The CDC recognizes childhood obesity as a persistent public health concern as it affects approximately 14 million children in the US.1 A 2019 study shows promising results that teaching healthy habits in early childhood may help prevent obesity.2 The current pilot study took place in Alabama, where a large percentage of children are overweight or obese, putting them at risk for chronic conditions such as hypertension, diabetes, and cardiovascular disease in adulthood.1,3 This problem is especially concerning given that decreased physical activity and increased sedentary behavior in adolescents are contributing to poor cardiovascular health that can continue into adulthood.4 Improving the health of children, adolescents, and adults requires reducing obesity rates throughout the lifespan, beginning in early childhood.5 Behaviors established at a young age, such as regularly sleeping the recommended hours, spending less time watching TV or using other electronic screen devices, and spending more time with family eating meals together, can make a difference in keeping children healthy. This pilot study aims to identify the prevalence and parent/caregiver perceptions of specific health habits in preschool children, as well as barriers to implementation of these habits. NPs can use this information to teach parents or caregivers the role these health habits can play in preventing or reducing childhood obesity.6,7
The American Academy of Sleep Medicine recommends 10 to 13 hours of sleep in 24 hours, including naps, for children ages 3 to 5 years.8 From a longitudinal study in 2014, researchers identified that a child's sleep behaviors formed early in life often persist as they grow older.9 In a similar study in Sweden, children age 10 years who slept less than the recommended amount were more likely to be overweight.7 Poor sleep quality and poor diet both commonly occur in families with low income; one study examined the relationship between dietary and sleep patterns in children ages 3 to 5 years from low-income families. They found that later timing of sleep patterns and greater differences between weekday and weekend sleep timing and sleep duration correlated with lower intake of vegetables and higher intake of processed and fried foods.10
Recognizing the literature currently available, it is important for NPs to understand that helping parents/caregivers cultivate a routine of recommended amounts of sleep per age of the child can institute habits that may help prevent overweight and obesity as children grow and mature into adolescents and adults.4,6,7,9-19
In today's electronic environment, children are exploring TV, electronic tablets, phones, and other gaming devices earlier than in years past.6 Duch and colleagues completed a systematic review of 29 studies regarding correlates of screen time in young children.6 Factors positively correlated with screen time included older child age and membership in a racial/ethnic minority group. There was no correlation between maternal employment, family's native language, or paternal education and screen time. Study results in the review were mixed on whether there was any association between household income and screen time.6 Brockmann and colleagues conducted a study on TV habits and sleep quality in children ages 1 to 6 years in Chile.12 They found that over half of the children in the study had TVs in their bedrooms, which was associated with a higher prevalence of nightmares, sleep terrors, sleep talking, and being tired upon awakening. Further, children who watched TV before bed had more abnormal scores on the Sleep Disturbance Scale for Children than those who watched TV earlier in the day.12 These results highlight the importance of limiting screen time, particularly for younger children, to avoid the detrimental consequences related to this behavior.6
Sometimes, even well-designed interventions for children and their caregivers have less than favorable results regarding TV-watching habits. Maddison and colleagues conducted a two-arm, parallel, randomized controlled intervention trial where researchers engaged in face-to-face training of a parent/caregiver and the child.11 The family was also provided a TV-monitoring device and activities to promote other ways to spend time as a family. Unfortunately, there were no significant changes in body mass index (BMI) z-scores over the 24-week study. There was a trend toward an increase in moderate-intensity physical activity for children in the intervention group; however, it was not significant.11
Although there is no standard definition qualifying participation in family meals, a systematic review in 2016 regarding family meals found that most of the included studies focused on the number of family meals per week, and ‘frequent’ family meals was often defined as at least three to five meals per week.13 Sharing family evening meals has been identified as a potential protective factor for childhood obesity.14-16 Anderson and Whitaker analyzed data from a longitudinal study including over 8,500 children age 4 years to evaluate the association between obesity and presence of the household routines of eating a meal as a family more than 5 nights per week, sleeping at least 10.5 hours per night, and limiting weekday screen time to no more than 2 hours daily.14 These researchers found that higher BMI in children was associated with lower frequency of all three routines.14 Among children exposed to adequate sleep, frequent family meals, and limited screen time, the prevalence of obesity was 14.3% compared with 24.5% for children exposed to none of the household routines. The presence of any one of the given routines lowered the odds of obesity between 23% and 25%.14 Magriplis and colleagues found that more frequent family meals were associated with significantly healthier dietary patterns such as lower amounts of potentially obesogenic foods (processed foods, sugared beverages, and fast food) and greater amounts of nonobesogenic foods (fruits, vegetables, and whole grains) in a large cross-sectional survey of school-aged Greek children.17 Healthy dietary patterns had an inverse association with total screen time and eating while using some type of screen device and a positive association with sleep.17
