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Takahashi I, Obara T, Ishikuro M, Orui M, Noda A, Shinoda G, Nagami F, Hozawa A, Nishimura T, Tsuchiya KJ, Kuriyama S. Prospective associations of screen time at age 2 with specific behavioral subscales at age 3: a cohort study. J Public Health (Oxf) 2024:fdae240. [PMID: 39263935 DOI: 10.1093/pubmed/fdae240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Revised: 06/05/2024] [Indexed: 09/13/2024] Open
Abstract
BACKGROUND We aim to discover which, if any, of the subscales of internalizing and externalizing behavioral problems at age 3 are still associated with screen time (ST) at age 2 after adjusting for behavioral problems scores at age 2. METHODS This study was conducted under the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study. Information was gathered prospectively, with 7207 mother-child pairs included in the analysis. Children's ST was categorized in hours a day at age 2 (<1, 1-<2, 2-<4, ≥4). We assessed children's behavioral problems using the Child Behavior Checklist for Ages 1½-5 (CBCL) at ages 2 and 3. 'Having behavioral problems' was defined by them being within a clinical range for internalizing behaviors (withdrawn, somatic complaints, anxious/depressed and emotionally reactive) and externalizing behaviors (attention problems and aggressive behaviors) at age 3. Continuous scores on each of the behavioral problem scales at age 2 were used as covariates. RESULTS Greater ST for children at age 2 was associated with specific subscales for emotionally reactive and aggressive behaviors at age 3. CONCLUSIONS This study found that ST is prospectively associated with some behavioral scales but not others.
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Affiliation(s)
- Ippei Takahashi
- Division of Molecular Epidemiology, Graduate School of Medicine, Tohoku University, 7F, Tohoku Medical Megabank Building 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
| | - Taku Obara
- Division of Molecular Epidemiology, Graduate School of Medicine, Tohoku University, 7F, Tohoku Medical Megabank Building 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, 7F, Tohoku Medical Megabank Building 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
- Department of Pharmaceutical Sciences, Tohoku University Hospital, 1-1 Seiryo-machi, Aoba-ku, Sendai 980-8574, Japan
| | - Mami Ishikuro
- Division of Molecular Epidemiology, Graduate School of Medicine, Tohoku University, 7F, Tohoku Medical Megabank Building 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, 7F, Tohoku Medical Megabank Building 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
| | - Masatsugu Orui
- Division of Molecular Epidemiology, Graduate School of Medicine, Tohoku University, 7F, Tohoku Medical Megabank Building 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, 7F, Tohoku Medical Megabank Building 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
| | - Aoi Noda
- Division of Molecular Epidemiology, Graduate School of Medicine, Tohoku University, 7F, Tohoku Medical Megabank Building 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, 7F, Tohoku Medical Megabank Building 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
- Department of Pharmaceutical Sciences, Tohoku University Hospital, 1-1 Seiryo-machi, Aoba-ku, Sendai 980-8574, Japan
| | - Genki Shinoda
- Division of Molecular Epidemiology, Graduate School of Medicine, Tohoku University, 7F, Tohoku Medical Megabank Building 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, 7F, Tohoku Medical Megabank Building 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
| | - Fuji Nagami
- Department of Public Relations and Planning, Tohoku Medical Megabank Organization, Tohoku University, 3F, Tohoku Medical Megabank Building 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
| | - Atsushi Hozawa
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, 7F, Tohoku Medical Megabank Building 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
- Division of Epidemiology, Graduate School of Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan
- Division of Personalized Prevention and Epidemiology, Graduate School of Medicine, Tohoku University, 7F, Tohoku Medical Megabank Building 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
| | - Tomoko Nishimura
- United Graduate School of Child Development, Hamamatsu University School of Medicine, 1-20-1 Handayama, Chuo-ku, Hamamatsu City, Shizuoka 431-3192, Japan
- Research Center for Child Mental Development, Hamamatsu University School of Medicine, 1-20-1 Handayama, Chuo-ku, Hamamatsu City, Shizuoka 431-3192, Japan
| | - Kenji J Tsuchiya
- United Graduate School of Child Development, Hamamatsu University School of Medicine, 1-20-1 Handayama, Chuo-ku, Hamamatsu City, Shizuoka 431-3192, Japan
- Research Center for Child Mental Development, Hamamatsu University School of Medicine, 1-20-1 Handayama, Chuo-ku, Hamamatsu City, Shizuoka 431-3192, Japan
| | - Shinichi Kuriyama
- Division of Molecular Epidemiology, Graduate School of Medicine, Tohoku University, 7F, Tohoku Medical Megabank Building 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, 7F, Tohoku Medical Megabank Building 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
- Division of Disaster Public Health, International Research Institute of Disaster Science, Tohoku University, 7F, Tohoku Medical Megabank Building 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
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Takahashi I, Obara T, Kikuchi S, Kobayashi N, Obara R, Noda A, Ohsawa M, Ishikawa T, Mano N, Nishigori H, Ueno F, Shinoda G, Murakami K, Orui M, Ishikuro M, Tomita H, Kuriyama S. Combination of taking neuropsychiatric medications and psychological distress in pregnant women, with behavioral problems in children at 2 years of age: The Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study. PCN REPORTS : PSYCHIATRY AND CLINICAL NEUROSCIENCES 2024; 3:e226. [PMID: 39071169 PMCID: PMC11272827 DOI: 10.1002/pcn5.226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/20/2024] [Revised: 06/27/2024] [Accepted: 07/02/2024] [Indexed: 07/30/2024]
Abstract
Aim To examine the association of the combination of taking neuropsychiatric medications from the onset of pregnancy to mid-pregnancy and maternal psychological distress at mid-pregnancy, with children's behavioral problems. Methods Neuropsychiatric medication use from the onset of pregnancy to mid-pregnancy was defined by the self-reported name of the neuropsychiatric medication in the questionnaire in early and mid-pregnancy. Maternal psychological distress was defined by the Kessler Psychological Distress Scale (K6) ≥13 on the questionnaire in mid-pregnancy. We classified the participants into four categories based on the combination of taking neuropsychiatric medications and psychological distress: "None," "Medications only," "K6 ≥ 13 only," and "Both." Children's behavioral problems were assessed using the Child Behavior Checklist for Ages 1½-5 (CBCL) at 2 years of age. The clinical ranges of the internalizing and externalizing scales of the CBCL were defined as behavioral problems. We conducted a multivariable logistic regression analysis to examine the associations between the four categories of maternal exposure and children's behavioral problems. Results Compared with the "None" category (n = 9873), the "K6 ≥ 13 only" category (n = 308) was statistically significantly associated with internalizing and externalizing problems. In contrast, the "Medications only" (n = 93) and "Both" (n = 22) categories were not statistically significantly associated with internalizing and externalizing problems, although the point estimates of the odds ratio in the "Both" category were relatively high (1.58 for the internalizing problem and 2.50 for the externalizing problem). Conclusion The category of mothers taking neuropsychiatric medications and having no psychological distress during pregnancy was not associated with children's behavioral problems in the present population.
