Association of the incidence of atopic dermatitis until 3 years old with climate conditions in the first 6 months of life: Japan Environment and Children's Study (JECS).

OBJECTIVE: To determine the climate conditions that affect the incidence of atopic dermatitis from infancy to 3 years old. STUDY
DESIGN: We analyzed 100,303 children born from 2011 to 2014 for follow-up until 3 years old using cohort data from the Japan Environment and Children's Study. The study included 15 Regional Centers, including 19 prefectures across Japan. We used meteorological data of the Japan Meteorological Agency. We calculated the hazard ratio (HR) of the standard deviation and low vs. high mean values of several climate conditions in children in their first 6 months of life to determine the incidence of atopic dermatitis.
RESULTS: The Kaplan-Meier curve showed that children born in the months of October to December had the highest incidence of atopic dermatitis. Among climate conditions, a one standard deviation increase in the temperature (HR = 0.87), minimum temperature (HR = 0.87), and vapor pressure (HR = 0.87) showed the lowest HRs for the incidence of atopic dermatitis. These results were confirmed by an analysis by strata of the birth season. A low vapor pressure (HR = 1.26, p<0.0001) and the combination of a low mean temperature or low mean minimum temperature and low vapor pressure (HR = 1.26, p<0.0001) were associated with the highest incidence of atopic dermatitis. These results were consistent when they were adjusted for a maternal and paternal history of allergy and the prefecture of birth.
CONCLUSION: Among climate conditions, a low vapor pressure is the most strongly associated with a high incidence of atopic dermatitis. Measuring vapor pressure may be useful for preventing atopic dermatitis.

Introduction

Globally, approximately 10%–20% of children are affected by atopic dermatitis (AD) [1, 2]. Investigation of the cause of AD is necessary to help relieve patients’ symptoms and reduce the number of patients. To date, many genetic and environmental factors are considered to be candidates for causing AD [3, 4]. Among the candidates of environmental risk factors [5, 6], seasonal climate conditions, chemical irritants, bacterial colonization, psychological stress [5], and birth month [7] are the main factors.

Our previous study showed that birth from April to June had the smallest risk of AD, and birth from October to December had the greatest risk of AD [7]. Theoretically, a genetic predisposition for AD does not affect the association between exposure of the birth month and the outcome of AD as a confounding factor. Therefore, this association appears to be affected by an environmental factor(s). The particular environmental factor involved in AD may be the climate condition because the difference in the risk of AD between April and June and that between October and December appears to be due to the season when children are exposed. In our previous study, Kaplan–Meier curves suggested that the amount of AD risk by birth season does not change much from 6 months to 3 years of age [7]. This finding suggests that the determinants of developing AD up to 3 years of age could be environmental factors from birth to 6 months of age.

Relating birth cohort data [8-11] and meteorological data [12] may help answer the question of how the birth month is associated with the incidence of AD. The reason for the association between the birth month and the prevalence of AD needs to be determined. Several meteorological measures represent features of seasonality in which newborns are exposed. Therefore, this study aimed to examine which climate element for birth in spring and autumn is associated with the incidence of AD.

Materials and methods

Ethics statement

The Japan Environment and Children’s Study (JECS) protocol was reviewed and approved by the Ministry of the Environment’s Institutional Review Board on Epidemiological Studies and by the Ethics Committees of all participating institutions. The study was performed in accordance with the ethical guidelines and regulations of the Declaration of Helsinki. All participants and parents or guardians of the children provided written informed consent before participating in the study.

Measures

Details on the JECS cohort are published elsewhere [8]. Approximately 100,000 expecting mothers who lived in the designated study areas were recruited over 3 years from January 2011. Exposure to environmental factors was assessed by chemical analyses of biospecimens and household environment measurements using monitoring data and questionnaires. One of the JECS’ priority outcomes was allergic diseases [8]. We recruited expecting mothers from January 2011 to March 2014 in 15 Regional Centers covering 19 prefectures across Japan [8]. We used the JECS data “jecs-ta-20190930-qsn” for answers to questionnaires, which were sent by post or provided to caregivers when their children were aged 6 months, 1 year, 1.5 years, 2 years, and 3 years. We asked if physicians had diagnosed the children with AD.

