Prescribing trends of proton pump inhibitors and histamine blockers among children in the United Kingdom (1998-2019): A population-based assessment.

PURPOSE: To describe the prescribing trends of proton pump inhibitors (PPIs) and H2 receptor antagonists (H2 RAs) among children with gastroesophageal reflux in the United Kingdom between 1998 and 2019. METHODS: We conducted a population-based retrospective cohort study using data from the Clinical Practice Research Datalink that included all children aged ≤18 years with a first ever diagnosis of gastroesophageal reflux between 1998 and 2019. Using negative binomial regression, we estimated crude and adjusted annual prescription rates per 1000 person-years and corresponding 95% confidence intervals (CIs) for PPIs and H2 RAs. We also assessed rate ratios of PPIs and H2 RAs prescription rates to examine changes in prescribing over time. RESULTS: Our cohort included 177 477 children with a first ever diagnosis of gastroesophageal reflux during the study period. The median age was 13 years (IQR: 1, 17) among children prescribed PPIs and 0.2 years (IQR: 0.1, 0.6) among those prescribed H2 RAs. The total prescription rate of all GERD drugs was 1468 prescriptions per 1000 person-years (PYs) (95% CI 1463-1472). Overall, PPIs had a higher prescription rate (815 per 1000 PYs, 95% CI 812-818) than H2 RAs (653 per 1000 PYs 95% CI 650-655). Sex- and age-adjusted rate ratios of 2019 versus 1998 demonstrated a 10% increase and a 76% decrease in the prescription rates of PPIs and H2 RAs, respectively. CONCLUSIONS: Prescription rates for PPIs increased, especially during the first half of the study period, while prescription rates for H2 RA decreased over time.

Generating synthetic data from administrative health records for drug safety and effectiveness studies.

Introduction: Administrative health records (AHRs) are used to conduct population-based post-market drug safety and comparative effectiveness studies to inform healthcare decision making. However, the cost of data extraction, and the challenges associated with privacy and securing approvals can make it challenging for researchers to conduct methodological research in a timely manner using real data. Generating synthetic AHRs that reasonably represent the real-world data are beneficial for developing analytic methods and training analysts to rapidly implement study protocols. We generated synthetic AHRs using two methods and compared these synthetic AHRs to real-world AHRs. We described the challenges associated with using synthetic AHRs for real-world study. Methods: The real-world AHRs comprised prescription drug records for individuals with healthcare insurance coverage in the Population Research Data Repository (PRDR) from Manitoba, Canada for the 10-year period from 2008 to 2017. Synthetic data were generated using the Observational Medical Dataset Simulator II (OSIM2) and a modification (ModOSIM). Synthetic and real-world data were described using frequencies and percentages. Agreement of prescription drug use measures in PRDR, OSIM2 and ModOSIM was estimated with the concordance coefficient. Results: The PRDR cohort included 169,586,633 drug records and 1,395 drug types for 1,604,734 individuals. Synthetic data for 1,000,000 individuals were generated using OSIM2 and ModOSIM. Sex and age group distributions were similar in the real-world and synthetic AHRs. However, there were significant differences in the number of drug records and number of unique drugs per person for OSIM2 and ModOSIM when compared with PRDR. For the average number of days of drug use, concordance with the PRDR was 16% (95% confidence interval [CI]: 12%-19%) for OSIM2 and 88% (95% CI: 87%-90%) for ModOSIM. Conclusions: ModOSIM data were more similar to PRDR than OSIM2 data on many measures. Synthetic AHRs consistent with those found in real-world settings can be generated using ModOSIM. Synthetic data will benefit rapid implementation of methodological studies and data analyst training.

Sodium-Glucose Cotransporter 2 Inhibitors and the Short-term Risk of Bladder Cancer: An International Multisite Cohort Study.

