Potential prevention of small for gestational age in Australia: a population-based linkage study.

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.

Unexplained variation in hospital caesarean section rates.

OBJECTIVES: To assess recent hospital caesarean section (CS) rates in New South Wales, adjusted for case mix; to quantify the amount of variation that can be explained by case mix differences; and to examine the potential impact on the overall CS rate of reducing variation in practice. DESIGN AND SETTING: Population-based record linkage study of births in 81 hospitals in New South Wales, 2009-2010, using the Robson classification to categorise births, and multilevel logistic regression to examine variation in hospital CS rates within Robson groups. MAIN OUTCOME MEASURES: Hospital CS rates. RESULTS: The overall CS rate was 30.9%, ranging from 11.8% to 47.4% (interquartile range, 23.9%-33.1%) among hospitals. The three groups contributing most to the overall CS rate all comprised women with a single cephalic pregnancy who gave birth at term, including: those who had had a previous CS (36.4% of all CSs); nulliparous women with an elective delivery (prelabour CS or labour induction, 23.4%); and nulliparous women with spontaneous labour (11.1%). After adjustment for case mix, marked unexplained variation in hospital CS rates persisted for: nulliparous women at term; women who had had a previous CS; multifetal pregnancies; and preterm births. If variation in practice was reduced for these risk-based groups by achieving the "best practice" rate, this would lower the overall rate by an absolute reduction of 3.6%, from 30.9% to 27.3%. CONCLUSION: Understanding hospital heterogeneity in performing CS and implementing evidence-based practices may result in improved maternity care. We have identified five risk-based groups as priority targets for reducing practice variation in CS rates.

Using hospital discharge data to identify incident pregnancy-associated cancers: a validation study.

BACKGROUND: Pregnancy-associated cancer is associated with maternal morbidities and adverse pregnancy outcomes, and is reported to be increasing. Hospital discharge data have the potential to provide timely information on cancer incidence, which is central to evaluation and improvement of clinical care for women. This study aimed to assess the validity of hospital data for identifying incident pregnancy-associated cancers compared with incident cancers from an Australian population-based statutory cancer registry. METHODS: Birth data from 2001-2008, comprised 470,277 women with 679,736 maternities, were linked to cancer registry and hospitalisation records to identify newly diagnosed cancers during pregnancy or within 12 months of delivery. Two hospital-identified cancer groups were examined; "index cancer hospitalisation" - first cancer admission per woman per pregnancy and "all cancer hospitalisations" -the total number of hospitalisations with a cancer diagnosis and women could have multiple hospitalisations during pregnancy. The latter replicates a scenario where identification of individuals is not possible and hospitalisations are used as the unit of analysis. RESULTS: The incidence of pregnancy-associated cancer (according to cancer registry) was 145.4/100,000 maternities. Incidence of cancer was substantially over-estimated when using hospitalisations as the unit of analysis (incidence rate ratio, IRR 1.7) and under-estimated when using the individual (IRR 0.8). Overall, the sensitivity of "index cancer hospitalisation" was 60.4%, positive predictive value (PPV) 77.7%, specificity and negative predictive value both 100%. Melanoma ascertainment was only 36.1% and breast cancer 62.9%. For other common cancers sensitivities ranged from 72.1% to 78.6% and PPVs 56.4% to 87.3%. CONCLUSION: Although hospital data provide another timely source of cancer identification, the validity is insufficient to obtain cancer incidence estimates for the obstetric population.