We collected climate condition data by prefecture and month from the Japan Meteorological Agency website [12]. We downloaded data of the monthly mean temperature, maximum temperature, minimum temperature, temperature difference, precipitation amount, sunshine duration, sunshine percentage, solar radiation quantity, vapor pressure, humidity, wind velocity, and cloud cover from February 2011 to May 2015. We regarded the 6-month mean climate condition value as the environment to which newborns were exposed. We chose this time because, in our previous study, the environment of the first 6 months after birth had the potential to determine the environmental risk of AD [7]. An example of this time period is neonates who were born in February 2011 were regarded to be exposed to climate conditions from February to July 2011.

From February 2011 to May 2015, we calculated the overall means of data of the monthly means of climate condition values from February 2011 to May 2015. These values were used as cut-off values for categorizing children as being exposed to a high/low climate condition. Using this categorization, the climate condition in the child’s residential area over 6 months beginning with the child’s birth month was compared with the cut-off values.

We used a maternal and paternal history of asthma, allergic rhinitis, pollen allergy, AD, allergic conjunctivitis, and/or food allergy for considering a child’s genetic predisposition to AD as covariates in a random effects model. The father and mother were asked individually about a history of allergic diseases to determine their experience of each diagnosed disease by a physician.

Statistical analyses

The 12 months of the year were categorized into four seasons (i.e., starting with January to March). We constructed a Kaplan–Meier curve of incident AD by the birth season. Using the Cox proportional model, we calculated the hazard ratio (HR) for a one standard deviation (SD) increase in the climate condition. We conducted this analysis with 6-month and 3-month means of the climate condition. Because 6-month means were more strongly associated with the incidence of AD (Table 1), we also calculated HRs for 6-month means of the climate condition by strata of the birth season. Additionally, we calculated HRs of low vs. high values of the climate condition for 6 months from birth. In this analysis, because we found a large difference in the incidence of AD among temperature, minimum temperature, and vapor pressure, we calculated HRs of combinations of high/low mean/maximum/minimum temperature and high/low vapor pressure.

Table 1

HRs (95% confidence intervals) of the incidence of atopic dermatitis for a one standard deviation increase in the mean climate condition from birth to 3 or 6 months.

Climate condition	Mean (SD)	HR for 1 SD, 6 months	HR for 1 SD, 3 months
Temperature	14. 9 (5.7)	0.87* (0.86, 0.89)	0.91* (0.89, 0.92)
Maximum temperature	19.3 (5.9)	0.88* (0.86, 0.89)	0.91* (0.89, 0.92)
Minimum temperature	11.1 (5.9)	0.87* (0.85, 0.89)	0.91* (0.89, 0.92)
Temperature difference	8.2 (1.3)	1.04* (1.02, 1.06)	1.01 (0.99, 1.03)
Precipitation amount	137 (64)	0.91* (0.89, 0.93)	0.94* (0.92, 0.96)
Sunshine duration	167 (26)	0.98* (0.96, 0.99)	0.95* (0.93, 0.97)
Sunshine percentage	45.7 (6.8)	1.03* (1.01, 1.05)	1.01 (0.99, 1.03)
Solar radiation quantity	13.3 (2.8)	0.94* (0.92, 0.96)	0.91* (0.89, 0.93)
Vapor pressure	13.5 (4.9)	0.87* (0.85, 0.88)	0.91* (0.89, 0.93)
Atmospheric pressure	1,007 (9.9)	0.98* (0.96, 0.999)	0.99 (0.97, 1.01)
Humidity	68.5 (5.4)	0.92* (0.90, 0.94)	0.96* (0.94, 0.98)
Wind velocity	3.02 (0.93)	0.95* (0.93, 0.97)	0.94* (0.92, 0.96)

*p<0.05. SD, standard deviation; HR, hazard ratio.

We then calculated this HR with adjustment for a maternal and paternal history of allergy and birthplace (prefectures) in the random effect model. In survival analyses, data from participants who were lost to follow-up (n = 20,652) or those who did not develop AD until 3 years of age (n = 69,001) were considered as being censored. Finally, we plotted the latitude and the accumulated incidence of AD at 3 years of age among the birthplaces. Although there were 19 different prefectures, a small subset of data in one prefecture was treated as belonging to data of another prefecture. Therefore, we plotted the latitude for 18 prefectural meteorological observatories. In these plots, we calculated Pearson’s correlation coefficients and p values. In this analysis of our ecological study, if there was a climate condition-associated incidence of AD, we attempted to determine whether it was simply attributable to latitude. We conducted all statistical analyses using SAS statistical software version 9.4 (SAS Institute, Cary, NC, USA). A p value of <0.05 in two-tailed tests was considered to indicate a significant difference.

