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    Risk factors for maternal morbidity in Victoria, Australia: a population-based study

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    Author
    Lindquist, AC; Kurinczuk, JJ; Wallace, EM; Oats, J; Knight, M
    Date
    2015-01-01
    Source Title
    BMJ Open
    Publisher
    BMJ PUBLISHING GROUP
    University of Melbourne Author/s
    Oats, Jeremy; Lindquist, Anthea
    Affiliation
    Melbourne School of Population and Global Health
    Obstetrics and Gynaecology
    Metadata
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    Document Type
    Journal Article
    Citations
    Lindquist, A. C., Kurinczuk, J. J., Wallace, E. M., Oats, J. & Knight, M. (2015). Risk factors for maternal morbidity in Victoria, Australia: a population-based study. BMJ OPEN, 5 (8), https://doi.org/10.1136/bmjopen-2015-007903.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/257706
    DOI
    10.1136/bmjopen-2015-007903
    Abstract
    OBJECTIVES: The aim of this analysis was to quantify the risk factors associated with maternal morbidity among women in Victoria, Australia, focusing particularly on sociodemographic factors. DESIGN: Case-control analysis. PARTICIPANTS: Data on all maternities in Victoria from 1 January 2006 to 31 December 2008. METHODS: A case-control analysis was conducted using unconditional logistic regression to calculate adjusted ORs (aORs). Cases were defined as all women noted to have had a severe complication during the index pregnancy. Severe maternal morbidity was defined by the validated, composite Australian Maternal Morbidity Outcome Indicator. Socioeconomic position was defined by Socio-Economic Indices for Areas (SEIFA), specifically the Index of Relative Socioeconomic Disadvantage (IRSD), and other variables analysed were age, parity, Indigenous background, multiple pregnancy, country of birth, coexisting medical condition, previous caesarean section, spontaneous abortion or ectopic pregnancy. RESULTS: The study population comprised 211,060 women, including 1119 cases of severe maternal morbidity (0.53%). Compared with the highest IRSD quintile, the aOR for the 2nd quintile was 1.23 (95% CI 1.03 to 1.49), 0.98 (95% CI 0.79 to 1.21) for the 3rd quintile, 1.55 (95% CI 1.28 to 1.87) for the 4th and 1.21 (95% CI 1.00 to 1.47) for the lowest (most deprived) quintile. Indigenous status was associated with twice (aOR 2.02; 95% CI 1.32 to 3.09) the odds of being a case. Other risk factors for severe maternal morbidity were age ≥ 35 years (aOR 1.22; 95% CI 1.04 to 1.44), coexisting medical condition (aOR 1.39; 95% CI 1.16 to 1.65), multiple pregnancy (aOR 2.30; 95% CI 1.71 to 3.10), primiparity (aOR 1.36; 95% CI 1.18 to 1.57), previous caesarean section (aOR 1.79; 95% CI 1.53 to 2.10) and previous spontaneous miscarriage (aOR 1.25; 95% CI 1.08 to 1.44). CONCLUSIONS: The findings from Victoria strongly suggest that social disadvantage needs to be acknowledged and further investigated as an independent risk factor for adverse maternal outcomes in Australia and incorporated into appropriate policy planning and healthcare programmes.

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