Maternal body mass index in early pregnancy is associated with overweight and obesity in children up to 16 years of age.

AIMS: Childhood obesity is an increasing public health problem. The aim of this study was to investigate the correlation between maternal body mass index in early pregnancy and body mass index in children up to the age of 16 years, and to estimate the prevalence of childhood overweight and obesity in a rural municipality in Sweden.
METHODS: The study population comprised 312 pregnant women who attended the antenatal clinics in Lidköping during the year 1999 and their 319 children. Data on body mass index from antenatal clinics, child health care centres and school health care were used in linear and multinomial logistic regressions adjusted for maternal age, smoking status, and parity.
RESULTS: Overweight or obesity were found in 23.0% of 16-year-olds. The correlation between maternal and child body mass index at all studied ages was positive and significant. Body mass index in 16-year-old boys showed the strongest correlation with maternal body mass index (adjusted r-square = 0.31). The adjusted relative-risk ratio for 16-year old children to be classified as obese as compared to normal weight, per 1 unit increase in maternal body mass index was 1.46 (95% confidence interval 1.29-1.65, p<0.001). Among adolescents with obesity, 37.6% had been overweight or obese at 4 years of age.
CONCLUSIONS: This study confirms the correlation between maternal and child body mass index and that obesity can be established early in childhood. Further, we showed a high prevalence of overweight and obesity in children, especially in boys, in a Swedish rural municipality. This suggests a need for early intervention in the preventive work of childhood obesity, preferably starting at the antenatal clinic and in child health care centres.

Introduction

Obesity is a major and increasing public health problem among children all over the world and it results in huge societal costs [1-4]. The prevalence of overweight and obesity is increasing in both high-income and low-income countries, even though the increase seems to level out during later years in western countries such as Sweden where the national prevalence of overweight, including obesity, was 12.8% for girls and 16.0% for boys 12 years old in 2016 [5]. The prevalence has been shown to be lower among children who live in urban areas and/or have mothers with higher education [2, 3]. The Public Health Agency of Sweden reported overweight and obesity in 21% of Swedish high school students 16–19 years old in 2020. European studies have shown a correlation between body mass index (BMI) in early childhood and BMI later in adolescence and early adulthood and that adolescents with obesity were obese from the age of 5 years with accelerating BMI between 2 and 6 years of age [4, 6]. Thus, increasing BMI in children predicts overweight and obesity in adolescence and is therefore a target for preventive measures.

Childhood obesity may increase the risk of asthma, psychological illness and sleep disturbances and long-term effects such as infertility, diabetes type 2, hypertension, ischemic heart disease, stroke, and arthritis [7]. Even in early adulthood, individuals with obesity in childhood have an increased risk of death [8].

Twin and adoption studies have suggested that genetic factors contribute up to 70% of BMI, but environmental factors contribute as well [9]. In these studies, the genetic impact was lowest in mid-childhood and increased in the teens. Numerous studies have shown an association between maternal overweight and obesity versus overweight and obesity among their children in different ages, and in most studies maternal BMI (mBMI) is positively associated with child BMI [10, 11]. However, in many of these studies children were only followed until early or mid-childhood. Several studies have shown a stronger correlation between mBMI and child BMI, compared to paternal BMI and child BMI [12, 13], suggesting that in addition to genetic influences, the in utero environment may have an impact on the child’s growth later in life [14]. The impact of adverse uterine environment factors on metabolic traits later in life differs between the sexes as described in a newly published review [15]. However, while some observational studies indicate that boys may have a higher risk of developing obesity following maternal over-nutrition [16] the opposite has also been found [17].

As there are few longitudinal studies that investigate the correlation of BMI between mother and child, the aim of this study was to explore the correlation between the mother´s BMI in early pregnancy and BMI in boys and girls up to the age of 16 years. The aim was also to investigate the prevalence of overweight and obesity and the development of BMI from early childhood into adolescence.

Material and methods

Setting

In Sweden, all pregnant women are offered free healthcare and monitoring at antenatal clinic during pregnancy and the children are offered free health care at Child Health Care (CHC) centres that focus on prevention of diseases and injuries. Growth is regularly measured up to the age of 6 years by specialized nurses and the children are offered vaccinations. About 99% of children in Sweden aged 0–6 years participate in the program [18]. Thereafter, school healthcare with specialized nurses offers regular health visits up to 12th grade.

Study population

The municipality Lidköping, in southwestern Sweden had approximately 38 000 inhabitants in 1999 and consists of a small urban area surrounded by rural areas. The study population comprised all pregnant women who attended the antenatal clinics during the year 1999 and their children born 1999–2000. From medical records of the first visit in early pregnancy data on age of the pregnant woman, gestational week, parity, height, weight, BMI, and smoking habits were retrieved. The children were identified by using the unique personal identity number assigned to each Swedish resident [19] in the medical records from the CHC centres. Information about date of birth, sex, gestational age, birth height, birth weight, body height and weight at 1- and 4-year routine check-ups were collected. Data from mother and child pairs were linked in a register. The register was completed with data on body weight and height at the ages of 7, 10, 13 and 16 years as well as date of examination at school healthcare. If data from multiple visits were available for a child, we chose the visit closest to 7, 10, 13 and 16 years of age. A population register was used to locate the children’s home address to find the schools of children who had moved. The study was approved by the Regional Ethics Review Board in Gothenburg (reference 935–18). Informed consent was not retrieved from the studied individuals since we are reporting results from retrospective data from registers. The need for consent was waived by the ethics committee.

