Association between mealtime regularity and postpartum depression in first-time Japanese mothers: a cross- sectional study

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Although daily lifestyle behaviors have been implicated in PPD, the roles of breakfast skipping and mealtime regularity, which are key components of chrononutrition, remain insufficiently understood. This study examined the associations between mealtime regularity and postpartum depressive symptoms in first-time Japanese mothers. Methods This cross-sectional study included 841first-time Japanese mothers with a child aged 0–12 months (UMIN000051573; approved on July 10, 2023). Depressive symptoms were assessed using the Edinburgh Postnatal Depression Scale (EPDS). Mealtime regularity and breakfast frequency were evaluated using self-administered questionnaires. Furthermore, associations between EPDS scores and eating-related behaviors were examined using generalized estimating equations, after adjusting for sociodemographic factors, health-related behaviors, mothers’ and infants’ sleep characteristics, and partners’ working days. Results Mothers with regular mealtime had significantly lower EPDS scores than those with irregular mealtime. After full adjustment for potential confounders, regular mealtime remained independently associated with lower EPDS scores, whereas breakfast skipping was not. Conclusion Regular mealtime, rather than breakfast consumption, was independently associated with fewer postpartum depressive symptoms. These findings suggest that the temporal organization of eating behaviors may represent a novel and modifiable lifestyle factor relevant to postpartum mental health. Further longitudinal and interventional studies are warranted to clarify causality and evaluate mealtime regularity as a potential target for PPD prevention. chrononutrition sleep circadian clock breakfast skipping nighttime snack first-time mothers Introduction Postpartum depression (PPD) is a common mental health disorder that affects approximately 17% of mothers worldwide [ 1 ]. PPD has serious consequences on maternal well-being, mother–infant bonding, and child development [ 2 , 3 ]. PPD is also highly prevalent in Japan, affecting approximately 10–15% of postpartum mothers [ 4 , 5 ]. PPD has been variably defined as a condition occurring between 4 weeks and 12 months after childbirth [ 6 ]. However, depressive symptoms frequently emerge during pregnancy rather than after childbirth, underscoring the importance of identifying modifiable lifestyle-related risk factors associated with PPD initiation and severity [ 7 ]. While psychological therapies and antidepressants effectively treat PPD, access to these treatments remains limited, and preventive strategies targeting lifestyle behaviors are still inadequate [ 8 ]. PPD is associated with daily lifestyle behaviors, such as sleep, physical activity, and food and nutrition. Sleep disturbance, including fragmented sleep, poor sleep quality, and frequent nighttime awakenings related to infant care, has been consistently reported as a risk factor for PPD [ 9 – 11 ]. Meanwhile, regular physical activity and exercise have been associated with a lower risk and reduced severity of PPD symptoms [ 12 ]. Dietary habits have also been implicated in postpartum mental health issues. A systematic review found that greater adherence to a healthy postpartum diet—characterized by higher consumption of fruits, vegetables, fish, grains, and legumes, or micronutrients such as vitamin D, iron, vitamin B12, folate, and zinc—was generally associated with lower PPD symptoms [ 13 , 14 ]. In Japanese populations, healthier dietary habits, including a higher intake of fish and omega-3 fatty acids, and overall healthier dietary patterns, are associated with lower depressive symptoms during pregnancy and a reduced risk of PPD [ 15 , 16 ]. Concurrently, chrononutrition, which focuses on the time and regularity of food intake in relation to circadian rhythms, has emerged as an important determinant of mental and metabolic health [ 17 ]. Although breakfast skipping has been linked to depression and mental health outcomes in the non-pregnant population, evidence regarding its association with PPD remains limited [ 18 – 20 ]. A recent cross-sectional study of pregnant women in Korea found that skipping breakfast was significantly associated with higher PPD scores [ 21 ]. Additionally, associations between irregular mealtime and poor mental health have been reported in the non-pregnancy population [ 22 , 23 ]. A cross-sectional study of Japanese women four months postpartum found that irregular eating patterns, such as “not eating meals regularly,” were significantly associated with poorer mental health status [ 24 ]. Furthermore, women with poor sleep, depression, anxiety, and stress showed significantly higher odds of unhealthy eating behaviors, including meal skipping and meal delaying [ 25 ]. Overall, the current evidence suggests potential associations between lifestyle behaviors and postpartum mental health. However, more studies are required to better understand the associations between modifiable daily behaviors and postpartum depression. Therefore, this cross-sectional study investigated the association between mealtime regularity and PPD symptoms in first-time Japanese mothers of infants aged 0–12 months, after adjusting for sleep quality, health-related behaviors, infant sleep characteristics, and sociodemographic factors. Materials and Methods Ethical Approval and Data Collection This cross-sectional study explored the relationships among the postpartum mother’s mental health, social and environmental factors, and daily behaviors. Further, all methods used in this cross-sectional study complied with the STROBE statement [ 26 ]. This study also adhered with the guidelines of the Declaration of Helsinki and was approved by Hiroshima University’s Ethical Committee for Epidemiology on July 10, 2023 (No. E2023-0047; UMIN000051573). Subsequently, informed consent was provided by all participants in the surveys; they consented to the collection and use of their data for research. Aresearch company (Macromill Inc., Tokyo, Japan) was commissioned to conduct an online survey from Aug 1–4, 2023. The participants in the research company’s cohort lived in Japan. Finally, the company was instructed to collect samples with a 1:1 male-to-female ratio and ensure an even distribution across the ages (1–12 months old) of the babies. Participants A priori power analysis for multiple linear regression was conducted to determine the sample size. Assuming a two-sided α of 0.05, 80% power, and up to 10 covariates, a sample size of approximately 800 participants was sufficient to detect a small effect size (0.02). The inclusion criteria for the participants were as follows: (1) mother who had only a firstborn baby aged 0–12 months; (2) mother who was working before pregnancy; (3) mother who was not working when she answered this questionnaire; and (4) mother whose partner had exhausted childcare leave. The exclusion criteria comprised single mothers living with their baby. Our survey covered 1,030 participants. After excluding those with missing response variables and those who did not meet the inclusion criteria, we analyzed a total of 841 participants. Questionnaire Construction The sociodemographic variables included mother’s age, baby’s age (in months) and sex, and partner’s working days (days/weeks). Data were also obtained on whether the pregnancy resulted from infertility treatment, the duration of pregnancy, and presence or absence of cesarean delivery. The mothers’ anthropometric data, including weight and height, were collected to calculate Body Mass Index (BMI). Their personality data were collected using the Big-Five personality traits [ 27 ]. Each personality trait (extraversion, agreeableness, conscientiousness, neuroticism, and openness) was calculated as the average of the scores on two related questions (average score range: 1–7). The Japanese version of the Edinburgh Postnatal Depression Scale (EPDS) was used to assess postpartum depression [ 28 ]. The EPDS score was calculated as the sum of the 10 questions included in the scale. An EPDS score of ≥ 9 was used as an indicator of higher PPD symptoms. The Oguri-Shirakawa-Azumi Sleep Inventory Middle-aged and Aged version (OSA-MA) was used to evaluate sleep problems, which were defined by participants’ lower scores [ 29 , 30 ]. Behaviors related to health markers were assessed based on the number of days per week of breakfast intake, nighttime snack intake, alcohol consumption, caffeinated beverage intake, smoking, and exercise. Mealtime regularity was assessed using the question, “Do you currently eat meals at the same time each day?” with a five-point answer scale (1 = strongly disagree; 2 = disagree; 3 = neither agree or disagree; 4 = agree; and 5 = strongly agree) [ 22 ]. Baby’s awakenings during nighttime sleep (times/day) and sleep latency with the mother (in minutes) were also examined as risk factors for PPD. Statistical Analyses Data were analyzed using IBM SPSS Statistics (version 29.0; IBM Ltd., Armonk, NY, United States). Descriptive statistics are presented as means and standard deviations. During this study, we divided two groups based on mealtime regularity (scores of 1–3 for “irregular or neither” and 4–5 for “regular”), breakfast intake (0–6 days/week or 7 days/week), and EPDS score (score of less than 9 for without symptom and ≥ 9 for PPD). The Mann–Whitney U test was used to examine significant differences between the groups. As EPDS scores did not show a normal distribution, generalized estimating equations (GEE) were selected to test the association between EPDS scores (continuous variable) and mealtime regularity (0 = irregular or neither; 1 = regular) and/or breakfast frequency (0 = 0–6 days/week; 1 = 7 days/week). For the GEE, potential confounders (mother’s age, her BMI, personality, OSA-MA, frequency of nighttime snacking, alcohol consumption, caffeinated beverage intake, smoking, and exercise, baby’s age, baby’s nighttime awakenings and sleep latency, and partner’s working days) were adjusted. Statistical significance was set at p < 0.05. Result Participants’ characteristics based on mealtime regularity and breakfast frequency Participant characteristics based on mealtime regularity, breakfast frequency, and EPDS scores are summarized in Table 1 . Mothers with regular mealtime were slightly older than those with irregular or neither mealtime (31.1 ± 4.2 vs. 30.4 ± 4.2 years, p = 0.02) and had significantly lower EPDS scores (6.9 ± 5.7 vs. 8.6 ± 5.7, p < 0.001). Regular mealtime was also associated with more favorable sleep-related outcomes, including higher scores for sleepiness on rising, initiation and maintenance of sleep, refreshing on rising, and sleep length, as assessed using the OSA-MA sleep inventory (all p < 0.05). Mothers who reported daily breakfast consumption (7 days/week) were older, had lower BMI, and exhibited lower EPDS scores compared with those who consumed breakfast 0–6 days/week (7.3 ± 5.6 vs. 8.3 ± 6.0, p = 0.021). Significant differences were also observed in several lifestyle behaviors, including alcohol consumption, smoking, and exercise frequency (all p < 0.01). No significant differences were found between the groups regarding delivery outcomes or infant characteristics, except for baby’s nighttime awakenings (p = 0.039). Further, breakfast intake frequency was significantly higher in the regular mealtime group, compared with the irregular mealtime group (6.1 ± 1.9 vs. 4.9 ± 2.5 days/week, p < 0.001). These results indicated that mealtime regularity and breakfast consumption were closely related behaviors. Table 1 Characteristics of participants by mealtime regularity, breakfast frequency, and EPDS scores The Mann–Whitney U test was used to examine significant differences between the groups. Mealtime regularity Breakfast intake EPDS scores Total Irregular or neither Regular 0–6 days/week 7 days/week Lower (< 9) Higher (≥ 9) n = 841 n = 400 n = 441 n = 318 n = 523 n = 523 n = 318 n (%) n (%) n (%) p n (%) n (%) p n (%) n (%) p Pregnancy by fertilization No 647 (76.9) 312 (78.0) 335 (76.0) 0.512 257 (80.8) 390 (74.6) 0.043 401 (76.7) 246 (77.4) 0.866 Yes 194 (23.1) 88 (22.0) 106 (24.0) 61 (19.2) 133 (25.4) 122 (23.3) 72 (22.6) Gestation period Full-term delivery 778 (92.5) 376 (94.0) 402 (91.1) 0.149 297 (93.3) 481 (91.9) 0.501 496 (94.8) 282 (88.7) < 0.001 Preterm or postterm delivery 63 (7.5) 24 (6.0) 39 (8.8) 21 (6.6) 42 (8.0) 27 (5.2) 36 (11.3) Cesarean section No 685 (81.5) 328 (82.0) 357 (80.9) 0.723 253 (79.5) 432 (82.6) 0.274 425 (81.3) 260 (81.8) 0.466 Yes 156 (18.5) 72 (18.0) 84 (19.0) 65 (20.4) 91 (17.3) 98 (18.7) 58 (18.2) Mean SD Mean SD Mean SD p Mean SD Mean SD p Mean SD Mean SD p Mother’s age (years) 30.8 4.2 30.4 4.2 31.1 4.2 0.02 29.8 4.3 31.4 4.1 < 0.001 30.8 4.1 30.9 4.5 0.654 Baby’s age (months) 6.4 3.5 6.1 3.4 6.7 3.6 0.006 6.1 3.4 6.6 3.6 0.063 6.1 3.5 6.8 3.6 0.005 BMI (kg/㎡) 21.0 3.2 21.1 3.4 21.0 3.0 0.715 21.5 3.4 20.7 3.0 < 0.001 21.0 2.9 21.1 3.5 0.653 Personality_Extraversion (score) 4.1 1.4 4.1 1.4 4.1 1.4 0.905 4.1 1.4 4.1 1.4 0.766 4.2 1.4 3.8 1.3 < 0.001 Personality_Agreeableness (score) 4.9 1.0 4.8 1.1 5.0 1.0 0.001 4.8 1.0 5.0 1.0 0.003 5.1 1.0 4.7 1.0 < 0.001 Personality_Conscientiousness (score) 3.8 1.2 3.7 1.2 3.8 1.2 0.14 3.6 1.1 3.9 1.2 < 0.001 3.8 1.2 3.8 1.1 0.498 Personality_Neuroticism (score) 4.3 1.2 4.5 1.2 4.2 1.2 0.007 4.4 1.2 4.3 1.2 0.507 4.1 1.2 4.7 1.1 < 0.001 Personality_Openness (score) 3.6 1.1 3.6 1.1 3.6 1.2 0.863 3.7 1.1 3.6 1.1 0.068 3.6 1.2 3.6 1.1 0.99 EPDS scores 7.7 5.8 8.6 5.7 6.9 5.7 < 0.001 8.3 6.0 7.3 5.6 0.021 - - - - - OSA-MA Sleepiness on rising (Zc score) 15.4 5.9 14.7 5.9 16.1 5.9 0.001 15.1 5.8 15.6 6.0 0.134 16.9 5.6 13.1 5.6 < 0.001 OSA-MA Initiation and maintenance of sleep (Zc score) 13.2 5.8 12.7 5.6 13.7 6.0 0.019 13.0 5.8 13.3 5.8 0.984 14.4 6.1 11.3 4.9 < 0.001 OSA-MA Frequent dreaming (Zc score) 16.2 8.6 16.1 8.4 16.3 8.8 0.728 15.8 8.4 16.5 8.7 0.325 17.3 8.6 14.5 8.4 < 0.001 OSA-MA Refreshing on rising (Zc score) 12.6 6.3 11.7 6.0 13.4 6.4 < 0.001 11.9 6.5 12.9 6.2 0.024 14.1 6.3 10.0 5.5 < 0.001 OSA-MA Sleep length (Zc score) 19.4 6.8 18.6 6.9 20.2 6.7 < 0.001 18.8 7.3 19.7 6.5 0.06 20.7 6.5 17.2 6.7 < 0.001 Mealtime regularity (score) 3.2 1.2 - - - - - 2.7 1.2 3.5 1.1 < 0.001 3.3 1.2 3.0 1.2 0.002 Breakfast intake (days/week) 5.5 2.3 4.9 2.5 6.1 1.9 < 0.001 - - - - - 5.6 2.1 5.3 2.4 0.042 Nighttime snack intake (days/week) 2.4 2.7 2.4 2.7 2.3 2.7 0.294 2.3 2.5 2.4 2.8 0.362 2.4 2.7 2.4 2.7 0.991 Alcohol intake (days/week) 0.5 1.3 0.5 1.4 0.5 1.3 0.915 0.8 1.7 0.3 1.0 < 0.001 0.5 1.3 0.6 1.4 0.333 Caffeine intake (days/week) 2.8 2.7 2.8 2.7 2.8 2.7 0.944 2.8 2.5 2.8 2.8 0.283 2.9 2.7 2.6 2.7 0.197 Smoking (days/week) 0.3 1.3 0.4 1.5 0.2 1.0 0.155 0.6 1.8 0.1 0.7 < 0.001 0.1 0.9 0.5 1.7 < 0.001 Exercise (days/week) 0.8 1.6 0.7 1.5 0.8 1.6 0.914 0.9 1.8 0.7 1.5 0.008 0.6 1.5 1.0 1.7 0.006 Baby's awakenings during nighttime sleep (times/day) 1.5 1.2 1.6 1.2 1.4 1.2 0.105 1.4 1.2 1.6 1.2 0.039 1.4 1.2 1.6 1.2 0.023 Duration of baby’s sleep latency with mother (min) 32.9 21.6 35.9 22.7 30.2 20.1 < 0.001 34.8 24.5 31.8 19.5 0.222 31.3 20.3 35.7 23.3 0.004 Partner's working days (days/week) 5.1 0.8 5.2 0.8 5.1 0.8 0.011 5.1 1.0 5.1 0.6 0.231 5.2 0.7 5.0 0.9 0.017 Mothers with higher EPDS scores showed a higher frequency of preterm or postterm deliveries. Additionally, they tended to have older infants, and displayed certain personality traits (lower extraversion and agreeableness, and higher neuroticism). These mothers had lower OSA-MA sleep scores across all domains, irregular mealtime, lower breakfast frequency, higher smoking rates, and higher exercise frequency. Consequently, their babies experienced higher nighttime awakenings, longer sleep onset latency. Finally, the mother’s partner tended to have fewer working days (Table 1 ). Associations between mealtime regularity, breakfast frequency, and EPDS Scores Associations among mealtime regularity, breakfast frequency, and EPDS scores were examined using GEE (Table 2 ). In Model 1, mother’s age, her BMI, personality, pregnancy conditions, and health-related behaviors (sleep, nighttime snacking, alcohol consumption, caffeinated beverage intake, and smoking) were used as covariates. Covariates also covered baby’s age, sex, and sleep condition, and the partner’s working days. Regular mealtime was significantly associated with lower EPDS scores (B = − 0.71; 95% CI − 1.37 to − 0.04; p = 0.036), whereas breakfast frequency was not significantly associated with EPDS scores (B = 0.03; 95% CI − 0.68 to 0.75; p = 0.925). In Model 2, by analyzing both mealtime regularity and breakfast frequency in the same equation, regular mealtime remained significantly associated with lower EPDS scores (B = − 0.76; 95% CI − 1.45 to − 0.07; p = 0.031). By contrast, breakfast frequency remained non-significant (B = 0.23; 95% CI − 0.52 to 0.98; p = 0.545). The quasi-likelihood under the independence model criterion (QIC) indicated a comparable fit across the models. Confounding factors, including baby’s sex and age, gestation period, mother’s personality (extraversion, agreeableness, and neuroticism), OSA-MA scores, smoking and exercise frequency, and partner’s working days were also significantly associated with EPDS scores in Model 2. Table 2 Association between mealtime regularity or breakfast frequency and EPDS scores using GEE analysis 95% CI QIC Independent variables B Lower Upper Wald Chi-Square p Model 1 17436.3 Mealtime regularity -0.71 -1.37 -0.04 4.402 0.036 17530.6 Breakfast frequency 0.03 -0.68 0.75 0.009 0.925 Model 2 17430.1 Mealtime regularity -0.76 -1.45 -0.07 4.66 0.031 Breakfast frequency 0.23 -0.52 0.98 0.367 0.545 Mealtime regularity was divided into irregular/neither and regular