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. Author manuscript; available in PMC: 2022 Apr 1.
Published in final edited form as: Eat Behav. 2021 Feb 25;41:101492. doi: 10.1016/j.eatbeh.2021.101492

Momentary and personal characteristics predicting maternal fruit and vegetable preparation for children using ecological momentary assessment

Bridgette Do a, Shirlene D Wang a, Christine H Naya a, Genevieve F Dunton a,b, Tyler B Mason a
PMCID: PMC8131213  NIHMSID: NIHMS1677955  PMID: 33677396

Abstract

A large body of literature on child-focused research regarding healthy eating within the family context has focused on behavioral management strategies, such as reinforcement, or parental modeling through personal intake or encouragement. However, food preparation behaviors among mothers have been understudied. Also unknown is how maternal food preparations behaviors vary across population subgroups and contexts. The study objective was to elucidate momentary characteristics (i.e., time of day, weekday, and family meals) and personal characteristics (i.e., ethnicity, working status, household characteristics, body mass index, income, and child’s age) associated with maternal fruit and vegetable (F/V) preparation through ecological momentary assessment (EMA). 186 mothers (Mage=40.81) of children (Mage=9.61, 49.5% female) completed six semi-annual waves, each lasting seven days. Mothers completed up to eight EMA surveys a day, which assessed family meals and F/V preparation, and reported personal characteristics through paper questionnaires. Multilevel generalized estimating equations examined the likelihood of F/V preparation. Momentary, within-day characteristics (i.e., occurrence of family meals, weekdays, afternoons) were associated with greater likelihood of mothers’ fresh F/V preparation (ps<0.05). Additionally, personal characteristics such as non-Hispanic ethnicity, not working full-time, having a child aged six months to five years in the household, and lower child BMI-z were associated with greater fresh F/V preparation among mothers (ps<0.05). Findings may inform family-based obesity and nutrition intervention programs by understanding which families and in what contexts mothers are more likely to prepare F/Vs.

Keywords: meal preparation, cooking, ecological momentary assessment, child, parent, fruit, vegetable

1. Introduction

Approximately 60% of children ages 4-18 years old did not meet the recommended daily fruit guidelines, and 93% of children did not meet the recommended daily vegetable guidelines based on 2010 National Health and Nutrition Examination Survey (NHANES) data (Banfield et al., 2016). These trends are concerning as poor dietary intake, particularly low fruit and vegetable (F/V) intake, is one of the main lifestyle behaviors linked to childhood obesity (Hoelscher et al., 2013). Dietary habits developed in childhood persist into adulthood, and children with low vegetable intake are less likely to consume recommended levels of vegetables as adults (Maynard et al., 2006; Hung et al., 2004). The benefits of F/V consumption have been consistently shown in epidemiological research. For example, F/Vs contain a myriad of beneficial vitamins and minerals that help maintain healthy blood pressure and blood sugar levels, as well as reducing the risk for chronic illnesses. The negative health consequences of low F/V intake include greater risk for cardiovascular disease and chronic illness such as type 2 diabetes, cardiovascular disease, and certain types of cancer in adulthood and increased mortality rates from these diseases (Holt et al., 2009; Bazzano, 2006; Yeh et al., 2008).

Parents and the home environment are important influences on F/V consumption throughout a child’s life, as older children and adolescents still consume about 65% of their energy intake at home (Yeh et al., 2008; Guthrie et al., 2002; Lin et al., 2001). Systematic reviews have consistently found that familial factors, such as family meals, encouragement, and parental intake, influence children's F/V intake as parents play a major role in providing food and determining what their children eat (Patrick et al., 2005; Cullen et al., 2007; Pearson et al., 2009; Anzman et al., 2010). Furthermore, behavior management techniques, like reinforcement systems, and parental modeling through personal have been largely utilized in healthful eating interventions among families (Natale et al., 2014; Burrows et al., 2010). Existing research shows that availability of F/Vs is positively associated with child consumption; for instance, availability and accessibility of F/Vs explained 35% of the variance in the intake of fruit, fruit juice, and vegetables among a sample of 4th grade girls (Cullen et al., 2007). Additionally, greater availability of certain foods, such as vegetables, has been positively associated with intake of and preferences for these foods (Hanson et al., 2005; Krølner et al., 2011; Rasmussen et al., 2006).

