Skip to main content
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2022 Aug 19.
Published in final edited form as: J Adolesc Health. 2018 Nov 2;64(3):340–346. doi: 10.1016/j.jadohealth.2018.08.029

The Profundity of the Everyday: Routinized Family Environments in Adolescence Predict Development in Young Adulthood

Allen W Barton 1, Gene H Brody 1, Tianyi Yu 1, Steven M Kogan 1,2, Edith Chen 3, Katherine B Ehrlich 1,4
PMCID: PMC9389627  NIHMSID: NIHMS1827471  PMID: 30392861

Abstract

Purpose:

The current study was designed to investigate the unique, long-term effects of routinized family environments during adolescence on multiple developmental domains in young adulthood for rural African Americans.

Methods:

Prospective data were collected annually for 6 years from 504 rural African American youth and their parents, beginning when the youth were 16.

Results:

Results indicated that youth whose primary caregivers reported more routinized family environments during adolescence reported less alcohol use, greater emotional self-regulation, lower epinephrine levels, and higher rates of college/university enrollment in young adulthood. These effects remained significant for nearly all outcomes with supportive parenting, harsh parenting, household chaos, socioeconomic risk, and sex controlled.

Conclusions:

Findings substantiate the benefits of consistent, predictable family environments for healthy development and suggest that family routines constitute an important, yet underdeveloped, factor for adolescents’ long-term development.

Keywords: African American, routines, family, self-regulation, alcohol use, education, epinephrine


The rural southeastern United States is one of the most impoverished regions in the country. Poverty and other aspects of disadvantage are powerful influences on children’s lives, forecasting lifelong trajectories in cognitive development (1), psychosocial development (2), and physical health (3). Despite their elevated risk, many African American youth who grow up in this region exhibit positive adjustment during adolescence and into young adulthood. Identifying protective factors that contribute to the long-term development of rural African American and other at-risk adolescents remains pivotal to public health research and practice.

Decades of research underscore the influence of the immediate family context for adolescents’ long-term development (4). To date, most of this research has focused on interpersonal (i.e., functional) aspects of the parent-child relationship, such as supportive parenting practices and overall relationship quality (4). In addition to these often-studied constructs, emerging findings from studies with adolescents (5, 6) as well as prior research with young children (7) converge to suggest that more structural aspects of the family environment—such as the degree of consistency, routinization, and stability in the home—may confer similar wide-reaching benefits for youth. Boyce and colleagues (8), in one of the first systematic investigations on the topic, described predictable, repeated, consistent patterns that characterize day-to-day home life—hereafter called family routines—as the fundamental “organizational units of ordinary life in families” (p. 194) that are fundamental to the health and well-being of the family and its individual members. Bronfenbrenner (9) similarly noted that healthy development necessitates an immediate environment characterized by predictability and consistency (see 10). More recently, leading developmental scientists have similarly maintained that predictability in one’s environment is of foundational importance to an understanding of human development (11). Consistent with this position, research on family routines with adolescents, although limited, has found associations between the degree of routinization in the home and children’s mental health, physical health, academic achievement, and delinquent behavior (5, 12, 13). Research on household chaos has also documented that disorganized and chaotic family environments forecast impaired cognitive, physiological, and psychosocial development in children (14, 15).

The benefits of routinized family environments, if confirmed, have significant implications for broadening basic and applied research with adolescents. Empirical support for the centrality of family routines for adolescent development, however, remains limited in three important ways. First, few studies of family routines have controlled for prominent parenting behaviors (e.g., support, harshness) and other family environment characteristics (e.g., chaos) that are known to influence development (6, 13, 14). Thus, it remains unclear whether predictable, well-structured family environments exert a unique effect on adolescents’ development or constitute an artifact of parenting processes and/or levels of household chaos. Second, most research on family routines has concentrated on psychological outcomes with school-aged children (7, 16). Consequently, little empirical work has investigated the long-term effects of family routines during adolescence on outcomes in young adulthood, and few studies have also considered the effects of family routines on non-psychological outcomes at any life stage (for exception, see 6). Third, minority families and those of low socioeconomic status (SES) appear to be underrepresented in this research, despite their elevated risk for experiencing unpredictable, chaotic family environments (10, 17).

