Exploring Associations of Household Chaos and Child Health Behaviors in Rural Families

Abstract

OBJECTIVES:

Regular physical activity (PA) and limited sedentary behavior (SB) and screen-time are essential for children’s health, and rural children are less likely to meet PA recommendations. Household chaos (HHchaos), defined as disorganization characterized by noise and crowding, is associated with negative behavioral outcomes in children. The present study examined associations between HHchaos and PA, SB, and screen-time among rural children.

METHODS:

Parent/child dyads (n=105) were enrolled in NU-HOME, a family-based, obesity prevention randomized-controlled trial. Hierarchical regression analyses of baseline data were used to examine unadjusted and adjusted (child age, sex, BMI z-scores and economic assistance) associations between HHchaos and outcomes.

RESULTS:

Children were 8.96±1.05 years old, 58% female and 53% were categorized as normal weight. Total daily PA, SB, and weekday screen-time were 259.1±58.22 minutes, 499.9±77.46 minutes, and 1.79±1.48 hours, respectively. Unadjusted HHchaos scores (mean=5.04±3.6; range=0–15 with higher score indicating more chaos) were not associated with child PA or SB. HHchaos was positively associated with child screen-time in all models (p<0.01).

CONCLUSIONS:

Our findings suggest that decreasing household chaos may be useful in reducing child screen-time. Our findings align with current literature in viewing household chaos as a risk factor for children’s health.

Introduction

Household chaos, defined as the level of noise, disorganization, and crowding in a home,¹ is an environmental factor that can affect a child’s health behavior. Household chaos may contribute to a lack of structure resulting in difficulty maintaining routines; children in homes with higher household chaos have been shown to experience an increased likelihood of behavioral problems,² poorer sleep,³ greater screen-time,⁴ and lower early literacy skills.⁵ Parents and children residing in crowded homes, characterized by the number of children or other residents per room, consistently report greater negative familial interactions.⁶ Additionally, families in homes with high household chaos report eating fewer family meals and experience greater stress around preparing meals.⁷ Conversely, structured family environments tend to be more developmentally beneficial for children.⁸ Routines around bedtime, chores, and mealtimes are associated with positive health outcomes, including improved sleep quality and shorter periods of sickness.^9,10 The reduction of stress and added opportunity for positive interactions between parents and children that can result from establishing routines¹¹ may aid children in creating and maintaining their own routines. Yet, further exploration is needed regarding home environment and health behaviors such as physical activity (PA) and sedentary behavior (SB), which play an important role in leading a healthy lifestyle.

Although a recent review investigating physical activity and screen-time comparisons between urban and rural youth indicated mixed results,¹² weight status differences between rural and urban children are more consistently reported in the literature, with rural children more likely to have overweight and obesity.^13–16 Given that health behaviors, including physical activity, sedentary behavior, and screen-time, play a key role in weight status,^17,18 investigating barriers to these health behaviors such as household chaos could inform future obesity prevention interventions among rural populations in the US. Yet, to our knowledge, no empirical studies have examined the relationship of household chaos with children’s health behaviors in rural families. Further, household chaos has not been explored specifically in the context of PA and SB, and only briefly explored with child screen-time.⁴ Examining associations between household chaos and these health behaviors is innovative and furthers knowledge about how family routines (or lack thereof) influence children’s health among those in rural settings.

Sixty minutes of daily moderate-to-vigorous physical activity (MVPA) is recommended for children between the ages of 6 and 17 in the United States.¹⁹ PA lessens the risk of conditions including heart disease, type II diabetes, osteoporosis, and obesity.²⁰ It is also linked to higher cognition and academic achievement.²¹ Children who participate in regular PA experience lower levels of stress and anxiety in addition to greater self-esteem.²² Despite these extensive benefits, only 24% of US children meet the daily recommendation.²⁰ Parent PA,²³ PA self-efficacy,²⁴ and parental support²⁵ are factors commonly cited to have influence on a child’s exercise behavior.

