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Association between socioeconomic status, body mass index, and maternal morbidity Ayesha Siddiqui, MD MSc ED393 Epidemiology Thesis co-directors: Catherine.

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Presentation on theme: "Association between socioeconomic status, body mass index, and maternal morbidity Ayesha Siddiqui, MD MSc ED393 Epidemiology Thesis co-directors: Catherine."— Presentation transcript:

1 Association between socioeconomic status, body mass index, and maternal morbidity Ayesha Siddiqui, MD MSc ED393 Epidemiology Thesis co-directors: Catherine Deneux-Tharaux, Elie Azria Collaborating mentor: Elizabeth Howell Equipe EPOPé : Epidémiologie Périnatale, Obstétricale, et Pédiatrique Centre de Recherche Epidémiologie et Statistiques INSERM U October 2016

2 Background: severe maternal outcomes in developed countries
Maternal mortality generally low in most developed countries Maternal morbidity is likely a more sensitive indicator of obstetric care Severe acute maternal morbidity/near misses: the most severe complications of pregnancy which a woman survives

3 Background: severe acute maternal morbidity (SAMM)
Definition: Several, based on data source Some better validated than others Incidence/trends: USA: 163/10,000 delivery hospitalisations ( ), increasing France: data not available Source: CDC

4 Background: SAMM analyses
Patient System Quality Determinants are multifactorial Exploration of modifiable and competing risks SAMM

5 Background: selected patient-level factors associated with SAMM
Obesity Limited studies examining association with SAMM Majority focused on antepartum conditions, C-section rates, instrumental delivery, neonatal outcomes Socioeconomic factors Race/ethnicity Immigrant status Employment Race/ethnicity: AA (2-7x odds) Immigrant: SSA immigrants in Canada, Aus, and Denmark (OR: 1.67) Employment: manual > managerial/professional Limited obesity studies: 2 studies in UK (one small c/c n= 100, retro cohort n=under 300K) and one in ND of low risk pts (c/c n=4500) – dose response Obesity has been shown to be independently associated with socioeconomic status in the general population as well as among pregnant women

6 Study hypothesis: The association between low SES and SAMM is mediated by maternal obesity Obesity Low SES Maternal Obesity SAMM Currently unknown if obesity mediates the relationship between SES and SAMM We chose to study obesity as it is a potentially modifiable variable “Obesity” = BMI>30 kg/m2 BMI = body mass index SES = socioeconomic status SAMM = severe acute maternal morbidity

7 Specific objectives To test and quantify the association between BMI/obesity and SAMM To test the hypothesis that maternal obesity is an intermediary in the association between SES and SAMM

8 Predictors: BMI/obesity
Data sources - France PreCARE Clinical research study, prospective cohort Sample: all pregnant women registered to deliver at 4 university hospitals in Paris between 10/ /2011 (n=10,419) Self-administered questionnaires: medical and social histories at enrolment and immediate post-partum Medical chart & clinician questionnaires: demographic characteristics, pregnancy, delivery (including SAMM events) Predictors: SES Synthetic quantitative index built on the 2010 French National Perinatal Survey Various other composite possibilities Predictors: BMI/obesity Height Weight – pre-pregnancy Weight – at delivery Co-variates Medical characteristics: Pre-pregnancy Delivery Post-partum Outcome Composite SAMM outcome WHO SAMM components, e.g.: Hypertensive complications Hemorrhage Sepsis Interpreters/RA’s for self-admin: inclusion of those with low literacy and those who don’t speak French Social index: we have many social variables of good quality, limited missing data, will allow different dimensions of SES to be explored previously published index an option, several other ways to do it, different strengths – part of the work

9 Predictors: BMI/obesity
Data sources - France EPIMOMS Population-based prospective case-control study, 6 French regions, between Sample: 183,000 pregnant women Cases: women experienced SAMM (n=2,541) Controls (unmatched): women with uncomplicated deliveries (n=3,651) Medical chart: maternal demographic characteristics, pregnancy, delivery Predictors: SES Age Place of birth Nationality Educational level Professional category Predictors: BMI/obesity BMI Height Weight – pre-pregnancy Weight – at delivery Co-variates Medical characteristics: Pre-pregnancy Delivery Post-partum Outcomes Composite SAMM outcome WHO SAMM components, e.g.: Hypertensive complications Hemorrhage Sepsis Outcome def: delphi process

10 Predictors: BMI/obesity
Data sources - USA Existing database: New York City Vital Statistics birth records linked with New York State discharge abstract data -The Statewide Planning and Research Cooperative System (SPARCS) Sample: all delivery hospitalizations in New York City from (40 hospitals, ≈120, 000 deliveries per year) Birth certificate: sociodemographic, pregnancy, and delivery information SPARCS: insurance and diagnosis/procedure billing codes Predictors: SES Age Zip code Race/ethnicity Place of birth, how many years in USA Marital status Education Employment (and type) Insurance status Predictors: BMI/obesity Height Pre-pregnancy weight Co-variates Medical characteristics: Pre-pregnancy Delivery Post-partum Outcomes Existing composite SAMM variable in database using CDC definition SAMM components SAMM components from birth cert or diag/proc codes from SPARCS?