To address these limitations, the present study investigated the unique effects of family routines during adolescence across four young adulthood outcomes: alcohol use, emotional self-regulation, epinephrine and norepinephrine levels (biological markers of stress resulting from sympathetic nervous system activation), and college/university enrollment at age 21. These outcomes were selected because they provide developmentally appropriate constructs in domains for which family routines have proven influential in young children (i.e., behavioral, psychosocial, physiological, and educational). Hypotheses were tested from a well-characterized sample of rural African American adolescents and each youth’s primary caregiver, with six waves of data collected yearly, beginning when youth were 16. Analytic models included supportive parenting, harsh parenting, family SES risk, youth sex, household chaos, and baseline measures (as available), thereby ruling out several alternative explanations for the hypothesized association of family routines with young adults’ outcomes.

Methods

Participants

The present study included a subsample of participants in a longitudinal study of African American families that began when youth were 11 years of age. All families resided in small towns and communities in rural Georgia in which poverty rates are among the highest in the nation and unemployment rates are above the national average (18). From lists that schools provided of fifth-grade students, 667 families were selected randomly for an initial assessment (see 19). Family routines were first assessed when the youth’s mean age was 16 years (M = 16.00; SD = .38). For the current study, we selected individuals who had completed at least the age 16 or age 17 assessment to satisfy requirements for missing data estimation. The final study sample included 504 participants. Comparisons of these 504 youth with the 163 who were not included revealed no differences at study enrollment in parenting practices, youth sex, parental education, or other demographic variables (e.g., poverty status). Of the youth in the final sample, 54% were female. Median family income per month was $1849 (SD = $2583); 46% of the families’ incomes were below 100% of the poverty level, and another 21% of the families’ incomes were between 100 and 150% of the poverty level.

Procedures

Six waves of data were collected on an approximately annual basis, three during adolescence (mean ages 16, 17, and 18) and three during young adulthood (mean ages 19, 20, and 21). Primary caregivers consented to their minor youth’s participation in the study, and minor youth assented to their own participation. Youth 18 years of age and older consented to their own participation. African American field researchers visited families’ homes to administer computer-based interviews at each wave of data collection using a standardized protocol. All assessments were conducted in private. Overnight urine voids were collected during all three waves in young adulthood. Participants were compensated $100 at each data collection wave. The study’s protocol was approved by the Institutional Review Board of the university at which the research took place.

Measures

Family routines.

Primary caregivers reported on routinization in the family using seven items adapted from the Family Routines Inventory (20). Sample items, which were answered dichotomously (1 if true, 0 if false), included, “We eat together as a family once a day,” “[Youth] goes to bed at a regular time,” and “Children in my house do regular household chores.” Items were summed, with a possible range of 0 to 7.

Supportive parenting.

Parents reported supportive caregiving practices using four items adapted from a scale that Carver and colleagues (21) developed; parents responded when youth were 16, 17, and 18 years of age. A sample item was, “[Youth] gets emotional support from me” (1 = not at all true; 5 = very true). Items were summed, and the resulting composite score was averaged across the three waves of data collection (Cronbach’s alpha ≥ .79 at all waves).

Harsh parenting.

Parents’ reports of verbally and physically harsh parenting were assessed using a four-item scale (22); parents responded to this measure when the youth were 16 and 17 years of age. A sample item was, “When [Youth] does something wrong, how often do you blow up at [him/her]?” 1 = never; 5 = always). Items were summed, and the resulting composite score was averaged across the two waves of data collection (Cronbach’s alpha ≥ .56 at each wave). Low internal consistency for measures of harsh parenting is common in the literature given low base rates of these disciplinary practices (23).

Household chaos.

Chaos and disorganization in the home was assessed using the 15-item Confusion, Hubbub, and Order Scale (24). Parents were asked to indicate as true (1) or false (0) statements about life in their homes. Examples included, “There is often a fuss going on at our home,” and “No matter what our family plans, it usually doesn’t seem to work out.” Items were summed, with a possible range of 0 to 15.

Family SES risk.

Family SES risk was computed from a six-item index of parent-reported sociodemographic factors. Six standard risk indicators were assessed (e.g., primary caregiver noncompletion of high school; family receipt of Temporary Assistance for Needy Families), with each risk factor scored dichotomously (0 if absent, 1 if present; see 19). Items were summed at each wave, with a possible range of 0 to 6. Scores at each wave were then averaged to create an assessment of mean family SES risk during the youth’s high school years.

Alcohol use.