OBJECTIVE: To determine whether sodium-glucose cotransporter 2 (SGLT2) inhibitors, compared with glucagon-like peptide 1 receptor agonists (GLP-1RAs) or dipeptidyl peptidase 4 (DPP-4) inhibitors, are associated with an increased risk of early bladder cancer events. RESEARCH DESIGN AND METHODS: We conducted a multisite, population-based, new-user, active comparator cohort study using the U.K. Clinical Practice Research Datalink, Medicare fee-for-service, Optum's de-identifed Clinformatics Data Mart Database (CDM), and MarketScan Health databases from January 2013 through December 2020. We assembled two cohorts of adults with type 2 diabetes initiating 1) SGLT2 inhibitors or GLP-1RAs and 2) SGLT2 inhibitors or DPP-4 inhibitors. Cox proportional hazards models were fit to estimate hazard ratios (HRs) and 95% CIs of incident bladder cancer. The models were weighted using propensity score fine stratification. Site-specific HRs were pooled using random-effects models. RESULTS: SGLT2 inhibitor (n = 453,560) and GLP-1RA (n = 375,997) users had a median follow-up ranging from 1.5 to 2.2 years. Overall, SGLT2 inhibitors were not associated with an increased risk of bladder cancer compared with GLP-1RAs (HR 0.90, 95% CI 0.81-1.00). Similarly, when compared with DPP-4 inhibitors (n = 853,186), SGLT2 inhibitors (n = 347,059) were not associated with an increased risk of bladder cancer (HR 0.99, 95% CI 0.91-1.09) over a median follow-up ranging from 1.6 to 2.6 years. Results were consistent across sensitivity analyses. CONCLUSIONS: Contrary to previous randomized controlled trials, these findings indicate that the use of SGLT2 inhibitors is not associated with an increased risk of bladder cancer compared with GLP-1RAs or DPP-4 inhibitors. This should provide reassurance on the short-term effects of SGLT2 inhibitors on bladder cancer incidence.

Use of levothyroxine among pregnant women with subclinical hypothyroidism in the United Kingdom: A population-based assessment.

Our study aimed to describe levothyroxine prescription patterns and trends over time among pregnant women with subclinical hypothyroidism (SCH) in the United Kingdom. We used data from the Clinical Practice Research Datalink linked to its Pregnancy Register and the Hospital Episode Statistics database from 1998 to 2017. The study population included women with a diagnosis of SCH or an abnormal thyroid-simulated hormone (TSH) level one year prior to or during pregnancy. We compared characteristics between women who received a prescription for levothyroxine during pregnancy and those who did not. We further described the timing, dose, duration, and temporal trends of levothyroxine prescriptions. Our cohort included 6,757 pregnancies from 6,287 women with SCH, of whom 10% received levothyroxine during pregnancy. Among women who received levothyroxine, most received their first prescription during the first trimester (median gestational age: 7 weeks; interquartile range [IQR]: 0, 16) with a median daily dosage of 50 mcg (IQR: 50, 73). Levothyroxine prescription varied over time, decreasing from 23% of pregnant women in 1998 to 7.5% in 2003, remaining stable until 2014, and increasing to 12.5% in 2016. Smoking, diabetes, polycystic ovary syndrome, infertility, timing of SCH diagnosis, age, TSH level at diagnosis, and general practice regions were associated with prescription. Few women with SCH received levothyroxine during pregnancy, and treatment varied by patient characteristics and geographical regions. These results highlight the need to increase awareness among healthcare providers and will guide future studies that explore barriers to initiating levothyroxine treatment for women with SCH during pregnancy.

Good practices for the design, analysis, and interpretation of observational studies on birth spacing and perinatal health outcomes.

BACKGROUND: Meta-analyses of observational studies have shown that women with a shorter interpregnancy interval (the time from delivery to start of a subsequent pregnancy) are more likely to experience adverse pregnancy outcomes, such as preterm delivery or small for gestational age birth, than women who space their births further apart. However, the studies used to inform these estimates have methodological shortcomings. METHODS: In this commentary, we summarise the discussions of an expert workgroup describing good practices for the design, analysis, and interpretation of observational studies of interpregnancy interval and adverse perinatal health outcomes. RESULTS: We argue that inferences drawn from research in this field will be improved by careful attention to elements such as: (a) refining the research question to clarify whether the goal is to estimate a causal effect vs describe patterns of association; (b) using directed acyclic graphs to represent potential causal networks and guide the analytic plan of studies seeking to estimate causal effects; (c) assessing how miscarriages and pregnancy terminations may have influenced interpregnancy interval classifications; (d) specifying how key factors such as previous pregnancy loss, pregnancy intention, and maternal socio-economic position will be considered; and (e) examining if the association between interpregnancy interval and perinatal outcome differs by factors such as maternal age. CONCLUSION: This commentary outlines the discussions of this recent expert workgroup, and describes several suggested principles for study design and analysis that could mitigate many potential sources of bias.