Overweight and obesity

BMI was calculated for both mother and child using weight and height registered in the medical records from the antenatal clinics, CHC centres and school health care. For the mother underweight was defined according to the World Health Organisation as BMI <18.5 kg/m2, normal weight as BMI 18.5–24.9 kg/m2, overweight as BMI 25.0–29.9 kg/m2, and obesity as BMI ≥30.0 kg/m2 [20]. Mothers with underweight were categorized as normal weight in the analyses due to the small number (n = 2). Because BMI in children varies naturally with age, overweight and obesity were assessed using iso-BMI with cut-offs for overweight and obesity according to the classification by Cole et al. [21] on exact age at time of examination. Likewise, underweight was classified using the iso-BMI cut-off scale [22]. Iso-BMI is useful from 2 years of age and therefore overweight and obesity was not assessed at birth and at the age of 1, instead body weight was used to compare with mBMI.

Statistical methods

Descriptive statistics were used to describe the study population and the prevalence of overweight and obesity in the pregnant mothers and their children in different age groups. Chi2-test was used to explore sex differences in prevalence of overweight and obesity, as compared to under- or normal weight in each child age group. Difference in median weight and BMI according to sex was tested by the Mann-Whitney test. Univariate linear regression was used to analyse the association between mBMI in early pregnancy and child BMI at 4, 7, 10, 13 and 16 years of age, for the whole study population and for boys and girls separately. Up to 1 year of age body weight was used in the linear regression to analyse association with mBMI. In an additional linear regression model, analyses were adjusted for maternal age, parity and smoking. Multinomial logistic regression was used to calculate relative-risk ratios with 95% confidence intervals (CI) for 4, 7, 10, 13, and 16 year old children to be underweight, overweight or obese as compared to normal weight per 1 unit increase in mBMI, and additionally per 5 units increase in mBMI to correlate to a 1 step increase in mBMI-category from normal weight to overweight to obesity. In an adjusted model, maternal age, parity and smoking were used as covariates. As some mothers had multiple births, robust standard errors were used in the linear and multinomial logistic regression models. We also divided the 16 year-olds into 4 subgroups according to weight class (underweight, normal weight, overweight or obesity) and determined the percentage of children with underweight, normal weight, overweight or obesity at 4, 7, 10 and 13 years for each subgroup to track development of BMI during childhood. All analyses were performed with the use of Stata version 17.0 (Stata Corp., College station, TX, US). All tests were two-tailed and conducted at 0.05 significance level.

Results

Clinical characteristics of the mothers

The number of pregnancies registered at the antenatal clinics in Lidköping during 1999 were 371, Fig 1. The study population finally consisted of 312 mothers and their 319 children. The women were 28.8±5.0 years and the first visit at the clinic was at 11.5±2.0 weeks of pregnancy, Table 1. Parity varied between 0–7 with median of 1 (interquartile range 2). BMI in mothers was 24.7±4.1 kg/m2. The prevalence of overweight and obesity was 25.3% (n = 79) and 11.2% (n = 35) respectively.

Fig 1

Flow chart of mother and child pairs.

Table 1

Characteristics of women at time of enrollment at the antenatal clinic in Lidköping 1999 presented in body mass index (BMI) classification groups.

	Total (n = 312)	Normal weight* (n = 198)	Overweight (n = 79)	Obesity (n = 35)
Age (years)	28.8 (5.0)	28.6 (5.0)	29.4 (5.1)	29.2 (4.9)
Height (cm)	166.4 (5.6)	166.7 (5.7)	165.4 (5.4)	166.9 (5.4)
Weight (kg)	68.5 (12.2)	61.9 (6.5)	74.3 (5.8)	92.8 (10.5)
BMI (kg/m2)	24.7 (4.1)	22.3 (1.7)	27.1 (1.2)	33.2 (2.6)
Parity	1.0 (2.0)	1.0 (1.0)	1.0 (2.0)	1.0 (2.0)
Gestational week	11.5 (2.0)	11.4 (1.8)	11.5 (2.1)	11.9 (2.5)
Smoking, yes	20 (6.4)	11 (5.6)	5 (6.3)	4 (11.4)

Mean (standard deviation) is presented for continuous variables except for parity where median (interquartile range) is presented. For categorical variables n (%) is presented.

Overweight is defined as BMI 25.0–29.9 kg/m2 and obesity as BMI ≥30.0 kg/m2.

*Underweight (n = 2) is classified as normal weight.

Clinical characteristics of the children

New-born boys (n = 168) were slightly heavier than girls (n = 151) (median weight 3.77 kg versus 3.49 kg, p = 0.0012) and this difference remained until 1 year of age (median weight 10.52 kg versus 9.90 kg, p<0.001). Median BMI for boys and girls at 4, 7, 10, 13, and 16 years of age showed no sex differences and BMI increased with increasing age for both sexes. At 4 years of age, the proportion of girls classified as either having overweight or obesity as compared to under- or normal weight was significantly larger than among boys (24.5% versus 15.0%, p = 0.032), Fig 2. At 7, 10 and 13 years there was no such difference. From 13 to 16 years of age the prevalence of obesity increased for both boys and girls to 8.3% and 3.1%, respectively. At the age of 16 years the proportion of boys and girls with either overweight or obesity were 30.5% versus 14.6% (p = 0.002). In all 16-year-old children (n = 274) 23.0% had either overweight or obesity.

Fig 2

Distribution of body mass index (BMI) classes according to the isoBMI classification in children born 1999–2000 in the municipality Lidköping at different ages for boys (A) and girls (B) separately.

Association between maternal BMI in early pregnancy and child weight/BMI

There was a positive, significant association between mBMI in early pregnancy and the child’s body weight at birth and at 1 year. Overall, there was a positive significant association between mBMI and child BMI from 4 to 16 years for the whole study group, Table 2. The strongest association was found between mBMI and BMI for 16-year-old boys where one BMI unit increase in mBMI was associated with a 0.56 kg/m2 (95% CI 0.37–0.76, p<0.001) increase in child BMI in the adjusted model.

Table 2

Association between maternal body mass index in early pregnancy and child weight at birth and 1 year, and child body mass index at 4, 7, 10, 13 and 16 years for the entire study population and for boys and girls separately.

