Japanese growth charts stratified by birth weight in 500-gram increments: Findings from the Japan Environment and Children’s Study

Abstract

Growth charts are essential tools for monitoring the physical development of children. We analyzed data from a nationwide Japanese birth cohort of 98,987 participants to create eight growth charts stratified by birth weight in 500-gram increments. Infants with birth weight < 2,500 g showed significant improvements in height and weight standard deviation (SD) scores by 4 yr of age. Boys and girls weighing 500–999 g at birth had average length/height SD scores of –6.40 and –8.20, which improved to –1.26 and –1.17 by 4 yr of age, respectively. Conversely, infants with birth weight ≥ 3,500 g showed decreased height and weight SD scores by 4 yr of age. Boys and girls weighing ≥ 4,000 g had average length/height SD scores of 1.87 and 2.10 at birth, which decreased to 0.34 and 0.51 by 4 yr of age, respectively. These findings reveal distinct growth patterns for different birth weight categories, highlighting the impact of birth weight on early childhood growth trajectories. The growth charts developed here serve as a valuable tool for evaluating children born small or large. These charts enable a more accurate monitoring of children’s growth and can be useful in both clinical and public health settings.

Highlights

● Growth charts (0–4 yr) were developed from a Japanese national birth cohort.

● Height and weight SD scores increased in infants born < 2,500 g and decreased in those born> 3,500 g by 4 yr of age.

● Birth weight strongly predicts growth trajectories in early childhood.

Introduction

Growth charts serve as tools to monitor children’s physical development. Originally developed by the National Center for Health Statistics in the United States in 1977, the growth chart was revised in 2000, transforming it into the Centers for Disease Control and Prevention Growth Chart and gaining widespread adoption (1). The World Health Organization Child Development Standards, developed in 2006 using data from children in six countries, considered factors that influence growth. These standards now serve as indicators for “how children should develop” rather than “how children are developing” (2). In recent years, growth charts tailored to specific countries have been developed (3,4,5,6). These revisions and updates rely on improved statistical procedures and more comprehensive national data, thus enhancing the accuracy of assessing and monitoring infant and child growth in local communities and healthcare facilities. However, the current reference growth curves do not sufficiently consider physical development in children with low birth weight (LBW) or high birth weight (HBW). In Japan, growth charts are derived from the Infant Physical Growth Survey conducted every decade, and those based on the 2000 survey are widely used throughout the country (7). In contrast, previous studies have faced challenges in constructing growth curves for infants with LBW or HBW owing to the limited number of participants.

Previous reports have emphasized the importance of constructing LBW growth curves. Infants with LBW or those who are small for their gestational age may remain smaller after birth (8,9,10), whereas infants with HBW may remain larger after birth than infants with normal birth weight (11, 12). Families express significant concerns about the postnatal growth of children born small and large. In healthcare guidance within medical institutions and municipalities, interest in creating appropriate assessment tools tailored to birth weight is increasing. To overcome the limitations of previous studies, this study used data from the Japan Environment and Children’s Study (JECS), a national prospective birth cohort supported by the Ministry of the Environment, Japan, to develop growth charts based on birth weight and identify growth profiles.

Methods

Study design and participants

We analyzed data from the JECS, an ongoing national birth cohort study (13). Pregnant women were recruited from 15 regional centers across the nation between January 2011 and March 2014 to participate in the JECS (jecs-ta-20190930 and jecs-qa-20210401 datasets). The JECS protocol was reviewed and approved by the Ministry of the Environment’s Institutional Review Board on Epidemiological Studies (No. 100910001) and ethics committees of all participating institutions. All the participants provided written informed consent. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology reporting guidelines (14).

A total of 103,057 pregnancies, equivalent to 104,059 fetal records, were registered. In cases of multiple pregnancies, only firstborn children were included in the analysis. Initially, we excluded 1,221 miscarriages, 356 stillbirths, 2,123 cases with missing birth data, 18 cases of unspecified sex, and 352 cases with no birth weight records. Finally, 98,987 participants were included in this study.

