Linking infant size and early growth with maternal lifestyle and breastfeeding – the first year of life in the CRIBS cohort

Abstract

Background

Every third child in Croatia is classed as overweight or obese. Infant growth can represent early warning signs for obesity.

Aim

To detect early risk factors for obesity by investigating infant size and early growth trajectories and their association with maternal lifestyle and breastfeeding.

Subjects and methods

Ninety-eight mother–child pairs from the Croatian Islands’ Birth Cohort Study (CRIBS) cohort were included in the study. Data were collected from questionnaires and medical records. Growth data were converted to Z-scores using World Health Organisation (WHO) standards and used as the primary outcome.

Results

Z-score trajectories in the first year of life were in line with WHO standards. A direct link between infant size and maternal socioeconomic status (SES) or breastfeeding was not detected. However, child weight gain in the first 6 months was associated with maternal body mass index (BMI) before pregnancy (p < 0.01). A positive association was also established between breastfeeding and maternal SES and mothers that report an unhealthy diet have heavier children (p < 0.05, respectively).

Conclusion

Infant size and early growth in Croatia is in line with WHO standards and risk factors for obesity development were detectable in the first year of life, but not highly pronounced. However, more effective BMI monitoring and promotion of a healthy diet and lifestyle of women before and during pregnancy is needed.

Keywords:

• Infant size
• infant growth
• CRIBS cohort
• maternal lifestyle
• breastfeeding

Introduction

Two thirds of adults (65%) in Croatia are classed as overweight or obese and, together with Malta, Croatia shares first place in the European Union in terms of the percentage of adults with excessive body mass and obesity (Eurostat 2021). Results for children in Croatia are even more alarming – the Childhood Obesity Surveillance Initiative (COSI) Croatia 2018/2019 showed that 35.0% of children aged 8–9 in Croatia were classed as overweight or obese. It is predicted that, together with Hungary and Turkey, Croatia will be at the very top with a predicted 19% of children aged 5–19 with obesity in 2030 (Musić Milanović et al. 2021; Ministry of Health, Republic of Croatia, 2022). The reason for this adverse situation is still unclear and, since paediatric obesity is a strong risk factor for adult obesity and the development of non-communicable diseases (type 2 diabetes mellitus, dyslipidaemia, hypertension, non-alcoholic fatty liver disease, cardiovascular disease, premature mortality), it needs to be investigated in more detail to determine its causes.

The obesogenic lifestyle of children starts in the mother’s womb and continues throughout childhood, making the “early-life exposome” one of the most important time frames for the study of obesity. Increasing evidence suggests that child growth patterns, other than indicating a child’s immediate well-being, can represent early warning signs for obesity in later life (Mook-Kanamori et al. 2011). Growth rate in early postnatal life is highly dependent on birth weight, since smaller babies tend to catch-up and heavier babies tend to catch-down during the first months of postnatal life (Ong 2006). Previous research in Croatia has shown that high pre-pregnancy BMI and excessive gestational weight gain of mothers are associated with having newborns that are large for their gestational age and therefore at greater risk of becoming overweight or obese themselves (Šarac et al. 2022). Findings from the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort indicate that higher waist circumference and BMI, and lower insulin sensitivity in 8-year-old children, were predicted by increased weight gain from birth to 3 years of age (Ong et al. 2004). Other longitudinal studies also suggest that rapid infancy weight gain is linked to higher risks of hypertension, insulin resistance, obesity, and cardiovascular disease in later life (Correa-Burrows et al. 2021).

Breastfeeding is a known factor influencing child growth and it has been found to generally reduce an individual’s current and future risk for overweight and/or obesity (Horta et al. 2023). However, the recommendations to exclusively breastfeed within the first 6 months and continue breastfeeding up to 2 years of age proposed by the World Health Organisation (WHO) and the United Nations Children’s Fund (Victora et al. 2016; WHO 2021) are rarely followed – only 36% of 0–6 months old infants were exclusively breastfed from 2007 to 2014 worldwide. The European Childhood Obesity Surveillance Initiative (COSI) reported that high birth weight was associated with increased risk of becoming overweight and that breastfeeding for at least 6 months had protective effects against obesity (Rito et al. 2019). In Croatia, breastfeeding is still considered the desirable way to feed a newborn baby and, thus, the rate of early initiation of breastfeeding is high (80%) (Miloš et al. 2019). To our knowledge data on exclusive breastfeeding rates in the first 6 and/or 12 months do not exist on the national Croatian level. Given the nutritional importance of breastfeeding and the health benefits both for mother and baby, studies of the effects of maternal nutritional status and breastfeeding on early child growth and development are necessary, but sparse in Croatia, limited to the neonatal period and without longitudinal follow-up.