SB is defined as any action that is completed in a sitting or lying down position expending no more than 1.5 METS (metabolic equivalents of energy) (eg, reading a book, drawing a picture, or watching television).²⁶ Although there are no specific SB guidelines, Americans are encouraged to reduce their sedentary time, and begin by replacing it with light PA.¹⁹ On average, children spend 51% of their after-school time engaging in sedentary activities, including screen-time.²⁷ Screen-based activities are often examined as a measure of SB in relevant literature. The national screen-time recommendation for elementary-aged children is no more than two hours daily,^28–31 but the average screen-time reported in 2015 among children aged 8–12 years is 4 hours and 36 minutes per day.³² Parent screen-time³³ is an influential factor on a child’s screen-time.

Examining the relationship between household chaos with child PA, SB, and screen-time provides further insight into how family milieu influences children’s health. If the lack of structure caused by household chaos does in fact add difficulty when establishing routines, reducing household chaos may be a strategy to promote healthy behaviors. Therefore, the aim for the present study is to determine whether child PA, SB, and screen-time are associated with household chaos in rural families.

Methods

Participants and Recruitment

Baseline data were collected in 2017–2018 as part of the NU-HOME study, a randomized controlled trial to test a family-based, child obesity prevention intervention in rural Minnesota. Participants were eligible for the NU-HOME trial if they lived within 50 miles of the New Ulm, Minnesota community and were not planning to move outside of the area within the following six months. Child participants were required to be 7–10 years of age. Most participants were recruited by a letter from a local medical center (53%). Others were recruited by friends and family members, community events, and fliers from their child’s school.

A total of 114 parent-child dyads were included in the NU-HOME trial and randomly assigned to either the intervention group (n=58) or wait-list control group (n=56). Of these 114 participant pairs, 105 (92%) were included in the analytic sample for the current study due to 9 children with incomplete accelerometry data (minimum of 8 hours of wear time on ≥3 days). Written consent and assent were obtained from parent and child participants, respectively. The study was approved by the University of Minnesota Institutional Review Board and the Quorum Institutional Review Board.

Data Collection Instruments and Measures

For data collection, parent and child participants were asked to travel to a local community school district building. Parent participants completed psychosocial surveys about themselves, their households, and their child that were programmed in REDCap software and administered electronically using an iPad. Child participants were fitted with accelerometers and completed interviews with trained research staff.

Tanita scales (TBF400-Total Body Composition Analyzer) and other standardized procedures³⁴ were used by trained staff to measure child and parent participant height and weight.³⁵ BMI was calculated [weight (kg)/height (m)²]³⁶ using height and weight measurements taken during each data collection timepoint. Child BMI percentiles and standardized z-scores were generated based on CDC growth charts to create an age-adjusted and sex-adjusted BMI (kg/m²).

Primary Independent Variable of Interest

Household Chaos.

As part of the psychosocial survey, parent participants completed an adapted version of the Confusion, Hubbub, and Order Scale (CHAOS), which assesses the level of environmental chaos present in their home.¹ One item from the original survey was adapted to read “electronics take up a lot of our time at home” instead of “the telephone takes up a lot of our time at home.” Other CHAOS questionnaire items included statements such as, ‘we almost always seem to be rushed’, ‘it’s a real zoo in our home,’ and ‘you can’t hear yourself think in our home.’ Response options were “true” or “false”, coded as 1 or 0, respectively. Items were summed to create a chaos score. The scale range was from 0–15 with a higher score indicating a higher level of chaos (scale development sample: Cronbach’s α=0.79, test-retest r=0.74; current study sample: Cronbach’s α=0.83). For analysis, the CHAOS score was dichotomized using a median split; low chaos (less than or equal to 4) versus high chaos (greater than 4) households.

Primary Outcomes of Interest

Child Physical Activity and Sedentary Behavior.