categories. Breakfast frequency was divided into 0–6 days/week and 7 days/week. Irregular/neither mealtime or 0–6 days/week breakfast intake were used as a reference in the GEE models. Adjustment included age, BMI, baby’s age (months), baby’s sex, pregnancy by fertilization, gestation period, cesarean section, Big Five personality traits, OSA score, nighttime snack intake, alcohol intake, caffeine intake, smoking, baby’s awakenings during night-time sleep, duration of baby’s sleep latency with mother, and partner’s working days. QIC: quasi-likelihood under the independence model criterion; B: unstandardized regression coefficient; CI: confidence interval. Discussion In this cross-sectional study of first-time Japanese postpartum mothers, regular mealtime was independently associated with lower EPDS scores, whereas breakfast frequency was not. This association remained significant after adjusting for sociodemographic factors, health-related behaviors, and mother and infant sleep characteristics. A previous study has reported an association between regular eating habits and postpartum mental health; however, the study did not clearly define what constituted “regular eating” and did not adjust for breakfast skipping [ 24 ]. To our knowledge, this study is the first to demonstrate an association between irregularity in meal timing and PPD symptoms. In this study, no significant association was observed between breakfast skipping and PPD symptoms. Although numerous studies have reported an association between breakfast skipping and mental health in the general population, evidence regarding the relationship between breakfast skipping and perinatal mental health remains limited [ 19 , 21 ]. Breakfast skipping during or after pregnancy has been associated with inadequate nutritional intake, gestational diabetes, and adverse neurodevelopmental outcomes in the offspring [ 31 – 34 ]. Furthermore, the inadequate intake of key nutrients has been linked to PPD symptoms, underscoring the importance of regular breakfast consumption during the perinatal period [ 13 – 16 ]. Conversely, habitual breakfast skipping may result in regular daily fasting intervals, which could potentially exert beneficial effects on physical and mental health. Several intervention studies in non-pregnant populations have demonstrated that intermittent fasting and time-restricted eating are associated with improved mental health outcomes [ 18 , 35 ]. Intermittent fasting has also been suggested to be effective in improving mental health, especially in relation to gestational diabetes [ 36 ]. Together, these factors may attenuate or obscure the association between breakfast consumption and mental health during the postpartum period in the present study. Irregular eating patterns have recently emerged as an important lifestyle factor associated with mental health and metabolic outcomes. Irregular mealtime is linked to poor mental health, including higher levels of psychological distress and anxiety, and stressful life events [ 37 – 39 ]. Irregular mealtime has been associated with poor sleep quality and increased daytime sleepiness, suggesting a close relationship between disrupted eating rhythms and sleep disturbances [ 40 ]. In this study, irregular mealtime was directly associated with PPD symptoms, even after adjusting for a wide range of potential confounders (including maternal sleep disturbance). Beyond mental health and sleep, irregular mealtime has been associated with obesity and cardiovascular risk among shift and non-shift workers [ 41 – 43 ]. Moreover, discrepancies in mealtime between weekdays and weekends—referred to as “eating jet lag”—have been linked to BMI and lifestyle-related diseases independent of sleep irregularity [ 44 – 46 ]. One plausible mechanism by which irregular mealtime influences mental health is disruption of the circadian clock. The circadian clock is a fundamental system that maintains physiological homeostasis and is entrained by daily environmental cues, particularly light exposure and food intake [ 47 ]. Irregular mealtime provides inconsistent zeitgebers (entrainment stimulation) to the circadian system, leading to circadian misalignment [ 48 ]. Circadian disruption is associated with an increased risk of various health conditions, including metabolic disorders and other lifestyle-related diseases [ 49 ]. Collectively, these findings highlighted irregular mealtime as a novel and potentially modifiable behavioral factor relevant to mental, sleep, and cardiometabolic health. This study had several limitations. Owing to the cross-sectional design, causal relationships between irregular mealtime and postpartum depressive symptoms could not be established. The use of an online self-administered survey may have introduced selection and reporting bias. The study population was limited to first-time Japanese mothers with prior work experience who were not currently employed, which may limit the generalizability of the findings. Although household income is known to be associated with postpartum depression, it was not included as a covariate due to a high proportion of missing data (26.6%). Furthermore, irregular mealtime was assessed using a simplified measure. Future studies should incorporate more detailed assessments of mealtime variability and examine irregular meal skipping and irregular nutrient intake in relation to postpartum depressive symptoms. Conclusion In conclusion, this cross-sectional study demonstrated that irregular mealtime was independently associated with PPD symptoms among first-time Japanese mothers, even after accounting for sleep disturbances and other relevant confounding factors. Further prospective and interventional studies are needed to clarify the causal relationship and determine whether interventions targeting mealtime regularity may contribute to the prevention or management of postpartum depression. Declarations Competing Interests Y.M. is a full-time employee of the Combi Corporation, which conducted the online survey and provided financial support for this study to the other authors. Funding This work was partially supported by the Combi Corporation and JST-FOREST Program (JPMJFR205G for Y.T.). Author Contribution Y.T., Y.M., Y.L., and S.S. collected the data, wrote the main manuscript text, and prepared tables. All authors reviewed the manuscript. Data Availability These data will be provided to the researchers upon request for research purposes. References Shorey S, Chee CYI, Ng ED, Chan YH, Tam WWS, Chong YS. Prevalence and incidence of postpartum depression among healthy mothers: A systematic review and meta-analysis. 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Kubota C, Okada T, Aleksic B, Nakamura Y, Kunimoto S, Morikawa M, Shiino T, Tamaji A, Ohoka H, Banno N, Morita T, Murase S, Goto S, Kanai A, Masuda T, Ando M, Ozaki N. Factor structure of the Japanese version of the Edinburgh Postnatal Depression Scale in the postpartum period. PLoS ONE. 2014;9(8):e103941. 10.1371/journal.pone.0103941 . Yamamoto Y. Standardization of revised version of OSA sleep inventory for middle age and aged. Brain Sci Mental Disorder. 1999;10:401–9. Yamashita S, Oe M, Kimura M, Okuyama Y, Seino S, Kajiyama D, Matsuoka R, Masuda Y,Tsukinoki K (2022) Improving Effect of Acetic Acid Bacteria ( Gluconacetobacter hansenii GK-1) on sIgA and Physical Conditions in Healthy People: Double-Blinded Placebo-Controlled Study. Food and Nutrition Sciences 13 (06):541–557. doi:10.4236/fns.2022.136041. Atomei OL, Vicoveanu P, Iațcu CO, Gliga FI, Craciun CC, Tarcea M. Associations Between Maternal Meal Frequency Patterns During Pregnancy and Neonatal Anthropometric Outcomes: A Quantitative Cross-Sectional Study. Nutrients. 2025;17(15). 10.3390/nu17152437 . Schwedhelm C, Lipsky LM, Temmen CD, Nansel TR. Eating Patterns during Pregnancy and Postpartum and Their Association with Diet Quality and Energy Intake. Nutrients. 2022;14(6). 10.3390/nu14061167 . Imaizumi K, Murata T, Isogami H, Fukuda T, Kyozuka H, Yasuda S, Yamaguchi A, Sato A, Ogata Y, Shinoki K, Hosoya M, Yasumura S, Hashimoto K, Fujimori K, Nishigori H, Kamijima M, Yamazaki S, Ohya Y, Kishi R, Yaegashi N, Mori C, Ito S, Yamagata Z, Inadera H, Nakayama T, Sobue T, Shima M, Nakamura H, Suganuma N, Kusuhara K, Katoh T. The Japan E, Children’s Study G (2024) Association between daily breakfast habit during pregnancy and neurodevelopment in 3-year-old offspring: The Japan Environment and Children’s Study. Scientific Reports 14 (1):6337. 10.1038/s41598-024-55912-x Mie S, Masayo M, Megumi H. Effects of skipping breakfast on dietary intake and circulating and urinary nutrients during pregnancy. Asia Pac J Clin Nutr. 2019;28(1). 10.6133/apjcn.201903_28(1).0014 . Sharifi S, Rostami F, Babaei Khorzoughi K, Rahmati M. Effect of time-restricted eating and intermittent fasting on cognitive function and mental health in older adults: A systematic review. Prev Med Rep. 2024;42:102757. 