F/V preparation and cooking are major potential targets to improve dietary intake that have been rarely studied (Smith et al., 2016; Olfert et al., 2019). Preparation and cooking by parents are of particular interest due to the fact that they involve some time and effort. Previous studies have shown that children consume more F/Vs when the food is cut up or sliced by a parent (Christian et al., 2013). In addition, focus groups with 4th and 5th grade classes have shown that they preferred vegetables prepared by a parent at home compared to at school (Baranowski et al., 1993). Also, in a previous analysis of data from the current study, Do and colleagues (2020) found that mothers who more often prepared fresh F/V had children who consumed more F/V; additionally, at moments when mothers reported more F/V preparation, their child was more likely to report F/V consumption. However, there is a paucity of research on factors associated with mothers’ F/V preparation.

While the relationship between family meals and F/V intake has been previously examined, there less is known about the relationship between family meals and F/V preparation. Family meals was positively associated with improved dietary intake among adolescents (Neumark et al., 2003; Berge et al., 2003; Berge et al., 2016; Larson et al., 2006). For example, adolescents of families who reported sometimes eating a family meal together consumed on average one fifth more portions of F/V than families who never eat a meal together and children who consumed more meals with their families across the week also consumed more F/Vs (Larson et al., 2006; Andaya et al., 2011). Additionally, serving vegetables at family meals was associated with children’s overall vegetable intake (Trofholz et al., 2017). Given the potential health benefits of having meals together as a family, a deeper understanding on the relationship between family meals and F/V preparation is warranted.

There are also a variety of disparities that may impact available income for F/Vs, time to prepare food, and food insecurity that in return affect parents’ ability to prepare healthful food. Identified barriers to F/V preparation include high cost and perceived lack of time (Yeh, et al., 2008). In the general population, there is a gap between the perceived cost of fresh F/Vs compared to convenience foods such as potato chips or fast food (Hawrysz, 2009). Limited time has also been consistently identified as a contributor to decreased general food preparation behaviors and increased consumption of convenience foods (Jabs et al., 2007; Sliwa et al., 2015; Monsivais et al., 2014). Evidence shows that pre-prepared meals contained less F/V compared to fully or partly homecooked meals (Fertig et al., 2019). With the growing number of dual-income families, families’ eating habits have changed from the increased income and decreased food preparation time (Hawrysz, 2009; Bauer et al., 2012). Further, given the increased demands on time and energy from both work and family, employed parents may engage in more time-saving behaviors, such as meals that can be quickly prepared or eating out, to save cooking and cleaning time (Jackson et al., 1985). Understanding the potential factors associated with F/V preparation for children is necessary for future health promotion programs among families.

Previous studies have primarily assessed food preparation using retrospective surveys, which ask participants to summarize behaviors over a specified period (e.g., past 7 days), and thus, are subject to recall biases (Shiffman, 2008). Ecological momentary assessment (EMA) of mothers’ F/V preparation has the potential to extend this research area and overcome some limitations in the literature. EMA is a real-time data capture method that may reduce biases related to recall by collecting data on participants' momentary behaviors and experiences in their natural environments (Shiftman, 2008). In addition to examining differences between participants (between-subjects effects; e.g., personal characteristics), the repeated measures collected throughout the day by EMA can examine differences within individuals across the course of the day (within-subjects effects; e.g. momentary characteristics) (Mason et al., 2019).

To support and advance current literature on maternal food preparation behaviors, specifically F/V preparation, this study used EMA to elucidate the personal characteristics (e.g., working status, household characteristics, body mass index, income, and child’s age) and momentary, within-day characteristics (e.g., time of day, weekday vs. weekend day, and family meals) associated with maternal fresh F/V preparation and cooking in naturalistic settings. The current study specifically inquired about preparation of fresh F/Vs, given the added nutritional value compared to canned or frozen F/Vs (Rickman et al., 2007a; Rickman et al., 2007b). The current analyses was exploratory in nature.

2. Materials and Methods

2.1. Study Design and Participants

Study participants included mothers enrolled in the Mothers and Their Children’s Health (MATCH) study. The MATCH study is a longitudinal study examining the effects of maternal stress on their children’s obesity-related behaviors and risk through real-time data capture methodologies (Dunton et al., 2015). The study took place between 2014 and 2018. Participants were asked to participate in six semi-annual waves spanning across three years. Participants were recruited through informational flyers and in-person staff visits to community centers and elementary schools in the greater Los Angeles area. The inclusion criteria for the MATCH study were: (1) child is between 8-12 years old, (2) child lives with the mother at least 50% of the time, and (3) mother can read and speak English or Spanish. The exclusion criteria were: (1) mother is currently pregnant, (2) mother currently works away from the home for more than two weekday evenings per week (between the hours of 5-9 P.M. or more than eight hours on any weekend day, (3) the child is currently enrolled in a special education program, (4) the child is considered underweight by a body mass index (BMI) percentile < 5%, (5) mother or child report a physical health condition that may limit physical activity, (6) mother or child currently take medications for thyroid functions or psychological conditions such as depression, anxiety, mood disorders, or attention-deficit/hyperactivity disorder, or (7) mother or child currently uses oral or inhalant corticosteroids for asthma. Mothers did not have to be biological parents to the children and there was no exclusion criteria based on family structure.