In addition, socioeconomic status (SES) and maternal lifestyle (nutrition, smoking) in pregnancy can play an important role in child growth patterns. Studies have shown that infants from low SES families have lower birth weights than those from high SES families (Dubois and Girard 2006; Jansen et al. 2009) but during infancy and childhood lower SES is associated with higher levels of adiposity due to adverse dietary habits (Stamatakis et al. 2010). SES can also mediate the strength of association between breastfeeding and levels of adiposity. Namely, disadvantaged infants are less likely to breastfeed relative to more advantaged children and it is therefore important to investigate maternal-related pathways through which socioeconomic disadvantage influences early childhood obesity (Gibbs and Forste 2014). Nutrition in pregnancy has also been recognised as an important modifiable environmental factor influencing child growth and development. In that sense, the Mediterranean diet has a well-known desirable dietary pattern. The term “Mediterranean diet” has been widely used to describe the typical traditional diet for the area of the Mediterranean basin and is characterised by prevalent consumption of fruits, vegetables, whole-grains cereals, legumes, and nuts. Paradoxically, although the health benefits of the Mediterranean diet are widely recognised and scientifically proven, adherence to this dietary pattern in its native countries is decreasing (Naja et al. 2021; Šarac et al. 2021). Our previous study suggested that a non-Mediterranean, westernised dietary pattern is followed in the Mediterranean part of Croatia. This is more pronounced in the island population and accompanied by more adverse socioeconomic and lifestyle conditions (Havaš Auguštin et al. 2020). Mother’s dietary habits also influence foetal development and pregnancy outcomes – poor and inappropriate maternal nutrition is causally associated with abnormal foetal growth patterns and increased risks of developing childhood and adult chronic diseases (Marshall et al. 2022).

There is a general lack of comparative studies on child growth and its association with maternal characteristics such as socioeconomic status and breastfeeding duration in Croatia. Since a centralised medical data collection system is not available for researchers in Croatia, epidemiological studies are based on data obtained from individual cohorts. However, there are no prospective studies covering early growth and development (the so-called “first 1000 days,” i.e. pregnancy and the first years of a child’s life). Therefore, the objectives of this study were: (i) to investigate infant size and trajectories of early child growth and development (0–12 months) within the first Croatian Islands’ Birth Cohort Study (CRIBS) and (ii) to link them with selected maternal characteristics previously highlighted as significant, as well as breastfeeding patterns. A long-term goal of the study is to detect early risk factors for obesity development in later life.

Subjects and methods

Data from the CRIBS were used for this report. CRIBS was a pilot study with a longitudinal approach conducted on pairs of pregnant women and their newborns. Healthy pregnant women were recruited at the gynaecological offices on the Eastern Adriatic islands of Brač and Hvar and in the city of Split from 2016 to 2018 and they all gave birth at the University Hospital Centre Split. Inclusion criteria were: natural conception, singleton pregnancies, and no history of chronic diseases. Children were followed up until the age of 2, with an aim to assess risk factors associated with metabolic syndrome. More details on recruitment, follow-up, and the CRIBS cohort can be found in Perinić Lewis et al. (2019) and Šarac et al. (2022).