Overall, children who eat regular family meals and obtain proper amounts of sleep have consistently been shown to have a lower incidence of obesity.15,18,20 Caregiver demands and family composition may also have a large impact on child health habits related to obesity. Factors such as employment and marital status may affect the time and resources caregivers need to develop healthy habits for their children. In data from the National Survey of Children's Health, Singh and colleagues found that between 2003 and 2007 there was a 23% to 33% increase in obesity prevalence for children from higher caregiver unemployment, low-income, and low-education households compared with a 10% increase for all US children.19 Obesity prevalence also significantly increased over the 4 years for children from single-mother households.19 Marital and employment status may be indicators of socioeconomic status, as individuals with low socioeconomic status have recorded greater rates of child obesity and overweight, and employment and family composition are commonly used subdomains of measuring socioeconomic status.21,22
This pilot study sought to characterize the home habits that increase the risk of obesity in children from low-income homes in the southern US. Overweight and obesity is a common problem in low-income communities that is well documented in the literature. The aim of this study was to identify the prevalence and parent/caregiver perceptions of specific health habits (adequate sleep, limited screen time, and family meals) of preschool-age children. Further, this study sought to gain insight into structural barriers to implementing recommended healthy home habits. Gaining a better understanding of the interactions among current home practices of sleep habits, screen time, and family meals will enable NPs to intervene and educate patients about these habits in a way that is culturally competent.
Participants and procedures. Parents/caregivers of children who participated in this study lived in a lower-income area or one with health disparities and sent their children to a local preschool center. Parents/caregivers were recruited using a flyer displayed in the center. Those who were interested in participating in the study then obtained, completed, and returned a paper survey and informed consent contained in a confidential folder from the child-care center nurse. A researcher then collected the enclosed paper surveys. Participants had the option to enter their name into a drawing for a crockpot upon completion of the survey. All data were kept separate from any identifying factors of the caregivers, such as names of the child or caregiver. The university's institutional review board approval was received before the start of the study.
Measures. A self-report survey was adapted with permission from Haines and colleagues.16 Questions were related to children's sleep, screen time, and family meals. Demographic questions such as age, gender, race/ethnicity, relationship to child, income, marital status, and employment status were included.
Family composition and life demands. Marital and employment status were used as proxy variables for family composition and life demands. Marital status options were married, not married (but living with a partner), widowed, divorced, separated, and single (never married). Dichotomous groups were created combining married and not married (but living with a partner) in one group (partnered) and the remaining options in the other (unpartnered). Employment status included eight choices: employed full time (at least 35 hours per week), employed part time (fewer than 35 hours per week), employed (currently on maternal or medical leave), not employed (not looking for work), not employed (looking for work), student, disabled, and retired. Three group variables were created combining participants that identified as employed full time or employed part time. This group is referred to as the employed group. The second group consisted of both unemployed categories (looking for work/not looking for work) and those that indicated that they were on maternity or medical leave. This group is referred to as the unemployed group. The “other” group included participants that indicated being a student, disabled, or retired.
Sleep. Sleep was measured with open-ended response questions in which participants indicated the time their child goes to bed and the time the child wakes up on both weekdays and weekends. Participants reported their perceptions of their child's sleep using Likert-type response options. For example, participants were asked, if “Recommending 10 hours or more of sleep each day is realistic for my child” with responses ranging from 1 (strongly disagree) to 5 (strongly agree).
Family meals. Participants reported about family meals using one question, “During the past 7 days, how many times did your child sit down with other members of his or her family to eat a meal together?” Responses ranged from 1 (never) to 6 (5 or more).
