*Article* **Effects of School-Based Interventions on Reducing Sugar-Sweetened Beverage Consumption among Chinese Children and Adolescents**

**Zhenni Zhu 1,2, Chunyan Luo 3, Shuangxiao Qu 3, Xiaohui Wei 4, Jingyuan Feng 4, Shuo Zhang 5, Yinyi Wang <sup>6</sup> and Jin Su 1,\***


**Abstract:** We set up a series of school-based interventions on the basis of an ecological model targeting sugar-sweetened beverage (SSB) reduction in Chinese elementary and middle schools and evaluated the effects. A total of 1046 students from Chinese elementary and middle schools were randomly recruited in an intervention group, as were 1156 counterparts in a control group. The interventions were conducted in the intervention schools for one year. The participants were orally instructed to answer all the questionnaires by themselves at baseline and after intervention. The difference in difference statistical approach was used to identify the effects exclusively attributable to the interventions. There were differences in grade composition and no difference in sex distribution between the intervention and control groups. After adjusting for age, sex, and group differences at baseline, a significant reduction in SSB intake was found in the intervention group post intervention, with a decrease of 35.0 mL/day (*p* = 0.034). Additionally, the frequency of SSB consumption decreased by 0.2 times/day (*p* = 0.071). The students in the elementary schools with interventions significantly reduced their SSB intake by 61.6 mL/day (*p* = 0.002) and their frequency of SSB consumption by 0.3 times/day (*p* = 0.017) after the intervention. The boys in the intervention group had an intervention effect of a 50.2 mL/day reduction in their SSB intake (*p* = 0.036). School-based interventions were effective in reducing SSB consumption, especially among younger ones. The boys were more responsive to the interventions than the girls. (ChiCTR, ChiCTR1900020781.)

**Keywords:** sugar-sweetened beverage; school-based; intervention; ecological model; difference in difference approach

#### **1. Introduction**

Each year, sugar-sweetened beverage (SSB) intake is related to the loss of about 8.5 million disability-adjusted life years (DALYs), and three quarters of this burden occurs in low- and middle-income countries [1]. SSBs were defined as nonalcoholic beverages sweetened by sugar, such as carbonated beverages, sugar-sweetened fruit or vegetable juice beverages, etc. The frequent consumption of excess amounts of SSBs is a risk factor for obesity [2], type 2 diabetes [3], cardiovascular disease [4], and dental caries [5]. The

**Citation:** Zhu, Z.; Luo, C.; Qu, S.; Wei, X.; Feng, J.; Zhang, S.; Wang, Y.; Su, J. Effects of School-Based Interventions on Reducing Sugar-Sweetened Beverage Consumption among Chinese Children and Adolescents. *Nutrients* **2021**, *13*, 1862. https://doi.org/ 10.3390/nu13061862

Academic Editors: Odysseas Androutsos and Evangelia Charmandari

Received: 7 April 2021 Accepted: 27 May 2021 Published: 30 May 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

potential pathophysiology of SSB consumption explained the unfavorable health outcomes linked to SSBs. SSBs contain energy but no micro- and macronutrients, except glucose and fructose. Excessive glucose intake is known for causing adverse glycemic effects on metabolism [6], and fructose can be converted into fat, unfettered by the cellular controls that prevent unrestrained lipid synthesis from glucose [7]. The adverse health outcomes linked to SSBs occur in both adults and children [8,9]. Behavioral factors such as diet linked to mortality causes are preventable and both shape and are shaped by the social environment [10]. Studies have shown that interventions can achieve favorable results in reducing SSB intake in children but not in adults [11]. It is possible that interventions might have effects on individuals who were before or at their behavioral development period rather than those already forming behavioral models.

Comprehensive school-based program achieved some changes on dietary intakes of students [12,13]. School-based interventions aiming at decreasing SSB consumption have shown promising results in previous Western studies [14]. More than half of the children and adolescents in China consumed SSB, and the increasing consumption of SSBs has created the obvious threat of obesity among Chinese children and adolescents [15,16]. However, there has been no study reporting evaluations of school-based interventions tackling SSB reduction in China. Considering the different environmental and cultural backgrounds compared to Western countries, we set up a series of school-based interventions on the basis of an ecological model targeting SSB reduction in Chinese elementary and middle schools and evaluated the effects on SSB reduction among Chinese children and adolescents.

#### **2. Materials and Methods**

#### *2.1. Study Population*

We adopted epidemiological methods to establish a parallel control group intervention experiment for one year, from February 2019 to January 2020, in Shanghai, China. Three elementary schools and two middle schools were randomly recruited into the intervention group, and the same number of adjacent counterparts into the control group. Students in the 3rd and 4th grades from the selected elementary schools and the 6th and 7th grades from the selected middle schools were enrolled into the intervention or control group according to their school's allocation. The participants were not informed of which group they were assigned.

The theoretical minimum sample size was 1051 for the intervention and control groups, respectively, following the formula of sample size calculation for experiments with comparisons between two different groups:

$$\mathbf{n} = \left[ (\mathbf{Z}\_{\alpha/2} + \mathbf{Z}\_{\beta}) \mathbf{S}/\delta \right]^2$$

We set α = 0.05 and β = 0.10. S represented standard deviation of SSB intake, andδ represented allowance error.

We decided to select 220 students in each grade of a school and a total of 1100 students in both the intervention and control groups. After enrollment, 1082 and 1259 students were in the intervention and control groups, respectively. By eliminating the students lost to follow up, there were 1046 in the intervention group and 1156 in the control group (Figure 1).

**Figure 1.** Flow chart of subjects throughout the research.

This study was approved by the Shanghai Municipal Center for Disease Control on 17 May 2017 (No. 2017-18). Informed consent was obtained from each participant or the participant's parents or guardian before the research. The study complied with the code of ethics of the World Medical Association (Declaration of Helsinki). This intervention study was registered at the Chinese Clinical Trial Registry (http://www.chictr.org.cn, accessed on 7 April 2021) with the registration number of ChiCTR1900020781 (http://www.chictr. org.cn/showproj.aspx?proj=35002, accessed on 19 January 2019).