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Affiliation(s)
- Ippei Takahashi
- Division of Molecular Epidemiology, Graduate School of MedicineTohoku UniversitySendaiJapan
| | - Taku Obara
- Division of Molecular Epidemiology, Graduate School of MedicineTohoku UniversitySendaiJapan
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank OrganizationTohoku UniversitySendaiJapan
- Department of Pharmaceutical SciencesTohoku University HospitalSendaiJapan
| | - Saya Kikuchi
- Department of PsychiatryTohoku Graduate School of MedicineSendaiJapan
- Department of PsychiatryTohoku University HospitalSendaiJapan
| | - Natsuko Kobayashi
- Department of PsychiatryTohoku Graduate School of MedicineSendaiJapan
- Department of PsychiatryTohoku University HospitalSendaiJapan
| | - Ryo Obara
- Division of Molecular Epidemiology, Graduate School of MedicineTohoku UniversitySendaiJapan
- Department of PsychiatryKawasaki Kokoro HospitalMiyagiJapan
| | - Aoi Noda
- Division of Molecular Epidemiology, Graduate School of MedicineTohoku UniversitySendaiJapan
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank OrganizationTohoku UniversitySendaiJapan
- Department of Pharmaceutical SciencesTohoku University HospitalSendaiJapan
| | - Minoru Ohsawa
- Department of Education and Support for Regional MedicineTohoku University HospitalSendaiJapan
- Department of Kampo MedicineTohoku University HospitalSendaiJapan
| | - Tomofumi Ishikawa
- Laboratory of Clinical PharmacyTohoku University Graduate School of Pharmaceutical SciencesSendaiJapan
| | - Nariyasu Mano
- Department of Pharmaceutical SciencesTohoku University HospitalSendaiJapan
- Laboratory of Clinical PharmacyTohoku University Graduate School of Pharmaceutical SciencesSendaiJapan
| | - Hidekazu Nishigori
- Department of Development and Environmental MedicineFukushima Medical University Graduate School of MedicineFukushimaJapan
| | - Fumihiko Ueno
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank OrganizationTohoku UniversitySendaiJapan
| | - Genki Shinoda
- Division of Molecular Epidemiology, Graduate School of MedicineTohoku UniversitySendaiJapan
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank OrganizationTohoku UniversitySendaiJapan
| | - Keiko Murakami
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank OrganizationTohoku UniversitySendaiJapan
| | - Masatsugu Orui
- Division of Molecular Epidemiology, Graduate School of MedicineTohoku UniversitySendaiJapan
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank OrganizationTohoku UniversitySendaiJapan
| | - Mami Ishikuro
- Division of Molecular Epidemiology, Graduate School of MedicineTohoku UniversitySendaiJapan
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank OrganizationTohoku UniversitySendaiJapan
| | - Hiroaki Tomita
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank OrganizationTohoku UniversitySendaiJapan
- Department of PsychiatryTohoku Graduate School of MedicineSendaiJapan
- Department of PsychiatryTohoku University HospitalSendaiJapan
- International Research, Institute of Disaster ScienceTohoku UniversitySendaiJapan
| | - Shinichi Kuriyama
- Division of Molecular Epidemiology, Graduate School of MedicineTohoku UniversitySendaiJapan
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank OrganizationTohoku UniversitySendaiJapan
- International Research, Institute of Disaster ScienceTohoku UniversitySendaiJapan
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Mizuno S, Wagata M, Nagaie S, Ishikuro M, Obara T, Tamiya G, Kuriyama S, Tanaka H, Yaegashi N, Yamamoto M, Sugawara J, Ogishima S. Development of phenotyping algorithms for hypertensive disorders of pregnancy (HDP) and their application in more than 22,000 pregnant women. Sci Rep 2024; 14:6292. [PMID: 38491024 PMCID: PMC10943000 DOI: 10.1038/s41598-024-55914-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 02/28/2024] [Indexed: 03/18/2024] Open
Abstract
Recently, many phenotyping algorithms for high-throughput cohort identification have been developed. Prospective genome cohort studies are critical resources for precision medicine, but there are many hurdles in the precise cohort identification. Consequently, it is important to develop phenotyping algorithms for cohort data collection. Hypertensive disorders of pregnancy (HDP) is a leading cause of maternal morbidity and mortality. In this study, we developed, applied, and validated rule-based phenotyping algorithms of HDP. Two phenotyping algorithms, algorithms 1 and 2, were developed according to American and Japanese guidelines, and applied into 22,452 pregnant women in the Birth and Three-Generation Cohort Study of the Tohoku Medical Megabank project. To precise cohort identification, we analyzed both structured data (e.g., laboratory and physiological tests) and unstructured clinical notes. The identified subtypes of HDP were validated against reference standards. Algorithms 1 and 2 identified 7.93% and 8.08% of the subjects as having HDP, respectively, along with their HDP subtypes. Our algorithms were high performing with high positive predictive values (0.96 and 0.90 for algorithms 1 and 2, respectively). Overcoming the hurdle of precise cohort identification from large-scale cohort data collection, we achieved both developed and implemented phenotyping algorithms, and precisely identified HDP patients and their subtypes from large-scale cohort data collection.
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Affiliation(s)
- Satoshi Mizuno
- Department of Informatics for Genomic Medicine, Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-Ku, Sendai, Miyagi, 980-8575, Japan
| | - Maiko Wagata
- Department of Feto-Maternal Medical Science, Tohoku Medical Megabank Organization, Tohoku University, Miyagi, Japan
| | - Satoshi Nagaie
- Department of Informatics for Genomic Medicine, Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-Ku, Sendai, Miyagi, 980-8575, Japan
| | - Mami Ishikuro
- Department of Molecular Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Miyagi, Japan
| | - Taku Obara
- Department of Molecular Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Miyagi, Japan
| | - Gen Tamiya
- Department of Statistical Genetics and Genomics, Tohoku Medical Megabank Organization, Tohoku University, Miyagi, Japan
| | - Shinichi Kuriyama
- Department of Molecular Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Miyagi, Japan
| | | | - Nobuo Yaegashi
- Department of Gynecology and Obstetrics, Tohoku University Graduate School of Medicine, Tohoku University, Miyagi, Japan
| | - Masayuki Yamamoto
- Department of Biochemistry and Molecular Biology, Tohoku Medical Megabank Organization, Tohoku University, Miyagi, Japan
| | - Junichi Sugawara
- Department of Gynecology and Obstetrics, Tohoku University Graduate School of Medicine, Tohoku University, Miyagi, Japan
- Suzuki Memorial Hospital, 3-5-5, Satonomori, Iwanumashi, Miyagi, Japan
| | - Soichi Ogishima
- Department of Informatics for Genomic Medicine, Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-Ku, Sendai, Miyagi, 980-8575, Japan.
- Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, Miyagi, Japan.
