Growth Curve Modeling Approach Research Articles

A longitudinal study of enjoyment and group-level emotion regulation in online collaborative English language learning

This study investigates the dynamic connection between two emotional constructs, enjoyment and group-level emotion regulation (co- and socially-shared regulation), during one 21-week semester of online collaborative English language learning. The study involved 268 Chinese undergraduate English-major students who completed a series of English writing tasks in 88 online groups of three or four members. During their online collaboration, participants were invited to complete the enjoyment scale and the emotion regulation scale at three separate times at seven-week intervals. When analyzing the data, a latent growth curve (LGC) modeling approach was employed to examine the intercepts and slopes of participants’ scaled responses to questions regarding enjoyment, co-regulation, and socially-shared regulation and to analyze the covariance between them. The findings reveal that participants’ levels of enjoyment and group-level emotion regulation were generally high at the initial stage of their online collaboration and continued to increase toward the end of the semester. Furthermore, an increase in the level of their enjoyment was significantly and positively associated with an increase in the levels of both their co- and socially-shared regulation, with the relationship with socially-shared regulation during online collaborative learning being stronger. These findings will enable language teachers to develop strategies for supporting language learners’ emotion regulation in online contexts.

Foreign direct investment, sectoral distribution and income inequality in developed and developing economies

Despite some progress in reducing income inequality between countries over the last two decades, there is evidence that income inequality is on the rise within nations. This article uses panel data compiled from multiple sources and a growth curve modeling approach to examine the relationship between foreign direct investment (FDI) and within-nation income inequality across two samples: one comprising 2,095 country-year observations nested in 141 countries from 1991 to 2018 to explore the broader FDI-income inequality relationship, and a second, more focused sample of 405 country-year observations nested in 61 countries from 2000 to 2018, designed to analyze effects of the sectoral distribution of FDI. The analyses find that the relationship between FDI and income inequality is positive and linear for non-OECD economies but follows an inverted U-shaped path for developed countries. Moreover, in this article, I have developed and introduced two new indices, the FDI Pluralism Index and FDI Sectoral Gini Coefficient, to measure the distribution of FDI among the sectors of the host economy. Results show that a concentration of FDI in one sector aggravates income inequality since foreign capital tends to flow into the most profitable industries, creating uneven growth between sectors and increasing between-sector income inequality.

An investigation of cardiac vagal tone over time and its relation to vigilance performance: a growth curve modeling approach.

Research over the last couple of decades has demonstrated a relationship between psychophysiological measures, specifically cardiac functions, and cognitive performance. Regulation of the cardiac system under parasympathetic control is commonly referred to as cardiac vagal tone and is associated with the regulation of cognitive and socioemotional states. The goal of the current study was to capture the dynamic relationship between cardiac vagal tone and performance in a vigilance task. We implemented a longitudinal growth curve modeling approach which unveiled a relationship between cardiac vagal tone and vigilance that was non-monotonic and dependent upon each person. The findings suggest that cardiac vagal tone may be a process-based physiological measure that further explains how the vigilance decrement manifests over time and differs across individuals. This contributes to our understanding of vigilance by modeling individual differences in cardiac vagal tone changes that occur over the course of the vigilance task.

Effects of a brief self-compassion intervention for college students with impostor phenomenon.

The present study used a latent growth curve modeling approach to (a) examine the effectiveness of a brief self-compassion intervention on reducing impostor phenomenon, maladaptive perfectionism, and psychological distress and (b) explore who would benefit more from this intervention. A total of 227 college students at a large Midwest university were randomly assigned to participate in either a 4-week brief self-compassion intervention group or a nonintervention control group. Analyses of the effectiveness of the intervention suggested the brief self-compassion intervention had significant treatment effects for reducing impostor phenomenon and maladaptive perfectionism. Moreover, this study also examined whether participants with different levels of fear of self-compassion and core self-evaluation would report different levels of treatment effectiveness. Fear of self-compassion was found to be a significant moderator of the intervention effects in reducing maladaptive perfectionism and psychological distress. Specifically, participants in the intervention group with higher levels of fear of self-compassion reported a greater decline in both maladaptive perfectionism and psychological distress over time when compared to those with lower levels of fear of self-compassion. Core self-evaluation significantly moderated the effectiveness of this intervention in reducing participants' levels of impostor phenomenon and maladaptive perfectionism. Specifically, participants in the intervention group with lower core self-evaluation reported a greater reduction in maladaptive perfectionism over time when compared to those with higher core self-evaluation. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Rural-Urban Disparities in Multimorbidity Associated With Climate Change and Air Pollution: A Longitudinal Analysis Among Chinese Adults Aged 45.