Results

The data of 100,303 children were analyzed. By the ages of 6 months, 1 year, 1.5 years, 2 years, and 3 years, accumulated numbers of 1,715 of 100,303 children, 4,505 of 90,549 children, 7,030 of 86,934 children, 8,558 of 83,859 children, and 10,650 of 79,651 children, respectively, had developed AD. Fig 1 shows the association between the birth season and the incidence of AD to 3 years of age. From 6 months to 3 years of age, birth between April and June had the lowest incidence of AD, and birth between October and December had the highest incidence of AD.

Fig 1

Birth season and the incidence of atopic dermatitis up to 3 years of age.

Table 1 shows the HRs of AD for a one SD increase in the climate conditions. Among the climate conditions, HRs were significantly lower for a one SD increase in the 6-month mean temperature (HR = 0.87, p<0.0001), maximum temperature (HR = 0.88, p<0.0001), minimum temperature (HR = 0.87, p<0.0001), and vapor pressure (HR = 0.87, p<0.0001). Table 2 shows the HRs of a one SD increase in the climate condition by the birth season. In this analysis, a higher temperature, higher maximum temperature, higher minimum temperature, and higher vapor pressure also showed significantly lower HRs of AD (all p<0.0001). Among the seasons, birth between April and June showed the lowest HRs for a higher temperature, higher maximum temperature, higher minimum temperature, and higher vapor pressure (HRs = 0.64–0.68).

Table 2

Crude HRs of the incidence of atopic dermatitis for a one standard deviation increase in the mean climate condition from birth to 6 months by birth season.

Climate condition	HR for 1 SD	HR for 1 SD	HR for 1 SD	HR for 1 SD
	Birth from January to March	Birth from April to June	Birth from July to September	Birth from October to December
Temperature	0.83*	0.64*	0.86*	0.86*
Maximum temperature	0.85*	0.68*	0.87*	0.87*
Minimum temperature	0.82*	0.65*	0.85*	0.85*
Temperature difference	1.06*	1.04*	1.06*	1.01
Precipitation amount	0.96	0.95*	0.92*	0.89*
Sunshine duration	0.96	0.96	1.01	1.01
Sunshine percentage	0.995	0.95	1.03	1.02
Solar radiation quantity	0.95	0.91*	0.94	1.01
Vapor pressure	0.83*	0.65*	0.83*	0.79*
Atmospheric pressure	0.94*	0.98	0.96*	0.98
Humidity	0.95*	0.95*	0.90*	0.98
Wind velocity	0.91*	0.97	0.94*	0.93*

*p<0.05. SD, standard deviation; HR, hazard ratio.

Table 3 shows the HRs of AD for a low vs. high climate condition value. A low temperature (HR = 1.23, p<0.0001), low maximum temperature (HR = 1.21, p<0.0001), low minimum temperature (HR = 1.23, p<0.0001), and low vapor pressure (HR = 1.26, p<0.0001) showed significantly higher HRs than those for a high temperature, high maximum temperature, high minimum temperature, and high vapor pressure, respectively. A low vapor pressure only, the combination of a low temperature and a low vapor pressure, and the combination of a low minimum temperature and a low vapor pressure had the highest HRs (1.26) of AD.

Table 3

HRs (95% confidence intervals) of the incidence of atopic dermatitis for a low vs. high mean climate condition from birth to 6 months.

Low vs. high value	Cut-off value for high or low	HR
Temperature,°C	15.8	1.23 (1.18, 1.28)
Maximum temperature,°C	20.2	1.21 (1.16, 1.26)
Minimum temperature,°C	12.1	1.23 (1.19, 1.29)
Precipitation amount, mm	148	1.20 (1.15, 1.25)
Sunshine duration, hours	166	1.05 (1.01, 1.09)
Sunshine percentage, %	45	0.95 (0.92, 0.99)
Solar radiation quantity, MJ/m2	13.8	1.13 (1.08, 1.17)
Vapor pressure, hPa	14.4	1.26 (1.21, 1.31)
Atmospheric pressure, hPa	1,006	0.85 (0.81, 0.90)
Humidity, %	69	1.19 (1.15, 1.24)
Wind velocity, m/s	3.1	0.90 (0.86, 0.93)
Low temperature and low vapor pressure		1.26 (1.21, 1.31)
Low temperature and high vapor pressure		0.74 (0.59, 0.93)
High temperature and low vapor pressure		1.14 (1.03, 1.26)
High temperature and high vapor pressure		Reference
Low maximum temperature and low vapor pressure		1.25 (1.20, 1.30)
Low maximum temperature and high vapor pressure		0.78 (0.65, 0.93)
High maximum temperature and low vapor pressure		1.20 (1.09, 1.32)
High maximum temperature and high vapor pressure		Reference
Low minimum temperature and low vapor pressure		1.26 (1.21, 1.31)
Low minimum temperature and high vapor pressure		0.83 (0.64, 1.09)
High minimum temperature and low vapor pressure		1.17 (1.06, 1.30)
High minimum temperature and high vapor pressure		Reference

