{"title":"Making sense of US maternal mortality data.","authors":"Elliott K Main","doi":"10.1111/ppe.13139","DOIUrl":"https://doi.org/10.1111/ppe.13139","url":null,"abstract":"","PeriodicalId":19698,"journal":{"name":"Paediatric and perinatal epidemiology","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142625337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Teresa Janevic, Eugene Declercq, Elizabeth A Howell
{"title":"Data have consequences-Centring equity in the maternal mortality surveillance debate.","authors":"Teresa Janevic, Eugene Declercq, Elizabeth A Howell","doi":"10.1111/ppe.13138","DOIUrl":"10.1111/ppe.13138","url":null,"abstract":"","PeriodicalId":19698,"journal":{"name":"Paediatric and perinatal epidemiology","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142625335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Substance Use and Cardiovascular Health in Pre-Conception Care: Surprising Findings!","authors":"Amy R Mahar, Jorge E Chavarro","doi":"10.1111/ppe.13145","DOIUrl":"https://doi.org/10.1111/ppe.13145","url":null,"abstract":"","PeriodicalId":19698,"journal":{"name":"Paediatric and perinatal epidemiology","volume":"38 8","pages":"677-678"},"PeriodicalIF":2.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142740202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The burden of paediatric adverse medical events.","authors":"Asma M Ahmed, Lindsay A Thompson","doi":"10.1111/ppe.13127","DOIUrl":"10.1111/ppe.13127","url":null,"abstract":"","PeriodicalId":19698,"journal":{"name":"Paediatric and perinatal epidemiology","volume":" ","pages":"700-702"},"PeriodicalIF":2.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142292857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Monitoring trends and inequities in neonatal mortality rates using national perinatal data collections.","authors":"Helen D Bailey, Carol Bower","doi":"10.1111/ppe.13135","DOIUrl":"10.1111/ppe.13135","url":null,"abstract":"","PeriodicalId":19698,"journal":{"name":"Paediatric and perinatal epidemiology","volume":" ","pages":"714-716"},"PeriodicalIF":2.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142505354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Emma Skovgaard Pedersen, Ellen M Mikkelsen, Henrik Toft Sørensen, Elizabeth E Hatch, Lauren A Wise, Kenneth J Rothman, Joseph B Stanford, Anne Sofie Dam Laursen
{"title":"The association between the use of fertility indicators and fecundability in a Danish preconception cohort.","authors":"Emma Skovgaard Pedersen, Ellen M Mikkelsen, Henrik Toft Sørensen, Elizabeth E Hatch, Lauren A Wise, Kenneth J Rothman, Joseph B Stanford, Anne Sofie Dam Laursen","doi":"10.1111/ppe.13108","DOIUrl":"10.1111/ppe.13108","url":null,"abstract":"<p><strong>Background: </strong>The use of fertility indicators to predict ovulation has largely been studied for contraceptive purposes, while less so as fertility-promoting tools.</p><p><strong>Objective: </strong>To investigate the association between fertility indicators and fecundability in Danish women trying to conceive.</p><p><strong>Methods: </strong>Web-based preconception cohort study. We analysed data from 11,328 females aged 18-49 years trying to conceive without fertility treatment for ≤6 menstrual cycles, from the Danish SnartGravid.dk and SnartForældre.dk cohorts (2007-2023). Participants reported the use of fertility indicators (counting days since the last menstrual period, cervical fluid monitoring, urinary ovulation testing, feeling ovulation, using a smartphone fertility app and measuring basal body temperature [BBT]). Time to pregnancy was measured in menstrual cycles ascertained by self-reported pregnancy status. We estimated fecundability ratios (FR) and 95% confidence intervals (CI) using proportional probabilities regression models adjusted for age, socio-economic position, health indicators, reproductive history and gynaecological factors.