#### *2.2. SSB Intake, Frequency, and Knowledge Assessment*

The investigators were public health doctors in local community health centers and received a standard training course on the facilitation of the questionnaires. The participants were orally instructed to answer all the questionnaires by themselves. The investigators verified the answers after each questionnaire was completed.

The information collected at the baseline and post one-year intervention were both at the interval between January to February, just before and after the complete one-year intervention period.

A general questionnaire was used to obtain demographic information and SSB-related knowledge. There were six questions related to SSB consumption and health which were used to assess the SSB-related knowledge of the participants. The participant received one point if they gave the right answer. A full score was six. The six questions were as follows:


An SSB frequency questionnaire was administrated to collect information on SSB intake and frequency in the past 3 months. This questionnaire originated from a former food frequency questionnaire that was developed and validated by the China Center for Disease and Control and Prevention [17]. SSBs were defined as nonalcoholic beverages sweetened by sugar, excluding fresh juice, categorized as carbonated beverages, sugarsweetened fruit or vegetable juice beverages, protein-based beverages, probiotic beverages, milk-based beverages, bottled tea beverages, coffee drink, and typical Southeast Asian milky tea (a popular SSB in China). According to each SSB category, SSB consumption frequency was listed in terms of consumption times per day, week, month, or year, and the amount consumed each time was recorded.

The survey was conducted in the pre- and post-intervention periods using the same questionnaires. No disastrous events such as rain or snow disasters that would have affected the normal food supply took place during the research period. The weather was typical of the marine climate in Shanghai, China.

#### *2.3. Interventions*

The interventions were designed using the structures of an ecological model targeting individuals and their environment, including multiple levels of influence [18]. The interventions were conducted for one year by the teachers in the intervention schools with the collaboration of public health doctors in local community health centers. The control schools had no intervening events. All the participating schools followed the city-wide education schedule during the intervention period.

	- - Hold "restricting SSBs"-themed class meeting every semester (twice a year) and praise students with outstanding health behaviors (the themed class meeting was designed to provide SSB-related knowledge regarding the six questions about SSB-related knowledge in the questionnaire).
	- -Distribute SSB-related knowledge materials every semester (twice a year).
	- -Record one's own SSB behaviors once per week.
	- - Establish WeChat (the most popular social communication application in China) groups for parents and publish new media promotional materials once a month.
	- - Distribute promotional cards to students every semester (twice a year; the cards showed cartoon figures and information regarding the six questions on SSB-related knowledge in the questionnaire, as well as mottos and goals for the new semester).
	- - Carry out a blackboard painting activity with the theme of "understanding SSBs" every semester (twice a year).


#### e. Community level


#### *2.4. Statistical Analyses*

Statistical analyses were conducted using the SAS statistical software (v. 9.4; SAS Institute, Cary, NC, USA). The comparisons were conducted between the participants in the same level of different schools, different groups and pre and post intervention. T tests were applied to determine the differences between the intervention and control groups pre and post intervention. The difference in difference (DID) statistical approach was used to identify the net effects exclusively attributable to the interventions in this study [19]. The DID approach was designed for quasi-experimental research studying causal relationships in public health settings where randomized controlled trials (RCTs) are infeasible or unethical. In the current analysis of DID, an interactive item of the variate representing group classification and a variate representing pre- or post-intervention classification was included in the multivariate general linear regression models, representing the intervention effect. Age, sex, and the variates mentioned above were included in the same models as covariates. A two-sided *p* < 0.05 was considered to indicate statistical significance.

#### **3. Results**

#### *3.1. Characteristics of the Participants*

At baseline, 1082 subjects were recruited in the intervention group and 1259 subjects in the control group. At one-year follow-up, 1046 remained in the intervention group and 1156 in the control group. The retention rates were 96.7% and 91.8% in the intervention and control groups, respectively. Differences in sex distribution were not observed between the two groups either pre or post intervention. The differences in grade composition were significant between the groups both pre and post intervention (Table 1).


#### **Table 1.** Characteristics of the participants pre and post intervention (%).

#### *3.2. Differences in SSB Intake, Frequency, and Knowledge between the Groups pre and Post Intervention*

At baseline, the SSB intakes were 286.0 ± 266.5 mL/day and 286.0 ± 288.2 mL/day in the intervention and control groups, respectively. The frequencies of SSB consumption were 1.6 ± 1.6 times/day and 1.7 ± 1.9 times/day, respectively. The scores for SSB-related knowledge were 4.3 ± 1.2 and 4.5 ± 1.0, respectively. There was no difference in the SSB intake and frequency of SSB consumption between the two groups and their subgroups (*p* > 0.05). The scores for SSB-related knowledge were significantly different between the two groups (*p* < 0.001).

After the one-year intervention, the SSB intakes were 220.9 ± 262.3 mL/day and 254.4 ± 268.9 mL/day in the intervention and control groups, respectively. The frequencies of SSB consumption were 1.1 ± 1.5 times/day and 1.4 ± 1.7 times/day, respectively. The scores for SSB-related knowledge were 4.4 ± 1.3 and 4.5 ± 1.1, respectively. Significant differences existed in the SSB intake and the frequency of SSB consumption between groups (*p* = 0.003, *p* < 0.001). The scores for SSB-related knowledge showed no statistical difference between the groups (*p* = 0.060) (Table 2).

**Table 2.** The differences in SSB intake, frequency, and knowledge between the groups pre and post intervention.


SSB, sugar-sweetened beverage.

#### *3.3. The Effects on SSB Intake, Frequency, and Knowledge Attributed to the Interventions*

After adjusting for age, sex, and group differences at baseline, a significant reduction in SSB intake which was exclusively attributed to the interventions was found in the intervention group post intervention, with a decrease of 35.0 mL/day (*p* = 0.034). Additionally, the frequency of SSB consumption decreased by 0.2 times/day, with a borderline significance (*p* = 0.071), due to the intervention. No statistically significant effect was found in the score for SSB-related knowledge after the intervention (*p* = 0.347).