A total of 464 mothers expressed interest in participating in the study through flyers and in-person staff visits, but 154 mothers later declined interest or were unable to be reached, thus leaving 310 mothers who were successfully screened for eligibility. A total of 202 mothers were eligible for the study, provided informed consent, and were initially enrolled in the study at baseline. Participants were included in the analyses if they had data from at least one wave with no missing data for the predictors of interest (N=186). All aspects of the study were approved by the Institutional Review Boards at the University of Southern California and Northeastern University (Reference: HS-12-0046) and were conducted in accordance with the Declaration of Helsinki.

2.2. Procedures

Eligible participants, both mothers and children, attended two in-person data collection sessions per wave; each wave lasted a total of seven days. At baseline, participants provided written informed consent. During each wave, study staff took participants’ anthropometric measurements at the first data collection session; height was measured to the nearest 0.1 cm with a portable statiometer (PE-AIM-101) and weight was measured to the nearest 0.1 kg with an electronically calibrated digital scale (Tanita WB-11a). Mothers reported demographic and personal information through paper-and-pencil questionnaires at each wave. Participants dropped off all study materials and received compensation during the second data collection session that occurred at the end of the seven days. Participants were compensated 100 USD each for every completed wave (mother-child dyads could receive a maximum total of 200 USD per wave). Families had an opportunity to receive bonus compensation: 100 USD for completing the first three waves and an additional 300 USD for completing all six waves. Families could receive up to 1600 USD in compensation across the three years.

Participants were loaned an Android smartphone (MotoG or Motorola X) without a data plan for the 7-day study monitoring period of each wave (Motorola Mobility, Chicago, IL, USA). A custom software phone application for smartphones utilizing the Android operating system collected EMA data (Google Inc., Mountain View, CA, USA). Participants who owned a personal Android phone that was compatible with the study application were given the option to download the application on their own phone. The study application was available in English or Spanish. Participants were trained on how to use the study application through verbal and written instructions. EMA data were wirelessly uploaded and stored on a secure Internet-accessible server.

During each wave, participants received EMA prompts on the evening of the first data collection session, across the next six days, and up until 5:00 P.M. on the day of the second data collection session when the phone was returned to study staff. Participants were asked to carry the study smartphone with them at all times that they were awake, aside from non-compatible activities (e.g., sleeping, showering, swimming). Participants were instructed to connect their study smartphone to their home wireless Internet (Wi-Fi). If wireless connection was not available, EMA data were downloaded directly from the study phone when it was returned to study staff.

Mothers completed EMA surveys on their smartphones through the study application at random times through the notification of a prompt (i.e., signal-contingent). Participants were notified to complete surveys through an audible prompt and/or vibration. When prompted, participants were asked to stop their current activity and complete an EMA survey. On average, mothers completed each survey in 124.0 seconds (Dzubur et al., 2018). If no entry was made, the study application sent up to two reminder signals at 3-minute intervals (e.g., at 3 and 6 minutes after the initial prompt). The EMA survey closed 12 minutes after the initial prompt and was considered “missed”. Participants were instructed to ignore signals during any inconvenient activities (e.g., driving, sleeping, bathing). Mothers were prompted up to four times per day on weekdays and up to eight times per day on weekend days. On weekdays, participants were randomly prompted once during each of the following time windows: 3:00-4:00 P.M., 5:00-6:00 P.M., 7:00-8:00 P.M., and 9:00-9:30 P.M. On weekend days, participants were randomly prompted once during each of the following time windows: 7:00-8:00 A.M., 9:00-10:00 A.M., 11:00 A.M.−12:00 P.M., 1:00-2:00 P.M., 3:00-4:00 P.M., 5:00-6:00 P.M., 7:00-8:00 P.M., and 9:00-9:30 P.M. Mothers were not prompted before 3:00 P.M. on weekdays given that the participating child in the larger study was in school during those hours. During each wave, participants provided study staff with their sleep and wake-up times to ensure that surveys were not prompted while they were sleeping.