Assessments of the frequency of past-month alcohol use, drawn from the Monitoring the Future study (25), were administered when youth were ages 19, 20, and 21. Youth were asked at each wave, “During the past month, on how many days have you had a drink of alcohol?” (0 = none; 5 = twenty or more). The mean of responses across the three waves were summed to create a composite score of alcohol use from 19 to 21 years of age.

University enrollment.

Current college/university enrollment was assessed as a demographic variable when youth were age 21. Youth were asked, “Are you currently enrolled in school or any type of educational program?” (1 = Yes, I am currently enrolled in a four-year college or university; 0 = otherwise). 21% reported enrollment in 4-year college/university at age 21.

Emotional self-regulation.

Youth’s emotional self-regulation was assessed as a latent variable with three indicators: self-regulation, emotional reactivity, and hostility. Self-regulation was measured using a 17-item questionnaire (26), emotional reactivity was assessed using a six-item scale (27), and hostility was assessed using an eight-item measure (28). Sample items for self-regulation, emotional reactivity, and hostility were, respectively, “I’m able to accomplish goals I set for myself,” “I operate on a short fuse when my emotions are involved,” and “You have a lot of anger inside you.” Responses ranged from 1 (strongly disagree) to 4 (strongly agree) for self-regulation and from 1 (strongly disagree) to 5 (strongly agree) for emotional reactivity and hostility. Items at each wave were summed and then averaged across ages 19 to 21 for each construct; the mean composite scores were used as the observed values for the latent variable. Cronbach’s alphas across all waves were ≥ .91 for self-regulation, ≥.63 for emotional reactivity, and ≥.90 for hostility.

Epinephrine and norepinephrine.

The epinephrine and norepinephrine measurement protocol was based on procedures that Evans (29) developed for field studies involving children and adolescents. Details of these protocols in the current sample are reported elsewhere (19). In brief, on the day of each data collection visit participants received instructions and supplies for collecting all urine voided overnight from 8 pm to 8 am. The following morning, a research assistant visited the home and transported the urine to a university laboratory. Epinephrine and norepinephrine were assayed with high-pressure liquid chromatography with electrochemical detection; levels of each biomarker were averaged across the three assessments.

Additional measures at age 16.

To strengthen the causal hypothesis outlined in our conceptual model, we selected additional measures assessed at age 16 to be treated as baseline control variables for each of the outcomes examined. No measures at age 16 were identical to the outcome measures, so we used conceptually similar, developmentally appropriate constructs. For alcohol use, we used a similar one-item measure of past-month alcohol use. For emotional self-regulation, we used youth-reported self-control as measured by eight items from the Children’s Self-Control Scale (30) (Cronbach’s alpha = .71). For college/university enrollment, we used youth’s orientation to schooling as measured via the efficacy subscale of the Academic Orientation Scale that Conger (31) developed (Cronbach’s alpha = .80). As no biological data were available from participants prior to age 19, no baseline control for epinephrine and norepinephrine was included.

The online supplement contains a complete list of items and response options for each measure.

Results

Preliminary analyses

Table 1 displays descriptive statistics and bivariate correlations for the sample. Primary caregivers reported engaging in a mean of 4.77 of the seven routines assessed (SD = 1.56), with a median of 5 routines across all three waves. The bivariate correlations between family routines and developmental outcomes supported hypothesis testing and statistical modeling. Measures included as baseline control variables were all correlated with their respective outcome. Missing data were minimal and were handled using full information maximum likelihood estimation. Models were run using Mplus 7.4 software (32).

Table 1.

Correlation Matrix and Descriptive Statistics for Study Variables (N = 504)

1 2 3 4 5 6 7 8 9 10 11 12 13
Outcomes
1. Alcohol use ---
2. Epinephrine 0.12
3. Norepinephrine −0.01 0.54
4. Self-regulation −0.13 0.00 0.06
5. Emo. reactivity 0.19 −0.00 0.02 −0.53
6. Hostility 0.22 0.07 −0.01 −0.57 0.58
7. Univ. enroll. a 0.06 −0.06 −0.01 0.19 −0.13 −0.11
Predictors
8. Family routines −0.14 −0.10 −0.04 0.19 −0.15 −0.15 0.16
9. Supp. parenting −0.06 −0.06 0.01 0.24 −0.09 −0.11 0.12 0.36
10. Harsh parenting 0.17 0.02 0.04 −0.14 0.14 0.11 −0.06 −0.13 −0.23
11. Household Chaos 0.08 0.02 0.05 −0.13 0.15 0.17 −0.10 −0.32 −0.32 0.33
12. Family SES risk −0.09 0.01 0.07 −0.10 0.04 0.09 −0.20 −0.02 −0.07 0.05 0.18
13. Sex b 0.11 0.31 −0.05 −0.07 −0.11 0.07 −0.07 −0.04 −0.13 0.00 0.00 −0.01