Child PA and SB were measured by accelerometry (ActiGraph wGT3X-BT and GT3XP-BTLE models, Fort Walton Beach, FL). The ActiGraph has been validated for use with children and has high inter-rater reliability (R_t=0.87) and strong correlations with energy expenditure (r=0.78).³⁷ Child participants were fitted with an accelerometer by a trained research assistant and instructed to wear the monitor on their right hip. Children were encouraged to wear it for most waking hours on seven consecutive days except for time spent doing water-based activities (eg, swimming or bathing). Monitors were initialized prior to data collection and were set to begin collecting data at 6:00am on the day after they were distributed to participants. Data were collected and stored in 10-second epochs.

Data collected via accelerometry were analyzed using ActiLife software (version 6.9.1; Actigraph, LLC, Pensacola, FL). Non-wear time was defined as any period of ≥60 minutes of consecutive zeros. Participants must have had a minimum of 8 hours of wear time on ≥3 days to be included in analyses. Nine of the 114 participants (7.9%) were excluded from analysis due to not meeting the wear time requirement.

Evenson cutpoints for children were used to classify PA intensities: sedentary (0–100), light (101–2295), moderate (2296–4011), and vigorous (≥4012).³⁸ Total PA included counts above 100 and MVPA included counts above 2296.

Child Screen-Time.

Items adapted from the Planet Health study evaluated child screen-time as hours per weekday and weekend day (present study sample: Cronbach’s α=0.95).³⁹ Parents were asked to answer two questions on the amount of time their child typically participates in a variety of screen-based activities on weekdays and weekends. Response options were none, less than ½, ½−1, 1 ½−2, 2 ½−4, 4 ½−6, and ≥6 hours/day and were recoded to 0, 0.3, 0.75, 1.75, 3.25, 5.25, and 6.5, respectively, to create a continuous variable.

Behavior-Related Covariates

Parent Physical Activity.

Parent participants’ weekly PA behavior was assessed using an adapted Godin-Shepard Leisure Time Physical Activity Questionnaire.⁴⁰ Parents were asked how many hours they spend doing exercise that is strenuous, moderate, and mild in a typical week. Examples of physical activities were provided for each intensity level. Responses were none, <½, ½−2, 2 ½−4, 4 ½−6, and >6 hours/week and were recoded as 0, 0.3, 1.3, 3.3, 5.3, and 6.3, respectively, to create a continuous variable. Parent participants’ PA behavior was evaluated as moderate-to-vigorous and total weekly PA (current study sample: Cronbach’s α=0.92). Weekly moderate-to-vigorous activity was calculated by summing parent’s moderate and vigorous PA responses. Total weekly activity was created by adding all mild, moderate, and vigorous PA amounts reported by parents. The present study analyzed moderate-to-vigorous and total PA as these measures most relate to the Physical Activity Guidelines for Americans.²⁰

Child Physical Activity Self-Efficacy.

Child participants’ PA self-efficacy was assessed using an adapted self-efficacy questionnaire (test retest correlations ranged from 0.61 to 0.82; current study sample Cronbach’s α=0.69).⁴¹ Child participants were asked questions such as, ‘How hard do you think it would be to be physically active instead of watching TV?’ ‘How hard do you think it would be to play sports on a team?’ and ‘How hard do you think it would be to be physically active most days of the week?’. Response options were “not at all hard”, “a little hard”, and “very hard” and coded as 1, 2, and 3, respectively. Items were summed and the summation score ranged from 9–25, with a higher score indicating lower self-efficacy.

Family Support of Physical Activity.

Family support of PA was assessed on the child survey using an adapted 5-item scale from Saunders, Motl, Dowda, Dishman and Pate ⁴² (current study sample Cronbach’s α=0.54). Child participants answered questions about their parents’ support of their PA behaviors. Items prompted children to respond with how often an adult might ‘encourage [them] to be physically active or play sports’ or ‘watch [them] while being physically active or playing sports.’ Responses included “none”, “once”, “sometimes”, “almost every day”, and “every day” coded as 0, 1, 2, 3, and 4, respectively. Responses were summed and the summation score ranged from 0–20, with a higher score indicating higher familial support.

Parent Screen-Time.

