Depicting deterministic variables within directed acyclic graphs (DAGs): An aid for identifying and interpreting causal effects involving derived variables and compositional data.

Deterministic variables are variables that are functionally determined by one or more parent variables. They commonly arise when a variable has been functionally created from one or more parent variables, as with derived variables, and in compositional data, where the 'whole' variable is determined from its 'parts'. This article introduces how deterministic variables may be depicted within directed acyclic graphs (DAGs) to help with identifying and interpreting causal effects involving derived variables and/or compositional data. We propose a two-step approach in which all variables are initially considered, and a choice is made whether to focus on the deterministic variable or its determining parents. Depicting deterministic variables within DAGs brings several benefits. It is easier to identify and avoid misinterpreting tautological associations, i.e., self-fulfilling associations between deterministic variables and their parents, or between sibling variables with shared parents. In compositional data, it is easier to understand the consequences of conditioning on the 'whole' variable, and correctly identify total and relative causal effects. For derived variables, it encourages greater consideration of the target estimand and greater scrutiny of the consistency and exchangeability assumptions. DAGs with deterministic variables are a useful aid for planning and interpreting analyses involving derived variables and/or compositional data.

Testing the causal relationships of physical activity and sedentary behaviour with mental health and substance use disorders: a Mendelian randomisation study.

Observational studies suggest that physical activity can reduce the risk of mental health and substance use disorders. However, it is unclear whether this relationship is causal or explained by confounding bias (e.g., common underlying causes or reverse causality). We investigated the bidirectional causal relationship of physical activity (PA) and sedentary behaviour (SB) with ten mental health and substance use disorders, applying two-sample Mendelian Randomisation (MR). Genetic instruments for the exposures and outcomes were derived from the largest available, non-overlapping genome-wide association studies (GWAS). Summary-level data for objectively assessed PA (accelerometer-based average activity, moderate activity, and walking) and SB and self-reported moderate-to-vigorous PA were obtained from the UK Biobank. Data for mental health/substance use disorders were obtained from the Psychiatric Genomics Consortium and the GWAS and Sequencing Consortium of Alcohol and Nicotine Use. MR estimates were combined using inverse variance weighted meta-analysis (IVW). Sensitivity analyses were conducted to assess the robustness of the results. Accelerometer-based average PA was associated with a lower risk of depression (b = -0.043, 95% CI: -0.071 to -0.016, effect size[OR] = 0.957) and cigarette smoking (b = -0.026; 95% CI: -0.035 to -0.017, effect size[ß] = -0.022). Accelerometer-based SB decreased the risk of anorexia (b = -0.341, 95% CI: -0.530 to -0.152, effect size[OR] = 0.711) and schizophrenia (b = -0.230; 95% CI: -0.285 to -0.175, effect size[OR] = 0.795). However, we found evidence of reverse causality in the relationship between SB and schizophrenia. Further, PTSD, bipolar disorder, anorexia, and ADHD were all associated with increased PA. This study provides evidence consistent with a causal protective effect of objectively assessed but not self-reported PA on reduced depression and cigarette smoking. Objectively assessed SB had a protective relationship with anorexia. Enhancing PA may be an effective intervention strategy to reduce depressive symptoms and addictive behaviours, while promoting sedentary or light physical activities may help to reduce the risk of anorexia in at-risk individuals.

Head Acceleration Events During Tackle, Ball-Carry, and Ruck Events in Professional Southern Hemisphere Men's Rugby Union Matches: A Study Using Instrumented Mouthguards.

OBJECTIVES: Describe head acceleration events (HAEs) experienced by professional male rugby union players during tackle, ball-carry, and ruck events using instrumented mouthguards (iMGs). DESIGN: Prospective observational cohort. METHODS: Players competing in the 2023 Currie Cup (141 players) and Super Rugby (66 players) seasons wore iMGs. The iMG-recorded peak linear acceleration (PLA) and peak angular acceleration (PAA) were used as in vivo HAE approximations and linked to contact-event data captured using video analysis. Using the maximum PLA and PAA per contact event (HAEmax), ordinal mixed-effects regression models estimated the probabilities of HAEmax magnitude ranges occurring, while accounting for the multilevel data structure. RESULTS: As HAEmax magnitude increased the probability of occurrence decreased. The probability of a HAEmax ≥15g was 0.461 (0.435-0.488) (approximately 1 in every 2) and ≥45g was 0.031 (0.025-0.037) (1 in every 32) during ball carries. The probability of a HAEmax >15g was 0.381 (0.360-0.404) (1 in every 3) and >45g 0.019 (0.015-0.023) (1 in every 53) during tackles. The probability of higher magnitude HAEmax occurring was greatest during ball carries, followed by tackles, defensive rucks and attacking rucks, with some ruck types having similar profiles to tackles and ball carries. No clear differences between positions were observed. CONCLUSION: Higher magnitude HAEmax were relatively infrequent in professional men's rugby union players. Contact events appear different, but no differences were found between positions. The occurrence of HAEmax was associated with roles players performed within contact events, not their actual playing position. Defending rucks may warrant greater consideration in injury prevention research.