11 Data analysis: SO1 To test and quantify the association between BMI/obesity and SAMM
Dependent variable (outcome): SAMM composite and individual components (WHO) Independent variable: pre-pregnancy BMI, categorical variable (clinical cutoffs) Approach: classical adjusted logistic regression model

12 Data analysis: SO1 Considerations/anticipated challenges
Co-variate inclusion will vary by availability by database BMI distributions will differ by country  assessment of extreme categories N of SAMM outcome in PreCARE cohort likely low French data: Epimoms best suited

13 Data analysis: SO2 Maternal obesity is an intermediary in the association between SES and SAMM
Quantitative estimation of mediated effects Combination of 2 causal hypotheses: structural equation modelling  path analysis Counterfactual approach to ascertain the indirect effect of SES on SAMM  model multiple intermediate factors MacKinnon, DP et al 1993

14 Data analysis: SO2 Considerations/anticipated challenges
Definition of SES variable (composite categorical or components) Must include known confounders of all 3 relationships in the final model (exposure-outcome, exposure-mediator, mediator-outcome) Difficult to model categorical mediators Must test for interaction in the model Ability to conduct sensitivity analyses

15 Innovation Examination of a medical risk factor (obesity) as a social marker Parallel investigations in contrasting contexts Implications for future investigations: Inform evidence-based interventions to address patient-level modifiable and competing risks of SAMM

16 Timeline Year 1 The effect of maternal BMI on SAMM (publications 1 and 2) Years 2/3 Mediation of the association between SES and SAMM by maternal obesity (publications 3 and 4)

17 References  Alkema, L., et al., Global, regional, and national levels and trends in maternal mortality between 1990 and 2015, with scenario-based projections to 2030: a systematic analysis by the UN Maternal Mortality Estimation Inter-Agency Group. The Lancet, (10017): p Berg, C.J., et al., Preventability of pregnancy-related deaths: results of a state-wide review. Obstetrics & Gynecology, (6): p Bouvier‐Colle, M.H., et al., What about the mothers? An analysis of maternal mortality and morbidity in perinatal health surveillance systems in Europe. BJOG: An International Journal of Obstetrics & Gynaecology, (7): p Centers for Disease Control and Prevention. Severe Maternal Morbidity in the United States. 16 September 2016]; Available from: Clark-Ganheart, C.A., et al., Pregnancy Outcomes Among Obese Women and Their Offspring by Attempted Mode of Delivery. Obstetrics & Gynecology, (5): p Creanga, A.A., et al., Racial and ethnic disparities in severe maternal morbidity: a multistate analysis, American journal of obstetrics and gynecology, (5): p e e8. Drewnowski, A., et al., Food environment and socioeconomic status influence obesity rates in Seattle and in Paris. International Journal of Obesity, (2): p Grobman, W.A., et al., Racial and ethnic disparities in maternal morbidity and obstetric care. Obstetrics and gynecology, (6): p Grotta, A & Bellocco, R. A review of mediation analysis in Stata: principles, methods and applications. Online presentation, Available at: Lindquist, A., M. Knight, and J.J. Kurinczuk, Variation in severe maternal morbidity according to socioeconomic position: a UK national case–control study. BMJ open, (6): p. e MacKinnon, David P., and James H. Dwyer. "Estimating mediated effects in prevention studies." Evaluation review 17.2 (1993): Nair, M., J.J. Kurinczuk, and M. Knight, Ethnic variations in severe maternal morbidity in the UK–A Case Control Study. PloS one, (4): p. e95086. Ng, S.-K., et al., Socioeconomic disparities in prepregnancy BMI and impact on maternal and neonatal outcomes and postpartum weight retention: the EFHL longitudinal birth cohort study. BMC pregnancy and childbirth, (1): p. 1. Pallasmaa, N., et al., The impact of maternal obesity, age, pre-eclampsia and insulin dependent diabetes on severe maternal morbidity by mode of delivery—a register-based cohort study. Archives of gynecology and obstetrics, (2): p Salihu, H.M., et al., The superobese mother and ethnic disparities in preterm birth. Journal of the National Medical Association, (11): p Saucedo, M., C. Deneux-Tharaux, and M.-H. Bouvier-Colle, Ten years of confidential inquiries into maternal deaths in France, 1998–2007. Obstetrics & Gynecology, (4): p Say, L., J.P. Souza, and R.C. Pattinson, Maternal near miss–towards a standard tool for monitoring quality of maternal health care. Best Practice & Research Clinical Obstetrics & Gynaecology, (3): p Sebire, N.J., et al., Maternal obesity and pregnancy outcome: a study of pregnancies in London. International Journal of Obesity & Related Metabolic Disorders, (8). Urquia, M.L., et al., Severe maternal morbidity associated with maternal birthplace in three high-immigration settings. The European Journal of Public Health, (4): p Vinayagam, D. and E. Chandraharan, The adverse impact of maternal obesity on intrapartum and perinatal outcomes. ISRN obstetrics and gynecology, Witteveen, T., et al., Overweight and severe acute maternal morbidity in a low-risk pregnant population in the Netherlands. PloS one, (9): p. e74494. World Health Organization, Evaluating the quality of care for severe pregnancy complications: the WHO near-miss approach for maternal health. Geneva: World Health Organization, 2011: p. 29.

18 Thank you


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