After intervention, the participants in the elementary schools with the intervention significantly reduced their SSB intake by 61.6 mL/day (*p* = 0.017) and their frequency of SSB consumption by 0.3 time/day (*p* = 0.002), but no changes were observed in the SSB intake and frequency of SSB consumption among those from middle schools with the intervention (*p* = 0.945 and *p* = 0.978, respectively). The boys in the intervention group had an intervention effect of a 50.2 mL/day reduction in SSB intake (*p* = 0.036), while the girls presented no significant intervention effect in SSB intake (*p* = 0.403) (Table 3).


**Table 3.** The effects attributable to the interventions on SSB intake, frequency, and knowledge after the one-year intervention a.

<sup>a</sup> β represented the net change of the indicator attributable to the interventions only post intervention compared with that pre-intervention.

#### **4. Discussion**

In the current study, the one-year school-based interventions achieved favorable effects in reducing SSB consumption among Chinese children and adolescents. Regarding the feasibility of the intervention implemented, each participant was not assigned randomly into an intervention or control group. Actually, the participants were allocated indiscriminately into interventions or control groups according to their school's allocation in the study. Moreover, other citywide health promotion events at the time or the underlying natural growth of individuals might have affected their SSB consumption as well. All these factors made it difficult to identify the effects exclusively attributed to the current interventions. The DID approach provided an alternative means for us to study the net effects on the SSB consumption changes which were exclusively attributable to the interventions [19,20]. After adjusting for age, sex, and group differences at baseline, we discovered a substantial scale of SSB reduction attributable to the interventions in this study. The school stood out as one of the most common settings to improve health behaviors [21]. Previous studies indicated that Western school-based interventions were promising to reduce SSB consumption [14]. Our results give more evidence regarding school-based interventions in the setting of an Eastern culture and environment. The current results also supported the theory that the ecological model helped to develop an environment conducive to change, facilitating the adoption of healthy behaviors [22].

We found that the beneficial effects occurred among the younger children rather than the adolescents in the current study. Both the amount and the frequency of SSB consumption reduced after the one-year intervention, while SSB-related knowledge also increased modestly among the younger children. However, there was no obvious change in the amount and the frequency of SSB consumption and SSB-related knowledge among the participants in the middle schools between pre- and post-intervention. These findings coincided with previous studies showing that interventions focusing on SSB control are more effective on younger children than older ones [23,24]. This also suggests that future interventions or policies aiming at reducing SSBs should target younger children in order to achieve more favorable cost-effective outcomes.

We observed that the consumption of SSBs decreased in the boy participants but not in the girl participants. In the current study, the consumption of SSBs was discrepant at baseline in that the boys consumed more SSBs than the girls no matter whether they were in the intervention or control group. Boys had a higher preference for SSBs and consumed more SSBs than girls in their daily lives [15,25,26]. This might explain the significant effects on the boys after the intervention while there were hardly any effects on the girls in our study. Furthermore, the prevalence of overweight and obesity is much higher in boys than in girls in China [27]. The discrepancies between boys and girls in terms of intervention effects should be taken into consideration when conceiving obesity control strategies among children and adolescents.

In this study, we failed to discover enough evidence of improvement in SSB-related knowledge among our participants through the interventions. Only a modest increase in knowledge score that was of borderline significance (*p* = 0.066) occurred among the participants in the elementary schools with the intervention. In the current interventions, we provided SSB-related knowledge through routine school activities to the students and electronic messages to their parents, which aimed to set up supportive environments for SSB restriction. Previous studies showed that knowledge was not associated with SSB behaviors among children [28]. Other factors such as parental health behavior might determine SSB consumption among children [29,30]. Parental modelling was more crucial to children's behavioral development [31]. These might be the reasons why the behavior of SSB consumption changed but the SSB-related knowledge remained unimproved among the participants after the intervention in our study.

A limitation of this study was the methodology used to assess SSB intake and frequency. We designed an SSB consumption questionnaire to obtain SSB intake and frequency, which were self-reported by the participants, thus the data on SSB intake and frequency were limited by the accuracy of participants' estimation and recall. Furthermore, although we adjusted for potential confounding factors, we did not treat dietary intake as one of the confounders under the limitation of data collection. This might have caused bias in the current results. Besides this, the investigators were not blinded to the allocation of schools as intervention and control. This awareness of the investigators might have caused data collection bias. Finally, it was possible that some of the six questions used to assess the SSB-related knowledge were beyond the understanding of the students, which might have influenced our assessment of the SSB-related knowledge change.

#### **5. Conclusions**

School-based interventions designed in an ecological model were effective in the reduction in SSB consumption among Chinese children and adolescents, especially among younger children. The boys were more responsive to the interventions than the girls.

**Author Contributions:** Z.Z. conceived and designed the experiments; S.Q. and C.L. performed the experiments; Z.Z. analyzed the data; X.W., J.F., and S.Z. interpreted the statistical results; X.W., J.F., and Y.W. wrote the draft paper; Z.Z. wrote the paper and the final version of the manuscript; J.S. supervised the study. All authors have read and agreed to the published version of the manuscript.

**Funding:** This study was funded by the Study of Diet and Nutrition Assessment and Intervention Technology (No.2020YFC2006300) from Active Health and Aging Technologic Solutions Major Project of National Key R&D Program—Intervention Strategies of Main Nutrition Problems in China (No.2020YFC2006305); Shanghai Municipal Health Commission—Academic Leader Program (GWV-10.2-XD12); the Foundation of Shanghai Municipal Health Commission (201740073); and the Youth Nutrition Elite Development Program of Chinese Nutrition Society.

**Institutional Review Board Statement:** The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Shanghai Municipal Center for Disease Control on 17 May 2017 (No. 2017-18).

**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.

**Data Availability Statement:** The datasets used and analyzed in the current study are available from the corresponding author on reasonable request.

**Acknowledgments:** We are grateful to all the individuals who participated in this study. We also thank the teachers from the participating schools as well as the public health doctors at the local districts' Centers for Disease Control and Prevention and the local community health centers for their assistance with the intervention implementation and data collection.

**Conflicts of Interest:** The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

#### **Abbreviations**

SSB, sugar-sweetened beverage; DALYs, disability-adjusted life years; DID, difference in difference; RCTs, randomized controlled trials.