2.3. Measures

2.3.1. Personal characteristics

Participants completed paper-and-pencil questionnaires during each wave. Questionnaires assessed self-reported ethnicity (Hispanic/Latino vs. not Hispanic/Latino), annual household income, household status (single parent vs. not a single parent), marital status (married vs. not married), working status (work full-time vs. does not work-full time), and child’s age. In addition, participants indicated how many children, including non-relatives, lived in their household in the following age ranges: 0 – 6 months, 6 months – 5 years old, 6 years old – 12 years old, and 13 −17 years old. For the current study, having at least one child in the age range was coded as 1, and having no children in the age range was coded as 0. Mothers’ BMI (kg/m2) was calculated using their height and weight measurements taken by research staff at baseline. Children’s height and weight measurements from research staff at baseline were used to calculated Centers for Disease Control and Prevention (CDC) age- and sex-specific BMI-z scores using EpiInfo (CDC, Atlanta, GA, USA). The current study utilized baseline data for the following predictors: Hispanic/Latino ethnicity, annual household income quartile, working status, having a child between the age 6 months – 5 years old living in the household, BMI (kg/m2), and child’s BMI-z score. Self-identified race was not utilized in the current analyses, but descriptive statistics are shown in Table 1.

Table 1.

Participant characteristics at baseline (N=186)

Variable n (%)
Racea
  AI/ANb 5
  Asian 22
  Black or African American 28
  NH/PIc 3
  White 77
  Other 66
Ethnicity
  Hispanic/Latino 93 (50)
  Not Hispanic/Latino 93 (50)
Child’s Sex
  Male 92 (49.5)
  Female 99 (50.5)
Employment status
  Work full-time 105 (56.5)
  Does not work full-time 109 (43.5)
Type of household
  Single parent 41 (22.0)
  Non single parent 145 (78.0)
Marital status
  Married 127 (68.3)
  Not married 59 (31.7)
Annual household income
  Less than $34,999 50 (26.9)
  $35,000-$74,999 56 (30.1)
  $75,000-$104,999 36 (19.4)
  Greater than $105,000 44 (23.6)
BMI category
  Underweight 3 (1.6)
  Normal Weight 61 (32.8)
  Overweight 60 (32.3)
  Obesity 62 (33.3)
Child BMI-z category
  Underweight 3 (1.6)
  Normal Weight 118 (63.4)
  Overweight 35 (18.8)
  Obesity 30 (16.2)
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a

Participants were able to check more than race that they identify with, thus percentages are not displayed

b

AI/AN = American Indian or Alaska Native

c

NH/PI = Native Hawaiian or Pacific Islander

2.3.2. Momentary Characteristics

Characteristics that occurred at the momentary, within-day were collected through EMA. The occurrence of a family meal was assessed through the following item: “ “Since you woke up this morning [first prompt of the day]/Over the last 2 hours [all subsequent prompts], which have happened? (check all)”. During the first prompt of the day, the EMA item asked “Since you woke up this morning, which have happened? (check all)”. The response options included: “eaten a meal together as a family”, “child watched TV/videos while eating”, child ate a meal in the car”, “let my child watch TV/videos as a reward”, and “gave my child food as a reward.” These responses were adapted from the Parenting Strategies for Eating and Activity Scale in order to assess weight-related parenting practices (Larios et al., 2009). Responses were coded as 1 if the item was checked, and 0 if the item was not checked. Only the response option “eating a meal together as a family” was utilized in the current analyses. In addition, weekend day (vs. weekday) and time of day (morning [before 12pm; only weekend prompts], afternoon [12pm - 5pm], evening [after 5pm]) were included in the analyses as momentary characteristics for predicting maternal F/V preparation.

2.3.3. Maternal fruit and vegetable preparation

Maternal fresh F/V preparation was measured by the following EMA item: “Since you woke up this morning [first prompt of the day]/Over the last 2 hours [all subsequent prompts], have you cooked or prepared any fresh fruits or vegetables for your child to eat?”. Response options were “yes” (coded as 1) and “no” (coded as 0). To reduce participant burden, the EMA program was designed to prompt mothers this item, along with other parenting-related questions, during a randomly-selected 60% of the prompts that they indicated that they had spent some time with their child in the last 2 hours. At all EMA prompts mothers indicated if they had spent time with their child in the last 2 hours (“yes” vs. “no”). Therefore, when a mother indicated that they had spent time with their child in the last 2 hours, only 60% of those prompts asked about F/V preparation.