M 2.17 6.81 37.36 54.97 16.26 14.41 0.24 4.77 16.96 5.73 3.66 2.25 0.46
SD 2.30 4.78 21.65 7.04 3.60 5.79 N/A 1.56 2.49 1.28 2.12 1.25 N/A
Percent missing 0.00 0.60 0.60 0.00 0.00 0.00 10.51 0.00 0.00 0.00 0.00 0.00 0.00

Note. Descriptive statistics reflect pairwise deletion.

N/A = Not applicable to a dichotomous variable.

Correlations |r| > .086 significant at p < .05;

Correlations |r| > .121 significant at p < .01

a

1 = Currently enrolled in a 4-year college/university.

b

1 = Male.

Latent growth curve models of family routines during adolescence indicated no significant mean change over time across all families (M = −.08 [SE = .04]; p = ns) and no significant variability between families in rate of change over time (σ2 = .20 [SE = .12]; p = ns). Given these results, scores were averaged so that the resulting composite score indicated mean levels of routines between youth age 16 to 18.

Hypothesis Testing

To test our hypothesis, we constructed a series of models in which alcohol use, epinephrine levels, emotional self-regulation, and university enrollment were predicted from successive blocks of variables: family routines, sociodemographic factors, and baseline control variables (Block 1), parenting variables (Block 2), and household chaos (Block 3). Alcohol use was measured as a zero-inflated Poisson distribution, given the overdispersion of zero values. Emotional self-regulation was modeled as a latent variable (all factor loadings λ ≥ .69). Logistic regression was used for university enrollment.

Table 2 presents results of these analyses for all developmental outcomes. A consistent pattern emerged: Family routines demonstrated significant effects across all outcomes above and beyond the effects of other variables included in the model, including baseline control variables. Specifically, with supportive parenting, harsh parenting, family SES risk, sex, and the age 16 baseline measures controlled (i.e., Blocks 1 and 2), youth whose primary caregivers reported more family routines during adolescence reported less alcohol use during young adulthood and displayed lower epinephrine levels compared with youth from families with fewer reported routines. Family routines during adolescence were also associated positively with youth’s emotional self-regulation and college/university enrollment in young adulthood. Odds ratios indicated that every unit of increase in family routines was associated with a 10% increase in the likelihood of college/university enrollment. Even after the addition of household chaos into the model (Block 3), a similar pattern of results appeared. Family routines continued to predict epinephrine levels, emotional self-regulation, and college/university enrollment; the one exception was alcohol use, which household routines no longer significantly predicted.

Table 2.

Main effects of family routines on young adulthood outcomes

Model 1 (n = 504)
Model 2 (n = 501)
Alcohol use (ages 19 – 21) 1
Epinephrine (ages 19 – 21)
Norepinephrine (ages 19-21)
B (se) B (se) B (se) B (β) (se) B (β) (se) B (β) (se) B (β) (se)

Block 1 Block 2 Block 3 Block 1 Block 2 Block 3 Block 1 Results of Blocks 2 and 3 not displayed given non-significant results from Block 1
Family routines (ages 16-18) −0.08** (.03) −0.06* (.03) −0.06 (.03) −0.28 (−.10)* (.13) −0.29 (−.10)* (.14) −0.29 (−.10)* (.14) −0.61 (−.04) (.62)
SES risk (age 16-18) −0.06 (.04) −0.07 (.04) −0.07 (.04) 0.03 (.01) (.16) 0.03 (.01) (.16) 0.03 (.01) (.16) 1.15 (.06) (.78)
Youth sex2 0.28** (.09) 0.28** (.09) 0.28** (.09) 2.94 (.31)** (.40) 2.95 (.31)** (.41) 2.95 (.31)** (.41) −2.04 (−.05) (1.93)
Baseline control (age 16) 0.27** (.07) 0.27** (.06) 0.27** (.06) --- --- --- ---
Supp. parenting (age 16-18) −0.01 (.02) −0.01 (.02) 0.03 (.02) (.09) 0.03 (.01) (.09)
Harsh parenting (ages 16-17) 0.07* (.03) 0.06* (.03) 0.03 (.01) (.16) 0.03 (.01) (.16)
Household Chaos (ages 16-18) 0.01 (.02) −0.04 (−.02) (.11)
Model 3 (n = 463) Model 4 (n = 415)
Emotional Self-Regulation (ages 19 – 21)
University Enrollment (age 21) 1
B (β) (se) B (β) (se) B (β) (se) Odds Ratio (se) Odds Ratio (se) Odds Ratio (se)