</p><p><strong>Results: </strong>Fertility indicators were used by 63.3% of participants at study entry. Counting days was the most common (46.9%), while measuring BBT was the least (3.0%). Other indicators ranged from 17.0% to 23.6%, with 69.7% using more than one indicator. Compared with non-use, use of any fertility indicator was associated with greater fecundability (adjusted FR 1.14, 95% CI 1.08, 1.19). Cervical fluid monitoring showed the strongest association (aFR 1.46, 95% CI 1.03, 2.07), followed by urinary ovulation testing (aFR 1.35, 95% CI 1.16, 1.58) and counting days (aFR 1.18, 95% CI 1.09, 1.29). Feeling ovulation and fertility apps were modestly associated with fecundability, while measuring BBT was not associated. Sensitivity analysis restricting to ≤2 cycles of attempt time and two cycles of follow-up showed an aFR for any indicator use of 1.21 (95% CI 1.13, 1.31).</p><p><strong>Conclusion: </strong>In this Danish preconception cohort, use of fertility indicators was associated with a higher fecundability, varying by type of indicator.</p>","PeriodicalId":19698,"journal":{"name":"Paediatric and perinatal epidemiology","volume":" ","pages":"641-650"},"PeriodicalIF":2.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11603762/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141897948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zifan Wang, Donna D Baird, Michelle A Williams, Anne Marie Z Jukic, Allen J Wilcox, Christine L Curry, Tyler Fischer-Colbrie, Jukka-Pekka Onnela, Russ Hauser, Brent A Coull, Shruthi Mahalingaiah
{"title":"Early-life menstrual characteristics and gestational diabetes in a large US cohort.","authors":"Zifan Wang, Donna D Baird, Michelle A Williams, Anne Marie Z Jukic, Allen J Wilcox, Christine L Curry, Tyler Fischer-Colbrie, Jukka-Pekka Onnela, Russ Hauser, Brent A Coull, Shruthi Mahalingaiah","doi":"10.1111/ppe.13129","DOIUrl":"10.1111/ppe.13129","url":null,"abstract":"<p><strong>Background: </strong>Associations between early-life menstrual cycle characteristics (MCC) and gestational diabetes (GDM) remain unclear.</p><p><strong>Objectives: </strong>To evaluate associations between early-life MCCs and GDM in first pregnancy, across pregnancies and its recurrence.</p><p><strong>Methods: </strong>This analysis included participants from a US-based digital cohort enrolled between 11/2019 and 9/2023 who provided consent, completed relevant surveys, were without diabetes and aged ≥18 at first pregnancy (n = 30,473). Age at menarche [<11 (early), 11-15 (referent), ≥16 (late) years] and time from menarche to cycle regularity [<1 (referent), 1-2, 3-4, ≥5 years, not yet regular, regular after hormones] were self-recalled at enrolment. Additionally, the last three categories were considered prolonged time-to-regularity (PTTR). GDM history was recalled at enrolment for each pregnancy. We restricted to pregnancies of ≥24 weeks with a live birth. We evaluated associations of early-life MCCs with GDM at first pregnancy using modified Poisson regression, across pregnancies using cluster-weighted Poisson generalised estimating equation and GDM recurrence using multinomial logistic regression, adjusted for sociodemographic, early-life factors and age at pregnancy. Missing variables were imputed with multiple imputation by chained equations.</p><p><strong>Results: </strong>Among 30,473 participants, 20,591 had eligible first pregnancies, of which 5.9% reported GDM. In 17,512 participants with ≥2 pregnancies, 8.3% had GDM once and 3.7% had recurrent GDM. Early menarche (<11 years, vs. 11-15 years) was associated with GDM in first pregnancy (RR 1.34, 95% CI 1.15, 1.57), across pregnancies (RR 1.24, 95% CI 1.10, 1.39) and recurrence (OR 1.51, 95% CI 1.21, 1.89). PTTR was associated with GDM in the first pregnancy (RR 1.22, 95% CI 1.08, 1.38), across pregnancies (RR 1.16, 95% CI 1.05, 1.27) and recurrence (OR 1.19, 95% CI 0.99, 1.43).</p><p><strong>Conclusions: </strong>Earlier menarche and prolonged time-to-regularity are associated with higher risk of GDM and recurrence, suggesting menstrual characteristics during childhood/adolescence as potential early-life markers for GDM.</p>","PeriodicalId":19698,"journal":{"name":"Paediatric and perinatal epidemiology","volume":"38 8","pages":"654-665"},"PeriodicalIF":2.