An Evaluation of Healthcare Use and Child Morbidity 4 Years After User Fee Removal in Rural Burkina Faso.

Objectives Increasing financial access to healthcare is proposed to being essential for improving child health outcomes, but the available evidence on the relationship between increased access and health remains scarce. Four years after its launch, we evaluated the contextual effect of user fee removal intervention on the probability of an illness occurring and the likelihood of using health services among children under 5. We also explored the potential effect on the inequality in healthcare access. Methods We used a comparative cross-sectional design based upon household survey data collected years after the intervention onset in one intervention and one comparison district. Propensity scores weighting was used to achieve balance on covariates between the two districts, which was followed by logistic multilevel modelling to estimate average marginal effects (AME). Results We estimated that there was not a significant difference in the reduced probability of an illness occurring in the intervention district compared to the non-intervention district [AME 4.4; 95% CI 1.0-9.8)]. However, the probability of using health services was 17.2% (95% CI 15.0-26.6) higher among children living in the intervention district relative to the comparison district, which rose to 20.7% (95% CI 9.9-31.5) for severe illness episodes. We detected no significant differences in the probability of health services use according to socio-economic status [χ2 (5) = 12.90, p = 0.61]. Conclusions for Practice In our study, we found that user fee removal led to a significant increase in the use of health services in the longer term, but it is not adequate by itself to reduce the risk of illness occurrence and socioeconomic inequities in the use of health services.

Comparison of statistical approaches dealing with time-dependent confounding in drug effectiveness studies.

In longitudinal studies, if the time-dependent covariates are affected by the past treatment, time-dependent confounding may be present. For a time-to-event response, marginal structural Cox models are frequently used to deal with such confounding. To avoid some of the problems of fitting marginal structural Cox model, the sequential Cox approach has been suggested as an alternative. Although the estimation mechanisms are different, both approaches claim to estimate the causal effect of treatment by appropriately adjusting for time-dependent confounding. We carry out simulation studies to assess the suitability of the sequential Cox approach for analyzing time-to-event data in the presence of a time-dependent covariate that may or may not be a time-dependent confounder. Results from these simulations revealed that the sequential Cox approach is not as effective as marginal structural Cox model in addressing the time-dependent confounding. The sequential Cox approach was also found to be inadequate in the presence of a time-dependent covariate. We propose a modified version of the sequential Cox approach that correctly estimates the treatment effect in both of the above scenarios. All approaches are applied to investigate the impact of beta-interferon treatment in delaying disability progression in the British Columbia Multiple Sclerosis cohort (1995-2008).

Effect Estimation in Point-Exposure Studies with Binary Outcomes and High-Dimensional Covariate Data - A Comparison of Targeted Maximum Likelihood Estimation and Inverse Probability of Treatment Weighting.

Inverse probability of treatment weighting (IPW) and targeted maximum likelihood estimation (TMLE) are relatively new methods proposed for estimating marginal causal effects. TMLE is doubly robust, yielding consistent estimators even under misspecification of either the treatment or the outcome model. While IPW methods are known to be sensitive to near violations of the practical positivity assumption (e. g., in the case of data sparsity), the consequences of this violation in the TMLE framework for binary outcomes have been less widely investigated. As near practical positivity violations are particularly likely in high-dimensional covariate settings, a better understanding of the performance of TMLE is of particular interest for pharmcoepidemiological studies using large databases. Using plasmode and Monte-Carlo simulation studies, we evaluated the performance of TMLE compared to that of IPW estimators based on a point-exposure cohort study of the marginal causal effect of post-myocardial infarction statin use on the 1-year risk of all-cause mortality from the Clinical Practice Research Datalink. A variety of treatment model specifications were considered, inducing different degrees of near practical non-positivity. Our simulation study showed that the performance of the TMLE and IPW estimators were comparable when the dimension of the fitted treatment model was small to moderate; however, they differed when a large number of covariates was considered. When a rich outcome model was included in the TMLE, estimators were unbiased. In some cases, we found irregular bias and large standard errors with both methods even with a correctly specified high-dimensional treatment model. The IPW estimator showed a slightly better root MSE with high-dimensional treatment model specifications in our simulation setting. In conclusion, for estimation of the marginal expectation of the outcome under a fixed treatment, TMLE and IPW estimators employing the same treatment model specification may perform differently due to differential sensitivity to practical positivity violations; however, TMLE, being doubly robust, shows improved performance with richer specifications of the outcome model. Although TMLE is appealing for its double robustness property, such violations in a high-dimensional covariate setting are problematic for both methods.

