Intervals and Outcomes of First and Second Pregnancies in Low-Income Women: A Record-Linkage Longitudinal Prospective Cohort Study.
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ABSTRACT:
SUBMITTER: Reardon DC
PROVIDER: S-EPMC8240602 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundNearly half of all pregnancies in the United States are reported as unintended and rates are highest among women of low socioeconomic status. The purpose of this study was to examine the associations between unintended pregnancies and maternal mental health and timing of prenatal care among low-income women.MethodsIn this cross-sectional study, 870 women, whom were participating in the First 1000 Days program in three community health centers in the Boston area, were enrolled at their first prenatal visit from August 2016 - September 2017. We assessed pregnancy intention by self-report using the Pregnancy Risk Assessment Monitoring System. We used self-reported survey information and electronic health record data to assess the following outcomes: current stress, current depression, and timing of initial prenatal visit. We used multivariable logistic regression models to examine associations and adjusted for sociodemographic factors.ResultsWomen were a mean (SD) age of 29.3 (6.1), and 39.2% reported that their pregnancy was unintended. 50.6% of women were Hispanic, 28.4% were White, 10.1% were Black, and 10.9% were other races. 78.9% of women reported an annual household income <$50,000. Overall, 26.7% of women reported current stress, 8.2% reported current depression, and 18.3% of women initiated prenatal care after their first trimester. In multivariable analyses, women with unintended pregnancies had higher odds of experiencing current stress (OR: 1.72; 95% CI: 1.22, 2.41), current depression (OR: 1.83; 95% CI: 1.04, 3.20), and initiation of prenatal care post-first trimester (OR: 1.84; 95% CI: 1.23, 2.74).ConclusionsUnintended pregnancies were associated with current stress and depression, and delayed prenatal care in this sample of low-income women suggesting the importance of identifying high-risk women and tailoring interventions to support women's needs.Trial registrationClinicalTrials.gov (NCT03191591; Retrospectively registered on June 19, 2017).
| S-EPMC7552564 | biostudies-literature
Project description:Intermediate fine mapping has received considerable attention recently, with the goal of providing statistically precise and valid chromosomal regions for fine mapping following initial identification of broad regions that are linked to a disease. The following classes of methods have been proposed and compared in the literature: (1) LOD-support intervals, (2) generalized estimating equations, (3) bootstrap, and (4) confidence set inference framework. These methods provide confidence intervals either with coverage levels deviating from the nominal confidence levels or that are not fully efficient. Here, we propose a novel Bayesian method for constructing such intervals using affected sibling pair data. The susceptibility gene location is treated as a parameter in this method, with a uniform prior. A Metropolis-Hastings algorithm is implemented to sample from the posterior distribution and highest posterior density intervals of the disease gene locations are constructed. Correct coverage levels are maintained by our method. Both simulation studies and an application to a rheumatoid arthritis dataset demonstrate the improved efficiency of the Bayesian intervals compared with existing methods.
| S-EPMC2766027 | biostudies-literature
Project description:ObjectiveTo determine the perinatal outcomes of fetuses diagnosed with a pathogenic copy number variant (CNV) or variant of uncertain significance (VUS); and to characterize these variants in terms of testing indication, genomic location, size, and inheritance.MethodsRetrospective study of singleton pregnancies with a pathogenic CNV or VUS from a single laboratory during 2012-2018. Probabilistic record linkage between the prenatal diagnosis dataset and perinatal outcome data for births from 20 weeks gestation was performed. If no birth record was found, this implied a pregnancy loss <20 weeks.ResultsWe included 6945 prenatal microarray results; a pathogenic CNV was detected in 230 (3.3%, 95% CI: 2.9%-3.8%) and a VUS in 483 (7.0%, 95% CI: 6.4%-7.6%). Of pregnancies with a pathogenic CNV, 20.0% (95% CI: 15.3%-25.6%) had a live birth, 3.0% (95% CI: 1.5%-6.2%) had a perinatal death (stillbirth or neonatal death), and 77% (95% CI: 71.1%-81.9%) had no birth record. Of those with a VUS, 64.4% (95% CI: 60.0%-68.5%) had a live birth, 1.8% (95% CI: 1.0%-3.5%) had a perinatal death, and no birth record was found for 33.7% (95% CI: 29.7%-38.1%). Most pathogenic CNVs (61.1%) were <7 Mb in size. The most common microdeletion syndromes were DiGeorge, Wolf-Hirschhorn, and Cri-du-chat syndromes.ConclusionThis study provides an overview of perinatal outcomes and frequency of recurrent CNVs observed in the prenatal microarray era.
