Discussion
In our population, GDM incidence increased from 8.7% in 2008–2011 to 12.5% in 2012–2015. At the same time, socioeconomic differences in GDM reduced but nonetheless persisting even after adjusting for maternal risk factors; the greatest difference for GDM across socioeconomic groups was for BMI. Our findings showed women with lower socioeconomic levels than upper level employees, particularly long-term unemployed women, experienced higher aORs of GDM with increasing maternal age. This disproportionate socioeconomic-related risk of GDM across age groups was not accounted for by differences in BMI or smoking status.
At the population level, during a period of advances in well-being and welfare policies, the incidence of GDM increased,13 14 while socioeconomic differences in GDM narrowed within the population. This paradoxical situation occurred alongside epidemiological transitions, including increases in rates of maternal obesity and maternal age.14 15
Our results show that women of lower socioeconomic status had a higher risk of GDM, in line with other studies that used education as a proxy for socioeconomic status.7 15 We performed an appropriately conservative statistical adjustment and found that socioeconomic differences in GDM in our population partly result from inequalities in smoking during pregnancy, despite strong tobacco control efforts, and maternal obesity.16 17 In addition, persistent socioeconomic differences in GDM, regardless of well-developed screening and welfare policies, indicate that women’s knowledge or other elements associated with socioeconomic status predict health-related behavior.14 Therefore, factors associated with socioeconomic status can be used to prevent GDM or reduce the incidence of GDM, as women of higher socioeconomic groups with higher levels of education and income experienced in our studies. Mackenbach suggested that during the period of epidemiological changes, health improvement depends on behavior changes such as healthy diet and quitting smoking.14 These changes occur first among the higher socioeconomic groups; this can partly explain the socioeconomic differences in GDM.14
Our results indicate that consequences of postponing pregnancy intentionally or unintentionally (eg, subfecundity related to obesity) were more harmful for GDM among those with lower socioeconomic levels than upper level employees, as also reported in other settings.18 19 However, interaction between socioeconomic status and maternal age regarding GDM was not tested. Our findings of the vulnerability of long-term unemployed women and women in manual occupations could arise through the clustering of risk factors and as the result of cumulative effects of psychosocial stresses and disadvantages associated with low socioeconomic status over the reproductive years.20 Furthermore, socioeconomic differences in maternal obesity and smoking have been evidenced from the beginning of reproductive years.16 17 Earlier onset of smoking and obesity among women with lower socioeconomic status means a longer duration of exposure and more severe consequences on pregnancy outcomes and the future health of mothers.21–23 Therefore, a more detrimental effect of risk factors among women with lower socioeconomic status could contribute to the socioeconomic differences in the incidence of GDM within the population. Unlike other studies, barriers to health resources do not explain the GDM paradox in Finland, where all women have the same access to health information and services.
Using the MBR with a high degree of coverage and a methodology free from selection bias enabled us to evaluate the association between socioeconomic status, maternal risk factors, and GDM.24 Finnish register data contain detailed information about maternal health and socioeconomic status over the life course and have been considered a potential gold mine for health inequality research.25 The large sample size allowed us to assess effect modification across subgroups, constituting a major strength of this study.
Using occupation and occupational status as the proxy of socioeconomic status was both a strength and a weakness. In Finland, education, occupation, and income are inter-related; women of higher socioeconomic status have higher education and income and can afford to live in higher socioeconomic areas. However, we acknowledge that indicators of socioeconomic status are not interchangeable, and each indicator has its own dimensions. Also, self-reported height and weight are known to be subjected to misreporting,26 but as midwives or public health nurses measured and checked height and weight at the first antenatal visit, the risk of measurement errors is small. As our data were based on routinely collected information for administrative purposes, we had no information on other factors that could affect the association between socioeconomic status and GDM, including lifestyle-related factors and gestational weight gain. Prior studies have found that excessive gestational weight gain was associated with an increased risk of GDM.27 In this study, we had no information on whether excessive gestational weight gain could affect the strength of the associations; this topic warrants further investigations. Our results are relevant in countries where women of lower socioeconomic groups have a higher risk of GDM, which cannot be explained by maternal risk factors or interventions.
In our study, younger mothers showed lower risks of GDM than other age groups; however, pregnancy in adolescents and young mothers is already considered a high-risk status because of an increased risk of adverse pregnancy outcomes28; particularly pregnancies occurring in young mothers with GDM would be expected to be at high risk.29 Additionally, studies have indicated that GDM in young mothers is becoming increasingly common, and it seems GDM cannot be only attributed to women 35 years or older.30 It is therefore fundamental to develop strategies for the prevention and intervention of GDM from the beginning of the reproductive years.
Moreover, addressing only unhealthy behaviors at the population level benefits mainly women with higher socioeconomic status and further increases inequalities.14 31 Based on proportion universalism, public health interventions should be universal, at the same time applying targeted interventions to narrow the maternal health inequality gap. To apply this strategy, we assessed interaction on the additive scale to identify priority populations who benefit the most from targeted interventions.32 Based on our results, maternal age of 30 years and older among long-term unemployed women, women in manual occupations and students generate more cases of GDM. Thus, the increasing trend in postponing pregnancy could increase GDM among women with lower socioeconomic status at the ecosystem level. In this situation, interventions directed at low socioeconomic status while considering maternal age would be able to prevent most cases of GDM, reduce the burden of GDM at the population level, and decrease inequalities in GDM within the population.32 This approach could be tested in designated prospective clinical trials. For instance, a prospective randomized controlled trial indicated that even simple lifestyle interventions among high-risk mothers reduced the incidence of GDM by 39%.33