#### **References**


## *Article* **Breastfeeding and Overweight in European Preschoolers: The ToyBox Study**

**Natalya Usheva 1,\*, Mina Lateva 2, Sonya Galcheva 2, Berthold V. Koletzko 3, Greet Cardon 4, Marieke De Craemer 5,6, Odysseas Androutsos 7, Aneta Kotowska 8, Piotr Socha 8, Luis A. Moreno 9, Yannis Manios 10, Violeta Iotova <sup>2</sup> and on behalf of the ToyBox-Study Group †**


**Abstract:** The benefits of breastfeeding (BF) include risk reduction of later overweight and obesity. We aimed to analyse the association between breastfeeding practices and overweight/obesity among preschool children participating in the ToyBox study. Data from children in the six countries, participating in the ToyBox-study (Belgium, Bulgaria, Germany, Greece, Poland, and Spain) 7554 children/families and their age is 3.5–5.5 years, 51.9% were boys collected cross-sectionally in 2012. The questionnaires included parents' self-reported data on their weight, height, socio-demographic status, and infant feeding practices. Measurements of preschool children's weight and height were done by trained researchers using standard protocols and equipment. The ever breastfeeding rate in the total sample was 85.0% (*n* = 5777). Only 6.3% (*n* = 428) of the children from the general sample were exclusively breastfed (EBF) for the duration of the first six months. EBF for four to six months was significantly (*p* < 0.001) less likely among mothers with formal education < 12 years (adjusted Odds Ratio (OR) = 0.61; 95% Confidence interval (CI) 0.44–0.85), smoking throughout pregnancy (adjusted OR = 0.39; 95% CI 0.24–0.62), overweight before pregnancy (adjusted OR = 0.67; 95%CI 0.47–0.95) and ≤25 years old. The median duration of any breastfeeding was five months. The prevalence of exclusive formula feeding during the first five months in the general sample was about 12% (*n* = 830). The prevalence of overweight and obesity at preschool age was 8.0% (*n* = 542) and 2.8% (*n* = 190), respectively. The study did not identify any significant association between breastfeeding practices and obesity in childhood when adjusted for relevant confounding factors (*p* > 0.05). It is likely that sociodemographic and lifestyle factors associated with breastfeeding practices may have an impact on childhood obesity. The identified lower than desirable rates and duration of breastfeeding practices should prompt enhanced efforts for effective promotion, protection, and support of breastfeeding across Europe, and in particular in regions with low BF rates.

**Keywords:** breastfeeding; preschoolers; overweight; obesity

**Citation:** Usheva, N.; Lateva, M.; Galcheva, S.; Koletzko, B.V.; Cardon, G.; De Craemer, M.; Androutsos, O.; Kotowska, A.; Socha, P.; Moreno, L.A.; et al. Breastfeeding and Overweight in European Preschoolers: The ToyBox Study. *Nutrients* **2021**, *13*, 2880. https://doi.org/10.3390/ nu13082880

Academic Editor: Megumi Haruna

Received: 31 July 2021 Accepted: 19 August 2021 Published: 21 August 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

#### **1. Introduction**

Optimal nutrition during the first years of life is important to promote healthy growth and development of children. Inappropriate nutrition augments the risk of illness and childhood obesity. Obesity is an escalating public health problem worldwide, with an expected prevalence of 9.1% among preschoolers in 2020 [1,2] and an estimated 70 million overweight or obese children and adolescents by 2025, the majority living in low- and middle-income countries [3]. According to the criteria of the International Obesity Task Force (IOTF), about 17.9% of European children aged 2–7 years were identified with overweight or obesity in the recently published systematic review, including 32 studies (*n* = 197,755 children) from 27 European countries [4]. Currently available options for treating overweight and obese children are less than satisfactory, therefore implementation of effective preventive measures, including promotion of optimal feeding from early on, is of utmost importance [5].

Breastfeeding is considered as a "golden standard", the best nutrition for infants, and is associated with numerous short- and long-term health benefits, such as higher cognitive development scores and reduced risk of gastro-intestinal infections, otitis media, atopic dermatitis, and asthma, as well as later non-communicable diseases in adults such as type 2 diabetes and obesity [6–11]. It has been proposed that about one million cases of childhood obesity per year may be prevented by recommended breastfeeding (BF) practices [12]. The reported advantages of exclusive breastfeeding (EBF) compared to partial breastfeeding have led to the World Health Organization (WHO) global public health recommending exclusive breastfeeding for six months and continued breastfeeding for ≥two years with complementary foods introduced [13]. The protective role of BF against overweight and obesity was first reported in a large cross-sectional study in 1999 [14] and has since been replicated in many studies around the world [11,15–17]. Potential mechanisms underpinning this association are differences in the composition of human milk and breast milk substitutes and their impact on infant hormonal and metabolic response and growth characteristics. Behavioural differences and associated confounders such as mother's body mass index (BMI), education, and tobacco use in pregnancy have also been discussed [18–24]. We analysed the association between breastfeeding and obesity among school children, with adjustment for important potential confounders relevant to overweight and obesity among the large European sample of schoolchildren participating in the ToyBox Study.

#### **2. Materials and Methods**

The ToyBox study (Available online: www.toybox-study.eu (accessed on 21 June 2021) adhered to the Declaration of Helsinki and the conventions of the Council of Europe on human rights and biomedicine. All participating countries obtained ethical clearance from the respective ethical committees and local authorities, and all parents/caregivers provided a signed consent form before being enrolled in the study.