Block 1 Block 2 Block 3 Block 1 Block 2 Block 3
Family routines (ages 16-18) 0.54 (.15)** (.17) 0.44 (.13)* (.18) 0.41 (.12)* (.18) 1.15 ** (.05) 1.13 * (.05) 1.13 * (.05)
SES risk (age 16-18) −0.25 (−.06) (.21) −0.22 (−.05) (.21) −0.19 (−.05) (.21) −0.83 ** (.06) −0.83** (.06) −0.83** (.06)
Youth sex2 −0.06 (−.01) (.53) −0.02 (−.00) (.53) −0.02 (−.00) (.53) 0.89 (.15) 0.90 (.15) 0.90 (.15)
Baseline control (age 16) 0.67 (.51)** (.07) 0.65 (.49)** (.07) 0.64 (.49)** (.07) 1.07** (.02) 1.07** (.02) 1.07** (.02)
Supp. parenting (age 16-18) 0.14 (.06) (.12) 0.12 (.05) (.12) 1.02 (.03) 1.02 (.03)
Harsh parenting (ages 16-17) −0.31 (−.07) (.21) −0.28 (−.06) (.21) 0.98 (.05) 0.98 (.05)
Household Chaos (ages 16-18) −0.10 (−.04) (.14) 0.99 (.05)

Note.

1

Standardized parameters are not available because alcohol use was modeled as a zero-inflated Poisson distribution.

2

1 = university enrollment. 1 = male. Model 1 was estimated using Monte Carlo integration algorithm with restricted maximum likelihood estimation given zero-inflated Poisson distribution. Models 2 was estimated using maximum likelihood estimation and was fully constrained (no model fit indices).

*

p < .05;

**

p < .01

Note.

1

1 = Currently enrolled in university.

2

1 = male. Models 3 and 4 were estimated using maximum likelihood estimation. Model 4 was fully constrained (no model fit indices). Model 3 fit: Block 1: χ2(7) = 30.429 (p < .01). CFI = .96; RMSEA = .085, [.06, .12], SRMR = .027. Block 2: χ2(11) = 45.89 (p < .01). CFI = .94; RMSEA = .083, [.06, .11], SRMR = .028. * p < .05; ** p < .01. Block 3: χ2(13) = 50.78 (p < .01). CFI = .93; RMSEA = .079, [.06, .10], SRMR = .026.

*

p < .05;

**

p < .01.

Significant effects associated with other predictors were sparse. With other variables in the model controlled, neither supportive parenting nor harsh parenting was associated with any other outcomes in young adulthood. For sociodemographic variables, family SES risk was negatively associated with youth’s university enrollment at age 21 and, compared with young women, young men reported more alcohol use, evinced higher epinephrine levels, and were less likely to be enrolled at a 4-year college/university at age 21.

Post hoc mediation and moderation analyses

Given these significant findings, subsequent analyses were conducted to investigate (a) emotional self-regulation at age 19 as a mediator for the effects of family routines on alcohol use, epinephrine levels, and university enrollment (following procedures outlined by Hayes (33)), and (b) SES risk as a moderator of the effects of family routines on young adult outcomes (following procedures outlined by Aiken and West (34). No indirect effects through age 19 emotional self-regulation were significant; the Family Routines × SES risk interaction term also was not significant for any outcome (tabulated results available from the first author), indicating that the effects of family routines did not vary by levels of SES risk.

Summary

In sum, the results confirmed our hypothesis that, among this sample of rural African Americans, routinized and predictable family environments during adolescence would be associated with a variety of positive developmental outcomes in young adulthood above and beyond parenting, household chaos, and sociodemographic variables.