10.1016/j.pmedr.2024.102757 . Ali AM, Kunugi H. Intermittent Fasting, Dietary Modifications, and Exercise for the Control of Gestational Diabetes and Maternal Mood Dysregulation: A Review and a Case Report. Int J Environ Res Public Health. 2020;17(24). 10.3390/ijerph17249379 . Maruo Y, Irie Y, Obata Y, Takayama K, Yamaguchi H, Kosugi M, Hazama Y, Yasuda T. Medium-term Influence of the Coronavirus Disease 2019 Pandemic on Patients with Diabetes: A Single-center Cross-sectional Study. Intern Med. 2022;61(3):303–11. 10.2169/internalmedicine.8010-21 . Faris ME, Vitiello MV, Abdelrahim DN, Cheikh Ismail L, Jahrami HA, Khaleel S, Khan MS, Shakir AZ, Yusuf AM, Masaad AA, Bahammam AS. Eating habits are associated with subjective sleep quality outcomes among university students: findings of a cross-sectional study. Sleep Breath. 2022;26(3):1365–76. 10.1007/s11325-021-02506-w . Qiu D, He J, Li Y, Ouyang F, Xiao S. Stressful Life Events, Unhealthy Eating Behaviors and Obesity among Chinese Government Employees: A Follow-Up Study. Nutrients. 2023;15(11). 10.3390/nu15112637 . Shimura A, Hideo S, Takaesu Y, Nomura R, Komada Y, Inoue T. Comprehensive assessment of the impact of life habits on sleep disturbance, chronotype, and daytime sleepiness among high-school students. Sleep Med. 2018;44:12–8. 10.1016/j.sleep.2017.10.011 . Sato N, Terasaki H, Tahara Y, Michie M, Umezawa A, Shibata S. Day-to-Day Variability in Meal Timing and Its Association with Body Mass Index: A Study Using Data from a Japanese Food-Logging Mobile Application. Nutrients. 2025;17(22). 10.3390/nu17223504 . Pot GK, Almoosawi S, Stephen AM. Meal irregularity and cardiometabolic consequences: results from observational and intervention studies. Proc Nutr Soc. 2016;75(4):475–86. 10.1017/s0029665116000239 . Samhat Z, Attieh R, Sacre Y. Relationship between night shift work, eating habits and BMI among nurses in Lebanon. BMC Nurs. 2020;19:25. 10.1186/s12912-020-00412-2 . Chen YE, Ku CW, Chong MF, Yap F, Chan JKY, Loy SL, Chen LW. Associations of > 1-h compared with 1-h meal timing variability (eating jetlag) with plasma glycemic parameters and continuous glucose monitoring measures among pregnant females: a prospective cohort study. Am J Clin Nutr. 2025;122(1):244–54. 10.1016/j.ajcnut.2025.04.026 . Teixeira GP, da Cunha NB, Azeredo CM, Rinaldi AEM, Crispim CA. Eating time variation from weekdays to weekends and its association with dietary intake and BMI in different chronotypes: findings from National Health and Nutrition Examination Survey (NHANES) 2017–2018. Br J Nutr. 2024;131(7):1281–8. 10.1017/s0007114523002738 . Zerón-Rugerio MF, Hernáez Á, Porras-Loaiza AP, Cambras T, Izquierdo-Pulido M. Eating Jet Lag: A Marker of the Variability in Meal Timing and Its Association with Body Mass Index. Nutrients. 2019;11(12). 10.3390/nu11122980 . Tahara Y, Shibata S. Circadian rhythms of liver physiology and disease: experimental and clinical evidence. Nat Rev Gastroenterol Hepatol. 2016;13(4):217–26. 10.1038/nrgastro.2016.8 . Potter GD, Cade JE, Grant PJ, Hardie LJ. Nutrition and the circadian system. Br J Nutr. 2016;116(3):434–42. 10.1017/s0007114516002117 . Bass J, Takahashi JS. Circadian integration of metabolism and energetics. Science. 2010;330(6009):1349–54. 10.1126/science.1195027 . Additional Declarations Competing interest reported. Y.M. is a full-time employee of the Combi Corporation, which conducted the online survey and provided financial support for this study to the other authors. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 30 Mar, 2026 Reviews received at journal 23 Mar, 2026 Reviews received at journal 21 Mar, 2026 Reviewers agreed at journal 13 Mar, 2026 Reviewers agreed at journal 10 Mar, 2026 Reviewers agreed at journal 02 Mar, 2026 Reviewers invited by journal 02 Mar, 2026 Editor invited by journal 23 Feb, 2026 Editor assigned by journal 20 Feb, 2026 Submission checks completed at journal 20 Feb, 2026 First submitted to journal 19 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8921233","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":600793184,"identity":"cd335782-54bd-4395-b080-79940c133e5c","order_by":0,"name":"Yu Tahara","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEUlEQVRIiWNgGAWjYJACZhDBL8HYAKQO8MCFwXwcGsBaJGeQrMXgBph3gLCjDG7kH/xcUHNP3vh2c9uHD3/uyOi2H2CTYKixY2Cejd0agxvJzNIzjhUbbrtzsHnmzLZnPGZnEoBajiUzMM7BbiVQC4M0D1sC47Ybic3MvA2HecwO5H+TYGA7wMA4IwGnLb95/iXYb54B1MLzB6jl/AOgLf/wamGT5m1LSNwgAdLCBtRyA+gwxjbcWiTPPDaz5u1LSJ4BdBjjzDaQlgfMFol9yTy4/MJ3PPHxbZ5vCbb9M9IfM3z4c9je7HwC440P3+zkDHGEmAJ2k4BO4jGcgVWKQR67SWApCZxSo2AUjIJRMLIAANjWYToBzOczAAAAAElFTkSuQmCC","orcid":"","institution":"Hiroshima University","correspondingAuthor":true,"prefix":"","firstName":"Yu","middleName":"","lastName":"Tahara","suffix":""},{"id":600793185,"identity":"a0229dc4-db2e-4f0a-bbf4-ae45f71d2f0d","order_by":1,"name":"Yuko Makioka","email":"","orcid":"","institution":"Combi Corporation","correspondingAuthor":false,"prefix":"","firstName":"Yuko","middleName":"","lastName":"Makioka","suffix":""},{"id":600793186,"identity":"211ee7bd-d841-4e8f-8a74-82b9b1a3c4fa","order_by":2,"name":"Yun-Peng Lo","email":"","orcid":"","institution":"Hiroshima University","correspondingAuthor":false,"prefix":"","firstName":"Yun-Peng","middleName":"","lastName":"Lo","suffix":""},{"id":600793187,"identity":"2faed242-2530-4861-9608-fd4c07817e5f","order_by":3,"name":"Tatsuhiko Kubo","email":"","orcid":"","institution":"Hiroshima University","correspondingAuthor":false,"prefix":"","firstName":"Tatsuhiko","middleName":"","lastName":"Kubo","suffix":""},{"id":600793188,"identity":"7ec42f39-dee9-42c2-9efd-a718dfee6314","order_by":4,"name":"Shigenobu Shibata","email":"","orcid":"","institution":"Hiroshima University","correspondingAuthor":false,"prefix":"","firstName":"Shigenobu","middleName":"","lastName":"Shibata","suffix":""}],"badges":[],"createdAt":"2026-02-19 23:23:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8921233/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8921233/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104402670,"identity":"e62f5f1b-faf1-4dab-be24-3419dd23635d","added_by":"auto","created_at":"2026-03-11 12:16:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1006298,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8921233/v1/8c698b62-c86f-41a3-8764-2ae8b915d807.pdf"}],"financialInterests":"Competing interest reported. Y.M. is a full-time employee of the Combi Corporation, which conducted the online survey and provided financial support for this study to the other authors.","formattedTitle":"Association between mealtime regularity and postpartum depression in first-time Japanese mothers: a cross- sectional study","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePostpartum depression (PPD) is a common mental health disorder that affects approximately 17% of mothers worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. PPD has serious consequences on maternal well-being, mother\u0026ndash;infant bonding, and child development [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. PPD is also highly prevalent in Japan, affecting approximately 10\u0026ndash;15% of postpartum mothers [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. PPD has been variably defined as a condition occurring between 4 weeks and 12 months after childbirth [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. However, depressive symptoms frequently emerge during pregnancy rather than after childbirth, underscoring the importance of identifying modifiable lifestyle-related risk factors associated with PPD initiation and severity [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. While psychological therapies and antidepressants effectively treat PPD, access to these treatments remains limited, and preventive strategies targeting lifestyle behaviors are still inadequate [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePPD is associated with daily lifestyle behaviors, such as sleep, physical activity, and food and nutrition. Sleep disturbance, including fragmented sleep, poor sleep quality, and frequent nighttime awakenings related to infant care, has been consistently reported as a risk factor for PPD [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Meanwhile, regular physical activity and exercise have been associated with a lower risk and reduced severity of PPD symptoms [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDietary habits have also been implicated in postpartum mental health issues. A systematic review found that greater adherence to a healthy postpartum diet\u0026mdash;characterized by higher consumption of fruits, vegetables, fish, grains, and legumes, or micronutrients such as vitamin D, iron, vitamin B12, folate, and zinc\u0026mdash;was generally associated with lower PPD symptoms [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In Japanese populations, healthier dietary habits, including a higher intake of fish and omega-3 fatty acids, and