Ninety-eight infants with complete data at four time points (at birth, 1, 6, and 12 months) were investigated in this study. All infants were term newborns, i.e. born between 38 and 42 completed weeks of gestation. Demographic, socioeconomic, medical, and lifestyle data before and during pregnancy and medical data after the delivery were collected through five self-completed questionnaires: two administered during pregnancy (one in the second and one in the third trimester) and three administered after the child’s birth – at 1, 6, and 12 months of age. Available medical data were also retrieved from the hospital’s medical records, both for pregnant women and their newborns. Measurements of newborns were performed at the University Hospital Centre Split. Child anthropometric measurements at 1, 6, and 12 months were available from paediatric records. Children’s age and sex-adjusted Z-scores were calculated according to the WHO Child Growth Standards in R Studio (4.2.1. version) with anthro package by WHO (https://www.who.int/tools/child-growth-standards/software). BMI-for-age Z-score cut-off points of < −2.0, > 2.0, and > 3.0 recommended by the WHO to classify children 0–5 years of age as underweight, overweight, and obese, respectively, were used. Maternal pre-pregnancy BMI was self-reported and additionally validated by a measurement at the first visit to the gynaecological practice. BMI categories were defined as follows: underweight (BMI < 18.5 kg/m²); appropriate weight (BMI = 18.5–24.9 kg/m²); overweight (BMI = 25–29.9 kg/m²); and obesity (BMI ≥ 30 kg/m²). Maternal anthropometric measurements for the calculation of gestational weight gain (GWG) were taken once in each trimester, during visits to the gynaecology practices for regular monitoring of pregnancy. GWG categories (inadequate, adequate, and excessive) were defined according to the guidelines for pregnancy weight gain issued by the Institute of Medicine (IOM) (Šarac et al. 2022).

Information on general and exclusive breastfeeding and its duration was self-reported by mothers. Indicators of socio-economic status (SES) included in this study were monthly household income, maternal education, and mother’s working status. Education was categorised into four groups: highest educational level (university, MA, PhD), higher educational level (university, BA), middle educational level (high school), and low education level (primary school). Monthly income per family was divided into three categories: ≤1,000 euros, 1,000–2,000 euros, ≥2,000 euros. Mother’s working status was either employed or unemployed. Tobacco consumption in pregnancy was assessed by a questionnaire in the third trimester with the following questions: “Do you currently smoke?,” “If no, have you ever smoked?”

The assessment of dietary intake in pregnancy was determined using the Dietary Adequacy Assessment Questionnaire for Adults (DAAQA). The DAAQA consisted of 101 food items and dietary habits comprising food preparation, food consumption, and dietary supplements habits, together with the frequency of food consumption. The intakes of different foodstuffs were reported as daily, weekly, or monthly intake frequencies. Adherence to the Mediterranean diet was assessed through the Mediterranean Diet Serving Score (MDSS). The score includes 14 food groups, adding 1, 2, or 3 points to the total score based on the consumption frequency and the relative importance of particular types of food, without assigning negative points. The maximum possible MDSS score in the original study (Monteagudo et al. 2015) was 24 points, and the cut-off of ≥13.5 points was considered as good compliance. However, the maximum possible MDSS score in this study was 23 points and the cut-off was set at 12.5 points, since we excluded one category (fermented beverages) from the calculation. The MDSS score and its calculation has been described in more detail in the study by Havaš Auguštin et al. (2020).

All CRIBS participants signed an informed consent form for the participation and record linkage (for both the mother and the child) prior to their inclusion in the study. Research has been performed in accordance with the Declaration of Helsinki and Ethical Committee Approval for the CRIBS study was obtained from the Institute for Anthropological Research (Zagreb, Croatia). Collection of data and anthropometric measurements were taken in accordance with the relevant guidelines and regulations.

Z-scores were calculated in R using the anthro package from WHO (https://www.who.int/tools/child-growth-standards/software), as described above, and used to compare BMI-for-age Z-scores for children at three time points against the WHO standard. Performed statistical analyses included t-test analysis for child anthropometric characteristics (weight and length) by gender (mean values), a multiple linear regression analysis of the association between infant weight at four time points and selected maternal characteristics, and a Spearman correlation for the association between mother’s pre-pregnancy BMI and child’s weight points, as well as for linking maternal MDSS score with different weight-related child Z-score values from 6 to 12 months. All data analyses were performed using R version 4.2.1 and Python version 3.8.8. Graphs, t-test for weight and length (at birth, 1 month, 6 months, 12 months), gestational age by gender and growth curves for genders were calculated in Python version 3.8.8. Calculations were made with SciPy and Pingouin packages and graphs were made with Matplotlib and Seaborn packages. Spearman correlations were plotted in R version 4.2.1 with tydiverse and ggplot2 packages.