HR, hazard ratio.

S1 Table shows the HRs of AD for high climate condition values with adjustment for a maternal and paternal history of allergy and birthplace. A low temperature, low maximum temperature, low minimum temperature, and low vapor pressure had significantly higher adjusted HRs, which ranged from 1.17 to 1.19, than their corresponding high values (all p<0.001). A low temperature only, the combination of a low temperature and a low vapor pressure, the combination of a low maximum temperature and a low vapor pressure, and the combination of a low minimum temperature and a low vapor pressure showed the highest adjusted HRs (1.19) (all p<0.001).

S1 Fig shows a scatter plot of 18 prefectures by latitude and the accumulated incidence of AD until 3 years of age for an ecological study. Pearson’s correlation coefficient was 0.409 and the p value was 0.092. We did not find a significant relationship between the latitude and the incidence of AD in this ecological study.

Discussion

When we investigated the association of AD with the climate condition, while avoiding confounding, a low vapor pressure was most strongly associated with a higher incidence of AD in childhood. Temperature, maximum temperature, and minimum temperature were also associated with a higher incidence of AD.

This study suggested that the risk of AD by birth month was determined by 6 months of age (Fig 1). Therefore, we considered that season-associated environmental factors should affect the risk of AD. We compared the risk of AD among SDs of climate conditions (Table 1). This comparison suggested that any temperature and vapor pressure could be candidates of environmental risk factors for AD. Additionally, the variability in the mean climate condition from birth to 6 months was more strongly associated with the incidence of AD than that from birth to 3 months. In Japan, temperature and vapor pressure rise from spring to summer, and they fall from autumn to winter [7]. Therefore, the birth month could confound the association of the risk of AD with temperature and vapor pressure. To avoid confounding, we calculated HRs of climate conditions by strata of the birth season (Table 2). Our results suggested that temperature and vapor pressure affected the risk of AD separately from the birth month. Additionally, a decreased risk of AD with birth from April to June may be greatly affected by exposure to a higher temperature and a higher vapor pressure.

To understand the environmental risk factors, we calculated HRs of low vs. high climate conditions (Table 3). We found higher HRs (1.23–1.26) for temperature or vapor pressure in the current study than that (HR = 1.20) in our previous study when we compared birth from October to December with birth from April to June [7]. We could not initially determine which was the most important risk factor among temperature, maximum temperature, minimum temperature, and vapor pressure. Therefore, we calculated all HRs of these conditions for low vs. high values. We also investigated the influence of the combination of a low/high temperature and a low/high vapor pressure on the risk of AD. Although a low temperature and a low vapor pressure were associated with an increased incidence of AD, the combination of a low temperature and a low vapor pressure did not have a synergistic influence on this incidence (HR = 1.26). However, a low vapor pressure only showed the same HR (1.26). Therefore, vapor pressure was considered as an important climate condition for developing AD.

Few studies have investigated the association between the climate condition during the neonatal period and the risk of AD. A previous study investigated the association between temperature and ambulatory visits with AD in the United States, and showed that increased temperature increased the likelihood of office visits for AD [13]. However, in the investigation of calendar months, there was no clear effect of seasonality on office visits for AD. Ecological data suggested an inverse association between the mean annual temperature and the prevalence of AD in children, and showed no clear association between humidity and the prevalence of AD [14]. Our study, which used relatively individual data, also showed an association between a higher temperature and a lower incidence of AD. A high temperature enables air to contain more water, and therefore this could increase vapor pressure. The present analysis also showed that a higher vapor pressure decreased the incidence of AD.