In cases of multiple pregnancies, only the first-born child was included in the analysis to maintain the statistical independence of observations and avoid the over-representation of multiple births. However, twins were not entirely excluded because multiple births are commonly associated with LBW. Additionally, we included children classified as light-for-date (LFD) or heavy-for-date (HFD) because they contribute significantly to the number of LBW (< 2,500 g) and overweight (≥ 3,500 g) cases, respectively. In contrast, a sensitivity analysis was conducted by excluding twins, infants who were LFD and HFD, and infants with specific syndromes and other factors known to affect postnatal growth. Subsequently, participants were categorized into nine groups based on birth weight: Group A, < 500 g; Group B, 500–999 g; Group C, 1,000–1,499 g; Group D, 1,500–1,999 g; Group E, 2,000–2,499 g; Group F, 2,500–2,999 g; Group G, 3,000–3,499 g; Group H, 3,500–3,999 g; and Group I, ≥ 4,000 g.

Variables

Variables of parity, stillbirths and miscarriages, multiple pregnancies, weeks of gestation, birth weight, and birth length were extracted from birth records. These records were primarily transcribed by physicians, midwives/nurses, and/or research coordinators during the mothers’ hospitalization.

Data on weight and length/height up to 4 yr of age, along with age in months, were extracted from semiannual self-administered questionnaires. Participants were instructed to transcribe the measurements recorded at health checkups or medical facilities, although measurements taken at childcare facilities or homes were also accepted.

The 6-mo survey form included records from 3–4 mo. The 1-yr survey form included two sets of measurements: one from checkups conducted between 5 and 8 mo and the other from checkups conducted beyond 9 mo. The semiannual survey form after 1.5 yr of age included the most recent measured weight, length/height, and measurement date. Ten measurements, including those obtained at birth, were taken. Data for lengths/heights < 40 cm and > 150 cm and weights > 40 kg were excluded. Measurements deviating by ± 5 standard deviations (SD) scores and those where the measurement months on the questionnaire were reversed from 6 mo to 4 yr of age were also excluded. Additionally, data with measurement months deviating by ± 12 mo from the median were excluded. The gestational age, age at measurement, weight, length/height, and data points used to develop the growth curves, obtained from 10 measurements from birth to 4 yr of age, are presented in Supplementary Tables 1–2.

LFD and HFD were defined as birth weights below and above the 10th percentile for gestational age, respectively, considering sex and parity based on Japanese reference data on normal fetal growth (15, 16). As there was no reference for 42 wk or more, the reference for 41 wk and 6 d was used.

Data on multiple pregnancies and congenital abnormalities, including chromosomal abnormalities and congenital anomalies of the brain, cardiopulmonary organs, gastrointestinal organs, and bones, were extracted from records up to 1 mo after birth. These details were primarily recorded by physicians, nurses, midwives, and research coordinators, who used medical records to complete a pre-specified questionnaire. If physical abnormalities were recorded, the corresponding boxes were checked. Consequently, cases of multiple congenital abnormalities (e.g., brain and cardiovascular malformations occurring together) were also documented. This information was used as the exclusion criterion for sensitivity analysis.

Statistical analysis

Infant growth curves from the 2000 survey (17) and 2010 growth chart survey published in the Maternal and Child Health Handbook were smoothed using the Lambda-Mu-Sigma (LMS) method (18, 19), which is commonly used to smooth the distribution of anthropometric values along the age axis (4, 5, 20, 21). Variables related to skewness (L), median (M), and variability (S) of the distribution were calculated using the Box-Cox transformation and then smoothed. The resulting L, M, and S curves contain information to plot percentile curves and can be used to accurately convert the measured values into SD scores.

Generalized Additive Models for Location, Scale and Shape (GAMLSS) implemented in R were used to generate growth curves (22). In recent years, the use of GAMLSS to construct growth curves has increased (6).

GAMLSS estimates four parameters (µ, σ, ν, τ) in the distribution, representing location (median), scale (variation), skewness (power transformation for symmetry), and kurtosis (degrees of freedom), respectively. The estimated values were expressed as a function, with the horizontal axis as the objective variable, utilizing more than 100 estimation methods, some of which are equivalent to the LMS method. Previous studies have reported that including kurtosis in the smoothing estimation along with location, scale, and skewness during the creation of growth curves does not significantly change the goodness of fit (18). Therefore, given the favorable outcomes observed with the inclusion of kurtosis, we adopted the Box-Cox t distribution model for this study.