Phosphodiesterase Type 5 Inhibitors and the Risk of Melanoma Skin Cancer.

BACKGROUND: The association between phosphodiesterase type 5 inhibitors (PDE5-Is), drugs used in the treatment of erectile dysfunction (ED), and melanoma skin cancer is controversial. OBJECTIVE: To assess whether the use of PDE5-Is is associated with an increased risk of melanoma skin cancer. DESIGN, SETTING, AND PARTICIPANTS: Using the UK Clinical Practice Research Datalink, we assembled a cohort of men newly diagnosed with ED between 1998 and 2014 and followed until 2015. PDE5-I exposure was considered as a time-varying variable lagged by 1 yr for latency purposes. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Cox proportional hazards models were used to estimate adjusted hazard ratios (HRs) with 95% confidence intervals (CIs) of incident melanoma associated with PDE5-I use overall and by number of prescriptions and pills received. Identical analyses were conducted for basal and squamous cell carcinoma, two cancers for which PDE5-related pathways are not thought to be involved. RESULTS AND LIMITATIONS: The cohort included 142 983 patients, of whom 440 were newly diagnosed with melanoma during follow-up (rate: 63.0 per 100 000 person-years). Compared with nonuse, PDE5-I use was not associated with an overall increased risk of melanoma (rates: 66.7 vs 54.1 per 100 000 person-years; HR: 1.18; 95% CI, 0.95-1.47). The risk was significantly increased among those who had received seven or more prescriptions and ≥25 pills (HR: 1.30 [95% CI, 1.01-1.69] and 1.34 [95% CI, 1.04-1.72], respectively). In contrast, there was no overall association with basal and squamous cell carcinoma, with an unclear association with numbers of prescriptions and pills received. CONCLUSIONS: The use of PDE5-Is was not associated with an overall increased risk of melanoma skin cancer. The increased risks observed in the highest prescription and pill categories require further validation. PATIENT SUMMARY: In this study, the use of phosphodiesterase type 5 inhibitors was not associated with an increased risk of melanoma skin cancer.

Statistical power in parallel group point exposure studies with time-to-event outcomes: an empirical comparison of the performance of randomized controlled trials and the inverse probability of treatment weighting (IPTW) approach.

BACKGROUND: Estimating statistical power is an important component of the design of both randomized controlled trials (RCTs) and observational studies. Methods for estimating statistical power in RCTs have been well described and can be implemented simply. In observational studies, statistical methods must be used to remove the effects of confounding that can occur due to non-random treatment assignment. Inverse probability of treatment weighting (IPTW) using the propensity score is an attractive method for estimating the effects of treatment using observational data. However, sample size and power calculations have not been adequately described for these methods. METHODS: We used an extensive series of Monte Carlo simulations to compare the statistical power of an IPTW analysis of an observational study with time-to-event outcomes with that of an analysis of a similarly-structured RCT. We examined the impact of four factors on the statistical power function: number of observed events, prevalence of treatment, the marginal hazard ratio, and the strength of the treatment-selection process. RESULTS: We found that, on average, an IPTW analysis had lower statistical power compared to an analysis of a similarly-structured RCT. The difference in statistical power increased as the magnitude of the treatment-selection model increased. CONCLUSIONS: The statistical power of an IPTW analysis tended to be lower than the statistical power of a similarly-structured RCT.

Simple Estimation of Patient-Oriented Effects From Randomized Trials: An Open and Shut CACE.