Distinct Body Mass Index Trajectories to Young-Adulthood Obesity and Their Different Cardiometabolic Consequences.

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Hepatectomy risk assessment with functional magnetic resonance imaging (HEPARIM).

BACKGROUND: Post hepatectomy liver failure (PHLF) remains a significant risk in patients undergoing curative liver resection for cancer, however currently available PHLF risk prediction investigations are not sufficiently accurate. The Hepatectomy risk assessment with functional magnetic resonance imaging trial (HEPARIM) aims to establish if quantitative MRI biomarkers of liver function & perfusion can be used to more accurately predict PHLF risk and FLR function, measured against indocyanine green (ICG) liver function test. METHODS: HEPARIM is an observational cohort study recruiting patients undergoing liver resection of 2 segments or more, prior to surgery patients will have both Dynamic Gadoxetate-enhanced (DGE) liver MRI and ICG testing. Day one post op ICG testing is repeated and R15 compared to the Gadoxetate Clearance (GC) of the future liver remnant (FLR-GC) as measure by preoperative DGE- MRI which is the primary outcome, and preoperative ICG R15 compared to GC of whole liver (WL-GC) as a secondary outcome. Data will be collected from medical records, biochemistry, pathology and radiology reports and used in a multi-variate analysis to the value of functional MRI and derive multivariant prediction models for future validation. DISCUSSION: If successful, this test will potentially provide an efficient means to quantitatively assess FLR function and PHLF risk enabling surgeons to push boundaries of liver surgery further while maintaining safe practice and thereby offering chance of cure to patients who would previously been deemed inoperable. MRI has the added benefit of already being part of the routine diagnostic pathway and as such would have limited additional burden on patients time or cost to health care systems. (Hepatectomy Risk Assessment With Functional Magnetic Resonance Imaging - Full Text View - ClinicalTrials.gov , n.d.) TRIAL REGISTRATION: ClinicalTrials.gov, ClinicalTrials.gov NCT04705194 - Registered 12th January 2021 - Retrospectively registered.

Early childhood weight gain: Latent patterns and body composition outcomes.

BACKGROUND: Despite early childhood weight gain being a key indicator of obesity risk, we do not have a good understanding of the different patterns that exist. OBJECTIVES: To identify and characterise distinct groups of children displaying similar early-life weight trajectories. METHODS: A growth mixture model captured heterogeneity in weight trajectories between 0 and 60 months in 1390 children in the Avon Longitudinal Study of Parents and Children. Differences between the classes in characteristics and body size/composition at 9 years were investigated. RESULTS: The best model had five classes. The "Normal" (45%) and "Normal after initial catch-down" (24%) classes were close to the 50th centile of a growth standard between 24 and 60 months. The "High-decreasing" (21%) and "Stable-high" (7%) classes peaked at the ~91st centile at 12-18 months, but while the former declined to the ~75th centile and comprised constitutionally big children, the latter did not. The "Rapidly increasing" (3%) class gained weight from below the 50th centile at 4 months to above the 91st centile at 60 months. By 9 years, their mean body mass index (BMI) placed them at the 98th centile. This class was characterised by the highest maternal BMI; highest parity; highest levels of gestational hypertension and diabetes; and the lowest socio-economic position. At 9 years, the "Rapidly increasing" class was estimated to have 68.2% (95% confidence interval [CI] 48.3, 88.1) more fat mass than the "Normal" class, but only 14.0% (95% CI 9.1, 18.9) more lean mass. CONCLUSIONS: Criteria used in growth monitoring practice are unlikely to consistently distinguish between the different patterns of weight gain reported here.

