Objective and subjective childhood socioeconomic disadvantage and incident depression in adulthood: a longitudinal analysis in the Sister Study

Association between prenatal socioeconomic disadvantage, adverse birth outcomes, and inflammatory response at birth

Prenatal socioeconomic disadvantage is associated with inflammation in mid- to late-life, yet whether a pro-inflammatory phenotype is present at birth and the role of adverse birth outcomes in this pathway remains unclear. We utilized data on prenatal socioeconomic disadvantage at the individual- (i.e., mother's and father's education level, insurance type, marital status, and Women, Infants, and Children benefit receipt) and census-tract level as well as preterm (< 37 weeks gestation) and small-for-gestational-age (SGA) (i.e., < 10th percentile of sex-specific birth weight for gestational age) birth status, and assessed inflammatory markers (i.e., C-reactive protein, serum amyloid p, haptoglobin, and α-2 macroglobulin) in archived neonatal bloodspots from a Michigan population-based cohort of 1000 neonates. Continuous latent variables measuring individual- and combined individual- and neighborhood-level prenatal socioeconomic disadvantage were constructed and latent profile analysis was used to create a categorical inflammatory response variable (high versus low) based on continuous inflammatory marker levels. Structural equation models were used to estimate the total and direct effect of prenatal socioeconomic disadvantage on the inflammatory response at birth as well as indirect effect via preterm or SGA birth (among term neonates only), adjusting for mother's age, race/ethnicity, body mass index, smoking status, comorbidities, and antibiotic use/infection as well as grandmother's education level. There was a statistically significant total effect of both individual- and combined individual- and neighborhood-level prenatal socioeconomic disadvantage on high inflammatory response among all neonates as well as among term neonates only, and a positive but not statistically significant direct effect in both groups. The indirect effects via preterm and SGA birth were both negative, but not statistically significant. Our findings suggest prenatal socioeconomic disadvantage contributes to elevated neonatal inflammatory response, but via pathways outside of these adverse birth outcomes.

Risk factors relate to the variability of health outcomes as well as the mean: A GAMLSS tutorial

Background:

Risk factors or interventions may affect the variability as well as the mean of health outcomes. Understanding this can aid aetiological understanding and public health translation, in that interventions which shift the outcome mean and reduce variability are typically preferable to those which affect only the mean. However, most commonly used statistical tools do not test for differences in variability. Tools that do have few epidemiological applications to date, and fewer applications still have attempted to explain their resulting findings. We thus provide a tutorial for investigating this using GAMLSS (Generalised Additive Models for Location, Scale and Shape).

Methods:

The 1970 British birth cohort study was used, with body mass index (BMI; N = 6007) and mental wellbeing (Warwick-Edinburgh Mental Wellbeing Scale; N = 7104) measured in midlife (42–46 years) as outcomes. We used GAMLSS to investigate how multiple risk factors (sex, childhood social class, and midlife physical inactivity) related to differences in health outcome mean and variability.

Results:

Risk factors were related to sizable differences in outcome variability—for example males had marginally higher mean BMI yet 28% lower variability; lower social class and physical inactivity were each associated with higher mean and higher variability (6.1% and 13.5% higher variability, respectively). For mental wellbeing, gender was not associated with the mean while males had lower variability (–3.9%); lower social class and physical inactivity were each associated with lower mean yet higher variability (7.2% and 10.9% higher variability, respectively).

Conclusions:

The results highlight how GAMLSS can be used to investigate how risk factors or interventions may influence the variability in health outcomes. This underutilised approach to the analysis of continuously distributed outcomes may have broader utility in epidemiologic, medical, and psychological sciences. A tutorial and replication syntax is provided online to facilitate this (https://osf.io/5tvz6/).

Funding:

DB is supported by the Economic and Social Research Council (grant number ES/M001660/1), The Academy of Medical Sciences / Wellcome Trust (“Springboard Health of the Public in 2040” award: HOP001/1025); DB and LW are supported by the Medical Research Council (MR/V002147/1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.