Assessing causality in epidemiology: revisiting Bradford Hill to incorporate developments in causal thinking

Myths and misinformation associated with vaccine incompleteness: A survey study

OBJECTIVE

Vaccine hesitancy is a relevant driver of backslides in immunization rates globally. Myths and misinformation are key contributors to vaccine hesitancy. We aimed to investigate associations between beliefs in popular vaccine myths and vaccine incompleteness.

METHODS

In this survey, participants were asked questions on current vaccination status; barriers and motivations for vaccination; and beliefs regarding popular myths: the measles vaccine causes autism in children; acquiring the disease is preferable to facing vaccine side effects; and natural immunity developed from getting the disease is better than the immunity elicited by vaccination. We assessed the effect of failing to disagree with the myths on current vaccination status.

RESULTS

Of 4305 participants, 933 (22 %) were partially vaccinated and 61 (1 %) were fully unvaccinated; 403 (10 %) failed to disagree with the autism myth; 411 (10 %) failed to disagree with the side effects myth; and 904 (22 %) failed to disagree with the natural immunity myth. Failing to disagree with the myths was significantly associated with vaccine incompleteness.

CONCLUSION

Vaccine-related myths are associated with both partial and total vaccine incompleteness in Brazil.

PRACTICE IMPLICATIONS

Strategies to improve adherence to vaccination recommendations should include interventions to limit the spread or elucidate vaccine-related myths and misconceptions.

Confounders: A threat to the interpretation of research findings in endodontics

Confounding is a significant challenge in endodontic research, as it can blur the true effect and relationship between exposure and outcomes, potentially compromising the internal validity of research findings. Confounding variables can create apparent differences between study groups when no actual difference exists or fail to reveal true differences when they are present. Additionally, confounding can lead to either an underestimation or an overestimation of the effect of exposure on the outcome. This narrative review aims to (i) define confounder variables and explain how to identify them, (ii) elaborate methods for controlling confounders, and (iii) discuss how confounders can obscure any causal relationship. Confounding variables can be controlled through study design such as randomization, matching and restriction, or adjusted using statistical methods like stratification and multivariable models. However, inadequate control of confounding can result in residual confounding, which poses a significant threat to the interpretation of findings in endodontic research.

Statistics Primer for Radiologists: Part 2-Advanced statistics for Enhancing Diagnostic Precision and Research Validity

Second part of this statistics primer focuses on advanced statistical concepts continuing on the foundation of basic statistics built from the first part of this primer. This advanced primer aims to delve deeper into essential statistical concepts beyond the basics, equipping the reader with the knowledge to effectively analyze complex data sets, explore correlations and causality, employ regression analysis techniques, interpret survival curves, and evaluate diagnostic tests rigorously. It primarily focuses on the statistical tests used to analyze the relationship between groups of variables (the statistical tests to analyze the difference between groups of variables was discussed in the part 1 of this series). Toward the end of the article concepts of survival curves and methods for assessing the diagnostic accuracy of tests are stressed upon.

Exploring the pathways linking prenatal and early childhood greenness exposure to attention-deficit/hyperactivity disorder symptoms during childhood: An approach based on robust causal inference

BACKGROUND

Epidemiological studies suggest that exposure to greenness during childhood may protect children from developing attention-deficit hyperactivity disorder (ADHD).

OBJECTIVE

We analyzed the effect of both prenatal (pregnancy) and early childhood (4-5-year follow-up) residential greenness exposure and green space availability on ADHD symptoms during childhood (up to the age of 12 years) and further explored the potential mediating role of PM2.5 and physical activity in the association.

METHODS

The study population included participants from the INfancia y Medio Ambiente (INMA) prospective birth cohort (Gipuzkoa, Sabadell, and Valencia). Average Normalized Difference Vegetation Index (NDVI) in buffers of 100-, 300- and 500-m around the residential addresses was used as an indicator of greenness, while green space availability was determined based on the presence of a major green space within 150-m from the residence. Childhood ADHD symptoms were assessed at the 6-8- and 10-12-year follow-ups using Conners Parents Rating Scale-Revised: Short Form.

RESULTS

Although no association was found for the prenatal exposure period, increased early childhood NDVI inversely associated with the OR of clinically significant ADHD symptoms during the 6-8-year follow-up at the 100-m (OR 0.03, 95% CI: 0.003 to 0.44), 300-m (OR 0.04, 95% CI: 0.003 to 0.42) and 500-m (OR 0.08, 95% CI: 0.01 to 0.76) buffers, but exclusively in the context of direct effects. Additionally, the 10-12-year follow-up analysis found moderate to weak evidence of potential total and direct effects of NDVI at both 100- and 300-m buffers on inattention scores, as well as for NDVI at the 300-m buffer on ADHD index scores. The analysis did not reveal evidence of mediation through PM2.5 or physical activity.

CONCLUSIONS

The evidence suggests that early childhood greenness exposure may reduce the risk of developing ADHD symptoms later in childhood, and that this association is not mediated through PM2.5 and physical activity.

Breaking Down Bias: A Methodological Primer on Identifying, Evaluating, and Mitigating Bias in Cardiovascular Research

Systematic error, often referred to as bias is an inherent challenge in observational cardiovascular research, and has the potential to profoundly influence the design, conduct, and interpretation of study results. If not carefully considered and managed, bias can lead to spurious results, which can misinform clinical practice or public health initiatives and compromise patient outcomes. This methodological primer offers a concise introduction to the identification, evaluation, and mitigation of bias in observational cardiovascular research studies assessing the causal association of an exposure (or treatment) on an outcome. Using high-profile examples from the cardiovascular literature, this review provides a theoretical overview of three main types of bias - selection bias, information bias, and confounding - and discusses the implications of specialized types of biases commonly encountered in longitudinal cardiovascular research studies, namely, competing risks, immortal time bias, and confounding by indication. Furthermore, strategies and tools that can be used to minimize and assess the influence of bias are highlighted, with a specific focus on using the target trial framework, directed acyclic graphs, quantitative bias analysis, and formal risk of bias assessments. This review aims to assist researchers and healthcare professionals in designing observational studies and selecting appropriate methodologies to reduce bias, ultimately enhancing the estimation of causal associations in cardiovascular research.

Developing an HIV-specific falls risk prediction model with a novel clinical index: a systematic review and meta-analysis method

BACKGROUND

Falls are a common problem experienced by people living with HIV yet predictive models specific to this population remain underdeveloped. We aimed to identify, assess and stratify the predictive strength of various physiological, behavioral, and HIV-specific factors associated with falls among people living with HIV and inform a predictive model for fall prevention.

METHODS

Systematic review and meta-analysis were conducted to explore predictors of falls in people living with HIV. Data was sourced, screened, extracted, and analyzed by two independent reviewers from eight databases up to January 2nd, 2024, following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) protocol. Evidence quality and bias were assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) and the Mixed Method Appraisal Tool (MMAT), respectively. Pooled odds ratios (OR) with 95% confidence intervals (CI) were computed using random-effects models to establish associations between predictors and falls risk. We applied established criteria (Bradford Hill's criteria, Rothman's and Nweke's viewpoints) to stratify risk factors and create a weighted predictive algorithm.