Parent screen-time was assessed similarly to child screen-time using an adapted questionnaire from the Planet Health study.³⁹ Parent screen-time data were collected via self-report. Parents were asked to answer two questions on the amount of time they typically participate in a variety of screen-based activities on weekdays and weekends. Response options were none, less than ½, ½−1, 1 ½−2, 2 ½−4, 4 ½−6, and ≥6 hours/day and were recoded to 0, 0.3, 0.75, 1.75, 3.25, 5.25, and 6.5, respectively, to create a continuous variable. Parent participant screen-time was evaluated as mean daily hours. Weekly screen-time hours were calculated by multiplying the number of weekday hours by 7 and weekend hours by 2 and adding the totals together. Weekly screen-time hours were used to calculate mean daily screen-time by dividing the weekly hours by 7.

Demographic Variables

Parent and child ages were calculated from parent-reported birthdates of each and the date of data collection. Economic assistance was assessed as yes if parents answered “yes” to either ‘does your child receive free or reduced-price school lunch?’ or ‘does your household receive public assistance?’. Parents indicated the number of children living in their household, their sex, and their child’s sex.

Statistical Analysis

SAS 9.4 was used to conduct analyses in the present study. Statistical significance was determined at p<0.05. Descriptive analyses (means and frequencies) were run for the sociodemographic outcomes of interest and household chaos.

Hierarchical linear regression models were analyzed for child PA, SB, and screen-time outcomes. To address the aim of the current study, three levels of models were run. First, unadjusted models were run containing only household chaos and the dependent variable of interest. In the secondary models, the following potential confounders were added: child age, child sex, child BMI z-score, and whether the family receives economic assistance. To assess the relative contribution of household chaos scores to each model in the context of known factors associated with children’s PA, covariates were added during the third and final set of models such that PA models (moderate-to-vigorous and total) included parent PA, child PA self-efficacy, and child PA support, whereas models using SB or screen-time (weekday and weekend) as a dependent variable included parent screen-time. The number of children in the household was included as a covariate for each outcome of interest, as this variable has been shown to play a role in household chaos.

Results

Table 1 presents descriptive statistics of child, parent, and household variables. Slightly more child participants identify as female (58.1%) than male. Thirty-one parent participants (29.5%) report that they receive economic assistance. More parent participants identify as female (98.1%) than male. The mean age for parents is thirty-eight, and most (40%) were classified as having obesity. The mean value of household chaos is 5.04±3.60 on a scale from 1–15.

Table 1.

Descriptive Sociodemographic Characteristics of the Analytic Sample (n=105)

Descriptive Variables	Participants
Child Variables
Age, mean years (SD)a	8.96 (1.06)
BMI z-score, mean (SD)	0.92 (0.94)
Weight status,b n (%)
Normal	56 (53.33)
Overweight	23 (21.90)
Obese	26 (24.76)
Sex, n (%)
Male	44 (41.90)
Female	61 (58.10)
Parent Variables
Age, mean years (SD)	38 (5.42)
BMI, mean kg/m2 (SD)	29.98 (6.87)
Weight status,c n (%)
Normal	24 (22.86)
Overweight	37 (35.24)
Obese	42 (40.00)
Sex, n (%)
Male	2 (1.90)
Female	103 (98.10)
Household Variables
Economic assistance,d n (%)
Yes	31 (29.52)
No	74 (70.48)
Number of children living in household, mean # (SD)	2.99 (1.95)
Household chaos scores,e mean (SD)	5.04 (3.60)

^aSD denotes standard deviation

^bChild weight status categories include normal (5^th percentile to 84^th percentile), overweight (85^th percentile to 94^th percentile), and obese (≥95^th percentile).

^cParent weight status categories include normal (18.5–24.9), overweight (25.0–29.9), and obese (30 and above).

^dEconomic assistance represents parent-reported public assistance or child receiving free or reduced-price school lunch.

^eHousehold chaos is assessed by the Confusion, Hubbub, and Order Scale ¹. The scale ranges from 0–14 with a higher score indicating a higher level of household chaos.