2.4. Statistical analyses

Generalized estimated equations with a logistic function tested the associations between personal characteristics, momentary characteristics, and the likelihood of EMA-assessed maternal F/V preparation. Child age and occurrence of a family meal were disaggregated into between-subject (BS; Level-2, person-level) and within-subject (WS; Level-1, prompt level) effects. The between-subject level represents the deviation of one’s own mean from the group mean across all available prompts and waves, while the within-subject level represents any given prompt’s deviation from one’s own mean across all available prompts and waves (Hedeker et al, 2012). Separate univariate models assessed the relationship between predictors of interest and maternal F/V preparation. Type of household (single parent vs. non single parent), child’s sex, marital status (married vs. not married), and having at least one child 0–6 months, 6 years −12 years old, or 13 −17 years old were not significantly associated with the outcome of interest (ps > .05) and therefore not included in the final model. A final multi-variable model examined the relationship between predictors of interest (weekday, time of day, child age, family meals, ethnicity, household income, working status, having at least one child 6 months −5 years old, BMI, and child BMI-z). All analyses were conducted in SPSS (Version 25).

3. Results

3.1. Descriptive Characteristics

Participant characteristics are shown in Table 1. At baseline, mothers were on average 40.80 years old and children were on average 9.61 years old. About half of the children in the study were female. Less than 2% of children had a measured BMI in the underweight category, 65.1% in the normal weight category, 18.8% in the overweight category, and 16.1% in the obese category. Half of the mothers identified as Hispanic/Latino, the majority were employed full-time, and about 20% of the mothers reported having at least one child ages six months to five years old in the household. On average, mothers had a BMI classified as overweight. Of the 5,558 total prompts completed, 822 (14.8%) occurred during the morning (before 12 P.M.; only weekend prompts), 1,418 (25.5%) occurred during the afternoon (12-5 P.M.), and 3,318 (59.7%) occurred during the evening (after 5 P.M.). 2,712 (48.8%) of the completed EMA prompts were administered on during the weekend. Of the EMA prompts that answered the question regarding F/V cooking and preparation, 4,181 (42.3%) of prompts indicated “yes” to cooking or preparing fresh F/Vs for their child to eat in the past two hours.

3.2. Data Availability

Participants were included in the analyses if they had data from at least one wave with no missing data for the predictors of interest (N=186). Of the 202 mothers enrolled at baseline, a total of 27,667 EMA prompts were successfully delivered to 200 mothers across six waves. Mothers answered an average of 79.0% (range 7.4% to 100%) delivered EMA prompts, which resulted in a total of 21,861 completed EMA prompts across all six waves. Of these completed prompts, mothers indicated being with their child during 16,594 (75.9.%) prompts. The EMA protocol prompted the question about F/V preparation 60% of the time resulting in mothers answering the question regarding F/V preparation in 9,876 (59.5%) prompts. Missing EMA data on the predictors or outcome of interest, from 14 participants, were excluded from the analyses. Therefore, the final analytic sample included 186 mothers with a total of 5,558 EMA prompts. A total of 1,178 prompts (21.2%) among 175 mothers came from wave 1, 920 prompts (16.6%) among 137 mothers came from wave 2, 830 prompts (14.9%) among 134 mothers came from wave 3, 902 prompts (14.4%) among 132 mothers came from wave 4, 873 prompts (15.7%) among 138 mothers came from wave 5, and 955 prompts (17.2%) among 143 mothers came from wave 6.

On average, participants took 216 seconds (SD=137 seconds) to respond to an EMA prompt after thy were first signaled. Participants were more likely to comply with EMA prompts on weekend days compared to weekdays (B=0.65, SE=0.02, p<0.001). Mothers who did not identify as Hispanic/Latino were more likely to comply with prompts compared to mothers who identified as Hispanic/Latino (B=0.17, SE=0.02, p<0.01). Participants were more likely to comply with EMA prompts in the morning (B=0.16, SE=0.03, p<0.01) or afternoon (B=0.29, SE=0.03, p<0.01) compared to the evening.