There are inconsistent ecological data of the association between the latitude and the incidence of AD [14, 15]. An Australian report suggested that a higher incidence of eczema was associated with a higher latitude of residence (odds ratio = 1.90 for south vs. north regions) [16]. In our study, there was a slight correlation between the latitude and the accumulated incidence of AD, although this was not significant (S1 Fig). Low latitude areas receive solar irradiation, which produces vitamin D. Because vitamin D supplementation may help ameliorate the severity of AD [17], residing at a low latitude may prevent AD. Vapor pressure and temperature are likely to be high if the latitude of the residence is low. These previous studies [14-16] and our ecological analyses were not able to determine the climate condition responsible for the risk of AD.

AD is caused by the interplay of several factors [18]. Skin dryness in winter [19] may partly explain the high incidence of AD in children born between October and December. Vapor pressure is due to the pressure of water vapor, which is determined by the temperature and volume of gasiform water in a unit volume of air. In contrast, humidity (or relative humidity), which is frequently announced in the weather forecast, is the percentage of water volume of the maximum water volume that a unit volume of air can contain at a particular temperature. Therefore, vapor pressure and humidity are strongly correlated. These definitions mean that vapor pressure rather than humidity can better indicate the moisture in air and may be directly associated with skin moisture. This may be the reason why vapor pressure was more strongly associated with the incidence of AD than humidity in this study. This is in line with our finding that newborns delivered between October and December had the highest incidence of AD (Fig 1) because they were surrounded by a low vapor pressure in the first 6 months (winter) from birth.

If vapor pressure rather than humidity is important for developing AD, we could use this information to prevent child AD. If neonates are born in autumn to winter, they experience a low vapor pressure for the first 6 months of life. Parents could prepare a humidifier for their neonate to decrease this disease risk. They could also pay attention to the vapor pressure value. To prevent AD, a home electrical appliance that shows vapor pressure rather than humidity could be more useful for patients with AD. Because humidity is calculated from the saturated vapor pressure and real vapor pressure, this type of appliance should be able to be manufactured.

Parents need to treat skin dryness in winter when vapor pressure falls for infants who are born between October and December. In a season or area of dry air, effort should be made to achieve retention of moisture. A meta-analysis showed that emollient use in infants younger than 6 months was significantly effective for preventing AD, while there were conflicting results on its effectiveness in infants aged between 6 and 12 months [20]. Because a low vapor pressure was a risk factor for AD in our study, protecting the skin from dry air should decrease the risk of AD.

Previous studies investigated latitude [16], humidity [21], or sunshine [22] as a risk or preventive factor for AD. Each climate condition changes along with other climate conditions. Therefore, the climate conditions confound each other. The present study showed that vapor pressure may play a principal role in the risk of AD. To the best of our knowledge, no studies have shown that vapor pressure is a risk factor for AD. We propose that measuring vapor pressure could be useful for the prevention of AD.

Our study had the following limitations. First, the indoor condition was not measured in this study. We could not exclude the effect of a household environment with the use of cleaners, bleaches, and detergents. Second, our results are limited because we did not detect Staphylococcus aureus in the skin [23], which could contribute to an increased risk of AD. Third, dichotomizations of a long/short sunshine duration and high/low humidity were determined by single cut-off values. Observational results could have varied, depending on the cut-off values. Fourth, the incidence of AD was reported by caregivers based on a physician’s diagnosis. Therefore, there could have been recall bias of the caregivers. Fifth, physicians who diagnosed children included specialists of AD and non-specialists. Non-specialist physicians might have underdiagnosed AD in infancy because this diagnosis can cause stigma to children and caregivers [24]. Sixth, short-term factors, such as yellow sand from China and seasonal pollen in the air, were not considered in this study. Studies have suggested that these factors may worsen dermatitis [25, 26].

Conclusions

Among climate conditions, such as temperature and relative humidity, a low vapor pressure is the most strongly associated with a high incidence of AD in Japan. Paying attention to vapor pressure may reduce the incidence of AD in neonates who are born between October and December.

Adjusted HRs (95% confidence intervals) of atopic dermatitis for a low vs. high mean climate condition from birth to 6 months.

(DOCX)

Click here for additional data file.

Scatter plot of the latitude and the accumulated incidence of atopic dermatitis at 3 years of age.

Owing to the small number of participants, data from Shiga Prefecture were included with those of the neighboring Kyoto Prefecture.

(TIF)

Click here for additional data file.