Results

The baseline maternal and infant characteristics are presented in Table 1. Education of participants was high – half of the women had a university or even PhD degree (51% in total), coupled with 46.7% of participants with high school education. Household income was generally low or average for the majority of participants, while 76.5% of mothers were employed. Lifestyle of participants showed a high percentage of smokers or ex-smokers in the study (19.4% of mothers identified themselves as active smokers during pregnancy), with low adherence to the Mediterranean diet. Mean pre-pregnancy BMI was 22.37 ± 0.40 (standard deviation (SD) = 4.04) – 8.2% of mothers were underweight when entering the study and 16.3% had overweight or obesity. During pregnancy, 45.9% of women gained appropriate weight and 31.6% gained excessive weight. The rate of Caesarean section in this cohort was lower than the general Croatian average (18.4 vs. 27.6%) (Rodin et al. 2022). Regarding infant size at birth, 74.5% were born as average, 14.3% were large, and 11.2% small for their gestational age. All children were breastfed at the first week of age, 82.5% were exclusively breastfed at 1 month, and more than 40% at 6 months, with 30% of children still being breastfed at 1 year of life. When the difference between islands and the mainland is inspected, more women from the mainland breastfed their children in the first 6 months when compared to the mothers from the islands (Figure 1).

Figure 1. Child nutrition in the first 6 months with regards to location.

Table 1. Baseline maternal and infant characteristics.

Maternal characteristics		N (%)
Education	University, MA, PhD	36 (36.7)
	University, BA	14 (14.3)
	High School	46 (46.9)
	Primary School	2 (2.0)
Household income	>2,000 euros	6 (6.1)
	1,000–2,000 euros	46 (46.9)
	<1,000 euros	46 (46.9)
Working status	employed	75 (76.5)
	unemployed	23 (23.5)
Parity	primipara	54 (55.1)
	multipara	44 (44.9)
Smoking	yes	19 (19.4)
	ex-smoker	34 (34.7)
	never	45 (45.9)
Mediterranean Diet Serving Score	low	79 (80.6)
	high	19 (19.4)
Pre-pregnancy BMI	underweight	8 (8.2)
	normal	74 (75.5)
	overweight/obese	16 (16.3)
Gestational weight gain	inadequate	22 (22.4)
	adequate	45 (45.9)
	excessive	31 (31.6)
Birth mode	vaginal	80 (81.6)
	Caesarean section	18 (18.4)
Infant characteristics
Size for gestational age	SGA	11 (11.2)
	AGA	73 (74.5)
	LGA	14 (14.3)
Exclusive breastfeeding in the first 6 months	yes	40 (41.0)
	no	58 (59.0)
Breastfeeding until 12 months	yes	30 (30.5)
	no	68 (69.4)

The children were evenly distributed between genders (52% males and 48% females). More than 97% had an Apgar score of 10 at birth. The mean gestational age was 40.11 weeks ± 0.99 weeks, the mean birth weight was 3,546.53 g ± 528 g, the mean weight at 1 month 4,517.65 g ± 644 g, the mean weight at 6 months 7,728.55 g ± 1,112.59 g and mean weight at 12 months 9,860.67 g ± 1,704.26 g . The mean weight gain (WG) in the first 6 months was 4,182.02 g ± 584.59 g and between 6 and 12 months it was 2,132.12 g ± 591.67 g. There were no significant differences in gender distribution with regards to gestational age, but significant differences between boys and girls were observed for all anthropometric measures, at all time points (p < 0.01) (Table 2).

Table 2. Child anthropometric characteristics by gender (mean values).