In randomized controlled trials, the intention-to-treat estimator provides an unbiased estimate of the causal effect of treatment assignment on the outcome. However, patients often want to know what the effect would be if they were to take the treatment as prescribed (the patient-oriented effect), and several researchers have suggested that the more relevant causal effect for this question is the complier average causal effect (CACE), also referred to as the local average treatment effect. Sophisticated approaches to estimating the CACE include Bayesian and frequentist methods for principal stratification, inverse-probability-of-treatment-weighted estimators, and instrumental-variable (IV) analysis. All of these approaches exploit information about adherence to assigned treatment to improve upon the intention-to-treat estimator, but they are rarely used in practice, probably because of their complexity. The IV principal stratification estimator is simple to implement but has had limited use in practice, possibly due to lack of familiarity. Here, we show that the IV principal stratification estimator is a modified per-protocol estimator that should be obtainable from any randomized controlled trial, and we provide a closed form for its robust variance (and its uncertainty). Finally, we illustrate sensitivity analyses we conducted to assess inference in light of potential violations of the exclusion restriction assumption.

Contour plot assessment of existing meta-analyses confirms robust association of statin use and acute kidney injury risk.

OBJECTIVES: Robustness of an existing meta-analysis can justify decisions on whether to conduct an additional study addressing the same research question. We illustrate the graphical assessment of the potential impact of an additional study on an existing meta-analysis using published data on statin use and the risk of acute kidney injury. STUDY DESIGN AND SETTING: A previously proposed graphical augmentation approach is used to assess the sensitivity of the current test and heterogeneity statistics extracted from existing meta-analysis data. In addition, we extended the graphical augmentation approach to assess potential changes in the pooled effect estimate after updating a current meta-analysis and applied the three graphical contour definitions to data from meta-analyses on statin use and acute kidney injury risk. RESULTS: In the considered example data, the pooled effect estimates and heterogeneity indices demonstrated to be considerably robust to the addition of a future study. Supportingly, for some previously inconclusive meta-analyses, a study update might yield statistically significant kidney injury risk increase associated with higher statin exposure. CONCLUSIONS: The illustrated contour approach should become a standard tool for the assessment of the robustness of meta-analyses. It can guide decisions on whether to conduct additional studies addressing a relevant research question.

Improving blood pressure control through pharmacist interventions: a meta-analysis of randomized controlled trials.

BACKGROUND: Control of blood pressure (BP) remains a major challenge in primary care. Innovative interventions to improve BP control are therefore needed. By updating and combining data from 2 previous systematic reviews, we assess the effect of pharmacist interventions on BP and identify potential determinants of heterogeneity. METHODS AND RESULTS: Randomized controlled trials (RCTs) assessing the effect of pharmacist interventions on BP among outpatients with or without diabetes were identified from MEDLINE, EMBASE, CINAHL, and CENTRAL databases. Weighted mean differences in BP were estimated using random effect models. Prediction intervals (PI) were computed to better express uncertainties in the effect estimates. Thirty-nine RCTs were included with 14 224 patients. Pharmacist interventions mainly included patient education, feedback to physician, and medication management. Compared with usual care, pharmacist interventions showed greater reduction in systolic BP (-7.6 mm Hg, 95% CI: -9.0 to -6.3; I(2)=67%) and diastolic BP (-3.9 mm Hg, 95% CI: -5.1 to -2.8; I(2)=83%). The 95% PI ranged from -13.9 to -1.4 mm Hg for systolic BP and from -9.9 to +2.0 mm Hg for diastolic BP. The effect tended to be larger if the intervention was led by the pharmacist and was done at least monthly. CONCLUSIONS: Pharmacist interventions - alone or in collaboration with other healthcare professionals - improved BP management. Nevertheless, pharmacist interventions had differential effects on BP, from very large to modest or no effect; and determinants of heterogeneity could not be identified. Determining the most efficient, cost-effective, and least time-consuming intervention should be addressed with further research.

Do population-based interventions widen or narrow socioeconomic inequalities? The case of breastfeeding promotion.

