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. Author manuscript; available in PMC: 2023 Oct 4.
Published in final edited form as: Appetite. 2021 Jun 16;166:105465. doi: 10.1016/j.appet.2021.105465

Associations between advertisement-supported media exposure and dietary quality among preschool-age children

Jennifer E Carroll a,d, George Price a, Meghan R Longacre b,c, Kristy M Hendricks b, Gail Langeloh a, Paul Beach a, Madeline A Dalton a,c, Jennifer A Emond a,c,*
PMCID: PMC10549928  NIHMSID: NIHMS1932412  PMID: 34146648

Abstract

Foods of low nutritional quality are heavily marketed to children, and exposure to food ads shapes children’s preferences and intake towards advertised foods. Whether food ad exposure independently relates to an overall lower diet quality among children remains unclear. We examined the association between ad-supported media use, a proxy for food ad exposure, and diet quality using the baseline data (2014–2015) from 535 3–5-year-olds in a community-based cohort study. Parents reported their child’s dietary intake over 3 days via a diary, and diet quality was assessed with the Healthy Eating Index (HEI-2015) where higher scores reflect greater adherence to USDA dietary guidelines. Children’s media exposure was measured through online parent surveys. Mean HEI score was 54.5 (SD = 9.4). In models adjusted for sociodemographic characteristics and metrics of parent diet quality, children’s HEI scores were 0.5 points lower (adjusted beta = −0.5 [95% CI: 0.8, −0.1]; P < 0.01) for each 1-h increment in weekly viewing of ad-supported children’s TV networks. Children’s use of media that may have food ads (e.g., apps, online games) also related to a lower diet quality yet to a lesser extent (adjusted beta −0.2 [−0.2, −0.1]; P < 0.01). In contrast, children’s ad-free media use was not associated with diet quality (P = 0.21). Findings support the premise that exposure to food advertisements via media may result in a lower quality diet among children independently of other risk factors.

Keywords: Food advertisements, Preschoolers, Healthy eating index, Media exposure

1. Introduction

Early childhood is a critical time to shape healthy eating habits among children. Young children’s dietary patterns, food preferences and palates are formed in early childhood and habits often continue through adolescence and adulthood (Beckerman et al., 2017; Birch, 1998; Ventura & Worobey, 2013). Young children in the US, on average, have diets of low nutritional quality. Children aged 3–5 years exceed the recommended intakes of sodium, saturated fat, and sugar, while also consuming too few non-starchy vegetables, fruit, and whole grains (Banfield et al., 2016; Hamner & Moore, 2019; Wang et al., 2018; Welker et al., 2018). Nationally representative data from the National Health and Nutrition Examination Survey (NHANES) document that young children’s diet quality declines with age and that decline may begin as early as one year of age (Banfield et al., 2016; Hamner & Moore, 2019; Thomson et al., 2019).

Poor diet quality may be a modifiable risk factor associated with various health conditions in young children, such as increased risk for high cholesterol, triglycerides, and blood pressure, along with impaired glucose tolerance and type II diabetes (Vos et al., 2017). Furthermore, poor quality diets during early childhood has been associated with poor health conditions that affect adolescents such as high blood pressure (Marrodan et al., 2013), early puberty (a risk factor for cancer, mortality, metabolic syndrome) (Cheng et al., 2010). Poor eating habits developed during childhood may continue into adulthood, potentially leading to various cardiometabolic diseases (i.e., heart disease, diabetes, metabolic syndrome, cancer) and other risk factors for diseases (i.e., obesity, social-psychological conditions) as adults (, 2020CDC; Vos et al., 2017). Thus, identifying modifiable risk factors for declining dietary quality among children is paramount to help establish a foundation of dietary habits which support lifelong health and quality of life.

Child-directed food marketing is a likely and prevalent modifiable risk factor for unhealthy eating habits. Foods of low nutritional quality, those that are largely of low-nutritional value and contribute to excess calories to the diet, are heavily marketed and readily available to young children (Boyland & Whalen, 2015; Calvert, 2008; Harris et al., 2017, p. 214). TV remains one of the primary mediums of children’s exposure to foods advertisements, along with newer media exposure that has not been thoroughly investigated. During the time of the present study, research documented that young children between ages 2–4 years viewed an average of 2 h and 39 min of screen media per day, with TV exposure accounting for an average of 1 h and 9 min (Rideout, 2017). Children aged 5–8 years viewed an average of almost 3 h per day of total screen media, with TV exposure accounting for 1 h and 4 min per day on average (Rideout, 2017).

Findings across multiple studies support that exposure to food advertisements shapes young children’s preferences for (Needlman, 2009) and intake of (Emond et al., 2019a,b) advertised foods, including preschool-age children. Research further supports that the effect of food advertisement exposure generalizes to other non-advertised, energy-dense and highly palatable foods (Boyland et al., 2016), such as if a child watches an advertisement with potato chips, they may crave and eat a salty, crunchy snack (Boyland et al., 2013). However, whether children’s food-advertisement exposure via media specifically relates to a lower dietary quality overall remains uncertain (Falbe et al., 2014; Huffman et al., 2012; Miller et al., 2008; Sisson et al., 2012). For example, many past studies examining children’s media use and their dietary intake did not account for children’s exposure to advertisement-supported versus advertisement-free media use, making it difficult to discern between the effects of sedentary behavior versus exposure to advertising. Additionally, many studies examined the intake of specific food groups but not children’s overall dietary quality (Shqair et al., 2019).