The GAMLSS scripts in R, along with the k values, number of samplings, and SD score removal for each group, are presented in Supplementary Methods and Supplementary Table 3. In principle, all measurements were included; however, as there was dissipation toward the end of the curve as the months progressed, measurements up to 48 mo were used and those after 49 mo were excluded. The “k” value corresponds to degrees of freedom, and k = 4 was used for most groups, while k = 1, 9, and 16 were employed for some of the growth curves that did not smooth well with k = 4. In some datasets where errors affected the plotting of growth curves, random sampling of 4–30% or SD score removal was used to eliminate outliers. This is because, in GAMLSS, having a sample size that is too large or the presence of outliers leads to an increased computational load, overfitting, slow convergence, and numerical instability, making practical and accurate analysis difficult. During random sampling, reproducibility was checked using multiple seed values. All statistical analyses were performed using JMP, R software (version 4.1.2; R Foundation for Statistical Computing, Vienna, Austria), and the R package “GAMLSS” (5).

There are various definitions for catch-up growth; however, in this study, we defined catch-up growth as an increase in length/height or weight to mean –2 SD or above, following previous reports (23). Reference values were based on those used clinically in Japan (7). In contrast, catch-down growth was defined as a reduction in length/height or weight below the mean +2 SD.

In sensitivity analysis, cases with factors that could potentially influence growth were excluded. Differences in the mean values before and after exclusion were calculated, and 95% confidence intervals were used to evaluate whether the observed differences were statistically significant.

Results

Table 1 presents the participants’ characteristics. Sex distribution varied across the groups: Groups E and F had a higher proportion of girls (55.6% and 53.6%, respectively), whereas Groups G–I had a higher proportion of boys. LFD was prevalent in the LBW group (approximately half in Groups A–E). HFD infants were more common in the HBW group (especially in Groups H and I). Multiparous cases exceeded 10% in Groups A–E.

Table 1. Characteristics of the participants *.

Group A, with birth weights < 500 g, had a limited number of cases, which precluded the generation of growth curves. Figures 1, 2, 3, 4, 5, 6, 7, 8 show length/height and weight growth charts for boys and girls up to 48 mo of age in Groups B–I. Supplementary Tables 4–11 detail the µ, σ, ν, and τ values for length/height and weight by sex and age, along with the selected percentiles used to calculate the percentages to create the growth curves.

Fig. 1.

Growth charts in Group B with 500–999 g birth weight. The gray lines indicate the Japanese reference lines for weight and length/height, showing the 3rd, 10th, 50th, 90th, and 97th percentiles from the bottom. The blue and orange lines represent the 3rd, 10th, 25th, 50th, 75th, 90th, and 97th percentiles from the bottom for boys and girls, respectively.

Fig. 2.

Growth charts in Group C with 1,000–1,499 g birth weight. The gray lines indicate the Japanese reference lines for weight and length/height, showing the 3rd, 10th, 50th, 90th, and 97th percentiles from the bottom. The blue and orange lines represent the 3rd, 10th, 25th, 50th, 75th, 90th, and 97th percentiles from the bottom for boys and girls, respectively.

Fig. 3.

Growth charts in Group D with 1,500–1,999 g birth weight. The gray lines indicate the Japanese reference lines for weight and length/height, showing the 3rd, 10th, 50th, 90th, and 97th percentiles from the bottom. The blue and orange lines represent the 3rd, 10th, 25th, 50th, 75th, 90th, and 97th percentiles for boys and girls, respectively.

Fig. 4.

Growth charts in Group E with 2,000–2,499 g birth weight. The gray lines indicate the Japanese reference lines for weight and length/height, showing the 3rd, 10th, 50th, 90th, and 97th percentiles from the bottom. The blue and orange lines represent the 3rd, 10th, 25th, 50th, 75th, 90th, and 97th percentiles from the bottom for boys and girls, respectively.

Fig. 5.

Growth charts in Group F with 2,500–2,999 g birth weight. The gray lines indicate the Japanese reference lines for weight and length/height, showing the 3rd, 10th, 50th, 90th, and 97th percentiles from the bottom. The blue and orange lines represent the 3rd, 10th, 25th, 50th, 75th, 90th, and 97th percentiles from the bottom for boys and girls, respectively.

Fig. 6.