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4
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Takahashi I, Obara T, Ishikuro M, Murakami K, Ueno F, Noda A, Onuma T, Shinoda G, Nishimura T, Tsuchiya KJ, Kuriyama S. Screen Time at Age 1 Year and Communication and Problem-Solving Developmental Delay at 2 and 4 Years. JAMA Pediatr 2023; 177:1039-1046. [PMID: 37603356 PMCID: PMC10442786 DOI: 10.1001/jamapediatrics.2023.3057] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 06/22/2023] [Indexed: 08/22/2023]
Abstract
Importance Whether some domains of child development are specifically associated with screen time and whether the association continues with age remain unknown. Objective To examine the association between screen time exposure among children aged 1 year and 5 domains of developmental delay (communication, gross motor, fine motor, problem-solving, and personal and social skills) at age 2 and 4 years. Design, Participants, and Setting This cohort study was conducted under the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study. Pregnant women at 50 obstetric clinics and hospitals in the Miyagi and Iwate prefectures in Japan were recruited into the study between July 2013 and March 2017. The information was collected prospectively, and 7097 mother-child pairs were included in the analysis. Data analysis was performed on March 20, 2023. Exposure Four categories of screen time exposure were identified for children aged 1 year (<1, 1 to <2, 2 to <4, or ≥4 h/d). Main Outcomes and Measures Developmental delays in the 5 domains for children aged 2 and 4 years were assessed using the Japanese version of the Ages & Stages Questionnaires, Third Edition. Each domain ranged from 0 to 60 points. Developmental delay was defined if the total score for each domain was less than 2 SDs from its mean score. Results Of the 7097 children in this study, 3674 were boys (51.8%) and 3423 were girls (48.2%). With regard to screen time exposure per day, 3440 children (48.5%) had less than 1 hour, 2095 (29.5%) had 1 to less than 2 hours, 1272 (17.9%) had 2 to less than 4 hours, and 290 (4.1%) had 4 or more hours. Children's screen time was associated with a higher risk of developmental delay at age 2 years in the communication (odds ratio [OR], 1.61 [95% CI, 1.23-2.10] for 1 to <2 h/d; 2.04 [1.52-2.74] for 2 to <4 h/d; 4.78 [3.24-7.06] for ≥4 vs <1 h/d), fine motor (1.74 [1.09-2.79] for ≥4 vs <1 h/d), problem-solving (1.40 [1.02-1.92] for 2 to <4 h/d; 2.67 [1.72-4.14] for ≥4 vs <1 h/d), and personal and social skills (2.10 [1.39-3.18] for ≥4 vs <1 h/d) domains. Regarding risk of developmental delay at age 4 years, associations were identified in the communication (OR, 1.64 [95% CI, 1.20-2.25] for 2 to <4 h/d; 2.68 [1.68-4.27] for ≥4 vs <1 h/d) and problem-solving (1.91 [1.17-3.14] for ≥4 vs <1 h/d) domains. Conclusions and Relevance In this study, greater screen time for children aged 1 year was associated with developmental delays in communication and problem-solving at ages 2 and 4 years. These findings suggest that domains of developmental delay should be considered separately in future discussions on screen time and child development.
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Affiliation(s)
- Ippei Takahashi
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Taku Obara
- Graduate School of Medicine, Tohoku University, Sendai, Japan
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Department of Pharmaceutical Sciences, Tohoku University Hospital, Sendai, Japan
| | - Mami Ishikuro
- Graduate School of Medicine, Tohoku University, Sendai, Japan
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Keiko Murakami
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Fumihiko Ueno
- Graduate School of Medicine, Tohoku University, Sendai, Japan
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Aoi Noda
- Graduate School of Medicine, Tohoku University, Sendai, Japan
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Department of Pharmaceutical Sciences, Tohoku University Hospital, Sendai, Japan
| | - Tomomi Onuma
- Graduate School of Medicine, Tohoku University, Sendai, Japan
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Genki Shinoda
- Graduate School of Medicine, Tohoku University, Sendai, Japan
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Tomoko Nishimura
- United Graduate School of Child Development, Hamamatsu University School of Medicine, Hamamatsu, Japan
- Research Center for Child Mental Development, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - Kenji J. Tsuchiya
- United Graduate School of Child Development, Hamamatsu University School of Medicine, Hamamatsu, Japan
- Research Center for Child Mental Development, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - Shinichi Kuriyama
- Graduate School of Medicine, Tohoku University, Sendai, Japan
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
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5
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Mizuno S, Nagaie S, Tamiya G, Kuriyama S, Obara T, Ishikuro M, Tanaka H, Kinoshita K, Sugawara J, Yamamoto M, Yaegashi N, Ogishima S. Establishment of the early prediction models of low-birth-weight reveals influential genetic and environmental factors: a prospective cohort study. BMC Pregnancy Childbirth 2023; 23:628. [PMID: 37653383 PMCID: PMC10472725 DOI: 10.1186/s12884-023-05919-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Accepted: 08/12/2023] [Indexed: 09/02/2023] Open
Abstract
BACKGROUND Low birth weight (LBW) is a leading cause of neonatal morbidity and mortality, and increases various disease risks across life stages. Prediction models of LBW have been developed before, but have limitations including small sample sizes, absence of genetic factors and no stratification of neonate into preterm and term birth groups. In this study, we challenged the development of early prediction models of LBW based on environmental and genetic factors in preterm and term birth groups, and clarified influential variables for LBW prediction. METHODS We selected 22,711 neonates, their 21,581 mothers and 8,593 fathers from the Tohoku Medical Megabank Project Birth and Three-Generation cohort study. To establish early prediction models of LBW for preterm birth and term birth groups, we trained AI-based models using genetic and environmental factors of lifestyles. We then clarified influential environmental and genetic factors for predicting LBW in the term and preterm groups. RESULTS We identified 2,327 (10.22%) LBW neonates consisting of 1,077 preterm births and 1,248 term births. Our early prediction models archived the area under curve 0.96 and 0.95 for term LBW and preterm LBW models, respectively. We revealed that environmental factors regarding eating habits and genetic features related to fetal growth were influential for predicting LBW in the term LBW model. On the other hand, we identified that genomic features related to toll-like receptor regulations and infection reactions are influential genetic factors for prediction in the preterm LBW model. CONCLUSIONS We developed precise early prediction models of LBW based on lifestyle factors in the term birth group and genetic factors in the preterm birth group. Because of its accuracy and generalisability, our prediction model could contribute to risk assessment of LBW in the early stage of pregnancy and control LBW risk in the term birth group. Our prediction model could also contribute to precise prediction of LBW based on genetic factors in the preterm birth group. We then identified parental genetic and maternal environmental factors during pregnancy influencing LBW prediction, which are major targets for understanding the LBW to address serious burdens on newborns' health throughout life.
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Affiliation(s)
- Satoshi Mizuno
- Department of Informatics for Genomic Medicine, Group of Integrated Database Systems, Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-Ku, Sendai, Miyagi, 980-8575, Japan
| | - Satoshi Nagaie
- Department of Informatics for Genomic Medicine, Group of Integrated Database Systems, Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-Ku, Sendai, Miyagi, 980-8575, Japan
| | - Gen Tamiya
- Department of Statistical Genetics and Genomics, Group of Disease Risk Prediction, Tohoku Medical Megabank Organization, Tohoku University, Miyagi, Japan
| | - Shinichi Kuriyama
- Department of Molecular Epidemiology, Group of the Birth and Three-Generation Cohort Study, Tohoku Medical Megabank Organization, Tohoku University, Miyagi, Japan
| | - Taku Obara
- Department of Molecular Epidemiology, Group of the Birth and Three-Generation Cohort Study, Tohoku Medical Megabank Organization, Tohoku University, Miyagi, Japan
| | - Mami Ishikuro
- Department of Molecular Epidemiology, Group of the Birth and Three-Generation Cohort Study, Tohoku Medical Megabank Organization, Tohoku University, Miyagi, Japan
| | - Hiroshi Tanaka
- Medical Data Science Promotion, Tokyo Medical and Dental University, Tokyo, Japan
| | - Kengo Kinoshita
- Department of Statistical Genetics and Genomics, Group of Systems Bioinformatics, Tohoku Medical Megabank Organization, Tohoku University, Miyagi, Japan
| | - Junichi Sugawara
- Department of Gynecology and Obstetrics, Tohoku University Graduate School of Medicine, Tohoku University, Miyagi, Japan
- Department of Feto-Maternal Medical Science, Group of Community Medical Supports, Tohoku Medical Megabank Organization, Tohoku University, Miyagi, Japan
- Suzuki Memorial Hospital 3-5-5, Satonomori, Iwanumashi, Miyagi, 989-2481, Japan
| | - Masayuki Yamamoto
- Department of Medical Biochemistry, Graduate School of Medicine, Tohoku University, Sendai, Japan
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Miyagi, Japan
| | - Nobuo Yaegashi
- Department of Gynecology and Obstetrics, Tohoku University Graduate School of Medicine, Tohoku University, Miyagi, Japan
| | - Soichi Ogishima
- Department of Informatics for Genomic Medicine, Group of Integrated Database Systems, Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-Ku, Sendai, Miyagi, 980-8575, Japan.
