Evaluating the seasonality of growth in infants using a mobile phone application

Growth in early life is a crucial area of pediatric study, with several models attempting to explain its complexities. The Infancy-Childhood-Puberty (ICP) model highlights three distinct growth phases, with infancy characterized by the fastest growth velocity. This rapid growth is influenced by factors such as nutrition and sex; however, the role of seasonality remains unclear, particularly in developed countries. Previous studies in low-income countries have suggested a link between food availability and seasonal growth variations, but this hasn't been extensively investigated in developed nations. The challenge has been the difficulty of collecting sufficiently detailed, prospective data on child growth. The advent of mobile health applications offers a new avenue for data collection, enabling large-scale studies on this topic. This study leverages data from the "Papatto Ikuji" mobile phone application to examine the effect of seasonality on infant growth in Japan, addressing the lack of research in developed nations on this subject.

Existing literature highlights seasonal variations in growth velocity among toddlers and school-aged children, though the underlying mechanisms remain uncertain. Studies in low-income countries have pointed to food availability as a primary driver, linking higher growth rates to seasons with greater food abundance. However, this explanation is not necessarily transferable to populations with consistent nutritional access. Other potential factors include hormonal influences (e.g., growth hormone secretion) and vitamin D levels, which exhibit seasonal fluctuations. The ICP model suggests that the determinants of growth differ between infancy and childhood. The current study aimed to explore whether the seasonal variation observed in older children also exists in infants, potentially providing insights into the underlying mechanisms.

This study utilized longitudinal data from the "Papatto Ikuji" mobile phone application, a popular childcare support app in Japan. Data were collected from January 2014 to October 2017, encompassing records for 9,409 Japanese infants. Parents voluntarily entered their child's length and weight measurements. On average, each infant had 4.8 length and 5.4 weight entries. Length-for-age (LAZ) and weight-for-age (WAZ) z-scores were calculated using age- and sex-specific Japanese references. The primary outcome measures were the daily change in LAZ (ALAZ/day) and WAZ (AWAZ/day) z-scores between consecutive measurements, calculated as (Z_T2 - Z_T1) / (T₂ - T₁), where Z represents the z-score and T represents the date. Measurements with intervals between 15 and 100 days were included. Seasonality was assessed by aggregating ALAZ/day and AWAZ/day values for each year and season, as well as by month across multiple years. Multilevel linear regression analysis was used to examine the association between ALAZ/day and season while adjusting for age, sex, nutritional group (breastfeeding, mixed feeding, formula-dominant feeding), period of measurement, and season of birth. The time sequence (Period 1 to 4) represented the interval from season of birth to the season of the reference date (midpoint of the two consecutive measurements). SAS 9.4 was used for all data analyses. Ethical approval was obtained, and informed consent was waived due to the anonymized nature of the data.

The study analyzed 20,007 ALAZ/day and 33,236 AWAZ/day measurements. Visual inspection of the data revealed consistent fluctuations in ALAZ/day across years, with higher values in summer and lower values in winter. AWAZ/day did not show a similar pattern. Multilevel linear regression analysis, adjusting for confounding variables, demonstrated a significant difference in ALAZ/day between summer and winter (mean difference 0.0026, 95% CI 0.0015 to 0.0036; *P* < 0.001). This difference accounted for 13% of the average linear growth velocity in 6-month-old infants. The analysis also revealed a modest effect of nutrition, with formula-fed infants showing slightly higher ALAZ/day values compared to breastfed infants (mean difference 0.0015, 95% CI 0.0006 to 0.0025; *P* < 0.001). No significant seasonality effect was observed for AWAZ/day.

This study provides the first empirical evidence of a seasonality effect on linear growth in human infants in a developed country setting. The observed seasonal variation in linear growth, with increased growth velocity in summer, is consistent with findings in older children. This consistency challenges the assumption that the determinants of growth are vastly different between infancy and childhood. While food availability, hormonal control, and vitamin D levels were considered as potential mechanisms, the study lacked the necessary biochemical data to confirm any of these hypotheses. The observed effect, although statistically significant, is relatively small in magnitude and may not directly impact clinical practice. However, understanding these seasonal patterns could contribute to public health initiatives by highlighting potential population-level deficiencies, such as vitamin D insufficiency.

This mobile phone app-based study reveals a previously unrecognized seasonal effect on infant linear growth in Japan, with increased growth in summer and decreased growth in winter. This finding contributes to our understanding of infant growth and highlights the potential of mobile health data for large-scale research in pediatrics. Further research is needed to elucidate the underlying mechanisms driving this seasonal pattern and to investigate the generalizability of these findings to other populations.

This study's limitations include the lack of biochemical data (e.g., GH, IGF1, vitamin D), which would help clarify the mechanisms driving seasonal growth variations. The reliance on self-reported data, while likely of high quality due to parental motivation, may introduce measurement error. The study also lacked data on residential area, preventing the investigation of potential latitude effects. Finally, weight-for-height, an indicator of ponderal growth, was not analyzed due to limited age-specific standardized data.