Toward a Clearer Definition of Selection Bias When Estimating Causal Effects

Influence of High-Altitude Residential History on Optimal HbA1c Cutoff for Detecting Abnormal Glucose Metabolism

Aims: To explore the influence of recent high-altitude residential history on the optimal cutoff of glycosylated hemoglobin (HbA1c) for detecting abnormal glucose metabolism. Methods: The study included 505 self-reported healthy Han participants of age 18-65 years, recruited in Chengdu and categorized based on recent (within 3 months) high-altitude (>2,500 m) residential history. The 1999 WHO criteria was used as the gold standard for defining prediabetes and diabetes. HbA1c test performance was assessed using receiver operating characteristic curve, with the optimal cutoff determined by Maximum Youden index. Propensity score matching with 0.02 calipers and nearest neighbor method was used to balance confounding factors between groups. Results: Of the participants, 238 (47.13%) were populations with recent high-altitude residential history (HA group), and 267 (52.87%) were low-altitude dwellers (LA group). The HA group had slightly higher HbA1c levels (p > 0.05) and higher erythrocyte and hemoglobin levels (p < 0.05), compared to the LA group. Weak correlations between prediabetes and HbA1c levels were observed in the HA group (rs = 0.21, p < 0.05) and the LA group (rs = 0.07, p = 0.25). The optimal cutoff for the detection of diabetes was 6.5% (area under the curve [AUC] 0.94) in the HA group and 5.9% (AUC 0.97) in the LA group, which remained unchanged after adjustment for confounders. Conclusions: The optimal cutoff of HbA1c for the detection of diabetes in populations with recent history of living at high altitude was higher than that in general populations living at low altitude, and the diagnostic value of HbA1c for prediabetes was also inadequate.

Use of transportability methods for real-world evidence generation: a review of current applications

Aim: To evaluate how transportability methods are currently used for real-world evidence (RWE) generation to inform good practices and support adoption and acceptance of these methods in the RWE context. Methods: We conducted a targeted literature review to identify studies that transported an effect estimate of the clinical effectiveness or safety of a biomedical exposure to a target real-world population. Records were identified from PubMed-indexed articles published any time before 25 July 2023 (inclusive). Two reviewers screened abstracts/titles and reviewed the full text of candidate studies to identify the final set of articles. Data on the therapeutic area, exposure(s), outcome(s), original and target populations and details of the transportability analysis (e.g., analytic method used, estimate transported, stated assumptions) were abstracted from each article. Results: Of 458 unique records identified, six were retained in the final review. Articles were published during 2021-2023, focused on the US/Canada context, and covered a range of therapeutic areas. Four studies transported an RCT effect estimate, while two transported effect estimates derived from real-world data. Almost all articles used weighting methods to transport estimates. Two studies discussed all transportability assumptions, and one evaluated the likelihood of meeting all assumptions and the impact of potential violations. Conclusion: The use of transportability methods for RWE generation is an emerging and promising area of research to address evidence gaps in settings with limited data and infrastructure. More transparent and rigorous reporting of methods, assumptions and limitations may increase the use and acceptability of transportability for producing robust evidence on treatment effectiveness and safety.

Core Concepts in Pharmacoepidemiology: Quantitative Bias Analysis

Pharmacoepidemiological studies provide important information on the safety and effectiveness of medications, but the validity of study findings can be threatened by residual bias. Ideally, biases would be minimized through appropriate study design and statistical analysis methods. However, residual biases can remain, for example, due to unmeasured confounders, measurement error, or selection into the study. A group of sensitivity analysis methods, termed quantitative bias analyses, are available to assess, quantitatively and transparently, the robustness of study results to these residual biases. These approaches include methods to quantify how the estimated effect would be altered under specified assumptions about the potential bias, and methods to calculate bounds on effect estimates. This article introduces quantitative bias analyses for unmeasured confounding, misclassification, and selection bias, with a focus on their relevance and application to pharmacoepidemiological studies.

How to develop causal directed acyclic graphs for observational health research: a scoping review

Causal directed acyclic graphs (DAGs) serve as intuitive tools to visually represent causal relationships between variables. While they find widespread use in guiding study design, data collection and statistical analysis, their adoption remains relatively rare in the domain of psychology. In this paper we describe the relevance of DAGs for health psychology, review guidelines for developing causal DAGs, and offer recommendations for their development. A scoping review searching for papers and resources describing guidelines for DAG development was conducted. Information extracted from the eligible papers and resources (n = 11) was categorised, and results were used to formulate recommendations. Most records focused on DAG development for data analysis, with similar steps outlined. However, we found notable variations on how to implement confounding variables (i.e., sequential inclusion versus exclusion). Also, how domain knowledge should be integrated in the development process was scarcely addressed. Only one paper described how to perform a literature search for DAG development. Key recommendations for causal DAG development are provided and discussed using an illustrative example.

Lactated Ringer vs Normal Saline Solution During Sickle Cell Vaso-Occlusive Episodes

Importance

Sickle cell disease (SCD), a clinically heterogenous genetic hemoglobinopathy, is characterized by painful vaso-occlusive episodes (VOEs) that can require hospitalization. Patients admitted with VOEs are often initially resuscitated with normal saline (NS) to improve concurrent hypovolemia, despite preclinical evidence that NS may promote erythrocyte sickling. The comparative effectiveness of alternative volume-expanding fluids (eg, lactated Ringer [LR]) for resuscitation during VOEs is unclear.

Objective

To compare the effectiveness of LR to NS fluid resuscitation in patients with SCD and VOEs.

Design, Setting, and Participants

This multicenter cohort study and target trial emulation included inpatient adults with SCD VOEs who received either LR or NS on hospital day 1. The Premier PINC AI database (2016-2022), a multicenter clinical database including approximately 25% of US hospitalizations was used. The analysis took place between October 6, 2023, and June 20, 2024.

Exposure

Receipt of LR (intervention) or NS (control) on hospital day 1.

Main Outcome and Measures

The primary outcome was hospital-free days (HFDs) by day 30. Targeted maximum likelihood estimation was used to calculate marginal effect estimates. Heterogeneity of treatment effect was explored in subgroups.

Results

A total of 55 574 patient encounters where LR (n = 3495) or NS (n = 52 079) was administered on hospital day 1 were included; the median (IQR) age was 30 (25-37) years. Patients who received LR had more HFDs compared with those who received NS (marginal mean difference, 0.4; 95% CI, 0.1-0.6 days). Patients who received LR also had shorter hospital lengths of stay (marginal mean difference, -0.4; 95% CI, -0.7 to -0.1 days) and lower risk of 30-day readmission (marginal risk difference, -5.8%; 95% CI, -9.8% to -1.8%). Differences in HFDs between LR and NS were heterogenous based on fluid volume received: among patients who received less than 2 L, there was no difference in LR vs NS; among those who received 2 or more L, LR was superior to NS.

Conclusion and Relevance

This cohort study found that, compared with NS, LR had a small but significant improvement in HFDs and secondary outcomes including 30-day readmission. These results suggest that, among patients with VOEs in whom clinicians plan to give volume resuscitation fluids on hospital admission, LR should be preferred over NS.