overall healthier dietary patterns, are associated with lower depressive symptoms during pregnancy and a reduced risk of PPD [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eConcurrently, chrononutrition, which focuses on the time and regularity of food intake in relation to circadian rhythms, has emerged as an important determinant of mental and metabolic health [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Although breakfast skipping has been linked to depression and mental health outcomes in the non-pregnant population, evidence regarding its association with PPD remains limited [\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. A recent cross-sectional study of pregnant women in Korea found that skipping breakfast was significantly associated with higher PPD scores [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Additionally, associations between irregular mealtime and poor mental health have been reported in the non-pregnancy population [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. A cross-sectional study of Japanese women four months postpartum found that irregular eating patterns, such as \u0026ldquo;not eating meals regularly,\u0026rdquo; were significantly associated with poorer mental health status [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Furthermore, women with poor sleep, depression, anxiety, and stress showed significantly higher odds of unhealthy eating behaviors, including meal skipping and meal delaying [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Overall, the current evidence suggests potential associations between lifestyle behaviors and postpartum mental health. However, more studies are required to better understand the associations between modifiable daily behaviors and postpartum depression.\u003c/p\u003e \u003cp\u003eTherefore, this cross-sectional study investigated the association between mealtime regularity and PPD symptoms in first-time Japanese mothers of infants aged 0\u0026ndash;12 months, after adjusting for sleep quality, health-related behaviors, infant sleep characteristics, and sociodemographic factors.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e \u003cstrong\u003eEthical Approval\u003c/strong\u003e \u003cp\u003e \u003cem\u003eand Data Collection\u003c/em\u003e \u003c/p\u003e \u003c/p\u003e \u003cp\u003eThis cross-sectional study explored the relationships among the postpartum mother\u0026rsquo;s mental health, social and environmental factors, and daily behaviors. Further, all methods used in this cross-sectional study complied with the STROBE statement [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This study also adhered with the guidelines of the Declaration of Helsinki and was approved by Hiroshima University\u0026rsquo;s Ethical Committee for Epidemiology on July 10, 2023 (No. E2023-0047; UMIN000051573). Subsequently, informed consent was provided by all participants in the surveys; they consented to the collection and use of their data for research. Aresearch company (Macromill Inc., Tokyo, Japan) was commissioned to conduct an online survey from Aug 1\u0026ndash;4, 2023. The participants in the research company\u0026rsquo;s cohort lived in Japan. Finally, the company was instructed to collect samples with a 1:1 male-to-female ratio and ensure an even distribution across the ages (1\u0026ndash;12 months old) of the babies.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eA priori power analysis for multiple linear regression was conducted to determine the sample size. Assuming a two-sided α of 0.05, 80% power, and up to 10 covariates, a sample size of approximately 800 participants was sufficient to detect a small effect size (0.02). The inclusion criteria for the participants were as follows: (1) mother who had \u003cem\u003eonly\u003c/em\u003e a firstborn baby aged 0\u0026ndash;12 months; (2) mother who was working before pregnancy; (3) mother who was not working when she answered this questionnaire; and (4) mother whose partner had exhausted childcare leave. The exclusion criteria comprised single mothers living with their baby. Our survey covered 1,030 participants. After excluding those with missing response variables and those who did not meet the inclusion criteria, we analyzed a total of 841 participants.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eQuestionnaire Construction\u003c/h3\u003e\n\u003cp\u003eThe sociodemographic variables included mother\u0026rsquo;s age, baby\u0026rsquo;s age (in months) and sex, and partner\u0026rsquo;s working days (days/weeks). Data were also obtained on whether the pregnancy resulted from infertility treatment, the duration of pregnancy, and presence or absence of cesarean delivery. The mothers\u0026rsquo; anthropometric data, including weight and height, were collected to calculate Body Mass Index (BMI). Their personality data were collected using the Big-Five personality traits [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Each personality trait (extraversion, agreeableness, conscientiousness, neuroticism, and openness) was calculated as the average of the scores on two related questions (average score range: 1\u0026ndash;7).\u003c/p\u003e \u003cp\u003eThe Japanese version of the Edinburgh Postnatal Depression Scale (EPDS) was used to assess postpartum depression [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The EPDS score was calculated as the sum of the 10 questions included in the scale. An EPDS score of \u0026ge;\u0026thinsp;9 was used as an indicator of higher PPD symptoms. The Oguri-Shirakawa-Azumi Sleep Inventory Middle-aged and Aged version (OSA-MA) was used to evaluate sleep problems, which were defined by participants\u0026rsquo; lower scores [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Behaviors related to health markers were assessed based on the number of days per week of breakfast intake, nighttime snack intake, alcohol consumption, caffeinated beverage intake, smoking, and exercise. Mealtime regularity was assessed using the question, \u0026ldquo;Do you currently eat meals at the same time each day?\u0026rdquo; with a five-point answer scale (1\u0026thinsp;=\u0026thinsp;strongly disagree; 2\u0026thinsp;=\u0026thinsp;disagree; 3\u0026thinsp;=\u0026thinsp;neither agree or disagree; 4\u0026thinsp;=\u0026thinsp;agree; and 5\u0026thinsp;=\u0026thinsp;strongly agree) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Baby\u0026rsquo;s awakenings during nighttime sleep (times/day) and sleep latency with the mother (in minutes) were also examined as risk factors for PPD.\u003c/p\u003e\n\u003ch3\u003eStatistical Analyses\u003c/h3\u003e\n\u003cp\u003eData were analyzed using IBM SPSS Statistics (version 29.0; IBM Ltd., Armonk, NY, United States). Descriptive statistics are presented as means and standard deviations. During this study, we divided two groups based on mealtime regularity (scores of 1\u0026ndash;3 for \u0026ldquo;irregular or neither\u0026rdquo; and 4\u0026ndash;5 for \u0026ldquo;regular\u0026rdquo;), breakfast intake (0\u0026ndash;6 days/week or 7 days/week), and EPDS score (score of less than 9 for without symptom and \u0026ge;\u0026thinsp;9 for PPD). The Mann\u0026ndash;Whitney U test was used to examine significant differences between the groups. As EPDS scores did not show a normal distribution, generalized estimating equations (GEE) were selected to test the association between EPDS scores (continuous variable) and mealtime regularity (0\u0026thinsp;=\u0026thinsp;irregular or neither; 1\u0026thinsp;=\u0026thinsp;regular) and/or breakfast frequency (0\u0026thinsp;=\u0026thinsp;0\u0026ndash;6 days/week; 1\u0026thinsp;=\u0026thinsp;7 days/week). For the GEE, potential confounders (mother\u0026rsquo;s age, her BMI, personality, OSA-MA, frequency of nighttime snacking, alcohol consumption, caffeinated beverage intake, smoking, and exercise, baby\u0026rsquo;s age, baby\u0026rsquo;s nighttime awakenings and sleep latency, and partner\u0026rsquo;s working days) were adjusted. Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e"},{"header":"Result","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u0026rsquo; characteristics based on mealtime regularity and breakfast frequency\u003c/h2\u003e \u003cp\u003eParticipant characteristics based on mealtime regularity, breakfast frequency, and EPDS scores are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Mothers with regular mealtime were slightly older than those with irregular or neither mealtime (31.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2 vs. 30.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2 years, p\u0026thinsp;=\u0026thinsp;0.02) and had significantly lower EPDS scores (6.