Child anthropometry
	Boys	Girls	p-value
Gestational age (weeks)	40.33	39.89	0.099207
Weight at birth (g)	3,711.76	3,365.95	0.0009
Length at birth (cm)	51.51	49.96	0.0004
Weight at 1 month (g)	4,753.72	4,261.49	0.00009
Length at 1 month (cm)	55.58	54.16	0.0025
Weight at 6 months (g)	8,130.00	7,451.06	0.00001
Length at 6 months (cm)	69.41	66.61	0.000002
Weight at 12 months (g)	10,449.61	9,657.45	0.0001
Length at 12 months (cm)	78.62	75.76	8.40E-07

Children from the CRIBS cohort exhibited normal early growth and development in the first year of life. Boys in this study were on average heavier and attained more growth in weight in the first year of life compared to girls, as was expected, and they were both heavier than the WHO standards (p < 0.01). At around 6 months of age, curves for both genders became less steep and weight gain slowed down, as depicted in Figure 2. When BMI-for-age Z-scores at three time points were analysed, no significant deviations from standards were observed (Figure 3, p-values > 0.05 at all time points). 93.88% of children at birth and at 12 months were within the −2 and 2 SD range of WHO standards, as well as 98.9% of children at 6 months. Two children were found to be underweight (Z-score < −2.0), 11 were found to be overweight (Z-score > 2.0), and only one was found to have obesity (Z-score > 3.0) at 1 year of age.

Figure 2. WHO and CRIBS weight growth curves by gender.

Figure 3. BMI-for-age Z-scores for children at three time points (left to right: birth, 6 months, 12 months) compared with the WHO standard (p > 0.05 at all time points).

Child’s weight at birth, at 1 and 6 months, but not at 12 months, was also positively associated with maternal BMI before pregnancy (p = 0.0007, p = 0.006, p = 0.007, p = 0.1, respectively). Although a positive association was detected overall, it is mostly related to mothers with obesity (BMI > 30), as depicted in Figure 4. The Spearman’s correlation coefficient and p-values between mother’s pre-pregnancy BMI and each child’s weight point are presented as graphs. The differences in child’s body mass according to different categories of maternal BMI were adjusted for smoking, gender, and breastfeeding (in the case of birth weight only by smoking and gender). Maternal GWG did not show a significant association with child anthropometry in the first year of life.

Figure 4. The correlation between maternal pre-pregnancy BMI and (a) child’s birth weight; (b) child weight at 1 month; (c) child weight at 6 months; and (d) child weight at 12 months.

Breastfeeding did not show a significant association with child anthropometry in the first year of life. However, it was observed that maternal education (r = 0.3699, 95% CI = 0.19–0.53, p = 0.0001) and average monthly household income (r = 0.24, 95% CI = 0.05–0.42, p = 0.0143) had a positive association with the duration of breastfeeding. Namely, wealthier women with higher educational attainment from the city of Split breastfed for longer.

The association of infant weight at four time points in the first year of life with maternal SES and lifestyle is presented in Table 3. Although individual p-values were significant, the overall models (for each time point) did not provide enough statistical power for confirming the link between maternal education, working status, income, and smoking, and infant anthropometric characteristics in the first year of life.

Table 3. Association of maternal characteristics with infant weight at four time points.

Infant weight	Maternal characteristics	β	p-value	R^2
At birth	Education	−159.211	0.226	0.085
	Working status	−221.418	0.076	0.085
	Financial status	94.287	0.432	0.085
	Smoking status	104.848	0.136	0.085
1 month	Education	−5.918	0.971	0.072
	Working status	−360.697	0.019	0.072
	Financial status	97.528	0.508	0.072
	Smoking status	78.779	0.359	0.072
6 months	Education	−151.774	0.434	0.124
	Working status	−529.925	0.005	0.124
	Financial status	138.593	0.434	0.124
	Smoking status	158.341	0.127	0.124
12 months	Education	−32.444	0.925	0.063
	Working status	−690.641	0.037	0.063
	Financial status	−52.753	0.868	0.063
	Smoking status	207.604	0.262	0.063

Additionally, child anthropometry at 6 and 12 months has been observed to be associated with maternal dietary habits, namely the Mediterranean Diet Serving Score (MDSS) calculated for all CRIBS mothers and described in detail in the previous CRIBS publication (Havaš Auguštin et al. 2020). More than 80% of mothers in this study reported low adherence to the Mediterranean diet during pregnancy. The Spearman’s correlation coefficient and p-values for the association between maternal MDSS and child Z-scores from 6 to 12 months (when a child’s nutrition is becoming more similar to the mother’s) are presented in Table 4. The results show that in the families of children with higher Z-score values, mothers have a low MDSS, indicating poor familial dietary habits.