Growth charts in Group G with 3,000–3,499 g birth weight. The gray lines indicate the Japanese reference lines for weight and length/height, showing the 3rd, 10th, 50th, 90th, and 97th percentiles from the bottom. The blue and orange lines represent the 3rd, 10th, 25th, 50th, 75th, 90th, and 97th percentiles from the bottom for boys and girls, respectively.

Fig. 7.

Growth charts in Group H with 3,500–3,999 g birth weight. The gray lines indicate the Japanese reference lines for weight and length/height, showing the 3rd, 10th, 50th, 90th, and 97th percentiles from the bottom. The blue and orange lines represent the 3rd, 10th, 25th, 50th, 75th, 90th, and 97th percentiles from the bottom for boys and girls, respectively.

Fig. 8.

Growth charts in Group I with over 4,000 g birth weight. The gray lines indicate the Japanese reference lines for weight and length/height, showing the 3rd, 10th, 50th, 90th, and 97th percentiles from the bottom. The blue and orange lines represent the 3rd, 10th, 25th, 50th, 75th, 90th, and 97th percentiles from the bottom for boys and girls, respectively.

As shown in Fig. 1 and Tables 2, 3, the average length/height SD scores (50th percentile) of boys and girls in Group B were extremely low at birth at –6.40 and –8.20, respectively. Following birth, the average length/height SD scores improved to –2.67 for boys and –2.62 for girls at 12 mo, improving further and surpassing –2 by 23–24 mo, indicating catch-up growth. The growth rate continued to show gradual improvement, reaching –1.43 SD and –1.21 at 36 mo, and further improving to –1.26 and –1.17 at 48 mo for boys and girls, respectively. Regarding weight, the average SD scores at birth were –5.63 for boys and –5.66 for girls. By 36 mo, the average weight SD scores had increased to approximately –1.2 and then remained relatively stable until 48 mo.

Table 2. Mean length/height and weight SD scores for boys by birth weight groups (Relative to Japanese Reference Values).

Table 3. Mean length/height and weight SD scores for girls by birth weight groups (Relative to Japanese Reference Values).

The average length SD scores (50th percentile) for boys and girls in Group C were –4.52 and –5.20 at birth, respectively (Fig. 2 and Tables 2–3). Boys showed catch-up growth in length by 10 mo, whereas girls showed catch-up growth by 8 mo. By 12 mo, the average length/height SD scores reached –1.74 for boys and –1.64 for girls, further improving to –1.29 and –1.30 at 24 mo and to –0.95 and –0.72 at 36 mo, respectively. However, at 48 mo, the average height SD scores remained relatively stable at –0.97 for boys and –0.82 for girls, indicating that their growth aligned with the reference curve. The average SD scores at birth were –4.16 for boys and –4.21 for girls. By 5–6 mo, the average weight SD scores exceeded –2, improving continuously and reaching –0.64 for boys and –0.68 for girls at 24 mo. Subsequently, the values remained relatively stable until 48 mo.

Groups D and E, with birth weights of 1,500–1,999 g and 2,000–2,499 g, respectively, were born slightly smaller than average (Figs. 3–4 and Tables 2–3). The trends in the average length/height and weight (50th percentile) were similar to those observed in Group C. Specifically, the average length/height SD scores improved steadily from birth to approximately 36 mo but remained relatively stable from 36 to 48 mo. Regarding weight, the average SD scores improved until approximately 24 mo but showed slight changes from 24 to 48 mo.

Infants in Groups F and G, weighing 2,500–3,499 g, were within the average birth weight range in Japan, with boys and girls having average birth weights of 3.05 kg and 2.96 kg, respectively. As shown in Figs. 5–6 and Tables 2–3, the average length/height and weight (50th percentile) SD scores trajectories in Group F remained stable for both boys and girls from birth to 4 yr of age; the average length/height and weight SD scores changed only slightly between ages 0 and 4 yr of age, with boys showing a change from –0.32 to –0.42 in length/height and from 0.16 to –0.03 in weight, while girls exhibited a change from –0.20 to –0.35 in length/height and from –0.36 to –0.18 in weight. Although there were minor fluctuations, no significant changes in growth rates were observed, and the growth pattern followed the reference curve. In contrast, the average SD scores in Group G were slightly higher at birth, with boys having +0.46 in length and +0.49 in weight, while girls had +0.61 in length and +0.57 in weight. However, by 48 mo, both height and weight had almost completely adjusted to the average reference values.