Chronic conditions and multimorbidity are increasing worldwide. Yet, understanding the relationship between climate change, air pollution, and longitudinal changes in multimorbidity is limited. Here, we examined the effects of sociodemographic and environmental risk factors in multimorbidity among adults aged 45+ and compared the rural-urban disparities in multimorbidity. Data on the number of chronic conditions (up to 14), sociodemographic, and environmental factors were collected in 4 waves of the China Health and Retirement Longitudinal Study (2011-2018), linked with the full-coverage particulate matter 2.5 (PM2.5) concentration data set (2000-2018) and temperature records (2000-2018). Air pollution was assessed by the moving average of PM2.5 concentrations in 1, 2, 3, 4, and 5 years; temperature was measured by 1-, 2-, 3-, 4-, and 5-year moving average and their corresponding coefficients of variation. We used the growth curve modeling approach to examine the relationship between climate change, air pollution, and multimorbidity, and conducted a set of stratified analyses to study the rural-urban disparities in multimorbidity related to temperature and PM2.5 exposure. We found the higher PM2.5 concentrations and rising temperature were associated with higher multimorbidity, especially in the longer period. Stratified analyses further show the rural-urban disparity in multimorbidity: Rural respondents have a higher prevalence of multimorbidity related to rising temperature, whereas PM2.5-related multimorbidity is more severe among urban ones. We also found temperature is more harmful to multimorbidity than PM2.5 exposure, but PM2.5 exposure or temperature is not associated with the rate of multimorbidity increase with age. Our findings indicate that there is a significant relationship between climate change, air pollution, and multimorbidity, but this relationship is not equally distributed in the rural-urban settings in China. The findings highlight the importance of planning interventions and policies to deal with rising temperature and air pollution, especially for rural individuals.

Measuring the rate of psychological growth and examining its antecedents: A growth curve modeling approach.

Humanistic psychologists have conceptualized a tendency among humans to experience continual open-ended psychological growth. This study aims to measure the rate at which one grows psychologically using a novel growth curve modeling approach that addresses previous limitations. We also examine the effects of nine potential contributors to growth identified from the literature. Throughout the freshman year, 556 college students responded six times. Increments of growth were added up to create cumulative growth, which was then fit to a growth curve model to produce an estimate of the growth rate. The growth rate was then regressed on the Time 1 predictors to examine their unique effects. Models fit well. Five predictors significantly predicted the growth rate after controlling for the average of other predictors. When all predictors were entered simultaneously, three predictors (hope, meaning, and personal growth initiative) showed significant unique effects. The growth rate predicted well-being and satisfaction at Time 6. We successfully measured the rate of psychological growth and examined its antecedents. Follow-up analyses suggested that the predictors not showing unique effects may indirectly predict growth rates via the proximal role of the three significant predictors, an idea that awaits future corroboration using within-individual designs.