Response to: Simpson's Paradox is suppression, but Lord's Paradox is neither: clarification of and correction to Tu, Gunnell, and Gilthorpe (2008) by Nickerson CA & Brown NJL (https://doi.org/10.1186/1742-7622-5-2).

We commend Nickerson and Brown on their insightful exposition of the mathematical algebra behind Simpson's paradox, suppression and Lord's paradox; we also acknowledge there can be differences in how Lord's paradox is approached analytically, compared to Simpson's paradox and suppression, though not in every example of Lord's paradox. Furthermore, Simpson's paradox, suppression and Lord's paradox ask the same contextual questions, seeking to understand if statistical adjustment is valid and meaningful, identifying which analytical option is correct. In our exposition of this, we focus on the perspective of context, which must invoke causal thinking. From a causal thinking perspective, Simpson's paradox, suppression and Lord's paradox present very similar analytical challenges.

The Association Between Childhood Leukemia and Population Mixing: An Artifact of Focusing on Clusters?

BACKGROUND: Studies investigating the population-mixing hypothesis in childhood leukemia principally use two analytical approaches: (1) nonrandom selection of areas according to specific characteristics, followed by comparisons of their incidence of childhood leukemia with that expected based on the national average; and (2) regression analyses of region-wide data to identify characteristics associated with the incidence of childhood leukemia. These approaches have generated contradictory results. We compare these approaches using observed and simulated data. METHODS: We generated 10,000 simulated regions using the correlation structure and distributions from a United Kingdom dataset. We simulated cases using a Poisson distribution with the incidence rate set to the national average assuming the null hypothesis that only population size drives the number of cases. Selection of areas within each simulated region was based on characteristics considered responsible for elevated infection rates (population density and inward migration) and/or elevated leukemia rates. We calculated effect estimates for 10,000 simulations and compared results to corresponding observed data analyses. RESULTS: When the selection of areas for analysis is based on apparent clusters of childhood leukemia, biased assessments occur; the estimated 5-year incidence of childhood leukemia ranged between zero and eight per 10,000 children in contrast to the simulated two cases per 10,000 children, similar to the observed data. Performing analyses on region-wide data avoids these biases. CONCLUSIONS: Studies using nonrandom selection to investigate the association between childhood leukemia and population mixing are likely to have generated biased findings. Future studies can avoid such bias using a region-wide analytical strategy. See video abstract at, http://links.lww.com/EDE/B431.

PLATOON: Premature Loss of bAby Teeth and its impact On Orthodontic Need - protocol.

OBJECTIVE: To investigate the impact of premature extraction of primary teeth (PEPT) on orthodontic treatment need in a cohort of children participating in the Born in Bradford (BiB) longitudinal birth cohort. DESIGN: Observational, cross-sectional cohort. PARTICIPANTS: We aim to recruit 1000 children aged 7-11 years: 500 with a history of PEPT and 500 matched non-PEPT controls. METHODS: After informed consent/assent, orthodontic records will be collected, including extra and intra-oral photographs and alginate impressions for study models. Participants will also complete a measure of oral health-related quality of life (COHIP-SF 19). The records will be used to quantify space loss, identify other occlusal anomalies and assess orthodontic treatment need using the Index of Orthodontic Treatment Need. For each outcome, summary statistics will be calculated and the data for children with and without PEPT compared. The records of the children identified to be in need of orthodontic treatment will be examined by an expert orthodontic panel to judge if this treatment should be undertaken at the time of the records or delayed until the early permanent dentition. Collecting robust records in the mixed dentition provides the clinical basis to link each stage of the causal chain and enable the impact of PEPT on orthodontic need to be characterised. This study is the first to provide the foundations for future longitudinal data collection allowing the long-term impact of PEPT to be studied.

Translating HbA1c measurements into estimated average glucose values in pregnant women with diabetes.