Gaps in the usage and reporting of multiple imputation for incomplete data: findings from a scoping review of observational studies addressing causal questions

BACKGROUND

Missing data are common in observational studies and often occur in several of the variables required when estimating a causal effect, i.e. the exposure, outcome and/or variables used to control for confounding. Analyses involving multiple incomplete variables are not as straightforward as analyses with a single incomplete variable. For example, in the context of multivariable missingness, the standard missing data assumptions ("missing completely at random", "missing at random" [MAR], "missing not at random") are difficult to interpret and assess. It is not clear how the complexities that arise due to multivariable missingness are being addressed in practice. The aim of this study was to review how missing data are managed and reported in observational studies that use multiple imputation (MI) for causal effect estimation, with a particular focus on missing data summaries, missing data assumptions, primary and sensitivity analyses, and MI implementation.

METHODS

We searched five top general epidemiology journals for observational studies that aimed to answer a causal research question and used MI, published between January 2019 and December 2021. Article screening and data extraction were performed systematically.

RESULTS

Of the 130 studies included in this review, 108 (83%) derived an analysis sample by excluding individuals with missing data in specific variables (e.g., outcome) and 114 (88%) had multivariable missingness within the analysis sample. Forty-four (34%) studies provided a statement about missing data assumptions, 35 of which stated the MAR assumption, but only 11/44 (25%) studies provided a justification for these assumptions. The number of imputations, MI method and MI software were generally well-reported (71%, 75% and 88% of studies, respectively), while aspects of the imputation model specification were not clear for more than half of the studies. A secondary analysis that used a different approach to handle the missing data was conducted in 69/130 (53%) studies. Of these 69 studies, 68 (99%) lacked a clear justification for the secondary analysis.

CONCLUSION

Effort is needed to clarify the rationale for and improve the reporting of MI for estimation of causal effects from observational data. We encourage greater transparency in making and reporting analytical decisions related to missing data.

Sociocultural and masculinity influences on colorectal cancer screening participation among Hispanic/Latino men in Florida, New York, and Texas

BACKGROUND

This cross-sectional study explored how masculinity beliefs may influence colorectal cancer (CRC) screening participation among ethnic subgroups of screening-age-eligible (45-75 years) Hispanic/Latino men.

METHODS

Using a consumer panel, we recruited self-identified Hispanic/Latino men fluent in English or Spanish, and residing in Florida, New York, or Texas. The Masculinity Barriers to Medical Care (MBMC) scale and its six subscales were used to assess masculinity beliefs. Multivariable logistic regression was used to estimate the association between MBMC and CRC screening participation, adjusting for Hispanic/Latino subgroup, marital status, survey language, age group, and health insurance status. Results were then stratified by Hispanic/Latino subgroup.

RESULTS

Of the participants (n=611), approximately 31% identified as Puerto Rican, 30% as other Hispanic/Latino, 26% as Mexican, and 14% as Cuban; 63% had ever been screened for CRC. We found no differences in the prevalence of screening participation by Hispanic/Latino subgroup. The majority of participants had completed both a stool-based test and an exam-based screening test (29.3%). After adjusting for confounding, MBMC reduced the odds of screening participation. Slight MBMC-subscale differences were observed by Hispanic/Latino subgroup. For example, higher scores on the Restrictive Emotionality subscale were associated with a lower likelihood of screening participation among Puerto Rican men, but higher odds of screening for Cuban men.

CONCLUSIONS

Masculinity barriers to CRC screening may exist. Tailored interventions to address masculinity barriers among specific Latino subgroups may improve CRC screening uptake in this population.

Older adults' compliance with mobile ecological momentary assessments in behavioral nutrition and physical activity research: pooled results of four intensive longitudinal studies and recommendations for future research

BACKGROUND

Mobile Ecological Momentary Assessment (EMA) is increasingly used to gather intensive, longitudinal data on behavioral nutrition, physical activity and sedentary behavior and their underlying determinants. However, a relevant concern is the risk of non-random non-compliance with mobile EMA protocols, especially in older adults. This study aimed to examine older adults' compliance with mobile EMA in health behavior studies according to participant characteristics, and prompt timing, and to provide recommendations for future EMA research.

METHODS

Data of four intensive longitudinal observational studies employing mobile EMA to understand health behavior, involving 271 community-dwelling older adults (M = 71.8 years, SD = 6.8; 52% female) in Flanders, were pooled. EMA questionnaires were prompted by a smartphone application during specific time slots or events. Data on compliance (i.e. information whether a participant answered at least one item following the prompt), time slot (morning, afternoon or evening) and day (week or weekend day) of each prompt were extracted from the EMA applications. Participant characteristics, including demographics, body mass index, and smartphone ownership, were collected via self-report. Descriptive statistics of compliance were computed, and logistic mixed models were run to examine inter- and intrapersonal variability in compliance.

RESULTS

EMA compliance averaged 77.5%, varying from 70.0 to 86.1% across studies. Compliance differed among subgroups and throughout the day. Age was associated with lower compliance (OR = 0.96, 95%CI = 0.93-0.99), while marital/cohabiting status and smartphone ownership were associated with higher compliance (OR = 1.83, 95%CI = 1.21-2.77, and OR = 4.43, 95%CI = 2.22-8.83, respectively). Compliance was lower in the evening than in the morning (OR = 0.82, 95%CI = 0.69-0.97), indicating non-random patterns that could impact study validity.

CONCLUSIONS

The findings of this study shed light on the complexities surrounding compliance with mobile EMA protocols among older adults in health behavior studies. Our analysis revealed that non-compliance within our pooled dataset was not completely random. This non-randomness could introduce bias into study findings, potentially compromising the validity of research findings. To address these challenges, we recommend adopting tailored approaches that take into account individual characteristics and temporal dynamics. Additionally, the utilization of Directed Acyclic Graphs, and advanced statistical techniques can help mitigate the impact of non-compliance on study validity.

The associations between religious/spiritual beliefs and behaviours and study participation in a prospective cohort study (ALSPAC) in Southwest England

Background

Longitudinal studies are key to understanding risk factors for health, well-being, and disease, yet associations may be biased if study invitation and participation are non-random. Religious/spiritual beliefs and behaviours (RSBB) are increasingly recognised as having potentially important relationships with health. However, it is unclear whether RSBB is associated with study participation. We examine whether RSBB is associated with participation in the longitudinal birth cohort ALSPAC (Avon Longitudinal Study of Parents and Children).

Methods

Three RSBB factors were used: religious belief (belief in God/a divine power; yes/not sure/no), religious affiliation (Christian/none/other), and religious attendance (frequency of attendance at a place of worship). Participation was measured in three ways: i) total number of questionnaires/clinics completed (linear and ordinal models); ii) completion of the most recent questionnaire (logistic model); and iii) length of participation (survival model). Analyses were repeated for the ALSPAC mothers, their partners, and the study children, and were adjusted for relevant socio-demographic confounders.