Screen time. Screen time was measured using open-ended response questions asking the caregiver to report the number of hours and minutes the child spent watching TV, using a computer/laptop, and a handheld device (cell phone, iPad, tablet, video games) for both weekday (Monday through Friday) and weekend (Saturday and Sunday). Likert-type questions were also included asking caregivers to describe screen-time behaviors and measure caregiver perceptions of child screen time. An example item includes, “Recommending children watch TV 2 hours or less each day is realistic for my child.” Responses ranged from 1 (strongly disagree) to 5 (strongly agree).
Statistical analysis. In addition to descriptive statistics, a series of independent sample t tests were run to determine differences in sleep, screen time, and family meals for the marital groups. One-way analysis of variance (ANOVA) was used to determine differences in sleep, screen time, and family meals among employment groups. Fisher's Least Significant Difference post hoc test was used to test all significant ANOVA results. Only significant differences are reported.
Participants included 54 caregivers of children conveniently sampled from a child-care center in the southern Gulf Coast of Alabama. A total of 64 responses were collected, but 10 cases were excluded due to large sections of missing data and evidence of inattentive responding (N = 54). The sample was mostly female (92%) with a mean age of 30.68 years (SD = 9.61). Participants predominantly identified as Black (72.2%), followed by Asian (13.0%), and White (11.1%). The children had a mean age of 2.47 years (SD = 1.32), and 61.1% were male. Caregivers identified their child's race as Black (68.5%), Asian (9.3%), White (9.3%), Hispanic (3.7%), and other (5.6 %) or multiple races or ethnicities (3.7%) (See Demographic data). Descriptive statistics and measures of central tendency were analyzed. More than half (53.7%) of the participants reported that they were single (never married). Participants varied in education levels, but 50% indicated high school diploma/GED as the highest level of education obtained, followed by 20.4% with some college/vocational school, and 20.4% graduated college/completed vocational school. Annual household income varied from $10,800 to $95,000 with a mean of $29,186 (SD = $21,019.99). The mean, however, may be skewed by two cases that have been identified as outliers because of z scores greater than 3. Both cases include an income of $95,000. When excluding these two cases, the mean income was $24,311.11 (SD = $10,860.84). However, these estimates only include 29 and 27 participants, respectively, due to either missing data or the inability to distinguish if the income reported reflected annual, monthly, or weekly income.
Sleep. The average amount of sleep parents/caregivers reported their child getting each night was approximately 10.32 hours (SD = 2.31). There were no significant differences between marital groups (P = .84). Next, an ANOVA was then used to determine that there were significant differences in child sleep between the three employment status groups (F (2,43) = 5.74, P = .006). The employed group (mean = 10.46, SD = 3.17, P = .002) and the “other” group (mean = 10.00, SD = 1.41, P = .03) indicated their children obtained significantly more hours of sleep compared with the unemployed group (mean = 7.30, SD = 1.75). The recommendation of 10 or more hours of sleep per night was realistic for 64.8% of participants. An additional one-sample t-test and ANOVA were run and found significant differences based on caregiver marital status, with individuals who were partnered mostly agreeing or strongly agreeing with the statement (mean = 4.46, SD = .66) compared with the unpartnered group [(mean = 3.55, SD = 1.16); t (52) = 3.28, P = .002]. There were no significant differences in employment status (P = .71) related to this recommendation.
Sleep and screen time. More than half of the sample (69%) indicated that their children sometimes watched TV or used a handheld device before bed, whereas other participants said that their children often (27.3%) or always (34.7%) watched TV or used a handheld device before bed. When asked how often their children fell asleep watching TV at bedtime, 27.8% indicated “sometimes” and 14.8% indicated “often or always.” Fewer participants indicated that their children fell asleep using a handheld device at bedtime: 13% “sometimes” and 9.3% “often or always.”
Family meals. A little over a third of the sample (37%) indicated they ate family meals together three to four times per week (mean = 3.96, SD = 1.55). Twenty-seven percent of parents/caregivers reported eating meals together five or more times per week. Many participants (42.6%) indicated that their children never ate breakfast or dinner with the TV turned on and that their child did not use a computer/laptop or handheld device when eating breakfast (74.1%) or dinner (64.2%). There were no significant differences in family meal participation between partnered and unpartnered groups or employment status groups.
The current study sought to investigate the prevalence of sleep, screen time, and family meals as well as caregiver perceptions and barriers to developing these habits. Fortunately, family meals were highly prevalent among the sample, and the sample's mean sleep duration was above the recommended benchmark. Findings indicate that employment status may be an important caregiver factor to consider when crafting interventions to increase sleep among preschool-age children. The present findings add to the literature regarding unemployment as a potential exacerbating factor for reduced sleep duration among children.
