Background The health of an (unborn) child is largely determined by the health and social determinants of its parents. The extent to which social determinants of parents or prospective parents affect their own health depends partly on their coping or resilience abilities. Inadequate abilities allow negative effects of unfavourable social determinants to prevail, rendering them vulnerable to adverse health outcomes. Addressing these determinants in the reproductive-aged population is therefore a key approach in improving the health of the future generation. This systematic review aims to synthesise evidence on social determinants of vulnerability, i.e., inadequate coping or low resilience, in the general population of reproductive age. Methods The databases EMBASE, Medline, PsycINFO, CINAHL, Google Scholar, Web of Science, and Cochrane Library, were systematically searched from database inception to December 2th 2021. Observational studies examining social determinants and demographics in relation to vulnerability among the general population of reproductive age (men and women aged 18-40 years), conducted in a high-income country in Europe or North America, Australia or New Zealand were eligible for inclusion. Relevant data was extracted from each included article and findings were presented in a narrative and tabulated manner. Results We identified 40,028 unique articles, of which 78 were full text reviewed. Twenty-five studies were included, of which 21 had a cross-sectional study design (84%). Coping was the most frequently assessed outcome measure (n = 17, 68%). Thirty social determinants were identified. Overall, a younger age, lower socioeconomic attainment, lack of connection with the social environment, and adverse life events were associated with inadequate coping or low resilience. Conclusions This review shows that certain social determinants are associated with vulnerability in reproductive-aged individuals. Knowing which factors make people more or less vulnerable carries health-related implications. More high-quality research is needed to obtain substantial evidence on the strength of the effect of these social conditions in this stage of life.
Background Early detection of vulnerability during or before pregnancy can contribute to optimizing the first 1000 days, a crucial period for children’s development and health. We aimed to identify classes of vulnerability among pregnant women in the Netherlands using pre-pregnancy data on a wide range of social risk and protective factors, and validate these classes against the risk of adverse outcomes. Methods We conducted a latent class analysis based on 42 variables derived from nationwide observational data sources and self-reported data. Variables included individual, socioeconomic, lifestyle, psychosocial and household characteristics, self-reported health, healthcare utilization, life-events and living conditions. We compared classes in relation to adverse outcomes using logistic regression analyses. Results In the study population of 4172 women, we identified five latent classes. The largest ‘healthy and socioeconomically stable’-class [n = 2040 (48.9%)] mostly shared protective factors, such as paid work and positively perceived health. The classes ‘high care utilization’ [n = 485 (11.6%)], ‘socioeconomic vulnerability’ [n = 395 (9.5%)] and ‘psychosocial vulnerability’ [n = 1005 (24.0%)] were characterized by risk factors limited to one specific domain and protective factors in others. Women classified into the ‘multidimensional vulnerability’-class [n = 250 (6.0%)] shared multiple risk factors in different domains (psychosocial, medical and socioeconomic risk factors). Multidimensional vulnerability was associated with adverse outcomes, such as premature birth and caesarean section. Conclusions Co-existence of multiple risk factors in various domains is associated with adverse outcomes for mother and child. Early detection of vulnerability and strategies to improve parental health and well-being might benefit from focussing on different domains and combining medical and social care and support.
Background: Advances in computing power have enabled the collection, linkage and processing of big data. Big data in conjunction with robust causal inference methods can be used to answer research questions regarding the mechanisms underlying an exposure-outcome relationship. The g-formula is a flexible approach to perform causal mediation analysis that is suited for the big data context. Although this approach has many advantages, it is underused in perinatal epidemiology and didactic explanation for its implementation is still limited. Objective:The aim of this was to provide a didactic application of the mediational gformula by means of perinatal health inequalities research. Methods:The analytical procedure of the mediational g-formula is illustrated by investigating whether the relationship between neighbourhood socioeconomic status (SES) and small for gestational age (SGA) is mediated by neighbourhood social environment. Data on singleton births that occurred in the Netherlands between 2010 and 2017 (n = 1,217,626) were obtained from the Netherlands Perinatal Registry and linked to sociodemographic national registry data and neighbourhood-level data. The g-formula settings corresponded to a hypothetical improvement in neighbourhood SES from disadvantaged to non-disadvantaged. Results: At the population level, a hypothetical improvement in neighbourhood SES resulted in a 6.3% (95% confidence interval [CI] 5.2, 7.5) relative reduction in the proportion of SGA, that is the total effect. The total effect was decomposed into the natural direct effect (5.6%, 95% CI 5.1, 6.1) and the natural indirect effect (0.7%, 95% CI 0.6, 0.9). In terms of the magnitude of mediation, it was observed the natural indirect effect accounted for 11.4% (95% CI 9.2, 13.6) of the total effect of neighbourhood SES on SGA. Conclusions:The mediational g-formula is a flexible approach to perform causal mediation analysis that is suited for big data contexts in perinatal health research. Its
IntroductionResearch focusing on the associations between non-medical determinants and unfavourable perinatal health outcomes is increasing. Despite increasing knowledge on this theme, it still remains unclear to what extent social, environmental and lifestyle factors contribute to these unfavourable outcomes. Therefore, we aim to provide a systematic review, preferably with meta-analysis, in order to provide insight into the associations between non-medical determinants and perinatal mortality, preterm birth and being small for gestational age (SGA).Methods and analysisObservational studies performed in European countries studying the associations between non-medical determinants and unfavourable perinatal health outcomes will be included. Primary outcomes of interest are perinatal mortality, preterm birth and SGA. To retrieve potential eligible articles, a systematic literature search was performed in the following online databases on 5 October 2018: MEDLINE, Embase, Web of Science, Cochrane and Google Scholar. Additionally, a reference list check and citation search will be performed. Data of the included articles will be extracted using a standardised and piloted data extraction form. Risk of bias will be assessed using the Newcastle-Ottawa Scale. The study selection and data extraction process will be performed by two reviewers independently. Disagreements will be resolved through discussion with a third reviewer. The pooled effects will be calculated separately for each association found between one of the outcome measures and the non-medical determinants using a random effects model. Heterogeneity of the studies will be assessed using the I2statistic.Ethics and disseminationNo ethical approval is necessary for a systematic review with meta-analysis. The findings will be published in a peer-reviewed journal.PROSPERO registration numberCRD42018056105.
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