Dataset Information

Seasonality of birth and implications for temporal studies of preterm birth.

ABSTRACT: A strength of time-series analyses is the inherent control of individual-level risk factors that do not vary temporally. However, in studies of adverse pregnancy outcomes, risk factors considered time-invariant at the individual level may vary seasonally when aggregated into a pregnancy risk set. To illustrate, we describe the seasonal patterns of birth in Atlanta and demonstrate how these patterns could lead to confounding in time-series studies of seasonally-varying exposures and preterm birth.The study cohort included all births in 20-county metropolitan Atlanta delivered during the period 1994-2004 (n = 715,875). We assessed the seasonal patterns of estimated conception and birth for the full cohort and for subgroups stratified by sociodemographic factors. Based on the observed patterns, we quantified the degree of potential confounding created by (1) differences in the gestational age distribution in the risk set across calendar months and (2) differences in the sociodemographic composition of the risk set across calendar months.The overall seasonal pattern of birth was characterized by a peak in August-September and troughs in April-May and November-January. Seasonal patterns differed among racial and ethnic groups, maternal education levels, and marital status. As a consequence of these seasonal patterns, systematic seasonal differences in the gestational age distribution and the sociodemographic composition of the risk set led to differences in expected rates of preterm birth across calendar months.Time-series investigations of seasonally-varying exposures and adverse pregnancy outcomes should consider the potential for bias due to seasonal heterogeneity in the risk set.

SUBMITTER: Darrow LA

PROVIDER: S-EPMC3743217 | biostudies-literature | 2009 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Seasonality of birth and implications for temporal studies of preterm birth.

Darrow Lyndsey A LA Strickland Matthew J MJ Klein Mitchel M Waller Lance A LA Flanders W Dana WD Correa Adolfo A Marcus Michele M Tolbert Paige E PE

Epidemiology (Cambridge, Mass.) 20090901 5

<h4>Background</h4>A strength of time-series analyses is the inherent control of individual-level risk factors that do not vary temporally. However, in studies of adverse pregnancy outcomes, risk factors considered time-invariant at the individual level may vary seasonally when aggregated into a pregnancy risk set. To illustrate, we describe the seasonal patterns of birth in Atlanta and demonstrate how these patterns could lead to confounding in time-series studies of seasonally-varying exposure ...[more]

PMID: 19535987

Similar Datasets

Project description:ImportanceSurvival of infants born extremely preterm (EP) (<28 weeks' gestation) has increased since the early 1990s. It is necessary to know whether increased survival is accompanied by increased neurodevelopmental disability.ObjectiveTo examine changes in major (ie, moderate or severe) neurodevelopmental disability and survival free of major neurodevelopmental disability at 2 years in infants born EP.Design, setting, and participantsFour prospective longitudinal cohort studies comprising all EP live births at 22 to 27 weeks' gestation from April 1, 2016, to March 31, 2017, and earlier eras (1991-1992, 1997, and 2005), and contemporaneous term-born controls in the state of Victoria, Australia. Among 1208 live births during the periods studied, data were available for analysis of 2-year outcomes in 1152 children: 422 (1991-1992), 215 (1997), 263 (2005), and 252 (2016-2017). Data analysis was performed from September 17, 2020, to April 15, 2021.ExposuresExtreme preterm live birth.Main outcomes and measuresSurvival, blindness, deafness, cerebral palsy, developmental delay, and neurodevelopmental disability at 2 years' corrected age. Developmental delay comprised a developmental quotient less than -1 SD relative to the control group means on the Bayley Scales for each era. Major neurodevelopmental disability comprised blindness, deafness, moderate to severe cerebral palsy, or a developmental quotient less than -2 SDs. Individual neurodevelopmental outcomes in each era were contrasted relative to the 2016-2017 cohort using logistic regression adjusted for gestational age, sex, birth weight z score, and sociodemographic variables. Changes in survival free of major neurodevelopmental disability over time were also assessed using logistic regression.ResultsSurvival to 2 years was highest in 2016-2017 (73% [215 of 293]) compared with earlier eras (1991-1992: 53% [225 of 428]; 1997: 70% [151 of 217]; 2005: 63% [170 of 270]). Blindness and deafness were uncommon (<3%). Cerebral palsy was less common in 2016-2017 (6%) than in earlier eras (1991-1992: 11%; 1997: 12%; 2005: 10%). There were no obvious changes in the rates of developmental quotient less than -2 SDs across eras (1991-1992: 18%; 1997: 22%; 2005: 7%; 2016-2017: 15%) or in rates of major neurodevelopmental disability (1991-1992: 20%; 1997: 26%; 2005: 15%; 2016-2017: 15%). Rates of survival free of major neurodevelopmental disability increased steadily over time: 42% (1991-1992), 51% (1997), 53% (2005), and 62% (2016-2017) (odds ratio, 1.30; 95% CI, 1.15-1.48 per decade; P < .001).Conclusions and relevanceThese findings suggest that survival free of major disability at age 2 years in children born EP has increased by an absolute 20% since the early 1990s. Increased survival has not been associated with increased neurodevelopmental disability.