3.3. Generalized Estimating Equations

Results are summarized in Table 2. All variables of interest (shown in Table 2) were included in the final model simultaneously (multi-variable model). The final multilevel model using GEE showed a positive within-subject association between an occurrence of a family meal and the likelihood of F/V preparation (B=1.10 [95% CI: 0.96, 1.25], OR=3.00). This result suggests that when family meals occurred, mothers were three times as likely to cook or prepare F/Vs. Weekdays were associated with F/V preparation, such that mothers were 1.42 times as likely to report F/V preparation on weekdays (B=0.35 [95% CI: 0.20, 0.50], OR=1.42). Additionally, time of day was associated with F/V preparation; mothers were 1.20 times as likely to report F/V preparation during the afternoon compared to evening (B=0.18 [95% CI: 0.02, 0.35], OR=1.20), but they were about 25% less likely to cook or prepare F/Vs during the morning compared to evenings (B=−0.27 [(95% CI: −0.48, −0.05], OR=0.76). Given that the EMA items had a 2-hour recall window, the findings suggest that mothers were more likely to prepare F/V in the afternoons (11 A.M.−4 P.M.) compared to evenings (3:00-9:30 P.M.) and less likely to prepare F/V in the mornings (7 A.M.−12 P.M.) compared to evenings (3:00-9:00 P.M.). It is important to note that morning prompts were only given on weekend days. We also found a positive between-subject association between occurrence of family meal and F/V preparation (B=2.79 [95% CI: 1.76, 3.83], OR=16.28) suggesting that families that ate meals together had about 16 times the odds of cooking or preparing fresh F/Vs in the same past two hours. In addition, mothers who did not identify as Hispanic or Latino were about one-and-a-half times as likely to report F/V preparation (B=0.44 [95% CI: 0.13, 0.76], OR=1.55). Similarly, those who did not work full-time were about one-and-a-half times as likely to report F/V preparation (B=0.43 [95% CI: 0.15, 0.71], OR=1.54). Mothers that had at least one child between the ages of six months to five years living in the same household were about one-and-a-half times as likely to report preparation of F/V (B=0.42 [95% CI: 0.08, 0.76], OR=1.52). Mothers of children with higher baseline BMI-z scores at baseline were 10% less likely to report preparing F/Vs (B=−0.11 [95% CI: −0.22, −0.01], OR=0.90).

Table 2.

Results of multilevel model examining the effects of personal and momentary characteristics on maternal preparation of fruits and vegetables (F/V)

Maternal F/V Preparation
N
Level-1 (Prompts) 5,558
Level-2 (Participants) 186
B (SE) 95% CI
Intercept −0.80 (0.34) [−1.47, −0.14]
Level-1 Predictors
Weekdaya 0.35 (0.07)** [0.20, 0.50]
Time of day (morning)b −0.27 (0.11)* [−0.48, −0.05]
Time of day (afternoon)b 0.18 (0.09)* [0.02, 0.35]
Child age (WS) −0.03 (0.04) [−0.11, 0.06]
Child age (BS) −0.02 (0.07) [−0.16, 0.11]
Family meal (WS) 1.10 (0.07)** [0.96, 1.25]
Family meal (BS) 2.79 (0.53)** [1.76, 3.83]
Level-2 Predictors
Not Hispanic/Latinoc 0.44 (0.16)** [0.13, 0.76]
Household incomec −0.06 (0.07) [−0.19, 0.07]
Does not work full-timec 0.43 (0.14)** [0.15, 0.71]
Child 6 months-5 years oldc 0.42 (0.17)* [0.08, 0.76]
BMI (kg/m2)c 0.01 (0.01) [−0.004, 0.03]
Child BMI-zc −0.11 (0.06)* [−0.22, −0.01]
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*

p < .05

**

p < .01.

Note. Level-1 includes predictors that are time-varying (i.e., momentary) and Level-2 includes predictors that are stable across the waves of assessment (i.e., personal characteristics). BS= Between-subjects (person-level mean); WS= Within-subjects (centered from the person-level mean); BMI = Body mass index (kg/m2); BMI-z =Body mass index (kg/m2) standardized by child’s sex and age.

a

Weekday= 1 vs. weekend day = 0

b

Morning (before 12pm), afternoon (12pm – 5pm), evening (reference; after 5pm)

c

Measured at baseline

4. Discussion

The purpose of this paper was to examine personal and momentary characteristics that predict mothers’ preparation of fresh F/Vs for children in natural setting. Positive relationships were seen between family meals, weekdays, afternoons, non-Hispanic ethnicity, not working full-time, having at least one child aged six months to five years old in the household, and lower child BMI-z with mothers’ fresh F/V preparation. Findings from this paper increase our understanding of which mothers are likely to prepare fresh F/Vs for their children, and when mothers are likely to prepare fresh F/V for their children.

Results indicated that there were both within- and between-subjects associations between having a family meal and mothers’ preparation of fresh F/Vs. In particular, at times when mothers reported having a family meal, they were more likely to report preparing fresh F/Vs for their child, and mothers who reported having more family meals across EMA, prepared more F/Vs. These findings are consistent with the largely between-subjects literature suggesting that family meals are associated with greater F/V consumption among children (Watts et al., 2017). Results of the current study additionally indicate that this pattern is partially due to the direct preparation of meals that include fresh F/Vs. Consistently, in a study of 1,923 parents, 70% of parents mentioned regularly serving vegetables, other than potatoes, during family meals (Neumark-Sztainer et la., 2014). Increasing the occurrence of family meals may be an efficacious strategy to also increase overall F/V intake.

