# Associations of preschoolers' dietary patterns with eating behaviors and parental feeding practices at a 12-month follow-up of obesity treatment

Pernilla Sandvik, Sami Kuronen, Hannah Reijs Richards, Karin Eli, Anna Ek, Maria Somaraki, Paulina Nowicka

<figure><img src="image_1.png" /></figure>

## To cite this version:

Pernilla Sandvik, Sami Kuronen, Hannah Reijs Richards, Karin Eli, Anna Ek, et al.. Associations of preschoolers' dietary patterns with eating behaviors and parental feeding practices at a 12-month follow-up of obesity treatment. Appetite, 2022, 168, pp.105724. 10.1016/j.appet.2021.105724. hal-04332252

HAL Id: hal-04332252

https://hal.inrae.fr/hal-04332252

Submitted on 8 Dec 2023

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_3.png" /></figure>

# Associations of preschoolers' dietary patterns with eating behaviors and parental feeding practices at a 12-month follow-up of obesity treatment

Pernilla Sandvik<sup>a</sup>, Sami Kuronen<sup>a,1</sup>, Hannah Reijs Richards<sup>a,1</sup>, Karin Eli<sup>c,d</sup>, Anna Ek<sup>b</sup>, Maria Somaraki<sup>a</sup>, Paulina Nowicka<sup>a,b,*</sup>

## ARTICLE INFO

### Keywords:

- Family

- Food frequency questionnaire

- Food fussiness

- Lifestyle behavior checklist

## ABSTRACT

Although dietary patterns are key to the management of childhood obesity, they are rarely assessed and thus poorly understood. This study examines preschoolers' dietary patterns and correlates 12 months after the start of obesity treatment (n = 99, mean age 5.2 years, 52% girls). A food frequency questionnaire (FFQ), the Child Eating Behavior Questionnaire (CEBQ), Child Feeding Questionnaire (CFQ) and Lifestyle Behavior Checklist (LBC) were answered by parents to assess children's food intake, eating behaviors, parental feeding practices, and obesity-related behaviors, respectively. Principal component analysis identified dietary patterns based on FFQ data. Through multiple linear regressions we examined correlations between a healthy (HD) and a less healthy (LHD) dietary pattern and mean scores of the CEBQ, CFQ, LBC scales as well as BMI z-scores. The reported intake of items in the LHD decreased after treatment while no differences were found for the HD. Children's eating behaviors, in particular food fussiness, showed consistent associations with diet (b = -0.39, 95% CI -0.63, -0.14 for HD and b = 0.41, 95% CI 0.15, 0.66 for LHD). Feeding practices and obesity-related behaviours were weakly associated with the dietary patterns (HD and Monitoring: b = 0.36, 95% CI 0.09, 0.62; LHD and Screen time b = 0.08, 95% CI 0.01, 0.15). Among the measured variables, eating behaviors had the largest impact on children's dietary patterns. The LHD was associated with a higher BMI z-score but no associations were found between changes in LHD intake and changes in BMI z-scores. Our findings suggest that decreasing food fussiness in children with obesity is key to positive dietary changes. Assessment of children's eating behaviors can help tailor dietary advice and provide support for families of children with obesity.

## 1. Background

Insights into dietary patterns are a vital part of effective interventions for childhood obesity (Ells et al., 2018; Duncanson et al., 2021). The recommended dietary patterns are high in fruit and vegetables and low in energy-dense, nutrient-poor (EDNP) foods and sugar-sweetened beverages (Spear et al., 2007). EDNP foods include fast foods such as pizza and hamburgers, and different types of snack foods such as potato chips, sweet pastries, ice cream, sweets, and chocolate. EDNP foods are associated with a higher intake of energy, sugar, total fat

and saturated fat, as well as with a higher intake of sugar-sweetened beverages (Powell & Nguyen, 2013). A high intake of sugar-sweetened beverages increases obesity risk in both children and adults (Malik, Pan, Willett, & Hu, 2013), possibly due to their being high in calories but not satiating (Mattes, 2006). As opposed to EDNP foods, intake of fruit and vegetables has numerous positive health effects, such as supporting a healthy body weight (Slavin, 2005) and reducing the risk of developing the metabolic syndrome (Tian, Su, Wang, Duan, & Jiang, 2018), cardiovascular disease, cancer and all-cause mortality (Aune et al., 2017).

<footnote><sup>a</sup> Department of Food Studies, Nutrition, and Dietetics, Uppsala University, Uppsala, Sweden</footnote>

<footnote><sup>b</sup> Division of Pediatrics, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden</footnote>

<footnote><sup>c</sup> Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, UK</footnote>

<footnote><sup>d</sup> School of Anthropology and Museum Ethnography, University of Oxford, Oxford, UK</footnote>

<footnote>* Corresponding author. Department of Food Studies, Nutrition and Dietetics, Uppsala University, Box 560, SE-751 22, Uppsala, Sweden.</footnote>

<footnote>E-mail addresses: pernilla.sandvik@ikv.uu.se (P. Sandvik), sami.kuronen@hotmail.com (S. Kuronen), hannahreijsrichards@gmail.com (H. Reijs Richards), Karin.Eli@warwick.ac.uk, karin.eli@anthro.ox.ac.uk (K. Eli), anna.ek@ki.se (A. Ek), mariasomaraki90@gmail.com (M. Somaraki), paulina.nowicka@ikv.uu.se, paulina.nowicka@ki.se (P. Nowicka).</footnote>

<footnote n="1">¹ Contributed equally to the manuscript.</footnote>
This study addresses a crucial gap in the field of childhood obesity treatment research: while studies have focused on weight outcomes, children's food intake has largely remained unexplored as most treatment studies do not report on food intake (Burrows et al., 2012; Dun-canson et al., 2021). This is especially important in the preschool age, a developmental period that might be particularly challenging for parents due to high prevalence of food fussiness (Cardona Cano et al., 2015), and for which few treatment options exist. Further, obesity is a chronic condition that needs continuous management, and, to our knowledge, no previous study has explored associations between weight outcomes, behavioral characteristics, and healthier or less healthy food patterns among preschoolers who received treatment for obesity. Insight into factors associated with the food intake of children who are managing their obesity can aid in the tailoring of future interventions, particularly with regards to long-term management.

Eating behaviors affect how much and how often a child eats (Syrad, Johnson, Wardle, & Llewellyn, 2016) and can also influence what children eat. Some eating behaviors in children are linked to a less healthy dietary pattern and/or a higher weight status. These include a high enjoyment of food (Quah et al., 2019; Spahić & Pranjić, 2019; Spence, Carson, Casey, & Boule, 2011; Viana, Sinde, & Saxton, 2008; Webber, Hill, Saxton, Van Jaarsveld, & Wardle, 2009), eating more in response to emotions (Jalo et al., 2019), a low satiety response and a high interest in food (Spahić & Pranjić, 2019; Spence et al., 2011; Viana et al., 2008; Webber et al., 2009). The most widely used measure to study children's eating behaviors (de Lauzon-Guillain et al., 2012) is the Child Eating Behavior Questionnaire (CEBQ) (Wardle, Guthrie, Sanderson, & Rapoport, 2001). The instrument consists of statements that describe the child's appetite, clustered into eight subscales. The subscale Enjoyment of food has been associated with fruit and vegetable liking, while the subscales Slowness in Eating, Food Fussiness and Satiety Responsiveness have been inversely associated with fruit and vegetable liking (Fildes et al., 2015). Food Fussiness has also been associated with a low intake of vegetables (Hayes et al., 2016; Sandvik et al., 2019), whilst children who are highly responsive to food have shown a higher preference for EDNP foods (Fildes et al., 2015).

Parental feeding practices are strategies used during mealtime to affect the child's eating habits, often as a response to child eating behaviors (Ek et al., 2016). These practices are modifiable and can alter children's dietary habits (Holland et al., 2014). The practices are frequently measured using the Child Feeding Questionnaire (CFQ), which includes the subscales Restriction (limiting the availability of certain foods), Monitoring (overseeing the child's food intake) and Pressure to Eat (encouraging the child to eat more) (Birch et al., 2001). How feeding practices affect children's eating patterns and weight status is not completely clear. Monitoring has been negatively associated with non-core food intake and sweetened beverage intake in young children with overweight (Haszard, Skidmore, Williams, & Taylor, 2015). Studies have found that higher levels of parental restriction of certain foods are associated with higher child weight status, while pressuring the child to eat is not associated with higher child weight status (Birch, 2001; Nowicka, Sorjonen, Pietrobelli, Flodmark, & Faith, 2014). These relationships are likely explained by parents' responses to a child's eating behavior and/or concern for the child's weight status (Ek et al., 2016; Hurley, Pallan, Lancashire, Adab & WAVES Study; Investigators, 2018; Webber, Cooke, Hill, & Wardle, 2010), rather than indicating a causal relationship between restriction/pressure to eat and a child's weight.