Table 4. Association of maternal MDSS score with different weight-related child Z-score values at 6 and at 12 months.

MDSS score
	R	95% CI	p-value
Weight-for-length Z-score at 6 months	9.74E-06	[−0.02, 0.2]	0.049
Weight-for-age Z-score at 6 months	−0.164	[−0.35 0.03]	0.370
BMI-for-age Z-score at 6 months	0.011	[−0.19 0.21]	0.051
Weight-for-length Z-score at 12 months	−0.229	[−0.41 − 0.03]	0.026
Weight-for-age Z-score at 12 months	−0.304	[−0.48 − 0.11]	0.003
BMI-for-age Z-score at 12 months	−0.169	[−0.36 0.03]	0.102

Discussion

This study was initiated out of the necessity to build upon the limited literature currently available on the impact of breastfeeding, maternal SES, and lifestyle on child growth and obesity development in Croatia. For this purpose, infant size and early growth trajectories and their associations with maternal characteristics and breastfeeding patterns were investigated within the CRIBS birth cohort. Our study suggested that: (i) risk factors for obesity development are not highly pronounced, but are still detectable in the first year of life; and (ii) more effective BMI monitoring and promotion of healthy diet and lifestyle before and during pregnancy is needed, especially in smaller, rural island communities.

The distribution of children within genders and their mean birth weight were as reported in Šarac et al. (2022). Significant differences in all anthropometric characteristics were observed between genders, but both males and females showed normal growth in weight. They were generally slightly bigger than WHO growth standards, but no major deviations have been noticed in their Z-score values. When mean birth weights were compared with the data on 2,711 children from the Childhood Obesity Surveillance Initiative (COSI) - Croatia 2018/2019, boys in the CRIBS study were on average heavier at birth (3,495.3 g in CroCOSI vs. 3,711.76 g in the present study). These differences could perhaps be explained by considerable regional variation in weight and height that exists in Croatia. The southern Dalmatian parts of the country, encompassing the region where the CRIBS study was performed, exhibit certain growth specificities. Namely, the highest values for all anthropometric measurements, especially height, have been recorded for young males from the Split-Dalmatia County. Dalmatians are currently among the tallest populations in Europe, with a mean height of 184.1 cm (Smolej-Narančić 1999; Grasgruber et al. 2019), which could explain the higher anthropometric values of infants within the CRIBS cohort.

When looking at the connection between pregnancy and infant growth, the nutritional status of a pregnant woman shapes infant growth in the first year of life and it is believed to be a good predictor of adverse long-term outcomes for both the infant and the mother (Sun et al. 2020). In our study, a significant correlation existed between maternal pre-pregnancy BMI and infant growth in the first 6 months – mothers that entered their pregnancy with a high BMI, and especially ones with obesity, also gave birth to bigger babies and this correlation stays persistent until 6 months. This finding suggests that obesity prevention in children should actually start with obesity prevention among young women of childbearing age. At 1 year, however, this connection was no longer visible, indicating that other factors become more important with time, such as nutrition.

Nutrition in pregnancy has also been recognised as an important modifiable environmental factor influencing child growth and development. The coastal part of Croatia is geographically and traditionally a part of the wider Mediterranean area and the main diet on the Dalmatian islands has historically been the Mediterranean diet. However, over the course of the last century the way of living has changed radically – globalisation and population transition, as well as the general depopulation trend in island populations have brought new trends and lifestyles. Recent research has shown that the situation in Croatia reflects the trends in other Mediterranean countries, which is westernisation of diet and a shift to less healthy food choices, especially in younger generations (Šarac et al. 2021.; Gerić et al. 2022). Women in our study demonstrated low compliance with the Mediterranean diet (only 20% report healthy eating habits), although healthy dietary habits should be a high priority during pregnancy. When compared to the child anthropometry, our results suggest that mothers who reported low adherence to a healthy diet also have children that were bigger at 6 and 12 months. This finding is supported by previous studies reporting an association between maternal adherence to the Mediterranean diet during pregnancy and offspring outcomes, such as adiposity (Chatzi et al. 2017; Eckl et al. 2021).

