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Potential prevention of small for gestational age in Australia: a population-based linkage study
Lee K Taylor1, Yuen Yi Cathy Lee, Kim Lim
1Centre for Epidemiology and Evidence, New South Wales Ministry of Health, Sydney, Australia. ltayl@doh.health.nsw.gov.au.
Insights
Reducing smoking in pregnancy can decrease the rate of small for gestational age (SGA) infants. Early antenatal care and managing high-risk pregnancies may also help prevent SGA births.
Area of Science:
- Obstetrics and Gynecology
- Neonatal Health
- Public Health
Background:
- Small for gestational age (SGA) infants face higher risks of illness and death.
- Identifying SGA risk factors is crucial for population-level prevention strategies.
Purpose of the Study:
- To identify risk factors associated with SGA births.
- To assess the potential for reducing SGA at a population level.
Main Methods:
- Linked birth and hospital records from New South Wales (2007-2010).
- Analysis stratified by preterm, term non-diabetic, and term diabetic mothers.
- Logistic regression and generalized estimating equations used to analyze SGA risk factors and calculate population attributable fractions (PAFs) for modifiable factors.
Main Results:
- Smoking during pregnancy was the leading modifiable risk factor, with the highest PAFs for preterm SGA (12.4%) and term SGA in non-diabetic mothers (10.3%).
- Other modifiable factors like illicit drug use, pregnancy hypertension, and late antenatal care initiation showed lower PAFs (<3%).
- Term infants of non-diabetic mothers constituted the largest proportion (88.5%) of SGA infants.
Conclusions:
- Reducing smoking in pregnancy offers a significant opportunity to decrease SGA prevalence.
- Earlier initiation of antenatal care and improved management of high-risk pregnancies may further contribute to reducing SGA rates.
Background:
Small for gestational age (SGA) infants are at increased risk of morbidity and mortality. We sought to identify risk factors associated with SGA and examined the potential for reducing the proportion of infants with SGA at a population level.
Methods:
Birth and hospital records were linked for births occurring in 2007-2010 in New South Wales, Australia. The analysis was stratified into three groups: preterm births, term births to non-diabetic mothers and term births to diabetic mothers. Logistic regression was used to examine the association between SGA and a range of socio-demographic and behavioural factors and health conditions, with generalised estimating equations to account for correlation among births to the same mother. Model-based population attributable fractions (PAFs) were calculated for risk factors that were considered causative and potentially modifiable.
Results:
Of 28,126 SGA infants, the largest group was term infants of non-diabetic mothers (88.5%), followed by term infants of diabetic mothers (6.3%) and preterm infants (5.3%). The highest PAFs were for smoking: 12.4% for preterm SGA and 10.3% for term SGA infants of non-diabetic mothers. Other risk factors for SGA that were considered modifiable included: illicit drug dependency or abuse in pregnancy in all three groups, and pregnancy hypertension and late commencement of antenatal care in term infants of non-diabetic mothers, but PAFs were less than 3%.
Conclusions:
There are opportunities for modest reduction of the prevalence of SGA through reduction in smoking in pregnancy, and possibly earlier commencement of antenatal care and improved management of high-risk pregnancies.
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