The relationship between maternal pre-pregnancy body mass index and exclusive breastfeeding initiation: Findings from an Australian obstetric cohort.

BACKGROUND: To assess the type of infant nutrition at initiation of first feed in association with increasing maternal pre-pregnancy Body Mass Index in an Australian obstetric population. METHODS: A retrospective cohort study from 2008 to 2013 was undertaken. Body Mass Index was available for 12,347 women categorised into groups according to: underweight (≤18 kg/m2); normal weight (19-24 kg/m2); overweight (25-29 kg/m2); obese class I (30-34 kg/m2); obese class II (35-39/kg2) and obese class III (40+ kg/m2). Type and initiation of infant feeding is routinely recorded in the study hospital's birthing outcomes system. Six body mass index categories and mode of infant feeding were examined using logistic regression. Confounding factors that were controlled for included smoking status, parity, country of birth and maternal age. RESULTS: Within this cohort, 609 (4.93%) women were underweight, 6235 (50.50%) had a normal BMI, 3116 (25.24%) were overweight, 1314 (10.64%) were obese class I, 596 (4.83%) were obese class II and 477 (3.86%) were obese class III. In adjusted models', as BMI rose, women were significantly less likely to initiate exclusive breastfeeding and more likely to exclusively formula feed. Women with a BMI of 40+ kg/m2 had an AOR of 2.91(CI 1.94-4.25) for initiating exclusive formula at the time of their infant's first feed. CONCLUSIONS: Women who are overweight or obese are significantly less likely to initiate exclusive breastfeeding and more likely to give exclusive formula at the time of their newborn infants first feed. Effective breastfeeding interventions are required for these high-risk groups in the days leading up to and within the first hours after birth.

Association of BMI and interpregnancy BMI change with birth outcomes in an Australian obstetric population: a retrospective cohort study.

OBJECTIVE: To assess maternal and neonatal outcomes associated with increasing body mass index (BMI) and interpregnancy BMI changes in an Australian obstetric population. METHODS: A retrospective cohort study from 2008 to 2013 was undertaken. BMI for 14 875 women was categorised as follows: underweight (≤18 kg/m(2)); normal weight (19-24 kg/m(2)); overweight (25-29 kg/m(2)); obese class I (30-34 kg/m(2)); obese class II (35-39 kg/m(2)) and obese class III (40+ kg/m(2)). BMI categories and maternal, neonatal and birthing outcomes were examined using logistic regression. Interpregnancy change in BMI and the risk of adverse outcomes in the subsequent pregnancy were also examined. RESULTS: Within this cohort, 751 (5.1%) women were underweight, 7431 (50.0%) had normal BMI, 3748 (25.1%) were overweight, 1598 (10.8%) were obese class I, 737 (5.0%) were obese class II and 592 (4.0%) were obese class III. In bivariate adjusted models, obese women were at an increased risk of caesarean section, gestational diabetes, hypertensive disorders of pregnancy and neonatal morbidities including macrosomia, large for gestational age (LGA), hypoglycaemia, low 5 min Apgar score and respiratory distress. Multiparous women who experienced an interpregnancy increase of ≥3 BMI units had a higher adjusted OR (AOR) (CI) of the following adverse outcomes in their subsequent pregnancy: low 5-min Apgar score 3.242 (1.557 to 7.118); gestational diabetes mellitus (GDM) 3.258 (1.129 to 10.665) and hypertensive disorders of pregnancy 3.922 (1.243 to 14.760). These women were more likely to give birth vaginally 2.030 (1.417 to 2.913). Conversely, women whose parity changed from 0 to 1 and who experienced an interpregnancy increase of ≥3 BMI units had a higher AOR (CI) of caesarean section in their second pregnancy 1.806 (1.139 to 2.862). CONCLUSIONS: Women who are overweight or obese have a significantly increased risk of various adverse outcomes. Interpregnancy weight gain, regardless of parity and baseline BMI, also increases various adverse outcomes. Effective weight management strategies are needed.

Methods for automatically analyzing humpback song units.

This paper presents mathematical techniques for automatically extracting and analyzing bioacoustic signals. Automatic techniques are described for isolation of target signals from background noise, extraction of features from target signals and unsupervised classification (clustering) of the target signals based on these features. The only user-provided inputs, other than raw sound, is an initial set of signal processing and control parameters. Of particular note is that the number of signal categories is determined automatically. The techniques, applied to hydrophone recordings of humpback whales (Megaptera novaeangliae), produce promising initial results, suggesting that they may be of use in automated analysis of not only humpbacks, but possibly also in other bioacoustic settings where automated analysis is desirable.