Results

Religious attendance was positively associated with participation in all adjusted models in all three cohorts. For example, study mothers who attended a place of worship at least once a month on average completed two more questionnaires (out of a possible 50), had 50% greater odds of having completed the most recent questionnaire, and had 25% reduced risk of drop-out, relative to those who did not attend. In the adjusted analyses, religious belief and attendance were not associated with participation. However, the majority of unadjusted models showed associations between RSBB and participation.

Conclusion

After adjusting for confounders, religious attendance - not religious belief or affiliation - was associated with participation in ALSPAC. These results indicate that use of RSBB variables (and religious attendance in particular) may result in selection bias and spurious associations; these potential biases should be explored and discussed in future studies using these data.

To weight or not to weight? The effect of selection bias in 3 large electronic health record-linked biobanks and recommendations for practice

OBJECTIVES

To develop recommendations regarding the use of weights to reduce selection bias for commonly performed analyses using electronic health record (EHR)-linked biobank data.

MATERIALS AND METHODS

We mapped diagnosis (ICD code) data to standardized phecodes from 3 EHR-linked biobanks with varying recruitment strategies: All of Us (AOU; n = 244 071), Michigan Genomics Initiative (MGI; n = 81 243), and UK Biobank (UKB; n = 401 167). Using 2019 National Health Interview Survey data, we constructed selection weights for AOU and MGI to represent the US adult population more. We used weights previously developed for UKB to represent the UKB-eligible population. We conducted 4 common analyses comparing unweighted and weighted results.

RESULTS

For AOU and MGI, estimated phecode prevalences decreased after weighting (weighted-unweighted median phecode prevalence ratio [MPR]: 0.82 and 0.61), while UKB estimates increased (MPR: 1.06). Weighting minimally impacted latent phenome dimensionality estimation. Comparing weighted versus unweighted phenome-wide association study for colorectal cancer, the strongest associations remained unaltered, with considerable overlap in significant hits. Weighting affected the estimated log-odds ratio for sex and colorectal cancer to align more closely with national registry-based estimates.

DISCUSSION

Weighting had a limited impact on dimensionality estimation and large-scale hypothesis testing but impacted prevalence and association estimation. When interested in estimating effect size, specific signals from untargeted association analyses should be followed up by weighted analysis.

CONCLUSION

EHR-linked biobanks should report recruitment and selection mechanisms and provide selection weights with defined target populations. Researchers should consider their intended estimands, specify source and target populations, and weight EHR-linked biobank analyses accordingly.

Effectiveness of integrase strand transfer inhibitors among treatment-naive people living with HIV/AIDS in Guangdong, China: A real-world, retrospective cohort study

Integrase strand transfer inhibitors (INSTIs) in anti-retroviral therapy (ART) have been recommended by the World Health Organization for their higher efficacy, favorable safety and tolerability. However, the clinical evidence supporting switching to INSTI-containing regimens in low-and-middle-income countries (LMICs) is limited, as few patients have access to these regimens. We aimed to assess the effectiveness of INSTI-containing regimens in real-world settings in China compared to government-provided free ART. We compared the short-term (first 4 mo following ART initiation) and long-term (1 year after ART initiation) effectiveness between INSTI-containing regimens and free ART drugs provided by the Chinese government in 4 dimensions: viral suppression status, immune response, liver and kidney function, and AIDS-related diseases. We obtained data from electronic medical records in the National Infectious Disease Surveillance System. To control baseline confounders, we used propensity score matching (PSM), calculated using logistic regression including socio-demographic and baseline factors. Among 12,836 patients from 2012 to 2019, 673 (5.2%) used INSTI-containing regimens. Patients with INSTI-containing regimens were matched to those with free drugs (644 vs 644). For short-term effectiveness, patients initiating INSTI-containing regimens were more likely to achieve viral suppression (81.4% vs 52.0%; P < .001). The differences in immune response, liver and kidney function and AIDS-related diseases were not significant between the 2 groups. For long-term effectiveness, viral suppression rates were similar (87.96% vs 84.59%; P = .135), with no significant differences in immune response, liver and kidney function, or AIDS-related diseases. Our study suggests that patients initiating ART with INSTI-containing regimens have worse physical status at baseline than patients starting with free ART drugs. Furthermore, we found better virological performances of INSTI-containing regimens in the short-term but not in the long-term due to a high rate of drug changes. Our findings have clinical implications and provide new evidence regarding the effectiveness of INSTI-containing regimens in LMICs.

Causal Inference Challenges in the Relationship Between Social Determinants and Cardiovascular Outcomes

The effects of social determinants on cardiovascular outcomes are frequently estimated in epidemiologic analyses, but the profound causal and statistical challenges of this research program are not widely discussed. Here, we carefully review definitions and measures for social determinants of cardiovascular health and then examine the various assumptions required for valid causal inference in multivariable analyses of observational data, such as what one would typically encounter in cohorts, population surveys, health care databases, and vital statistics databases. We explain the necessity of the "well-defined exposure" and show how this goal relates to the "consistency assumption" that is necessary for valid causal inference. Well-defined exposure is especially challenging for social determinants of health because they are seldom simple atomistic interventions that are easily conceptualized and measured. We then review threats to valid inference that arise from confounding, selection bias, information bias, and positivity violations. Other causal considerations are reviewed and explained, such as correct model specification, absence of immortal time, and avoidance of the "Table 2 Fallacy," and their application to social determinants of cardiovascular outcomes are discussed. Fruitful approaches, including focusing on policy interventions and the "target trial" frameworks are proposed and provide a pathway for a more efficacious research program that can more reliably improve population health. Valid causal inference in this setting is quite challenging, but-with clever design and thoughtful analysis-the important role of social factors in patterning cardiovascular outcomes can be quantified and reported.

Local retail food environment exposure and diet quality in rural and urban adults: A longitudinal analysis of the ORISCAV-LUX cohort study

Despite growing interest in understanding how food environments shape dietary behaviors, European longitudinal evidence is scarce. We aimed to investigate the associations of 9-year average and change in exposure to local retail food environments with the diet quality of residents in Luxembourg. We used data from 566 adults enrolled in both waves of the nationwide ORISCAV-LUX study (2007-2017). Dietary quality was assessed by the Diet Quality Index-International (DQI-I). Exposure to "healthy" and "less healthy" food outlets was assessed by both absolute and relative GIS-based measurements. The results showed a 56.3% increase in less healthy food outlets over the period. In adjusted linear mixed models, high (vs. low) 9-year average exposure to less healthy food outlets was associated with lower DQI-I, when examining spatial access (β = -1.25, 95% CI: -2.29, -0.22) and proportions (β = -1.24, 95% CI: -2.15, -0.33). Stratified analyses showed these associations to be significant only among urban residents. There was no association between change in exposure to less healthy food outlets and DQI-I. Increased exposure to healthy outlets in rural areas, using absolute measurements, was associated with worsened DQI-I. Neighborhood socioeconomic status did not moderate the above associations. Findings suggest that the proliferation of less healthy food outlets may have contributed to the deterioration of the diet quality of urban residents, and support the use of relative measurements to fully capture the healthiness of food environments.