Table 2 presents descriptives and mean differences for the three primary outcomes of interest (child PA, SB, and screen-time) based on level of household chaos. There were no statistically significant differences in child PA and SB by household chaos groups. However, both weekday and weekend child screen-time were significantly different between low and high chaos groups by approximately 40 minutes, with those in the high chaos group engaging in more screen-time.

Table 2.

Comparative Statistics of Child Physical Activity, Sedentary Behavior, and Screen-Time for the Total Analytic Sample and by Low and High Chaos Households

Child Health Behaviors	Analytic Sample	Household Chaos
	(n=105)	Low (≤4) (n=58)	High(>4) (n=47)
	Mean (SD)	Mean (SD)	Mean (SD)
Physical activity,a min/day
Moderate-to-vigorous	44.95 (18.58)	45.76 (18.79)	43.94 (18.48)
Totalb	259.08 (58.22)	257.44 (53.33)	261.10 (64.28)
Sedentary behavior,c min/day	499.93 (77.46)	503.06 (74.85)	496.06 (81.20)
Screen-time, hrs/day
Weekday	1.79 (1.48)	1.49 (1.33)**	2.17 (1.58)**
Weekend	2.72 (1.59)	2.41 (1.54)**	3.11 (1.59)**

^aPhysical activity cut points are as follows: moderate (2296–4011 counts), moderate-to-vigorous (≥2296 counts), and vigorous (≥4012 counts).

^bTotal physical activity includes any activity >100 counts.

^cSedentary behavior includes any activity ≤100 counts.

^*p<.05

^**p<.01

^***p<.001

Table 3 presents the hierarchical regression results for primary outcomes. None of the unadjusted or fully adjusted models showed statistically significant associations between household chaos and child PA. In the adjusted models, child sex (male) and number of children in the household were significantly and positively associated with child MVPA, whereas only number of children in the household was associated with total PA.

Table 3.