Data was collected between May and June 2012 using the primary caregivers' questionnaire, which was filled in by parents/caregivers of preschoolers in six European countries (Belgium, Bulgaria, Germany, Greece, Poland, and Spain). Parents/caregivers of preschoolers born between January 2007 and December 2008 who attended the randomly selected kindergartens within the provinces of Oost-Vlaanderen and West-Vlaanderen (Belgium), Varna (Bulgaria), Bavaria (Germany), Attica (Greece), Mazowieckie (Poland), and Zaragoza (Spain) were grouped in three socioeconomic levels and invited to participate in ToyBox study. The necessary information about the ToyBox study was presented previously [25]. A standardized self-administered questionnaire for primary caregivers' was used to determine the perinatal data of preschoolers (comprising of anthropometric measurements at birth and breastfeeding practices during the first year of life), as well as participating families' socio-demographic characteristics. Questions about the nutrition of children during the first 12 months of life were targeted on identifying the presence/absence of breastfeeding each month after birth and when water, tea, juice, formula milk, and solid/semi-solid foods

were included. In order to minimize recall bias, the guidance to the parents/caregivers was to refer to the children's medical records for the questions in the perinatal section. As a result, the test–retest reliability study showed an excellent value of ICC (intra-class correlation coefficient)—0.75 for this section of the questionnaire. The socio-demographic characteristics were previously found to have very high reliability (i.e., all ICCs ≥ 0.937), while the reliability of the questions on parental weight and height spread from moderate to very high (i.e., ICC ranged from 0.489 to 0.911) [26]. Other papers [27,28] presented the data collected using validated questionnaires as well as the corresponding results about health-related behaviors (dietary habits, physical activity, and sedentary behavior) of preschoolers and their parents.

Mothers' years of education were used as stratification criteria for the socioeconomic status (SES) of the families by categorizing it as low (≤12 years), medium (13–16 years), and high (≥16 years of education).

Preterm birth was defined as <37 gestational weeks, and full-term birth as ≥37 gestational weeks. Questions on breastfeeding status were based on definitions according to the WHO indicators [29]. Exclusive breastfeeding was defined as BF with no other food or liquid given, except drops and syrups (vitamins, minerals, medicines). Breastfeeding with an additional supply of water or water-based liquids, such as fruit juice, tea, or syrups, was considered predominant breastfeeding. Full BF refers to either exclusive or predominant breastfeeding. The inclusion of other milk and foods (formula milk, and/or semi-solids) was considered partial breastfeeding. Ever breastfeeding rate is the proportion of infants less than 12 months who were ever breastfed. The "later stage BF initiation" was defined as starting of BF at any time but not from birth.

According to the study protocol, the questionnaires with more than 75% of the required information provided were included in the statistical analysis. The analysis did not include the children for which the information about feeding in the first two months (*n* = 444) nor about the time of solid foods' introduction (*n* = 300).

#### *2.1. Anthropometric Data*

Children's weight (0.1 kg measurement resolution) and height (0.1 cm measurement resolution) were obtained by means of a standardized protocol and equipment, subjected to calibration before and during the data collection period [30]. For the purpose of ensuring a very good intra- and inter- observed reliability agreement [31], research assistants, who passed extensive training before commencing the study, carried out all measurements to achieve. The definition of overweight, including obesity was based on the WHO criteria: for children age < 5 years as BMI z-score > 2 standard deviation (SD) and BMI z-score > 3 SD, respectively, whereas, for children age > 5 years, the ranges were encompassed into BMI z-score > 1 SD for overweight and into BMI z-score > 2 SD for obesity. Calculated ponderal index (PI = weight/height3) served for evaluation of children's weight status at their birth with the normal PI range being 2.2–3.0 g/cm3, PI > 3.0 was considered indicative for overweight; while PI < 2.2 indicated low weight newborns. Parents/caregivers selfreported parental weight and height, while their BMI was calculated. Categorization of parents/caregivers with regard to their BMI defined the groups of normal weight (≤24.9 kg/m2), overweight (≥25 and ≤29.9 kg/m2), and obese (≥30 kg/m2) ones [32].

#### *2.2. Statistical Analyses*

Continuous variables are shown as the means ± standard deviation for the cases of normal distribution (e.g., age of preschoolers, age of mothers, the introduction of solid foods) and as the medians and IQR (interquartile range) for variables deviating from a normal distribution (duration of breastfeeding). Shapiro-Wilk tests were used for testing of normality of variables' distribution.

With regard to country and children's BMI categories, the χ<sup>2</sup> test and Fisher's exact test were applied to these categorical variables. For comparison of the means from two samples, an independent samples *t*-test was implemented, whereas for the means of more

than two samples (birth weight; mother's age)—the one-way ANOVA (analysis of variance) with a Scheffe's post-hoc analysis.

The median Mann-Whitney test was used for the comparison of the medians from independent samples. Pearson's and Spearman's correlation analyses were utilized for exploration of the relationship between feeding practices and children's BMI as well as mother's characteristics. The odds of being overweight/obese (dependent variable), while accounting for different breastfeeding practices were estimated by means of logistic regression analysis with 95% confidence intervals (CIs). The validity of significant associations to the duration of breastfeeding, when adjusted for these other variables, potential confounding variables and covariates (mother's age and BMI before pregnancy, SES (socio-economic status), smoking habits during pregnancy, and country) was determined on the basis of the obtained results. For the purpose of quantifying the probability of conforming to the current recommendations for the EBF in 4–6 months of age, logistic regression analysis was carried out adjusting for mothers' age and BMI before pregnancy, SES, smoking habits during pregnancy, and country. Conformance to recommendations for EBF 4–6 months of age (yes/no) and overweight/obesity at preschool age (yes/no) were specified as dependent variables in the relevant models. The variables presented as logistic regression model coefficients were chosen on the basis of their relevance for the investigated subject and also these tested negatively for the presence of collinearity, thus not bringing any tangible influence too. The Statistical Package for Social Sciences (IBM SPSS v. 20, Chicago, IL, USA) was used for the data analysis with *p* < 0.05 set as a level of significance.

#### **3. Results**

A total of 6800 questionnaires from the six countries met the qualifying criteria for inclusion in the analysis is. The sociodemographic characteristics of respondents are shown in Table 1. The mean age of children is 4.75 ± 0.43 years; 52.3% boys, with no statistically significant difference in gender distribution between the participating countries. Further details with regard to characteristics of the ToyBox study sample are presented in other papers [25,32].


**Table 1.** Characteristics of participants by country.


**Table 1.** *Cont.*

\* χ<sup>2</sup> test; \*\* ANOVA; BMI—Body mass index; SES—socio-economic study; SD—standard deviation.