Reweighting UK Biobank corrects for pervasive selection bias due to volunteering

BACKGROUND

Biobanks typically rely on volunteer-based sampling. This results in large samples (power) at the cost of representativeness (bias). The problem of volunteer bias is debated. Here, we (i) show that volunteering biases associations in UK Biobank (UKB) and (ii) estimate inverse probability (IP) weights that correct for volunteer bias in UKB.

METHODS

Drawing on UK Census data, we constructed a subsample representative of UKB's target population, which consists of all individuals invited to participate. Based on demographic variables shared between the UK Census and UKB, we estimated IP weights (IPWs) for each UKB participant. We compared 21 weighted and unweighted bivariate associations between these demographic variables to assess volunteer bias.

RESULTS

Volunteer bias in all associations, as naively estimated in UKB, was substantial-in some cases so severe that unweighted estimates had the opposite sign of the association in the target population. For example, older individuals in UKB reported being in better health, in contrast to evidence from the UK Census. Using IPWs in weighted regressions reduced 87% of volunteer bias on average. Volunteer-based sampling reduced the effective sample size of UKB substantially, to 32% of its original size.

CONCLUSIONS

Estimates from large-scale biobanks may be misleading due to volunteer bias. We recommend IP weighting to correct for such bias. To aid in the construction of the next generation of biobanks, we provide suggestions on how to best ensure representativeness in a volunteer-based design. For UKB, IPWs have been made available.

Impact of dental visiting patterns on oral health: A systematic review of longitudinal studies

AIM

To systematically review longitudinal studies investigating the impact of dental visiting patterns on oral health across the life course.

METHODS

Five databases (MEDLINE, Embase, Scopus, Web of Science, CINAHL) were searched up to March 2023. Results were screened based on eligibility criteria in a two-stage process: title and abstract, and full-text review. A backward search of reference lists and a forward search of citations of the included papers was also conducted. The quality of the included papers was assessed using the Newcastle-Ottawa Scale. Key study information was extracted and a narrative synthesis of the findings was performed.

RESULTS

Eleven papers from five longitudinal studies in five countries (Australia, Brazil, China, New Zealand, Sweden) met the inclusion criteria. Studies of moderate to high quality consistently reported that regular dental attendance was associated with having less dental caries experience, fewer missing teeth and better oral health-related quality of life. Inconsistent findings were observed for decayed teeth, and no association was found for periodontal condition.

CONCLUSIONS

This review highlights an association between regular dental visiting pattern and improved oral health, notably less dental caries experience and better oral health-related quality of life. Dental attendance emerges as an important predictor of oral health across the life course, underscoring the importance of routine dental care.

REGISTRATION INFORMATION

The PROSPERO registration number is CRD42023396380.

Toxoplasma gondii seropositivity and cognitive functioning in older adults: an analysis of cross-sectional data of the National Health and Nutrition Examination Survey 2011-2014

OBJECTIVES

This study sought to examine the relationship between Toxoplasma gondii seropositivity and cognitive function in older adults.

DESIGN

An observational cross-sectional study.

SETTING

The National Health and Nutrition Examination Survey (NHANES) study took place at participants' homes and mobile examination centres.

PARTICIPANTS

A total of 2956 older adults aged 60 and above from the NHANES from 2011 to 2014 were included in the study. Exposure of interest: participants had serum Toxoplasma gondii antibody analysed in the laboratory. A value>33 IU/mL was categorised as seropositive for Toxoplasma gondii infection; <27 IU/mL was categorised as seronegative for Toxoplasma gondii infection.

PRIMARY AND SECONDARY OUTCOME MEASURES

Cognitive tests included the Consortium to Establish a Registry for Alzheimer's Disease Word Learning subtest (CERAD-WL) for immediate and delayed memory, the Animal Fluency Test (AFT), and the Digit Symbol Substitution Test (DSST).

RESULTS

About half of the 2956 participants (mean age 70.0) were female (51.0%), non-Hispanic White (48.3%), and completed some college or above (48.3%). A total of 703 participants were positive for Toxoplasma gondii infection (23.8%). Adjusted linear regression showed that compared with participants with negative Toxoplasma gondii infection, those with positive Toxoplasma gondii infection had lower CERAD-WL immediate memory (beta (β) -0.16, 95% CI -0.25 to -0.07), CERAD-WL delayed memory (β -0.15, 95% CI -0.24 to -0.06), AFT (β -0.15, 95% CI -0.24 to -0.06), DSST (β -0.34, 95% CI -0.43 to -0.26), and global cognition (β -0.24, 95% CI -0.32 to -0.16) z-scores after controlling for the covariates.

CONCLUSIONS

Toxoplasma gondii seropositivity is associated with worse immediate and delayed verbal learning, language proficiency, executive functioning, processing speed, sustained attention, working memory, as well as global cognition in older adults. Public health measures aiming at preventing Toxoplasma gondii infection may help preserve cognitive functioning in older adults.

Selection Bias in Health Research: Quantifying, Eliminating, or Exacerbating Health Disparities?

Purpose of review

To summarize recent literature on selection bias in disparities research addressing either descriptive or causal questions, with examples from dementia research.

Recent findings

Defining a clear estimand, including the target population, is essential to assess whether generalizability bias or collider-stratification bias are threats to inferences. Selection bias in disparities research can result from sampling strategies, differential inclusion pipelines, loss to follow-up, and competing events. If competing events occur, several potentially relevant estimands can be estimated under different assumptions, with different interpretations. The apparent magnitude of a disparity can differ substantially based on the chosen estimand. Both randomized and observational studies may misrepresent health disparities or heterogeneity in treatment effects if they are not based on a known sampling scheme.

Conclusion

Researchers have recently made substantial progress in conceptualization and methods related to selection bias. This progress will improve the relevance of both descriptive and causal health disparities research.

Differential Participation, a Potential Cause of Spurious Associations in Observational Cohorts in Environmental Epidemiology

Differential participation in observational cohorts may lead to biased or even reversed estimates. In this article, we describe the potential for differential participation in cohorts studying the etiologic effects of long-term environmental exposures. Such cohorts are prone to differential participation because only those who survived until the start of follow-up and were healthy enough before enrollment will participate, and many environmental exposures are prevalent in the target population and connected to participation via factors such as geography or frailty. The relatively modest effect sizes of most environmental exposures also make any bias induced by differential participation particularly important to understand and account for. We discuss key points to consider for evaluating differential participation and use causal graphs to describe two example mechanisms through which differential participation can occur in health studies of long-term environmental exposures. We use a real-life example, the Canadian Community Health Survey cohort, to illustrate the non-negligible bias due to differential participation. We also demonstrate that implementing a simple washout period may reduce the bias and recover more valid results if the effect of interest is constant over time. Furthermore, we implement simulation scenarios to confirm the plausibility of the two mechanisms causing bias and the utility of the washout method. Since the existence of differential participation can be difficult to diagnose with traditional analytical approaches that calculate a summary effect estimate, we encourage researchers to systematically investigate the presence of time-varying effect estimates and potential spurious patterns (especially in initial periods in the setting of differential participation).

To weight or not to weight? Studying the effect of selection bias in three large EHR-linked biobanks

Objective

To explore the role of selection bias adjustment by weighting electronic health record (EHR)-linked biobank data for commonly performed analyses.