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6
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Takahashi I, Obara T, Kikuchi S, Kobayashi M, Ishikuro M, Murakami K, Ueno F, Noda A, Onuma T, Matsuzaki F, Kobayashi N, Hamada H, Iwama N, Saito M, Sugawara J, Tomita H, Kure S, Yaegashi N, Kuriyama S. Association between maternal psychological distress and children's neurodevelopment in offspring aged 4 years in Japan: The Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study. J Paediatr Child Health 2023; 59:548-554. [PMID: 36751990 DOI: 10.1111/jpc.16353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 01/09/2023] [Accepted: 01/22/2023] [Indexed: 02/09/2023]
Abstract
AIM An association between maternal psychological distress and children's development has been reported, but reports from Japan are limited. This study aimed to examine the association of maternal psychological distress with children's neurodevelopment in Japan. METHODS The study assessed data of 7646 mother-infant pairs in the Japanese population. We used Kessler Psychological Distress Scale, a screening tool for psychological distress, to assess maternal psychological distress in early pregnancy and 2 years postpartum and divided it into four categories: none in both the pre-natal and post-natal periods, only the pre-natal period, only the post-natal period and both the pre-natal and post-natal periods. Children's neurodevelopment was assessed using the Ages & Stages Questionnaires Third Edition (ASQ-3) at 4 years of age. ASQ-3 comprises five domains (communication, gross motor, fine motor, problem solving and personal-social), and the score of less than -2 standard deviation relative to the mean in reference was defined as having developmental delay. We conducted multivariate logistic regression analysis to examine the association between maternal psychological distress and children's neurodevelopment. RESULTS The prevalence of developmental delay of communication, gross motor, fine motor, problem solving and personal-social were 4.0%, 4.3%, 4.9%, 3.8% and 4.6%, respectively. Maternal psychological distress in only the postpartum period and both pre-natal and postpartum periods were associated with risks of developmental delay in all domains. Maternal psychological distress in only the pre-natal period was associated with developmental delay in communication. CONCLUSIONS Maternal psychological distress is associated with risks of children's developmental delay.
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Affiliation(s)
- Ippei Takahashi
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Taku Obara
- Graduate School of Medicine, Tohoku University, Sendai, Japan.,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.,Department of Pharmaceutical Sciences, Tohoku University Hospital, Sendai, Japan
| | - Saya Kikuchi
- Graduate School of Medicine, Tohoku University, Sendai, Japan.,Department of Psychiatry, Tohoku University Hospital, Sendai, Japan
| | - Mika Kobayashi
- Graduate School of Medicine, Tohoku University, Sendai, Japan.,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Mami Ishikuro
- Graduate School of Medicine, Tohoku University, Sendai, Japan.,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Keiko Murakami
- Graduate School of Medicine, Tohoku University, Sendai, Japan.,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Fumihiko Ueno
- Graduate School of Medicine, Tohoku University, Sendai, Japan.,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Aoi Noda
- Graduate School of Medicine, Tohoku University, Sendai, Japan.,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.,Department of Pharmaceutical Sciences, Tohoku University Hospital, Sendai, Japan
| | - Tomomi Onuma
- Graduate School of Medicine, Tohoku University, Sendai, Japan.,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Fumiko Matsuzaki
- Graduate School of Medicine, Tohoku University, Sendai, Japan.,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Natsuko Kobayashi
- Graduate School of Medicine, Tohoku University, Sendai, Japan.,Department of Psychiatry, Tohoku University Hospital, Sendai, Japan
| | - Hirotaka Hamada
- Graduate School of Medicine, Tohoku University, Sendai, Japan.,Department of Obstetrics and Gynecology, Tohoku University Hospital, Sendai, Japan
| | - Noriyuki Iwama
- Graduate School of Medicine, Tohoku University, Sendai, Japan.,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.,Department of Obstetrics and Gynecology, Tohoku University Hospital, Sendai, Japan
| | - Masatoshi Saito
- Department of Obstetrics and Gynecology, Tohoku University Hospital, Sendai, Japan
| | - Junichi Sugawara
- Graduate School of Medicine, Tohoku University, Sendai, Japan.,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Hiroaki Tomita
- Graduate School of Medicine, Tohoku University, Sendai, Japan.,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.,Department of Psychiatry, Tohoku University Hospital, Sendai, Japan.,International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
| | - Shigeo Kure
- Graduate School of Medicine, Tohoku University, Sendai, Japan.,International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
| | - Nobuo Yaegashi
- Graduate School of Medicine, Tohoku University, Sendai, Japan.,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.,Department of Obstetrics and Gynecology, Tohoku University Hospital, Sendai, Japan
| | - Shinichi Kuriyama
- Graduate School of Medicine, Tohoku University, Sendai, Japan.,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.,International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
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7
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Yu Z, Matsukawa N, Saigusa D, Motoike IN, Ono C, Okamura Y, Onuma T, Takahashi Y, Sakai M, Kudo H, Obara T, Murakami K, Shirota M, Kikuchi S, Kobayashi N, Kikuchi Y, Sugawara J, Minegishi N, Ogishima S, Kinoshita K, Yamamoto M, Yaegashi N, Kuriyama S, Koshiba S, Tomita H. Plasma metabolic disturbances during pregnancy and postpartum in women with depression. iScience 2022; 25:105666. [PMID: 36505921 PMCID: PMC9732390 DOI: 10.1016/j.isci.2022.105666] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 08/17/2022] [Accepted: 11/21/2022] [Indexed: 11/27/2022] Open
Abstract
Examining plasma metabolic profiling during pregnancy and postpartum could help clinicians understand the risk factors for postpartum depression (PPD) development. This analysis targeted paired plasma metabolites in mid-late gestational and 1 month postpartum periods in women with (n = 209) or without (n = 222) PPD. Gas chromatogram-mass spectrometry was used to analyze plasma metabolites at these two time points. Among the 170 objected plasma metabolites, principal component analysis distinguished pregnancy and postpartum metabolites but failed to discriminate women with and without PPD. Compared to women without PPD, those with PPD exhibited 37 metabolites with disparate changes during pregnancy and the 1-month postpartum period and an enriched citrate cycle. Machine learning and multivariate statistical analysis identified two or three compounds that could be potential biomarkers for PPD prediction during pregnancy. Our findings suggest metabolic disturbances in women with depression and may help to elucidate metabolic processes associated with PPD development.