31 Mar 2022

13 Apr 2022

Responses to the Editor and reviewer

As requested, we have prepared a revised version of our manuscript based on the comments and suggestions received. We hope that these revisions have sufficiently addressed the Editor’s and reviewer’s concerns. Our point-by-point responses are included below each comment (in italics), with line numbers indicating the relevant changes in the revised manuscript. We extend our sincere thanks to the Editor and reviewer for all the helpful comments provided.

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3. One of the noted authors is a group or consortium [the Japan Environment and Children’s Study Group]. In addition to naming the author group, please list the individual authors and affiliations within this group in the acknowledgments section of your manuscript. Please also indicate clearly a lead author for this group along with a contact email address.

We thank the Editor for the suggestion. We have added the names of the JECS group to the Acknowledgments section. We have also indicated the contact e-mail address of the principal investigator.

Line 273: “The members of the JECS Group as of 2022 are as follows: Michihiro Kamijima (principal investigator, Nagoya City University, Nagoya, Japan, jecsen@nies.go.jp), Shin Yamazaki (National Institute for Environmental Studies, Tsukuba, Japan), Yukihiro Ohya (National Center for Child Health and Development, Tokyo, Japan), Reiko Kishi (Hokkaido University, Sapporo, Japan), Nobuo Yaegashi (Tohoku University, Sendai, Japan), Koichi Hashimoto (Fukushima Medical University, Fukushima, Japan), Chisato Mori (Chiba University, Chiba, Japan), Shuichi Ito (Yokohama City University, Yokohama, Japan), Hidekuni Inadera (University of Toyama, Toyama, Japan), Takeo Nakayama (Kyoto University, Kyoto, Japan), Hiroyasu Iso (Osaka University, Suita, Japan), Masayuki Shima (Hyogo College of Medicine, Nishinomiya, Japan), Hiroshige Nakamura (Tottori University, Yonago, Japan), Narufumi Suganuma (Kochi University, Nankoku, Japan), Koichi Kusuhara (University of Occupational and Environmental Health, Kitakyushu, Japan), and Takahiko Katoh (Kumamoto University, Kumamoto, Japan).”

4. Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

We have reviewed the references to ensure that they are complete and correct.

Responses to additional comments from the Editor

1. Please clarify if a vapor pressure is equal to atmospheric humidity.

We thank the Editor for the comment. Atmospheric humidity can be specified by the partial pressure of water vapor (e, in hPa), vapor density (g m−3), specific humidity (q, g/g of moist air), or relative humidity (RH = 100e/es) (https://www.sciencedirect.com/topics/earth-and-planetary-sciences/atmospheric-humidity). To avoid confusion of the readers, we used the term “vapor pressure”, and have emphasized the difference between vapor pressure and relative humidity in the Discussion section.

Line 226: “Vapor pressure is due to the pressure of water vapor, which is determined by the temperature and volume of gasiform water in a unit volume of air. In contrast, humidity (or relative humidity), which is frequently announced in the weather forecast, is the percentage of water volume of the maximum water volume that a unit volume of air can contain at a particular temperature.”

2. How the effect of a household environment (use of cleaners, bleaches, detergents, etc.) was excluded from the study?

We appreciate the Editor’s insightful comment. Because the household environment was not sufficiently examined, and we could not exclude the effect of this environment, this was a limitation to this study. We have added the following text to the manuscript:

Line 254: “Our study had the following limitations. First, the indoor condition was not measured in this study. We could not exclude the effect of the household environment with the use of cleaners, bleaches, and detergents.”

3. Was a barometric pressure included in the meteorologic parameters assessed? What about an effect of a short-term pollution?

We included mean barometric pressure as mean atmospheric pressure in the tables. The association between a one standard deviation increase in mean atmospheric pressure and the incidence of atopic dermatitis (AD) was small (0.98, 95% CI: 0.96, 0.999 in Table 1; 0.94, 0.98 in Table 2). Therefore, we did not consider atmospheric pressure as a risk factor for AD.

Short-term factors, such as yellow sand from China and seasonal pollen in the air, were not considered in this study. This information has been added as another limitation.

Line 263: “Sixth, short-term factors, such as yellow sand from China and seasonal pollen in the air, were not considered in this study. Studies have suggested that these factors may worsen dermatitis [26, 27].”