BACKGROUND: Despite numerous population-based randomized intervention trials, the impact of such interventions on socioeconomic inequalities has rarely been examined. We used data from a large cluster-randomized trial to assess the impact of a breastfeeding promotion intervention on socioeconomic inequalities in breastfeeding (exclusivity and duration) and in child cognitive ability at early school age. METHODS: The Promotion of Breastfeeding Intervention Trial (PROBIT) randomized 31 Belarusian maternity hospitals and their affiliated polyclinics either to receive a breastfeeding promotion intervention modelled on the WHO/UNICEF Baby-Friendly Hospital Initiative or to continue the standard practices in effect at the time of randomization. We estimated and compared inequalities in discontinuation of exclusive breastfeeding before 3 months and of any breastfeeding before 12 months and in child verbal IQ at age 6.5 years, across maternal education strata between the two intervention arms. FINDINGS: Socioeconomic inequalities in discontinuing exclusive breastfeeding before 3 months were negligible in the control group. However, graded inequalities by maternal education emerged in the intervention group {relative risk [RR] = 1.12 [95% confidence interval (CI): 1.04, 1.20] for partial university and RR = 1.20 [95% CI: 1.11, 1.31] for secondary education or less vs complete university; risk difference [RD] = 0.06 [95% CI: 0.03, 0.09] and 0.10 [95% CI: 0.06, 0.14], respectively}. For discontinuing any breastfeeding before 12 months, small socioeconomic gradients in the control group were widened in the intervention group (RR = 1.04 and 1.16, respectively, for mothers with secondary education or less). Despite these differential effects on breastfeeding, however, we observed a small, nonsignificant reduction in socioeconomic inequalities in child verbal IQ at age 6.5 years. CONCLUSIONS: A population-based intervention to promote breastfeeding slightly widened socioeconomic inequalities in breastfeeding but not those in child cognitive ability.

Maternal vitamin D status and the risk of mild and severe preeclampsia.

BACKGROUND: We sought to determine the association between maternal vitamin D status at ≤26 weeks' gestation and the risk of preeclampsia by clinical subtype. METHODS: We conducted a case-cohort study among women enrolled at 12 US sites from 1959 to 1966 in the Collaborative Perinatal Project. In serum collected at ≤26 weeks' gestation (median 20.9 weeks) from 717 women who later developed preeclampsia (560 mild and 157 severe cases) and from 2986 mothers without preeclampsia, we measured serum 25-hydroxyvitamin D, over 40 years later, using liquid chromatography-tandem mass spectrometry. RESULTS: Half of women in the subcohort had 25-hydroxyvitamin D (25(OH)D) >50 nmol/L. Maternal 25(OH)D 50 to 74.9 nmol/L was associated with a reduction in the absolute and relative risk of preeclampsia and mild preeclampsia compared with 25(OH)D <30 nmol/L in the crude analysis but not after adjustment for confounders, including race, prepregnancy body mass index, and parity. For severe preeclampsia, 25(OH)D ≥50 nmol/L was associated with a reduction in three cases per 1000 pregnancies (adjusted risk difference = -0.003 [95% confidence interval = -0.005 to 0.0002]) and a 40% reduction in risk (0.65 [0.43 to 0.98]) compared with 25(OH)D <50 nmol/L. Conclusions were unchanged (1) after restricting to women with 25(OH)D measured before 22 weeks' gestation or (2) with formal sensitivity analyses for unmeasured confounding. CONCLUSIONS: Maternal vitamin D deficiency may be a risk factor for severe preeclampsia but not for its mild subtypes. Contemporary cohorts with large numbers of severe preeclampsia cases would be needed to confirm or refute these findings.

A weight-gain-for-gestational-age z score chart for the assessment of maternal weight gain in pregnancy.

BACKGROUND: To establish the unbiased relation between maternal weight gain in pregnancy and perinatal health, a classification for maternal weight gain is needed that is uncorrelated with gestational age. OBJECTIVE: The goal of this study was to create a weight-gain-for-gestational-age percentile and z score chart to describe the mean, SD, and selected percentiles of maternal weight gain throughout pregnancy in a contemporary cohort of US women. DESIGN: The study population was drawn from normal-weight women with uncomplicated, singleton pregnancies who delivered at the Magee-Womens Hospital in Pittsburgh, PA, 1998-2008. Analyses were based on a randomly selected subset of 648 women for whom serial prenatal weight measurements were available through medical chart record abstraction (6727 weight measurements). RESULTS: The pattern of maternal weight gain throughout gestation was estimated by using a random-effects regression model. The estimates were used to create a chart with the smoothed means, percentiles, and SDs of gestational weight gain for each week of pregnancy. CONCLUSION: This chart allows researchers to express total weight gain as an age-standardized z score, which can be used in epidemiologic analyses to study the association between pregnancy weight gain and adverse or physiologic pregnancy outcomes independent of gestational age.