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.7 vs. 8.6\u0026thinsp;\u0026plusmn;\u0026thinsp;5.7, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Regular mealtime was also associated with more favorable sleep-related outcomes, including higher scores for sleepiness on rising, initiation and maintenance of sleep, refreshing on rising, and sleep length, as assessed using the OSA-MA sleep inventory (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Mothers who reported daily breakfast consumption (7 days/week) were older, had lower BMI, and exhibited lower EPDS scores compared with those who consumed breakfast 0\u0026ndash;6 days/week (7.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.6 vs. 8.3\u0026thinsp;\u0026plusmn;\u0026thinsp;6.0, p\u0026thinsp;=\u0026thinsp;0.021). Significant differences were also observed in several lifestyle behaviors, including alcohol consumption, smoking, and exercise frequency (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). No significant differences were found between the groups regarding delivery outcomes or infant characteristics, except for baby\u0026rsquo;s nighttime awakenings (p\u0026thinsp;=\u0026thinsp;0.039). Further, breakfast intake frequency was significantly higher in the regular mealtime group, compared with the irregular mealtime group (6.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9 vs. 4.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5 days/week, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). These results indicated that mealtime regularity and breakfast consumption were closely related behaviors.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of participants by mealtime regularity, breakfast frequency, and EPDS scores The Mann\u0026ndash;Whitney U test was used to examine significant differences between the groups.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"22\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c20\" colnum=\"20\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c21\" colnum=\"21\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c22\" colnum=\"22\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c10\" namest=\"c6\"\u003e \u003cp\u003eMealtime regularity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c16\" namest=\"c12\"\u003e \u003cp\u003eBreakfast intake\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c22\" namest=\"c18\"\u003e \u003cp\u003eEPDS scores\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eIrregular or neither\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eRegular\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e0\u0026ndash;6 days/week\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e7 days/week\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003eLower (\u0026lt;\u0026thinsp;9)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c21\" namest=\"c20\"\u003e \u003cp\u003eHigher (\u0026ge;\u0026thinsp;9)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;841\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;441\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c21\" namest=\"c20\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c21\" namest=\"c20\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePregnancy by fertilization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e647 (76.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e312 (78.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e335 (76.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e257 (80.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e390 (74.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e0.043\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e401 (76.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c21\" namest=\"c20\"\u003e \u003cp\u003e246 (77.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.866\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e194 (23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e88 (22.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e106 (24.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e61 (19.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e133 (25.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e122 (23.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c21\" namest=\"c20\"\u003e \u003cp\u003e72 (22.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestation period\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFull-term delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e778 (92.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e376 (94.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e402 (91.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e297 (93.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e481 (91.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e496 (94.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c21\" namest=\"c20\"\u003e \u003cp\u003e282 (88.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePreterm or postterm delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e63 (7.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e24 (6.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e39 (8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e21 (6.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e42 (8.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e27 (5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c21\" namest=\"c20\"\u003e \u003cp\u003e36 (11.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCesarean section\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e685 (81.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e328 (82.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e357 (80.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e253 (79.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e432 (82.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e425 (81.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c21\" namest=\"c20\"\u003e \u003cp\u003e260 (81.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.466\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e156 (18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e72 (18.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e84 (19.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e65 (20.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e91 (17.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e98 (18.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c21\" namest=\"c20\"\u003e \u003cp\u003e58 (18.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMother\u0026rsquo;s age (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e31.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e29.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e31.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e30.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e30.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.654\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBaby\u0026rsquo;s age (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBMI (kg/㎡)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e21.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e21.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e20.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e21.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e21.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.653\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePersonality_Extraversion (score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.766\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePersonality_Agreeableness (score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePersonality_Conscientiousness (score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.498\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePersonality_Neuroticism (score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePersonality_Openness (score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eEPDS scores\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e0.021\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eOSA-MA Sleepiness on rising (Zc score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e15.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e15.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e16.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e13.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eOSA-MA Initiation and maintenance of sleep (Zc score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.019\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e13.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e13.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e14.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e11.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eOSA-MA Frequent dreaming (Zc score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.728\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e15.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e16.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.325\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e17.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eOSA-MA Refreshing on rising (Zc score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e11.