#### *3.1. Breastfeeding Practices*

The ever breastfeeding rate in the total sample is 85.0% (*n* = 5777). The highest rates are reported in the samples from Poland (94.7%) and Bulgaria (92.8%), while the lowest is in the Belgian sample (66.7%). Prevalence of the BF initiation from the time of birth is 96.1% (*n* = 5531) and has a statistically positive weak correlation with the country (Pearson's *r* = 0.13; <0.001): the highest are in Belgium (99.6%) and Germany (99.1%). Children in Spain and Greece more often than in other study countries started BF not from birth but from a later time: 12.4%; *n* = 75 and 7%; *n* = 99, respectively.

Only 6.3% (*n* = 428) of the children were exclusively breastfed for the duration of the first six months after birth. Frequencies higher than the average of the total sample are observed for Germany (*n* = 163; 14.8%) and Poland (*n* = 105; 7.9%). Greece has the lowest frequency (2.7%); followed by Belgium (2.8%) and Spain (5.2%) (Table 2).



\* Introduction of solid foods is significantly different with exception of the next comparisons—Greece and Spain *p* = 0.13; Greece and Poland *p* = 0.9; Poland and Spain *p* = 0.18 (ANOVA; Scheffe Post-hoc test); \*\* *p*-value in median test; † *p*-value in χ2-test; BF—breastfeeding; EBF—exclusive breastfeeding; SF—solid foods; IQR—Interquartile range; SD—standard deviation.

#### *3.2. Duration of Breastfeeding*

The median duration of BF among infants during the first 12 months is highest among Polish (9 months) and German (7 months) participants, with a significantly higher duration than the median duration of the entire sample (5 months, *p* < 0.001). For the entire sample, after adjustment for the risk factors there is a weak but significant positive relationship between the duration of breastfeeding and maternal characteristics: education level (Spearman's *ρ* = 0.15; *p* = 0.023), SES (Spearman's *ρ* = 0.09; *p* < 0.001), age at the pregnancy (Pearson's *r* = 0.061; *p* < 0.0001). Additionally, mothers with a pre-pregnancy BMI ≥ 25(Pearson's *r* = −0.14; *p* < 0.001) and smoking habits during pregnancy (Pearson's *r* = −0.06; *p* < 0.0001) had a shorter duration of BF. Infants who were breastfed exclusively for 4–6 months have a longer duration of any BF (Pearson's *r* = 0.32; *p* < 0.0001). Factors associated with the continued BF (>12 months) are mother's education ≥ 14 years (*p* < 0.0001), normal weight before pregnancy (*p* < 0.0001), non-smoking habits during pregnancy (*p* < 0.0001), 25–40 years age group (*p* = 0.001) and SES (*p* = 0.02).

Exclusive formula feeding during first 4–6 months is about 12% (*n* = 830), with the highest value observed in the Belgian sample (*n* = 253; 22.4%) and the lowest in the Polish sample (4.5%; *p* < 0.001), which is associated with the following mothers' characteristics: education ≥ 14 years (*p* < 0.0001), non-smoking habits during pregnancy (*p* < 0.0001), higher age (*p* < 0.0001) and higher SES (*p* = 0.025); normal pre-pregnancy weight (*p* = 0.03).

Mothers' education less than 12 years (*p* < 0.0001); BMI > 25 kg/m<sup>2</sup> (*p* < 0.0001); tobacco use throughout pregnancy (*p* < 0.001) and low SES (*p* < 0.001) are associated with a higher frequency of formula feeding. The same risk factors (maternal education less than 12 years (OR = 0.61; 95%CI 0.44–0.85), smoking throughout pregnancy (OR = 0.39; 95% CI 0.24–0.62), overweight before pregnancy (OR = 0.67; 95%CI (0.47–0.95)) are associated with not achieving EBF for 4–6 months (*p* < 0.05), Table 3.

**Table 3.** Maternal characteristics associated with non-compliance to recommendations for exclusive breastfeeding (EBF) for 4–6 months.


<sup>1</sup> Adjusted for age and BMI before pregnancy, smoking habits during pregnancy, country and SES. <sup>2</sup> Adjusted for age and BMI before pregnancy, country and SES. <sup>3</sup> Adjusted for age BMI before pregnancy, smoking habits during pregnancy, country and SES. <sup>4</sup> Adjusted for age before pregnancy, smoking habits during pregnancy, country and SES; (BMI—Body mass index; SES—socio-economic status; EBF—exclusive breastfeeding)

#### *3.3. Breastfeeding Practices and Weight Status of the Preschoolers*

The prevalence of overweight and obesity according to the WHO criteria was 8.0% (*n* = 542) and 2.8% (*n* = 190), respectively (Table 1). Infant feeding practices exhibited a different association with the prevalence of overweight and obesity at different stages of childhood. A lower percentage of children were obese in the EBF 4–6 months group than

the formula-fed group (1.6% vs. 6.5%; *p* = 0.012) (Table 4). Factors negatively related to the prevalence of overweight and obesity in preschoolers after controlling for confounding factors are EBF throughout the first three months of life (Pearson's *r* = −0.03; *p* = 0.01) and non-significantly—duration of any breastfeeding (Spearman's *ρ* = −0.02; *p* = 0.12).


**Table 4.** Breastfeeding practicies and weight status of children.

BF—breastfeeding; EBF—exclusive breastfeeding.

Formula feeding at 4–6 months is linked to a higher prevalence of overweight and obesity at 6 months of infancy (13.8%) and among preschoolers (13.5%), but the association was non-significant when adjusted for confounding factors (Spearman's *ρ* = 0.02; *p* = 0.18). (Table 4)

Table 5 shows the output from the logistic regression analysis with reducing factors for overweight or obesity being identified: the odds to become overweight at preschool age among children who were BF for 4–6 months is 0.87 (OR = 0.87; 95%CI 0.62–1.21; *p* = 0.40); 0.64 for EBF 6 months. The introduction of solid foods after six months of EBF is related to 69% less risk for overweight at preschool age (*p* = 0.25) in comparison to the formula milk feeding when adjusted for the mother's characteristics (age and BMI before pregnancy, smoking habits during pregnancy, country, SES) and gender of the children.

**Table 5.** Logistic regression analysis of the association of infant feeding practices and the overweight or obesity among preschool children.