AIMS/HYPOTHESIS: This study aimed to examine the relationship between average glucose levels, assessed by continuous glucose monitoring (CGM), and HbA1c levels in pregnant women with diabetes to determine whether calculations of standard estimated average glucose (eAG) levels from HbA1c measurements are applicable to pregnant women with diabetes. METHODS: CGM data from 117 pregnant women (89 women with type 1 diabetes; 28 women with type 2 diabetes) were analysed. Average glucose levels were calculated from 5-7 day CGM profiles (mean 1275 glucose values per profile) and paired with a corresponding (±1 week) HbA1c measure. In total, 688 average glucose-HbA1c pairs were obtained across pregnancy (mean six pairs per participant). Average glucose level was used as the dependent variable in a regression model. Covariates were gestational week, study centre and HbA1c. RESULTS: There was a strong association between HbA1c and average glucose values in pregnancy (coefficient 0.67 [95% CI 0.57, 0.78]), i.e. a 1% (11 mmol/mol) difference in HbA1c corresponded to a 0.67 mmol/l difference in average glucose. The random effects model that included gestational week as a curvilinear (quadratic) covariate fitted best, allowing calculation of a pregnancy-specific eAG (PeAG). This showed that an HbA1c of 8.0% (64 mmol/mol) gave a PeAG of 7.4-7.7 mmol/l (depending on gestational week), compared with a standard eAG of 10.2 mmol/l. The PeAG associated with maintaining an HbA1c level of 6.0% (42 mmol/mol) during pregnancy was between 6.4 and 6.7 mmol/l, depending on gestational week. CONCLUSIONS/INTERPRETATION: The HbA1c-average glucose relationship is altered by pregnancy. Routinely generated standard eAG values do not account for this difference between pregnant and non-pregnant individuals and, thus, should not be used during pregnancy. Instead, the PeAG values deduced in the current study are recommended for antenatal clinical care.

Modelling height in adolescence: a comparison of methods for estimating the age at peak height velocity.

BACKGROUND: Controlling for maturational status and timing is crucial in lifecourse epidemiology. One popular non-invasive measure of maturity is the age at peak height velocity (PHV). There are several ways to estimate age at PHV, but it is unclear which of these to use in practice. AIM: To find the optimal approach for estimating age at PHV. SUBJECTS AND METHODS: Methods included the Preece & Baines non-linear growth model, multi-level models with fractional polynomials, SuperImposition by Translation And Rotation (SITAR) and functional data analysis. These were compared through a simulation study and using data from a large cohort of adolescent boys from the Christ's Hospital School. RESULTS: The SITAR model gave close to unbiased estimates of age at PHV, but convergence issues arose when measurement error was large. Preece & Baines achieved close to unbiased estimates, but shares similarity with the data generation model for our simulation study and was also computationally inefficient, taking 24 hours to fit the data from Christ's Hospital School. Functional data analysis consistently converged, but had higher mean bias than SITAR. Almost all methods demonstrated strong correlations (r > 0.9) between true and estimated age at PHV. CONCLUSIONS: Both SITAR or the PBGM are useful models for adolescent growth and provide unbiased estimates of age at peak height velocity. Care should be taken as substantial bias and variance can occur with large measurement error.

Model Selection of the Effect of Binary Exposures over the Life Course.

Epidemiologists are often interested in examining the effect on a later-life outcome of an exposure measured repeatedly over the life course. When different hypotheses for this effect are proposed by competing theories, it is important to identify those most supported by observed data as a first step toward estimating causal associations. One method is to compare goodness-of-fit of hypothesized models with a saturated model, but it is unclear how to judge the "best" out of two hypothesized models that both pass criteria for a good fit. We developed a new method using the least absolute shrinkage and selection operator to identify which of a small set of hypothesized models explains most of the observed outcome variation. We analyzed a cohort study with repeated measures of socioeconomic position (exposure) through childhood, early- and mid-adulthood, and body mass index (outcome) measured in mid-adulthood. We confirmed previous findings regarding support or lack of support for the following hypotheses: accumulation (number of times exposed), three critical periods (only exposure in childhood, early- or mid-adulthood), and social mobility (transition from low to high socioeconomic position). Simulations showed that our least absolute shrinkage and selection operator approach identified the most suitable hypothesized model with high probability in moderately sized samples, but with lower probability for hypotheses involving change in exposure or highly correlated exposures. Identifying a single, simple hypothesis that represents the specified knowledge of the life course association allows more precise definition of the causal effect of interest.

Platelet-derived growth factor maintains stored calcium through a nonclustering Orai1 mechanism but evokes clustering if the endoplasmic reticulum is stressed by store depletion.