Indeed, Garmy and colleagues found that sleep was strongly related to increased risk of overweight and obesity.7 However, parental life demands were not measured or considered in this relationship. Therefore, it is important to consider parental resources when studying health habits related to obesity. This can also inform future policy and interventions aimed at reducing childhood obesity through healthy habits. If parents do not have the resources to ensure their child obtains the recommended sleep or family meals, then interventions may not be as effective. Thus, future interventions and policies should aim to provide the parent with resources and adapt to their individual fiscal and/or time demands.
The present study adds to the mixed literature regarding family meals and health habits among children. The prevalence of family meals was high in this sample, and additionally, a large portion did not use screens while participating in family meals. These findings are congruent with the previous work of Haines and colleagues that found that family meals were high among their sample and that even though their intervention had an effect on child BMI, it did not have an effect on family meals.16 These findings indicate that interventions may be more effective by focusing on other health habits related to obesity, such as sleep. Interestingly, the moderate number of children who spent time either watching TV or using a handheld device before sleep seemed to be unrelated to sleep duration. This contradicts research from Garmy and colleagues that found that screen time was associated with less sleep.7 Measures of sleep quality may better capture the influence of screen time and sleep among children.
Limitations and future research
The current study has several limitations. First, and most important, cumulative screen viewing times were obtained, but excluded in analyses due to a large amount of unreliable viewing times reported. A convenience sample was used; thus, the sample may not be generalizable to the general population of parents/caregivers of preschool-age children. Further, the present study attempted to create modifications to the survey developed by Haines and colleagues.16 However, due to the difficulty of collecting pencil and paper data and the anonymous submission of surveys, many of the responses in the survey were not complete. For instance, 10 participants were excluded after leaving all or much of the survey blank. Additionally, many open-ended questions seemed to be misinterpreted or read incorrectly. For instance, among screen-time measures the authors attempted to improve previous studies by asking the participant to document the average hours of screen time the child participates in with TVs, computers, and handheld devices. However, there were frequent high outliers of parents indicating their children used 8, 10, 11, and even 24.5 hours of handheld devices, TV, and computer time on average per day.
Because this was a pilot study, the research team would like to replicate this study with a larger, more diverse population of parents/caregivers and their children. The researchers also plan to implement body composition measures such as BMI in a manner that does not involve self-report, so that the height, weight, and possibly waist circumference could add more precise information related to the risk of obesity in this population. In addition, a future research study could be developed to collect these data in a clinical setting, working closely with NPs while tracking the influence of a culturally competent NP-led intervention for caregivers that encourages recommended sleep habits, limited screen time, and healthy family meals for particular age groups.
NPs have a unique opportunity to emphasize the importance of health habits directly through parent/caregiver communication. Considering the results of the present study would be beneficial before discussing child obesity or increasing healthy habits within the home. First, NPs must consider that parents/caregivers may not be able to prioritize their children's sleep, so tailoring interventions to individual circumstances may increase caregiver participation and awareness of healthy home habits. In addition, it is possible that situational circumstances or external factors also limit caregivers' ability to increase frequency of family meals or limit screen time. It is up to the NP to recognize these possible barriers and provide realistic suggestions for families to implement these habits. For instance, an NP may introduce caregivers to a mobile health (mHealth) application to increase children's health habits.23,24 Consequently, if caregivers feel it would be relatively easy to use an mHealth app to increase child health behaviors, the NP could encourage this as a regular activity. (See NP resources for family discussions on healthy habits.)
The current pilot study used descriptive methodology to identify the prevalence and perceptions of healthy habits (regular sleep of at least 10 hours per night, regular family meals at least three to five times per week, and limited screen time per day) in preschool children whose parent/caregiver lived in a lower-income area or one with health disparities. Many of the children in this study were getting the recommended amount of sleep per night for their age. Over one-third of parents/caregivers in this study had family meals at least three to four times per week with approximately 25% of participants having family meals five or more times per week. A large percentage of preschool children in this pilot study watched TV or used a handheld device when going to bed, so this area could be improved.
These healthy habits are a part of a good routine for preschoolers that may prevent overweight and obesity in the future. Aiding parents/caregivers to recognize the importance of these routines implemented at a young age may begin a healthy trajectory to help children grow into healthier adults.
