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Hassen TA, Chojenta C, Khan MN, Shifti DM, Harris ML. Short birth interval in the Asia-Pacific region: A systematic review and meta-analysis. J Glob Health 2024; 14:04072. [PMID: 38700432 PMCID: PMC11067827 DOI: 10.7189/jogh.14.04072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/05/2024] Open
Abstract
Background Short birth interval is associated with an increased risk of adverse health outcomes for mothers and children. Despite this, there is a lack of comprehensive evidence on short birth interval in the Asia-Pacific region. Thus, this study aimed to synthesise evidence related to the definition, classification, prevalence, and predictors of short birth interval in the Asia-Pacific region. Methods Five databases (MEDLINE, Scopus, Cumulative Index to Nursing and Allied Health Literature, Maternity and Infant Care, and Web of Science) were searched for studies published between September 2000 and May 2023 (the last search was conducted for all databases in May 2023). We included original studies published in English that reported on short birth interval in the Asia-Pacific region. Studies that combined birth interval with birth order, used multi-country data and were published as conference abstracts and commentaries were excluded. Three independent reviewers screened the articles for relevancy, and two reviewers performed the data extraction and quality assessment. The risk of bias was assessed using the Joanna Briggs Institute critical appraisal tool. The findings were both qualitatively and quantitatively synthesised and presented. Results A total of 140 studies met the inclusion criteria for this review. About 58% (n = 82) of the studies defined short birth interval, while 42% (n = 58) did not. Out of 82 studies, nearly half (n = 39) measured a birth-to-birth interval, 37 studies measured a birth-to-pregnancy, four measured a pregnancy-to-pregnancy, and two studies measured a pregnancy loss-to-conception. Approximately 39% (n = 55) and 6% (n = 8) of studies classified short birth intervals as <24 months and <33 months, respectively. Most of the included studies were cross-sectional, and about two-thirds had either medium or high risk of bias. The pooled prevalence of short birth interval was 33.8% (95% confidence interval (CI) = 23.0-44.6, I2 = 99.9%, P < 0.01) among the studies that used the World Health Organization definition. Conclusions This review's findings highlighted significant variations in the definition, measurement, classification, and reported prevalence of short birth interval across the included studies. Future research is needed to harmonise the definition and classification of short birth interval to ensure consistency and comparability across studies and facilitate the development of targeted interventions and policies. Registration PROSPERO CRD42023426975.
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Affiliation(s)
- Tahir Ahmed Hassen
- Centre for Women's Health Research, School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Australia
| | - Catherine Chojenta
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Australia
| | - Md Nuruzzaman Khan
- Centre for Women's Health Research, School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Australia
- Department of Population Science, Jatiya Kabi Kazi Nazrul Islam University, Mymensingh, Bangladesh
| | - Desalegn Markos Shifti
- Centre for Women's Health Research, School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Australia
- Child Health Research Centre, The University of Queensland, Brisbane, Australia
| | - Melissa Leigh Harris
- Centre for Women's Health Research, School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Australia
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Zhang X, Zhao G, Ma J, Tao F, Pan CW, Zhang F, Wang Y, Yang W, Xiang Y, Wang X, Tian Y, Yang J, Du W, Zhou Y. Design, methodology, and baseline of eastern China student health and wellbeing cohort study. Front Public Health 2023; 11:1100227. [PMID: 37181702 PMCID: PMC10173362 DOI: 10.3389/fpubh.2023.1100227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 02/28/2023] [Indexed: 05/16/2023] Open
Abstract
Purpose To describe the study design, methodology, and cohort profile of the Eastern China Student Health and Wellbeing Cohort Study. The cohort baseline includes (1) targeted disease (myopia, obesity, elevated blood pressure, and mental health) and (2) exposures (individual behaviors, environment, metabolomics, and gene and epigenetics). Participants Annual physical examination, questionnaire-based survey, and bio-sampling have been carried out in the study population. In the first stage (2019-2021), a total of 6,506 students in primary schools are enrolled in the cohort study. Findings to date Of all the cohort participants, the ratio of male to female is 1.16 among a total of 6,506 student participants, of which 2,728 (41.9%) students are from developed regions and 3,778 (58.1%) students are from developing regions. The initial age of observation is 6-10 years, and they will be observed until they graduate from high school (>18 years of age). (1) Targeted diseases: The growth rates of myopia, obesity, and high blood pressure vary by regions, and for developed regions, the prevalence of myopia, obesity, and elevated blood pressure is 29.2%, 17.4%, and 12.6% in the first year, respectively. For developing regions, the prevalence of myopia, obesity, and elevated blood pressure is 22.3%, 20.7%, and 17.1% in the first year, respectively. The average score of CES-D is 12.9 ± 9.8 in developing regions/11.6 ± 9.0 in developed regions. (2) Exposures: ① The first aspect of individual behaviors: the questionnaire topics include diet, physical exercise, bullying, and family. ② The second aspect of environment and metabolomics: the average desk illumination is 430.78 (355.84-611.56) LX, and the average blackboard illumination is 365.33 (286.83-516.84) LX. Metabolomics like bisphenol A in the urine is 0.734 ng/ml. ③ The third aspect of gene and epigenetics: SNPs (rs524952, rs524952, rs2969180, rs2908972, rs10880855, rs1939008, rs9928731, rs72621438, rs9939609, rs8050136 and so on) are detected. Future plans Eastern China Student Health and Wellbeing Cohort Study is aiming to focus on the development of student-targeted diseases. For children with student common diseases, this study will focus on targeted disease-related indicators. For children without targeted disease, this study aims to explore the longitudinal relationship between exposure factors and outcomes, excluding baseline confounding factors. Exposure factors include three aspects: (1) individual behaviors, (2) environment and metabolomics, and (3) gene and epigenetics. The cohort study will continue until 2035.
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Affiliation(s)
- Xiyan Zhang
- Department of Child and Adolescent Health Promotion, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
- School of Public Health, Nanjing Medical University, Nanjing, China
| | - Genming Zhao
- Department of Epidemiology, School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Jun Ma
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, China
| | - Fangbiao Tao
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China
| | - Chen-Wei Pan
- School of Public Health, Medical College of Soochow University, Suzhou, China
| | - Fengyun Zhang
- Department of Child and Adolescent Health Promotion, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Yan Wang
- Department of Child and Adolescent Health Promotion, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Wenyi Yang
- Department of Child and Adolescent Health Promotion, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Yao Xiang
- Department of Child and Adolescent Health Promotion, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Xin Wang
- Department of Child and Adolescent Health Promotion, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Yunfan Tian
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jie Yang
- Department of Child and Adolescent Health Promotion, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
- School of Public Health, Nanjing Medical University, Nanjing, China
| | - Wei Du
- School of Public Health, Southeast University, Nanjing, China
| | - Yonglin Zhou
- Department of Child and Adolescent Health Promotion, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
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