Results also found that mothers were more likely to prepare fresh F/Vs on weekdays compared to weekends. Research suggests that meals and snacks are less structured on weekends. and parental supervision of food intake may be more relaxed on weekend days compared to school days (Rothausen et al, 2012; Taylor et al., 2005). Thus, mothers may not prepare foods for children on weekends and may be more likely to allow unhealthy foods such as fast food or high-sugar/high-fat snacks. Compared to evenings, mothers were more likely to prepare fresh F/Vs in the afternoon and less likely in the morning. It is possible that many children do not eat breakfast regularly as research shows that middle-to-late childhood is when breakfast consumption begins to decrease (Utter et al., 2007). Also, given the ubiquity of ready-to-eat breakfast foods, children may eat these types of foods opposed to fresh F/Vs in the morning. When interpreting the current study’s results regarding mornings, it should be noted that morning prompts only occurred on weekend days. With regard to afternoons versus evening, another study found a high proportion of fruit consumption by children in the afternoon (Rockell et al., 2011). Thus, fruit may be a common after-school or mid-day snack option. Future research should distinguish preparation for the type of meal (e.g. snack vs. dinner) in order specify the contexts that F/V preparation is more likely to occur in.

The findings suggest that there population subgroup differences associated with maternal F/V preparation. Mothers who identified as Hispanic/Latino were less likely to prepare fresh F/Vs compared to non-Hispanic mothers. Future research should examine possible structural barriers and systemic inequities that may influence these differences, such as accessibility to and affordability of healthy foods, employment (e.g., type of job, working hours), and food insecurity. Mothers who were not working full-time were more likely to prepare fresh F/Vs. Those who were working full-time may have less opportunity to prepare F/Vs given work demands and potentially increased stress, which could reduce the likelihood of preparing of healthy foods. Congruently, research has found that children of mothers who work tend to consume more unhealthy snacks and less F/Vs (Datar et al., 2014). In addition, employed mothers report less frequent family meals, which we found in the current study was related to more preparation (Neumark-Sztainer et al., 2003). While mothers of all employment statuses were included in the study, mothers who reported working on weeknights or more than eight hours a day on weekend days were excluded from the study. This exclusion criteria may have impacted the demographic makeup of the sample and the current findings may not be generalizable to parents with different work schedules. Those working jobs with nightshifts (e.g., healthcare) or weekend hours may have been underrepresented (e.g., hospitality, retail, fast food). It is also important to acknowledge that families who have a parent present to prepare food regularly may differ than those who do not. There are additional factors that may influence mothers’ ability to prepare F/Vs for their children that should be examined but are beyond the scope of the current study. Future research can explore the effects of disparities (e.g., neighborhood characteristics, available time, food insecurity, access to healthy foods) on the relationship between within-day characteristics and F/V preparation by collecting additional geographic or community-level data. Furthermore, additional research on fathers, primary caregivers, and families of more diverse socioeconomic and geographic backgrounds is needed.

Child characteristics were also found to be associated with F/V preparation. Mothers who had at least one child between the age of six months and five years were more likely to prepare fresh F/Vs. When mothers prepare F/Vs for younger children, they may also prepare them for older children as well. Finally, results suggest that children’s BMI-z scores were associated with mothers’ F/V preparation. Future studies should incorporate additional metabolic parameters (e.g., body composition, cholesterol, glucose) to better understand the relationship between child characteristics and F/V preparation, given that BMI has limitations has a marker of health, such as the inability to differentiate between fat and muscle mass. The association between BMI and F/V preparation may due to factors at a variety of levels, ranging from individual to systemic; these potential factors should be examined in future studies.

Findings of this study can inform family-based obesity and nutrition intervention and prevention programs. Results further delineate the importance of family meals as well as incorporating fresh F/Vs in morning and evening meals. Evidence for the relationship between family meals and maternal F/V preparation at the within-day level underscores the benefits of having family meals and programs could provide techniques to incorporate family meals with food that is prepared at home. In addition, results show that prevention programs should challenge commonly held beliefs by mothers that children’s diets do not need to be as structured on weekends compared to weekdays (Hoffmann et al., 2018); they should discuss the importance of preparation of F/V on weekends, given that unhealthy food consumption on weekends can contribute to weight gain (Haines et al., 2003; Hart et al., 2011). With regard to personal characteristics, targeted preventions and strategies are needed to increase fresh F/V preparation and address structural barriers among particular groups such as working and Hispanic mothers and mothers of children of higher weights. It should be noted that children’s F/V consumption can come from other sources (e.g., other caregivers, themselves) and the current study does not discuss children’s diet quality. However, mothers’ F/V preparation is an important driver for children’s F/V intake, as seen in prior research (Do et al., 2020), making it critical to understand the predictors of mothers’ preparation of F/V.

