Population studies indicate a strong relationship between birth weight (BW) and body size in later life. However, BW as a variable was never accounted for in studies on the relationship between attention-deficit/hyperactivity disorder (ADHD) and overweight. This study aims to assess the relationship between ADHD and overweight with control of birth weight and other confounding factors. Prevalence of overweight was compared in clinical sample of 219 boys with ADHD and 396 boys without ADHD, aged 6–18 years. The following factors were controlled: BW, parents income and education level, place of residence, ADHD type, selected comorbid disorders and stimulant treatment. Overweight and obesity were diagnosed according to the criteria proposed by the International Obesity Task Force. Logistic regression analysis was used to estimate the association between ADHD and the prevalence of overweight and obesity. Boys with ADHD differed significantly from the control group in distribution of low BW (8.2 vs. 3.0 %, χ ² = 8.23, p = 0.02). Low BW was associated with a lower prevalence of overweight than normal and high BW (0 vs. 12.14 %, χ ² = 4.12, p = 0.04). Overweight was observed significantly more often in boys with ADHD (17.3 vs. 8.3 %, χ ² = 11.23, p < 0.001) even after adjustment for BW and other variables (OR = 2.44, 95 % CI 1.38–4.29, p = 0.002) and after controlling for ADHD type, stimulant treatment and selected comorbid disorders. Independently to applied analysis, obesity was not associated with ADHD. Lower birth weight is over twice more often observed in boys with ADHD than in control group. Although this phenomenon may reduce the rate of overweight in the studied group, ADHD remains strongly associated with increased prevalence of overweight.

Objective: Previous studies have associated attention-deficit/hyperactivity disorder (ADHD) with growth deviations and obesity. However, available data regarding the growth of children with ADHD in their early childhood are insufficient. Therefore, we aimed to examine whether there are differences in body size between preschool boys with and without ADHD. Methods: The study used cross-sectional and retrospective longitudinal data concerning 112 boys with ADHD and a community-based sample of 308 boys without ADHD. The groups were homogeneous in terms of socioeconomic status, place of residence, term of birth, and birth weight. The average age of diagnosis was 8.3 years, and none of boys had been treated with stimulants before they were 7 years of age. Comparisons were made at the ages of 2, 4, and 6 years, for World Health Organization (WHO)-norm-standardized height, weight, body mass index (BMI), prevalence of underweight, overweight, and obesity. Separate analysis were made for the cross-sectional measurements of current body size. Results: Boys with ADHD at the age of 2 had significantly lower z scores for weight ( t =−1.98, p =0.04) and BMI ( t =−2.09, p =0.04), and at the age of 4 for weight ( t =−2.05, p =0.04) than the boys from the control group. A significantly lower percentage of overweight/obesity was observed in boys with ADHD at the age of 2 in comparison with the control group. At the age of 6, boys with ADHD were underweight more often. Cross-sectional analysis of current body size showed that boys with ADHD had lower z scores for height ( t =−3.08, p =0.002) and higher z scores ( t =3.13, p =0.002) for BMI. Overweight was more frequent in this group. Conclusions: Preschool boys with ADHD (age of 2–6 years) have a tendency toward lower body weight than their peers. But in subsequent phases of development, they are shorter and more frequently overweight than boys without ADHD, when place of residence, socioeconomic status, term of birth, birth weight, comorbid conditions, and treatment are controlled.