The objective of this study is to examine the association between exposure to advertisement-supported media and overall dietary quality in preschoolers by using a recommended global index for diet quality (i.e., the Heathy Eating Index 2015 version) based on a detailed inventory of children’s dietary intake that was customized to capture the intake of child-specific foods. This study includes multiple media types, such as traditional TV and online platforms, and controls for multiple key confounders, including proxies of parent diet quality.

2. Methods

This analysis utilized baseline data from a community-based cohort study of preschool-age children and their parent or caregiver (“parent” herein), designed to examine the influence of food marketing exposure on children’s dietary intake (Emond, 2019a; 2019b). Participants were recruited March 2014–October 2015 from community sites (e.g., pediatric clinics, childcare centers) in two New Hampshire, U.S. cities; Facebook and participant referrals were also used. Children were 3–5 years old with no health condition impacting food intake and who lived with the parent at least three days a week or alternate weeks. Parents were required to be literate in English and reside within 1 h’s drive of the recruitment site with no plans to relocate within one year. If parents had multiple age-eligible children, the child at the recruitment site was selected; if two or more age-eligible children were present, one was randomly selected. Among the 667 parent-child dyads screened and eligible for the study, 624 (93.6%) enrolled. Shortly after enrollment (i.e., at baseline), parents completed a survey, parents and children completed a clinic visit where the child’s height and weight were measured, and each parent completed a written 3-day food diary for their child. The survey was pre-tested with a demographically comparable sample for comprehension, face validity and completion time. Signed informed written consent was obtained from all parents. Parents received $50 in gift cards if they completed all baseline study components and children received a toy. The Dartmouth College Committee for the Protection of Human Subjects approved the study.

2.1. Children’s dietary quality

Parents recorded in detail all food, beverages and vitamin supplements consumed by their child over a period of 3 days (2 weekdays and 1 weekend day). Trained research assistants instructed parents how to complete the diaries using a standardized protocol. The following was also given to each parent: written instructions on how to keep a detailed food diary, a sample entry, a booklet in which to record the child’s intake; a food portion kit (3D portion size models, measuring cups, ruler, 8-ounce water bottle) to estimate portion sizes; a daycare provider form with instructions to record a child’s intake while at daycare; a recipe form to record the contents of homemade/customized items; and a postage-paid envelope to return the completed diary to the study team. All completed food diaries were reviewed by a trained nutritionist supervised by a registered dietitian, and parents were contacted to clarify questions about confusing or potentially missing entries (e.g., missing meals.)

All foods, beverages, and supplements consumed were entered into the Nutrition Data System for Research (NDSR) version 2014, a dietary assessment program developed by the Nutrition Coordinating Center (NCC) at the University of Minnesota (Schakel et al., 1988; Schakel et al., 1997; Sievert et al., 1989). The NDSR database included >18,000 foods including 8,000 brand name and restaurant items. The USDA Nutrient Data Laboratory is the primary source of nutrient values and nutrient composition for the NDSR. Values are supplemented by food manufacturers’ information and data available in the scientific literature (Schakel et al., 1988). For any food or beverage not in the NDSR database, the NCC was contacted to determine if the item’s nutritional content was available or the nutrient information for a nutritionally equivalent product in the NDSR was appropriate for use. We further created an entry based on the manufacturer’s nutritional information for packaged foods specific to young children (e.g., squeezable fruit pouches, yogurt tubes) that were not in the NDSR (n = 830). Such packaged foods accounted for 19% of all unique food and beverage items in the final dietary database for this study. Quality checks were completed including comparing compiled nutrient data to the food diaries for a: 1) 5% subsample of children, 2) 15% subsample of all unique days of data (i.e., 15% of all days across all children), and 3) 5% of the food diaries were randomly selected and double entered by an experienced NDSR analyst at an external site (Tufts University School of Medicine, Boston, MA) for verification. All quality checks confirmed data were entered accurately. Compiled nutrient data were then reviewed by trained nutritionists, and improbable entries (e.g., daily caloric intakes below estimated basal metabolic rate) were reviewed in-depth and excluded if deemed invalid.