RESULTS

This review included 12 studies on falls/balance dysfunction in 117,638 participants (54,513 people living with HIV), with varying ages (45-50 years), sample sizes (32 - 26,373), study durations (6 months to 15 years), disease stages (CD4 + counts 347.2 cells/mm³ to ≥ 500 cells/µL) and fall definitions (self-reported histories to real-time reporting). Some predictors of falls in people living with HIV including depression, cannabis use, cognitive impairment/neurocognitive adverse effects (NCAE), hypertension, and stavudine-showed perfect risk responsiveness (Ri = 1), indicating their strong association with falls. Notably, cannabis use demonstrated the highest risk weight (Rw = 3.0, p < 0.05, 95%CI:1.51-5.82), followed by NCAE (Rw = 2.3, p < 0.05, 95%CI:1.66-3.21) and frailty with a broad confidence interval (Rw = 2.2, p < 0.05, 95%CI:0.73-14.40). Other significant predictors included hypertension (Rw = 1.8, p < 0.05, 95%CI:1.33-2.33), depression (Rw = 1.6, p < 0.05, 95%CI:1.22-2.18), stavudine use (Rw = 1.5, p < 0.05, 95%CI: 0.95-2.25), neuropathy (Rw = 1.3, p < 0.05, 95%CI:1.26-2.11), and polypharmacy (Rw = 1.2, p < 0.05, 95%CI:1.16-1.96). The fall risk threshold score was 12.8, representing the 76th percentile of the specific and sufficient risk weight.

CONCLUSION

Our meta-analysis identifies predictors of falls in people living with HIV, emphasizing physiological, behavioral, and HIV-specific factors. Integrating these into clinical practice could mitigate falls-related sequelae. We propose a novel approach to falls risk prediction using a novel clinical index, resulting in a HIV-specific falls risk assessment tool.

TRIAL REGISTRATION

The study protocol is registered with PROSPERO ID: CRD42023453556.

Pediatric acute kidney injury and adverse health outcomes: using a foundational framework to evaluate a causal link

Acute kidney injury (AKI) is a major global health problem, expensive to manage, and its associations with negative pediatric health outcomes have been clearly demonstrated. One of the most fundamental questions to consider as we use previous epidemiological information to advance research and care paradigms is the strength of the causal link between pediatric AKI and health outcomes. In this review, we apply the foundational framework of the Bradford Hill criteria to evaluate the extent to which a causal link exists between AKI and the associated adverse outcomes in children. Available data in children support a causal link between AKI and short-term outcomes including mortality, length of stay, and ventilation time. Clarifying the causal nature of longer term associations requires further high-quality observational studies in children, careful consideration of what defines the most meaningful and measurable longer term outcomes after pediatric AKI, and integration of evolving biological data related to mechanisms of disease. Preventing or mitigating AKI should lead to improved outcomes. Demonstrating such reversibility will solidify confidence in the causal relationship, improve child health, and highlight an aspect which is highly relevant to clinicians, scientists, and policy makers.

Applying Bradford Hill to assessing causality in systematic reviews: A transparent approach using process tracing

BACKGROUND

Bradford Hill (BH) viewpoints are widely used to assess causality in systematic reviews, but their application has often lacked reproducibility. We describe an approach for assessing causality within systematic reviews ('causal' reviews), illustrating its application to the topic of income inequality and health. Our approach draws on principles of process tracing, a method used for case study research, to harness BH viewpoints to judge evidence for causal claims.

METHODS

In process tracing, a hypothesis may be confirmed by observing highly unique evidence and disconfirmed by observing highly definitive evidence. We drew on these principles to consider the value of finding supportive or contradictory evidence for each BH viewpoint characterised by its uniqueness and definitiveness.

RESULTS

In our exemplar systematic review, we hypothesised that income inequality adversely affects self-rated health and all-cause mortality. BH viewpoints 'analogy' and 'coherence' were excluded from the causal assessment because of their low uniqueness and low definitiveness. The 'experiment' viewpoint was considered highly unique and highly definitive, and thus could be particularly valuable. We propose five steps for using BH viewpoints in a 'causal' review: (1) define the hypothesis; (2) characterise each viewpoint; (3) specify the evidence expected for each BH viewpoint for a true or untrue hypothesis; (4) gather evidence for each viewpoint (e.g., systematic review meta-analyses, critical appraisal, background knowledge); (5) consider if each viewpoint was met (supportive evidence) or unmet (contradictory evidence).

CONCLUSIONS

Incorporating process tracing has the potential to provide transparency and structure when using BH viewpoints in 'causal' reviews.

A review of OSHA-permissible exposure limits for occupational carcinogens in relation to quantitative risk assessments based on epidemiological findings

A very small proportion of all chemicals in commerce have occupational exposure limits (OELs) based on quantitative risk assessments which require estimates of exposure-response relationships (XRs). For only 18 of the 94 chemicals declared by NIOSH to be carcinogens were human XRs reported in or calculable from published reports. For the 18 carcinogens, 96 such XRs could be derived (corresponding to chemicals with multiple associated cancer end-points and/or multiple source studies). Twenty-four of 96 XR estimates came directly from reported statistical models (on continuous cumulative exposure), 45 were derived from summary study-population attributes, and 27 came from categorical analyses. Using the 96 XRs, OEL conferring one-per-thousand excess lifetime risk were calculated. OSHA's OEL, permissible exposure limits (PEL) were then compared to OEL derived from the 96 XRs. For 88 of the 96 calculated OELs (for which a corresponding PEL exists) all but 10 fell below the current PEL. Thirty-four OEL estimates were 10- to 100-fold below the PEL and 21 were greater than 100-fold below the PEL. This same pattern was observed using the different methods for deriving XRs. These findings can guide priorities in setting standards and the method is not limited to carcinogens.

MAD-microbial (origin of) Alzheimer's disease hypothesis: from infection and the antimicrobial response to disruption of key copper-based systems

Microbes have been suspected to cause Alzheimer's disease since at least 1908, but this has generally remained unpopular in comparison to the amyloid hypothesis and the dominance of Aβ and Tau. However, evidence has been accumulating to suggest that these earlier theories are but a manifestation of a common cause that can trigger and interact with all the major molecular players recognized in AD. Aβ, Tau and ApoE, in particular appear to be molecules with normal homeostatic functions but also with alternative antimicrobial functions. Their alternative functions confer the non-immune specialized neuron with some innate intracellular defenses that appear to be re-appropriated from their normal functions in times of need. Indeed, signs of infection of the neurons by biofilm-forming microbial colonies, in synergy with herpes viruses, are evident from the clinical and preclinical studies we discuss. Furthermore, we attempt to provide a mechanistic understanding of the AD landscape by discussing the antimicrobial effect of Aβ, Tau and ApoE and Lactoferrin in AD, and a possible mechanistic link with deficiency of vital copper-based systems. In particular, we focus on mitochondrial oxidative respiration via complex 4 and ceruloplasmin for iron homeostasis, and how this is similar and possibly central to neurodegenerative diseases in general. In the case of AD, we provide evidence for the microbial Alzheimer's disease (MAD) theory, namely that AD could in fact be caused by a long-term microbial exposure or even long-term infection of the neurons themselves that results in a costly prolonged antimicrobial response that disrupts copper-based systems that govern neurotransmission, iron homeostasis and respiration. Finally, we discuss potential treatment modalities based on this holistic understanding of AD that incorporates the many separate and seemingly conflicting theories. If the MAD theory is correct, then the reduction of microbial exposure through use of broad antimicrobial and anti-inflammatory treatments could potentially alleviate AD although this requires further clinical investigation.

Relationship between parental exposure to radiofrequency electromagnetic fields and primarily hematopoietic neoplasms (lymphoma, leukemia) and tumors in the central nervous system in children: a systematic review

Low-frequency electromagnetic fields have grown exponentially in recent years due to technological development and modernization. The World Health Organization (WHO)/International Agency for Research on Cancer (IARC) has classified radiofrequency electromagnetic fields (RF-EMFs) as possibly carcinogenic to humans (Group 2B), and recent studies have investigated the association between exposure to electromagnetic fields in parents and possible health effects in children, especially the development of tumours of the central nervous system (CNS). The objective of this systematic review was to collate all evidence on the relationship between parental occupational exposure to electromagnetic fields and the development of CNS cancer in children and to evaluate this association. This review was prepared according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PubMed, Embase, and Web of Science were searched from January 1990 to April 2021. The search was conducted using the following search string: "occupational" AND "child" AND "electromagnetic" AND "cancer". Seventeen articles met our inclusion criteria: 13 case-control studies, two cohort studies, and 2 meta-analyses. Most of the studies showed several methodological weaknesses that limited their results. Due to a lack of consistency regarding the outcome as well as the heterogeneity in the reviewed studies, the body of evidence for the effects of parental exposure to electromagnetic fields is not clear. Methodological heterogeneity in the way that studies were conducted could be responsible for the lack of consistency in the findings. Overall, the body of evidence allows no conclusion on the relationship between parental exposure to electromagnetic fields and the occurrence of CNS tumours in children.

Air quality and mental illness: role of bioaerosols, causal mechanisms and research priorities

BACKGROUND

Poor air quality can both trigger and aggravate lung and heart conditions, as well as affecting child development. It can even lead to neurological and mental health problems. However, the precise mechanisms by which air pollution affect human health are not well understood.

AIMS

To promote interdisciplinary dialogue and better research based on a critical summary of evidence on air quality and health, with an emphasis on mental health, and to do so with a special focus on bioaerosols as a common but neglected air constituent.

METHOD

A rapid narrative review and interdisciplinary expert consultation, as is recommended for a complex and rapidly changing field of research.

RESULTS

The research methods used to assess exposures and outcomes vary across different fields of study, resulting in a disconnect in bioaerosol and health research. We make recommendations to enhance the evidence base by standardising measures of exposure to both particulate matter in general and bioaerosols specifically. We present methods for assessing mental health and ideal designs. There is less research on bioaerosols, and we provide specific ways of measuring exposure to these. We suggest research designs for investigating causal mechanisms as important intermediate steps before undertaking larger-scale and definitive studies.

CONCLUSIONS

We propose methods for exposure and outcome measurement, as well as optimal research designs to inform the development of standards for undertaking and reporting research and for future policy.

Epidemiological Principles in Claims of Causality: An Enquiry into Repetitive Head Impacts (RHI) and Chronic Traumatic Encephalopathy (CTE)

Determining whether repetitive head impacts (RHI) cause the development of chronic traumatic encephalopathy (CTE)-neuropathological change (NC) and whether pathological changes cause clinical syndromes are topics of considerable interest to the global sports medicine community. In 2022, an article was published that used the Bradford Hill criteria to evaluate the claim that RHI cause CTE. The publication garnered international media attention and has since been promoted as definitive proof that causality has been established. Our counterpoint presents an appraisal of the published article in terms of the claims made and the scientific literature used in developing those claims. We conclude that the evidence provided does not justify the causal claims. We discuss how causes are conceptualised in modern epidemiology and highlight shortcomings in the current definitions and measurement of exposures (RHI) and outcomes (CTE). We address the Bradford Hill arguments that are used as evidence in the original review and conclude that assertions of causality having been established are premature. Members of the scientific community must be cautious of making causal claims until the proposed exposures and outcomes are well defined and consistently measured, and findings from appropriately designed studies have been published. Evaluating and reflecting on the quality of research is a crucial step in providing accurate evidence-based information to the public.

Maternal modifiable factors and risk of congenital heart defects: systematic review and causality assessment

OBJECTIVE

Primary prevention strategies are critical to reduce the global burden of congenital heart defects (CHDs); this requires robust knowledge of causal agents. We aimed to review associations between CHDs and maternal advanced age, obesity, diabetes, hypertension, smoking and alcohol consumption and assess the causal nature of the associations.

DESIGN

Systematic review of reviews with application of a Bradford Hill criteria score-based causal assessment system.

DATA SOURCES

We searched PubMed, Embase and Episteminokos (January 1990-April 2023).

ELIGIBILITY CRITERIA

Systematic reviews of original epidemiological studies reporting association (relative risk) between one or more of the above maternal factors and CHDs overall (any type) in subsequent offspring.

DATA EXTRACTION AND SYNTHESIS

Two independent reviewers selected eligible reviews, assessed the risk of bias and assigned the strength of evidence for causality.

RESULTS

There was strong evidence of a causal relationship between CHDs and maternal obesity (prepregnancy and early pregnancy) and pre-existing diabetes (six of seven Bradford Hill criteria met). For pre-existing hypertension (strength and biological gradient not met), and advanced age (strength, consistency and biological gradient not met), causal evidence was moderate. Evidence for the causal contribution of gestational diabetes, gestational hypertension, smoking and alcohol consumption was weak (strength, consistency, temporality and biological gradient not met).

CONCLUSIONS

CHDs can be reduced with stronger action to reduce maternal obesity and pre-existing diabetes prevalence. Investigating environmental exposures that have received limited attention, such as air pollutants and chemical exposures, is important to further inform prevention.

Guide to Decomposition of Causal Effects Into Mediation, Interaction, and Direct Effects: Case Study on Aerobic Exercise and Parkinson Disease

Mediation analysis can be applied in medical research with the aim of understanding the pathways that operate between an exposure and its effects on an outcome. This method can help to improve our understanding of pathophysiologic mechanisms and may guide the choice of potential treatment strategies. Traditional mediation analysis decomposes the total effect of an intervention on the outcome into 2 effects: (1) an indirect effect, from exposure using a mediator to the outcome, and (2) a direct effect, directly from exposure to outcome. A limitation of this method is that it assumes no interaction between the exposure and the mediator, which can either lead to an over- or underestimation of clinically relevant effects. The "4-way decomposition" method has the advantage of overcoming this limitation. Specifically, the total effect of an exposure on the outcome is decomposed into 4 elements: (1) reference interaction (interaction only), (2) mediated interaction (mediation and interaction), (3) the pure indirect effect (mediation but not interaction), and (4) the direct effect (no mediation and no interaction). We provide a guide to select the most appropriate method to investigate and decompose any causal effect given the research question at hand. We explain the application of the 4-way decomposition and illustrate this with a real-world example of how aerobic exercise may influence motor function in persons with Parkinson disease.

Comparative Risk of Injury with Concurrent Use of Opioids and Skeletal Muscle Relaxants

Concurrent use of skeletal muscle relaxants (SMRs) and opioids has been linked to an increased risk of injury. However, it remains unclear whether the injury risks differ by specific SMR when combined with opioids. We conducted nine retrospective cohort studies within a US Medicaid population. Each cohort consisted exclusively of person-time exposed to both an SMR and one of the three most dispensed opioids-hydrocodone, oxycodone, and tramadol. Opioid users were further divided into three cohorts based on the initiation order of SMRs and opioids-synchronically triggered, opioid-triggered, and SMR-triggered. Within each cohort, we used Cox proportional hazard models to compare the injury rates for different SMRs compared to methocarbamol, adjusting for covariates. We identified 349,543, 139,458, and 218,967 concurrent users of SMRs with hydrocodone, oxycodone, and tramadol, respectively. In the oxycodone-SMR-triggered cohort, the adjusted hazard ratios (HRs) were 1.86 (95% CI, 1.23-2.82) for carisoprodol and 1.73 (1.09-2.73) for tizanidine. In the tramadol-synchronically triggered cohort, the adjusted HRs were 0.69 (0.49-0.97) for metaxalone and 0.62 (0.42-0.90) for tizanidine. In the tramadol-SMR-triggered cohort, the adjusted HRs were 1.51 (1.01-2.26) for baclofen and 1.48 (1.03-2.11) for cyclobenzaprine. All other HRs were statistically nonsignificant. In conclusion, the relative injury rate associated with different SMRs used concurrently with the three most dispensed opioids appears to vary depending on the specific opioid and the order of combination initiation. If confirmed by future studies, clinicians should consider the varying injury rates when prescribing SMRs to individuals using hydrocodone, oxycodone, and tramadol.

A practical guide to estimating treatment effects in patients with rheumatic diseases using real-world data

OBJECTIVE

Randomized controlled trials are considered the gold standard in study methodology. However, due to their study design and inclusion criteria, these studies may not capture the heterogeneity of real-world patient populations. In contrast, the lack of randomization and the presence of both measured and unmeasured confounding factors could bias the estimated treatment effect when using observational data. While causal inference methods allow for the estimation of treatment effects, their mathematical complexity may hinder their application in clinical research.

METHODS

We present a practical, nontechnical guide using a common statistical package (Stata) and a motivational simulated dataset that mirrors real-world observational data from patients with rheumatic diseases. We demonstrate regression analysis, regression adjustment, inverse-probability weighting, propensity score (PS) matching and two robust estimation methods.

RESULTS

Although the methods applied to control for confounding factors produced similar results, the commonly used one-to-one PS matching method could yield biased results if not thoroughly assessed.

CONCLUSION

The guide we propose aims to facilitate the use of readily available methods in a common statistical package. It may contribute to robust and transparent epidemiological and statistical methods, thereby enhancing effectiveness research using observational data in rheumatology.

Access to civil justice as a social determinant of health: a legal epidemiological cross-sectional study

BACKGROUND

Although it is widely acknowledged that access to civil justice (ATJ) is a key social determinant of health (SDOH), the existing literature lacks empirical evidence supporting ATJ as a SDOH for specific dimensions of health.

METHODS

A legal epidemiological, cross-sectional, postal survey was conducted on n = 908 randomly sampled participants in Hong Kong in March 2023. Data collected were perceptions of the civil justice system, health, and sociodemographics. Perceived ATJ was assessed using a modified version of the Inaccessibility of Justice scale (IOJ) and Perceived Inequality of Justice scale (PIJ), i.e. the "modified IOJ-PIJ", consisting of 12 of the original 13 items from both scales divided into two subdomains: "procedural fairness", and "outcome neutrality". For health data, quality of life was assessed using the Hong Kong version of the Abbreviated World Health Organization Quality of Life questionnaire (WHOQOL-BREF(HK)), psychological distress (including symptoms of anxiety and depression) was assessed using the four-Item Patient Health Questionnaire (PHQ-4), and having comorbidities was assessed using Sangha's Self-Administered Comorbidity Questionnaire (SCQ). Structural equation modelling (SEM) was used to investigate the relationships between perceived ATJ and the measured health outcomes.

RESULTS

SEM demonstrated that both subdomains for ATJ had significantly negative associations (B < 0; p < 0.05) with all quality-of-life subdomains, except for between outcome neutrality with social relationships; both subdomains for ATJ had significantly positive association (B > 0; p < 0.05) with both anxiety and depression; and, after adjusting for age, only "procedural fairness" had significantly positive association (B > 0; p < 0.05) with having comorbidities.

CONCLUSION

This study provided empirical evidence that ATJ is a SDOH for specific dimensions of health. The results of this study encourage laws, policies, and initiatives aimed at improving ATJ, as well as collaborative efforts from the legal and health sectors through health-justice partnerships, and from the broader community, to safeguard and promote public health by strengthening ATJ.

A blueprint for a new commercial driving epidemiology: An emerging paradigm grounded in integrative exposome and network epistemologies

Excess health and safety risks of commercial drivers are largely determined by, embedded in, or operate as complex, dynamic, and randomly determined systems with interacting parts. Yet, prevailing epidemiology is entrenched in narrow, deterministic, and static exposure-response frameworks along with ensuing inadequate data and limiting methods, thereby perpetuating an incomplete understanding of commercial drivers' health and safety risks. This paper is grounded in our ongoing research that conceptualizes health and safety challenges of working people as multilayered "wholes" of interacting work and nonwork factors, exemplified by complex-systems epistemologies. Building upon and expanding these assumptions, herein we: (a) discuss how insights from integrative exposome and network-science-based frameworks can enhance our understanding of commercial drivers' chronic disease and injury burden; (b) introduce the "working life exposome of commercial driving" (WLE-CD)-an array of multifactorial and interdependent work and nonwork exposures and associated biological responses that concurrently or sequentially impact commercial drivers' health and safety during and beyond their work tenure; (c) conceptualize commercial drivers' health and safety risks as multilayered networks centered on the WLE-CD and network relational patterns and topological properties-that is, arrangement, connections, and relationships among network components-that largely govern risk dynamics; and (d) elucidate how integrative exposome and network-science-based innovations can contribute to a more comprehensive understanding of commercial drivers' chronic disease and injury risk dynamics. Development, validation, and proliferation of this emerging discourse can move commercial driving epidemiology to the frontier of science with implications for policy, action, other working populations, and population health at large.

PM2.5, component cause of severe metabolically abnormal obesity: An in silico, observational and analytical study

Obesity is currently one of the most alarming pathological conditions due to the progressive increase in its prevalence. In the last decade, it has been associated with fine particulate matter suspended in the air (PM2.5). The purpose of this study was to explore the mechanistic interaction of PM2.5 with a high-fat diet (HFD) through the differential regulation of transcriptional signatures, aiming to identify the association of these particles with metabolically abnormal obesity. The research design was observational, using bioinformatic methods and an explanatory approach based on Rothman's causal model. We propose three new transcriptional signatures in murine adipose tissue. The sum of transcriptional differences between the group exposed to an HFD and PM2.5, compared to the control group, were 0.851, 0.265, and -0.047 (p > 0.05). The HFD group increased body mass by 20% with two positive biomarkers of metabolic impact. The group exposed to PM2.5 maintained a similar weight to the control group but exhibited three positive biomarkers. Enriched biological pathways (p < 0.05) included PPAR signaling, small molecule transport, adipogenesis genes, cytokine-cytokine receptor interaction, and HIF-1 signaling. Transcriptional regulation predictions revealed CpG islands and common transcription factors. We propose three new transcriptional signatures: FAT-PM2.5-CEJUS, FAT-PM2.5-UP, and FAT-PM2.5-DN, whose transcriptional regulation profile in adipocytes was statistically similar by dietary intake and HFD and exposure to PM2.5 in mice; suggesting a mechanistic interaction between both factors. However, HFD-exposed murines developed moderate metabolically abnormal obesity, and PM2.5-exposed murines developed severe abnormal metabolism without obesity. Therefore, in Rothman's terms, it is concluded that HFD is a sufficient cause of the development of obesity, and PM2.5 is a component cause of severe abnormal metabolism of obesity. These signatures would be integrated into a systemic biological process that would induce transcriptional regulation in trans, activating obesogenic biological pathways, restricting lipid mobilization pathways, decreasing adaptive thermogenesis and angiogenesis, and altering vascular tone thus inducing a severe metabolically abnormal obesity.

The Relationship Between Time Spent on Social Media and Adolescent Cigarette, E-cigarette, and Dual Use: A Longitudinal Analysis of the UK Millennium Cohort Study

INTRODUCTION

To estimate the effect of social media use in 14 year olds on risk of and inequalities in cigarette, e-cigarette, and dual use at 17 years, using the UK-representative Millennium Cohort Study (born 2000-2002).

AIMS AND METHODS

The relationship of time spent on social media (using questionnaires [n = 8987] and time-use-diaries [n = 2520]) with cigarette, e-cigarette, and dual use was estimated using adjusted odds ratios (AORs) or relative risk ratios (ARRRs). Effect modification was examined (using parental education as an indicator for socioeconomic circumstances) by comparing adjusted risk differences within low and high-parental education groups. Analyses accounted for prespecified confounders (identified via directed acyclic graphs), baseline outcome measures (to address reverse causality), sample design, attrition, and item-missingness (through multiple imputation).

RESULTS

Time spent on social media was associated with increased risk of cigarette, e-cigarette, and dual use in a dose-response manner. Social media use for ≥2 hours/day (vs. 1-<30 minutes) was associated with increased cigarette (AOR 2.76 [95% confidence interval 2.19 to 3.48]), e-cigarette (3.24 [2.59 to 4.05]), and dual use (ARRR 4.11 [2.77 to 6.08]). The risk of cigarette use among 30 minutes-<1 hour/day users (vs. non-users) were smaller in those with high versus low parental education (ARDs 1.4% vs. 12.4%). Similar findings were observed across the higher time categories. Analyses using time-use-diaries, in complete case samples, and with additional adjustment for baseline outcome measures generally revealed similar findings.

CONCLUSIONS

After accounting for observed confounders and potential reverse causality, findings suggest social media use increases the risk of cigarette, e-cigarette, and dual use in a dose-response manner. Guidance addressing adolescent online safety should be prioritized.

IMPLICATIONS

This study's identification of a dose-response relationship and differential effects across socioeconomic groups, could assist in the development of guidance on time spent on social media. The adverse effects of social media use on adolescent cigarette, e-cigarette, and dual use supports legislation aimed at promoting adolescent online safety. Study findings strengthen calls to prohibit social media marketing of nicotine-related products and importantly highlight the need to increase awareness and understanding of the underlying algorithms which drive adolescent exposure to nicotine-related content on social media to ensure they are functioning in a way that best serves the adolescent population.

Building Learning Healthcare Systems for Critical Care Medicine

Learning healthcare systems are an evolving way of integrating informatics, analytics, and continuous improvement into daily practice in healthcare. This article discusses strategies to build learning healthcare systems for critical care medicine.

The association between prenatal cannabis use and congenital birth defects in offspring: A cumulative meta-analysis

OBJECTIVE

To examine the association between prenatal cannabis use and structural birth defects in exposed offspring.

METHODS

In line with the preregistered protocol (PROSPERO: CRD42022368623), we systematically searched PubMed/Medline, CINHAL, EMBASE, Web of Science, ProQuest, Psych-Info, and Google Scholar for published articles until 25 January 2024. The methodological quality of the included studies was appraised by the Newcastle-Ottawa Quality Assessment Scale (NOS). A meta-analysis was carried out to report the pooled effect estimates from the included studies. We further performed subgroup, leave-one-out sensitivity, and meta-regression analyses, which increased the robustness of our findings.

RESULTS

In this cumulative meta-analysis, thirty-six observational studies, consisting of 18 case-control and 18 cohort studies, with 230, 816 cases of birth defects and 18,049,013 controls (healthy babies) were included in the final analysis. We found that offspring exposed to maternal prenatal cannabis are at greater risks of a wide range of structural birth defects: cardiovascular/heart [OR = 2.35: 95 % CI 1.63 - 3.39], gastrointestinal [OR = 2.42: 95 % CI 1.61 - 3.64], central nervous system [OR = 2.87: 95 % CI 1.51 - 5.46], genitourinary [OR = 2.39: 95 % CI 1.11 - 5.17], and any (unclassified) birth defects [OR = 1.25: 95 % CI 1.12 - 1.41].

CONCLUSION

The findings from the current study suggest that maternal prenatal cannabis exposure is associated with a higher risk of different forms of structural birth defects in offspring. The findings underscore the significance of implementing preventive strategies, including enhanced preconception counselling, to address cannabis use during pregnancy and mitigate the risk of birth defects in offspring.

Assessing cardiovascular disease risk in women with a history of hypertensive disorders of pregnancy: A guidance paper for studies using administrative data

BACKGROUND

Hypertensive disorders of pregnancy (HDP) are a major cause of maternal morbidity and mortality, and their association with increased cardiovascular disease (CVD) risk represents a major public health concern. However, assessing CVD risk in women with a history of these conditions presents unique challenges, especially when studies are carried out using routinely collected data.

OBJECTIVES

To summarise and describe key challenges related to the design and conduct of administrative studies assessing CVD risk in women with a history of HDP and provide concrete recommendations for addressing them in future research.

METHODS

This is a methodological guidance paper.

RESULTS

Several conceptual and methodological factors related to the data-generating mechanism and study conceptualisation, design/data management and analysis, as well as the interpretation and reporting of study findings should be considered and addressed when designing and carrying out administrative studies on this topic. Researchers should develop an a priori conceptual framework within which the research question is articulated, important study variables are identified and their interrelationships are carefully considered.

CONCLUSIONS

To advance our understanding of CVD risk in women with a history of HDP, future studies should carefully consider and address the conceptual and methodological considerations outlined in this guidance paper. In highlighting these challenges, and providing specific recommendations for how to address them, our goal is to improve the quality of research carried out on this topic.

Advances in methodologies of negative controls: a scoping review

OBJECTIVES

Negative controls are considered an important tool to mitigate biases in observational studies. The aim of this scoping review was to summarize current methodologies of negative controls (both negative control exposure [NCE] and negative control outcome [NCO]).

STUDY DESIGN AND SETTING

We searched PubMed, Web of Science, Embase, and Cochrane Library (up to March 9, 2023) for articles on methodologies of negative controls. Two reviewers selected eligible studies and collected relevant data independently and in duplicate. We reported total numbers and percentages, and summarized methodologies narratively.

RESULTS

A total of 37 relevant methodological articles were included in our review. These publications covered NCE (n = 11, 29.8%), NCO (n = 13, 35.1%), or both (n = 13, 35.1%), with most focused on bias detection (n = 14, 37.8%), bias correction (n = 16, 43.3%), and P value or confidence interval (CI) calibration (n = 5, 13.5%). For the two remaining articles (5.4%), one discussed bias detection and P value or CI calibration and the other covered all the three functions. For bias detection, the existence of an association between the NCE (NCO) and outcome (exposure) variables of interest simply indicates that results may suffer from confounding bias, selection bias and/or information bias. For bias correction, however, the algorithms of negative control methods need more stringent assumptions such as rank preservation, monotonicity, and linearity.

CONCLUSION

Negative controls can be leveraged for bias detection, P value or CI calibration, and bias correction, among which bias correction has been the most studied methodologically. The current available methods need some stringent assumptions to detect or remove bias. More methodological research is needed to optimize the use of negative controls.

New diagnosis of multiple sclerosis in the setting of recent Sinopharm COVID-19 vaccine (BBIBP-CorV) exposure: A series of clinical cases and updated review of the literature

Background: Multiple sclerosis (MS) is the most common cause of non-traumatic disability in young individuals. There are limited reports of developing demyelinating events following the coronavirus disease 2019 (COVID-19) vaccination. Methods: We reported all individuals (n = 8) with new MS diagnoses with recent exposure (≤ 6 weeks) to the Sinopharm (BBIBP-CorV) vaccine between September 2021 and June 2022. We also reviewed the related literature published as of September 2023. Results: Of 338 newly diagnosed patients with MS who attended our tertiary referral MS center during the study period, 8 (2.36%) had their first demyelinating attack with a median interval of 2 [2.0, 4.0] weeks following the Sinopharm vaccine (sex ratio 1:1, median age: 20.5 [18.0, 27.0] years). No personal or family history of autoimmune/neurological disorders was documented, except for one patient's history of a previous potential demyelinating event and another's family history of immune thrombocytopenic purpura (ITP). All patients had demyelinating brain MRI lesions, and 4 had cervical spinal cord involvement. The brain areas most commonly affected were the periventricular and subcortical regions. Positive oligoclonal bands (OCBs) in all patients supported the MS diagnosis. All patients were diagnosed with relapsing-remitting MS and received intravenous methylprednisolone (IVMP) alone or in combination with plasma exchange (3/8). Rituximab was the most frequently used disease-modifying treatment (3/8). Conclusion: This study provides preliminary evidence of a potential association between the Sinopharm vaccine and the initial manifestations of MS. However, further larger-scale studies with control groups and long-term follow-ups are needed to confirm this association and determine the underlying mechanisms.

Is Simpler Always Better? The Case for Going Beyond the Amyloid Hypothesis in Alzheimer's Disease

Alzheimer's disease (AD) research has been dominated by the single-factor amyloid hypothesis in the last decades. Several other hypotheses have been proposed and increasingly attract attention considering the limited success of amyloid-based therapeutic strategies. Surprisingly, most published alternative etiological hypotheses for AD are similarly single-factor hypotheses, such as vascular, metabolic, mitochondrial, infectious, and inflammatory hypotheses, but the existence of so many different hypotheses suggests that AD is most likely a complex, multifactorial disorder. This inventory of different etiological hypotheses will hopefully help the field to move forward with explanatory models that consider the multifaceted aspects of this devastating disorder.

GRADE GUIDANCE 38: Updated guidance for rating up certainty of evidence due to a dose-response gradient

INTRODUCTION

This updated guidance from the Grading of Recommendations Assessment, Development, and Evaluation addresses rating up certainty of evidence due to a dose-response gradient (DRG) observed in synthesis of intervention and exposure studies.

STUDY DESIGN AND SETTING

This guidance was developed using iterative discussions and consensus in multiple meetings and was presented to attendees of the Grading of Recommendations Assessment, Development, and Evaluation Working Group meeting for feedback in November 2022 and for final approval in May 2023.

RESULTS

The guidance consists of two steps. The first is to determine whether the DRG is credible. We describe five items for assessing credibility: a) is DRG identified using a proper analytical approach; b) is confounding the cause of the DRG; c) is there serious concern about ecological bias; d) is the DRG consistent across studies; and e) is there indirect evidence supporting the DRG. The first two of these items are the most critical. If the DRG was judged to be credible, then the second step is to apply the DRG domain and consider rating up, but only by one level due to the concern about residual confounding.

CONCLUSION

Systematic review authors should only rate up certainty in evidence when a DRG is deemed credible.

Toxic neuropathies

PURPOSE OF REVIEW

Immunotherapy has had a significant impact on the treatment of an increasing number of cancers as well as in inflammatory, rheumatological and gastroenterological conditions.Recreational nitrous oxide use is now a global epidemic. Linezolid is now recommended for the treatment of drug-resistant tuberculosis (TB); neuropathy is a significant cause of morbidity.Global warming will result in increasing toxin exposure, such as ciguatera, in previously unaffected areas.

RECENT FINDINGS

With increasing experience, the pathophysiology underlying the neuropathic complications of these drugs has become clear with guidelines now available, for the complications of immune check-point inhibitors and nitrous oxide toxicity. The optimum dose and duration of treatment for resistant TB with regimens, including linezolid, has been ascertained.

SUMMARY

Although neuropathic complications with immunotherapy are relatively rare, it is essential that they are recognized and treated early. Nitrous oxide toxicity should be in the differential diagnosis for all patients, particularly those of younger age, presenting with a neuropathy or myleo-neuropathy. Ciguatera toxicity is under recognized and its geographical spread will increase due to global warming. Further research is necessary on the mechanisms and treatment of both acute and chronic effects, which at present, are only symptomatic.

Association between Vaccination Status for COVID-19 and the Risk of Severe Symptoms during the Endemic Phase of the Disease

The global health emergency caused by COVID-19 concluded in May 2023, marking the beginning of an endemic phase. This study aimed to evaluate the association between vaccination status and other patient characteristics and the risk of severe disease during this new endemic period. A nationwide cohort study was conducted in Mexico, where we analyzed data from 646 adults who had received positive confirmation of COVID-19 through PCR testing from May to August 2023. The overall risk of severe symptoms in the study sample was 5.3%. The average time elapsed from the last vaccine shot to symptom onset was over six months in all the immunized groups (1, 2 or 3 vaccine doses). Compared to unvaccinated patients, those with three vaccine doses showed an elevated risk of severe symptoms. Advancing age and various chronic comorbidities (specifically cardiovascular, kidney, and obstructive pulmonary conditions) were associated with a heightened risk of severe COVID-19 manifestations. These findings underscore the ongoing seriousness of COVID-19, even in an endemic phase, underscoring the urgent need for tailored interventions aimed at high-risk patients.

Understanding Training Load as Exposure and Dose

Various terms used in sport and exercise science, and medicine, are derived from other fields such as epidemiology, pharmacology and causal inference. Conceptual and nomological frameworks have described training load as a multidimensional construct manifested by two causally related subdimensions: external and internal training load. In this article, we explain how the concepts of training load and its subdimensions can be aligned to classifications used in occupational medicine and epidemiology, where exposure can also be differentiated into external and internal dose. The meanings of terms used in epidemiology such as exposure, external dose, internal dose and dose-response are therefore explored from a causal perspective and their underlying concepts are contextualised to the physical training process. We also explain how these concepts can assist in the validation process of training load measures. Specifically, to optimise training (i.e. within a causal context), a measure of exposure should be reflective of the mediating mechanisms of the primary outcome. Additionally, understanding the difference between intermediate and surrogate outcomes allows for the correct investigation of the effects of exposure measures and their interpretation in research and applied settings. Finally, whilst the dose-response relationship can provide evidence of the validity of a measure, conceptual and computational differentiation between causal (explanatory) and non-causal (descriptive and predictive) dose-response relationships is needed. Regardless of how sophisticated or "advanced" a training load measure (and metric) appears, in a causal context, if it cannot be connected to a plausible mediator of a relevant response (outcome), it is likely of little use in practice to support and optimise the training process.

Association between SARS-CoV-2 infection and newly diagnosed hypertension during pregnancy: prospective, population based cohort study

Objective

To study the association between SARS-CoV-2 infection and newly diagnosed hypertension during pregnancy.

Design

Prospective, population based cohort study.

Setting

All singleton pregnancies after 22 completed gestational weeks registered in the Swedish Pregnancy Register and the Medical Birth Registry of Norway, from 1 March 2020 to 24 May 2022.

Participants

312 456 individuals available for analysis (201 770 in Sweden and 110 686 in Norway), with pregnancies that reached 42 completed gestational weeks by the end of follow-up in the pregnancy registries, excluding individuals with SARS-CoV-2 infection before pregnancy and those with a diagnosis of pre-existing hypertension or onset of hypertension before 20 gestational weeks.

Main outcome measures

Newly diagnosed hypertension during pregnancy was defined as a composite outcome of a diagnosis of gestational hypertension, pre-eclampsia, HELLP (haemolysis, elevated liver enzymes, low platelets) syndrome, or eclampsia, from gestational week 20 to one week after delivery. The association between SARS-CoV-2 infection and hypertension during pregnancy was investigated with a stratified Cox proportional hazard model, adjusting for maternal age, body mass index, parity, smoking, region of birth, education, income, coexisting medical conditions, previous hypertension during pregnancy, number of healthcare visits during the past year, and vaccination against SARS-CoV-2. Pre-eclampsia was also analysed as a separate outcome.

Results

Of 312 456 individuals available for analysis, 8% (n=24 566) had SARS-CoV-2 infection any time during pregnancy, 6% (n=18 051) had a diagnosis of hypertension during pregnancy, and 3% (9899) had pre-eclampsia. SARS-CoV-2 infection during pregnancy was not associated with an increased risk of hypertension during pregnancy (adjusted hazard ratio 0.99, 95% confidence interval 0.93 to 1.04) or pre-eclampsia (0.98, 0.87 to 1.10). The results were similar for SARS-CoV-2 infection in all gestational trimesters and in different time periods that corresponded to dominance of different variants of the SARS-CoV-2 virus.

Conclusions

This population based study did not find any evidence of an association between SARS-CoV-2 infection during pregnancy and an increased risk of hypertension during pregnancy or pre-eclampsia.

Subjective and objective sleep and circadian parameters as predictors of depression-related outcomes: A machine learning approach in UK Biobank

BACKGROUND

Sleep and circadian disruption are associated with depression onset and severity, but it is unclear which features (e.g., sleep duration, chronotype) are important and whether they can identify individuals showing poorer outcomes.

METHODS

Within a subset of the UK Biobank with actigraphy and mental health data (n = 64,353), penalised regression identified the most useful of 51 sleep/rest-activity predictors of depression-related outcomes; including case-control (Major Depression (MD) vs. controls; postnatal depression vs. controls) and within-case comparisons (severe vs. moderate MD; early vs. later onset, atypical vs. typical symptoms; comorbid anxiety; suicidality). Best models (of lasso, ridge, and elastic net) were selected based on Area Under the Curve (AUC).

RESULTS

For MD vs. controls (n_(MD) = 24,229; n_(control) = 40,124), lasso AUC was 0.68, 95 % confidence interval (CI) 0.67-0.69. Discrimination was reasonable for atypical vs. typical symptoms (n_(atypical) = 958; n_(typical) = 18,722; ridge: AUC 0.74, 95 % CI 0.71-0.77) but poor for remaining models (AUCs 0.59-0.67). Key predictors across most models included: difficulty getting up, insomnia symptoms, snoring, actigraphy-measured daytime inactivity and lower morning activity (~8 am). In a distinct subset (n = 310,718), the number of these factors shown was associated with all depression outcomes.

LIMITATIONS

Analyses were cross-sectional and in middle-/older aged adults: comparison with longitudinal investigations and younger cohorts is necessary.

DISCUSSION

Sleep and circadian measures alone provided poor to moderate discrimination of depression outcomes, but several characteristics were identified that may be clinically useful. Future work should assess these features alongside broader sociodemographic, lifestyle and genetic features.

Beyond the biomedical, towards the agentic: A paradigm shift for population health science

Life expectancy in the United States is decreasing. Health disparities are widening. Growing evidence for and integration of social and structural determinants into theory and practice has not yet improved outcomes. The COVID-19 pandemic reinforced the fact. In this paper, we argue that the biomedical model and its underlying scientific paradigm of causal determinism, which currently dominate population health, cannot meet population health needs. While criticism of the biomedical model is not new, this paper advances the field by going beyond criticism to recognize the need for a paradigm shift. In the first half of the paper, we present a critical analysis of the biomedical model and the paradigm of causal determinism. In the second half, we outline the agentic paradigm and present a structural model of health based on generalizable, group-level processes. We use the experience of the COVID-19 pandemic to illustrate the practical applications of our model. It will be important for future work to investigate the empirical and pragmatic applications of our structural model of population health.

Improving interventional causal predictions in regulatory risk assessment

In 2022, the US EPA published an important risk assessment concluding that "Compared to the current annual standard, meeting a revised annual standard with a lower level is estimated to reduce PM2.5-associated health risks in the 30 annually-controlled study areas by about 7-9% for a level of 11.0 µg/m3… and 30-37% for a level of 8.0 µg/m3." These are interventional causal predictions: they predict percentage reductions in mortality risks caused by different counterfactual reductions in fine particulate (PM2.5) levels. Valid causal predictions are possible if: (1) Study designs are used that can support valid causal inferences about the effects of interventions (e.g., quasi-experiments with appropriate control groups); (2) Appropriate causal models and methods are used to analyze the data; (3) Model assumptions are satisfied (at least approximately); and (4) Non-causal sources of exposure-response associations such as confounding, measurement error, and model misspecification are appropriately modeled and adjusted for. This paper examines two long-term mortality studies selected by the EPA to predict reductions in PM2.5-associated risk. Both papers use Cox proportional hazards (PH) models. For these models, none of these four conditions is satisfied, making it difficult to interpret or validate their causal predictions. Scientists, reviewers, regulators, and members of the public can benefit from more trustworthy and credible risk assessments and causal predictions by insisting that risk assessments supporting interventional causal conclusions be based on study designs, methods, and models that are appropriate for predicting effects caused by interventions.

Re-assessing human mortality risks attributed to PM2.5-mediated effects of agricultural ammonia

How can and should epidemiologists and risk assessors assemble and present evidence for causation of mortality or morbidities by identified agents such as fine particulate matter or other air pollutants? As a motivating example, some scientists have warned recently that ammonia from the production of meat significantly increases human mortality rates in exposed populations by increasing the ambient concentration of fine particulate matter (PM2.5) in air. We reexamine the support for such conclusions, including quantitative calculations that attribute deaths to PM2.5 air pollution by applying associational results such as relative risks, odds ratios, or slope coefficients from regression models to predict the effects on mortality or morbidity of reducing PM2.5 exposures. Taking an outside perspective from the field of causal artificial intelligence (CAI), we conclude that these attribution calculations are methodologically unsound. They produce unreliable conclusions because they ignore an essential distinction between differences in outcomes observed at different levels of exposure and changes in outcomes caused by changing exposure. We find that multiple studies that have examined associations between changes over time in particulate exposure and mortality risk instead of differences in exposures and corresponding mortality risks have found no clear evidence that observed changes in exposure help to predict or explain subsequent changes in mortality risks. We conclude that there is no sound theoretical or empirical reason to believe that reducing ammonia emissions from farms has reduced or would reduce human mortality risks. More generally, applying CAI principles and methods can potentially improve current widespread practices of unsound causal inferences and policy-relevant causal claims that are made without the benefit of formal causal analysis in air pollution health effects research and in other areas of applied epidemiology and public health risk assessment.

Low level exposure to hydrogen sulfide: a review of emissions, community exposure, health effects, and exposure guidelines

Hydrogen sulfide (H2S) is a toxic gas that is well-known for its acute health risks in occupational settings, but less is known about effects of chronic and low-level exposures. This critical review investigates toxicological and experimental studies, exposure sources, standards, and epidemiological studies pertaining to chronic exposure to H2S from both natural and anthropogenic sources. H2S releases, while poorly documented, appear to have increased in recent years from oil and gas and possibly other facilities. Chronic exposures below 10 ppm have long been associated with odor aversion, ocular, nasal, respiratory and neurological effects. However, exposure to much lower levels, below 0.03 ppm (30 ppb), has been associated with increased prevalence of neurological effects, and increments below 0.001 ppm (1 ppb) in H2S concentrations have been associated with ocular, nasal, and respiratory effects. Many of the studies in the epidemiological literature are limited by exposure measurement error, co-pollutant exposures and potential confounding, small sample size, and concerns of representativeness, and studies have yet to consider vulnerable populations. Long-term community-based studies are needed to confirm the low concentration findings and to refine exposure guidelines. Revised guidelines that incorporate both short- and long-term limits are needed to protect communities, especially sensitive populations living near H2S sources.

Understanding clinical outcome measures reported in HIV pregnancy studies involving antiretroviral-naive and antiretroviral-experienced women

HIV infection is a clinically significant public health disease and contributes to increased risk of maternal and fetal morbidity and mortality. HIV pregnancy studies use outcome measures as metrics to show how people with HIV feel, function, or survive. These endpoints are crucial for tracking the evolution of HIV illness over time, assessing the effectiveness of antiretroviral therapy (ART), and comparing outcomes across studies. Although the need for ideal outcome measures is widely acknowledged, selecting acceptable outcome measures for these HIV pregnancy studies can be challenging. We discuss the many outcome measures that have been implemented over time to assess HIV in pregnancy studies, their benefits, and drawbacks. Finally, we offer suggestions for improving the reporting of outcome measures in HIV in pregnancy studies. Medical professionals can best care for pregnant women living with HIV receiving ART by having a thorough understanding of these outcome metrics.

How to Distinguish Correlation From Causation in Orthopaedic Research

Correlations in observational studies are commonly misinterpreted as causation. Although correlation is necessary to establish a causal relationship between two variables, correlations may also arise due to chance, reverse causality, or confounding. There are several methods available to orthopaedic researchers to determine whether the observed correlations are causal. These methods depend on the key components of the study including, but not limited to, study design and data availability on confounders. In this article, we illustrate the main concepts surrounding correlation and causation using intuitive real-world examples from the orthopaedic literature. Please visit the following https://www.youtube.com/watch?v=WW7pFudZbHA&t=52s for a video that explains the highlights of the paper in practical terms.