Discussion

Much of family life involves ordinary and repetitious activities: eating meals, doing household chores, getting ready for bed, and so forth. Although commonplace and, at times, seemingly trivial, the degree of predictability and consistency (or lack thereof) in everyday family life appears to have clear implications for adolescent development. From a 6-year prospective study with multi-informant, multi-level data, the current results substantiate the benefits of predictable family environments during adolescence for multiple outcomes in young adulthood for rural African Americans. Notably, the salutary effects of parent-reported family routines during adolescence were documented across behavioral, physiological, psychosocial, and educational domains and were observed to be independent from the effects of supportive parenting, harsh parenting, SES risk, biological sex, and, in most instances, household chaos.

Findings from the current study highlight the developmental significance of routinized family environments during adolescence in addition to young childhood, where most prior research has focused (7, 35). The present findings are also consistent with prior research on the benefits of family routines on multiple domains of development, including psychological and physiological well-being (5). Given emerging research findings suggesting that excelling in the areas of education, psychosocial adjustment, and behavior adjustment can come at a cost for minority youths’ physical health (36), there is a clear need for research that identifies processes that simultaneously promote psychological and physiological health. The present results suggest that a predictable, consistent family environment may represent such a construct.

The current results also have important implications for applied research and practice, particularly family-centered prevention endeavors. Traditionally, family-centered prevention programs have devoted little attention to family routines and chaos, focusing instead on cognitive-behavioral techniques common to parenting and couple-focused programs (37, 38). Both the current results and others (e.g., 6), however, suggest that enhancing predictability in the family environment may be as influential on children’s development as enriching family members’ behaviors. In addition, for children residing in chaotic, unpredictable family environments, even well-designed cognitive-behavioral interventions may be ineffective without first addressing instability in the home (39). Previous applied research efforts focused on modifying household routines to promote children’s health behaviors have documented increases in sleep duration and decreases in television viewing among young children (40).

Given non-significant mediation or moderation analyses, future research can continue to investigate mechanisms through which family routines exert this effect in young adults, as well as in persons for whom the effect of family routines is more (or less) pronounced. Future research can also consider factors that account for family routines’ prediction of variability in levels of epinephrine, but not norepinephrine. Because the effects of epinephrine are brought about by the adrenal medulla, whereas norepinephrine effects are brought about by the sympathetic nervous system, these results may suggest that routinized family environments more directly shape adrenal activity than the sympathetic nervous system.

Several limitations of the study should be addressed in future research. First, family routines were not assessed prior to youth age 16, precluding examinations of the effect of routines at earlier developmental stages. Second, the lack of observational data limits cross-validation of self-report responses. Third, although statistical models controlled for earlier levels of most outcomes, causality cannot be empirically confirmed given the lack of experimental randomization. These limitations notwithstanding, the results of this study demonstrate the unique predictive significance of family routines during adolescence for rural African Americans’ developmental outcomes and provide empirical support for increasing attention to family routines in basic and applied research designed to promote child and family well-being.

Supplementary Material

supplementary

IMPLICATIONS AND CONTRIBUTION.

African American adolescents experiencing routinized family environments across ages 16-18 years exhibited, in young adulthood, lower alcohol use and epinephrine levels, higher emotional self-regulation, and greater likelihood of being enrolled in a 4-year university. These effects generally persisted with potential confounding variables of parenting, household chaos, and SES risk controlled.

Acknowledgment

This research was supported by Award Number R01 HD030588 from the National Institute of Child Health and Human Development and Award Number P30 DA027827 from the National Institute on Drug Abuse, both to Gene H. Brody. The research presented in this paper is solely the responsibility of the authors and does not necessarily represent the official views of National Institutes of Health, which had no role in the study’s design, execution, or submission for publication. None of the authors reports any conflicts of interest, financial or otherwise. The authors thank Eileen Neubaum-Carlan for her editorial assistance in the preparation of this article.

Disclosure Statement

No authors declare any potential conflict of interested, real or perceived. This study was funded by grants from the National Institutes of Health awarded to Dr. Gene Brody (R01 HD030588 and P30 DA027827); the study sponsor had no involvement in the study design; the collection, analysis, and interpretation of data; the writing of the report; and the decision to submit the manuscript for publication. Dr. A. W. Barton wrote the first draft of the manuscript. No honorarium, grant, or other form of payment was given to anyone to produce the manuscript.