Materials and methods

We mapped diagnosis (ICD code) data to standardized phecodes from three EHR-linked biobanks with varying recruitment strategies: All of Us (AOU; n=244,071), Michigan Genomics Initiative (MGI; n=81,243), and UK Biobank (UKB; n=401,167). Using 2019 National Health Interview Survey data, we constructed selection weights for AOU and MGI to be more representative of the US adult population. We used weights previously developed for UKB to represent the UKB-eligible population. We conducted four common descriptive and analytic tasks comparing unweighted and weighted results.

Results

For AOU and MGI, estimated phecode prevalences decreased after weighting (weighted-unweighted median phecode prevalence ratio [MPR]: 0.82 and 0.61), while UKB's estimates increased (MPR: 1.06). Weighting minimally impacted latent phenome dimensionality estimation. Comparing weighted versus unweighted PheWAS for colorectal cancer, the strongest associations remained unaltered and there was large overlap in significant hits. Weighting affected the estimated log-odds ratio for sex and colorectal cancer to align more closely with national registry-based estimates.

Discussion

Weighting had limited impact on dimensionality estimation and large-scale hypothesis testing but impacted prevalence and association estimation more. Results from untargeted association analyses should be followed by weighted analysis when effect size estimation is of interest for specific signals.

Conclusion

EHR-linked biobanks should report recruitment and selection mechanisms and provide selection weights with defined target populations. Researchers should consider their intended estimands, specify source and target populations, and weight EHR-linked biobank analyses accordingly.

Selection Bias Requires Selection: The Case of Collider Stratification Bias

In epidemiology, collider stratification bias, the bias resulting from conditioning on a common effect of two causes, is oftentimes considered a type of selection bias, regardless of the conditioning methods employed. In this commentary, we distinguish between two types of collider stratification bias: collider restriction bias due to restricting to one level of a collider (or a descendant of a collider) and collider adjustment bias through inclusion of a collider (or a descendant of a collider) in a regression model. We argue that categorizing collider adjustment bias as a form of selection bias may lead to semantic confusion, as adjustment for a collider in a regression model does not involve selecting a sample for analysis. Instead, we propose that collider adjustment bias can be better viewed as a type of overadjustment bias. We further provide two distinct causal diagram structures to distinguish collider restriction bias and collider adjustment bias. We hope that such a terminological distinction can facilitate easier and clearer communication.

Identifiability of causal effects in test-negative design studies

Causal directed acyclic graphs (DAGs) are often used to select variables in a regression model to identify causal effects. Outcome-based sampling studies, such as the 'test-negative design' used to assess vaccine effectiveness, present unique challenges that are not addressed by the common back-door criterion. Here we discuss intuitive, graphical approaches to explain why the common back-door criterion cannot be used for identification of population average causal effects with outcome-based sampling studies. We also describe graphical rules that can be used instead in outcome-based sampling studies when the objective is limited to determining if the causal odds ratio is identifiable, and illustrate recent changes to the free online software Dagitty which incorporate these principles.

A multi-country analysis of COVID-19 hospitalizations by vaccination status

BACKGROUND

Individuals vaccinated against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), when infected, can still develop disease that requires hospitalization. It remains unclear whether these patients differ from hospitalized unvaccinated patients with regard to presentation, coexisting comorbidities, and outcomes.

METHODS

Here, we use data from an international consortium to study this question and assess whether differences between these groups are context specific. Data from 83,163 hospitalized COVID-19 patients (34,843 vaccinated, 48,320 unvaccinated) from 38 countries were analyzed.

FINDINGS

While typical symptoms were more often reported in unvaccinated patients, comorbidities, including some associated with worse prognosis in previous studies, were more common in vaccinated patients. Considerable between-country variation in both in-hospital fatality risk and vaccinated-versus-unvaccinated difference in this outcome was observed.

CONCLUSIONS

These findings will inform allocation of healthcare resources in future surges as well as design of longer-term international studies to characterize changes in clinical profile of hospitalized COVID-19 patients related to vaccination history.

FUNDING

This work was made possible by the UK Foreign, Commonwealth and Development Office and Wellcome (215091/Z/18/Z, 222410/Z/21/Z, 225288/Z/22/Z, and 220757/Z/20/Z); the Bill & Melinda Gates Foundation (OPP1209135); and the philanthropic support of the donors to the University of Oxford's COVID-19 Research Response Fund (0009109). Additional funders are listed in the "acknowledgments" section.

A Potential Outcomes Approach to Selection Bias

We propose a novel definition of selection bias in analytic epidemiology using potential outcomes. This definition captures selection bias under both the structural approach (where conditioning on selection into the study opens a noncausal path from exposure to disease in a directed acyclic graph) and the traditional definition (where a given measure of association differs between the study sample and the population eligible for inclusion). This approach is nonparametric, and selection bias under the approach can be analyzed using single-world intervention graphs both under and away from the null hypothesis. It allows the simultaneous analysis of confounding and selection bias, it explicitly links the selection of study participants to the estimation of causal effects using study data, and it can be adapted to handle selection bias in descriptive epidemiology. Through examples, we show that this approach provides a novel perspective on the variety of mechanisms that can generate selection bias and simplifies the analysis of selection bias in matched studies and case-cohort studies.

Interpreting Randomized Controlled Trials

This article describes rationales and limitations for making inferences based on data from randomized controlled trials (RCTs). We argue that obtaining a representative random sample from a patient population is impossible for a clinical trial because patients are accrued sequentially over time and thus comprise a convenience sample, subject only to protocol entry criteria. Consequently, the trial's sample is unlikely to represent a definable patient population. We use causal diagrams to illustrate the difference between random allocation of interventions within a clinical trial sample and true simple or stratified random sampling, as executed in surveys. We argue that group-specific statistics, such as a median survival time estimate for a treatment arm in an RCT, have limited meaning as estimates of larger patient population parameters. In contrast, random allocation between interventions facilitates comparative causal inferences about between-treatment effects, such as hazard ratios or differences between probabilities of response. Comparative inferences also require the assumption of transportability from a clinical trial's convenience sample to a targeted patient population. We focus on the consequences and limitations of randomization procedures in order to clarify the distinctions between pairs of complementary concepts of fundamental importance to data science and RCT interpretation. These include internal and external validity, generalizability and transportability, uncertainty and variability, representativeness and inclusiveness, blocking and stratification, relevance and robustness, forward and reverse causal inference, intention to treat and per protocol analyses, and potential outcomes and counterfactuals.

Study environment and the incidence of mental health problems and activity-limiting musculoskeletal problems among university students: the SUN cohort study

OBJECTIVE

To determine the association between different aspects of study environment and the incidence of mental health problems and activity-limiting musculoskeletal problems.

DESIGN, SETTING AND PARTICIPANTS

We recruited a cohort of 4262 Swedish university students of whom 2503 (59%) were without moderate or worse mental health problems and 2871 (67%) without activity-limiting musculoskeletal problems at baseline. The participants were followed at five time points over 1 year using web surveys.

EXPOSURES

Self-rated discrimination, high study pace, low social cohesion and poor physical environment measured at baseline.