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11603761/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142740200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The role of child BMI growth in neurodevelopment and school readiness-Current landscape and future directions.","authors":"Yi Ying Ong","doi":"10.1111/ppe.13132","DOIUrl":"10.1111/ppe.13132","url":null,"abstract":"","PeriodicalId":19698,"journal":{"name":"Paediatric and perinatal epidemiology","volume":" ","pages":"745-747"},"PeriodicalIF":2.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11603757/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142372490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Empowering fertility: Integrating indicators into personalised reproductive care.","authors":"Michaela S Olabisi, Sunni L Mumford","doi":"10.1111/ppe.13125","DOIUrl":"10.1111/ppe.13125","url":null,"abstract":"","PeriodicalId":19698,"journal":{"name":"Paediatric and perinatal epidemiology","volume":" ","pages":"651-653"},"PeriodicalIF":2.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11603747/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142292854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ye'elah E Berman, John P Newnham, Elizabeth A Nathan, Dorota A Doherty, Kiarna Brown, Sarah V Ward
{"title":"Perinatal mortality among term births: Informing decisions about singleton early term births in Western Australia.","authors":"Ye'elah E Berman, John P Newnham, Elizabeth A Nathan, Dorota A Doherty, Kiarna Brown, Sarah V Ward","doi":"10.1111/ppe.13124","DOIUrl":"10.1111/ppe.13124","url":null,"abstract":"<p><strong>Background: </strong>To minimise the risk of perinatal mortality, clinicians and expectant mothers must understand the risks and benefits associated with continuing the pregnancy.</p><p><strong>Objectives: </strong>Report the gestation-specific risk of perinatal mortality at term.</p><p><strong>Methods: </strong>Population-based cohort study using linked health data to identify all singleton births at gestations 37-41 weeks, in Western Australia (WA) from 2009 to 2019. Lifetable analysis was used to combine the risk of each type of perinatal mortality and calculate the cumulative risk of perinatal mortality, termed the perinatal risk index (PRI). Rates of antepartum and intrapartum stillbirth and neonatal death, as well as the PRI, were examined for each gestational week at term by non-Aboriginal and Aboriginal ethnicity. For non-Aboriginal women, rates were also examined by time-period (pre- vs. post-WA Preterm Birth Prevention Initiative (the Initiative) rollout), primiparity, and obstetric risk.</p><p><strong>Results: </strong>There were 332,084 singleton term births, including 60 perinatal deaths to Aboriginal mothers (3.2 deaths per 1000 births to Aboriginal mothers) and 399 perinatal deaths to non-Aboriginal mothers (1.3 deaths per 1000 births to non-Aboriginal mothers). For non-Aboriginal women, the PRI was at its lowest (PRI 0.80, 95% CI 0.61, 1.00) at 39 weeks gestation. For Aboriginal women, it was at its lowest at 38 weeks (PRI 2.43, 95% CI 0.48, 4.39) with similar risk at 39 weeks (PRI 2.68, 95% CI 1.22, 4.14). The PRI increased steadily after 39 weeks gestation. The risk of perinatal mortality was higher among Aboriginal women. The gestation-specific perinatal mortality rates were similar by the time-period, primiparity and obstetric risk.</p><p><strong>Conclusions: </strong>The gestational ages at term associated with the lowest risk of perinatal mortality reinforce that the recommendation not to deliver before 39 weeks without medical indication is applicable to both Aboriginal and non-Aboriginal women giving birth in WA. There was no increase in the perinatal mortality rate associated with the introduction of the Initiative.</p>","PeriodicalId":19698,"journal":{"name":"Paediatric and perinatal epidemiology","volume":" ","pages":"717-729"},"PeriodicalIF":2.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11603756/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142351433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}