Parents influence young children's behaviors and the most recent Cochrane review concludes that childhood obesity interventions that provide specific support regarding parenting practices result in lowering child weight status (body mass index (BMI) z-scores) (Colquitt et al., 2016). Targeting parents in treatment was also supported in an umbrella review, which included 14 systematic reviews and showed that interventions where only parents were involved were as effective as interventions involving parents and children (Chai et al., 2019). Thus, it is important to understand how parents perceive their children's

weight-related behaviors, such as overeating and low engagement in physical activity. The Lifestyle Behavior Checklist (LBC) (West & Sanders, 2009) was developed to evaluate what problematic behaviors parents perceive in their children and how confident they are in handling these problems. Compared to parents of children with a healthy weight, parents of children with overweight and obesity report more food-related problems, such as the child eating too much and too fast, and a lower confidence in handling these perceived problems (Ek, Sorjonen, Nyman, Marcus, & Nowicka, 2015; Morawska & West, 2013; West & Sanders, 2009). However, it is unknown how these perceptions are associated with children's food patterns.

The aim of this study is to explore dietary patterns and correlates of healthy and less healthy dietary patterns in preschool-aged children, 12 months after the start of obesity treatment. Specifically, we explore associations between children's dietary patterns and weight status, child eating behaviors, parental feeding practices, parents' perceptions of obesity-related problem behaviors and parents' confidence in handling these behaviors.

## 2. Method

This is an exploratory study based on secondary data from the More and Less study (ML) that took place from 2011 to 2017 at Karolinska Institutet, Stockholm, Sweden (Ek, Chamberlain, et al., 2015).

### 2.1. Design of the More and Less study

The ML was a randomized controlled trial which aimed to evaluate two obesity treatments for preschool-age children in Stockholm County, Sweden (Ek, Chamberlain, et al., 2015). In the present paper, we assess associations for the total study population. We do not compare treatment groups because no differences were observed across treatments in changes in reported intake of FFQ items (Somaraki et al., 2020).

In the ML, a parent-only support program focusing on parenting skills was delivered by a trained facilitator in a group setting. This program was compared to standard treatment focusing on lifestyle behavior advice, delivered in individual meetings between a healthcare professional and both parent and child. The results for the primary outcome (child body mass index (BMI)-z score) have been published previously (Ek et al., 2019). The participants (n = 174) were mainly recruited through child health care centers between March 2012 to March 2016. The included children were 4–6 years old and had obesity according to international standards (Cole, Bellizzi, Flegal, & Dietz, 2000; Cole & Lobstein, 2012). Children were excluded if they had a chronic disease or developmental problems that could affect weight and height and if parents were not able to communicate in Swedish. The ML study was approved by the Regional Ethical Board in Stockholm (ID: 2011/1329-31/4) on November 16, 2011. Written informed consent was provided by both parents.

Children and their parents were randomized to either the parent program or standard treatment. The parent program was delivered weekly for 10 weeks by registered dietitians in a group setting. Each of the sessions had a main theme which featured an evidence-based parenting practice and discussions about a lifestyle component such as diet or physical activity. Standard treatment was provided in an outpatient pediatric unit according to the action program for overweight and obesity in Stockholm County (The Health Care Administration, 2010). Families had at least four visits scheduled with a pediatrician and/or pediatric nurse, focusing on lifestyle changes. A treatment plan was formed, with treatment frequency and the involvement of different clinicians adjusted according to the individual needs of the child.

### 2.2. Measures

This study used data collected in the ML, from an FFQ, the CEBQ (Ek et al., 2016; Wardle et al., 2001), the CFQ (Birch et al., 2001; Nowicka
et al., 2014) and the LBC (Ek, Chamberlain, et al., 2015; West & Sanders, 2009). The analysis used baseline FFQ data, BMI-z scores and demographic information and data collected at the 12-month follow-up. Brief descriptions of the behavior-related questionnaires are presented in Table 1.

### 2.2.1. The food frequency questionnaire

A 10-item FFQ (see Appendix 1) was answered at baseline and at 12 months and was used to assess how often the children consumed different categories of foods: “fresh fruits”, “vegetables”, “pizza/ hamburger”, “fish”, “ice cream”, “cakes/cookies/buns”, “soft drinks”, “juice”, “sweets/chocolate”, “chips/snacks”. The FFQ had 13 possible responses ranging from “once a month or less” to “four times per day or more”. FFQs tend to have a higher reporting quality when measuring diet intake in children compared to other tools such as food diaries and 24-h recalls, possibly due to their structure and simplicity (Burrows et al., 2012) as well as a low respondent burden (Magarey et al., 2011). The Swedish National Food Agency has used a more comprehensive FFQ when examining the dietary intake of 4-, 8-, and 11-year-olds (Becker &

<table><caption>**Table 1**
Behavior-related questionnaires used in the study.</caption><thead><tr><th>Name of instrument</th><th>Domains measured</th><th>Number of items</th><th>Brief description of measures</th></tr></thead><tbody><tr><td rowspan="5">Child Eating Behavior Questionnaire (CEBQ)</td><td><strong>Food approach</strong></td><td></td><td></td></tr><tr><td>Food responsiveness</td><td>5</td><td>The child's general appetite and desire to eat</td></tr><tr><td>Emotional overeating</td><td>4</td><td>If the child eats more in response to emotions</td></tr><tr><td>Enjoyment of food</td><td>4</td><td>The child's interest in and enjoyment of food</td></tr><tr><td>Desire to drink</td><td>3</td><td>The child's desire to drink</td></tr><tr><td rowspan="5">Child Feeding Questionnaire (CFQ)</td><td><strong>Food avoidance</strong></td><td></td><td></td></tr><tr><td>Satiety responsiveness</td><td>4</td><td>If the child gets full easily or not</td></tr><tr><td>Slowness in eating</td><td>4</td><td>The child's eating pace</td></tr><tr><td>Emotional undereating</td><td>4</td><td>If the child eats less in response to emotions</td></tr><tr><td>Food fussiness</td><td>6</td><td>The child eats and tastes a limited variety of foods</td></tr><tr><td rowspan="3">Lifestyle Behavior</td><td>Restriction</td><td>6</td><td>The extent to which parents restrict the child's access to different foods</td></tr><tr><td>Pressure to eat</td><td>4</td><td>Parents' tendency to pressure the child to eat more food</td></tr><tr><td>Monitoring</td><td>3</td><td>The extent to which parents oversee the child's intake of different foods</td></tr><tr><td rowspan="5">Checklist (LBC)</td><td>Overeating</td><td>9</td><td>If the child eats large amounts or often asks for or takes food</td></tr><tr><td>Physical activity</td><td>3</td><td>If the child complains about and refuses physical activity</td></tr><tr><td>Emotional correlates of being overweight</td><td>3</td><td>If the child complains about his/her weight and appearance</td></tr><tr><td>Misbehavior in relation to food</td><td>2</td><td>If the child throws tantrums about food</td></tr><tr><td>Screen time</td><td>2</td><td>If the child has sedentary interests</td></tr><tr><td></td><td>Confidence scale</td><td>19</td><td>Parents' confidence in handling the problematic behaviors</td></tr></tbody></table>

Enghardt, 2004). An FFQ similar to the one used in this study was validated in an intervention trial focusing on the prevention of childhood obesity in Swedish health care centers (Döring et al., 2014). Changes in reported intake of the individual FFQ items in the RCT have previously been studied (Somaraki et al., 2020). The focus of the present study is exploring food patterns in the whole study sample.

### 2.2.2. The Child Eating Behavior Questionnaire

The 35-item CEBQ was used to evaluate children's eating behaviors. The items cluster into eight factors: Food responsiveness, Emotional overeating, Enjoyment of food, Desire to drink, Satiety responsiveness, Slowness in eating, Emotional undereating and Food fussiness. The first four represent the dimension Food approach and the other four represent Food avoidance. The questionnaire was filled out by one parent in each family. Each behavior was rated on a 1–5 Likert scale from “never” to “always”. The CEBQ has been validated in several studies (Sleddens, Kremers, & Thijs, 2008; Spence et al., 2011; Wardle et al., 2001) including in Swedish settings (Ek et al., 2016; Svensson, Lundborg, Cao, Nowicka, Marcus & Sobko, 2011). One item regarding snacking was excluded from the analysis as it loaded weakly on the Satiety responsiveness subscale (Ek et al., 2016).

### 2.2.3. The Child Feeding Questionnaire

The CFQ was designed for parents of 2 to 11-year-olds (Birch et al., 2001) and has been translated and validated in a Swedish population of almost 900 parents of 4-year-olds (Nowicka et al., 2014). The CFQ was used to assess mothers' and fathers' attitudes and feeding practices using the subscales Restriction, Pressure to eat and Monitoring. The subscales consist of 15 items in total and the parents rated each item on a Likert scale from 1 (never) to 5 (always). In this analysis two items concerning using food as a reward were excluded as previous research has shown that Swedish parents score low on these items due to social desirability (Nowicka et al., 2014).