OUTCOMES

Self-rated mental health problems defined as scoring above cut-off on any of the subscales of the Depression, Anxiety and Stress Scale. Self-rated activity-limiting musculoskeletal problems in any body location assessed by the Nordic Musculoskeletal Questionnaire.

STATISTICAL ANALYSIS

Discrete survival-time analysis was used to estimate the hazard rate ratio (HR) of each exposure-outcome combination while adjusting for gender, age, living situation, education type, year of studies, place of birth and parental education as potential confounders.

RESULTS

For discrimination, adjusted HRs were 1.75 (95% CI 1.40 to 2.19) for mental health problems and 1.39 (95% CI 1.12 to 1.72) for activity-limiting musculoskeletal problems. For high study pace, adjusted HRs were 1.70 (95% CI 1.48 to 1.94) for mental health problems and 1.25 (95% CI 1.09 to 1.43) for activity-limiting musculoskeletal problems. For low social cohesion, adjusted HRs were 1.51 (95% CI 1.29 to 1.77) for mental health problems and 1.08 (95% CI 0.93 to 1.25) for activity-limiting musculoskeletal problems. For perceived poor physical study environment, adjusted HRs were 1.20 (95% CI 0.99 to 1.45) for mental health problems and 1.20 (95% CI 1.01 to 1.43) for activity-limiting musculoskeletal problems.

CONCLUSIONS

Several aspects of the study environment were associated with the incidence of mental health problems and activity-limiting musculoskeletal problems in this sample of Swedish university students.

Obesity and renal cell carcinoma: Biological mechanisms and perspectives

Obesity, defined by body mass index (BMI), is an established risk factor for specific renal cell carcinoma (RCC) subtypes such as clear cell RCC, the most common RCC histology. Many studies have identified an association between obesity and improved survival after diagnosis of RCC, a potential "obesity paradox." Clinically, there is uncertainty whether improved outcomes observed after diagnosis are driven by stage, type of treatment received, or artifacts of longitudinal changes in weight and body composition. The biological mechanisms underlying obesity's influence on RCC are not fully established, but multiomic and mechanistic studies suggest an impact on tumor metabolism, particularly fatty acid metabolism, angiogenesis, and peritumoral inflammation, which are known to be key biological hallmarks of clear cell RCC. Conversely, high-intensity exercise associated with increased muscle mass may be a risk factor for renal medullary carcinoma, a rare RCC subtype that predominantly occurs in individuals with sickle hemoglobinopathies. Herein, we highlight methodologic challenges associated with studying the influence of obesity on RCC and review the clinical evidence and potential underlying mechanisms associating RCC with BMI and body composition.

Pay-it-forward incentives for hepatitis virus testing in men who have sex with men: a cluster randomized trial

Pay-it-forward incentives involve having a person receive a free test with community-generated messages and then asking if those who received a free test would like to donate money to support others to receive free testing. Here we undertook a two-arm cluster-randomized trial to evaluate pay-it-forward incentives with active community participation to promote hepatitis B virus (HBV) and hepatitis C virus (HCV) testing among men who have sex with men in China. Men randomized to the pay-it-forward arm received free HBV and HCV testing and were offered a chance to pay-it-forward by donating money to support the testing of another anonymous person. Each participant paid for their HCV and HBV test at 7.7 USD per test in the standard-of-care arm. The primary outcome was the proportion of men who tested for HBV and HCV. Between 28 March and 6 November 2021, 32 groups (10 men per group) of men were randomized to the pay-it-forward (n = 160, 16 clusters) and standard-of-care (n = 162, 16 clusters) arms, respectively. HBV and HCV rapid testing were higher in the pay-it-forward arm (59.4%) than in the standard-of-care arm (25.3%) (proportion difference 35.2%, 95% confidence interval 24.1-46.3%). No adverse events were reported. The community-led pay-it-forward incentives improved HBV and HCV testing among men who have sex with men. Clinical Trial registration: ChiCTR 2100046140.

Mixtures of Metals and Micronutrients in Early Pregnancy and Cognition in Early and Mid-Childhood: Findings from the Project Viva Cohort

BACKGROUND

The developing fetal brain is sensitive to many environmental exposures. However, the independent and joint effects of prenatal exposure to metals and micronutrients on child cognition are not well understood.

OBJECTIVES

Our aim was to evaluate associations of first-trimester (∼ 10 wk) maternal erythrocyte concentrations of mixtures of nonessential and essential metals and micronutrients with early (∼ 3 y) and mid-childhood (∼ 8 y) cognitive test scores in Project Viva, a prebirth cohort in Boston, Massachusetts, USA.

METHODS

We measured concentrations of five essential metals (Cu, Mg, Mn, Se, Zn) and two micronutrients (vitamin B12 and folate), together termed the "nutrient mixture," as well as six nonessential metals (As, Ba, Cd, Cs, Hg, Pb), together termed the "neurotoxic mixture," in first-trimester (∼ 10 wk) maternal erythrocytes (metals) or plasma (micronutrients). We assessed visual-motor function and receptive vocabulary in early childhood (∼ 3 y), and visual-motor function, visual memory, and fluid and crystallized intelligence in mid-childhood (∼ 8 y). We employed adjusted quantile g-computation and linear regression to estimate mixture and individual component associations, respectively.

RESULTS

Analyses included 900 mother-child pairs (74% college graduates; 52% male children). In mixture analyses, a quartile increase in the nutrient mixture was associated with a mean difference in early childhood receptive vocabulary score of 1.58 points [95% confidence interval (CI): 0.06, 3.10], driven by Zn and Se. A quartile increase in the neurotoxic mixture was associated with a mean difference in mid-childhood visual-motor score of - 3.01 points (95% CI: - 5.55 , - 0.47 ), driven by Ba and Cs. Linear regressions supported quantile g-computation findings for mixture component contributions.

DISCUSSION

Maternal circulating concentrations of several essential (Zn and Se) and nonessential (Ba and Cs) metals were associated with some domains of child cognition. In this folate-replete cohort, first-trimester circulating concentrations of known neurotoxic metals, such as Pb, were not associated with child cognition. https://doi.org/10.1289/EHP12016.

Exploring causality from observational data: An example assessing whether religiosity promotes cooperation

Causal inference from observational data is notoriously difficult, and relies upon many unverifiable assumptions, including no confounding or selection bias. Here, we demonstrate how to apply a range of sensitivity analyses to examine whether a causal interpretation from observational data may be justified. These methods include: testing different confounding structures (as the assumed confounding model may be incorrect), exploring potential residual confounding and assessing the impact of selection bias due to missing data. We aim to answer the causal question 'Does religiosity promote cooperative behaviour?' as a motivating example of how these methods can be applied. We use data from the parental generation of a large-scale (n = approximately 14,000) prospective UK birth cohort (the Avon Longitudinal Study of Parents and Children), which has detailed information on religiosity and potential confounding variables, while cooperation was measured via self-reported history of blood donation. In this study, there was no association between religious belief or affiliation and blood donation. Religious attendance was positively associated with blood donation, but could plausibly be explained by unmeasured confounding. In this population, evidence that religiosity causes blood donation is suggestive, but rather weak. These analyses illustrate how sensitivity analyses can aid causal inference from observational research.