The results for Groups H and I, with infants born larger than the average, are presented in Figs. 7–8 and Tables 2–3. Regarding the trajectories of the average length/height and weight (50th percentile), both groups experienced catchdown (defined as a decrease to the mean +2 SD or below) within the first 1–2 mo of life. In Group H, the average length SD scores at birth were +1.17 for boys and +1.36 for girls. These SD scores decreased to approximately +0.2 by 12 mo and remained almost unchanged until 48 mo, with no significant changes over this period. The weight trends followed a similar pattern. In Group I, the average length SD scores at birth were +1.87 for boys and +2.10 for girls. By 12 mo, the SD scores had decreased to approximately +0.5, further declining to approximately +0.3 by 24 mo, and this level was maintained until 48 mo. With regard to weight, the average SD score decreased to approximately +1 at 12 mo and remained stable until 48 mo, with no major changes observed.

A comparison of the postnatal trajectories among these cohort groups revealed that the relative body size rankings established at birth persisted throughout the postnatal period (Supplementary Fig. 1). This suggests that body size at birth influences postnatal body size.

Sensitivity analysis was conducted by excluding cases classified as LFD or HFD (Sapplementary Tables 12–13). After exclusion, Groups C–F showed mild but statistically significant increases (i.e., 95% confidence intervals did not include zero) in mean weight and height/length at several time points in both boys and girls, whereas Group H consistently showed decreases across all time points.

Group D showed the most prominent increase. Among boys, the mean weight at 4 yr increased by 0.52 kg (from 14.32 to 14.84 kg), and the mean height by 0.88 cm (from 96.82 to 97.70 cm). Among girls in Group D, the mean weight increased by 0.64 kg (from 14.08 to 14.72 kg) and the mean height by 1.09 cm (from 96.49 to 97.58 cm) at 4 yr of age.

In contrast, in Group H, both mean weight and height consistently decreased. For example, among boys, the mean weight at 4 yr decreased by 0.21 kg (from 16.41 to 16.20 kg), and the mean height by 0.35 cm (from 100.89 to 100.54 cm); among girls, the mean weight decreased by 0.36 kg (from 16.19 to 15.83 kg) and the mean height by 0.56 cm (from 100.13 to 99.57 cm).

Further sensitivity analyses were conducted by excluding multiple pregnancies, chromosomal abnormalities, and congenital anomalies involving the brain, heart, lungs, gastrointestinal tract, or bones, as well as excluding cases with fewer than half of the scheduled measurements. However, the resulting differences were minimal, and all confidence intervals included zero, indicating no statistically significant changes (Supplementary Tables 14–20).

Discussion

This study visualized the growth patterns of children categorized according to their birth weight as small, large, or average. A longitudinal examination of postnatal body weight and length/height revealed that children born smaller exhibited improved growth rates (Groups B–E), whereas those born larger (Groups H–I) did not, converging toward the median of the general population in all groups. The order of weight and length/height in Groups B–I remained consistent until 4 yr of age, with rare reversals. Groups F (2,500–2,999 g) and G (3,000–3,499 g), which represented children with birth weights close to the median, showed typical growth patterns similar to the population median. To our knowledge, this is the first study to visually present growth trajectories in detail for every 500 g birth weight. The growth curves developed in this study based on birth weight hold potential value in both clinical and healthcare settings.

The median weight and length/height of the eight groups showed rapid catch-up growth by 1–2 yr of age, especially among those born small (Groups B–E), whereas infants born large (Groups H–I) showed catch-down growth (Supplementary Fig. 1). Both curves approached the median values of the general population. Groups F and G, with birth weights around the median, maintained growth patterns close to the median of the general population until 4 yr of age. Predictors of final height, such as the well-known modified Roche-Wainer-Thissen method (24) and the Khamis-Roche method (25), have established correlations with childhood height. Regarding weight, studies have reported that BMI at 3 yr of age correlates with future BMI (26). Furthermore, environmental factors influence growth trajectories, and the effects of maternal metal exposure on infant weight trajectory patterns have been reported by the JECS (27). The strong association between birth weight, body weight, and length/height up to 4 yr of age observed in this study suggests that birth weight could be an indicator of future postnatal growth.