| S-EPMC10947476 | biostudies-literature
Project description:Studies involving the use of probabilistic record linkage are becoming increasingly common. However, the methods underpinning probabilistic record linkage are not widely taught or understood, and therefore these studies can appear to be a 'black box' research tool. In this article, we aim to describe the process of probabilistic record linkage through a simple exemplar. We first introduce the concept of deterministic linkage and contrast this with probabilistic linkage. We illustrate each step of the process using a simple exemplar and describe the data structure required to perform a probabilistic linkage. We describe the process of calculating and interpreting matched weights and how to convert matched weights into posterior probabilities of a match using Bayes theorem. We conclude this article with a brief discussion of some of the computational demands of record linkage, how you might assess the quality of your linkage algorithm, and how epidemiologists can maximize the value of their record-linked research using robust record linkage methods.
| S-EPMC5005943 | biostudies-literature
Project description:BackgroundAll obese pregnant women are considered at equal high risk with respect to complications in pregnancy and birth, and are commonly managed through resource-intensive care pathways. However, the identification of maternal characteristics associated with normal pregnancy outcomes could assist in the management of these pregnancies. The present study aims to identify the factors associated with uncomplicated pregnancy and birth in obese women, and to assess their predictive performance.MethodsData form obese women (BMI ≥ 30 kg/m2) with singleton pregnancies included in the UPBEAT trial were used in this analysis. Multivariable logistic regression was used to identify sociodemographic, clinical and biochemical factors at 15+0 to 18+6 weeks' gestation associated with uncomplicated pregnancy and birth, defined as delivery of a term live-born infant without antenatal or labour complications. Predictive performance was assessed using area under the receiver operating characteristic curve (AUROC). Internal validation and calibration were also performed. Women were divided into fifths of risk and pregnancy outcomes were compared between groups. Sensitivity, specificity, and positive and negative predictive values were calculated using the upper fifth as the positive screening group.ResultsAmongst 1409 participants (BMI 36.4, SD 4.8 kg/m2), the prevalence of uncomplicated pregnancy and birth was 36% (505/1409). Multiparity and increased plasma adiponectin, maternal age, systolic blood pressure and HbA1c were independently associated with uncomplicated pregnancy and birth. These factors achieved an AUROC of 0.72 (0.68-0.76) and the model was well calibrated. Prevalence of gestational diabetes, preeclampsia and other hypertensive disorders, preterm birth, and postpartum haemorrhage decreased whereas spontaneous vaginal delivery increased across the fifths of increasing predicted risk of uncomplicated pregnancy and birth. Sensitivity, specificity, and positive and negative predictive values were 38%, 89%, 63% and 74%, respectively. A simpler model including clinical factors only (no biomarkers) achieved an AUROC of 0.68 (0.65-0.71), with sensitivity, specificity, and positive and negative predictive values of 31%, 86%, 56% and 69%, respectively.ConclusionClinical factors and biomarkers can be used to help stratify pregnancy and delivery risk amongst obese pregnant women. Further studies are needed to explore alternative pathways of care for obese women demonstrating different risk profiles for uncomplicated pregnancy and birth.
| S-EPMC5669007 | biostudies-literature
Project description:BackgroundMilitary service exposes personnel to unusual situations with unclear health-related implications, and to identify both immediate and delayed risks, part of health surveillance includes examination of mortality and cancer rates that extends beyond periods of military service. The main aim of the Canadian Forces Cancer and Mortality Study II (CFCAMS II) is to describe the mortality and cancer experience of Canadian Armed Forces personnel (serving and released; about 230 000 people), with the further aim of informing health promotion and prevention programs for serving personnel and services for veterans after they leave the military.MethodsThis protocol is for a retrospective cohort study of serving and released Canadian Armed Forces personnel who enrolled on or after Jan. 1, 1976 in the Regular Force or Class C of the Reserve Force. To create our cohort, we identified record-linkage methods as the most appropriate mechanism to study mortality and cancer in those with a history of Canadian military service. Statistics Canada will link the CFCAMS II cohort file to the Canadian Vital Statistics (Mortality) and Canadian Cancer Registry databases for outcomes up to Dec. 31, 2014. The linkage will be stored in their highly secure linkage environment. Statistical analyses will be broadly divided into mortality and cancer incidence.ResultsWe will quantify mortality and cancer morbidity incidence and survival using multiple established methods, as well as age-period-cohort regression models to describe the relation between military service and mortality and cancer outcomes.InterpretationThe findings will represent novel and sound evidence on the risks and protective factors of military life.