	Unadjusted model Beta (95% CI)	R-square	p-value	Adjusted model Beta (95% CI)	R-square	p-value
Maternal body mass index versus child weight in kg
Birth	0.04 (0.02–0.05)	0.06	<0.001	0.03 (0.02–0.05)	0.09	<0.001
Boys, n = 168	0.03 (0.01–0.05)	0.06	0.006	0.03 (0.006–0.05)	0.09	0.010
Girls, n = 151	0.05 (0.02–0.07)	0.05	0.003	0.04 (0.009–0.07)	0.09	0.011
1 year age	0.07 (0.03–0.10)	0.05	<0.001	0.06 (0.03–0.10)	0.08	<0.001
Boys, n = 168	0.05 (0.01–0.09)	0.04	0.007	0.05 (0.009–0.09)	0.07	0.016
Girls, n = 151	0.07 (0.004–0.14)	0.04	0.039	0.07 (-0.002–0.13)	0.10	0.057
Maternal body mass index versus child body mass index
4 years age	0.10 (0.07–0.14)	0.10	<0.001	0.11 (0.07–0.14)	0.11	<0.001
Boys, n = 167	0.10 (0.06–0.15)	0.13	<0.001	0.11 (0.06–0.15)	0.14	<0.001
Girls, n = 151	0.12 (0.04–0.19)	0.07	0.002	0.12 (0.05–0.19)	0.10	0.001
7 years age	0.22 (0.14–0.29)	0.19	<0.001	0.21 (0.14–0.29)	0.21	<0.001
Boys, n = 164	0.23 (0.13–0.33)	0.24	<0.001	0.23 (0.13–0.32)	0.26	<0.001
Girls, n = 150	0.19 (0.09–0.29)	0.11	<0.001	0.19 (0.09–0.29)	0.14	<0.001
10 years age	0.29 (0.20–0.38)	0.19	<0.001	0.29 (0.21–0.38)	0.21	<0.001
Boys, n = 164	0.32 (0.20–0.44)	0.25	<0.001	0.32 (0.20–0.43)	0.27	<0.001
Girls, n = 150	0.24 (0.12–0.35)	0.10	<0.001	0.26 (0.15–0.38)	0.13	<0.001
13 years age	0.34 (0.23–0.45)	0.18	<0.001	0.35 (0.24–0.46)	0.19	<0.001
Boys, n = 163	0.39 (0.24–0.53)	0.24	<0.001	0.39 (0.23–0.54)	0.25	<0.001
Girls, n = 149	0.27 (0.14–0.40)	0.10	<0.001	0.28 (0.14–0.42)	0.11	<0.001
16 years age	0.47 (0.33–0.62)	0.22	<0.001	0.48 (0.33–0.63)	0.24	<0.001
Boys, n = 144	0.55 (0.36–0.74)	0.29	<0.001	0.56 (0.37–0.76)	0.31	<0.001
Girls, n = 130	0.27 (0.10–0.44)	0.08	0.002	0.26 (0.07–0.44)	0.11	0.006

The adjusted model was adjusted for maternal age, smoking status, and parity.

Maternal BMI and risk of child overweight or obesity

Relative-risk ratios for children 4, 7, 10, 13 and 16 years of age to be classified as overweight or obese as compared to normal weight, per 1 unit increase in mBMI is presented in Table 3, and per 5 unit increase in mBMI in S1 Table. For example, the relative-risk ratio for 16-year-olds to be classified as obese as compared to normal weight in the adjusted model was 1,46 (95% CI 1.29–1.65) if mBMI increased with 1 unit.

Table 3

Relative-risk ratios (RRR) for 4, 7, 10, 13, and 16-year old children to be classified as underweight, overweight or obese as compared to normal weight, per 1 unit increase in maternal body mass index.