4. Materials and Methods. Why Kaplan-Meier curves were used in statistical analysis of the obtained data? Specify what chemical analyses of bio-speciments included, what bio-speciments were used, and how such analyses were performed. Same for household environmental measurements. What kind of computational stimulation was used and how? Why a Cox proportional model was used and what it allowed to achieve? How a latitude was plotted? Why Pearson’s correlation coefficients were evaluated, what information they provide for your study? Two-sided p values mean a two-tailed test was used?

We thank the editor for the questions. The Kaplan–Meier curve in Fig 1 was used to illustrate the difference in the incidence of AD from the age of 6 months to 3 years among birth months. Additionally, a difference in the incidence of AD appeared to occur at 6 months of age. We presented Fig 1 to explain why we started this study on the association between seasonal meteorological factors and the incidence of AD.

Urine and blood from a subset of participants were sampled. Vitamin D, thyroid-stimulating hormone, thyroxine, triiodothyronine, and hemoglobin A1c concentrations were among various items measured (Sekiyama, M. et al. Study design and participants’ profile in the Sub-Cohort Study in the Japan Environment and Children’s Study (JECS). Journal of Epidemiology 2020, JE20200448. Online first). Because we are not permitted to use the data of biospecimens in this study, we were not able to use these data in the analysis. The values of biospecimens are used as exposures or outcomes of epidemiological studies. A few studies using these data have been published (e.g., Ma, C. et al. Association of prenatal exposure to cadmium with neurodevelopment in children at 2 years of age: The Japan Environment and Children's Study. Environ Int 2021, 156, 106762). Household environmental measurements from the JECS have also been published (Iwai-Shimada, M. et al. Questionnaire results on exposure characteristics of pregnant women participating in the Japan Environment and Children Study (JECS). Environmental health and preventive medicine 2018, 23, 45). Although computational simulation was performed at the study core center, we could not find the published information. Therefore, we have deleted the information about computational simulation from our study. The following text was added to the manuscript:

Line 71: “Exposure to environmental factors was assessed by chemical analyses of biospecimens and household environment measurements using monitoring data and questionnaires.”

We extended our analyses to examine the seasonality of the incidence of AD among climate conditions as follows. First, the Kaplan–Meier curve showed that the neonatal period until 6 months of age determined the risk of AD until 3 years of age. Second, in the time-to-event data, we compared the risk per unit of standard deviation among the conditions using the Cox proportional hazard model to determine which climate condition is involved in the incidence of AD because the units of climate conditions are different. Third, because temperature and vapor pressure rather than relative humidity were candidates involved in the incidence of AD, we compared the risk of AD by high/low mean temperature, maximum temperature, minimum temperature, and vapor pressure for 6 months in the model.

The latitude was plotted based on the birthplace of the studied children. We evaluated Pearson’s correlation coefficient to determine if the latitude is associated with the incidence of AD. If there is an association, latitude-associated climate conditions, including mean temperature and vapor pressure, may be involved in the incidence of AD. Notably, this was an ecological study, and the evidence level was weak. Although there was no significant association, we attempted to identify the reason for the association between the season of birth and the incidence of AD. We have added the reason why we performed this analysis to the Materials and Methods section and explained the results.

Line 110 in the Materials and Methods section: “Finally, we plotted the latitude and the accumulated incidence of AD at 3 years of age among the birthplaces. Although there were 19 different prefectures, a small subset of data in one prefecture was treated as belonging to data of another prefecture. Therefore, we plotted the latitude for 18 prefectural meteorological observatories. In these plots, we calculated Pearson’s correlation coefficients and p values. In this analysis of our ecological study, if there was a climate condition-associated incidence of AD, we attempted to determine whether it was simply attributable to latitude.”

Line 171 in the Results section: “We did not find a significant relationship between the latitude and the incidence of AD in this ecological study.”

Line 222 in the Discussion section: “Vapor pressure and temperature are likely to be high if the latitude of the residence is low. Previous studies and our ecological analyses were not able to determine the climate condition responsible for the risk of AD.”

The use of two-sided p values indicated that a two-tailed test was used. We have revised the description of p values as follows:

Line 116 in the Materials and Methods section: “A p value of <0.05 in two-tailed tests was considered to indicate a significant difference.”

5. Results. Table 1 shows no statistics because there was no difference between the parameters? What does Ref mean as a reference in Table 3.

We have added asterisks to Table 1 to indicate statistical significance. In Table 3, “Ref” means “reference”. We apologize for not defining this abbreviation and have spelled it out instead.