The Healthy Eating Index (HEI), 2015 version (Center for Nutrition Policy and Promotion, 2018), was used to quantify dietary quality. HEI scores range from 0 to 100, and higher scores indicate greater adherence to the USDA’s Dietary Guidelines for Americans (U.S. Department of Agriculture, 2015). HEI scores are a valid and standard method to assess dietary quality among children as young as 2 years (Guenther et al., 2013). The HEI 2015 version includes 13 dietary components: 9 adequacy components to encourage (total fruit, whole fruit, total vegetables, greens and beans, whole grains, dairy, total protein foods, seafood and plant proteins, fatty acids) and 4 components to consume in moderation (refined grains, sodium, added sugars and saturated fats). Each component is scored relative to the USDA dietary recommendations. Scores are standardized to 1,000 calories such that HEI scores are applicable across groups with different caloric needs. In the present study, each child’s dietary intake was first computed using each day of the food diary, then averaged over all days to compute average daily intake; weekdays were weighted to account for 5/7, and weekends 2/7, of the final daily average. HEI scores were computed using the average daily intake. Overall, 536 children had completed food diaries; however, one diary was excluded due to missing data on media use. Of the remaining 535 participants, 531 (99.25%) participants had three days of daily diary information, 3 (0.56%) participants had two days of daily diary information, and 1 (0.18%) participant had one day of daily diary information. In total, 514 (96.07%) participants had at least one weekday and one weekend entry, 19 (3.55%) participants had only weekday entries, and 2 (0.37%) participants had only weekend entries.

2.2. Children’s exposure to advertisement-supported media

Parents reported how many days a week, on average, their child engaged in six screen media activities: 1) watching TV, 2) watching DVDs or VHS, 3) watching programs on the internet or through streaming, 4) using apps on a smartphone, iPod, iPad or tablet, 5) using the internet or 6) playing games on a gaming station or computer. Parents then reported the time their child spent on each screen activity on days when using each type. Values were multiplied to compute the average hours per week children engaged in each screen media activity. Separately, parents selected which of 12 national children’s TV networks their child usually watched. Six networks were advertisement-supported: Boomerang, Cartoon Network, Disney XD, the Hub (aka, Discovery Kids), Nickelodeon, and Nicktoons. In 2015, Nickelodeon, Cartoon Network, and Disney XD were the three networks with the most advertisements viewed by children in the US during children’s programming (Harris & Kalnova, 2018). Importantly, previous analyses from this current study confirm that advertisements for the foods most frequently advertised to children (Harris et al., 2017, p. 214), sugary cereal and fast food (Emond, 2019a; 2019b), were common on those six networks during the study timeframe. Thus, in this analysis, we use exposure to advertisement-supported media as a strong proxy for exposure to food marketing based on this rationale. The remaining five children’s TV networks were advertisement-free: The Disney Channel, Disney Jr., Nick Jr., PBS Kids, and Sprout. Thirty-two parents also wrote in an “other” option which were reviewed, verified, and classified as advertisement-supported or advertisement-free network by the study team.

Children’s media use was classified as advertisement-supported, advertisement-free, and mixed advertisement-supported. Exposure to advertisement-supported media was quantified by multiplying the total number of weekly TV viewing hours by the proportion of children’s TV networks usually viewed that were advertisement-supported. Exposure to advertisement-free media was calculated by multiplying the total number of weekly TV viewing hours by the proportion of children’s TV networks usually viewed that were advertisement-free, plus weekly hours of DVD and VHS viewing. For example, a child with 15 h of TV viewing per week and who watched three children’s TV networks, two advertisement-supported and one advertisement-free, would have 10 h of advertisement-supported TV viewing and 5 h of advertisement-free TV viewing per week. Exposure to mixed advertisement-supported media included weekly viewing hours of the other four media categories: i) watching programs on the Internet or through streaming, ii) using apps, iii) using the Internet, or iv) playing games on a gaming station or computer. Importantly, these media categories that may or may not include food advertisements, however, many child-directed websites (Harris et al., 2017, p. 214), child-directed online-games (Emond et al., 2020; Harris et al., 2017, p. 214), and child-directed apps (Meyer et al., 2019) contain food advertisements.

2.3. Covariates

Parents reported on sociodemographic characteristics of their child, themselves, and the household. We also included parent-report of the child’s usual fast food intake (combined for analyses as less than once a month, at least monthly to less than once a week, at least weekly for analyses) to describe the association between that measure and diet quality. Children’s usual fast food intake was examined as a descriptive variable but was not included in the multivariable models because fast food intake likely lies along the causal pathway between advertisement exposure and dietary quality. Children’s weight status was based on height and weight measurements completed in the clinic using a standardized protocol. Age- and sex-adjusted BMI percentiles were computed using US Centers for Disease Control and Prevention formulas (Kuczmarski et al., 2002), with overweight defined as an age- and sex-adjusted BMI ≥ 85th and <95th percentile and obesity was defined as an age- and sex-adjusted BMI ≥ 95th percentile. Healthy weight was defined as an age- and sex-adjusted BMI <85th percentile. We also included the following lifestyle factors that may be associated with children’s diet quality: children’s usual hours of outside play (hours per week), usual hours of nighttime sleep time (hours per night calculated based on the child’s usual bedtime and wake time), a TV in the child’s bedroom (yes, no), frequency of eating dinner together as family (≤2, 3–4, 5–6, 7 nights a week), and measures of parent diet quality.