Most children born small for gestational age (SGA) have rapid postnatal growth. Despite its positive aspects, catch-up growth may affect the level of adipose tissue in the pre-pubertal and pubertal periods and therefore affect the age of puberty. The aim of this study was to determine the associations between size at birth, catch-up growth in infancy, BMI in peripubertal period, age at menarche, and the parameters of adolescent growth spurt of body height in girls born SGA. For 297 girls (22.6% SGA; 77.4% appropriate for gestational age (AGA)) complete body weight and height measurements and age at menarche were obtained. Adolescent growth spurt parameters were estimated using the JPA2 model (AUXAL SSI 3.1). Calculations were made in the Statistica 13 program using the Kruskal-Wallis and Kaplan–Meier tests. Girls born SGA with catch-up had the highest BMIs at the age of 8 years (H = 94.22, p < 0.001) and at menarche (H = 58.21, p < 0.001), experienced menarche earliest (H = 21.77, p < 0.001), same as the onset (H = 6.54, p = 0.012) and peak height velocity (H = 11.71, p = 0.003) of their adolescent growth spurt compared to SGA girls without catch-up and AGA girls. In SGA girls, catch-up growth has far-reaching consequences such as increased risk of fat accumulation and a rapid transition to puberty.

Gut microbiota succession overlaps with intensive growth in infancy and early childhood. The multitude of functions performed by intestinal microbes, including participation in metabolic, hormonal, and immune pathways, makes the gut bacterial community an important player in cross-talk between intestinal processes and growth. Long-term disturbances in the colonization pattern may affect the growth trajectory, resulting in stunting or wasting. In this review, we summarize the evidence on the mediating role of gut microbiota in the mechanisms controlling the growth of children.

Objectives: The purpose of the study was to evaluate the relationship between BMI at menarche and selected growth spurt parameters, such as age at take-off of the pubertal growth spurt (ATO), age at peak height velocity (APHV), growth spurt duration (APHV-ATO), and the pubertal growth rate. Methods: The study group consisted of 243 girls aged 10-16 years. Several measurements of body height and weight have been taken for each girl during the girls' development (longitudinal study). Nutritional status has been assessed using the IOTF (Cole et al. 2000; Cole et al. 2007). Girls were asked about their age at menarche. To investigate the growth rate, the age at TO and PHV for each girl was calculated using AUXAL.3 software and a structural model JPA2. Statistical analyses were made in Statistica 12.0 using Kruskal-Wallis test Kruskal-Wallis test and multiple regression analysis. Results: The mean age at menarche for the entire group was 12.59 (Me = 12.52, Min = 9.9, Max = 16.2). There was a significant statistical relationship between the level of BMI and age at menarche. The age at menarche decreased significantly with increasing levels of nutritional status (H = 33.2, p < 0.001). Also, TO and PHV occurred earlier in girls with higher values of BMI indicator (TO: H = 12.25, p < 0.05; PHV: H = 12.25, p < 0.05). Conclusions: The level of nutritional status at the age of menarche is significantly related to growth and the rate of biological maturation in girls. Higher BMI at menarche is associated with an earlier occurrence of menarche, TO and PHV.

Human papillomaviruses (HPVs) are a very complex group of pathogenic viruses, with more than 80 types, causing human infection. Given the prevalence of HPV infection and its relationship with the development of cervical and many other cancers, HPV vaccine development has been a major public health initiative worldwide in the last decade. The aim of the presented study was to identify HPV DNA by MY-PCR in 4,150 school children and adolescents, aged 10–18 years in the Wielkopolska region, Poland. All individuals were asked to fill in extensive questionnaires; further normal, oral squamous cells were collected from each pupil. Cellular DNA was isolated and used as a MY-PCR template to estimate the incidence of HPV-active infection. Forty five subjects (1.08% of the sample) were carriers of oropharyngeal HPVs. HPV status and variables of interest, such as age, gender, socioeconomical status, and risk factors (smoking and sexual intercourse history, alcohol consumption) were not correlated. The presence of HPVs in the oral cavity was cumulated in several schools of the region. DNA sequencing of MY-PCR products revealed only four HPV genotypes. The most frequent genotype was HPV11 (38/45 HPV-positive cases), while other more rare genotypes were HPV6 (3/45), HPV12 (3/45), and HPV57 (1/45). Conclusion: Our findings presented herein, reveal a relatively low prevalance of oropharyngeal HPVs in Polish adolescents and fill an important gap in the knowledge of oral HPV infections of children above 10 years and adolescents.