Quantifying Emotional Flow: Testing the Emotional Flow Hypothesis from a Longitudinal Latent Growth Curve (LGC) Modeling Approach

ABSTRACT This paper presents a longitudinal, latent growth curve (LGC) modeling approach to refine the emotional flow measure and hypothesis testing. Emotional flow is operationalized as the marked within-individuals variations in one or more discrete emotions over time, which can be modeled as the amount and shape of change in emotions during message exposure. Emotional flow effects are tested in the LGC framework using data collected from a web-based experimental study where individuals (US Qualtrics Panel, N = 620) read an anti-sugary sweetened beverage message in the standard threat appeal format. Simultaneous fear and hope flows were established with unconditional LGC modeling. The two flows and their interaction were then used to predict message effects outcomes. Results showed that flow effects were nonsignificant when either the fear flow or the hope flow was relatively flat in form, but robust when both emotional flows were with marked variations over the course of message exposure.

Subjective cognitive decline predicts lower cingulo-opercular network functional connectivity in individuals with lower neurite density in the forceps minor

Cognitive complaints of attention/concentration problems are highly frequent in older adults with subjective cognitive decline (SCD). Functional connectivity in the cingulo-opercular network (CON-FC) supports cognitive control, tonic alertness, and visual processing speed. Thus, those complaints in SCD may reflect a decrease in CON-FC. Frontal white-matter tracts such as the forceps minor exhibit age- and SCD-related alterations and, therefore, might influence the CON-FC decrease in SCD. Here, we aimed to determine whether SCD predicts an impairment in CON-FC and whether neurite density in the forceps minor modulates that effect. To do so, we integrated cross-sectional and longitudinal analyses of multimodal data in a latent growth curve modeling approach. Sixty-nine healthy older adults (13 males; 68.33 ± 7.95 years old) underwent resting-state functional and diffusion-weighted magnetic resonance imaging, and the degree of SCD was assessed at baseline with the memory functioning questionnaire (greater score indicating more SCD). Forty-nine of the participants were further enrolled in two follow-ups, each about 18 months apart. Baseline SCD did not predict CON-FC after three years or its rate of change (p-values > 0.092). Notably, however, the forceps minor neurite density did modulate the relation between SCD and CON-FC (intercept; b = 0.21, 95% confidence interval, CI, [0.03, 0.39], p = 0.021), so that SCD predicted a greater CON-FC decrease in older adults with relatively lower neurite density in the forceps minor. The neurite density of the forceps minor, in turn, negatively correlated with age. These results suggest that CON-FC alterations in SCD are dependent upon the forceps minor neurite density. Accordingly, these results imply modifiable age-related factors that could help delay or mitigate both age and SCD-related effects on brain connectivity.

Narcissists going above and beyond? The role of perceived negative inequity and self-enhancement motivation

PurposeUtilizing a self-regulatory perspective, the authors examine how narcissism influences perceived negative inequity and the downstream effects on self-enhancement motivation and organizational citizenship behaviors (OCBs) over time.Design/methodology/approachA total of 689 useable three-wave panel data were obtained via Amazon Mechanical Turk during a three-month period. A latent growth curve modeling approach using EQS 6.4 for Windows was employed to test the hypothesized model.FindingsResults illustrate that individuals with higher levels of narcissism perceive higher levels of perceived negative inequity and then form higher levels of self-enhancement motivation, which prompt more OCB directed toward the organization (OCBO) than OCB directed toward individuals (OCBI). When perceived negative inequity increases over time, narcissists experience a faster increase in self-enhancement motivation, which also leads to a faster increase in OCBO compared to the increase in OCBI.Originality/valueTheoretically, this study provides theoretical and empirical insights into understanding the process through which narcissists' OCBs are motivated. Practically, this study offers several practical recommendations that help managers manage OCBs effectively in the organization.

Disentangling the Influence of Data Contamination in Growth Curve Modeling: A Median Based Bayesian Approach