	Total		Boys		Girls
	RRR (95% CI)	p-value	RRR (95% CI)	p-value	RRR (95% CI)	p-value
4 years old
Unadjusted model
Normal weight	1 (reference)		1 (reference)		1 (reference)
Underweight	0.96 (0.84–1.11)	0.61	0.95 (0.78–1.15)	0.60	0.99 (0.80–1.24)	0.96
Overweight	1.17 (1.09–1.26)	<0.001	1.24 (1.13–1.36)	<0.001	1.15 (1.02–1.30)	0.018
Obesity	1.34 (1.13–1.57)	0.001	1.52 (1.08–2.14)	0.017	1.43 (1.01–2.04)	0.046
Adjusted model
Normal weight	1 (reference)		1 (reference)		1 (reference)
Underweight	0.97 (0.84–1.11))	0.63	0.96 (0.79–1.16)	0.66	0.98 (0.78–1.23)	0.86
Overweight	1.17 (1.09–1.26)	<0.001	1.24 (1.11–1.38)	<0.001	1.17 (1.03–1.34)	0.016
Obesity	1.32 (1.15–1.52)	<0.001	1.36 (1.10–1.68)	0.005	1.48 (0.93–2.36)	0.097
7 years old
Unadjusted model
Normal weight	1 (reference)		1 (reference)		1 (reference)
Underweight	0.95 (0.82–1.10)	0.49	0.86 (0.71–1.04)	0.11	1.13 (0.88–1.45)	0.35
Overweight	1.19 (1.10–1.29)	<0.001	1.20 (1.09–1.32)	<0.001	1.18 (1.02–1.36)	0.031
Obesity	1.41 (1.28–1.56)	<0.001	1.41 (1.24–1.60)	<0.001	1.49 (1.26–1.77)	<0.001
Adjusted model
Normal weight	1 (reference)		1 (reference)		1 (reference)
Underweight	0.96 (0.83–1.10)	0.54	0.87 (0.73–1.03)	0.097	1.09 (0.90–1.31)	0.39
Overweight	1.19 (1.09–1.29)	<0.001	1.19 (1.08–1.32)	0.001	1.16 (0.99–1.36)	0.063
Obesity	1.40 (1.26–1.55)	<0.001	1.40 (1.24–1.58)	<0.001	1.57 (1.26–1.94)	<0.001
10 years old
Unadjusted model
Normal weight	1 (reference)		1 (reference)		1 (reference)
Underweight	0.88 (0.77–1.01)	0.068	0.87 (0.72–1.04)	0.13	0.89 (0.73–1.10)	0.29
Overweight	1.21 (1.12–1.31)	<0.001	1.24 (1.12–1.37)	<0.001	1.19 (1.04–1.37)	0.012
Obesity	1.54 (1.27–1.87)	<0.001	1.74 (1.32–2.31)	<0.001	1.22 (0.99–1.49)	0.063
Adjusted model
Normal weight	1 (reference)		1 (reference)		1 (reference)
Underweight	0.87 (0.76–1.00)	0.056	0.86 (0.72–1.02)	0.089	0.85 (0.69–1.05)	0.13
Overweight	1.22 (1.12–1.32)	<0.001	1.24 (1.11–1.37)	<0.001	1.22 (1.05–1.42)	0.008
Obesity	1.52 (1.25–1.85)	<0.001	1.65 (1.25–2.16)	<0.001	1.17 (1.01–1.36)	0.040
13 years old
Unadjusted model
Normal weight	1 (reference)		1 (reference)		1 (reference)
Underweight	0.85 (0.71–1.01)	0.063	0.85 (0.64–1.14)	0.28	0.85 (0.68–1.06)	0.15
Overweight	1.19 (1.11–1.29)	<0.001	1.16 (1.06–1.26)	0.002	1.29 (1.11–1.49)	0.001
Obesity	1.54 (1.30–1.82)	<0.001	1.51 (1.27–1.80)	<0.001	1.47 (0.94–2.32)	0.091
Adjusted model
Normal weight	1 (reference)		1 (reference)		1 (reference)
Underweight	0.84 (0.72–0.99)	0.033	0.82 (0.63–1.06)	0.13	0.85 (0.68–1.05)	0.13
Overweight	1.19 (1.10–1.29)	<0.001	1.16 (1.05–1.28)	0.003	1.30 (1.10–1.54)	0.002
Obesity	1.54 (1.30–1.84)	<0.001	1.50 (1.27–1.77)	<0.001	1.56 (0.95–2.55)	0.077
16 years old
Unadjusted model
Normal weight	1 (reference)		1 (reference)		1 (reference)
Underweight	0.89 (0.75–1.06)	0.19	0.90 (0.71–1.14)	0.37	0.88 (0.69–1.13)	0.32
Overweight	1.21 (1.11–1.32)	<0.001	1.22 (1.09–1.36)	<0.001	1.15 (0.98–1.36)	0.094
Obesity	1.42 (1.26–1.60)	<0.001	1.46 (1.27–1.67)	<0.001	1.26 (0.92–1.73)	0.15
Adjusted model
Normal weight	1 (reference)		1 (reference)		1 (reference)
Underweight	0.93 (0.79–1.08)	0.34	0.95 (0.78–1.16)	0.59	0.91 (0.73–1.14)	0.43
Overweight	1.24 (1.13–1.35)	<0.001	1.25 (1.11–1.41)	<0.001	1.17 (0.99–1.38)	0.065
Obesity	1.46 (1.29–1.65)	<0.001	1.52 (1.32–1.76)	<0.001	1.41 (0.98–2.03)	0.068

The adjusted model was adjusted for maternal age, smoking status, and parity.

Trajectories of BMI from 4 years of age to adolescence

Fig 3 shows the retrospective trajectories of BMI at 4, 7, 10 and 13 years of age, presented as percentage of children who were underweight, normal weight, overweight, or obese at these ages according to their weight class at 16 years age. None of the 16-year olds with underweight were either overweight or obese earlier in life (Fig 3A). Among 16-year olds with normal weight, the majority had a normal weight throughout childhood (Fig 3B). For 16-year-olds with overweight 31.9% were overweight or obese at the age of 4 (Fig 3C). Most adolescents with obesity had a normal weight at 4 years of age, but 37.6% were either overweight or obese at this age (Fig 3D).

Fig 3

Development of weight class according to the isoBMI classification from early childhood to adolescence for children born 1999–2000 in Lidköping, divided into the weight class at 16 years; underweight (A), normal weight (B), overweight (C) and obesity (D).

Discussion

Main findings

This study showed that mBMI in early pregnancy was positively associated with child BMI throughout childhood to the age of 16 years and the correlation was strongest between mothers and 16-year-old sons. The risk of overweight or obesity at 16 years of age increased with increasing mBMI. In addition, most adolescents with normal weight had normal weight throughout childhood. We also found that the prevalence of overweight and obesity in 16-year-old children born 1999–2000 in the municipality Lidköping was 23.0%.

Strengths and limitations

The major strength of this study is the longitudinal design with maternal data from early pregnancy up to 16 years of age for the children. As the Swedish health care system offers free visits in both antenatal clinics and CHC centres we most likely included the majority of pregnant women and their children during 1999–2000. Data was available at several time points throughout childhood for most children, which enables estimations of prevalence of overweight and obesity at different ages. We used reliable measurements from antenatal clinics, CHC and school health care for calculating BMI/isoBMI and not self-reported body weight and height as in many other studies.

There are some limitations of the study, including a relatively small sample size. Further, the study population was homogeneous in terms of ethnicity, which limits the generalizability of the results. We had no information about maternal diabetes or gestational weight gain, both known to increase the risk of overweight and obesity in the offspring [23]. Also, information about other confounding factors, such as paternal BMI or socio-economic status was missing. Further, there were neither data on chronic illnesses or medication in the children nor data on lifestyle, which could have affected BMI progression. We used BMI as a proxy to assess overweight and obesity. This is a well-established method, but not as accurate as measuring body fat percentage since a higher amount of muscle mass could result in a higher BMI. Finally, BMI was recorded up to 15 weeks into pregnancy, which might not have been representative as pre-pregnancy BMI. However, Krukowski et al. [24] argued that most women are correctly classified in BMI classes based on a first trimester weight.