| S-EPMC6287975 | biostudies-literature
Project description:BackgroundFrance has a large population of second-generation immigrants (i.e., native-born children of immigrants) who are known to experience important socioeconomic disparities by country of origin. The extent to which they also experience disparities in mortality, however, has not been previously examined.MethodsWe used a nationally representative sample of individuals 18 to 64 years old in 1999 with mortality follow-up via linked death records until 2010. We compared mortality levels for second-generation immigrants with their first-generation counterparts and with the reference (neither first- nor second-generation) population using mortality hazard ratios as well as probabilities of dying between age 18 and 65. We also adjusted hazard ratios using educational attainment reported at baseline.ResultsWe found a large amount of excess mortality among second-generation males of North African origin compared to the reference population with no migrant background. This excess mortality was not present among second-generation males of southern European origin, for whom we instead found a mortality advantage, nor among North African-origin males of the first-generation. This excess mortality remained large and significant after adjusting for educational attainment.ContributionIn these first estimates of mortality among second-generation immigrants in France, males of North African origin stood out as a subgroup experiencing a large amount of excess mortality. This finding adds a public health dimension to the various disadvantages already documented for this subgroup. Overall, our results highlight the importance of second-generation status as a significant and previously unknown source of health disparity in France.
| S-EPMC8114944 | biostudies-literature
Project description:For the past 80 years, social scientists have been linking historical censuses across time to study economic and geographic mobility. In recent decades, the quantity of historical census record linkage has exploded, owing largely to the advent of new machine-readable data created by genealogical organizations. Investigators are examining economic and geographic mobility across multiple generations, but also engaging many new topics. Several analysts are exploring the effects of early-life socioeconomic conditions, environmental exposures, or natural disasters on family, health and economic outcomes in later life. Other studies exploit natural experiments to gauge the impact of policy interventions such as social welfare programs and educational reforms. The new data sources have led to a proliferation of record linkage methodology, and some widespread approaches inadvertently introduce errors that can lead to false inferences. A new generation of large-scale shared data infrastructure now in preparation will ameliorate weaknesses of current linkage methods.
| S-EPMC6200350 | biostudies-literature
Project description:PurposeThere is a recent and growing migrant population in Northern Ireland. However, rigorous research is absent regarding access to mental health care by different migrant groups. In order to address this knowledge gap, this study aimed to identify the relative use of psychotropic medication between the largest first generation migrant groups in Northern Ireland and the majority population.MethodsCensus (2011) data was linked to psychotropic prescriptions for the entire enumerated population of Northern Ireland using data linkage methodology through the Administrative Data Research Centre Northern Ireland (ADRC-NI).ResultsLower prescription dispensation for all psychotropic medication types, particularly antidepressants (OR = 0.35, CI 95% 0.33-0.36) and anxiolytics (OR = 0.42, CI 95% 0.40-0.44), was observed for all migrant groups with the exception of migrants from Germany.ConclusionsIt is likely that the results reflect poorer access to services and indicate a need to improve access and the match between resources, services and the health and social care needs of migrants. Further research is required to identify barriers to accessing primary care and mental health services.
| S-EPMC6935113 | biostudies-literature
Project description:BACKGROUND: Linkage studies often yield intervals containing several hundred positional candidate genes. Different manual or automatic approaches exist for the determination of the gene most likely to cause the disease. While the manual search is very flexible and takes advantage of the researchers' background knowledge and intuition, it may be very cumbersome to collect and study the relevant data. Automatic solutions on the other hand usually focus on certain models, remain "black boxes" and do not offer the same degree of flexibility. METHODOLOGY: We have developed a web-based application that combines the advantages of both approaches. Information from various data sources such as gene-phenotype associations, gene expression patterns and protein-protein interactions was integrated into a central database. Researchers can select which information for the genes within a candidate interval or for single genes shall be displayed. Genes can also interactively be filtered, sorted and prioritised according to criteria derived from the background knowledge and preconception of the disease under scrutiny. CONCLUSIONS: GeneDistiller provides knowledge-driven, fully interactive and intuitive access to multiple data sources. It displays maximum relevant information, while saving the user from drowning in the flood of data. A typical query takes less than two seconds, thus allowing an interactive and explorative approach to the hunt for the candidate gene. ACCESS: GeneDistiller can be freely accessed at http://www.genedistiller.org.
| S-EPMC2587712 | biostudies-literature