The majority of children born small, particularly those classified as LFD, exhibit catch-up growth (28). However, excessive catch-up growth poses the risk of future obesity and noncommunicable diseases (29). Nevertheless, the optimal growth rate for catch-up remains unclear. The growth charts presented in this study can serve as a reference for the growth patterns of children born small. For example, in Group B (extremely LBW; ELBW), the median weight at 12 mo corresponded to the 3rd percentile of the reference growth curve. In contrast, the 97th percentile corresponded to the 50th percentile of the reference growth curve, possibly indicating excessive catch-up growth. Establishing a reference for ELBW children to reach the 3rd percentile in length/height at 24 mo can reassure concerned parents. Early adiposity rebound contributes to obesity (30, 31). Evaluating the early growth of children born small is crucial, and this growth curve serves as an important tool for medical professionals and concerned parents.

Currently, the optimal growth pattern for children born large is unclear. However, the growth curves obtained in this study for children born weighing 3,500–3999 g or ≥ 4,000 g showed slightly larger weights and lengths at 12 mo than the weight and length of a reference child for both sexes. They were then aligned using a reference growth curve. The optimal nature of this growth pattern remains unknown until health outcomes in adolescence or adulthood are examined; however, this study provides a valuable reference for understanding the growth of children born large.

Biases can arise in growth curves developed based on patient information obtained from hospital visits (6). For example, these biases were based on the protocol of the hospital and physician judgment, affecting visit frequency and patient data variability. This limits the generalizability of the results to a specific hospital’s patient population. Moreover, using cross-sectional data presents a limitation, as neither historical background nor individual differences can be considered for each measurement point (1). This study was based on a prospective cohort, maintained consistency in participants, and data weights were measured uniformly according to the study protocol. Additionally, because the participants were randomly selected, the results can be generalized to a broader population.

In the sensitivity analysis excluding LFD and HFD cases, postnatal weight and height tended to increase in Groups C to F but decreased in Groups G and H. These findings suggest that even among infants with similar birth weights, those classified as LFD may have experienced poorer postnatal growth trajectories, whereas those classified as HFD may have been larger than average. Previous studies have shown that gestational age can independently influence postnatal growth even in infants with nearly identical birth weights (32). This highlights the importance of future studies, not only in evaluating growth trajectories specifically in LFD and HFD groups, but also in considering gestational age when assessing postnatal growth. Regarding multiple pregnancies and congenital anomalies, most observed differences were not statistically significant or clinically meaningful.

This study had some limitations. The development of separate growth curves for recumbent length (0–2 yr) and standing height (2–4 yr) was initially intended. However, upon reviewing the data, this approach was not feasible because of the self-reported method of the obtained measurements, which did not consistently distinguish between recumbent and standing measurements at the 2-yr cutoff. Therefore, the data reported at approximately 2 yr of age may have included both recumbent length and standing height. Nonetheless, this is unlikely to have a substantial impact on the overall trends observed in this study, particularly regarding the relationship between birth weight and growth up to 4 yr of age. The small number of children weighing < 500 g resulted in the inability to develop a growth chart for Group A. In this study, eliminating bias owing to differences in the number of measurements was not entirely possible. However, the distribution of measurements and the results of the sensitivity analysis suggest that the impact of measurement frequency on the study’s findings is likely minimal. The participants were predominantly Japanese, limiting the generalizability of the results to this population. However, children born small reportedly tend to remain small after birth worldwide, and growth trajectories based on birth weight are likely similar in non-Japanese countries. Nevertheless, there is a need to create growth curves specific to each country in the future. Although final height is known to have a strong correlation with parental height, the analytical model faced limitations, necessitating adjustments in the degrees of freedom and sampling for smoothing. However, we confirmed that the random sampling of Groups D–G was sufficient and did not affect the creation of growth curves, as multiple seed values yielded consistent results (data not shown). This study did not account for the effects of underlying conditions strongly associated with fetal and postnatal growth, such as genetic abnormalities and growth hormone deficiency, nor did it consider the independent influence of gestational age on birth weight. Further research is required to assess the effects of these factors on postnatal growth.

Conclusions

These findings suggest that birth weight influences growth later in life. We created eight growth charts for each sex stratified by birth weight using data from a large prospective birth cohort in Japan. These growth charts are expected to serve as valuable references for assessing a child’s growth.

Conflicts of interests

None reported.