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Affiliation(s)
- Zhiqian Yu
- Department of Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan,Corresponding author
| | - Naomi Matsukawa
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Daisuke Saigusa
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan,Laboratory of Biomedical and Analytical Sciences, Faculty of Pharma-Science, Teikyo University
| | - Ikuko N. Motoike
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan,Department of System Bioinformatics, Graduate School of Information Sciences, Tohoku University, Sendai, Japan
| | - Chiaki Ono
- Department of Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Yasunobu Okamura
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan,Innovations in Next-Generation Medicine, Advanced Research Center, Tohoku University, Sendai, Japan
| | - Tomomi Onuma
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Yuta Takahashi
- Department of Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Mai Sakai
- Department of Disaster Psychiatry, International Research Institute for Disaster Science, Tohoku University, Sendai, Japan
| | - Hisaaki Kudo
- Department of Biobank Life Science, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Taku Obara
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Keiko Murakami
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Matusyuki Shirota
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Saya Kikuchi
- Department of Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Natsuko Kobayashi
- Department of Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Yoshie Kikuchi
- Department of Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Junichi Sugawara
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Naoko Minegishi
- Department of Biobank Life Science, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Soichi Ogishima
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Kengo Kinoshita
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan,Department of System Bioinformatics, Graduate School of Information Sciences, Tohoku University, Sendai, Japan
| | - Masayuki Yamamoto
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan,Department of Medical Biochemistry, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Nobuo Yaegashi
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan,Department of Gynecology and Obstetrics, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Shinichi Kuriyama
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan,Division of Disaster Public Health, International Research Institute for Disaster Science, Tohoku University, Sendai, Japan
| | - Seizo Koshiba
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan,Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Hiroaki Tomita
- Department of Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan,Department of Disaster Psychiatry, International Research Institute for Disaster Science, Tohoku University, Sendai, Japan
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8
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Takahashi I, Murakami K, Kobayashi M, Kikuchi S, Igarashi A, Obara T, Ishikuro M, Ueno F, Noda A, Onuma T, Matsuzaki F, Kobayashi N, Hamada H, Iwama N, Saito M, Sugawara J, Tomita H, Yaegashi N, Kure S, Kuriyama S. Association of maternal psychological distress and the use of childcare facilities with children's behavioral problems: the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study. BMC Psychiatry 2022; 22:693. [PMID: 36357866 PMCID: PMC9650864 DOI: 10.1186/s12888-022-04330-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 10/21/2022] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Childcare facilities are a factor that lowers the established association of mother's postnatal psychiatric symptoms with children's behavioral problems. However, no studies have considered the prenatal psychiatric symptoms yet. This study examined whether the use of childcare facilities moderates the association of maternal psychological distress in early pregnancy and at two years postpartum with behavioral problems in children aged four years. METHODS The present study was based on the data from 23,130 mother-child pairs participating in the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study. K6 was used to classify maternal psychological distress in early pregnancy and at two years postpartum into four categories: none in both prenatal and postnatal periods (none), only the prenatal period (prenatal only); only the postnatal period (postnatal only); both prenatal and postnatal periods (both). The children's behavioral problems were assessed using the Child Behavior Checklist for Ages 1½-5 (CBCL) aged four years. The clinical range of the externalizing, internalizing, and total problem scales of the CBCL was defined as having behavioral problems. To examine whether availing childcare facilities moderates the association between maternal psychological distress and children's behavioral problems, we conducted a stratified analysis based on the use of childcare facilities or not, at two years of age. The interaction term between maternal psychological distress and use of childcare facilities was included as a covariate in the multivariate logistic regression analysis to confirm the p-value for the interaction. RESULTS The prevalence of the clinical ranges of externalizing problems, internalizing problems, and clinical range of total problems were 13.7%, 15.4%, and 5.8%, respectively. The association of maternal psychological distress with a high risk of children's behavioral problems was significant; however, the association between prenatal only psychological distress and externalizing problems in the group that did not use childcare facilities was not significant. Interactions between the use of childcare facilities and maternal psychological distress on behavioral problems in children were not significant. CONCLUSIONS Use of childcare facilities did not moderate the association of maternal psychological distress in early pregnancy and at two years postpartum with behavioral problems in children aged four years.
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Affiliation(s)
- Ippei Takahashi
- grid.69566.3a0000 0001 2248 6943Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Keiko Murakami
- Tohoku University Graduate School of Medicine, Sendai, Japan. .,Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-Machi, Aoba-Ku, Sendai, 980-8573, Japan.
| | - Mika Kobayashi
- grid.69566.3a0000 0001 2248 6943Tohoku University Graduate School of Medicine, Sendai, Japan ,grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-Machi, Aoba-Ku, Sendai, 980-8573 Japan
| | - Saya Kikuchi
- grid.69566.3a0000 0001 2248 6943Tohoku University Graduate School of Medicine, Sendai, Japan ,grid.412757.20000 0004 0641 778XDepartment of Psychiatry, Tohoku University Hospital, Sendai, Japan
| | - Ayaka Igarashi
- grid.69566.3a0000 0001 2248 6943Tohoku University School of Medicine, Sendai, Japan
| | - Taku Obara
- grid.69566.3a0000 0001 2248 6943Tohoku University Graduate School of Medicine, Sendai, Japan ,grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-Machi, Aoba-Ku, Sendai, 980-8573 Japan ,grid.412757.20000 0004 0641 778XDepartment of Pharmaceutical Sciences, Tohoku University Hospital, Sendai, Japan
| | - Mami Ishikuro
- grid.69566.3a0000 0001 2248 6943Tohoku University Graduate School of Medicine, Sendai, Japan ,grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-Machi, Aoba-Ku, Sendai, 980-8573 Japan
| | - Fumihiko Ueno
- grid.69566.3a0000 0001 2248 6943Tohoku University Graduate School of Medicine, Sendai, Japan ,grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-Machi, Aoba-Ku, Sendai, 980-8573 Japan
| | - Aoi Noda
- grid.69566.3a0000 0001 2248 6943Tohoku University Graduate School of Medicine, Sendai, Japan ,grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-Machi, Aoba-Ku, Sendai, 980-8573 Japan ,grid.412757.20000 0004 0641 778XDepartment of Pharmaceutical Sciences, Tohoku University Hospital, Sendai, Japan
| | - Tomomi Onuma
- grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-Machi, Aoba-Ku, Sendai, 980-8573 Japan
| | - Fumiko Matsuzaki
- grid.69566.3a0000 0001 2248 6943Tohoku University Graduate School of Medicine, Sendai, Japan ,grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-Machi, Aoba-Ku, Sendai, 980-8573 Japan
| | - Natsuko Kobayashi
- grid.69566.3a0000 0001 2248 6943Tohoku University Graduate School of Medicine, Sendai, Japan ,grid.412757.20000 0004 0641 778XDepartment of Psychiatry, Tohoku University Hospital, Sendai, Japan
| | - Hirotaka Hamada
- grid.69566.3a0000 0001 2248 6943Tohoku University Graduate School of Medicine, Sendai, Japan ,grid.412757.20000 0004 0641 778XDepartment of Obstetrics and Gynecology, Tohoku University Hospital, Sendai, Japan
| | - Noriyuki Iwama
- grid.69566.3a0000 0001 2248 6943Tohoku University Graduate School of Medicine, Sendai, Japan ,grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-Machi, Aoba-Ku, Sendai, 980-8573 Japan ,grid.412757.20000 0004 0641 778XDepartment of Obstetrics and Gynecology, Tohoku University Hospital, Sendai, Japan
| | - Masatoshi Saito