More than 40% of CRIBS mothers in this study breastfed exclusively for at least 6 months, which is significantly higher than the European average of approximately 25% children being breastfed at 6 months (Theurich et al. 2019). A similar percentage of Croatian mothers from the COSI study who breastfed for at least 6 months was observed (Rito et al. 2019). However, differences between island and mainland settings were recognised. The traditional island setting considers women living in households with more members and lower income, whilst in the urban mainland population less people live in joint households, and people are generally more educated and have a higher income. These observed sociodemographic profile differences are in line with the reported results for previous CRIBS studies (Perinić Lewis et al. 2019; Šarac et al. 2022) and can to a certain extent explain the differences in breastfeeding rates and higher breastfeeding prevalence on the mainland and among women with higher SES. Namely, low socioeconomic status is one of the major barriers to breastfeeding which contributes to the further increase in health inequalities worldwide and development of obesity (Chimoriya et al. 2020; Horta et al. 2023). Numerous studies report strong associations between sociodemographic factors and breastfeeding and show that much of the variation in breastfeeding rates is explained by the sociodemographic profile (Oakley et al. 2013; Victora et al. 2016; Chimoriya et al. 2020). It has also been suggested that the protective effect of exclusive breastfeeding in early childhood is associated with a considerably lower BMI and fat mass values at the age of 6 (Rito et al. 2019; Hildebrand et al. 2022). Although exclusive breastfeeding rates are significant in our study, the results did not show an association between breastfeeding patterns and infant growth in the first year of life. Our study highlighted different maternal characteristics related to child anthropometry at different time points, indicating that SES is a factor that should be considered in the long-term when looking at child growth. However, we did not detect a single maternal variable which would predominantly and consistently be linked to child size and early growth in the first year of life. It seems the impact of maternal characteristics and breastfeeding is more pronounced in the pre-school and school period (from 4 years onwards), thus CRIBS children are perhaps still too young to allow for any clear conclusions and their follow-up in subsequent years is necessary, as seen elsewhere (Pruszkowska-Przybylska et al. 2019).

Strengths and limitations

The major strengths of this study are that it presents the first longitudinal study of child early growth in Croatia and that it encompasses data from both mothers and their children. The major limitation of this study is the small sample size. The short observation period could be considered as a second limitation and more follow-up is needed to draw any far-reaching conclusions. Future studies on this topic should be conducted on a larger sample size and should include more covariables. They should also include participants from other parts of Croatia to gain more representative results. It is also important to stress that body composition would be a better indicator of maternal nutritional status and overweight or obesity. However, routine gynaecological examinations used in this study include BMI measurements, since body composition analysis requires additional equipment, currently unavailable in Croatian islands.

Conclusion

Early growth and development of CRIBS children is in line with previous results and expected values. Given the high rates of childhood overweight and obesity in Croatia at the age of 8–9, we can conclude that risk factors for obesity development are detectable in the first year of life, but not highly pronounced. New follow-ups and screening of pre-school children (aged 3–4) are necessary to catch the first signs of this negative trend. However, the finding that child weight gain is associated with maternal BMI before pregnancy is important and calls for more effective monitoring of pre-pregnancy BMI in regular pre- and perinatal maternal health surveillance and much earlier weight monitoring in general among young women of childbearing age. Additionally, the established connection between maternal dietary habits and child weight suggests it is necessary to raise awareness and encourage mothers to adopt healthy and sustainable lifestyles and eating patterns, especially in pregnancy and in smaller, rural island communities.

Acknowledgements

The authors thank participants of the CRIBS cohort for their commitment and willingness to join the study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data presented in the paper are part of the database of the Institute for Anthropological Research and can be made available upon request.

Additional information

Funding

This project was funded by the Croatian Science Foundation under the grant number HRZZ UIP-2014-09-6598.