### 2.2.4. The Lifestyle Behavior Checklist

The 25-item LBC, developed in Australia, is based on interviews with experts on childhood obesity and feedback from participants in a parenting program (West, Morawska, & Joughin, 2010; West & Sanders, 2009). The instrument has been translated and validated, with a few modifications, in a study with a Swedish population of close to 500 parents of preschoolers (Ek, Chamberlain, et al., 2015). The LBC was used to assess parents' perceptions of their child's obesity-related problem behaviors (the Problem scale). Both parents reported the degree to which their child's behaviors were problematic on a 7-point problem scale, ranging from “not at all” to “very much”. The items were divided into the subscales Overeating, Physical activity, Emotional correlates, Misbehavior in relation to food and Screen time. The parents were also asked to rate their confidence in dealing with each behavior from 1 (“certain I can't do it”) to 10 (“certain I can do it”) (the Confidence scale). 19 items were included from the analysis. Excluded items were less relevant to preschoolers or fitted poorly into the model, possibly due to ambiguous meaning (Ek, Chamberlain, et al., 2015).

### 2.2.5. Weight status at baseline and change after 12 months

The child's weight and height were measured three times by trained staff at baseline and 12 months. The mean of the three measurements was used to calculate the child's BMI. BMI was then used to identify the child's BMI z-score as derived from age- and sex-specific reference data (Cole et al., 2012). A mean change in BMI z-score variable was computed by subtracting the baseline value from the 12-month value.

### 2.2.6. Covariates

At baseline, parents completed sociodemographic questionnaires where they reported the child's sex and age, and the parents' ages, self-reported height and weight, education, and whether or not they had foreign background (defined as having been born outside Sweden, or
having parents born outside Sweden).

## 2.3. Statistical analysis

Baseline descriptive variables were calculated as mean and standard deviations (SD) for continuous variables and numbers and percentages for categorical variables. To assess differences between ML participants who answered the FFQ at the 12-month follow-up and those who did not, descriptive data were analyzed using two-sided independent *t*-tests (continuous variables) and Chi-squared tests (categorical variables).

To explore dietary patterns at 12 months, Principal Component Analyses (PCA) was performed using Varimax rotation with Kaiser Normalization. PCA is a widely used exploratory method in epidemiology to derive dietary patterns from habitual diet (Lioret et al., 2020; Northstone & Emmett, 2008). Two components with Eigenvalues >1 were identified (the detailed description of the process in Appendix 2).

Based on current dietary guidelines, one component was called “Healthy dietary pattern” (HD) and the other was called “Less healthy dietary pattern” (LHD). The dietary patterns are further described in the result section. Each child was provided standardized scores pertaining to each of the two patterns, based on their reported consumption frequency of the different FFQ items. Pearson correlation coefficient was used to explore the association between these two scores. In addition, frequency equivalents (monthly consumption) for the items in the FFQ and the total intake of items characterizing the HD and the LHD were calculated. Paired samples *t*-test were used to study differences between baseline and 12 months.

Multiple linear regression was used to explore associations between children’s HD and LHD scores (dependent variables) and the mean overall scores of the subscales of the CEBQ, the CFQ, and the LBC. The mean scores from the CEBQ and the CFQ and the summary score from the LBC were calculated and used in all models in accordance with earlier findings (Ek, Chamberlain, et al., 2015, Ek et al., 2016; Nowicka et al., 2014). For each analysis, only participants who answered all items in the subscale were included. All models were adjusted for child’s sex, age, and BMI z-score at baseline, as well as parent’s age, BMI, education level and foreign background. Education level was defined as either having a university degree or not. Foreign background was defined as both the participant’s parents having been born abroad, regardless of the participant’s own birthplace. Because only one parent per family completed the CEBQ, with the great majority of questionnaires completed by mothers, the mothers’ background variables were used in the adjusted models for the CEBQ. Unstandardized regression coefficients (b) and confidence intervals (CI) of 95% were calculated.

To study the dietary patterns in relation to weight status in the context of obesity treatment, linear regressions were conducted. BMI z-scores were specified as the dependent variable. In two separate models, HD and LHD at 12 months were used to predict BMI z-scores at 12 months. Changes in mean total frequency intake of the items in the two food patterns were used to predict changes in BMI z-scores from baseline to 12 months. These models were adjusted for child’s sex and age.

The level of significance was set to p < 0.05. All statistical tests were performed in SPSS version 25.

## 3. Results

Of the 174 families enrolled in the ML study, 99 completed the FFQ 12 months after baseline and were included in the analysis (see Table 2). A greater percentage of the parents who did not complete the FFQ at 12 months was of foreign background compared to the study sample (mothers: 76.6% vs 54.1%; fathers: 74.4% vs 50.4%).

<caption>**Table 2**</caption>

Sample descriptives at baseline for the participants with and without a completed FFQ at the 12-month follow-up.

<table><thead><tr><th rowspan="2">Variables</th><th>Completed FFQ at 12 months (n = 99)<sup>a</sup></th><th>Not completed FFQ at 12 months (n = 75)<sup>a</sup></th></tr><tr><th colspan="2">n (%) or mean (SD)</th></tr></thead><tbody><tr><td><strong>Children</strong></td><td></td><td></td></tr><tr><td>Girls</td><td>51 (51.5)</td><td>47 (62.7)</td></tr><tr><td>Age in years</td><td>5.2 (0.8)</td><td>5.3 (0.8)</td></tr><tr><td>BMI z-score</td><td>2.9 (0.6)</td><td>3.0 (0.6)</td></tr><tr><td><strong>Mother</strong></td><td></td><td></td></tr><tr><td>Age in years</td><td>36.7 (5.4)</td><td>36.4 (5.9)</td></tr><tr><td>BMI kg/m<sup>2</sup></td><td>28.3 (6.1)</td><td>27.8 (4.7)</td></tr><tr><td>University degree</td><td>44 (45.4)</td><td>14 (30.4)</td></tr><tr><td>Foreign background*</td><td>53 (54.1)</td><td>36 (76.6)</td></tr><tr><td><strong>Father</strong></td><td></td><td></td></tr><tr><td>Age in years</td><td>39.3 (6.9)</td><td>41.2 (7.7)</td></tr><tr><td>BMI kg/m<sup>2</sup></td><td>29.5 (4.4)</td><td>29.2 (4.6)</td></tr><tr><td>University degree</td><td>36 (40.0)</td><td>13 (34.2)</td></tr><tr><td>Foreign background*</td><td>46 (50.5)</td><td>29 (74.4)</td></tr></tbody></table>

Abbreviations: FFQ, Food Frequency Questionnaire; SD, standard deviation; BMI, body mass index.

<sup>a</sup> For parents’ variables, n vary due to missing values.

<sup>*</sup> denote the presence of a significant difference between the groups, p < 0.05.

Mean BMI-z scores of the children included in the analysis were at baseline 2.9 (SD 0.6), and at the 12-month follow-up 2.7 (SD 0.8) (p < 0.001). At the 12-month follow-up, two dietary patterns were identified. The HD explained 17% of the variance and was formed through correlations between “fresh fruit”, “vegetables” and “fish” (Cronbach’s alpha 0.56). The LHD explained 31% of the variance and was formed through correlations between “pizza/hamburger”, “ice cream”, “cakes/cookies/buns”, “soft drinks”, “juice”, “sweets/chocolate” and “chips/snacks” (Cronbach’s alpha 0.76). The Pearson correlation coefficient showed no significant association between the two patterns’ scores (r=<0.001, p = 1.000).

The children’s mean (SD) food frequency intake per month as reported at baseline and after 12 months is presented in Table 3. The

<caption>**Table 3**</caption>

Frequency of food intake per month as reported at baseline and at 12 months from baseline.

<table><thead><tr><th>Food items (FFQ)</th><th>N<sup>a</sup></th><th>Baseline Mean (sd)</th><th>12 months Mean (sd)</th><th>p-value<sup>b</sup></th></tr></thead><tbody><tr><td><strong>Healthy dietary pattern (HD)</strong></td><td>98</td><td>104 (50)</td><td>104 (44)</td><td>0.920</td></tr><tr><td>Fresh fruit</td><td>98</td><td>49 (27)</td><td>48 (25)</td><td>0.546</td></tr><tr><td>Vegetables</td><td>98</td><td>48 (28)</td><td>49 (25)</td><td>0.914</td></tr><tr><td>Fish</td><td>98</td><td>7 (6)</td><td>8 (8)</td><td>0.220</td></tr><tr><td><strong>Less healthy dietary pattern (LHD)</strong></td><td>94</td><td>31 (17)</td><td>24 (12)</td><td>&lt;0.001</td></tr><tr><td>Pizza/hamburgers</td><td>97</td><td>2 (1)</td><td>2 (1)</td><td>0.302</td></tr><tr><td>Ice cream</td><td>99</td><td>4 (4)</td><td>3 (2)</td><td>0.017</td></tr><tr><td>Cakes/cookies/buns</td><td>98</td><td>5 (4)</td><td>4 (3)</td><td>0.016</td></tr><tr><td>Soft drinks</td><td>96</td><td>5 (5)</td><td>4 (3)</td><td>0.004</td></tr><tr><td>Juice</td><td>96</td><td>8 (9)</td><td>5 (7)</td><td>0.005</td></tr><tr><td>Sweets/chocolate</td><td>97</td><td>5 (4)</td><td>4 (2)</td><td>0.010</td></tr><tr><td>Chips/snacks</td><td>97</td><td>3 (2)</td><td>3 (2)</td><td>0.156</td></tr></tbody></table>

<sup>a</sup>Including children with FFQ data at both baseline and 12 months.