Hierarchical Regression Analysis of Household Chaos and Child Health Behaviors

Variables	Model 1a		Model 2b		Model 3c
	β	95% CI	β	95% CI	β	95% CI
Physical activity (PA)
Moderate-to-vigorous PA
Household chaos	−.35	[−1.36, .66]	−.25	[−1.22, 0.71]	−.51	[−1.50, .49]
Child age	--	--	−2.83	[−6.13, 0.47]	−2.56	[−5.86, .75]
Child sex	--	--	−11.05**	[−18.04, −4.07]	−10.90**	[−17.72, −4.09]
Child BMI z-score	--	--	−2.72	[−6.34, .92]	−1.71	[−5.41, 1.98]
Economic assistance	--	--	−.38	[−7.99, 7.22]	−3.03	[−10.7, 4.65]
Number of children in household	--	--	--	--	4.31*	[.93, 7.07]
Parent weekly MVPA	--	--	--	--	−.66	[−1.85, .52]
Child PA self-efficacy	--	--	--	--	.48	[−.64, 1.61]
Child PA support	--	--	--	--	.72	[−.23, 1.68]
Model adjusted R2	−0.01		.09		.14
Model p-value	.49		.01		<.01
Total PA
Household chaos	.95	[−2.02, 4.11]	1.40	[−1.75, 4.55]	.47	[−2.69, 3.67]
Child age	--	--	−12.62	[−23.34, −1.91]	−11.51	[−22.07, −.96]
Child sex	--	--	−9.86	[−32.53, 12.81]	−9.42	[−31.18, 12.35]
Child BMI z-score	--	--	−5.33	[−17.15, 6.50]	−1.45	[−13.25, 10.35]
Economic assistance	--	--	−11.13	[−35.83, 13.57]	−20.98	[−45.48, 3.51]
Number of children in household	--	--	--	--	15.40**	[4.58, 26.21]
Parent weekly MVPA	--	--	--	--	−2.75	[−6.54, 1.04]
Child PA self-efficacy	--	--	--	--	1.91	[−1.69, 5.51]
Child PA support	--	--	--	--	2.75	[−.30, 5.81]
Model adjusted R2	−.01		.03		.11
Model p-value	.55		.18		.01
Sedentary behavior (SB)
Total SB
Household chaos	.45	[−3.8, 4.7]	.59	[−3.65, 4.84]	.88	[−3.67, 5.43]
Child age	--	--	4.18	[−10.26, 18.62]	4.07	[−10.50, 18.64]
Child sex	--	--	13.20	[−17.36, 43.75]	15.66	[−16.18, 47.51]
Child BMI z-score	--	--	4.45	[−11.49, 20.38]	4.43	[−11.66, 20.53]
Economic assistance	--	--	−29.08	[−62.36, 4.20]	−26.99	[−62.14, 8.15]
Number of children in household	--	--	--	--	−.15	[−15.68, 15.38]
Parent daily screen-time	--	--	--	--	−3.97	[−17.02, 9.09]
Model adjusted R2	−.01		−.0003		−0.02
Model p-value	.83		.43		.63
Screen-time
Weekday screen-time
Household chaos	.11**	[.03, .19]	.10*	[.02, .17]	.07	[−.01, .15]
Child age	--	--	.29*	[.04, .55]	.30*	[.05, .55]
Child sex	--	--	.24	[−3.1, .79]	.08	[−.48, .63]
Child BMI z-score	--	--	.29*	[.005,.58]	.30*	[.02, .58]
Economic assistance	--	--	.03	[−.56, .63]	−.18	[−.79, .43]
Number of children in household	--	--	--	--	.16	[−.11, .43]
Parent daily screen-time	--	--	--	--	.27*	[.05, .50]
Model adjusted r2	.06		.12		.15
Model p-value	<.01		<.01		<.01
Weekend screen-time
Household chaos	.13**	[.05, .22]	.13**	[.05, .21]	.09*	[.004, .17]
Child age	--	--	.25	[−.04, .52]	.25	[−.02, .52]
Child sex	--	--	−.02	[−.61, .57]	−.25	[−.83, .34]
Child BMI z-score	--	--	.27	[−.04, .58]	.28	[−.02, .58]
Economic assistance	--	--	−.36	[−.99, .29]	−.62	[−1.27, .02]
Number of children in household	--		--		.18	[−.11, .46]
Parent daily screen-time	--	--	--	--	.38**	[.14, .62]
Model adjusted R2	.08		.12		.19
Model p-value	<.01		<.01		<.001

^aModel 1 consists of only household chaos and the outcome variable of interest.

^bModel 2 includes household chaos, the outcome variable of interest, and any confounders identified from the literature.

^cModel 3 includes household chaos, the outcomes variable of interest, any confounders, and covariates identified from the literature.

^*p<.05

^**p<.01

^***p<.001

For all three models, the association between household chaos and child SB is not statistically significant. Despite the lack of statistical significance, it is worthy to note the β-coefficient for economic assistance in the adjusted models indicate potentially meaningful differences as families who receive economic assistance engage in approximately 30 minutes less SB when compared to families who do not.

Household chaos was significantly associated with child weekday screen-time across models 1 and 2, and weekend screen-time across all three models. Model 3 indicates that as household chaos increases by 1 unit, children engage in approximately 5 additional minutes of weekend screen-time. Associations between household chaos and weekend screen-time held even with the addition of significant variance accounted for by economic assistance and parent daily screen-time.

Discussion

Literature has shown that children thrive in structured environments⁸ and that their environment can impact their health.⁹ Therefore, it is plausible to consider that a lack of structure in the home resulting from household chaos may have detrimental effects on one’s ability to maintain healthy routines. The aim of the present study was to examine the relationship between household chaos with child PA, SB, and screen-time in rural families. It was hypothesized that the primary outcomes would be associated with household chaos, as families might face difficulties establishing routines conducive to regular PA and decreased SB and screen-time in a disorganized environment. Both weekday and weekend measures of child screen-time were significantly associated with household chaos in unadjusted models; however, this significant association did not hold in adjusted analyses for weekday screen-time, indicating that other factors not measured in our study may account for more of the variance in child screen-time during the week. Yet, household chaos was significantly associated with child weekend screen-time even in adjusted models. Lack of associations between child PA and SB with household chaos indicate that other personal or environmental factors are more likely to impact children’s PA and SB than a chaotic household. Findings have implications for future research to decrease children’s screen-time.