Findings in relation to other studies

The prevalence of overweight or obesity at the age of 4 years (2003–2004) was 19.5% in our study compared to 11% in a report from Swedish Public Health Agency where almost all Swedish 4-year-old children were included 2018 [5]. A Swedish study from 2016 showed a national prevalence of overweight, including obesity, of 16.0% for boys and 12.8% for girls 12 years old [2]. In our study the corresponding prevalence for boys at the age of 13 years (2012–2014) was 23.3% and for girls 18.8%. This is higher than the national prevalence a few years later. In a recent report from Swedish Public Health Agency overweight and obesity were found in 21% of Swedish high school children [5] and in our study the prevalence was 23.0%. This difference might be a trend of decreasing prevalence of overweight and obesity during the later years. Our results could be explained by regional differences of overweight and obesity as our study population lived in a rural area where the frequency of overweight and obesity has been shown to be higher than in urban areas [25]. Of note, compared to other high-income Western countries the estimated percentage of children being obese is much lower in our studied population. The prevalence of childhood obesity in high-income Western countries 2016 was 16.8% for boys and 13.3% for girls aged 5–19 [26]. In our study the highest estimation of obesity was 8.3% for 16-year old boys.

The correlation between mBMI before or in early pregnancy and child BMI has been well established in earlier studies [10, 11]. Our result is in line with these studies and the correlation was positive for both sexes in all studied ages up to 16 years. The association is most likely due to a complex combination of genetic factors, environmental and behavioural factors during childhood where the lifestyle of the family plays a big part [27, 28]. The environment in utero also seems to have impact on a child’s future growth and body composition. Pregnant women with overweight and particularly obesity transfer higher amounts of glucose, amino acids and free fatty acids through the placenta to the foetus compared to women with normal weight. This could result in permanent changes in control of appetite and energy metabolism in the developing foetus, resulting in overweight and obesity later in life [29]. In later years, research has also focused on epigenetic processes and how the environment in utero modifies genes expression, for example through DNA-metylation [30]. New technologies are used in order to study genetic and in utero causes of overweight and obesity in offspring such as Mendelian randomization [31]. Also, genetic imprinting and DNA methylation might play important roles for future risk assessment of obesity [15]. It seems clear that having a mother with overweight or obesity increases the child’s risk of having overweight or obesity but the exact mechanisms behind the causality are not yet understood. Our study gives no further explanation on the matter but confirms the association and emphasizes the need for further studies.

In our study the correlation between mBMI and child BMI grew stronger with increasing age in boys, but not in girls where the correlation overall was weaker. This suggests that maternal overweight and obesity may affect boys negatively to a higher degree than girls, which has been found in other studies [16, 25]. However, the opposite was found among 226 Swedish siblings [17], where a higher pre-pregnancy BMI was associated with increasing percentage fat mass in offspring in late adolescence, particular in daughters.

The sex difference in development of obesity depends on a multitude of factors including differential gene expression due to differences between the sexes in mRNA splicing, sex hormone effects, epigenetic mechanisms, mitochondrial and placental function [15]. In addition, the psychological pressure from peers and internet especially in teenage girls could influence the weight and bodily development [32]. The bodily changes during childhood and adolescence differ between individuals and occur at different points of time for instance occurrence of puberty [33]. These might be confounders in the analyses and could result in different outcomes in boys and girls and also explain deviating results in different studies.

A large German population-based study found that overweight and obesity manifested early in childhood and among overweight or obese adolescents, BMI had accelerated between 2 and 6 years of age [4]. In the current study we tracked BMI from 4 years of age and throughout childhood and found that 37.6% of 16-year olds with obesity had already had overweight or obesity early in childhood, indicating that early childhood may be a critical period for the development of sustained obesity. Epidemiological studies have previously shown that the risk of childhood obesity increases with an early “adiposity rebound”, the phase in childhood during which BMI starts to increase [34].

Conclusions

Our study confirms the correlation between maternal body mass index in early pregnancy and body mass index in children up to the age of 16 years. The prevalence of childhood overweight and obesity in the rural municipality we have studied was higher than previously reported nationally in Sweden. Our longitudinal study also confirms that obesity can be established in early childhood, which highlights the need for early intervention in the preventive work to combat childhood obesity, preferably starting at the antenatal clinic and follow-up in CHC centres and schools.

Relative-risk ratios (RRR) for 4, 7, 10, 13, and 16-year old children to be classified as underweight, overweight or obese as compared to normal weight, per 5 unit increase in maternal body mass index.

(DOCX)

Click here for additional data file.

21 Jul 2022

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We are deeply grateful to the nurses at the antenatal clinics, CHC centres and schools for their help during acquisition of data. The work was supported by the Skaraborg research and development council (grant: VGFOUSKB-869761).

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

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Reviewer #2: No

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Reviewer #1: This study by Önnestam et al. explores the longitudinal association between maternal BMI in early pregnancy and body mass index in children up to the age of 16 years in a regional Swedish population. Overall, this prospective study is well designed, method is appropriate, and the results are clear and well organized. The manuscript is interesting and has strengths, including repeated measurements over time. Some comments and suggestions are as follows:

1. In the last paragraph of the introduction, one of the objectives stated includes exploration of the correlation between maternal BMI and child BMI in gender-specific subgroups. However, there is no context provided as to why these subgroups were investigated. It would be helpful to provide context for this objective by adding a few lines in an earlier paragraph as to why analyzing BMI in boys and girls separately is important based on what is known from literature about sex-based differences in BMI.