- grid.69566.3a0000 0001 2248 6943Tohoku University Graduate School of Medicine, Sendai, Japan ,grid.412757.20000 0004 0641 778XDepartment of Obstetrics and Gynecology, Tohoku University Hospital, Sendai, Japan
| | - Junichi Sugawara
- grid.69566.3a0000 0001 2248 6943Tohoku University Graduate School of Medicine, Sendai, Japan ,grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-Machi, Aoba-Ku, Sendai, 980-8573 Japan ,grid.412757.20000 0004 0641 778XDepartment of Obstetrics and Gynecology, Tohoku University Hospital, Sendai, Japan
| | - Hiroaki Tomita
- grid.69566.3a0000 0001 2248 6943Tohoku University Graduate School of Medicine, Sendai, Japan ,grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-Machi, Aoba-Ku, Sendai, 980-8573 Japan ,grid.412757.20000 0004 0641 778XDepartment of Psychiatry, Tohoku University Hospital, Sendai, Japan ,grid.69566.3a0000 0001 2248 6943International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
| | - Nobuo Yaegashi
- grid.69566.3a0000 0001 2248 6943Tohoku University Graduate School of Medicine, Sendai, Japan ,grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-Machi, Aoba-Ku, Sendai, 980-8573 Japan ,grid.412757.20000 0004 0641 778XDepartment of Obstetrics and Gynecology, Tohoku University Hospital, Sendai, Japan
| | - Shigeo Kure
- grid.69566.3a0000 0001 2248 6943Tohoku University Graduate School of Medicine, Sendai, Japan ,grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-Machi, Aoba-Ku, Sendai, 980-8573 Japan
| | - Shinichi Kuriyama
- grid.69566.3a0000 0001 2248 6943Tohoku University Graduate School of Medicine, Sendai, Japan ,grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-Machi, Aoba-Ku, Sendai, 980-8573 Japan ,grid.69566.3a0000 0001 2248 6943International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
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9
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Iwama N, Obara T, Ishikuro M, Murakami K, Ueno F, Noda A, Onuma T, Matsuzaki F, Hoshiai T, Saito M, Metoki H, Sugawara J, Yaegashi N, Kuriyama S. Risk scores for predicting small for gestational age infants in Japan: The TMM birthree cohort study. Sci Rep 2022; 12:8921. [PMID: 35618764 PMCID: PMC9135745 DOI: 10.1038/s41598-022-12892-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2021] [Accepted: 05/16/2022] [Indexed: 11/30/2022] Open
Abstract
This study aimed to construct a prediction model for small-for-gestational-age (SGA) infants in Japan by creating a risk score during pregnancy. A total of 17,073 subjects were included in the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study, a prospective cohort study. A multiple logistic regression model was used to construct risk scores during early and mid-gestational periods (11–17 and 18–21 weeks of gestation, respectively). The risk score during early gestation comprised the maternal age, height, body mass index (BMI) during early gestation, parity, assisted reproductive technology (ART) with frozen-thawed embryo transfer (FET), smoking status, blood pressure (BP) during early gestation, and maternal birth weight. The risk score during mid-gestation also consisted of the maternal age, height, BMI during mid-gestation, weight gain, parity, ART with FET, smoking status, BP level during mid-gestation, maternal birth weight, and estimated fetal weight during mid-gestation. The C-statistics of the risk scores during early- and mid-gestation were 0.658 (95% confidence interval [CI]: 0.642–0.675) and 0.725 (95% CI: 0.710–0.740), respectively. In conclusion, the predictive ability of the risk scores during mid-gestation for SGA infants was acceptable and better than that of the risk score during early gestation.
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Affiliation(s)
- Noriyuki Iwama
- Department of Obstetrics and Gynecology, Tohoku University Hospital, 1-1, Seiryomachi, Sendai, Miyagi, 980-8574, Japan. .,Division of Molecular Epidemiology, Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
| | - Taku Obara
- Division of Molecular Epidemiology, Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.,Division of Molecular Epidemiology, Graduate School of Medicine, Tohoku University, Sendai, Japan.,Department of Pharmaceutical Sciences, Tohoku University Hospital, Sendai, Miyagi, Japan
| | - Mami Ishikuro
- Division of Molecular Epidemiology, Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.,Division of Molecular Epidemiology, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Keiko Murakami
- Division of Molecular Epidemiology, Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.,Division of Molecular Epidemiology, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Fumihiko Ueno
- Division of Molecular Epidemiology, Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.,Division of Molecular Epidemiology, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Aoi Noda
- Division of Molecular Epidemiology, Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.,Division of Molecular Epidemiology, Graduate School of Medicine, Tohoku University, Sendai, Japan.,Department of Pharmaceutical Sciences, Tohoku University Hospital, Sendai, Miyagi, Japan
| | - Tomomi Onuma
- Division of Molecular Epidemiology, Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.,Division of Molecular Epidemiology, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Fumiko Matsuzaki
- Division of Molecular Epidemiology, Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Tetsuro Hoshiai
- Department of Obstetrics and Gynecology, Tohoku University Hospital, 1-1, Seiryomachi, Sendai, Miyagi, 980-8574, Japan
| | - Masatoshi Saito
- Department of Obstetrics and Gynecology, Tohoku University Hospital, 1-1, Seiryomachi, Sendai, Miyagi, 980-8574, Japan.,Department of Maternal and Fetal Therapeutics, Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan
| | - Hirohito Metoki
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan.,Division of Public Health, Hygiene and Epidemiology, Tohoku Medical Pharmaceutical University, Sendai, Miyagi, Japan
| | - Junichi Sugawara
- Department of Obstetrics and Gynecology, Tohoku University Hospital, 1-1, Seiryomachi, Sendai, Miyagi, 980-8574, Japan.,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan.,Environment and Genome Research Center, Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan
| | - Nobuo Yaegashi
- Department of Obstetrics and Gynecology, Tohoku University Hospital, 1-1, Seiryomachi, Sendai, Miyagi, 980-8574, Japan.,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan.,Environment and Genome Research Center, Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan.,Department of Obstetrics and Gynecology, Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan
| | - Shinichi Kuriyama
- Division of Molecular Epidemiology, Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.,Division of Molecular Epidemiology, Graduate School of Medicine, Tohoku University, Sendai, Japan.,International Research Institute of Disaster Science, Tohoku University, Sendai, Miyagi, Japan
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10
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Murakami K, Ishikuro M, Obara T, Ueno F, Noda A, Onuma T, Matsuzaki F, Kikuchi S, Kobayashi N, Hamada H, Iwama N, Metoki H, Saito M, Sugawara J, Tomita H, Yaegashi N, Kuriyama S. Maternal personality and postpartum mental disorders in Japan: the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study. Sci Rep 2022; 12:6400. [PMID: 35430603 PMCID: PMC9013371 DOI: 10.1038/s41598-022-09944-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 03/21/2022] [Indexed: 11/09/2022] Open
Abstract
AbstractPersonality has been shown to predict postpartum depressive symptoms (PDS) assessed by the Edinburgh Postnatal Depression Scale (EPDS). However, existing studies have not considered the underlying symptom dimensions in the EPDS. We analyzed data from 15,012 women who participated in the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study. Personality was assessed in middle pregnancy using the short-form Eysenck Personality Questionnaire-Revised. PDS were defined as EPDS score ≥ 9 at 1 month after delivery. The EPDS items were further divided into three dimensions: depressed mood, anxiety, and anhedonia. Multiple analyses were conducted to examine the associations of each personality scale with PDS and three dimensions in the EPDS, adjusting for age, parity, mode of delivery, education, income, and social isolation. The prevalence of PDS assessed by the EPDS at 1 month after delivery was 13.1%. Higher neuroticism scores were associated with PDS (odds ratio [OR], 2.63; 95% confidence interval [CI], 2.48 to 2.79) and all three dimensions (all p < 0.001). Lower extraversion scores were associated with PDS (OR, 0.74; 95% CI, 0.70 to 0.78) and all three dimensions (all p < 0.001). Lower psychoticism scores were associated with PDS (OR, 0.89; 95% CI, 0.85 to 0.94) and anxiety (p < 0.001), but not with depressed mood (p = 0.20) or anhedonia (p = 0.92). In conclusion, higher neuroticism and lower extraversion were associated with PDS and the three underlying dimensions in the EPDS, while lower psychoticism was associated with anxiety, but not with depressed mood or anhedonia.