Detailed dietary intake assessments were not completed for parents. Instead, we used three measures to approximate parent diet quality: fruit and vegetable intake, soda intake, and fast food intake. For fruit and vegetable intake, parents reported their usual frequency of consuming fruit (fresh, frozen or canned) and vegetables (fresh, frozen, canned or salad); the responses for each were ordinal and were collapsed into one combined measure of less than 2–3 servings of each per day, less than 2–3 servings of one but at least 2–3 servings for the other, or at least 2–3 servings per day of both. Those thresholds roughly approximate the USDA dietary guidelines of 2, 1-cup servings of fruit and 2 ½, 1-cup servings of vegetables per day for a diet of 2000 calories (U.S. Department of Agriculture and U.S. Department of Health and Human Services, 2010). For analyses, parents’ usual frequency of soda intake was categorized as 0, 1–2 or 2 or more days a week and usual fast food intake was categorized as less than once a month, at least monthly to less than once a week, or at least weekly.

2.4. Statistical analyses

HEI scores were summarized overall and by sociodemographic factors and potential covariates; bivariable comparisons were completed with two-sample t-tests, one-way ANOVA or Pearson’s correlation coefficients as appropriate. Scatterplots were assessed to confirm a linear dose-response relationship between HEI scores and children’s use of advertisement-supported, advertisement-free, and mixed advertisement-supported media. Adjusted linear regression was used to fit HEI scores on each of the three measures of children’s media use. Main effects at the P < 0.05 level in adjusted analyses were considered statistically significant. Model covariates included measures associated with HEI scores at the P < 0.10 level from bivariate analyses; again, children’s usual fast food intake was not included as a covariate because it may partially mediate the association between exposure to advertisement-supported TV and dietary quality. Analyses were completed with the R Language for Statistical Computing (version 4.0.2).

3. Results

Complete food diaries were obtained for 535 children, which represented 85.7% of the children enrolled. When comparing those included in the analysis (n = 535) to those not included (n = 89), there was no statistically significant difference for age (P = 0.06), sex (P = 0.53), advertisement-supported media exposure (P = 0.07), advertisement-free media exposure (P = 0.37) or mixed advertisement-supported media exposure (P = 0.14). However, compared to the analytic sample, the sample not included was more likely to include children who were non-White, Hispanic (P = 0.04) and parents of lower education (P < 0.01) with lower annual household incomes (P < 0.01).

The analytic sample (Table 1) included mostly three year-olds (41.1%), an equal proportion of boys and girls, and children were mostly white, non-Hispanic (86.5%). HEI scores averaged 54.5 (SD: 9.4) and scores decreased with age (P = 0.03). HEI scores were positively associated with parental education (P < 0.001), household income (P = 0.07), and with parents residing with a spouse or partner (P = 0.04). HEI scores did not differ by children’s weight status (P = 0.62). Children’s HEI scores were associated with several lifestyle factors and measures of parent diet quality (Table 2). Lower HEI scores were associated with a TV in the child’s bedroom (P < 0.01), a more frequent intake of fast food (P < 0.001), and a lower frequency of eating dinner together as a family each week (P = 0.04). Children’s HEI scores were positively correlated with each metric of parental diet quality. Specifically, HEI scores were greater when parents themselves more often consumed fruits and vegetables (P < 0.01) and less often consumed soda (P = 0.02) or fast food (P < 0.01).

Table 1.

Sociodemographic characteristics and associations with children’s diet quality.
Children’s HEI scores
n (%) Mean (SD) P-valuea
Overall 535 (100%) 54.5 (9.4) -
Child characteristics
Age
 3 years 220 (41.1%) 55.6 (9.1) 0.03
 4 years 204 (38.1%) 54.2 (9.6)
 5 years 111 (20.7%) 52.7 (9.3)
Sex
 Girl 299 (55.9) 54.68 (8.9) 0.54
 Boy 236 (44.1) 54.18 (10.0)
Race/ethnicity
 Non-Hispanic White 463 (86.5%) 54.5 (9.4) 0.93
 Other 72 (13.5%) 54.6 (9.1)
Childcare outside of the home
 None 103 (19.3%) 54.8 (8.7) 0.62
 1–20 h per week 185 (34.6%) 54.9 (9.79)
 21+ hours per week 247 (46.2%) 54.0 (9.36)
Receives WIC benefits
 Yes 63 (11.8%) 53.7 (8.9) 0.49
 No 472 (88.2%) 54.6 (9.5)
Weight status
 Healthy weight 390 (72.9%) 54.7 (9.4) 0.62
 With overweight 92 (17.2%) 53.9 (9.6)
 With obesity 53 (9.9%) 53.7 (9.1)
Parent and household characteristics
Age
 20–29 years 99 (18.5%) 53.2 (9.2) 0.30
 30–39 years 351 (65.7%) 54.8 (9.7)
 40 years and older 84 (15.7%) 54.8 (8.3)
Education
 Up to an Associate’s or technical degree 209 (39.0%) 52.6 (8.6) <0.001
 Bachelor’s degree or higher 326 (61.0%) 55.6 (9.7)
Annual household income
 <$75,000 221 (41.2%) 53.4 (8.7) 0.07
 ≥$75,000 314 (58.8%) 55.1 (9.8)
Parent co-habitation status
 Lives with spouse or partner 464 (87.1%) 54.7 (9.4) 0.04
 Does not lives with spouse or 71 (12.9%) 52.2 (9.1)
partner Number of children in the home
 1 118 (22.1) 54.7 (9.1) 0.57
 2 287 (53.6) 54.8 (10.0)
 3 90 (16.8) 54.0 (8.3)
 4 or more 40 (7.5) 52.7 (8.1)
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Among 535 children and one parent enrolled in a cohort study who completed a multiple day food diary assessment. WIC: Women, Infants and Children.

a

P-values are from one-way ANOVAs or two-sample t-tests.