<sup>b</sup>Paired samples *t*-test.

p < 0.05 denote the presence of a significant difference between baseline and 12 months.
<table><caption>**Table 4**
Unstandardized regression effects for associations between dietary patterns (HD and LHD) and behavior related questionnaires 12 months after an obesity intervention.</caption><thead><tr><th rowspan="2">Questionnaire/subscales</th><th rowspan="2">n</th><th colspan="2">Healthy dietary pattern (HD) B (CI 95%)</th><th colspan="2">Less healthy dietary pattern (LHD) B (CI 95%)</th></tr><tr><th>unadjusted</th><th>adjusted<sup>a</sup></th><th>Unadjusted</th><th>adjusted<sup>a</sup></th></tr></thead><tbody><tr><td>Child eating behavior Questionnaire</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Food responsiveness</td><td>94</td><td>0.19 (-0.01, 0.39)</td><td>0.17 (-0.04, 0.39)</td><td>-0.01 (-0.23, 0.22)</td><td>0.002 (-0.23, 0.23)</td></tr><tr><td>Emotional overeating</td><td>92</td><td>-0.08 (-0.30, 0.14)</td><td>-0.09 (-0.32, 0.13)</td><td>0.11 (-0.13, 0.35)</td><td>0.03 (-0.20, 0.27)</td></tr><tr><td>Enjoyment of food</td><td>93</td><td><strong>0.49 (0.24, 0.74**)</strong></td><td><strong>0.54 (0.26, 0.81**)</strong></td><td>-0.13 (-0.43, 0.17)</td><td>-0.08 (-0.39, 0.23)</td></tr><tr><td>Desire to drink</td><td>94</td><td>-0.06 (-0.27, 0.15)</td><td>-0.08 (-0.30, 0.13)</td><td><strong>0.28 (0.05, 0.51*)</strong></td><td><strong>0.23 (0.003, 0.45*)</strong></td></tr><tr><td>Satiety responsiveness</td><td>92</td><td><strong>-0.43 (-0.77, -0.09*)</strong></td><td><strong>-0.47 (-0.85, -0.09*)</strong></td><td>0.28 (-0.11, 0.67)</td><td>0.31 (-0.09, 0.71)</td></tr><tr><td>Slowness in eating</td><td>93</td><td>-0.23 (-0.48, 0.02)</td><td>-0.19 (-0.47, 0.09)</td><td>0.12 (-0.16, 0.40)</td><td>0.19 (-0.10, 0.47)</td></tr><tr><td>Emotional undereating</td><td>93</td><td>-0.17 (-0.40, 0.06)</td><td>-0.13 (-0.37, 0.11)</td><td>0.14 (-0.13, 0.40)</td><td>-0.09 (-0.16, 0.34)</td></tr><tr><td>Food fussiness</td><td>93</td><td><strong>-0.41 (-0.64, -0.18**)</strong></td><td><strong>-0.39 (-0.63, -0.14*)</strong></td><td><strong>0.35 (0.09, 0.61*)</strong></td><td><strong>0.41 (0.15, 0.66*)</strong></td></tr><tr><td>Child feeding questionnaire (mothers)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Restriction</td><td>87</td><td>0.10 (-0.17, 0.37)</td><td>0.15 (-0.11, 0.41)</td><td>0.01 (-0.29, 0.30)</td><td>-0.01 (-0.28, 0.27)</td></tr><tr><td>Pressure to eat</td><td>87</td><td>-0.25 (-0.52, 0.02)</td><td>-0.13 (-0.42, 0.16)</td><td>0.21 (-0.08, 0.50)</td><td>0.18 (-0.12, 0.47)</td></tr><tr><td>Monitoring</td><td>89</td><td><strong>0.34 (0.07, 0.62*)</strong></td><td><strong>0.36 (0.09, 0.62*)</strong></td><td>0.06 (-0.24, 0.37)</td><td>0.13 (-0.16, 0.41)</td></tr><tr><td>Child feeding questionnaire (fathers)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Restriction</td><td>77</td><td>0.11 (-0.18, 0.41)</td><td>0.21 (-0.11, 0.53)</td><td>-0.10 (-0.37, 0.16)</td><td>-0.13 (-0.42, 0.16)</td></tr><tr><td>Pressure to eat</td><td>77</td><td>-0.16 (-0.45, 0.13)</td><td>-0.14 (-0.46, 0.19)</td><td>0.19 (-0.07, 0.45)</td><td>0.17 (-0.11, 0.45)</td></tr><tr><td>Monitoring</td><td>76</td><td>0.12 (-0.21, 0.45)</td><td>0.04 (-0.30, 0.38)</td><td>-0.01 (-0.30, 0.28)</td><td>0.002 (-0.29, 0.30)</td></tr><tr><td>Lifestyle behavior checklist (mothers)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Overeating</td><td>89</td><td>0.01 (-0.01, 0.03)</td><td>0.003 (-0.02, 0.02)</td><td>0.01 (-0.01, 0.03)</td><td>0.01 (-0.01, 0.03)</td></tr><tr><td>Physical activity</td><td>91</td><td>0.03 (-0.01, 0.07)</td><td>0.04 (-0.001, 0.08)</td><td>0.03 (-0.01, 0.07)</td><td>0.02 (-0.02, 0.06)</td></tr><tr><td>Emotional correlates of being overweight</td><td>91</td><td>0.02 (-0.05, 0.08)</td><td>0.03 (-0.04, 0.01)</td><td>0.03 (-0.04, 0.10)</td><td>0.001 (-0.07, 0.07)</td></tr><tr><td>Misbehavior in relation to food</td><td>90</td><td>-0.06 (-0.13, 0.01)</td><td>-0.04 (-0.11, 0.03)</td><td>0.05 (-0.02, 0.13)</td><td>0.03 (-0.04, 0.10)</td></tr><tr><td>Screen time</td><td>91</td><td><strong>-0.08 (-0.14, -0.01*)</strong></td><td>-0.07 (-0.14, 0.005)</td><td>0.06 (-0.01, 0.13)</td><td><strong>0.08 (0.01, 0.15*)</strong></td></tr><tr><td>Confidence scale</td><td>87</td><td>0.003 (-0.003, 0.01)</td><td>0.003 (-0.003, 0.01)</td><td><strong>-0.007 (-0.013, 0.000*)</strong></td><td>-0.01 (-0.01, 0.001)</td></tr><tr><td>Lifestyle behavior checklist (fathers)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Overeating</td><td>77</td><td>&lt;0.000 (-0.02, 0.03)</td><td>-0.01 (-0.03, 0.02)</td><td>0.01 (-0.01, 0.03)</td><td>0.004 (-0.02, 0.03)</td></tr><tr><td>Physical activity</td><td>76</td><td>-0.02 (-0.09, 0.05)</td><td>-0.02 (-0.09, 0.05)</td><td>0.05 (-0.01, 0.11)</td><td>0.04 (-0.02, 0.15)</td></tr><tr><td>Emotional correlates of being overweight</td><td>77</td><td>0.03 (-0.06, 0.11)</td><td>0.01 (-0.10, 0.09)</td><td>0.03 (-0.05, 0.10)</td><td>0.01 (-0.09, 0.08)</td></tr><tr><td>Misbehavior in relation to food</td><td>77</td><td>-0.04 (-0.14, 0.06)</td><td>-0.05 (-0.15, 0.05)</td><td>0.07 (-0.02, 0.15)</td><td>0.04 (-0.05, 0.14)</td></tr><tr><td>Screen time</td><td>77</td><td>-0.03 (-0.11, 0.05)</td><td>-0.02 (-0.10, 0.07)</td><td>0.05 (-0.02, 0.12)</td><td>0.02 (-0.05, 0.10)</td></tr><tr><td>Confidence scale</td><td>72</td><td>-0.003 (-0.01, 0.004)</td><td>-0.002 (-0.01, 0.01)</td><td>-0.002 (-0.01, 0.004)</td><td>-0.003 (-0.01, 0.004)</td></tr></tbody></table>

aggregated food frequency intake for the items representing the 12-month HD and LHD is also presented. No changes were found for frequency intake of the HD items from baseline to follow-up. Reported frequency intake of LHD items, however, had significantly decreased, mainly due to a significant reduction in the consumption frequency of all LHD items except “pizza/hamburgers” and “chips/snacks”.

The results from the multiple linear regressions for associations between the dietary patterns at 12 months and questionnaire subscales are presented in Table 4.

For the CEBQ subscales, a significant positive association was found between HD and Enjoyment of food (p < 0.001/<0.001 in the unadjusted and the adjusted model) and a significant negative association was found between HD and Satiety responsiveness (p = 0.013/0.015). For Food fussiness, there was a significant negative association with HD (p < 0.001/<0.001) and a positive association with LHD. A significant, positive association was found between LHD and Desire to drink (p = 0.017/0.047). For the CFQ, one significant association was found: a higher degree of CFQ Monitoring among mothers was associated with HD (p = 0.013/0.010). For the LBC, there were two significant associations with problematic Screen time, as reported by mothers: a negative association with HD (only in the unadjusted model, p = 0.017) and a positive association with LHD (only in the adjusted model, p = 0.037). LHD was inversely associated with mothers' Confidence in the unadjusted model (p = 0.048); however, the significance disappeared in the adjusted models.