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11
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Kikuchi S, Murakami K, Obara T, Ishikuro M, Ueno F, Noda A, Onuma T, Kobayashi N, Sugawara J, Yamamoto M, Yaegashi N, Kuriyama S, Tomita H. One-year trajectories of postpartum depressive symptoms and associated psychosocial factors: findings from the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study. J Affect Disord 2021; 295:632-638. [PMID: 34509778 DOI: 10.1016/j.jad.2021.08.118] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 08/05/2021] [Accepted: 08/28/2021] [Indexed: 02/06/2023]
Abstract
BACKGROUND Trajectories of postpartum depressive symptoms up to 1 year after childbirth and the related risk factors remain unclear. Accordingly, this study aimed to examine the 1-year trajectories of postpartum depressive symptoms and their associated risk factors. METHODS A total of 22,493 pregnant women were recruited between July 2013 and September 2016 in the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study in Japan. Among them, 11,668 women with no missing data were included in the analyses. Depressive symptoms were assessed at 1 month and 1 year postpartum using the Edinburgh Postnatal Depression Scale. Multinominal logistic regression analysis was conducted after adjusting for covariates. RESULTS The prevalence of depression was 13.9% at 1 month and 12.9% at 1 year postpartum. We identified four depression trajectories, i.e., "persistent (depressed throughout the 1 year postpartum)" (6.0%), "recovered (depressed at 1 month postpartum and recovered within a year)" (7.9%), "late-onset (became depressed after 1 month postpartum)" (6.8%), and "resilient (not depressed throughout 1 year postpartum)" (79.2%). Psychological distress during pregnancy was significantly associated with all trajectories (persistent: odds ratio [OR]=10.24, 95% confidence interval (CI)=8.40-12.48; recovered: OR=3.78, 95%CI=3.28-4.36; and late-onset: OR=3.96, 95%CI=3.40-4.62). LIMITATIONS Postpartum depression was evaluated only by a self-administered questionnaire and the dropout rate was not neglectable. CONCLUSIONS This study highlighted the high prevalence of depressive symptoms at 1 year postpartum and found that half of the depressive symptoms at 1 year were late-onset. The findings suggest the necessity of long-term follow-up (up to 1 year) for perinatal mental health.
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Affiliation(s)
- Saya Kikuchi
- Department of Psychiatry, Tohoku University Hospital; Department of Psychiatry, Graduate School of Medicine, Tohoku University.
| | - Keiko Murakami
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University; Department of Molecular Epidemiology, Graduate School of Medicine, Tohoku University
| | - Taku Obara
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University; Department of Molecular Epidemiology, Graduate School of Medicine, Tohoku University; Department of Pharmaceutical Sciences, Tohoku University Hospital
| | - Mami Ishikuro
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University; Department of Molecular Epidemiology, Graduate School of Medicine, Tohoku University
| | - Fumihiko Ueno
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University; Department of Molecular Epidemiology, Graduate School of Medicine, Tohoku University
| | - Aoi Noda
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University; Department of Molecular Epidemiology, Graduate School of Medicine, Tohoku University; Department of Pharmaceutical Sciences, Tohoku University Hospital
| | - Tomomi Onuma
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University
| | - Natsuko Kobayashi
- Department of Psychiatry, Tohoku University Hospital; Department of Psychiatry, Graduate School of Medicine, Tohoku University
| | - Junichi Sugawara
- Department of Community Medical Supports, Tohoku Medical Megabank Organization, Tohoku University; Environment and Genome Research Center, Graduate School of Medicine, Tohoku University; Department of Obstetrics and Gynecology, Graduate School of Medicine, Tohoku University
| | - Masayuki Yamamoto
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University
| | - Nobuo Yaegashi
- Department of Community Medical Supports, Tohoku Medical Megabank Organization, Tohoku University; Department of Obstetrics and Gynecology, Graduate School of Medicine, Tohoku University
| | - Shinichi Kuriyama
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University; Department of Molecular Epidemiology, Graduate School of Medicine, Tohoku University; Department of Disaster-related Public Health, International Research Institute of Disaster Science, Tohoku University
| | - Hiroaki Tomita
- Department of Psychiatry, Tohoku University Hospital; Department of Psychiatry, Graduate School of Medicine, Tohoku University; Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University; Department of Disaster Psychiatry, International Research Institute of Disaster Science, Tohoku University
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12
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Yamauchi T, Ochi D, Matsukawa N, Saigusa D, Ishikuro M, Obara T, Tsunemoto Y, Kumatani S, Yamashita R, Tanabe O, Minegishi N, Koshiba S, Metoki H, Kuriyama S, Yaegashi N, Yamamoto M, Nagasaki M, Hiyama S, Sugawara J. Machine learning approaches to predict gestational age in normal and complicated pregnancies via urinary metabolomics analysis. Sci Rep 2021; 11:17777. [PMID: 34493809 PMCID: PMC8423760 DOI: 10.1038/s41598-021-97342-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 08/25/2021] [Indexed: 02/07/2023] Open
Abstract
The elucidation of dynamic metabolomic changes during gestation is particularly important for the development of methods to evaluate pregnancy status or achieve earlier detection of pregnancy-related complications. Some studies have constructed models to evaluate pregnancy status and predict gestational age using omics data from blood biospecimens; however, less invasive methods are desired. Here we propose a model to predict gestational age, using urinary metabolite information. In our prospective cohort study, we collected 2741 urine samples from 187 healthy pregnant women, 23 patients with hypertensive disorders of pregnancy, and 14 patients with spontaneous preterm birth. Using gas chromatography-tandem mass spectrometry, we identified 184 urinary metabolites that showed dynamic systematic changes in healthy pregnant women according to gestational age. A model to predict gestational age during normal pregnancy progression was constructed; the correlation coefficient between actual and predicted weeks of gestation was 0.86. The predicted gestational ages of cases with hypertensive disorders of pregnancy exhibited significant progression, compared with actual gestational ages. This is the first study to predict gestational age in normal and complicated pregnancies by using urinary metabolite information. Minimally invasive urinary metabolomics might facilitate changes in the prediction of gestational age in various clinical settings.
