Investigating maternal risk factors as potential targets of intervention to reduce socioeconomic inequality in small for gestational age: a population-based study
1 Simon Fraser University, Faculty of Health Sciences, Burnaby, Canada
2 University of British Columbia, School of Population and Public Health, Vancouver, Canada
3 Child & Family Research Institute, BC Children’s Hospital, Vancouver, Canada
4 University of Victoria, School of Public Health and Social Policy, Faculty of Human and Social Development, Victoria, Canada
5 Department of Pathology and Laboratory Medicine, St Paul’s Hospital, Vancouver, Canada
6 Institut National de Santé Publique du Québec, Sainte-Foy, Canada
Citation and License
BMC Public Health 2012, 12:333 doi:10.1186/1471-2458-12-333Published: 8 May 2012
The major aim of this study was to investigate whether maternal risk factors associated with socioeconomic status and small for gestational age (SGA) might be viable targets of interventions to reduce differential risk of SGA by socioeconomic status (socioeconomic SGA inequality) in the metropolitan area of Vancouver, Canada.
This study included 59,039 live, singleton births in the Vancouver Census Metropolitan Area (Vancouver) from January 1, 2006 to September 17, 2009. To identify an indicator of socioeconomic SGA inequality, we used hierarchical logistic regression to model SGA by area-level variables from the Canadian census. We then modelled SGA by area-level average income plus established maternal risk factors for SGA and calculated population attributable SGA risk percentages (PAR%) for each variable. Associations of maternal risk factors for SGA with average income were investigated to identify those that might contribute to SGA inequality. Finally, we estimated crude reductions in the percentage and absolute differences in SGA risks between highest and lowest average income quintiles that would result if interventions on maternal risk factors successfully equalized them across income levels or eliminated them altogether.
Average income produced the most linear and statistically significant indicator of socioeconomic SGA inequality with 8.9% prevalence of SGA in the lowest income quintile compared to 5.6% in the highest. The adjusted PAR% of SGA for variables were: bottom four quintiles of height (51%), first birth (32%), bottom four quintiles of average income (14%), oligohydramnios (7%), underweight or hypertension, (6% each), smoking (3%) and placental disorder (1%). Shorter height, underweight and smoking during pregnancy had higher prevalence in lower income groups. Crude models assuming equalization of risk factors across income levels or elimination altogether indicated little potential change in relative socioeconomic SGA inequality and reduction in absolute SGA inequality for shorter height only.
Our findings regarding maternal height may indicate trans-generational aetiology for socioeconomic SGA inequalities and/or that adult height influences social mobility. Conditions affecting foetal and childhood growth might be viable targets to reduce absolute socioeconomic SGA inequality in future generations, but more research is needed to determine whether such an approach is appropriate.