The LHD showed a positive association with BMI-z scores at 12 months (b = 0.20, 95% CI 0.05 to 0.35, p = 0.01). The association remained significant when adjusting for child's sex and age (b = 0.21, 95% CI 0.06–0.36, p = 0.007). No associations were found between the HD and BMI z-scores at 12 months. No associations were found between changes in total frequency intake of the food items included in the patterns and changes in BMI-z scores.

## 4. Discussion

This study is among the first to examine correlations between pre-schoolers' dietary patterns following obesity treatment and their eating behaviors and weight status, as well as their parents' feeding practices and perceptions of children's problematic obesity-related behaviors. In this clinical sample, we found that it was mainly children's eating behaviors, measured by the CEBQ, that showed associations with the two parent-reported PCA-derived dietary patterns: a healthy dietary pattern (HD) and a less healthy dietary pattern (LHD). Compared to children perceived as less fussy, children perceived as fussy eaters had less healthy dietary patterns, with both a lower average score on the HD and a greater average score on the LHD. Other findings showed that enjoyment of food was positively associated with the HD, whereas a higher satiety responsiveness was negatively associated with the HD. Additionally, greater desire to drink was positively associated with the LHD. Among parental feeding practices, measured by the CFQ, only mothers'

<footnote><sup>a</sup>Adjusted for child's sex, age, baseline BMI z-score, parents' age, BMI, education, foreign background. *p < 0.05, **p < 0.001. Significant results are in bold.</footnote>
monitoring was positively associated with the HD. Problematic screen time behavior was the only obesity-related behavior measured by the LBC that was associated with the LHD. All associations were largely unaffected when adjusted for background factors.

Although the reported intake of foods relevant to obesity treatment was within recommended levels in all groups already at baseline, we did see a significant reduction in LHD items. Juice was the FFQ item that had decreased the most, from a mean intake of 8 times per month to 5 times per month. A previous study has found that mothers are ambivalent about whether juice may be considered part of a healthy diet (Eli, Hörnell, Malek, & Nowicka, 2017). It is possible that parents gained insights about juice through the treatment program, thereby reducing their children's consumption of juice. Changes in the total intake of items belonging to either HD or LHD showed no association with changes in weight status. This is consistent with Somaraki et al.'s (2020) finding that changes in intake of individual FFQ items did not mediate child weight loss in the ML study. Nonetheless, the reported intake of LHD foods showed a positive association with a higher BMI-z score.

The subscales of the CEBQ showed the strongest and most coherent associations with dietary patterns. Food fussiness was the only child eating behavior associated with both HD and LHD but in opposite directions, indicating that children perceived as fussy eaters were more likely to have obesity-related dietary patterns. Notably, a previous paper, focusing on picky eating, used baseline data from this cohort and did not find significant associations between food fussiness and individual EDNP food items or sweet beverages (Sandvik et al., 2019). Our findings might reflect changes from pre-to post treatment but may also indicate the importance of studying dietary patterns instead of individual food items when trying to identify links between children's food intake and their eating behaviors. Sandvik et al. (2019) also found that the inverse association between food fussiness and vegetable intake was present at baseline and was not affected by treatment. Only a few other studies have examined food intake and food fussiness in children with overweight and obesity. A study with 4-8-year-olds with overweight found that Food fussiness was associated with a lower fruit and vegetable intake and a higher consumption of sweetened beverages, but not with non-core foods (Haszard et al., 2015). In a non-clinical population, food fussiness was associated with a lower intake of dietary fiber from vegetables (Taylor, Northstone, Wenimont & Emmet, 2016a). Further, in 3-year-olds, picky eating was associated with a lower intake of micronutrients (carotene, iron and zinc) while no differences were found for energy intake compared to non-picky eaters (Taylor, Northstone, Wenimont & Emmet, 2016b). Interestingly, no clear associations have been found between picky eating and weight status, although picky eating may be indicative of a lower weight (Brown, Vander Schaaf, Cohen, Irby, & Skelton, 2016). However, some children with obesity also exhibit picky eating behaviors. A previous study showed that one third of parents with children with obesity perceived their children as being picky eaters (Sandvik et al., 2018). Further research should explore the food patterns of picky eaters of different weight status.

Our finding that a less healthy dietary pattern was associated with a higher desire to drink may reflect the higher consumption of sugar-sweetened beverages and juice among these children. This is possibly explained by greater access to these beverages, such that if parents remove sugar-sweetened beverages from the home the child may eventually stop expressing a desire to drink them. A US-based study conducted with 2-5-year-old African-American children and their fathers found that the child's desire to drink predicted an increased intake of sugar-sweetened beverages (Lora, Hubbs-Tait, Ferris, & Wakefield, 2016). In a UK-based study with older children, Desire to drink was

associated with a more frequent intake of sugar-sweetened beverages but not fruit juice (Sweetman, Wardle, & Cooke, 2008). Since the risk of developing obesity increases with a high intake of sugar-sweetened beverages, guiding parents in what beverages to offer children who frequently express desire to drink is an important part of childhood obesity prevention (Malik et al., 2013).

A notable finding is that children's dietary patterns are associated with enjoyment of food. In a previous study of Australian and British children's food preferences, children who liked fruits and vegetables were more often described as enjoying food and eating and having a low satiety response (Fildes et al., 2015). However, our finding goes beyond this focus on individual food items, suggesting a healthy dietary pattern as a whole is associated with children's enjoyment of food. In contrast, Fildes et al. (2015) found an association between Food Responsiveness and a preference for EDNP foods, whereas we found no association between Food Responsiveness and a less healthy dietary pattern. This could be due to the effects of obesity treatment, either on children's eating directly, or on their parents' awareness of what constitutes healthy eating and how to report dietary intake.

The limited associations we identified between parental feeding practices and children's dietary patterns were only partially consistent with previous research. We found a positive association between mothers' monitoring and the healthy dietary pattern. This is aligned with findings we reported in a previous study, where we found that an increase in mothers' monitoring led to decreased intake of sweets and chocolates 12 months after the initiation of obesity treatment (Somaraki et al., 2020). Along similar lines, in a study with Portuguese mothers and their 4-year-old children, Durão et al. (2015) reported that both Monitoring and Restriction increased the odds that children would consume amounts of fruits and vegetables that matched the national recommendations. However, Haszard et al. (2015) found that monitoring children's eating was associated with a lower intake of healthy food, though it should be noted that Haszard et al. (2015) did not use the CFQ and did not report which parent responded to the questionnaire. We found no associations between parental pressure to eat and children's dietary patterns. This is contrary to our previous findings where an increase in pressure to eat was associated with an increased intake of cookies and buns (Somaraki et al., 2020). The association between pressure to eat and less healthy diets among young children was also found in a systematic review and meta-analysis by Yee, Lwin, and Ho (2017). One possible explanation for this discrepancy is that our study focused on dietary patterns, whereas these earlier studies focused on individual types of food.

Of children's problematic obesity-related behaviors, as perceived by parents, only screen time behavior was associated with dietary patterns. Our finding that screen time was inversely associated with a healthy dietary pattern aligns with previous studies, which reported similar associations between television viewing and diet (Ford, Ward, & White, 2012). This finding may reflect associations between particular eating behaviors and screen time. Food fussiness, slowness in eating and more screen time are associated behaviors, and we have previously found an association between picky eating and screen time in a large sample of preschoolers (Sandvik et al., 2018). Further research is needed to understand why other problematic obesity-related behaviors were not associated with children's dietary patterns.

### 4.1. Strengths and limitations

Because the original ML was an intervention study for childhood obesity, the present analysis was not planned as part of ML. The analysis
is therefore limited by the lack of power calculations, which were not
performed due to the exploratory nature of this study. Furthermore, the
multiple linear regressions performed introduce a risk of false significant
results. However, because the study was exploratory, we chose not to
adjust the p-values (Bender & Lange, 2001). In the intervention, there
was a considerable loss to follow-up and the sample size of the present
study was relatively small. In particular, fathers had more missing data
than mothers, and a larger percentage of parents with foreign back-
ground did not complete the 12-month follow-up questionnaires.
However, our sample was still sociodemographically diverse, which
strengthens the external validity of the study. An additional limitation
relates to the identified dietary patterns, as no correlations were found
between the two patterns and an overlap between the two patterns is
therefore probable. When studying a large sample of preschool-aged
children in the US, Andersson, Ramsden and Kaye (2016) found no in-
verse association between two dietary patterns similar to the ones used
in our study. In addition, we relied on parents' reports to assess chil-
dren's food intake. Parent-reported intake can be fairly accurate if
parents observe the child's meals (Collins, Watson, & Burrows, 2010).
Because most Swedish 5-year-olds are enrolled in preschool where they
are served main meals and snack food, this may have limited parents'
ability to report food intake accurately, particularly regarding fruit and
vegetable intake, which is promoted in Swedish preschools. Moreover,
as with all FFQs, the one used in this study is a targeted dietary
assessment that only measures frequency and not amounts of a few
selected food items; thus, total diet or energy intake cannot be assessed.
Still, the short form FFQ can capture the consumption frequency of
relevant food items, which is important when studying food patterns
(Magarey et al., 2011).