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Affiliation(s)
- Takafumi Yamauchi
- grid.419819.c0000 0001 2184 8682X-Tech Development Department, NTT DOCOMO, INC, 3-6 Hikarino-oka, Yokosuka, Kanagawa 239-8536 Japan
| | - Daisuke Ochi
- grid.419819.c0000 0001 2184 8682X-Tech Development Department, NTT DOCOMO, INC, 3-6 Hikarino-oka, Yokosuka, Kanagawa 239-8536 Japan
| | - Naomi Matsukawa
- grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573 Japan
| | - Daisuke Saigusa
- grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573 Japan
| | - Mami Ishikuro
- grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573 Japan ,grid.69566.3a0000 0001 2248 6943Tohoku University Graduate School of Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575 Japan
| | - Taku Obara
- grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573 Japan ,grid.69566.3a0000 0001 2248 6943Tohoku University Graduate School of Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575 Japan
| | - Yoshiki Tsunemoto
- grid.419819.c0000 0001 2184 8682X-Tech Development Department, NTT DOCOMO, INC, 3-6 Hikarino-oka, Yokosuka, Kanagawa 239-8536 Japan
| | - Satsuki Kumatani
- grid.419819.c0000 0001 2184 8682X-Tech Development Department, NTT DOCOMO, INC, 3-6 Hikarino-oka, Yokosuka, Kanagawa 239-8536 Japan
| | - Riu Yamashita
- grid.272242.30000 0001 2168 5385Exploratory Oncology Research and Clinical Trial Center, National Cancer Center, 6-5-1 Kashiwanoha, Kashiwa, Chiba 277-8577 Japan
| | - Osamu Tanabe
- grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573 Japan ,grid.418889.40000 0001 2198 115XRadiation Effects Research Foundation, 5-2 Hijiyama Park, Minami-ku, Hiroshima, 732-0815 Japan
| | - Naoko Minegishi
- grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573 Japan
| | - Seizo Koshiba
- grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573 Japan ,grid.69566.3a0000 0001 2248 6943Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573 Japan
| | - Hirohito Metoki
- grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573 Japan ,grid.412755.00000 0001 2166 7427Faculty of Medicine, Tohoku Medical Pharmaceutical University, 4-4-1 Komatsushima, Aoba-ku, Sendai, 981-0905 Japan
| | - Shinichi Kuriyama
- grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573 Japan ,grid.69566.3a0000 0001 2248 6943Tohoku University Graduate School of Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575 Japan ,grid.69566.3a0000 0001 2248 6943International Research Institute of Disaster Science, Tohoku University, Aramaki Aza-Aoba 468-1, Aoba-ku, Sendai, 980-8572 Japan
| | - Nobuo Yaegashi
- grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573 Japan ,grid.69566.3a0000 0001 2248 6943Tohoku University Graduate School of Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575 Japan ,grid.69566.3a0000 0001 2248 6943Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573 Japan
| | - Masayuki Yamamoto
- grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573 Japan ,grid.69566.3a0000 0001 2248 6943Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573 Japan
| | - Masao Nagasaki
- grid.258799.80000 0004 0372 2033Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, 53 Shogoinkawahara-cho, Sakyo-ku, Kyoto City, Kyoto 606-8507 Japan ,grid.258799.80000 0004 0372 2033Center for the Promotion of Interdisciplinary Education and Research, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto, 606-8507 Japan
| | - Satoshi Hiyama
- grid.419819.c0000 0001 2184 8682X-Tech Development Department, NTT DOCOMO, INC, 3-6 Hikarino-oka, Yokosuka, Kanagawa 239-8536 Japan
| | - Junichi Sugawara
- grid.69566.3a0000 0001 2248 6943Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573 Japan ,grid.69566.3a0000 0001 2248 6943Tohoku University Graduate School of Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575 Japan
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13
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Yasuoka T, Iwama N, Ota K, Harada M, Hasegawa J, Yaegashi N, Sugiyama T, Suzuki N, Osuga Y. Pregnancy outcomes in children, adolescents, and young adults that survived cancer: A nationwide survey in Japan. J Obstet Gynaecol Res 2021; 47:3352-3361. [PMID: 34155729 DOI: 10.1111/jog.14909] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 04/25/2021] [Accepted: 06/10/2021] [Indexed: 11/27/2022]
Abstract
AIM Recent advances in cancer treatment have improved the prognosis of child, adolescent, and young adult (CAYA) cancer survivors. This study aimed to examine the current status of pregnancy outcomes among female cancer survivors in Japan. METHODS The first questionnaire was sent to 633 major tertiary institutions certified by the Japan Society of Obstetrics and Gynecology to identify institutions managing cases of pregnant cancer survivors between January 2011 and December 2015. The second questionnaire was sent only to institutions with pregnant cancer survivors during the study period. RESULTS We analyzed 2242 singleton deliveries of cancer survivors based on the responses received in the second questionnaire (199/255 responses; 78.0%). The three most frequent types of malignant tumors were uterine cervical (23.4%), breast (17.6%), and thyroid cancers (17.5%). Conception was aided by the use of assisted reproductive technology in 17.0% of the patients. The proportions of mothers aged 35-39.9 and ≥ 40 years were 36.5% and 11.8%, respectively. The prevalence of preterm birth (PTB) at <37, <34, and < 32 weeks' gestation were 16.7%, 6.8%, and 4.3%, respectively. The proportion of infants with low birth weight (LBW) was 18.9%. CONCLUSION The present study findings suggest that advanced maternal age was common among pregnant cancer survivors and these survivors often gave birth to PTB and LBW infants in Japan. The likelihood of adverse pregnancy outcomes should be considered by healthcare providers when planning counseling and perinatal care for cancer survivors.
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Affiliation(s)
- Toshiaki Yasuoka
- Department of Obstetrics and Gynecology, Ehime University Graduate School of Medicine, Toon, Japan
| | - Noriyuki Iwama
- Department of Obstetrics and Gynecology, Tohoku University Hospital, Sendai, Japan.,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Kuniaki Ota
- Fukushima Medical Center for Children and Women, Fukushima Medical University, Fukushima, Japan
| | - Miyuki Harada
- Department of Obstetrics and Gynecology, Faculty of Medicine, The University of Tokyo, Tokyo, Japan
| | - Junichi Hasegawa
- Department of Obstetrics and Gynecology, St. Marianna University School of Medicine, Kawasaki, Japan
| | - Nobuo Yaegashi
- Department of Obstetrics and Gynecology, Tohoku University Hospital, Sendai, Japan.,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.,Department of Obstetrics and Gynecology, Tohoku University Graduate School of Medicine, Sendai, Japan.,Environment and Genome Research Center, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Takashi Sugiyama
- Department of Obstetrics and Gynecology, Ehime University Graduate School of Medicine, Toon, Japan
| | - Nao Suzuki
- Department of Obstetrics and Gynecology, St. Marianna University School of Medicine, Kawasaki, Japan
| | - Yutaka Osuga
- Department of Obstetrics and Gynecology, Faculty of Medicine, The University of Tokyo, Tokyo, Japan
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