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Associations between biological and sociodemographic risks for developmental vulnerability in twins at age 5: a population data linkage study in Western Australia.

ABSTRACT: OBJECTIVE:To investigate the prevalence of, and associations between, prenatal and perinatal risk factors and developmental vulnerability in twins at age 5. DESIGN:Retrospective cohort study using bivariate and multivariable logistic regression. SETTING:Western Australia (WA), 2002-2015. PARTICIPANTS:828 twin pairs born in WA with an Australian Early Development Census (AEDC) record from 2009, 2012 or 2015. MAIN OUTCOME MEASURES:The AEDC is a national measure of child development across five domains. Children with scores <10th percentile were classified as developmentally vulnerable on, one or more domains (DV1), or two or more domains (DV2). RESULTS:In this population, 26.0% twins were classified as DV1 and 13.5% as DV2. In the multivariable model, risk factors for DV1 were maternal age <25 years (adjusted OR (aOR): 7.06, 95%?CI: 2.29 to 21.76), child speaking a language other than English at home (aOR: 6.45, 95%?CI: 2.17 to 19.17), male child (aOR: 5.08, 95%?CI: 2.89 to 8.92), age younger than the reference category for the study sample (?5 years 1?month to <5 years 10 months) at time of AEDC completion (aOR: 3.34, 95%?CI: 1.55 to 7.22) and having a proportion of optimal birth weight (POBW) <15th percentile of the study sample (aOR: 2.06, 95%?CI 1.07 to 3.98). Risk factors for DV2 were male child (aOR: 7.87, 95%?CI: 3.45 to 17.97), maternal age <25 (aOR: 5.60, 95%?CI: 1.30 to 24.10), age younger than the reference category (aOR: 5.36, 95%?CI: 1.94 to 14.82), child speaking a language other than English at home (aOR: 4.65, 95%?CI: 1.14 to 19.03), mother's marital status as not married at the time of twins' birth (aOR: 4.59, 95%?CI: 1.13 to 18.55), maternal occupation status in the lowest quintile (aOR: 3.30, 95%?CI: 1.11 to 9.81) and a POBW <15th percentile (aOR: 3.11, 95%?CI: 1.26 to 7.64). CONCLUSION:Both biological and sociodemographic risk factors are associated with developmental vulnerability in twins at 5 years of age.

SUBMITTER: Dhamrait GK

PROVIDER: S-EPMC7569973 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Associations between biological and sociodemographic risks for developmental vulnerability in twins at age 5: a population data linkage study in Western Australia.

Dhamrait Gursimran Kaur GK Christensen Daniel D Pereira Gavin G Taylor Catherine Louise CL

BMJ open 20201016 10

<h4>Objective</h4>To investigate the prevalence of, and associations between, prenatal and perinatal risk factors and developmental vulnerability in twins at age 5.<h4>Design</h4>Retrospective cohort study using bivariate and multivariable logistic regression.<h4>Setting</h4>Western Australia (WA), 2002-2015.<h4>Participants</h4>828 twin pairs born in WA with an Australian Early Development Census (AEDC) record from 2009, 2012 or 2015.<h4>Main outcome measures</h4>The AEDC is a national measure ...[more]

PMID: 33067288

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Project description:ObjectiveEarly childhood is a critical time to address risk factors associated with developmental vulnerability. This study investigated the associations between clusters of early life risk factors and developmental vulnerability in children's first year of full-time school at age 5.DesignA retrospective cohort study.SettingPopulation-wide linkage of administrative data records for children born in Tasmania, Australia in 2008-2010.ParticipantsThe cohort comprised 5440 children born in Tasmania in 2008-2010, with a Tasmanian 2015 Australian Early Development Census (AEDC) record and a Tasmanian Perinatal Collection record.Outcome measureThe AEDC is a national measure of child development across five domains: physical health and well-being, social competence, emotional maturity, language and cognitive skills (school-based), and communication skills and general knowledge. Children who scored below the 10th percentile on one or more AEDC domains were classified as developmentally vulnerable. Children with special needs are not included in the AEDC results.ResultsLatent class analysis identified five clusters of risk factors: low risks (65% of children), sociodemographic and health behaviour risks (24%), teenage mother and sociodemographic risks (6%), birth risks (3%), and birth, sociodemographic and health behaviour risks (2%). In this sample population, 20% of children were classified as developmentally vulnerable, but the proportion varied substantially by latent class. Logistic regression showed increased odds of developmental vulnerability associated with sociodemographic and health behaviour risks (OR 2.26, 95% CI 1.91 to 2.68, p<0.001), teenage mother and sociodemographic risks (OR 2.01, 95% CI 1.50 to 2.69, p<0.001), and birth, sociodemographic and health behaviour risks (OR 3.29, 95% CI 2.10 to 5.16. p<0.001), but not birth risks (OR 1.34, 95% CI 0.88 to 2.03, p=0.1649), relative to the reference group.ConclusionsThe patterning of risks across the five groups invites consideration of multisectoral policies and services to address complex clusters of risk factors associated with developmental vulnerability.