References

  • [1].Heckman JJ. Skill formation and the economics of investing in disadvantaged children. Science 2006, June 30;312:1900–1902. [DOI] [PubMed] [Google Scholar]
  • [2].Bradley RH, Corwyn RF. Socioeconomic Status and Child Development. Annual Review of Psychology 2002;53:371–399. [DOI] [PubMed] [Google Scholar]
  • [3].Miller GE, Chen E, Parker KJ. Psychological stress in childhood and susceptibility to the chronic diseases of aging: Moving toward a model of behavioral and biological mechanisms. Psychological Bulletin 2011;137:959–997. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [4].Kogan SM. The Role of Parents and Families in Preventing Young Adult Alcohol Use. Journal of Adolescent Health 2017;61:127–128. [DOI] [PubMed] [Google Scholar]
  • [5].Manczak EM, Williams D, Chen E. The Role of Family Routines in the Intergenerational Transmission of Depressive Symptoms between Parents and their Adolescent Children. J Abnorm Child Psychol 2017;45:643–656. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [6].Manczak EM, Leigh AKK, Chin C-P, et al. Consistency matters: Consistency in the timing and quality of daily interactions between parents and adolescents predicts production of proinflammatory cytokines in youths. Development and Psychopathology 2017:1–10. [DOI] [PubMed] [Google Scholar]
  • [7].Spagnola M, Fiese BH. Family Routines and Rituals: A Context for Development in the Lives of Young Children. Infants & Young Children 2007;20:284–299. [Google Scholar]
  • [8].Boyce WT, Jensen EW, James SA, et al. The family routines inventory: Theoretical origins. Social Science & Medicine 1983;17:193–200. [DOI] [PubMed] [Google Scholar]
  • [9].Bronfenbrenner U. The ecology of human development: experiements by nature and design. Cambridge, MA: Harvard University Press, 1979. [Google Scholar]
  • [10].Evans GW, Gonnella C, Marcynyszyn LA, et al. The Role of Chaos in Poverty and Children’s Socioemotional Adjustment. Psychological Science 2005;16:560–565. [DOI] [PubMed] [Google Scholar]
  • [11].Ellis BJ, Figueredo AJ, Brumbach BH, et al. Fundamental Dimensions of Environmental Risk. Human Nature 2009;20:204–268. [DOI] [PubMed] [Google Scholar]
  • [12].Brody GH, Flor DL. Maternal psychological functioning, family processes, and child adjustment in rural, single-parent, African American families. Developmental Psychology 1997;33:1000–1011. [DOI] [PubMed] [Google Scholar]
  • [13].Hair EC, Moore KA, Garrett SB, et al. The Continued Importance of Quality Parent–Adolescent Relationships During Late Adolescence. Journal of Research on Adolescence 2008;18:187–200. [Google Scholar]
  • [14].Evans GW, Wachs TD. Chaos and its influence on children’s development: An ecological perspective. Washington, DC: American Psychological Association, 2010. [Google Scholar]
  • [15].Chen E, Cohen S, Miller GE. How Low Socioeconomic Status Affects 2-Year Hormonal Trajectories in Children. Psychological Science 2010;21:31–37. [DOI] [PubMed] [Google Scholar]
  • [16].Fiese BH, Tomcho TJ, Douglas M, et al. A review of 50 years of research on naturally occurring family routines and rituals: Cause for celebration? Journal of Family Psychology 2002;16:381–390. [DOI] [PubMed] [Google Scholar]
  • [17].Jarrett RL, Bahar OS, Kersh RT. “When We Do Sit Down Together”: Family Meal Times in Low-Income African American Families With Preschoolers. Journal of Family Issues 2014. [Google Scholar]
  • [18].DeNavas-Walt C, Proctor BD. Income and poverty in the United States: 2013 (Current Population Reports P60-249). Washington, DC: U.S. Census Bureau; 2014. [Google Scholar]
  • [19].Brody GH, Yu T, Chen Y-f, et al. Cumulative socioeconomic status risk, allostatic load, and adjustment: A prospective latent profile analysis with contextual and genetic protective factors. Developmental Psychology 2013;49:913–927. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [20].Jensen EW, James SA, Boyce WT, et al. The family routines inventory: Development and validation. Social Science & Medicine 1983;17:201–211. [DOI] [PubMed] [Google Scholar]
  • [21].Carver CS, Scheier MF, Weintraub JK. Assessing coping strategies: A theoretically based approach. Journal of Personality and Social Psychology 1989;56:267–283. [DOI] [PubMed] [Google Scholar]