A notable strength of this study is the use of data from both mothers and fathers. The great majority of studies has focused on mothers' feeding practices. Because mothers and fathers can differ in feeding practices (Davison, Haines, Garcia, Douglas, & McBrideet, 2020), as well as in their reporting of children's problematic obesity-related eating behaviors (Sandvik et al., 2019), including fathers increases the study's external validity. This is particularly the case in Sweden, where it is common for parents to share feeding responsibilities. An additional strength is the study's adjustment for sociodemographic factors in modeling associations between children's dietary patterns, eating, feeding, and obesity-related behaviors. It is well established that background factors such as socioeconomic status and parents' weight affect children's risk of developing obesity (Shrewsbury & Wardle, 2008; Svensson et al., 2014; Wang, Min, Khuri, & Li, 2017) and diet quality early in life (Cameron et al., 2015), and a strength of our study is that we adjust for these factors.

5. Conclusion

Twelve months after the start of childhood obesity treatment,

children's dietary patterns had stronger associations with children's eating behaviors than with parental feeding practices and parental perceptions of children's problematic obesity-related behaviors. Thus, the results indicate that eating behaviors have a larger impact on children's dietary patterns. Reported intake of items in a less healthy dietary pattern decreased after treatment while no differences were found in the reported intake of items in a healthy dietary pattern. A less healthy dietary pattern was associated with a higher BMI-z score. Additionally, our findings suggest that addressing food fussiness in children with obesity is key to positive dietary changes, as decreasing food fussiness may lead children to develop healthier dietary patterns.

Author contributions

PN conceived the idea of this study in collaboration with MS, AE and PS. SK and HRR drafted the paper under the supervision of PN and together with KE and PS. PS led the revision of the manuscript. All authors made substantial contributions to the study's conception and design, data collection and analyses, and to the interpretation of the data. All authors contributed to reviewing and approving the final manuscript.

Funding

This work was supported by the Swedish Research Council (2014-02404), Karolinska Institutet Doctoral Funds, the Swedish Society of Medicine, VINNOVA (2011-03443), Jerring Foundation, Samariten Foundation, Magnus Bergvall Foundation, Ingrid and Fredrik Thuring Foundation, Helge Ax:son Foundation, Crown Princess Lovisa Foundation, Foundation Frimurare Barnhuset in Stockholm, Foundation Pediatric Care, Jane and Dan Olsson Foundation, Sigurd and Elsa Golje Memory Foundation and iShizu Matsumurais Donation.

Ethical statement

The study was approved by the Regional Ethical Board in Stockholm
(ID: 2011/1329-31/4) on November 16, 2011.

Declaration of competing interest

The authors declare no conflicts of interest.

Acknowledgements

We want to thank all participating families. We also thank Sofia
Ljung, Jonna Nyman, Louise Lindberg, Mahnoush Etminan Malek,
Kathryn Lewis Chamberlain, Jan Ejderhamn, Philip A. Fisher, Patricia
Chamberlain and Claude Marcus who were involved in the study design
or in data collection within the More and Less Study.

Appendix 1

How often does the child eat or drink the food items below? Please, mark one alternative for each item.
<figure><img src="image_4.png" /></figure>
# Appendix 2

Principal Component Analysis (PCA) 12 months. Table 1 shows the total explained variance, Fig. 1 shows the scree plot, Table 2 shows the rotated component matrix and Fig. 2 shows the component plot.

Two factors have been obtained based on the raw coding (range 1–13) namely:

* Factor 1 (the less healthy dietary pattern, LHD): pizza/hamburger, ice-cream, cakes/cookies/buns, soft drinks, juice, sweets/chocolate, chips/snacks.

* Factor 2 (the healthy dietary Pattern, HD): fruits, vegetables, fish.

<caption>**Table 1**</caption>

Total variance explained, 12 months dietary patterns.

<table><thead><tr><th rowspan="2">Component</th><th colspan="3">Initial Eigenvalues</th><th colspan="3">Extraction Sums of Squared Loadings</th><th colspan="3">Rotation Sums of Squared Loadings</th></tr><tr><th>Total</th><th>% of Variance</th><th>Cumulative %</th><th>Total</th><th>% of Variance</th><th>Cumulative %</th><th>Total</th><th>% of Variance</th><th>Cumulative %</th></tr></thead><tbody><tr><td>1</td><td>3142</td><td>31,423</td><td>31,423</td><td>3142</td><td>31,423</td><td>31,423</td><td>3142</td><td>31,422</td><td>31,422</td></tr><tr><td>2</td><td>1655</td><td>16,547</td><td>47,970</td><td>1655</td><td>16,547</td><td>47,970</td><td>1655</td><td>16,549</td><td>47,970</td></tr><tr><td>3</td><td>,999</td><td>9987</td><td>57,957</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>4</td><td>,917</td><td>9174</td><td>67,132</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>5</td><td>,798</td><td>7980</td><td>75,112</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>6</td><td>,730</td><td>7296</td><td>82,408</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>7</td><td>,539</td><td>5394</td><td>87,802</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>8</td><td>,452</td><td>4519</td><td>92,321</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>9</td><td>,395</td><td>3951</td><td>96,271</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>10</td><td>,373</td><td>3729</td><td>100,000</td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

Extraction Method: Principal Component Analysis.

<figure><img src="image_5.png" /><figcaption>**Fig. 1.** Scree plot, 12-months dietary pattern</figcaption></figure>

<caption>**Table 2**</caption>

Rotated component matrixª, 12-months

<table><thead><tr><th>Component</th><th>1</th><th>2</th></tr></thead><tbody><tr><td>C_1yr12a_Fruit C_1yr12a_Fruit</td><td>-,004</td><td>,768</td></tr><tr><td>C_1yr12b_Vegetables C_1yr12b_Vegetables</td><td>,045</td><td>,797</td></tr><tr><td>C_1yr12c_Pizza_ham C_1yr12c_Pizza_ham</td><td>,523</td><td>-,249</td></tr><tr><td>C_1yr12d_Fish C_1yr12d_Fish</td><td>,011</td><td>,579</td></tr><tr><td>C_1yr12e_Icecream C_1yr12e_Icecream</td><td>,541</td><td>,133</td></tr></tbody></table>

(continued on next page)
<table><caption>Table 2 (continued)</caption><thead><tr><th>Component</th><th>1</th><th>2</th></tr></thead><tbody><tr><td>C_1yr12f_Cookies_buns C_1yr12f_Cookies_buns</td><td>,790</td><td>,018</td></tr><tr><td>C_1yr12g_Sweet_drink C_1yr12g_Sweet_drink</td><td>,807</td><td>-,081</td></tr><tr><td>C_1yr12h_Juice C_1yr12h_Juice</td><td>,522</td><td>,027</td></tr><tr><td>C_1yr12i_Sweets C_1yr12i_Sweets</td><td>,750</td><td>,029</td></tr><tr><td>C_1yr12j_Snacks C_1yr12j_Snacks</td><td>,679</td><td>,075</td></tr></tbody></table>

Extraction Method: Principal Component Analysis.

Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 3 iterations.

<figure><img src="image_6.png" /><figcaption>Fig. 2. Component plot in rotated space, 12 months' dietary patterns.</figcaption></figure>

## References

Anderson, S. E., Ramsden, M., & Kaye, G. (2016). Diet qualities: Healthy and unhealthy aspects of diet quality in preschool children. *American Journal of Clinical Nutrition*, **103**(6), 1507-1513. https://doi.org/10.3945/ajcn.115.128454

Aune, D., Giovannucci, E., Boffetta, P., Fadnes, L. T., Keum, N., Norat, T., & Tonstad, S. (2017). Fruit and vegetable intake and the risk of cardiovascular disease, total cancer and all-cause mortality—a systematic review and dose-response meta-analysis of prospective studies. *International Journal of Epidemiology*, **46**(3), 1029-1056.

Becker, W., & Enghardt, B. H. (2004). *Swedish children's food habits 2003 - results from questionnaire items*. Uppsala: Swedish Food Agency.