The consequences of foreclosure for depressive symptomatology.

PURPOSE: We tested whether experiencing the stressful event of a home mortgage foreclosure was associated with depressive symptomatology. METHODS: Data derive from a cohort study of 662 new mothers in the Life-course Influences on Fetal Environment (LIFE) Study. Eligibility included black/African-American mothers, ages 18 to 45 years, who had just given birth to a singleton baby. Mothers enrolled June 2009 to December 2010 were interviewed immediately after giving birth. Our outcome measure was depressive symptoms based on the Center for Epidemiologic Studies-Depression Scale, dichotomized to measure severe depressive symptomatology during the week prior to the interview. RESULTS: A total of 8% of the sample experienced foreclosure in the past 2 years. Covariate-adjusted Poisson regression models showed that women experiencing a recent foreclosure had 1.76 times greater risk for severe depressive symptoms during the week prior to birth compared to women not experiencing foreclosure (95% confidence interval 1.25-2.47, p = .001); foreclosure was also associated with higher excess absolute risk for depressive symptoms (adjusted risk difference 0.173, 95% confidence interval 0.044-0.301, p = .008). CONCLUSIONS: Women who have recently experienced foreclosure are at risk for severe depressive symptoms. The mental health needs of pregnant women experiencing foreclosure or other housing stressors should be considered in clinical practice.

A simulation study of finite-sample properties of marginal structural Cox proportional hazards models.

Motivated by a previously published study of HIV treatment, we simulated data subject to time-varying confounding affected by prior treatment to examine some finite-sample properties of marginal structural Cox proportional hazards models. We compared (a) unadjusted, (b) regression-adjusted, (c) unstabilized, and (d) stabilized marginal structural (inverse probability-of-treatment [IPT] weighted) model estimators of effect in terms of bias, standard error, root mean squared error (MSE), and 95% confidence limit coverage over a range of research scenarios, including relatively small sample sizes and 10 study assessments. In the base-case scenario resembling the motivating example, where the true hazard ratio was 0.5, both IPT-weighted analyses were unbiased, whereas crude and adjusted analyses showed substantial bias towards and across the null. Stabilized IPT-weighted analyses remained unbiased across a range of scenarios, including relatively small sample size; however, the standard error was generally smaller in crude and adjusted models. In many cases, unstabilized weighted analysis showed a substantial increase in standard error compared with other approaches. Root MSE was smallest in the IPT-weighted analyses for the base-case scenario. In situations where time-varying confounding affected by prior treatment was absent, IPT-weighted analyses were less precise and therefore had greater root MSE compared with adjusted analyses. The 95% confidence limit coverage was close to nominal for all stabilized IPT-weighted but poor in crude, adjusted, and unstabilized IPT-weighted analysis. Under realistic scenarios, marginal structural Cox proportional hazards models performed according to expectations based on large-sample theory and provided accurate estimates of the hazard ratio.

Educational inequalities in preterm and term small-for-gestational-age birth over time.

PURPOSE: Time trends in educational inequalities in small-for-gestational-age (SGA) birth are important to evaluate for policy, especially at preterm gestational ages when morbidity and mortality are typically greater. We evaluated educational inequalities in preterm and term SGA birth over time, accounting for potential bias at preterm gestational ages. METHODS: Data included 2,204,056 singleton live births from 25 to 43 gestational weeks, 1981 to 2007. We estimated prevalence ratios (PR) and percent prevalence differences (PPD) of preterm and term SGA birth for a continuous education score, accounting for maternal characteristics. Sensitivity analyses included correction for misclassification of preterm SGA status, and use of fetuses-at-risk denominators in regression models. RESULTS: Although prevalence of SGA birth decreased over time, relative educational inequalities (PRs) persisted for preterm and term cases. PPDs decreased slightly, but more for term than preterm SGA birth. Sensitivity analyses indicated that PRs for education were stronger for preterm than term SGA birth. PPDs were larger for term SGA birth in the first period, but greater for preterm SGA birth in the last period. CONCLUSIONS: Relative educational inequalities in SGA birth persisted over time. The difference in prevalence between the least and most educated mothers is currently greater for preterm than for term SGA birth.