1. Centers for Disease Control and Prevention. Childhood overweight and obesity. 2018. www.cdc.gov/obesity/childhood/index.html
2. Fisher MC, Villegas E, Sutter C, Musaad SM, Koester B, Fiese BH. Sprouts growing healthy habits: curriculum development and pilot study. Front Public Health
3. Millner V, McDermott RC, Eichold BH. Alabama children
's body mass index, nutritional attitudes, and food consumption: an exploratory analysis. South Med J
4. Lenhart CM, Wiemken A, Hanlon A, Perkett M, Patterson F. Perceived neighborhood safety related to physical activity but not recreational screen-based sedentary behavior in adolescents. BMC Public Health
5. Walker E, Wolfe BM. Obesity prevention. In: Nguyen N, Brethauer S, Morton JM, Ponce J, Rosentahal RJ, eds. The ASMBS Textbook of Bariatric Surgery
. Cham, Switzerland: Springer International Publishing; 2020.
6. Duch H, Fisher EM, Ensari I, Harrington A. Screen time use in children
under 3 years old: a systematic review of correlates. Int J Behav Nutr Phys Act
7. Garmy P, Clausson EK, Nyberg P, Jakobsson U. Insufficient sleep
is associated with obesity and excessive screen time amongst ten-year-old children
in Sweden. J Pediatr Nurs
8. Paruthi S, Brooks LJ, D'Ambrosio C, et al. Recommended amount of sleep
for pediatric populations: a consensus statement of the American Academy of Sleep
Medicine. J Clin Sleep Med
9. Koulouglioti C, Cole R, Moskow M, McQuillan B, Carno M-A, Grape A. The longitudinal association of young children
's everyday routines to sleep
duration. J Pediatr Health Care
10. Jansen EC, Peterson KE, Lumeng JC, et al. Associations between sleep
and dietary patterns among low-income children
. J Acad Nutr Diet
11. Maddison R, Marsh S, Foley L, et al. Screen-time weight-loss intervention targeting Children
at home (SWITCH): a randomized controlled trial. Int J Behav Nutr Phys Act
12. Brockmann PE, Diaz B, Damiani F, Villarroel L, Nuñez F, Bruni O. Impact of television on the quality of sleep
in preschool children
. Sleep Med
13. McCullough MB, Robson SM, Stark LJ. A review of the structural characteristics of family meals
in the United States. Adv Nutr
14. Anderson SE, Whitaker RC. Household routines and obesity in US preschool
15. Hammons AJ, Fiese BH. Is frequency of shared family meals
related to the nutritional health of children
and adolescents. Pediatrics
16. Haines J, McDonald J, O'Brien A, et al. Healthy habits, happy homes: randomized trial to improve household routines for obesity prevention among preschool
. JAMA Pediatr
17. Magriplis E, Farajian P, Panagiotakos DB, Risvas G, Zampelas A. The relationship between behavioral factors, weight status and a dietary pattern in primary school aged children
: the GRECO study. Clin Nutr
18. Ford MC, Gordon NP, Howell A, et al. Obesity severity, dietary behaviors, and lifestyle risks vary by race/ethnicity and age in a Northern California cohort of children
with obesity. J Obes
19. Singh GK, Siahpush M, Kogan MD. Rising social inequalities in US childhood obesity, 2003-2007. Ann Epidemiol
20. Fruh S, Fulkerson JA, Mulekar MS, Kendrick LJ, Clanton C. The surprising benefits of the family
meal. J Nurse Pract
21. Kininmonth AR, Smith AD, Llewellyn CH, Fildes A. Socioeconomic status and changes in appetite from toddlerhood to early childhood. Appetite
22. Wang Y, Lim H. The global childhood obesity epidemic and the association between socio-economic status and childhood obesity. Int Rev Psychiatry
23. Downing KL, Salmon J, Hinkley T, Hnatiuk JA, Hesketh KD. Feasibility and efficacy of a parent-focused, text message-delivered intervention to reduce sedentary behavior in 2- to 4-year-old children
(mini movers): pilot randomized controlled trial. JMIR Mhealth Uhealth
24. Wearing JR, Nollen N, Befort C, Davis AM, Agemy CK. iPhone app adherence to expert-recommended guidelines for pediatric obesity prevention. Child Obes