2. Overall, the methodology is clearly explained. The results are also displayed clearly and sequentially. Information in the tables is also presented clearly.

3. In the results section, while the association between maternal BMI and child weight/BMI has been explored at all defined ages (i.e. 4, 7, 10, 13, 16), the association between maternal BMI and risk of child overweight or obesity has only been assessed at the age of 16. It may be interesting to also see association between maternal BMI and child obesity/overweight risk at the other specified ages as well. In addition, the authors may consider adding analysis that investigates maternal BMI as a categorical variable based on weight status (normal weight, overweight, or obese) in association with risk of child overweight/obesity (currently maternal BMI has only been analyzed as a continuous variable). This may provide clinically practical results for groups of pregnant women who fall into each weight category in addition to looking at risk associated with unit changes in maternal BMI.

4. In the discussion section, the authors should consider expanding discussion on changes in BMI associated with age due to normal growth and development and how that may be a confounder when analyzing changes in obesity/overweight trajectory, especially given that this is a pediatric sample. Additionally, the authors may consider discussing potential explanations for the difference in results noted between boys and girls (i.e. higher prevalence of overweight and obesity in boys and stronger correlation with mBMI) - for instance discussion of sex specific risk factors.

5. The manuscript requires minor grammatical revisions.

Reviewer #2: This study investigates the associations between maternal BMI in early pregnancy and the risk of child overweight/obesity at age 16. It is well written, clear and easy to read. However, the patterns of associations between pre-pregnancy BMI and offspring overweight has been extensively studied in the literature. Therefore, I regret to acknowledge that, despite the quality of the manuscript, this study does not add novelty to what is already know in the topic.

There may be some geographical specificities but they are not investigated in sufficient details. Moreover, the number of potential confounder taken into account is very low and makes the results subject to residual confounding.

Another objective of the paper is to describe tracking from 4 to 16 years, but the articulation between both objectives is not obvious.

I would also have additional minor comments and suggestions for the authors as follows:

- Models used are logistic models, so results should be odds ratio instead of Relative risks

- Why using 5-point maternal BMI increase, it’s a very important difference which artificially leads to extremely high ORs

- The § dedicated to the description of clinical characteristics is rather long and could be better organized. There seems to be interesting and sex-specific evolutions of prevalence, they could be described as such.

- In the results rather display and describe the adjusted rather than the unadjusted results (even if important confounders are lacking)

- Table 2: provide the numbers. And precise whether the numbers are all the same over the different ages (no missing value)?

- Some references are missing here and there in the discussion. For example, for the statement “we had no information about maternal diabetes or gestational weight gain, both known to increase the risk of overweight ad obesity in the offspring”; or “the prevalence of childhood obesity in high-income western countries…”

- There is a debate in the scientific community, especially due to recent results from mendelian randomisation studies, regarding the intrauterine programming of obesity hypothesis and the role of maternal pre-pregnancy obesity in this programming; this should be discussed in more details.

**********

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13 Sep 2022

PLOSONE-D-22-15811

Maternal body mass index in early pregnancy is associated with overweight and obesity in children up to 16 years of age

Answer: We would like to thank the Editor and reviewers for encouraging and constructive questions, comments and suggestions. Please find below our answers point by point.

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https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf.

Answer: We have amended the manuscript in order to comply with the PLOS ONE style requirements. In addition we have updated the web-links of 2 references (#5 and 20). In figure 2 have changed the orders of the panels so that boys are presented first in congruence with data presentation in the main text.

2. Please provide additional details regarding participant consent. In the ethics statement in the Methods and online submission information, please ensure that you have specified (1) whether consent was informed and (2) what type you obtained (for instance, written or verbal, and if verbal, how it was documented and witnessed). If your study included minors, state whether you obtained consent from parents or guardians. If the need for consent was waived by the ethics committee, please include this information.

If you are reporting a retrospective study of medical records or archived samples, please ensure that you have discussed whether all data were fully anonymized before you accessed them and/or whether the IRB or ethics committee waived the requirement for informed consent. If patients provided informed written consent to have data from their medical records used in research, please include this information.

Answer: The study was approved by the Regional Ethics Review Board in Gothenburg (reference 935-18). We have not retrieved informed consent from the studied individuals since we are reporting results from retrospective data from registers. The need for consent was waived by the ethics committee.

3. We note that the grant information you provided in the ‘Funding Information’ and ‘Financial Disclosure’ sections do not match.

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Answer: We have checked the grant number and added information of the grants role in the project. Please see below, point 4.

4. Thank you for stating the following in the Acknowledgments Section of your manuscript:

We are deeply grateful to the nurses at the antenatal clinics, CHC centres and schools for their help during acquisition of data. The work was supported by the Skaraborg research and development council (grant: VGFOUSKB-869761).

We note that you have provided funding information that is not currently declared in your Funding Statement. However, funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form.

Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement. Currently, your Funding Statement reads as follows:

The work was supported by the Skaraborg research and development council (grant: VGFOUSKB-869761).

Please include your amended statements within your cover letter; we will change the online submission form on your behalf.

Answer: We have now up-dated the funding information as follows and removed it from the manuscript:

The work was supported by the Skaraborg research and development council, Grant number: VGFOUSKB-869761. Web–site: http://www.vgregion.se/fouskaraborg. The grant was awarded to the first author, LÖ in 2018. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

We have included the amended statement in the Cover letter. Thank you very much for your help in changing the text in the online submission.

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a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially identifying or sensitive patient information) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent.

b) If there are no restrictions, please upload the minimal anonymized data set necessary to replicate your study findings as either Supporting Information files or to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. Please see http://www.bmj.com/content/340/bmj.c181.long for guidelines on how to de-identify and prepare clinical data for publication. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories.

We will update your Data Availability statement on your behalf to reflect the information you provide.