RATIONALE: Calcium entry through Orai1 channels drives vascular smooth muscle cell migration and neointimal hyperplasia. The channels are activated by the important growth factor platelet-derived growth factor (PDGF). Channel activation is suggested to depend on store depletion, which redistributes and clusters stromal interaction molecule 1 (STIM1), which then coclusters and activates Orai1. OBJECTIVE: To determine the relevance of STIM1 and Orai1 redistribution in PDGF responses. METHODS AND RESULTS: Vascular smooth muscle cells were cultured from human saphenous vein. STIM1 and Orai1 were tagged with green and red fluorescent proteins to track them in live cells. Under basal conditions, the proteins were mobile but mostly independent of each other. Inhibition of sarco-endoplasmic reticulum calcium ATPase led to store depletion and dramatic redistribution of STIM1 and Orai1 into coclusters. PDGF did not evoke redistribution, even though it caused calcium release and Orai1-mediated calcium entry in the same time period. After chemical blockade of Orai1-mediated calcium entry, however, PDGF caused redistribution. Similarly, mutagenic disruption of calcium flux through Orai1 caused PDGF to evoke redistribution, showing that calcium flux through the wild-type channels had been filling the stores. Acidification of the extracellular medium to pH 6.4 caused inhibition of Orai1-mediated calcium entry and conferred capability for PDGF to evoke complete redistribution and coclustering. CONCLUSIONS: The data suggest that PDGF has a nonclustering mechanism by which to activate Orai1 channels and maintain calcium stores replete. Redistribution and clustering become important, however, when the endoplasmic reticulum stress signal of store depletion arises, for example when acidosis inhibits Orai1 channels.

Capturing changes in dietary patterns among older adults: a latent class analysis of an ageing Irish cohort.

OBJECTIVE: Data-driven approaches to dietary patterns are under-utilized; latent class analyses (LCA) are particularly rare. The present study used an LCA to identify subgroups of people with similar dietary patterns, explore changes in dietary patterns over a 10-year period and relate these dynamics to sociodemographic factors and health outcomes. DESIGN: The 1998 baseline and 2008 follow-up of the Cork and Kerry Diabetes and Heart Disease Study. Diets were assessed with a standard FFQ. LCA, under the assumption of conditional independence, was used to identify mutually exclusive subgroups with different dietary patterns, based on food group consumption. SETTING: Republic of Ireland. SUBJECTS: Men and women aged 50-69 years at baseline (n 923) and at 10-year follow-up (n 320). RESULTS: Three dietary classes emerged: Western, Healthy and Low-Energy. Significant differences in demographic, lifestyle and health outcomes were associated with class membership. Between baseline and follow-up most people remained 'stable' in their dietary class. Most of those who changed class moved to the Healthy class. Higher education was associated with transition to a healthy diet; lower education was associated with stability in an unhealthy pattern. Transition to a healthy diet was associated with higher CVD risk factors at baseline: respondents were significantly more likely to be smokers, centrally obese and to have hypertension (non-significant). CONCLUSIONS: LCA is useful for exploring dietary patterns transitions. Understanding the predictors of longitudinal stability/transitions in dietary patterns will help target public health initiatives by identifying subgroups most/least likely to change and most/least likely to sustain a change.

Time to begin adjuvant chemotherapy and survival in breast cancer patients: a retrospective observational study using latent class analysis.

The analysis of time to treatment data and the evaluation of subsequent effects on health outcomes can be complex due to the nature of the data and the relationships amongst the variables. This study proposes an alternative method of analyzing such data using latent class analysis (LCA). The association between time to begin adjuvant chemotherapy after breast cancer surgery and survival was investigated using both "traditional" regression analysis and LCA. Women with breast cancer undergoing surgery and subsequent adjuvant chemotherapy in two English regions between January 01, 1998 and December 31, 2004 were identified from a linked cancer registry-Hospital Episode Statistics dataset (n = 10,366). Patient, tumor, and treatment information were extracted. A Cox proportional hazards model was used to analyze 5-year survival using regression analysis and LCA. Using "traditional" regression analysis, women beginning chemotherapy >10 weeks after surgery had worse survival in region 1 (HR = 1.49, 95% CI 1.13-1.95 compared to <3 weeks) but not region 2. LCA split the women into three groups representing short, medium, and long waits. The median time to begin chemotherapy in the "long" wait group was 70 (region 1) and 57 (region 2) days. In this group, increased time to begin chemotherapy was associated with worse survival (region 1 HR = 1.15, 95% CI 1.11-1.18; region 2 HR = 1.08, 95% CI 1.03-1.13 per week increase). LCA identified a group of 13-15% of women for whom a longer time to begin chemotherapy had an adverse effect on survival. This methodology provides an excellent framework in which to examine complex associations between the delivery of patient care and patient outcomes.

