (2016). Parental acceptance-rejection and adolescent maladjustment: Mothers’ and fathers’ combined roles. Journal of Child and Family Studies, 25, 1352–1362. doi: 10.1007/s10826-015-0305-5 [DOI] [Google Scholar]
  43. Monaghan M, Helgeson V, & Wiebe DJ (2015). Type 1 diabetes in young adulthood. Current Diabetes Reviews, 11, 239–50. doi: 10.2174/1573399811666150421114957 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Nansel TR, Thomas DM, & Liu A (2015). Efficacy of a Behavioral Intervention for Pediatric Type 1 Diabetes Across Income. AMERICAN JOURNAL OF PREVENTIVE MEDICINE, 49, 930–934. doi: 10.1016/j.amepre.2015.05.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. O’Brien DT, Farrell C, & Welsh BC (2019). Broken (windows) theory: A meta-analysis of the evidence for the pathways from neighborhood disorder to resident health outcomes and behaviors. Social Science and Medicine, 228, 272–292. doi: 10.1016/j.socscimed.2018.11.015 [DOI] [PubMed] [Google Scholar]
  46. Palmer DL, Osborn P, King PS, Berg CA, Butler J, Butner JE, … Wiebe DJ (2011). The structure of parental involvement and relations to disease management for youth with type 1 diabetes. Journal of Pediatric Psychology, 36, 596–605. doi: 10.1093/jpepsy/jsq019 [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Peters B, & Ehrenberg MF (2009). The influence of parental separation and divorce on father-child relationships. Journal of Divorce and Remarriage, 49, 78–109. doi: 10.1080/10502550801973005 [DOI] [Google Scholar]
  48. Powell PW, Chen R, Kumar A, Streisand R, & Holmes CS (2013). Sociodemographic effects on biological, disease care, and diabetes knowledge factors in youth with type 1 diabetes. JOURNAL OF CHILD HEALTH CARE, 17, 174–185. doi: 10.1177/1367493512456105 [DOI] [PubMed] [Google Scholar]
  49. Queen TL, Baucom KJW, Baker A, Mello D, Berg CA, & Wiebe DJ (2017). Neighborhood disorder and type 1 diabetes glycemic control in adolescence. Social Science & Medicine, 183, 126–129. doi: 10.1016/j.socscimed.2017.04.052 [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Redondo MJ, Connor CG, Ruedy KJ, Beck RW, Kollman C, Wood JR, … Consortium, P. D. (2014). Pediatric Diabetes Consortium type 1 diabetes new onset (NeOn) study: Factors associated with HbA1c levels one year after diagnosis. Pediatric Diabetes, 15, 294–302. doi: 10.1111/pedi.12061 [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Rohner RP, Khaleque A, & Cournoyer DE (2005). Parental acceptance-rejection: Theory, methods, cross-cultural evidence, and implications. Ethos, 33, 299–334. doi: 10.1525/eth.2005.33.3.299 [DOI] [Google Scholar]
  52. Secrest AM, Costacou T, Gutelius B, Miller RG, Thomas J, & Orchard TJ (2011). Associations between socioeconomic status and major complications in type 1 diabetes: The Pittsburgh epidemiology of diabetes complication (EDC) study. Annals of Epidemiology, 21, 374–381. doi: 10.1016/j.annepidem.2011.02.007 [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Simons LG, Wickrama KAS, Lee TK, Landers-Potts M, Cutrona C, & Conger RD (2016). Testing family stress and family investment explanations for conduct problems among african american adolescents. Journal of Marriage and Family, 78, 498–515. doi: 10.1111/jomf.12278 [DOI] [Google Scholar]
  54. Sparud-Lundin C, Öhrn I, & Danielson E (2010). Redefining relationships and identity in young adults with type 1 diabetes. Journal of Advanced Nursing, 66, 128–138. doi: 10.1111/j.1365-2648.2009.05166.x [DOI] [PubMed] [Google Scholar]
  55. Szepsenwol O, Simpson JA, Griskevicius V, & Raby KL (2015). The effect of unpredictable early childhood environments on parenting in adulthood. Journal of Personality and Social Psychology, 109, 1045–1067. doi: 10.1037/pspi0000032 [DOI] [PubMed] [Google Scholar]
  56. Thomas DM, Lipsky LM, Liu A, & Nansel TR (2018). Income relates to adherence in youth with type 1 diabetes through parenting constructs. Journal of Developmental & Behavioral Pediatrics, 39, 508–515. doi: 10.1097/DBP.0000000000000579 [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Wang JT, Wiebe DJ, & White PC (2011). Developmental trajectories of metabolic control among White, Black, and Hispanic youth with type 1 diabetes. The Journal of Pediatrics, 159, 571–576. doi: 10.1016/j.jpeds.2011.03.053 [DOI] [PubMed] [Google Scholar]
  58. White NH (2015). Long-term outcomes in youth with diabetes mellitus. Pediatric Clinics of North America, 62, 889–909. doi: 10.1016/j.pcl.2015.04.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Wiebe DJ, Chow CM, Palmer DL, Butner JE, Butler JM, Osborn P, & Berg CA (2014). Developmental processes associated with longitudinal declines in parental responsibility and adherence to type 1 diabetes management across adolescence. Journal of Pediatric Psychology, 39, 532–541. doi: 10.1093/jpepsy/jsu006 [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Wiebe DJ, Helgeson VS, & Berg CA (2016). The social context of managing diabetes across the life span. American Psychologist, 71, 526–538. doi: 10.1037/a0040355 [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Worrall-Davies A, Owens D, Holland P, & Haigh D (2002). The effect of parental expressed emotion on glycaemic control in children with Type 1 diabetes. Journal of Psychosomatic Research, 52, 107–113. doi: 10.1016/S0022-3999(01)00293-8 [DOI] [PubMed] [Google Scholar]
  62. Wysocki T, & Gavin L (2004). Psychometric properties of a new measure of fathers’ involvement in the management of pediatric chronic diseases. Journal of Pediatric Psychology, 29, 231–240. doi: 10.1093/jpepsy/jsh024 [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

1
NIHMS1588593-supplement-1.pdf (96.5KB, pdf)

RESOURCES