Answer: Data cannot be shared publicly because of ethical and legal restrictions from the Swedish authorities as the data contain sensitive and potentially identifying patient information. Data may however be available for researchers who meet the criteria for access to confidential data, upon reasonable request to the authors and with permission from the Swedish Ethical Review Authority (https://etikprovningsmyndigheten.se, registrator@etikprovning.se).

6. PLOS requires an ORCID iD for the corresponding author in Editorial Manager on papers submitted after December 6th, 2016. Please ensure that you have an ORCID iD and that it is validated in Editorial Manager. To do this, go to ‘Update my Information’ (in the upper left-hand corner of the main menu), and click on the Fetch/Validate link next to the ORCID field. This will take you to the ORCID site and allow you to create a new iD or authenticate a pre-existing iD in Editorial Manager. Please see the following video for instructions on linking an ORCID iD to your Editorial Manager account: https://www.youtube.com/watch?v=_xcclfuvtxQ.

Answer: The corresponding author (KBB) has up-dated her ORCID id.

7. We note that you have included the phrase “data not shown” in your manuscript. Unfortunately, this does not meet our data sharing requirements. PLOS does not permit references to inaccessible data. We require that authors provide all relevant data within the paper, Supporting Information files, or in an acceptable, public repository. Please add a citation to support this phrase or upload the data that corresponds with these findings to a stable repository (such as Figshare or Dryad) and provide and URLs, DOIs, or accession numbers that may be used to access these data. Or, if the data are not a core part of the research being presented in your study, we ask that you remove the phrase that refers to these data.

[Note: HTML markup is below. Please do not edit.]

Answer: We have included data formerly “not shown” in Table 2, as well as adjusted data as requested by the reviewers.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

Answer: Thank you!

________________________________________

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Answer: Thank you!

________________________________________

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: No

Answer: Please read our answers to items #5 and #7 under subheading Journal Requirements.

________________________________________

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Answer: Thank you!

________________________________________

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This study by Önnestam et al. explores the longitudinal association between maternal BMI in early pregnancy and body mass index in children up to the age of 16 years in a regional Swedish population. Overall, this prospective study is well designed, method is appropriate, and the results are clear and well organized. The manuscript is interesting and has strengths, including repeated measurements over time. Some comments and suggestions are as follows:

Answer: Thank you for this encouraging comment!

Reviewer #1: 1. In the last paragraph of the introduction, one of the objectives stated includes exploration of the correlation between maternal BMI and child BMI in gender-specific subgroups. However, there is no context provided as to why these subgroups were investigated. It would be helpful to provide context for this objective by adding a few lines in an earlier paragraph as to why analyzing BMI in boys and girls separately is important based on what is known from literature about sex-based differences in BMI.

Answer: Thank you very much for this suggestion. We have now added a few lines (Lines 75-79) in the Introduction (manuscript with track changes) to present the rationale for studying BMI in boys and girls separately. “The impact of adverse uterine environment factors on metabolic traits later in life differs between the sexes as described in a newly published review [15]. However, while some observational studies indicate that boys may have a higher risk of developing obesity following maternal over-nutrition [16] the opposite has also been found [17]”.

Reviewer #1: 2. Overall, the methodology is clearly explained. The results are also displayed clearly and sequentially. Information in the tables is also presented clearly.

Answer: Thank you very much.

Reviewer #1: 3. In the results section, while the association between maternal BMI and child weight/BMI has been explored at all defined ages (i.e. 4, 7, 10, 13, 16), the association between maternal BMI and risk of child overweight or obesity has only been assessed at the age of 16. It may be interesting to also see association between maternal BMI and child obesity/overweight risk at the other specified ages as well. In addition, the authors may consider adding analysis that investigates maternal BMI as a categorical variable based on weight status (normal weight, overweight, or obese) in association with risk of child overweight/obesity (currently maternal BMI has only been analyzed as a continuous variable). This may provide clinically practical results for groups of pregnant women who fall into each weight category in addition to looking at risk associated with unit changes in maternal BMI.

Answer: Thank you for this important suggestion. We have expanded table 3 with the association between maternal BMI and child obesity/overweight risk at the other specified ages as well per 1 unit increase in maternal body mass index. We have also revised the text above Table 3. Correspondingly we have altered the text in Statistical methods (Lines 138-142). As our data sample size is limited, we have chosen to refrain from categorizing data on maternal BMI as this would reduce the statistical power in our analyses considerably. However, the presented RRRs (supplementary S1 Table) per 5 units increase in maternal BMI corresponds to an increase in maternal weight status from normal weight to overweight to obesity.

Reviewer #1: 4. In the discussion section, the authors should consider expanding discussion on changes in BMI associated with age due to normal growth and development and how that may be a confounder when analyzing changes in obesity/overweight trajectory, especially given that this is a pediatric sample. Additionally, the authors may consider discussing potential explanations for the difference in results noted between boys and girls (i.e. higher prevalence of overweight and obesity in boys and stronger correlation with mBMI) - for instance discussion of sex specific risk factors.

Answer. We have added text in the Discussion (lines 302-310): “The sex difference in development of obesity depends on a multitude of factors including differential gene expression due to differences between the sexes in mRNA splicing, sex hormone effects, epigenetic mechanisms, mitochondrial and placental function [15]. In addition, the psychological pressure from peers and internet especially in teenage girls could influence the weight and bodily development [32]. The bodily changes during childhood and adolescence differ between individuals and occur at different points of time for instance occurrence of puberty [33]. These might be confounders in the analyses and could result in different outcomes in boys and girls and also explain deviating results in different studies”.

Reviewer #1: 5. The manuscript requires minor grammatical revisions.

Answer: The manuscript has been subjected to linguistic revision and amended according to the suggestions of the linguistic reviewer.