  • [22].Simons RL, Johnson C, Beaman J, et al. Parents and peer group as mediators of the effect of community structure on adolescent problem behavior. American Journal of Community Psychology 1996;24:145–171. [DOI] [PubMed] [Google Scholar]
  • [23].Brody GH, Ge X, Conger RD, et al. The influence of neighborhood disadvantage, collective socialization, and parenting on African American children’s affiliation with deviant peers. Child Development 2001;72:1231–1246. [DOI] [PubMed] [Google Scholar]
  • [24].Matheny AP, Wachs TD, Ludwig JL, et al. Bringing order out of chaos: Psychometric characteristics of the confusion, hubbub, and order scale. Journal of Applied Developmental Psychology 1995;16:429–444. [Google Scholar]
  • [25].Johnston LD, O’Malley PM, Bachman JG. Monitoring the Future national survey results on drug use 1975-1999. Volume I: Secondary school students (NIH Publication No. 00-4802). Bethesda, MD: National Institute on Drug Abuse., 2000. [Google Scholar]
  • [26].Brown JM, Miller WR, Lawendowski LA. The self-regulation questionnaire. Innovations in clinical practice: A source book 1999;17:281–292. [Google Scholar]
  • [27].Taylor SE, Seeman TE. Psychosocial Resources and the SES-Health Relationship. Annals of the New York Academy of Sciences 1999;896:210–225. [DOI] [PubMed] [Google Scholar]
  • [28].Joe GW, Broome KM, Rowan-Szal GA, et al. Measuring patient attributes and engagement in treatment. Journal of Substance Abuse Treatment 2002;22:183–196. [DOI] [PubMed] [Google Scholar]
  • [29].Evans GW. A multimethodological analysis of cumulative risk and allostatic load among rural children. Developmental Psychology 2003;39:924–933. [DOI] [PubMed] [Google Scholar]
  • [30].Humphrey LL. Children’s and teachers’ perspectives on children’s self-control: The development of two rating scales. Journal of Consulting and Clinical Psychology 1982;50:624–633. [DOI] [PubMed] [Google Scholar]
  • [31].Conger RD. Iowa youth and families project, Wave A (Report prepared for Iowa State University). Ames, IA: Institute for Social and Behaioral Research, 1989. [Google Scholar]
  • [32].Muthén LK, Muthén BO. Mplus User’s Guide. . 7th ‘edition’. Los Angeles, CA: Muthén & Muthén, 1998-2015. [Google Scholar]
  • [33].Hayes AF. Beyond Baron and Kenny: Statistical Mediation Analysis in the New Millennium. Communication Monographs 2009;76:408–420. [Google Scholar]
  • [34].Aiken LS, West SG. Multiple regression: Testing and interpreting interactions. Thousand Oaks, CA: Sage, 1991. [Google Scholar]
  • [35].Simpson JA, Griskevicius V, Kuo SIC, et al. Evolution, stress, and sensitive periods: The influence of unpredictability in early versus late childhood on sex and risky behavior. Developmental Psychology 2012;48:674–686. [DOI] [PubMed] [Google Scholar]
  • [36].Miller GE, Yu T, Chen E, et al. Self-control forecasts better psychosocial outcomes but faster epigenetic aging in low-SES youth. Proceedings of the National Academy of Sciences 2015;112:10325–10330. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [37].Van Ryzin MJ, Roseth CJ, Fosco GM, et al. A component-centered meta-analysis of family-based prevention programs for adolescent substance use. Clinical Psychology Review 2016;45:72–80. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [38].Johnson MD, Bradbury TN. Contributions of Social Learning Theory to the promotion of healthy relationships: Asset or liability? Journal of Family Theory & Review 2015;7:13–27. [Google Scholar]
  • [39].Weisner TS. Well-being, chaos, and culture: Sustaining a meaningful daily routines. In: Evans GW, Wachs TD, eds. Chaos and its influence on children’s development. Washington, DC: American Psychological Association, 2010:211–224. [Google Scholar]
  • [40].Haines J, McDonald J, O’Brien A, et al. Healthy habits, happy homes: Randomized trial to improve household routines for obesity prevention among preschool-aged children. JAMA Pediatrics 2013;167:1072–1079. [DOI] [PubMed] [Google Scholar]

Associated Data

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

Supplementary Materials

supplementary

RESOURCES