Table 2.

Child health behaviors, family eating habits and indicators of parent diet quality and associations with children’s diet quality.
Children’s HEI scores
n (%) Mean (SD) P-valuea
Child health behaviors
Hours of outside play
 <14 h per week 204 (38.1%) 54.6 (8.9) 0.53
 14–21 h per week 138 (25.8%) 55.0 (9.9)
 >21 h per week 193 (36.1%) 53.9 (9.5)
Nighttime sleep
 <10 h per night 44 (8.2%) 56.1 (10.4) 0.22
 ≥10 h per night 491 (91.8%) 54.3 (9.3)
TV in the bedroom
 Yes 95 (18.1%) 52.0 (9.7) <0.01
 No 431 (88.9%) 54.9 (9.2)
Usual fast food intake
 Less than once a month 189 (35.3%) 57.5 (9.4) <0.001
 At least monthly to less than once a week 200 (37.4%) 53.3 (9.0)
 At least weekly 146 (27.2%) 52.2 (8.9)
Family eating habits
Eat dinner together as a family, days per week
 2 or less 35 (6.5%) 52.2 (8.3) 0.04
 3 or 4 90 (16.9%) 52.8 (9.5)
 5 or 6 156 (29.2%) 54.2 (9.7)
 7 253 (47.4%) 55.5 (9.2)
Indicators of parent diet quality
 Daily vegetable and fruit intakeb
 Below guidelines for both 196 (36.8%) 52.8 (9.1) <0.01
 Below guidelines for one 135 (25.3%) 54.2 (8.9)
 Meets guidelines for both 202 (37.9%) 56.2 (9.7)
Frequency of soda intake
 0 days a week 394 (74.5%) 55.1 (9.5) 0.02
 1–2 days a week 71 (13.4%) 53.6 (9.3)
 3 or more days a week 64 (12.1%) 51.7 (8.6)
Frequency of fast food intake
 Less than once a month 169 (31.6%) 56.3 (9.5) <0.01
 At least monthly yet less than once a week 161 (30.1%) 54.4 (9.1)
 At least weekly 205 (38.3%) 52.9 (9.3)
Open in a new tab

Among 535 children and one parent enrolled in a cohort study who completed a multiple day food diary assessment. R = Pearson’s correlation coefficients. Scatterplots confirmed associations were linear in each instance.

a

P-values are from Pearson’ s correlation coefficients or one-way ANOVA.

b

A d-supported TV included viewing of any of the six predefined ad-supported children’s TV networks (Boomerang, Cartoon Network, Disney XD, the HUB, Nickelodeon, or Nicktoons). Ad-free TV included viewing of any of the five predefined ad-free children’s TV networks (Disney Channel, Disney Jr., Nick Jr., PBS Kids or Sprout) and was combined with DVD or VHS viewing. Mixed ad- exposure included mobile applications, Internet and video or computer games.

Children averaged 17.7 (SD: 14.1) total hours of screen media per week (Table 3). Viewing advertisement-supported media accounted for the smallest share, on average, of all media use, with a mean of 1.0 (SD: 2.3) hour per week and with one outlying value with ≥21 h per week. Viewing advertisement-free media accounted for the greatest share of all media use, on average, at a mean of 9.7 (SD: 8.4) hours per week. Viewing mixed advertisement-supported media averaged 6.6 (SD: 9.8) hours per week. Children’s HEI scores were inversely and linearly associated with viewing of each media type, with a small to medium effect size based on Pearson correlation coefficients of approximately −0.16 to −0.26.

Table 3.

Children’s weekly screen media use and associations with diet quality.
Children’s media use Children’s HEI scores
 P-valuea
Mean (SD)
Total screen media use, hours per week 17.7 (14.1) r = − 0.26 <0.001
Stratified by ad-exposureb
 Ad-supported TV
  As continuous, mean (SD)
   Hours per week 1.0 (2.3) r = − 0.19 <0.001
  As ordinal, n (%)
   0 h per week 389 (72.7%) 55.3 (9.3) <0.001
   1 –7 h per week 130 (24.3%) 52.9 (9.5)
   8–14 h per week 15 (2.8%) 46.5 (6.4)
   14–21 h per week 0 (0.0%) − (−)
   ≥21 h per week 1 (0.2%) 47.7 (−)
Mixed ad-exposure media
  As continuous, mean (SD)
   Hours per week 6.6 (9.8) r = − 0.20 <0.001
  As ordinal, n (%)
   0 h per week 63 (11.8%) 55.8 (10.1) <0.01
   1 –7 h per week 322 (60.2%) 55.2 (8.8)
   8–14 h per week 79 (14.8%) 53.6 (10.5)
   14–21 h per week 39 (7.3%) 52.4 (9.8)
   ≥ 21 h per week 32 (6.0%) 49.2 (8.2)
Ad-free TV, DVD or VHS
  As continuous, mean (SD)
   Hours per week 9.7 (8.4) r = − 0.16 <0.001
  As ordinal, n (%)
   0 h per week 60 (11.2%) 57.7 (9.0) <0.001
   1 –7 h per week 191 (35.7%) 55.8 (8.9)
   8–14 h per week 155 (29.0%) 53.1 (9.3)
   14–21 h per week 78 (14.6.%) 52.3 (10.6)
   ≥ 21 h per week 51 (9.5%) 53.1 (8.3)
Open in a new tab