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e12.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e0.024\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e14.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eOSA-MA Sleep length (Zc score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e18.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e19.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e20.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e17.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMealtime regularity (score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBreakfast intake (days/week)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e0.042\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eNighttime snack intake (days/week)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.991\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAlcohol intake (days/week)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.915\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.333\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCaffeine intake (days/week)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.944\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.197\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSmoking (days/week)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eExercise (days/week)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBaby's awakenings during nighttime sleep (times/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e0.039\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e0.023\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDuration of baby\u0026rsquo;s sleep latency with mother (min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e30.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e20.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e34.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e24.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e31.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e19.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e31.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e35.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e23.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePartner's working days (days/week)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.011\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cb\u003e0.017\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMothers with higher EPDS scores showed a higher frequency of preterm or postterm deliveries. Additionally, they tended to have older infants, and displayed certain personality traits (lower extraversion and agreeableness, and higher neuroticism). These mothers had lower OSA-MA sleep scores across all domains, irregular mealtime, lower breakfast frequency, higher smoking rates, and higher exercise frequency. Consequently, their babies experienced higher nighttime awakenings, longer sleep onset latency. Finally, the mother\u0026rsquo;s partner tended to have fewer working days (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAssociations between mealtime regularity, breakfast frequency, and EPDS Scores\u003c/h2\u003e \u003cp\u003eAssociations among mealtime regularity, breakfast frequency, and EPDS scores were examined using GEE (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In Model 1, mother\u0026rsquo;s age, her BMI, personality, pregnancy conditions, and health-related behaviors (sleep, nighttime snacking, alcohol consumption, caffeinated beverage intake, and smoking) were used as covariates. Covariates also covered baby\u0026rsquo;s age, sex, and sleep condition, and the partner\u0026rsquo;s working days. Regular mealtime was significantly associated with lower EPDS scores (B\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.71; 95% CI\u0026thinsp;\u0026minus;\u0026thinsp;1.37 to \u0026minus;\u0026thinsp;0.04; p\u0026thinsp;=\u0026thinsp;0.036), whereas breakfast frequency was not significantly associated with EPDS scores (B\u0026thinsp;=\u0026thinsp;0.03; 95% CI\u0026thinsp;\u0026minus;\u0026thinsp;0.68 to 0.75; p\u0026thinsp;=\u0026thinsp;0.925). In Model 2, by analyzing both mealtime regularity and breakfast frequency in the same equation, regular mealtime remained significantly associated with lower EPDS scores (B\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.76; 95% CI\u0026thinsp;\u0026minus;\u0026thinsp;1.45 to \u0026minus;\u0026thinsp;0.07; p\u0026thinsp;=\u0026thinsp;0.031). By contrast, breakfast frequency remained non-significant (B\u0026thinsp;=\u0026thinsp;0.23; 95% CI\u0026thinsp;\u0026minus;\u0026thinsp;0.52 to 0.98; p\u0026thinsp;=\u0026thinsp;0.545). The quasi-likelihood under the independence model criterion (QIC) indicated a comparable fit across the models. Confounding factors, including baby\u0026rsquo;s sex and age, gestation period, mother\u0026rsquo;s personality (extraversion, agreeableness, and neuroticism), OSA-MA scores, smoking and exercise frequency, and partner\u0026rsquo;s working days were also significantly associated with EPDS scores in Model 2.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between mealtime regularity or breakfast frequency and EPDS scores using GEE analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQIC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIndependent variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWald Chi-Square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17436.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMealtime regularity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.036\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17530.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBreakfast frequency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.925\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17430.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMealtime regularity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.031\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBreakfast frequency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.545\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eMealtime regularity was divided into irregular/neither and regular categories. Breakfast frequency was divided into 0\u0026ndash;6 days/week and 7 days/week. Irregular/neither mealtime or 0\u0026ndash;6 days/week breakfast intake were used as a reference in the GEE models. Adjustment included age, BMI, baby\u0026rsquo;s age (months), baby\u0026rsquo;s sex, pregnancy by fertilization, gestation period, cesarean section, Big Five personality traits, OSA score, nighttime snack intake, alcohol intake, caffeine intake, smoking, baby\u0026rsquo;s awakenings during night-time sleep, duration of baby\u0026rsquo;s sleep latency with mother, and partner\u0026rsquo;s working days.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eQIC: quasi-likelihood under the independence model criterion; B: unstandardized regression coefficient; CI: confidence interval.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this cross-sectional study of first-time Japanese postpartum mothers, regular mealtime was independently associated with lower EPDS scores, whereas breakfast frequency was not. This association remained significant after adjusting for sociodemographic factors, health-related behaviors, and mother and infant sleep characteristics. A previous study has reported an association between regular eating habits and postpartum mental health; however, the study did not clearly define what constituted \u0026ldquo;regular eating\u0026rdquo; and did not adjust for breakfast skipping [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. To our knowledge, this study is the \u003cem\u003efirst\u003c/em\u003e to demonstrate an association between irregularity in meal timing and PPD symptoms.\u003c/p\u003e \u003cp\u003eIn this study, no significant association was observed between breakfast skipping and PPD symptoms. Although numerous studies have reported an association between breakfast skipping and mental health in the general population, evidence regarding the relationship between breakfast skipping and \u003cem\u003eperinatal\u003c/em\u003e mental health remains limited [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Breakfast skipping during or after pregnancy has been associated with inadequate nutritional intake, gestational diabetes, and adverse neurodevelopmental outcomes in the offspring [\u003cspan additionalcitationids=\"CR32 CR33\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Furthermore, the inadequate intake of key nutrients has been linked to PPD symptoms, underscoring the importance of regular breakfast consumption during the perinatal period [\u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Conversely, habitual breakfast skipping may result in regular daily fasting intervals, which could potentially exert beneficial effects on physical and mental health. Several intervention studies in non-pregnant populations have demonstrated that intermittent fasting and time-restricted eating are associated with improved mental health outcomes [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Intermittent fasting has also been suggested to be effective in improving mental health, especially in relation to gestational diabetes [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Together, these factors may attenuate or obscure the association between breakfast consumption and mental health during the postpartum period in the present study.