Bender, R., & Lange, S. (2001). Adjusting for multiple testing—when and how? *Journal of Clinical Epidemiology*, **54**(4), 343-349. https://doi.org/10.1016/S0895-4356(00)00314-0

Birch, L. L., Fisher, J. O., Grimm-Thomas, K., Markey, C. N., Sawyer, R., & Johnson, L. L. (2001). Confirmatory factor analysis of the child feeding questionnaire: A measure of parental attitudes, beliefs and practices about child feeding and obesity proneness. *Appetite*, **36**(3), 201-210. https://doi.org/10.1006/appe.2001.0398

Brown, C. L., Vander Schaaf, E. B., Cohen, G. M., Irby, M. B., & Skelton, J. A. (2016). Association of picky eating and food neophobia with weight: A systematic review. *Childhood Obesity*, **12**(4), 247-262. https://doi.org/10.1089/chi.2015.0189

Burrows, T., Golley, R. K., Khambalia, A., McNaughton, S. A., Magarey, A., Rosenkranz, R. R., et al. (2012). The quality of dietary intake methodology and reporting in child and adolescent obesity intervention trials: A systematic review. *Obesity Reviews*, **13**(12), 1125-1138. https://doi.org/10.1111/j.1467-789X.2012.01022.x

Cameron, A. J., Spence, A. C., Laws, R., Hesketh, K. D., Lioret, S., & Campbell, K. J. (2015). A review of the relationship between socioeconomic position and the early-life predictors of Obesity. *Current Obesity Reports*, **4**(3), 350-362. https://doi.org/10.1007/s13679-015-0168-5

Cardona Cano, S., Tiemeier, H., Van Hoeken, D., Tharner, A., Jaddoe, V. W., Hofman, A., & Hoek, H. W. (2015). Trajectories of picky eating during childhood: A general population study. *International Journal of Eating Disorders*, **48**(6), 570-579.

Chai, L. K., Collins, C., May, C., Brain, K., Wong See, D., & Burrows, T. (2019). Effectiveness of family-based weight management interventions for children with overweight and obesity: An umbrella review. *JBI Database of Systematic Reviews and Implementation Reports*, **17**(7), 1341-1427. https://doi.org/10.11124/JBISRIR-2017-003695

Cole, T. J., Bellizzi, M. C., Flegal, K. M., & Dietz, W. H. (2000). Establishing a standard definition for child overweight and obesity worldwide; international survey. *British Medical Journal*, **320**(7244), 1240-1243. https://doi.org/10.1136/bmj.320.7244.1240

Cole, T. J., & Lobstein, T. (2012). Extended international (IOTF) body mass index cut-offs for thinness, overweight and obesity. *Pediatric Obesity*, **7**(4), 284-294. https://doi.org/10.1111/j.2047-6310.2012.00064.x

Collins, C. E., Watson, J., & Burrows, T. (2010). Measuring dietary intake in children and adolescents in the context of overweight and obesity. *International Journal of Obesity*, **34**(7), 1103-1115. https://doi.org/10.1038/ijo.2009.241

Colquitt, J. L., Loveman, E., O'Malley, C., Azevedo, L. B., Mead, E., Al-Khudairy, L., & Rees, K. (2016). Diet, physical activity, and behavioural interventions for the treatment of overweight or obesity in preschool children up to the age of 6 years. *Cochrane Database of Systematic Reviews*, (3). https://doi.org/10.1002/14651858.CD012105

Davison, K. K., Haines, J., Garcia, E. A., Douglas, S., & McBrideet, B. (2020). Fathers' food parenting: A scoping review of the literature from 1990 to 2019. *Pediatric Obesity*, **1-10**.

Döring, N., Hansson, L. M., Andersson, E. S., Bohman, B., Westin, M., Magnusson, M., et al. (2014). Primary prevention of childhood obesity through counselling sessions at Swedish child health centres: Design, methods and baseline sample characteristics of the PRIMROSE cluster-randomised trial. *BMC Public Health*, **14**(1), 335. https://doi.org/10.1186/1471-2458-14-335
Duncanson, K., Shrewsbury, V., Burrows, T., Chai, L. K., Ashton, L., Taylor, R., & Collins, C. E. (2021). Impact of weight management nutrition interventions on dietary outcomes in children and adolescents with overweight or obesity: A systematic review with meta-analysis. *Journal of Human Nutrition and Dietetics, 34*(1), 147-177.

Durão, C., Andreozzi, V., Oliveira, A., Moreira, P., Guerra, A., Barros, H., et al. (2015). Maternal child-feeding practices and dietary inadequacy of 4-year-old children. *Appetite, 92*, 15-23. https://doi.org/10.1016/j.appet.2015.04.067

Ek, A., Chamberlain, K. L., Ejderhamn, J., Fisher, P. A., Marcus, C., Chamberlain, P., et al. (2015a). The More and Less Study: A randomized controlled trial testing different approaches to treat obesity in preschoolers. *BMC Public Health, 15*, 735. https://doi.org/10.1186/s12889-015-1912-1

Ek, A., Lewis Chamberlain, K., Sorjonen, K., Hammar, U., Etminan Malek, M., Sandvik, P., et al. (2019). A parent treatment program for preschoolers with obesity: A randomized controlled trial. *Pediatrics, 144*(2), Article e20183457. https://doi.org/10.1542/peds.2018-3457

Ek, A., Sorjonen, K., Eli, K., Lindberg, L., Nyman, J., Marcus, C., et al. (2016). Associations between parental concerns about preschoolers' weight and eating and parental feeding practices: Results from analyses of the child eating behavior questionnaire, the child feeding questionnaire, and the lifestyle behavior checklist. *PLoS One, 11*(1), Article e0147257. https://doi.org/10.1371/journal.pone.0147257

Ek, A., Sorjonen, K., Nyman, J., Marcus, C., & Nowicka, P. (2015b). Child behaviors associated with childhood obesity and parents' self-efficacy to handle them: Confirmatory factor analysis of the lifestyle behavior checklist. *International Journal of Behavioral Nutrition and Physical Activity, 12*(1), 36. https://doi.org/10.1186/s12966-015-0194-4

Eli, K., Hörnell, A., Malek, M. E., & Nowicka, P. (2017). Water, juice, or soda? Mothers and grandmothers of preschoolers discuss the acceptability and accessibility of beverages. *Appetite, 112*, 133-142. https://doi.org/10.1016/j.appet.2017.01.011

Ells, L. J., Rees, K., Brown, T., Mead, E., Al-Khudairy, L., Azevedo, L., et al. (2018). Interventions for treating children and adolescents with overweight and obesity: An overview of Cochrane reviews. *International Journal of Obesity, 42*(11), 1823-1833. https://doi.org/10.1038/s41366-018-0230-y

Fildes, A., Mallan, K. M., Cooke, L., van Jaarsveld, C. H. M., Llewellyn, C. H., Fisher, A., et al. (2015). The relationship between appetite and food preferences in British and Australian children. *International Journal of Behavioral Nutrition and Physical Activity, 12*(1), 116. https://doi.org/10.1186/s12966-015-0275-4

Ford, C., Ward, D., & White, M. (2012). Television viewing associated with adverse dietary outcomes in children ages 2-6. *Obesity Reviews, 13*(12), 1139-1147. https://doi.org/10.1111/j.1467-789X.2012.01028.x

Haszard, J. J., Skidmore, P. M., Williams, S. M., & Taylor, R. W. (2015). Associations between parental feeding practices, problem food behaviours and dietary intake in New Zealand overweight children aged 4-8 years. *Public Health Nutrition, 18*(6), 1036-1043. https://doi.org/10.1017/S1368980014001256

Hayes, J. F., Altman, M., Kolko, R. P., Balantekin, K. N., Holland, J. C., Stein, R. I., et al. (2016). Decreasing food fussiness in children with obesity leads to greater weight loss in family-based treatment. *Obesity, 24*(10), 2158-2163. https://doi.org/10.1002/oby.21622

Holland, J. C., Kolko, R. P., Stein, R. I., Welch, R. R., Perri, M. G., Schechtman, K. B., et al. (2014). Modifications in parent feeding practices and child diet during family-based behavioral treatment improve child zBMI. *Obesity, 22*(5), 119-126. https://doi.org/10.1002/oby.20708

Hurley, K. L., Pallan, M. J., Lancashire, E. R., Adab, P., & WAVES Study Investigators. (2018). An exploration of the longitudinal relation between parental feeding practices and child anthropometric adiposity measures from the West Midlands Active Lifestyle and Healthy Eating in Schoolchildren (WAVES) Study. *American Journal of Clinical Nutrition, 108*(6), 1316-1323. https://doi.org/10.1093/ajcn/nqy241

Jalo, E., Kontinen, H., Vepsäläinen, H., Chaput, J. P., Hu, G., Maher, C., et al. (2019). Emotional eating, health behaviours, and obesity in children: A 12-country cross-sectional study. *Nutrients, 11*(2), Article e351. https://doi.org/10.3390/nu11020351

de Lauzon-Guillain, B., Oliveira, A., Charles, M. A., Grammatikaki, E., Jones, L., Rigal, N., et al. (2012). A review of methods to assess parental feeding practices and preschool children's eating behavior: The need for further development of tools. *Journal of the Academy of Nutrition and Dietetics, 112*(10), 1578-1602. https://doi.org/10.1016/j.jand.2012.06.356

Lioret, S., Campbell, K. J., McNaughton, S. A., Cameron, A. J., Salmon, J., Abbott, G., et al. (2020). Lifestyle patterns begin in early childhood, persist and are socioeconomically patterned, confirming the importance of early life interventions. *Nutrients, 12*(3), 724. https://doi.org/10.3390/nu12030724

Lora, K. R., Hubbs-Tait, L., Ferris, A. M., & Wakefield, D. (2016). African-American and Hispanic children's beverage intake: Differences in associations with desire to drink, fathers' feeding practices, and weight concerns. *Appetite, 107*(12), 558-567. https://doi.org/10.1016/j.appet.2016.09.012