Among 535 children and one parent enrolled in a cohort study who completed a multiple day food diary assessment. R = Pearson’s correlation coefficients. Scatterplots confirmed associations were linear in each instance.

a

P-values are from Pearson’s correlation coefficients or one-way ANOVA.

b

A d-supported TV included viewing of any of the six predefined ad-supported children’s TV networks (Boomerang, Cartoon Network, Disney XD, the HUB, Nickelodeon, or Nicktoons). Ad-free TV included viewing of any of the five predefined ad-free children’s TV networks (Disney Channel, Disney Jr., Nick Jr., PBS Kids or Sprout) and was combined with DVD or VHS viewing. Mixed ad-exposure included mobile applications, Internet and video or computer games.

Greater viewing of advertisement-supported media remained associated with lower HEI scores in fully adjusted model (Table 4). Specifically, on average, HEI scores decreased by half a point with each 1-h increment increase in viewing advertisement-supported TV per week (β^:0.5; 95% CI: 0.8, −0.1; P < 0.01). That effect translates into a −3.5 (95% CI: 5.6, −0.7) point difference for a child who averaged 7 h of advertisement-supported TV viewing per week and a −7.0 (95% CI: 11.2, −1.4) point difference for a child who averaged 14 h of advertisement-supported TV viewing per week, both relative to a child who did not watch advertisement-supported TV. Children’s viewing of mixed advertisement-supported also related to a lower quality diet in that same adjusted model, although to a lesser extent, at a mean difference of −0.2 (95% CI: 0.2, −0.1; P < 0.01) points in HEI scores with each 1-h increment increase in viewing mixed advertisement-supported media per week. In comparison, children’s viewing of advertisement-free media was not associated with children’s dietary quality in that adjusted model (β^:0.1; 95% CI: 0.2, 0.04; P = 0.21). Model findings remained largely unchanged when excluding the one child with ≥21 h per week of advertisement-supported TV viewing from the model. Other factors that remained statistically associated with children’s HEI scores at the P < 0.05 level in the final adjusted model were the child’s age and the parent’s frequency of fast food intake; both were inversely related to child diet quality. We completed a sensitivity analysis with the final adjusted regression model further adjusted for whether the child had a TV in his/her bedroom; results were unchanged and a TV in the bedroom was unrelated to HEI scores in that adjusted model.

Table 4.

Adjusted associations between children’s media use and diet quality.

 Outcome: Children’s HEI scores
b (95% CI)2 P-valuea
Model intercept 60.0 (53.9, 66.1) -
 Children’s media use, per 1 h per week increment
  Ad-supported TV −0.5 (−0.8, −0.1) < 0.01
  Mixed ad-exposure − 0.2 (−0.2, − 0.1) < 0.01
  Ad-free TV, DVD or VHS − 0.1 (−0.2, 0.04) 0.21
Covariates
  Child age, years −1.1 (−2.2, 0.1) 0.03
  Child sex: girl vs. boy 0.3 (−1.2, 1.9) 0.67
  Parent lives with spouse or partner 1.1 (−1.3, 3.6) 0.36
Parent educational level
  Some high school to Associate’s degree Reference 0.37
  Bachelor’s degree or higher 0.8 (−1.0, 2.7)
Annual household income
  ≥$75,000 vs. <$75,000 − 0.02 (−1.8, 1.8) 0.98
Frequency of eating dinner together as a family, days per week
  1–2 days Reference
  3–4 days 0.6 (−3.0, 4.1) 0.76
  5–6 days 1.7 (−1.6, 5.1) 0.31
  7 days 2.6 (−0.6, 5.8) 0.11
Parent vegetable and fruit intakeb
  Meets guidelines for both Reference
  Below guidelines for one −1.3 (−3.3, 0.6) 0.19
  Below guidelines for both −1.8 (−3.7, − 0.04) 0.06
Parent frequency of soda intake
  0 days a week Reference
  1 –2 days a week − 0.1 (−2.4, 2.2) 0.94
  More than 2 days a week − 0.6 (−3.2, 1.9) 0.63
Parent frequency of fast food intake
  Less than once a month Reference
  At least monthly yet less than once a week −1.8 (−3.7, 0.2) 0.08
  At least weekly − 2.9 (−4.8, −1.0) < 0.01
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Among 535 children and one parent enrolled in a cohort study who completed a multiple day food diary assessment.b = Adjusted, estimated beta coefficient.

a

Beta coefficients are from one adjusted linear regression model; all model covariates are presented.

b

A d-supported TV included viewing of any of the six predefined ad-supported children’s TV networks (Boomerang, Cartoon Network, Disney XD, the HUB, Nickelodeon, or Nicktoons). Ad-free TV included viewing of any of the five predefined ad-free children’s TV networks (Disney Channel, Disney Jr., Nick Jr., PBS Kids or Sprout) and was combined with DVD or VHS viewing. Mixed ad- exposure included mobile applications, Internet and video or computer games.