Our findings that for each one unit increase in household chaos, children participated in 5 additional minutes of weekend screen-time aligns with the findings from the one other study that examined this relationship.⁴ We can only speculate as to whether parents utilize electronic devices to entertain their children when households are chaotic, if children use screen-time as a strategy to escape chaotic environments, or both. Parents of chaotic homes may have increased difficulty setting limits and managing their child’s screen-time.⁴ Addressing excessive screen-time may require different intervention strategies compared to those used for decreasing other SB due to the use of an electronic device. For example, interventions could promote the use of screen-based electronic devices for active engagement such as learning a new dance or playing virtual sports. Additional exploratory research about characteristics of chaotic environments and their effect on child screen-time might be useful when developing interventions aimed at reducing screen-time and SB.

It is unclear why SB was not associated with household chaos. None of the variables in the models were significantly associated with SB. It may be that children spend similar time being sedentary regardless of household chaos. Otherwise, variables that may be associated with both SB and household chaos were not assessed in the present study and more exploration is warranted.

In our study, child PA was not associated with household chaos in any model. The number of children in the home, which was included as a covariate, was associated with child PA, indicating that this relationship may account for the lack of significance between child PA and household chaos, as a characteristic of household chaos is crowding. The idea that a greater number of children in a household results in more active children has been shown in previous research,⁴³ however the reasoning behind this idea has not been thoroughly studied. Perhaps homes with more children provide a greater opportunity to have someone with whom to participate in PA. Active children in the home may serve as role models to the other children who reside there, which could, in turn, influence their interest in being active.⁴⁴ Families with fewer children in the household might benefit from strategies implementing more time spent active as a family. Encouraging engagement in PA as a mode of “family time” could result in favorable outcomes. Additionally, parents with fewer children in the home might influence their child’s PA behaviors in a favorable way by planning opportunities to participate in PA with other children their age (eg, organizing “playdates”).

Strengths and Limitations

The current study has multiple strengths. These include the objectively measured child PA and SB data and the innovative examination of associations between household chaos with child PA, SB, and screen-time that extends our understanding of how household environments contribute to child health-behaviors in a less frequently explored population (rural communities).

The present study also had some limitations including that it is a cross-sectional design and therefore is unable to provide evidence of causality in the relationship between household chaos and child health behaviors. Additionally, many of the variables were participant-reported, which is subject to response bias. Household chaos could be underreported by parents if they were concerned about social desirability. Conversely, some families may find household chaos enjoyable or invigorating. Finally, generalizability of the study findings to other rural populations nationally is unknown.

Future Directions

Studies that examine which elements of a home with high household chaos lead to increased screen-time among residents may prove to be beneficial to design and administer effective strategies to reduce screen-time in a given population. Additionally, examining household chaos in relation to the development of childhood obesity through its effects on screen-time could further current knowledge of the risk factors that may be associated with a child’s environment. It is also important to note that the characteristics depicting a chaotic household may not always feel stressful to those residing there. For some individuals, the fast-paced and unpredictable nature of household chaos might be invigorating. For others, the normalcy of household chaos may lead to increased tolerance of chaos limiting the relationship between the disorganized environment routines. Future studies could better examine the perception of household chaos and whether residents react to disorderly situations uniformly. Additionally, adapting data collection measures to assess caregiving roles more accurately in the home to include other adults and children may improve methods of accounting for family structure and how it contributes to household chaos. Finally, the replication of the current study with a larger and more diverse study sample is necessary to improve generalizability and strengthen the reliability of the findings.

Conclusion

Household chaos is characterized by a lack of structure in the home and children’s health and development may benefit from a structured home environment that prioritizes routine. The present study corroborated previous findings of a positive association between household chaos and child screen-time, however more exploration is needed on the relationship between household chaos and other child health behaviors, including PA and SB, as the variables measured in our study did not significantly account for the variance in these outcomes.