6. Discussion. Be specific why any temperature (Low, high?) and vapor pressure are associated with a higher incidence of AD. Is a high heat or cold temperature associated with a likelihood of office visits for AD?

We thank the reviewer for the comment. We have added explanations about the association between a low temperature and a high incidence of AD.

Line 179: “When we investigated the association of AD with the climate condition, while avoiding confounding, a low vapor pressure was most strongly associated with a higher incidence of AD in childhood.”

Line 213: “A high temperature enables air to contain more water, and therefore this could increase vapor pressure.”

Line 230: “These definitions mean that vapor pressure rather than humidity can better indicate the moisture in air and may be directly associated with skin moisture. This may be the reason why vapor pressure was more strongly associated with the incidence of AD than humidity in this study.”

7. Conclusion. Make also a statement on the results on temperature and humidity association with higher incidences of AD.

We thank the reviewer for the comment. We mentioned in the Discussion section that among the climate conditions, a low vapor pressure, rather than a low temperature or low humidity, is the most strongly associated with a high incidence of AD. We have modified the summary and conclusion accordingly.

Line 179: “When we investigated the association of AD with the climate condition, while avoiding confounding, a low vapor pressure was most strongly associated with a higher incidence of AD in childhood. Temperature, maximum temperature, and minimum temperature were also associated with a higher incidence of AD.”

Line 266: “Among climate conditions, such as temperature and relative humidity, a low vapor pressure is the most strongly associated with a high incidence of AD in Japan. Paying attention to vapor pressure may reduce the incidence of AD in neonates who are born between October and December.”

Responses to comments from reviewer #1

This manuscript follows up on prior results indicating that in Japanese individuals a birth date between October to December correlates with increased risk for atopic dermatitis. The current work tries to tease out the features of seasonality that are responsible. The work is interesting and deserves publication.

We thank the reviewer for the comments. We have revised our manuscript accordingly.

1. The authors should state limitations of their conclusions in more detail.

We have added more details for the limitations (see below). We hope that this paragraph now sufficiently explains the limitations.

Line 254: “Our study had the following limitations. First, the indoor condition was not measured in this study. We could not exclude the effect of a household environment with the use of cleaners, bleaches, and detergents. Second, our results are limited because we did not detect Staphylococcus aureus in the skin [24], which could contribute to an increased risk of AD. Third, dichotomizations of a long/short sunshine duration and high/low humidity were determined by single cut-off values. Observational results could have varied, depending on the cut-off values. Fourth, the incidence of AD was reported by caregivers based on a physician’s diagnosis. Therefore, there could have been recall bias of the caregivers. Fifth, physicians who diagnosed children included specialists of AD and non-specialists. Non-specialist physicians might have underdiagnosed AD in infancy because this diagnosis can cause stigma to children and caregivers [25]. Sixth, short-term factors, such as yellow sand from China and seasonal pollen in the air, were not considered in this study. Studies have suggested that these factors may worsen dermatitis [26, 27].”

2. The sentence about a randomized controlled trial showing prevention of AD by use of moisturizer in infants <1year needs to be modified, reflecting the fact that there are multiple studies on this subject with conflicting results.

We thank the reviewer for the suggestion. We have revised the text in accordance with the reviewer’s advice.

Line 245: “A meta-analysis showed that emollient use in infants younger than 6 months was significantly effective for preventing AD, while there were conflicting results on its effectiveness in infants aged between 6 and 12 months [21].”

We hope that our responses to the Editor’s and reviewer’s comments and the corresponding manuscript revisions have addressed the main points raised. We are grateful for the helpful suggestions, and we hope that our manuscript is now suitable for publication in PLOS ONE.

Yours sincerely,

Hiroshi Yokomichi

Department of Health Sciences, University of Yamanashi,

1110 Shimokato, Chuo City, Yamanashi, 4093898, Japan

E-mail: hyokomichi@yamanashi.ac.jp

Phone: +81 55 273 9569

Fax: +81 55 273 7882

Submitted filename: Respone letter PLOS ONE 20220413.docx

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25 Apr 2022

Association of the incidence of atopic dermatitis until 3 years old with climate conditions in the first 6 months of life: Japan Environment and Children’s Study (JECS)

PONE-D-22-05326R1

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28 Apr 2022

PONE-D-22-05326R1

Association of the incidence of atopic dermatitis until 3 years old with climate conditions in the first 6 months of life: Japan Environment and Children’s Study (JECS)

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