4. Discussion

In this study, children’s use of advertisement-supported media, both the use of traditional network TV and online or digital platforms, was associated with an overall lower diet quality, while viewing of advertisement-free media was not. Specifically, we found that young children’s HEI-2015 scores were half of a point lower for each 1-h increment in weekly viewing of advertisement-supported children’s TV networks. That association equated to diet quality 3.5 points lower for a child who averaged 1 h of advertisement-supported children’s TV per day (7 h week) and 7 points lower for a child who averaged 2 h of advertisement-supported children’s TV per day (14 h per week), both as compared to child who did not view any advertisement-supported children’s TV. Increased viewing of mixed advertisement-support media, which included online and digital platforms where children may have been exposed to food advertising, was also associated with lower diet quality albeit at a lesser extent than exposure to advertisement-supported children’s TV networks. In contrast, children’s exposure to advertisement-free media was unrelated to children’s diet quality. Analyses accounted for multiple factors associated with children’s diet quality, including markers of the parent’s diet quality. Findings support the hypothesis that exposure to advertisement-supported media, a proxy for child-directed food-advertisement exposure, may ultimately result in a lower quality diet among young children, in a dose-dependent manner, independently of other risk factors.

In our study, children’s use of advertisement-supported children’s TV networks was most strongly associated with a lower dietary quality when considering our three media use categories. The high prevalence of food advertisements on children’s network TV is well documented: in 2014–2016 (a period that overlaps with that of this study), children aged 2–5 years old averaged over 1-h of traditional TV viewing per day (Rideout, 2017) and were exposed to an average of 10.4 food ads per day via TV (Harris et al., 2017, p. 214). Additionally, our previous work among this sample of children documented the prevalence of advertisements for sugar-sweetened breakfast cereals (Emond, 2019a) and children’s fast food meals (Emond, 2019b), two of the top food categories advertised to children (Harris et al., 2017, p. 214), on these children’s TV networks. Multiple studies support that young children’s exposure to food advertisements via TV is associated with their concurrent (Andreyeva et al., 2011; Dalton et al., 2017; Longacre et al., 2017) and subsequent intake (Emond, 2019a; 2019b) of advertised foods (i.e., high-sugar breakfast cereal, fast food, soda). Foods advertised to children are nutritionally poor (Harris et al., 2017, p. 214), and a greater intake of advertised foods in sufficient quantities may indeed relate to an overall lower dietary quality. However, it is also likely that children’s exposure to food advertisements generalizes to their desire for other similar, highly-palatable foods, even if not the specific brands advertised. That hypothesis is supported by experimental studies which demonstrate that TV food advertising exposure can cue immediate eating of highly-palatable snack foods with effects that are not brand-specific (Boyland et al., 2016; Boyland & Whalen, 2015; Emond et al., 2016).

In this study, children’s use of mixed advertisement-supported media was also associated with lower dietary quality scores in our study, although to a lesser extent than viewing of children’s advertisement-supported TV networks. Our measure of mixed advertisement-supported media included online platforms and apps, content that may or may not include food advertisements (WHO Regional Office for Europe, 2016) based on the exact content. We did not directly measure what content children accessed via those platforms. However, the placement of food advertisements on child-directed websites (Harris et al., 2017, p. 214), online educational games (Emond et al., 2020; Harris et al., 2017, p. 214), and apps (Meyer et al., 2019) is common. For example, in 2016 (a year that overlaps with this study timeframe), there were more than 33 million food-related banner advertisement “impressions”, or the total number of times any person viewed the banner advertisement in that year, on PopTropica.com, an online educational game for children (Harris et al., 2017, p. 214). Children are also exposed to food marketing via non-traditional advertising when online, such as when viewing “kid influencer” online videos, or online videos created by children promoted via social media (Alruwaily et al., 2020). For example, among a sample (n = 418) of YouTube videos promoted by the most popular kid influencers in 2019, 43% of the videos featured food, nearly all (90.3%) of which were unhealthy branded products (Alruwaily et al., 2020). Importantly, digital and online media is increasingly a prominent source of young children’s media use (Rideout & Robb, 2020). In 2020, viewing online videos accounted for the largest portion of children’s (age 0–8 years old) total media use at 37%, and YouTube accounted for most of that viewing time. In contrast, TV viewing from live, recorded, or on demand services was approximately 23% (Rideout & Robb, 2020). Therefore, given the associations we report between children’s exposure to advertisement-supported media and overall dietary quality, it is critical to examine how contemporary media use, including digital media use, may expose young children to food marketing and in turn, affect their dietary intake (WHO Regional Office for Europe, 2016).