\u003c/p\u003e \u003cp\u003eIrregular eating patterns have recently emerged as an important lifestyle factor associated with mental health and metabolic outcomes. Irregular mealtime is linked to poor mental health, including higher levels of psychological distress and anxiety, and stressful life events [\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Irregular mealtime has been associated with poor sleep quality and increased daytime sleepiness, suggesting a close relationship between disrupted eating rhythms and sleep disturbances [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In this study, irregular mealtime was directly associated with PPD symptoms, even after adjusting for a wide range of potential confounders (including maternal sleep disturbance). Beyond mental health and sleep, irregular mealtime has been associated with obesity and cardiovascular risk among shift and non-shift workers [\u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Moreover, discrepancies in mealtime between weekdays and weekends\u0026mdash;referred to as \u0026ldquo;eating jet lag\u0026rdquo;\u0026mdash;have been linked to BMI and lifestyle-related diseases independent of sleep irregularity [\u003cspan additionalcitationids=\"CR45\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. One plausible mechanism by which irregular mealtime influences mental health is disruption of the circadian clock. The circadian clock is a fundamental system that maintains physiological homeostasis and is entrained by daily environmental cues, particularly light exposure and food intake [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Irregular mealtime provides inconsistent \u003cem\u003ezeitgebers\u003c/em\u003e (entrainment stimulation) to the circadian system, leading to circadian misalignment [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Circadian disruption is associated with an increased risk of various health conditions, including metabolic disorders and other lifestyle-related diseases [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Collectively, these findings highlighted irregular mealtime as a novel and potentially modifiable behavioral factor relevant to mental, sleep, and cardiometabolic health.\u003c/p\u003e \u003cp\u003eThis study had several limitations. Owing to the cross-sectional design, causal relationships between irregular mealtime and postpartum depressive symptoms could not be established. The use of an online self-administered survey may have introduced selection and reporting bias. The study population was limited to first-time Japanese mothers with prior work experience who were not currently employed, which may limit the generalizability of the findings. Although household income is known to be associated with postpartum depression, it was not included as a covariate due to a high proportion of missing data (26.6%). Furthermore, irregular mealtime was assessed using a simplified measure. Future studies should incorporate more detailed assessments of mealtime variability and examine irregular meal skipping and irregular nutrient intake in relation to postpartum depressive symptoms.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this cross-sectional study demonstrated that irregular mealtime was independently associated with PPD symptoms among first-time Japanese mothers, even after accounting for sleep disturbances and other relevant confounding factors. Further prospective and interventional studies are needed to clarify the causal relationship and determine whether interventions targeting mealtime regularity may contribute to the prevention or management of postpartum depression.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eY.M. is a full-time employee of the Combi Corporation, which conducted the online survey and provided financial support for this study to the other authors.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was partially supported by the Combi Corporation and JST-FOREST Program (JPMJFR205G for Y.T.).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eY.T., Y.M., Y.L., and S.S. collected the data, wrote the main manuscript text, and prepared tables. 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Science. 2010;330(6009):1349\u0026ndash;54. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1126/science.1195027\u003c/span\u003e\u003cspan address=\"10.1126/science.1195027\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"chrononutrition, sleep, circadian clock, breakfast skipping, nighttime snack, first-time mothers","lastPublishedDoi":"10.21203/rs.3.rs-8921233/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8921233/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003ePostpartum depression (PPD) is a common mental health condition that negatively affects maternal wellbeing and child development. Although daily lifestyle behaviors have been implicated in PPD, the roles of breakfast skipping and mealtime regularity, which are key components of chrononutrition, remain insufficiently understood. This study examined the associations between mealtime regularity and postpartum depressive symptoms in first-time Japanese mothers.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis cross-sectional study included 841first-time Japanese mothers with a child aged 0\u0026ndash;12 months (UMIN000051573; approved on July 10, 2023). Depressive symptoms were assessed using the Edinburgh Postnatal Depression Scale (EPDS). Mealtime regularity and breakfast frequency were evaluated using self-administered questionnaires. Furthermore, associations between EPDS scores and eating-related behaviors were examined using generalized estimating equations, after adjusting for sociodemographic factors, health-related behaviors, mothers\u0026rsquo; and infants\u0026rsquo; sleep characteristics, and partners\u0026rsquo; working days.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eMothers with regular mealtime had significantly lower EPDS scores than those with irregular mealtime. After full adjustment for potential confounders, regular mealtime remained independently associated with lower EPDS scores, whereas breakfast skipping was not.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eRegular mealtime, rather than breakfast consumption, was independently associated with fewer postpartum depressive symptoms. These findings suggest that the temporal organization of eating behaviors may represent a novel and modifiable lifestyle factor relevant to postpartum mental health. Further longitudinal and interventional studies are warranted to clarify causality and evaluate mealtime regularity as a potential target for PPD prevention.\u003c/p\u003e","manuscriptTitle":"Association between mealtime regularity and postpartum depression in first-time Japanese mothers: a cross- sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-05 18:50:48","doi":"10.21203/rs.3.rs-8921233/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-30T17:55:07+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-24T03:02:44+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-21T05:50:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"290620002042039676156929183614166462005","date":"2026-03-13T11:17:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"20013099172370622094987959549881366024","date":"2026-03-10T22:42:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"226524039500462393041453514887320827086","date":"2026-03-02T09:45:51+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-02T09:25:31+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-23T18:11:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-20T23:31:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-20T23:31:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pregnancy and Childbirth","date":"2026-02-19T23:07:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3d21c882-9c6b-483b-9bbe-a5ab2a80f458","owner":[],"postedDate":"March 5th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-08T13:56:02+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-05 18:50:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8921233","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8921233","identity":"rs-8921233","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}