<sup>1</sup> Adjusted for mother's age and BMI before pregnancy, smoking habits during pregnancy, country, SES and children's gender; EBF—exclusive breastfeeding; BF—breastfeeding.

Regarding the association between other characteristics at birth and obesity, there is no correlation with preterm or term delivery (*p* = 0.89) and PI at birth (*p* = 0.36) in the total sample and the country level stratification (*p* > 0.05).

#### **4. Discussion**

The analyses of the collected data from 6 countries in Europe regarding the characteristics at birth, infant feeding practices, and risk of childhood obesity revealed that in nearly all the countries 85% of children were breastfed, with the notable exception of Belgium, where only 66.7% of children were breastfed. In spite of the solid evidence demonstrating major health benefits associated with BF, including risk reduction for overweight and obesity, breastfeeding remains still well below the global goal of 50% EBF at 2025 [33–35]. Our data represent the BF practices and related factors corresponding to the year 2012 but are in agreement with other recent survey analyses indicating less than satisfactory breastfeeding practices in many European countries [36]. In our sample, only 6.3% of children were exclusively breastfed during the 6th month of life and thus met the WHO recommendation. However, a recent survey performed by the WHO Regional Office for Europe and the European Society of Pediatric Gastroenterology, Hepatology and Nutrition revealed that more than 82% of European countries recommended the introduction of complementary feeding at the age of 4–5 months and hence exclusive breastfeeding for a shorter period than six months [37]. The rate of EBF in our study is lower than results for EBF at 4–6 months from European samples such as IDEFICS (45.5%) and COSI (lowest—10.5% for Spain), and from the World Health Statistics WHO—Reports [38,39]. The significant data discrepancy appears to be primarily due to the different approaches of the calculation methodologies, and potentially also due to some imprecision due to recall bias in our study. In the studies cited above, as well as in almost all the official data, the frequency of exclusive breastfeeding is presented according to the WHO "Indicators for assessing infant and young child feeding practices" as the prevalence of "exclusively breastfed for the first 6 months of life". Thus, this indicator does not measure the proportion of children meeting the WHO recommendation for exclusive breastfeeding of all children until 6 months, as pointed out by Pullum [40]. The prevalence data in the above-mentioned studies are very close to the goals in the "WHO global nutrition targets 2025" and can lead to inadequate political decisions regarding protection, promotion, and support of exclusive breastfeeding.

Children who were exclusively BF throughout the first three months of life were less likely to become overweight at preschool age when adjusted for country, age and gender, mother's pre-pregnancy age and BMI.

The odds to become overweight at preschool age among children who were BF for 4–6 months is 0.87 and 0.31 for the EBF and solids introduction at 4–6 months in comparison to the formula milk feeding, when adjusted for mother's characteristics (age and BMI before pregnancy, smoking habits during pregnancy, country, SES and gender of children). Thus the effect size for breastfeeding effects on later obesity in our study, although non-significant, is in the same order of magnitude as found in reviews and meta-analyses [15–18]. Our results also show a protective role of any breastfeeding against obesity and overweight, with 13% less risk at any BF of 4–6 months, and 69% for overweight and 12% for obesity at EBF and solid foods introduction for six months, compared to exclusive formula feeding. These results agree with the reported 26% decrease of the odds of overweight or obesity with any BF in 113 studies [23]. Also, infants fed formula during the first 4–6 months have a higher prevalence of overweight and obesity in preschool age (Table 4). Possible mechanisms for this relationship may include the different macronutrient composition of breast milk and formula, in particular the lower protein supply with breast milk [18], and potentially the presence of bioactive substances like ghrelin, leptin, insulin-like growth factor-1, adiponectin in human milk but not in formula [41]. There is published evidence that feeding formula milk has an accelerating effect on infant weight, height, body fat, apparently mediated through high levels of protein (the "early protein hypothesis") [18] and lower appetite control of bottle-fed infants [15,20,42,43]. Moreover, a recent study reported that formula feeding in the early life of infants small for their gestational age is related to prospective overweight in preschool age, but only among girls [44]. Breastfeeding also modulates the physiological development of the digestive tract [45] and intestinal colonization [46], which might contribute to risk reduction for obesity in

later life [47]. However, our results also show significant confounding of the association of breastfeeding and later overweight by low SES that is linked to both less breastfeeding success and more overweight. A more detailed analysis of the relationship between SES and overweight/obesity prevalence in children participating in the ToyBox study was previously published [32]. In the current analysis, SES is included as a confounder for which the analysis has been adjusted.

One of the limitations of the current presentation is the cross-sectional study design which is not able to identify the cause-effect association between the sociodemographic characteristics and the prevalence of overweight/obesity among preschoolers. Particularly, the selection of children from kindergartens within only one province in each country is the next methodological limitation of the study, which does not allow to draw a conclusion at a national level for each of the countries based on the collected data. Another limiting factor stems from the parental self-reporting of weight, height, gestational weight gain, and infant's birth weight, which despite the relatively close time for recollection might have introduced recall bias. Retrieving data about BF duration through mothers' recall for the time period 3–4 years ago can be seen as another limitation. This mostly impacts the reporting of EBF, as there is evidence that more than two years after birth mothers tend to overestimate the duration of BF [48]. In line with previous studies, our analysis indicates that breastfeeding practices are associated with factors that are also related to obesity development, such as maternal education, SES, BMI, and infant birth weight [38,49–51]. The statistical power to detect protective effects of breastfeeding on later obesity is limited by the fact that we could not compare exclusive breastfeeding from birth with exclusive formula feeding from birth, which has been reported to have the most marked effect on later obesity risk [52]. Even though we adjusted the calculation of ORs for these factors, residual confounding cannot be excluded, hence the extent of the causal effect of breastfeeding itself on later risk of overweight and obesity is difficult to determine.

A large number of study participants, the involvement of participants from several European countries which adds a level of independent validation, as well as the harmonized methodology in data collection and obtaining measurements may be noted as merits of this study [26,32].