Project description:BackgroundThe small sample sizes available within many very preterm (VPT) longitudinal birth cohort studies mean that it is often necessary to combine and harmonise data from individual studies to increase statistical power, especially for studying rare outcomes. Curating and mapping data is a vital first step in the process of data harmonisation. To facilitate data mapping and harmonisation across VPT birth cohort studies, we developed a custom classification system as part of the Research on European Children and Adults born Preterm (RECAP Preterm) project in order to increase the scope and generalisability of research and the evaluation of outcomes across the lifespan for individuals born VPT.MethodsThe multidisciplinary consortium of expert clinicians and researchers who made up the RECAP Preterm project participated in a four-phase consultation process via email questionnaire to develop a topic-specific classification system. Descriptive analyses were calculated after each questionnaire round to provide pre- and post- ratings to assess levels of agreement with the classification system as it developed. Amendments and refinements were made to the classification system after each round.ResultsExpert input from 23 clinicians and researchers from the RECAP Preterm project aided development of the classification system's topic content, refining it from 10 modules, 48 themes and 197 domains to 14 modules, 93 themes and 345 domains. Supplementary classifications for target, source, mode and instrument were also developed to capture additional variable-level information. Over 22,000 individual data variables relating to VPT birth outcomes have been mapped to the classification system to date to facilitate data harmonisation. This will continue to increase as retrospective data items are mapped and harmonised variables are created.ConclusionsThis bespoke preterm birth classification system is a fundamental component of the RECAP Preterm project's web-based interactive platform. It is freely available for use worldwide by those interested in research into the long term impact of VPT birth. It can also be used to inform the development of future cohort studies.

Project description:Background: Preterm birth (PTB) represents the leading cause of neonatal death. Large-scale genetic studies are necessary to determine genetic influences on PTB risk, but prospective cohort studies are expensive and time-consuming. We investigated the feasibility of retrospective recruitment of post-partum women for efficient collection of genetic samples, with self-collected saliva for DNA extraction from themselves and their babies, alongside self-recollection of pregnancy and birth details to phenotype PTB. Methods: 708 women who had participated in the OPPTIMUM trial (a randomised trial of progesterone pessaries to prevent PTB [ISRCTN14568373]) and consented to further contact were invited to provide self-collected saliva from themselves and their babies. DNA was extracted from Oragene OG-500 (adults) and OG-575 (babies) saliva kits and the yield measured by Qubit. Samples were analysed using a panel of Taqman single nucleotide polymorphism (SNP) assays. A questionnaire designed to meet the minimum data set required for phenotyping PTB was included. Questionnaire responses were transcribed and analysed for concordance with prospective trial data using Cohen's kappa ( k). Results: Recruitment rate was 162/708 (23%) for self-collected saliva samples and 157/708 (22%) for questionnaire responses. 161 samples from the mother provided DNA with median yield 59.0µg (0.4-148.9µg). 156 samples were successfully genotyped (96.9%). 136 baby samples had a median yield 11.5µg (0.1-102.7µg); two samples failed DNA extraction. 131 baby samples (96.3%) were successfully genotyped. Concordance between self-recalled birth details and prospective birth details was excellent ( k>0.75) in 4 out of 10 key fields for phenotyping PTB (mode of delivery, labour onset, ethnicity and maternal age at birth). Conclusion: This feasibility study demonstrates that self-collected DNA samples from mothers and babies were sufficient for genetic analysis but yields were variable. Self-recollection of pregnancy and birth details was inadequate for accurately phenotyping PTB, highlighting the need for alternative strategies for investigating genetic links with PTB.

Dataset Information

Seasonality of birth and implications for temporal studies of preterm birth.

Publications

Seasonality of birth and implications for temporal studies of preterm birth.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets