The role of causal reasoning in understanding Simpson's paradox, Lord's paradox, and the suppression effect: covariate selection in the analysis of observational studies

Tu et al present an analysis of the equivalence of three paradoxes, namely, Simpson's, Lord's, and the suppression phenomena. They conclude that all three simply reiterate the occurrence of a change in the association of any two variables when a third variable is statistically controlled for. This is not surprising because reversal or change in magnitude is common in conditional analysis. At the heart of the phenomenon of change in magnitude, with or without reversal of effect estimate, is the question of which to use: the unadjusted (combined table) or adjusted (sub-table) estimate. Hence, Simpson's paradox and related phenomena are a problem of covariate selection and adjustment (when to adjust or not) in the causal analysis of non-experimental data. It cannot be overemphasized that although these paradoxes reveal the perils of using statistical criteria to guide causal analysis, they hold neither the explanations of the phenomenon they depict nor the pointers on how to avoid them. The explanations and solutions lie in causal reasoning which relies on background knowledge, not statistical criteria

Reported associations between asthma and acute lymphoblastic leukemia: insights from a hybrid simulation study.

Numerous studies have reported a protective association between asthma and acute lymphoblastic leukemia (ALL), but the causal structure of this association remains unclear. We present a hybrid simulation to examine the compatibility of this association with uncontrolled confounding by infection or another unmeasured factor. We generated a synthetic cohort using inputs on the interrelations of asthma, ALL, infections, and other suggested risk factors from the literature and the Danish National Birth Cohort. We computed odds ratios (ORs) between asthma and ALL in the synthetic cohort with and without adjustment for infections and other (including unmeasured) confounders. Only if infection was an extremely strong risk factor for asthma (OR of 10) and an extremely strong protective factor against ALL (OR of 0.1) was the asthma-ALL association compatible with the literature (OR of 0.78). Similarly, strong uncontrolled confounding by an unmeasured factor could downwardly bias the asthma-ALL association, but not enough to replicate findings in the literature. This investigation illustrates that the reported protective association between asthma and ALL is unlikely to be entirely due to uncontrolled confounding by infections or an unmeasured confounder alone. Simulation can be used to advance our understanding of risk factors for rare outcomes as demonstrated by this study

Development and validation of a prediction equation for body fat percentage from measured BMI: a supervised machine learning approach.

Body mass index is a widely used but poor predictor of adiposity in populations with excessive fat-free mass. Rigorous predictive models validated specifically in a nationally representative sample of the US population and that could be used for calibration purposes are needed. The objective of this study was to develop and validate prediction equations of body fat percentage obtained from Dual Energy X-ray Absorptiometry using body mass index (BMI) and socio-demographics. We used the National Health and Nutrition Examination Survey (NHANES) data from 5931 and 2340 adults aged 20 to 69 in 1999-2002 and 2003-2006, respectively. A supervised machine learning using ordinary least squares and a validation set approach were used to develop and select best models based on R2 and root mean square error. We compared our findings with other published models and utilized our best models to assess the amount of bias in the association between predicted body fat and elevated low-density lipoprotein (LDL). Three models included BMI, BMI2, age, gender, education, income, and interaction terms and produced R-squared values of 0.87 and yielded the smallest standard errors of estimation. The amount of bias in the association between predicted BF% and elevated LDL from our best model was -0.005. Our models provided strong predictive abilities and low bias compared to most published models. Its strengths rely on its simplicity and its ease of use in low-resource settings

The impact of human development on individual health: a causal mediation analysis examining pathways through education and body mass index

ABSTRACT Background. The macro environment we live in projects what we can achieve and how we behave, and in turn, shapes our health in complex ways. Policymaking will benefit from insights into the mechanisms underlying how national socioeconomic context affects health. This study examined the impact of human development on individual health and the possible mediating roles of education and body mass index (BMI). Methods. We analyzed World Health Survey data on 109,448 participants aged 25 or older from 42 low-and middle-income countries with augmented human development index (HDI) in 1990. We used principal components method to create a health score based on measures from eight health state domains, used years of schooling as education indicator and calculated BMI from self-reported height and weight. We used causal mediation analysis technique with random intercepts to account for the multilevel structure. 6.62,] for females). We found a small positive effect of HDI on health via education across reference HDI levels (b ranging from 0.24 to 0.29 for males and 0.40 to 0.49 for females) but not via pathways involving BMI only. Conclusion. Human development has a non-linear effect on individual health, but the impact appears to be mainly through pathways other than education and BMI

Variability of residents’ ratings of faculty’s teaching performance measured by fiveand seven-point response scales

Background: Medical faculty’s teaching performance is often measured using residents’ feedback, collected by questionnaires. Researchers extensively studied the psychometric qualities of resulting ratings. However, these studies rarely consider the number of response categories and its consequences for residents’ ratings of faculty’s teaching performance. We compared the variability of residents’ ratings measured by five- and seven-point response scales. Methods: This retrospective study used teaching performance data from Dutch anaesthesiology residency training programs. Questionnaires with five- and seven-point response scales from the extensively studied System for Evaluation of Teaching Qualities (SETQ) collected the ratings. We inspected ratings’ variability by comparing standard deviations, interquartile ranges, and frequency (percentage) distributions. Relevant statistical tests were used to test differences in frequency distributions and teaching performance scores. Results: We examined 3379 residents’ ratings and 480 aggregated faculty scores. Residents used the additional response categories provided by the seven-point scale – especially

Maternal pre-pregnancy obesity and timing of puberty in sons and daughters: a population-based cohort study.

BackgroundIn many countries, an increased prevalence of obesity in pregnancy has coincided with a declining pubertal age. We aimed to explore the potential effect of maternal pre-pregnancy overweight and obesity on timing of puberty in sons and daughters.MethodsBetween 2012 and 2018, 15 819 of 22 439 invited children from the Danish National Birth Cohort, born 2000-03, provided half-yearly information from the age of 11 years on the pubertal milestones: Tanner stages, voice break, first ejaculation, menarche, acne and axillary hair. We estimated adjusted mean monthly differences (with 95% confidence intervals) in age at attaining the pubertal milestones for children exposed to maternal pre-pregnancy obesity [body mass index (BMI) ≥30.0 kg/m2] or overweight (BMI 25.0 to 29.9 kg/m2) with normal weight (BMI 18.5 to 24.9 kg/m2) as reference. In mediation analysis, we explored whether childhood BMI at age 7 years mediated the associations.ResultsMaternal pre-pregnancy obesity was associated with earlier age at attaining most pubertal milestones in sons, and pre-pregnancy overweight and obesity were associated with earlier age at attaining all pubertal milestones in daughters. When combining all pubertal milestones, pre-pregnancy obesity [sons: -1.5 (-2.5, -0.4) months; daughters: -3.2 (-4.2, -2.1) months] and overweight [daughters only: -2.6 (-3.3, -1.8) months] were associated with earlier timing of puberty. The associations in sons were completely mediated by higher childhood BMI and partly so in daughters.ConclusionsMaternal pre-pregnancy obesity appears to lower timing of puberty through childhood obesity in sons and mainly through other mechanisms in daughters