In our sample, HEI scores averaged 54.5, which aligns with previous cross-sectional studies regarding diet quality that reported HEI-2015 scores ranging from approximately 52.5 to 60.1 (Kachurak et al., 2019; Luecking et al., 2020; Maillot et al., 2019; Thomson et al., 2019) and with scores ranging from 46.5 to 60.1 including HEI 2010 (Banfield et al., 2016; Benjamin-Neelon et al., 2018; Ford et al., 2017; Ramsay et al., 2017). The HEI scores in this sample were far below the ideal score of 100, a score that indicates a diet in line with the USDA dietary guidelines (National Cancer Institute, 2020; Snetselaar, 2015; U.S. Department of Health and Human Services and U.S. Department of Agriculture., 2015). As most of these children are on-average following a low-quality diet, potential immediate health consequences (i.e., impaired glucose tolerance, type II diabetes, high blood pressure, etc.) (Vos et al., 2017), and later-in-life consequences (i.e., cardiometabolic diseases, cancer) (, 2020CDC; Vos et al., 2017), may have an increased risk of occurring. Studies support that children’s preferences and food patterns may be largely established by the preschool-years and may continue into adulthood (Birch, 1998; Woo et al., 2020). Thus, interventions or actions to support a high-quality dietary intake among children that are initiated before the preschool-years may be essential to help offset the development of low-quality dietary patterns and the related chronic disease sequalae. Our study supports that eliminating children’s food marketing exposure via media before the preschool years is important to support the development of high-quality diets among young children. In this sample, most of the screen time viewed was not advertisement-supported, suggesting that at least for this age group, there are several options available for advertisement-free media for parents to choose from.

Strengths of this study include taking place in a natural setting, the use of 3-day food diaries with a comprehensive food and drink database customized for child-specific food, and the inclusion of multiple risk factors that may relate to children’s dietary quality as covariates in our analyses. We also confirmed the presence of food-advertisements on the children’s TV networks children viewed in this study as reported in two previous reports among this same study sample (Emond, 2019a; 2019b). Study limitations include the assumption that children’s viewing and use of online platforms and apps contained food advertisements, however, other studies support this assumption (Emond et al., 2020; Harris et al., 2017, p. 214; Meyer et al., 2019). Also, while exposure to advertisement-supported media was used as a proxy for exposure to food advertisements, we did not include children’s exposure to food marketing via media used by others in the home or via other marketing methods. Children’s viewing of advertisement-supported media was low in this study, with all but one child viewing at most 14 h of advertisement-supported TV per week. Thus, results are generalizable to children with up to 14 h of media per week, and results require confirmation in samples with greater amounts of advertisement-supported TV viewing. Additionally, the results of this study are based on parents’ self-report of their child’s viewing and eating habits, which could be affected by social desirability bias, reporting bias, and recall error. However, our measures of media use and diet quality are consistent with those used in other studies among this age group (Banfield et al., 2016; Kachurak et al., 2019; Rideout, 2017). We included three indicators of dietary quality among parents as covariates: intake of fruits, vegetables, fast food, and sugar-sweetened beverages. While we did not use the HEI-2015 to assess parent’s overall dietary quality, the intake of those foods have been highly correlated with overall diet quality among adults (Poti et al., 2014). This study is cross-sectional and causality cannot be confirmed. Also, while we adjusted for several key covariates including family meal-time eating habits, a TV in the child’s bedroom, and parent diet quality, results could be affected by residual confounding. Our sample reflected a largely non-Hispanic, white population (~86%), which is similar to the New Hampshire community population where recruitment and enrollment took place (United States Census Bureau, 2019). However, results may not be generalizable to the entire US, and additional studies in more diverse populations are needed.

5. Conclusions

In this study of 535 preschool-age children recruited from the community, exposure to advertisement-supported media was associated with a lower dietary quality in a dose-response relationship, independent of other risk factors. Early childhood is an important timeframe to shape and support a diet of high quality to best support child health, and this study’s findings suggest that eliminating young children’s exposure to food advertisements via media may help in those efforts. As young children’s media use is shifting more towards online platforms and away from traditional TV, our findings demonstrate the need for additional research to understand how food marketing exposure on digital platforms, both via traditional and non-traditional marketing, ultimately influences children’s dietary intake. Findings from our study and this greater line of research further support regulations on child-directed food marketing to support children’s dietary quality.

Acknowledgements

We would like to thank all of the study participants and their families for participating in the study.

Funding

This work was supported by the National Institutes of Health, grant numbers R01HD071021 and K01DK117971.

Role of the funder/sponsor

The National Institutes of Health had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.

Footnotes

Declaration of competing interest

All authors declare that we have no conflicts of interest in the authorship or publication of this manuscript.

Financial disclosures

No financial disclosures were reported by the authors of this paper.

Ethics statement

The Dartmouth College Committee for the Protection of Human Subjects approved the study.

Data availablity

Data are available apon reasonable request. Ms. Carroll has full access to the data reported in the manuscript.

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Associated Data

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

Data Availability Statement

Data are available apon reasonable request. Ms. Carroll has full access to the data reported in the manuscript.

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