#### **5. Conclusions**

Our study found only a non-significant trend for reduced childhood overweight associated with breastfeeding when adjusting for relevant confounding factors. It is likely that sociodemographic and lifestyle factors associated with breastfeeding practices have an impact on childhood obesity. The findings of less than desirable breastfeeding rates and duration underline the need for enhanced protection, promotion, and support of breastfeeding throughout Europe. Particularly intensive efforts are necessary for populations with low breastfeeding rates and duration based on geographic region and other risk markers such as lower education and socioeconomic class, tobacco smoking, parental overweight and obesity [5,36]; short duration of maternity leave, psychological factors as maternal perceived stress and postpartum depression [53].

**Author Contributions:** Conceptualization, V.I. and N.U.; methodology, N.U., V.I. and G.C.; formal analysis, N.U., M.L. and S.G.; investigation, M.L., S.G. and M.D.C.; writing—original draft preparation, N.U., V.I.; writing—review and editing, B.V.K., M.D.C., O.A., V.I., G.C., A.K., S.G., Y.M., P.S., L.A.M.; supervision, V.I., Y.M. All authors have read and agreed to the published version of the manuscript.

**Funding:** The ToyBoxstudy was funded by the Seventh Framework Program (The Community Research and Development Information Service (CORDIS; FP7)) of the European Commission under grant agreement No. 245200. B.V.K. is the Else Kröner Senior professor of Paediatrics at LMU— University of Munich, financially supported by the Else Kröner-Fresenius-Foundation, the LMU Medical Faculty and the LMU University Hospitals. The content of this article reflects only the authors' views and the European Community is not liable for any use that may be made of the information contained therein.

**Institutional Review Board Statement:** The ToyBoxstudy (www.toybox-study.eu; accessed on 20 September 2020) adhered to the Declaration of Helsinki and the conventions of the Council of Europe on human rights and biomedicine. All the countries (Belgium, Bulgaria, Germany, Greece, Poland and Spain) obtained ethical clearance from the relevant ethics committees and local authorities: 1. Ethics Committee of Ghent University Hospital (Belgium)—EC/2010/037; 2. Committee for the Ethics of Scientific Studies (KENI) at the Medical University of Varna (Bulgaria)— 15/21.07.2011; 3. Ethics Committee of the Medical Faculty at LMU Munich (Ethikkommission der Ludwig-Maximilians-Universität München) (Germany)—400-11 (2012); 4. Bioethics Committee of the Harokopio University of Athens (Greece) (28/02-12-2010) and the Ministry of Education of Greece (approval code 29447/Γ7 (5 May 2011)); 5. Ethics Committee of the Children's Memorial Health Institute (Poland)—1/KBE/2012; 6. CEICA (Comité Ético de Investigación Clínica de Aragón (Spain))—PI11/056 30 August 2011. The ToyBox-study is registered with the clinical trials registry: clinicaltrials.gov, ID: NCT02116296.

**Informed Consent Statement:** All parents/caregivers provided a signed consent form before being enrolled in the study.

**Data Availability Statement:** The data presented in this study are available on request from the corresponding author. The data are not publicly available due to restrictions of informed consent and the requirement of IRB review and approval.

**Acknowledgments:** We gratefully acknowledge all the members of the ToyBox study group: Coordinator: Yannis Manios; Project manager: Odysseas Androutsos; Steering Committee: Yannis Manios, Berthold Koletzko, Ilse De Bourdeaudhuij, Mai Chin A Paw, Luis Moreno, Carolyn Summerbell, Tim Lobstein, Lieven Annemans, Goof Buijs; External Advisors: John Reilly, Boyd Swinburn, Dianne Ward; Harokopio University (Greece): Yannis Manios, Odysseas Androutsos, Eva Grammatikaki, Christina Katsarou, Eftychia Apostolidou, Anastasia Livaniou, Eirini Efstathopoulou, Paraskevi-Eirini Siatitsa, Angeliki Giannopoulou, Eff ie Argyri, Konstantina Maragkopoulou, Athanasios Douligeris, Roula Koutsi; Ludwig Maximilians Univers itaet Muenchen (Germany): Berthold Koletzko, Kristin Duvinage, Sabine Ibrügger, Angelika Strauß, Birgit Herbert, Julia Birnbaum, Annette Payr, Christine Geyer; Ghent University (Belgium): Department of Movement and Sports Sciences: Ilse De Bourdeaudhuij, Greet Cardon, Marieke De Craemer, Ellen De Decker; Department of Public Health: Lieven Annemans, Stefaan De Henauw, Lea Maes, Carine Vereecken, Jo Van Assche, Lore Pil; VU University Medical Center EMGO Institute for Health and Care Research (the Netherlands): EMGO Institute for Health and Care Research: Mai Chin A Paw, Saskia te Velde; University of Zaragoza (Spain): Luis Moreno, Theodora Mouratidou, Juan Fernandez, Maribel Mesana, Pilar De Miguel-Etayo, Esther M. González-Gil, Luis Gracia-Marco, Beatriz Oves; Oslo and Akershus University College of Applied Sciences (Norway): Agneta Yngve, Susanna Kugelberg, Christel Lynch, Annhild Mosdøl, Bente B Nilsen; University of Durham (UK): Carolyn Summerbell, Helen Moore, Wayne Douthwaite, Catherine Nixon; State Institute of Early Childhood Research (Germany): Susanne Kreichauf, Andreas Wildgruber; Children's Memorial Health Institute (Poland): Piotr Socha, Zbigniew Kulaga, Kamila Zych, Magdalena Gózd´ ´ z, Beata Gurzkowska, Katarzyna Szott; Medical University of Varna (Bulgaria): Violeta Iotova, Mina Lateva, Natalya Usheva, Sonya Galcheva, Vanya Marinova, Zhan eta Radkova, Nevyana Feschieva; International Association for the Study of Obesity (UK): Tim Lobstein, Andrea Aikenhead; CBO B.V. (the Netherlands): Goof Buijs, Annemiek Dorgelo, Aviva Nethe, Jan Jansen; AOK- Verlag (Germany): Otto Gmeiner, Jutta Retterath, Julia Wildeis, Axel Günthersberger; Roehampton University (UK): Leigh Gibson; University of Luxembourg (Luxembourg): Claus Voegele.

**Conflicts of Interest:** The authors declare no conflict of interest.

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