Formula supplementation in hospital and subsequent feeding at discharge among women who intended to exclusively breastfeed: An administrative data retrospective cohort study

Birth ◽  
2017 ◽  
Vol 44 (4) ◽  
pp. 352-362 ◽  
Author(s):  
Jason P. Bentley ◽  
Natasha Nassar ◽  
Maree Porter ◽  
Michelle de Vroome ◽  
Elizabeth Yip ◽  
...  
Keyword(s):  
Cohort Study ◽  
Administrative Data ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort

scholarly journals Associations between clusters of early life risk factors and developmental vulnerability at age 5: a retrospective cohort study using population-wide linkage of administrative data in Tasmania, Australia

BMJ Open ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. e033795
Author(s):  
Catherine Louise Taylor ◽  
Daniel Christensen ◽  
Joel Stafford ◽  
Alison Venn ◽  
David Preen ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cohort Study ◽  
Administrative Data ◽  
Health Behaviour ◽  
Retrospective Cohort Study ◽  
Early Life ◽  
Retrospective Cohort ◽  
Latent Class ◽  
Teenage Mother ◽  
Factors Associated

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.

Sign in / Sign up

Export Citation Format

Share Document