Magarey, A., Watson, J., Golley, R. K., Burrows, T., Sutherland, R., McNaughton, S. A., et al. (2011). Assessing dietary intake in children and adolescents: Considerations and recommendations for obesity. *International Journal of Pediatric Obesity, 6*(1), 2-11. https://doi.org/10.3109/17477161003728469

Malik, V. S., Pan, A., Willett, W. C., & Hu, F. B. (2013). Sugar-sweetened beverages and weight gain in children and adults: A systematic review and meta-analysis. *American Journal of Clinical Nutrition, 98*(4), 1084-1102. https://doi.org/10.3945/ajcn.113.058362

Mattes, R. (2006). Fluid calories and energy balance: The good, the bad, and the uncertain. *Physiology & Behavior, 89*(1), 66-70. https://doi.org/10.1016/j.physbeh.2006.01.023

Morawska, A., & West, F. (2013). Do parents of obese children use ineffective parenting strategies? *Journal of Child Health Care, 17*(4), 375-386. https://doi.org/10.1177/1367493512462263

Northstone, K., & Emmett, P. M. (2008). Are dietary patterns stable throughout early and mid-childhood? A birth cohort study. *British Journal of Nutrition, 100*(5), 1069-1076. https://doi.org/10.1017/S0007114508968264

Nowicka, P., Sorjonen, K., Pietrobelli, A., Flodmark, C. E., & Faith, M. S. (2014). Parental feeding practices and associations with child weight status. Swedish validation of the Child Feeding Questionnaire finds parents of 4-year-olds less restrictive. *Appetite, 81*, 232-241. https://doi.org/10.1016/j.appet.2014.06

Powell, L. M., & Nguyen, B. T. (2013). Fast-food and full-service restaurant consumption among children and adolescents: Effect on energy, beverage, and nutrient intake. *JAMA Pediatrics, 167*(1), 14-20. https://doi.org/10.1001/jamapediatrics.2013.417

Quah, P. L., Fries, L. R., Chan, M. J., Fogel, A., McCrickerd, K., Goh, A. T., et al. (2019). Validation of the children's eating behavior questionnaire in 5 and 6 year-old children: The GUSTO cohort study. *Frontiers in Psychology, 10*, 824. https://doi.org/10.3389/fpsyg.2019.00824

Sandvik, P., Ek, A., Eli, K., Somaraki, M., Bottai, M., & Nowicka, P. (2019). Picky eating in an obesity intervention for preschool-aged children – what role does it play, and does the measurement instrument matter? *International Journal of Behavioral Nutrition and Physical Activity, 16*(1), 76. https://doi.org/10.1186/s12966-019-0845-y

Sandvik, P., Ek, A., Somaraki, M., Hammar, U., Eli, K., & Nowicka, P. (2018). Picky eating in Swedish preschoolers of different weight status: Application of two new screening cut-offs. *International Journal of Behavioral Nutrition and Physical Activity, 15*, 74. https://doi.org/10.1186/s12966-018-0706-0

Shrewsbury, V., & Wardle, J. (2008). Socioeconomic status and adiposity in childhood: A systematic review of cross-sectional studies 1990-2005. *Obesity, 16*(2), 275-284. https://doi.org/10.1038/oby.2007.35

Slavin, J. L. (2005). Dietary fiber and body weight. *Nutrition, 21*(3), 411-418. https://doi.org/10.1016/j.nut.2004.08.018

Sleddens, E. F. C., Kremers, S. P. J., & Thijs, C. (2008). The children's eating behaviour questionnaire: Factorial validity and association with body mass index in Dutch children aged 6-7. *International Journal of Behavioral Nutrition and Physical Activity, 5* (1), 49. https://doi.org/10.1186/1479-5868-5-49

Somaraki, M., Eli, K., Sorjonen, K., Ek, A., Sandvik, P., & Nowicka, P. (2020). Changes in parental feeding practices and preschoolers' food intake following a randomized controlled childhood obesity trial. *Appetite, 154*, Article 104746. https://doi.org/10.1016/j.appet.2020.104746

Spahić, R., & Pranjić, N. (2019). Children's eating behaviour questionnaire: Association with BMI in children aged 3-10 years from Bosnia and Herzegovina. *Public Health Nutrition, 8*, 1-8. https://doi.org/10.1017/S1368980019002210

Spear, B. A., Barlow, S. E., Ervin, C., Ludwig, D. S., Saelens, B. E., Schetzina, K. E., et al. (2007). Recommendations for treatment of child and adolescent overweight and obesity. *Pediatrics, 120*, 254-288. https://doi.org/10.1542/peds.2007-2329F

Spence, J. C., Carson, V., Casey, L., & Boule, N. (2011). Examining behavioural susceptibility to obesity among Canadian pre-school children: The role of eating behaviours. *International Journal of Pediatric Obesity, 6*(2-2), 501-507. https://doi.org/10.3109/17477166.2010.512087

Svensson, V., Ek, A., Forssén, M., Ekbom, K., Cao, Y., Ebrahim, M., et al. (2014). Infant growth is associated with parental education but not with parental adiposity – early Stockholm obesity prevention project. *Acta Paediatrica, 103*(4), 418-425. https://doi.org/10.1111/apa.12551

Svensson, V., Lundborg, L., Cao, Y., Nowicka, P., Marcus, C., & Sobeko, T. (2011). Obesity related eating behaviour patterns in Swedish preschool children and association with age, gender, relative weight and parental weight - factorial validation of the Children's Eating Behaviour Questionnaire. *International Journal of Behavioral Nutrition and Physical Activity, 8*(1), 134. https://doi.org/10.1186/1479-5868-8-134

Sweetman, C., Wardle, J., & Cooke, L. (2008). Soft drinks and 'desire to drink' in preschoolers. *International Journal of Behavioral Nutrition and Physical Activity, 5*(1), 60. https://doi.org/10.1186/1479-5868-5-60

Syrad, H., Johnson, L., Wardle, J., & Llewellyn, C. H. (2016). Appetitive traits and food intake patterns in early life. *American Journal of Clinical Nutrition, 103*(1), 231-235. https://doi.org/10.3945/ajcn.115.117382

Taylor, C. M., Northstone, K., Wernimont, S. M., & Emmett, P. M. (2016a). Picky eating in preschool children: Associations with dietary fibre intakes and stool hardness. *Appetite, 100*, 263-271. https://doi.org/10.1016/j.appet.2016.02.021

Taylor, C. M., Northstone, K., Wernimont, S. M., & Emmett, P. M. (2016b). Macro-and micronutrient intakes in picky eaters: A cause for concern? *American Journal of Clinical Nutrition, 104*(6), 1647-1656. https://doi.org/10.3945/ajcn.116.137356

The Health Care Administration, & Stockholm County Council. (2010). *The action program for overweight and obesity 2010-2013*. Stockholm: Stockholm Health Care Administration.

Tian, Y., Su, L., Wang, J., Duan, X., & Jiang, X. (2018). Fruit and vegetable consumption and risk of the metabolic syndrome: A meta-analysis. *Public Health Nutrition, 21*(4), 756-765. https://doi.org/10.1017/S136898001700310X

Viana, V., Sinde, S., & Saxton, J. C. (2008). Children's eating behaviour questionnaire: Associations with BMI in Portuguese children. *British Journal of Nutrition, 100*(2), 445-450. https://doi.org/10.1017/S0007114508894391

Wang, Y., Min, J., Khuri, J., & Li, M. (2017). A systematic examination of the association between parental and child obesity across countries. *Advances in Nutrition, 8*(3), 436-448. https://doi.org/10.3945/an.116.013235

Wardle, J., Guthrie, C. A., Sanderson, S., & Rapoport, L. (2001). Development of the children's eating behavior questionnaire. *Journal of Child Psychology and Psychiatry, 42*(7), 963-970. https://doi.org/10.1111/j.1469-7610.00792
Webber, L., Cooke, L., Hill, C., & Wardle, J. (2010). Child adiposity and maternal feeding practices: A longitudinal analysis. *American Journal of Clinical Nutrition, 92*(6), 1423-1428. https://doi.org/10.3945/ajcn.2010.30112

Webber, L., Hill, C., Saxton, J., Van Jaarsveld, C. H., & Wardle, J. (2009). Eating behaviour and weight in children. *International Journal of Obesity, 33*(1), 21-28.
https://doi.org/10.1038/ijo.2008.219

West, F., Morawska, A., & Joughin, K. (2010). The Lifestyle Behaviour Checklist; evaluation of the factor structure. *Child: Care, Health and Development, 36*(4), 508-515. https://doi.org/10.1111/j.1365-2214.2010.01074.x

West, F., & Sanders, M. R. (2009). The lifestyle behaviour checklist: A measure of weight-related problem behaviour in obese children. *International Journal of Pediatric Obesity, 4*(4), 266-273. https://doi.org/10.3109/17477160902811199

Yee, A. Z., Lwin, M. O., & Ho, S. S. (2017). The influence of parental practices on child promotive and preventive food consumption behaviors: A systematic review and meta-analysis. *International Journal of Behavioral Nutrition and Physical Activity, 14*(1), 47. https://doi.org/10.1186/s12966-017-0501