Reviewer #2: This study investigates the associations between maternal BMI in early pregnancy and the risk of child overweight/obesity at age 16. It is well written, clear and easy to read. However, the patterns of associations between pre-pregnancy BMI and offspring overweight has been extensively studied in the literature. Therefore, I regret to acknowledge that, despite the quality of the manuscript, this study does not add novelty to what is already know in the topic.

There may be some geographical specificities but they are not investigated in sufficient details. Moreover, the number of potential confounder taken into account is very low and makes the results subject to residual confounding.

Another objective of the paper is to describe tracking from 4 to 16 years, but the articulation between both objectives is not obvious

Answer: Thank you for addressing these important points. We agree that there are former studies that report the association between mother and child weight, as we also acknowledge in Introduction (lines 68-71, in Revised manuscript with track changes), “Numerous studies have shown an association…..” and in the Discussion (276-277), “The correlation between mBMI before or in early pregnancy and child BMI ……”

There are fewer studies, though, with a long time follow up and with consecutive measurements over time. Therefore, we think that this study contributes to the knowledge of development of overweight and obesity in children and specifically the difference between boys and girls in this respect.

Of course we wished that potential confounders could have been included in the analyses, but the clinical health records we used are not originally intended for research and did not supply such information. We have described this limitation of the study in the Discussion, subheading Strengths and limitations, lines 248-251) “…information about other confounding factors, such as paternal BMI or socio-economic status was missing. Further, there were neither data on chronic illnesses or medication in the children nor data on lifestyle, which could have affected BMI progression”.

We describe that accelerating BMI in childhood has been shown to be associated to obesity in adolescence (lines 57-58, with references #4 and 6). Our data also allowed us to study this important and modifiable risk for overweight and obesity. To emphasize this we have altered the text about the rationale for tracking BMI of the children from 4 to 16 years of age.

In Introduction (lines 58-59), we added “Thus, increasing BMI in children predicts overweight and obesity in adolescence and is therefore a target for preventive measures.” and we also altered the Conclusion, (lines 326-328) “ …which highlights the need for early intervention in the preventive work to combat childhood obesity, preferably starting at the antenatal clinic and follow-up in CHC centers and schools.”

Reviewer #2: I would also have additional minor comments and suggestions for the authors as follows:

Reviewer #2: - Models used are logistic models, so results should be odds ratio instead of Relative risks

Answer: Thank you for the comment. We have performed the multinominal logistic regressions using the Stata command mlogit with the rrr option. According to the Stata reference manual this reports the estimated coefficients transformed to relative risk ratios and not odds ratios. Please see example 3 with the accompanying technical note regarding this subject in the Stata online reference manual (pages 7-8):

https://www.stata.com/manuals/rmlogit.pdf

Reviewer #2: - Why using 5-point maternal BMI increase, it’s a very important difference which artificially leads to extremely high ORs

Answer: Thank you for the comment. The rationale to describe RRRs per 5-point maternal BMI increase was to correlate the results to the 5 unit increase in BMI classification from normal weight (BMI 20-25) to overweight (BMI 25-30) and from overweight to obesity (BMI > 30). The presented RRRs associated with a 5-point maternal BMI increase are equal to the RRRs of a 1-unit maternal BMI increase to the power of 5. The reported p-values are the same using either RRRs of a 1- or 5-point maternal BMI increase. However, we agree that a 5-point maternal BMI increase is quite substantial and have accordingly changed the text in the methods and results section and Table 3 to reflect RRRs of 1-point maternal BMI increase. In addition, we have provided results expressed as RRRs of 5-point maternal BMI increase in supplementary S1 Table.

Reviewer #2: - The § dedicated to the description of clinical characteristics is rather long and could be better organized. There seems to be interesting and sex-specific evolutions of prevalence, they could be described as such.

Answer: Thank you for this suggestion, we have shortened the text accordingly (Clinical characteristics of the mothers) as the data are shown in Figure1. In Clinical characteristics of the children we found that most data are not obvious from Figure 2 so we did not shorten the text. In Figure 2 we reversed the panels for girls and boys to be congruent with the order in the text.

Reviewer #2: - In the results rather display and describe the adjusted rather than the unadjusted results (even if important confounders are lacking)

Answer: We have now expanded Table 2 to include both adjusted and unadjusted data. In the abstract (lines 34-36) and the result section (lines 190-192, 203) we now describe results from the adjusted analyses.

Reviewer #2: - Table 2: provide the numbers. And precise whether the numbers are all the same over the different ages (no missing value)?

Answer: We have provided the number of individuals (boys and girls separately) that contributed with data at different ages, please find it in Table 2.

Reviewer #2: - Some references are missing here and there in the discussion. For example, for the statement “we had no information about maternal diabetes or gestational weight gain, both known to increase the risk of overweight ad obesity in the offspring”; or “the prevalence of childhood obesity in high-income western countries…”

Answer: Thank you, we have added a reference; a review from 2017, reference #23 (Agarwal P et al 2017) to the statements above according to the reviewers suggestion and moved reference #26 (former #24) to the end of the next sentence in the text to clarify the statement.

Reviewer #2: - There is a debate in the scientific community, especially due to recent results from mendelian randomisation studies, regarding the intrauterine programming of obesity hypothesis and the role of maternal pre-pregnancy obesity in this programming; this should be discussed in more details.

Answer: Thank you for this suggestion. We have added a few lines regarding this matter in the Discussion part (lines 288-291). “New technologies are used in order to study genetic and in utero causes of overweight and obesity in offspring such as Mendelian randomization [31]. Also, genetic imprinting and DNA methylation might play important roles for future risk assessment of obesity [15]”.

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19 Sep 2022

Maternal body mass index in early pregnancy is associated with overweight and obesity in children up to 16 years of age

PONE-D-22-15811R1

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28 Sep 2022

PONE-D-22-15811R1

Maternal body mass index in early pregnancy is associated with overweight and obesity in children up to 16 years of age

Dear Dr. Bengtsson Boström:

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