4.1. Limitations

Strengths of the study include multiple waves of EMA in a diverse sample of mother-child dyads. Several limitations must be noted. Only one item was used to measure preparation of F/Vs as a strategy to limit the response burden of EMA. Thus, we cannot examine factors associated with preparation of fruit vs. vegetables separately. In addition, the specification of fresh F/Vs may have excluded situations in which mothers prepared frozen or canned F/Vs, which can still take time and effort, and provide nutritional value. Dietary intake and important psychological factors (e.g., motivation) were also not examined in the current study. In addition, mothers may have included situations where they served their child a piece of fruit without any preparation or cooking beforehand (e.g., banana); the current study was interested in specifically preparation given that these parenting behaviors involve some time and effort. Also, to reduce burden, the preparation item was only asked in a randomly-programmed 60% of prompts. Additionally, given the purpose of the larger MATCH study in examining dyadic relationships, mothers did not complete EMA recordings until 3:00 P.M. on weekdays due to child being at school. Thus, we may have missed detailed accounts of food preparation in the mornings on weekdays. Similarly, asking participants to report “Since you woke up this morning” for the weekday 3:00 P.M. prompt is a limitation. However, this made up only about 11% of EMA observations. There was also a potential for reactivity, such as preparing F/V as a result of the EMA prompts). However, reactivity is generally low with EMA procedures and the random prompts within preset intervals sought to prevent anticipatory effects (e.g., changing current behavior in anticipation of a survey prompt at a known time) (Shiffman, 2007; Munsch et al., 2009). There was also the possibility that participants were enrolled in health behavior interventions as the study did not include this in the exclusion criteria. Despite these limitations, this study furthered our knowledge of the personal and momentary, within-day characteristics associated with mothers’ preparation of fresh F/Vs.

5. Conclusions

The current study utilized EMA to elucidate the personal characteristics and the momentary, contextual factors that predict mothers’ preparation and cooking of fresh F/Vs for their children. Findings indicate at what moments mothers are likely to prepare and cook fresh F/Vs for their children. Study findings may inform future tailored family-based obesity prevention programs by distinguishing personal characteristics and daily factors that can be targeted.

Highlights.

  • Ecological momentary assessment examined mothers’ food preparation behaviors

  • There are inter- and intra-individual differences in maternal food preparation

  • Momentary, within-day factors are related to fruit and vegetable preparation

  • Personal characteristics are related to maternal food preparation

  • Family meal occurrence was associated with fresh fruit and vegetable preparation

  • Mothers are more likely to prepare fresh fruits and vegetables on weekdays

Acknowledgments

Role of Funding Sources

Funding for this study was provided by the National Institutes of Health/National Heart, Lung, and Blood Institute (grant number R01HL119255) and the American Cancer Society (118283-MRSGT-10-012-01-CPPB). Both sources had no role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication.

Footnotes

Declaration of Interest: None.

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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

Participants were included in the analyses if they had data from at least one wave with no missing data for the predictors of interest (N=186). Of the 202 mothers enrolled at baseline, a total of 27,667 EMA prompts were successfully delivered to 200 mothers across six waves. Mothers answered an average of 79.0% (range 7.4% to 100%) delivered EMA prompts, which resulted in a total of 21,861 completed EMA prompts across all six waves. Of these completed prompts, mothers indicated being with their child during 16,594 (75.9.%) prompts. The EMA protocol prompted the question about F/V preparation 60% of the time resulting in mothers answering the question regarding F/V preparation in 9,876 (59.5%) prompts. Missing EMA data on the predictors or outcome of interest, from 14 participants, were excluded from the analyses. Therefore, the final analytic sample included 186 mothers with a total of 5,558 EMA prompts. A total of 1,178 prompts (21.2%) among 175 mothers came from wave 1, 920 prompts (16.6%) among 137 mothers came from wave 2, 830 prompts (14.9%) among 134 mothers came from wave 3, 902 prompts (14.4%) among 132 mothers came from wave 4, 873 prompts (15.7%) among 138 mothers came from wave 5, and 955 prompts (17.2%) among 143 mothers came from wave 6.

On average, participants took 216 seconds (SD=137 seconds) to respond to an EMA prompt after thy were first signaled. Participants were more likely to comply with EMA prompts on weekend days compared to weekdays (B=0.65, SE=0.02, p<0.001). Mothers who did not identify as Hispanic/Latino were more likely to comply with prompts compared to mothers who identified as Hispanic/Latino (B=0.17, SE=0.02, p<0.01). Participants were more likely to comply with EMA prompts in the morning (B=0.16, SE=0.03, p<0.01) or afternoon (B=0.29, SE=0.03, p<0.01) compared to the evening.

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