Project description:Larval production and recruitment underpin the maintenance of coral populations, but these early life history stages are vulnerable to extreme variation in physical conditions. Environmental managers aim to minimise human impacts during significant periods of larval production and recruitment on reefs, but doing so requires knowledge of the modes and timing of coral reproduction. Most corals are hermaphroditic or gonochoric, with a brooding or broadcast spawning mode of reproduction. Brooding corals are a significant component of some reefs and produce larvae over consecutive months. Broadcast spawning corals are more common and display considerable variation in their patterns of spawning among reefs. Highly synchronous spawning can occur on reefs around Australia, particularly on the Great Barrier Reef. On Australia's remote north-west coast there have been fewer studies of coral reproduction. The recent industrial expansion into these regions has facilitated research, but the associated data are often contained within confidential reports. Here we combine information in this grey-literature with that available publicly to update our knowledge of coral reproduction in WA, for tens of thousands of corals and hundreds of species from over a dozen reefs spanning 20° of latitude. We identified broad patterns in coral reproduction, but more detailed insights were hindered by biased sampling; most studies focused on species of Acropora sampled over a few months at several reefs. Within the existing data, there was a latitudinal gradient in spawning activity among seasons, with mass spawning during autumn occurring on all reefs (but the temperate south-west). Participation in a smaller, multi-specific spawning during spring decreased from approximately one quarter of corals on the Kimberley Oceanic reefs to little participation at Ningaloo. Within these seasons, spawning was concentrated in March and/or April, and October and/or November, depending on the timing of the full moon. The timing of the full moon determined whether spawning was split over two months, which was common on tropical reefs. There were few data available for non-Acropora corals, which may have different patterns of reproduction. For example, the massive Porites seemed to spawn through spring to autumn on Kimberley Oceanic reefs and during summer in the Pilbara region, where other common corals (e.g. Turbinaria & Pavona) also displayed different patterns of reproduction to the Acropora. The brooding corals (Isopora & Seriatopora) on Kimberley Oceanic reefs appeared to planulate during many months, possibly with peaks from spring to autumn; a similar pattern is likely on other WA reefs. Gaps in knowledge were also due to the difficulty in identifying species and issues with methodology. We briefly discuss some of these issues and suggest an approach to quantifying variation in reproductive output throughout a year.

Project description:BackgroundLinkage of demographic, health, and developmental administrative data can enrich population-based surveillance and research on developmental and educational outcomes. Transparency of the record linkage process and results are required to assess potential biases.ObjectivesTo describe the approach used to link records of kindergarten children from the Early Development Instrument (EDI) in Ontario to health administrative data and test differences in characteristics of children by linkage status. We demonstrate how socio-demographic and medical risk factors amass in their contribution to early developmental vulnerability and test the concordance of health diagnoses in both the EDI and health datasets of linked records.MethodsChildren with records in the 2015 EDI cycle were deterministically linked to a population registry in Ontario, Canada. We compared sociodemographic and developmental vulnerability data between linked and unlinked records. Among linked records, we examined the contribution of medical and social risk factors obtained from health administrative data to developmental vulnerability identified in the EDI using descriptive analyses.ResultsOf 135,937 EDI records, 106,217 (78.1%) linked deterministically to a child in the Ontario health registry using birth date, sex, and postal code. The linked cohort was representative of children who completed the EDI in age, sex, rural residence, immigrant status, language, and special needs status. Linked data underestimated children living in the lowest neighbourhood income quintile (standardized difference [SD] 0.10) and with higher vulnerability in physical health and well-being (SD 0.11) , social competence (SD 0.10), and language and cognitive development (SD 0.12). Analysis of linked records showed developmental vulnerability is sometimes greater in children with social risk factors compared to those with medical risk factors. Common childhood conditions with records in health data were infrequently recorded in EDI records.ConclusionsLinkage of early developmental and health administrative data, in the absence of a single unique identifier, can be successful with few systematic biases introduced. Cross-sectoral linkages can highlight the relative contribution of medical and social risk factors to developmental vulnerability and poor school achievement.

Dataset Information

Associations between biological and sociodemographic risks for developmental vulnerability in twins at age 5: a population data linkage study in Western Australia.

Publications

Associations between biological and sociodemographic risks for developmental vulnerability in twins at age 5: a population data linkage study in Western Australia.

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