Adverse childhood experiences and adult outcomes using a causal framework perspective: Challenges and opportunities

BACKGROUND

Research on the effect of adverse childhood experiences (ACEs) on adult outcomes has typically relied on retrospective assessment of ACEs and cumulative scores. However, this approach raises methodological challenges that can limit the validity of findings.

OBJECTIVE

The aims of this paper are 1) to present the value of directed acyclic graphs (DAGs) to identify and mitigate potential problems related to confounding and selection bias, and 2) to question the meaning of a cumulative ACE score.

RESULTS

Adjusting for variables that post-date childhood could block mediated pathways that are part of the total causal effect while conditioning on adult variables, which often serve as proxies for childhood variables, can create collider stratification bias. Because exposure to ACEs can affect the likelihood of reaching adulthood or study entry, selection bias could be introduced via restricting selection on a variable affected by ACEs in the presence of unmeasured confounding. In addition to challenges regarding causal structure, using a cumulative score of ACEs assumes that each type of adversity will have the same effect on a given outcome, which is unlikely considering differing risk across adverse experiences.

CONCLUSIONS

DAGs provide a transparent approach of the researchers' assumed causal relationships and can be used to overcome issues related to confounding and selection bias. Researchers should be explicit about their operationalization of ACEs and how it is to be interpreted in the context of the research question they are trying to answer.

Behavioral and neural underpinnings of empathic characteristics in a Humanitude-care expert

Background

Humanitude approaches have shown positive effects in elderly care. However, the behavioral and neural underpinnings of empathic characteristics in Humanitude-care experts remain unknown.

Methods

We investigated the empathic characteristics of a Humanitude-care expert (YG) and those of age-, sex-, and race-matched controls (n = 13). In a behavioral study, we measured subjective valence and arousal ratings and facial electromyography (EMG) of the corrugator supercilii and zygomatic major muscles while participants passively observed dynamic facial expressions associated with anger and happiness and their randomized mosaic patterns. In a functional magnetic resonance imaging (MRI) study, we measured brain activity while participants passively observed the same dynamic facial expressions and mosaics. In a structural MRI study, we acquired structural MRI data and analyzed gray matter volume.

Results

Our behavioral data showed that YG experienced higher subjective arousal and showed stronger facial EMG activity congruent with stimulus facial expressions compared with controls. The functional MRI data demonstrated that YG showed stronger activity in the ventral premotor cortex (PMv; covering the precentral gyrus and inferior frontal gyrus) and posterior middle temporal gyrus in the right hemisphere in response to dynamic facial expressions versus dynamic mosaics compared with controls. The structural MRI data revealed higher regional gray matter volume in the right PMv in YG than in controls.

Conclusion

These results suggest that Humanitude-care experts have behavioral and neural characteristics associated with empathic social interactions.

SARS-CoV-2 self-test uptake and factors associated with self-testing during Omicron BA.1 and BA.2 waves in France, January to May 2022

BackgroundFollowing the SARS-CoV-2 Omicron variant spread, the use of unsupervised antigenic rapid diagnostic tests (self-tests) increased.AimThis study aimed to measure self-test uptake and factors associated with self-testing.MethodsIn this cross-sectional study from 20 January to 2 May 2022, the case series from a case-control study on factors associated with SARS-CoV-2 infection were used to analyse self-testing habits in France. A multivariable quasi-Poisson regression was used to explore the variables associated with self-testing among symptomatic cases who were not contacts of another infected individual. The control series from the same study was used as a proxy for the self-test background rate in the non-infected population of France.ResultsDuring the study period, 179,165 cases who tested positive through supervised tests were recruited. Of these, 64.7% had performed a self-test in the 3 days preceding this supervised test, of which 79,038 (68.2%) were positive. The most frequently reported reason for self-testing was the presence of symptoms (64.6%). Among symptomatic cases who were not aware of being contacts of another case, self-testing was positively associated with being female, higher education, household size, being a teacher and negatively associated with older age, not French by birth, healthcare-related work and immunosuppression. Among the control series, 12% self-tested during the 8 days preceding questionnaire filling, with temporal heterogeneity.ConclusionThe analysis showed high self-test uptake in France with some inequalities which must be addressed through education and facilitated access (cost and availability) for making it a more efficient epidemic control tool.

Association between seropositivity for toxocariasis and cognitive functioning in older adults: an analysis of cross-sectional data from the US National Health and Nutrition Examination Survey (NHANES), 2011-2014

OBJECTIVES

This study sought to examine the relationship between seropositivity for toxocariasis and cognitive functioning in a nationally representative sample of US older adults.

DESIGN

A cross-sectional study.

SETTING

National Health and Nutrition Examination Survey (NHANES) data collection took place in the US at participants' homes and mobile examination centres with specialised equipment.

PARTICIPANTS

The study population consisted of 3188 community-dwelling US older adults aged 60 and above from the NHANES 2011 to 2014.

OUTCOME MEASURES

IgG antibody against Toxocara spp was tested by a Luminex assay using recombinant rTc-CTL-1 antigen. A value >23.1 mean fluorescence intensity (MFI) indicated positive for toxocariasis and a value ≤23.1 MFI as negative for toxocariasis. The Consortium to Establish a Registry for Alzheimer's Disease Word Learning subtest immediate and delayed memory, the Animal Fluency test and the Digit Symbol Substitution Test (DSST) were used to assess cognitive functioning. Cognitive test-specific and global cognitive z scores were computed using sample means and SD.

RESULTS

The study population consisted of 3188 participants who represented a total of 111 896 309 civilian citizens in the USA. The mean age of the participants was 69.6 years (standard deviation 6.8). The prevalence of toxocariasis in this population was 7.3% (95% confidence interval [CI] 6.1% to 8.5%). The survey-weighted linear regression model showed that compared with participants who were toxocariasis seronegative, those who were seropositive had lower DSST z score (beta [β] = -0.12, 95% CI -0.22 to -0.01) and global cognition z score (β=-0.11, 95% CI -0.22 to -0.01), after controlling for age, sex, race/ethnicity, education, depressive symptoms, smoking status, body mass index, prevalent coronary heart disease, prevalent stroke, and systolic blood pressure, physical activity, and total cholesterol.

CONCLUSIONS

In our study, seropositive toxocariasis was independently and significantly associated with worse working memory, sustained attention, processing speed and global cognition in older adults. If this association is causal, public health measures to prevent human toxocariasis might help protect older adults' cognitive function.

Exploring the impact of selection bias in observational studies of COVID-19: a simulation study

BACKGROUND

Non-random selection of analytic subsamples could introduce selection bias in observational studies. We explored the potential presence and impact of selection in studies of SARS-CoV-2 infection and COVID-19 prognosis.

METHODS

We tested the association of a broad range of characteristics with selection into COVID-19 analytic subsamples in the Avon Longitudinal Study of Parents and Children (ALSPAC) and UK Biobank (UKB). We then conducted empirical analyses and simulations to explore the potential presence, direction and magnitude of bias due to this selection (relative to our defined UK-based adult target populations) when estimating the association of body mass index (BMI) with SARS-CoV-2 infection and death-with-COVID-19.

RESULTS

In both cohorts, a broad range of characteristics was related to selection, sometimes in opposite directions (e.g. more-educated people were more likely to have data on SARS-CoV-2 infection in ALSPAC, but less likely in UKB). Higher BMI was associated with higher odds of SARS-CoV-2 infection and death-with-COVID-19. We found non-negligible bias in many simulated scenarios.

CONCLUSIONS

Analyses using COVID-19 self-reported or national registry data may be biased due to selection. The magnitude and direction of this bias depend on the outcome definition, the true effect of the risk factor and the assumed selection mechanism; these are likely to differ between studies with different target populations. Bias due to sample selection is a key concern in COVID-19 research based on national registry data, especially as countries end free mass testing. The framework we have used can be applied by other researchers assessing the extent to which their results may be biased for their research question of interest.

Age, 12-Step Group Involvement, and Relapse Affect Use of Sobriety Date as Recovery Start Date: A Mixed Methods Analysis

The purpose of this paper is to explore the use of sobriety date as recovery start date, from the perspective of those in recovery, using a mixed methods approach. We report findings from 389 individuals who identify as being in recovery from a substance and/or alcohol use disorder concerning how they define their recovery start date. We report findings from logistic regression examining how the use of a sobriety date as a recovery start date differs across age, 12-step group engagement, and previous relapse occurrence. We complement these findings with qualitative data from focus groups discussions of how 44 individuals who identify as in recovery define what "recovery" means, how and why people choose their recovery start date, and the significance of sobriety in recovery start date definitions. About 50% (n = 182) of the quantitative sample defined their recovery start date as their date of last substance use or their first day of sobriety. Individuals who were younger, engaged in 12-step groups, and did not report a relapse had significantly greater odds of using a sobriety date as their recovery start date. Focus groups revealed nuances around sobriety date and, what for some was, a broader concept of recovery. The current findings prioritize the views of those in recovery to understand and define their own recovery start date. How those in recovery think about and define their recovery start date may have particular meaning. Research and clinical work would benefit from inquiring about recovery and sobriety dates separately.

Exploring potential for selection bias in using survey data to estimate the association between institutional trust and depression

PURPOSE

We tested the hypothesis that low institutional trust would be associated with depressive symptom elevation, with attention to potential selection bias.

METHODS

The District of Columbia Area Survey (DCAS) was conducted by mail in 2018. Invitations sent to 8800 households resulted in a sample of 1061 adults. Institutional trust questions referenced nonprofit organizations, businesses, and government. Depressive symptom elevation was assessed using PHQ-9. Logistic regression model estimates were compared with and without adjustment for sociodemographic characteristics and neighborhood satisfaction; among complete cases and following multiple imputation of missing covariate data; and with and without survey weights or correction for collider selection bias.

RESULTS

Of 968 participants without missing depressive symptom or trust data, 24% reported low institutional trust. Low institutional trust was associated with elevated depressive symptoms (adjusted OR following multiple imputation: 2.0; 95% CI: 1.1, 3.4), although the association was attenuated with use of survey weights (adjusted OR incorporating multiple imputation and survey weights: 1.6; 95% CI: 0.7, 3.2).

CONCLUSIONS

Under contrasting scenarios where low institutional trust and depressive symptoms jointly increase nonresponse, selection bias could lead to under- or overestimation of this association. Future research could explore posited selection bias scenarios that differ in direction of bias.

Higher blood cotinine level is associated with worse cognitive functioning in non-smoking older adults

Introduction

Secondhand smoke (SHS) is common in older adults; however, its cognitive effect is unclear. We aimed to examine the association between serum cotinine level and cognitive functioning among non-smoking older adults.

Materials and methods

A total of 2,703 older adults aged 60 and above from the National Health and Nutrition Examination (NHANES) Survey 2011-2014 were included. Serum cotinine level was analyzed in the laboratory. A level ≤10 ng/ml and a response of "no" to the question "Do you currently smoke?" were used to select non-smokers. Cognitive functioning was measured using the Consortium to Establish a Registry for Alzheimer's disease Word Learning subtest (CERAD-WL) immediate and delayed recall tests, the Animal Fluency test (AFT), and the Digit Symbol Substitution test (DSST). Multivariable linear regression models were constructed to examine the association between serum cotinine level quartile and test-specific and global cognition z scores adjusting for age, race/ethnicity, education, depressive symptoms, body mass index, alcohol use, smoking history, prevalent coronary heart disease (CHD), stroke, and systolic blood pressure.

Results

About half of the participants (mean age 70.5 years) were female (53.6%), non-Hispanic White (48.3%), and completed some college and above (50.2%). Multivariate linear regressions with a reference group being those in the 1st quantile (lowest) showed that participants in the 4th quartile (highest) of serum cotinine level had lower immediate recall [β = -0.16, 95% confidence interval (CI) = -0.29, -0.03], AFT (β = -0.19, 95% CI = -0.33, -0.05), DSST (β = -0.27, 95% CI = -0.39, -0.15), and global cognition (β = -0.26, 95% CI = -0.39, -0.14) z scores. Participants in the 3rd quartile had lower immediate recall (β = -0.16, 95% CI = -0.30, -0.02) and global cognition (β = -0.16, 95% CI = -0.29, -0.02) z scores. Participants in the 2nd quartile had lower delayed recall z scores (β = -0.16, 95% CI = -0.29, -0.02).

Conclusion

Higher serum cotinine level was associated with worse cognitive functioning in non-smoking older adults. Prevention and reduction of SHS in older adults may help protect their cognitive functioning.

The impact of COVID-19 on the mental health of pregnant women in Shanghai, China

Background

COVID-19 has dramatically impacted people's health, especially mental health. This study aimed to compare the psychological status of pregnant women before and after the COVID-19 outbreak.

Methods

Participants were recruited (from September 29, 2019, to November 5, 2020) and screened by the Patient Health Questionnaire (PHQ-9) and the Generalized Anxiety Disorder Scale (GAD-7). The study participants were categorized into three groups based on two turning-points: January 23, 2020, when China initiated a locked-down strategy, and May 11, 2020, when Shanghai started to ease the COVID-19 measures. Multivariable logistic regression was used to determine the factors associated with depression and anxiety in pregnant women. We used enter method for variable selection; only variables with P <0.10 were included in the final model.

Results

We recruited 478 pregnant women. After the outbreak, the depression rate (PHQ-9 ≥ 5) increased by 12.3% (from 35.4 to 47.7%), and the anxiety rate (GAD-7 ≥ 5) was stable (13.3 vs. 16.2%). The multivariable logistic regression results further confirmed that the odds of depression in pregnant women increased 81% after the outbreak (aOR = 1.81, 95%CI: 1.16-2.84). However, the median depression scale score was still statistically higher after the pandemic situation was stable (5.0 vs. 4.0) compared to the outbreak period.

Conclusion

The depression rate increased among pregnant women after the outbreak and was not recovered after the ease of COVID-19 measures in Shanghai. Health institutes should pay attention to the long-term influence of the pandemic.