Cardiac resynchronization therapy in pacemaker-dependent patients with left ventricular dysfunction.

AIMS: Heart failure and left ventricular (LV) systolic dysfunction (LVSD) are common in patients with permanent pacemakers. The aim was to determine if cardiac resynchronization therapy (CRT) at the time of pulse generator replacement (PGR) is of benefit in patients with unavoidable RV pacing and LVSD. METHODS AND RESULTS: Fifty patients with unavoidable RV pacing, LVSD, and mild or no symptoms of heart failure, listed for PGR were randomized 1 : 1 to either standard RV-PGR (comparator) or CRT. The primary endpoint was the difference in change in LV ejection fraction (LVEF) between RV-PGR and CRT groups from baseline to 6 months. Secondary endpoints included peak oxygen consumption, quality of life, and N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels. At 6 months there was a difference in change in median (interquartile range) LVEF [9 (6-12) vs. -1.5 (-4.5 to -0.8)%; P < 0.0001] between the CRT and RV-PGR arms. There were also improvements in exercise capacity (P = 0.007), quality of life (P = 0.03), and NT-proBNP (P = 0.007) in those randomized to CRT. After 809 (729-880) days, 17 patients had died or been hospitalized (6 in CRT group and 11 in the comparator RV-PGR group) and two patients in the RV-PGR arm had required CRT for deteriorating heart failure. Patients with standard RV-PGR had more days in hospital during follow-up than those in the CRT group [4 (2-7) vs. 11 (6-16) days; P = 0.047]. CONCLUSION: Performing CRT in pacemaker patients with unavoidable RV pacing and LVSD but without severe symptoms of heart failure, at the time of PGR, improves cardiac function, exercise capacity, quality of life, and NT-pro-BNP levels.

Age-period-cohort analysis for trends in body mass index in Ireland.

BACKGROUND: Obesity is a growing problem worldwide and can often result in a variety of negative health outcomes. In this study we aim to apply partial least squares (PLS) methodology to estimate the separate effects of age, period and cohort on the trends in obesity as measured by body mass index (BMI). METHODS: Using PLS we will obtain gender specific linear effects of age, period and cohort on obesity. We also explore and model nonlinear relationships of BMI with age, period and cohort. We analysed the results from 7,796 men and 10,220 women collected through the SLAN (Surveys of Lifestyle, attitudes and Nutrition) in Ireland in the years 1998, 2002 and 2007. RESULTS: PLS analysis revealed a positive period effect over the years. Additionally, men born later tended to have lower BMI (-0.026 kg · m(-2) yr(-1), 95% CI: -0.030 to -0.024) and older men had in general higher BMI (0.029 kg · m(-2) yr(-1), 95% CI: 0.026 to 0.033). Similarly for women, those born later had lower BMI (-0.025 kg · m(-2) yr(-1), 95% CI: -0.029 to -0.022) and older women in general had higher BMI (0.029 kg · m(-2) yr(-1), 95% CI: 0.025 to 0.033). Nonlinear analyses revealed that BMI has a substantial curvilinear relationship with age, though less so with birth cohort. CONCLUSION: We notice a generally positive age and period effect but a slightly negative cohort effect. Knowing this, we have a better understanding of the different risk groups which allows for effective public intervention measures to be designed and targeted for these specific population subgroups.

A prospective study of psychological distress and weight status in adolescents/young adults.

BACKGROUND: The obesity-psychological distress relationship remains controversial. PURPOSE: This study aims to assess whether adolescents' psychological distress was associated with body mass index (BMI) class membership determined by latent class analysis. METHODS: Distress (anxiety, depression) and BMI were measured annually for 4 years in 1,528 adolescents. Growth mixture modeling derived latent BMI trajectory classes for models with 2-11 classes. The relationship of distress to class membership was examined in the best-fitting model using vector generalized linear regression. RESULTS: BMI trajectories were basically flat. The five-class model [normal weight (48.8%), overweight (36.7%), obese who become overweight (3.7%), obese (9.4%), and severely obese (1.3%)] was the preferred model (Bayesian information criterion = 22789.2, df = 31; ρ = 0.84). Greater distress was associated with higher baseline BMI and, therefore, class membership. CONCLUSIONS: Psychological distress is associated with higher BMI class during adolescence. To determine whether distress "leads" to greater weight gain may require studies of younger populations.