Socioethnic disparities in severe maternal morbidity in Western Australia: a statewide retrospective cohort study

Abstract

ObjectivesTo assess the scale of ethnic inequalities in severe maternal morbidity (SMM) rates and quantify the contribution of maternal characteristics to these disparities.DesignRetrospective cohort study.SettingWhole-of-population linked administrative data from 2002 to 2015 in Western Australia.ParticipantsWomen with 410 043 birth events (includes all births from the same pregnancy) of 20 weeks’ or more gestation, including terminations for congenital anomalies.Primary and secondary outcome measuresWomen with SMM were identified based on a composite indicator of SMM using diagnosis and procedure codes developed for use in routinely collected data. Mothers were classified into seven ethnic groups, based on their reported ethnic origin. The associations between maternal ethnic origin and SMM were examined using a log-binomial model, which estimates risk ratios (RRs) and 95% CIs. The Blinder-Oaxaca decomposition technique was employed to partition the disparity in SMM between Aboriginal and Caucasian populations into ‘explained’ and ‘unexplained’ components.ResultsDuring the study period, 9378 SMM cases were documented. In the adjusted model, Aboriginal (RR 1.73, 95% CI 1.59 to 1.87), African (RR 1.64, 95% CI 1.43 to 1.89) and ‘other’ ethnicity (RR 1.49, 95% CI 1.37 to 1.63) women were at significantly higher risk of SMM compared with Caucasian women. Teenage and older mothers and socioeconomically disadvantaged women were also at greater risk of SMM. Differences in sociodemographic characteristics explained 33.2% of the disparity in SMM between Aboriginal and Caucasian women.ConclusionsThere are distinct disparities in SMM by ethnicity in Western Australia, with a greater risk among Aboriginal and African women. While improvements in SES and a reduction in teenage pregnancy can potentially support a sizeable reduction in SMM rate inequalities, future research should investigate other potential pathways and targeted interventions to close the ethnicity disparity.

A scoping review of maternal near miss assessment in Australia, New Zealand, South‐East Asia and the South Pacific region: How, what, why and where to?

“…In contrast, most high‐income settings data relating to MNM have been attained from routinely collected data sets with the majority undertaken retrospectively – the admission to high dependency unit/ICU and MMOI criteria were used most often in NZ and Australia, respectively 28–43 . These studies assessed the level of severe morbidity either as a composite indicator or associated with a particular condition and/or to determine risk factors associated with severe morbidity using routinely collected datasets, with large sample sizes retrospectively correlated to ICD‐10 codes.…”

“…Indirect obstetric causes such as pre‐existing medical problems were rarely identified although non‐obstetric infectious aetiologies were prominent in two LMIC studies 52,53 . Eight studies in our scoping review purposefully reviewed risk factors for MNM 21,22,27,32,39,43,54–56 . Among these studies, non‐European ethnicity, low socio‐economic status, and clinical factors such as older age, previous pregnancy, or medical complications were identified.…”

“…In contrast, most high-income settings data relating to MNM have been attained from routinely collected data sets with the majority undertaken retrospectively -the admission to high dependency unit/ICU and MMOI criteria were used most often in NZ and Australia, respectively. [28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43] These studies assessed the level of severe morbidity either as a composite indicator or associated with a particular condition and/or to determine risk factors associated with severe morbidity using routinely collected datasets, with large sample sizes retrospectively correlated to ICD-10 codes. Besides the MMOI, other ICD-based criteria included the modified Wahlberg et al 22 criteria, a Centre for Disease Control (CDC) SMM tool 44 and a modified combination of the WHO plus American College of Obstetricians and Gynecologists diagnostic and intervention codes.…”

“…52,53 Eight studies in our scoping review purposefully reviewed risk factors for MNM. 21,22,27,32,39,43,[54][55][56] Among these studies, non-European ethnicity, low socio-economic status, and clinical factors such as older age, previous pregnancy, or medical complications were identified. Other near miss studies either did not focus on risk factor determination, eg studies on preventability of severe morbidity reviewed risk factors specific to the disease condition of focus (eg women with juvenile arthritis [34][35][36]38 or reported on demographics but did not undertake statistical analysis due to the small numbers identified.…”

The Western Australian preterm birth prevention initiative: a whole of state singleton pregnancy cohort study showing the need to embrace alternative models of care for Aboriginal women

“…One in eleven Australians is born too early and among Aboriginal and/or Torres Strait Islander women (hereafter respectfully referred to as Aboriginal) the rate is almost double [3]. Perinatal outcomes are considerably worse for Australian Aboriginal infants, who experience higher rates of PTB, low birthweight and infant mortality both nationally [3], and in Western Australia (WA) [4][5][6]. The causes of these inequalities are complex and risk factors for poor perinatal outcomes are not necessarily the same in Aboriginal women as in the broader WA obstetric population.…”