Growth curve models (GCMs), with their ability to directly investigate within-subject change over time and between-subject differences in change for longitudinal data, are widely used in social and behavioral sciences. While GCMs are typically studied with the normal distribution assumption, empirical data often violate the normality assumption in applications. Failure to account for the deviation from normality in data distribution may lead to unreliable model estimation and misleading statistical inferences. A robust GCM based on conditional medians was recently proposed and outperformed traditional growth curve modeling when outliers are present resulting in nonnormality. However, this robust approach was shown to perform less satisfactorily when leverage observations existed. In this work, we propose a robust double medians growth curve modeling approach (DOME GCM) to thoroughly disentangle the influence of data contamination on model estimation and inferences, where two conditional medians are employed for the distributions of the within-subject measurement errors and of random effects, respectively. Model estimation and inferences are conducted in the Bayesian framework, and Laplace distributions are used to convert the optimization problem of median estimation into a problem of obtaining the maximum likelihood estimator for a transformed model. A Monte Carlo simulation study has been conducted to evaluate the numerical performance of the proposed approach, and showed that the proposed approach yields more accurate and efficient parameter estimates when data contain outliers or leverage observations. The application of the developed robust approach is illustrated using a real dataset from the Virginia Cognitive Aging Project to study the change of memory ability.

Longitudinal changes in Chinese minority college students’ health-related fitness: A multilevel latent growth curve modeling approach

Purpose: The study aimed to test the overall changes of health-related fitness (HRF) in minority Chinese college students and to examine HRF differences in gender, race, and year in college. Method: Participants (n = 1320) were minority college students with more than two-thirds females (ie 76.1%), and Hui, Tibetan, and Mongolia consisted of 13.8%, 13.8%, and 11.2%, respectively. Student HRF was tracked for four years. Data were analyzed using multilevel latent growth curve modeling. Results: Muscular strength and endurance were the weakest component in minority college students’ HRF, while body mass index was within the category of “excellent”. Males outperformed female on all components of HRF. Conclusions: It is suggested that interventions concerning minority females’ HRF and muscular strength and endurance for both genders be constructed and tested.

Resilience and Depression in Military Service: Evidence From the National Longitudinal Study of Adolescent to Adult Health (Add Health).

Research indicates that military service involves stressors that may be related to depression. However, the military provides financial, educational, psychological, and social advantages that may help to mitigate the effects of service-related stressors. Because most prior research was based on cross-sectional data or small clinical samples, we explored individual-level trajectories of depression over time. Data came from the restricted-use version of the National Longitudinal Study of Adolescent to Adult Health (Add Health) in four survey waves from 1994 to 2008, with a total of 1,112 service members, of whom 231 were female, and a total sample size of 13,544. Statistical estimation employed the multilevel growth curve modeling approach. Individuals who later served in the military had lower rates of depression than their civilian counterparts at year 1 of the study, and rates of depression decreased consistently for both groups throughout the study. Service members ended up with the same level of depression compared to civilians (year 14). Sex, race and parental education were unrelated to depression, and no evidence was found for the hypothesis that the military functions as a "bridging environment" to reduce depression by providing a more attractive alternative compared to civilian life. Individuals who were less depressed at year 1 of the study were more likely to enlist into the military. While both civilians and service members displayed decreasing depression over the years of the study, military members had less decrease in depression over time beginning at a lower level of depression than civilian. Taken together, the minor differences in depression between the civilian and military samples and the lower level of depression among military members at the beginning of the study suggest that military service selects against higher levels of depression at the start of service and, given the known stressors related to the military, membership in the service may be associated with resilience to depression.

Auditory neurophysiological development in early childhood: A growth curve modeling approach

ObjectiveDuring early childhood, the development of communication skills, such as language and speech perception, relies in part on auditory system maturation. Because auditory behavioral tests engage cognition, mapping auditory maturation in the absence of cognitive influence remains a challenge. Furthermore, longitudinal investigations that capture auditory maturation within and between individuals in this age group are scarce. The goal of this study is to longitudinally measure auditory system maturation in early childhood using an objective approach. MethodsWe collected frequency-following responses (FFR) to speech in 175 children, ages 3–8 years, annually for up to five years. The FFR is an objective measure of sound encoding that predominantly reflects auditory midbrain activity. Eliciting FFRs to speech provides rich details of various aspects of sound processing, namely, neural timing, spectral coding, and response stability. We used growth curve modeling to answer three questions: 1) does sound encoding change across childhood? 2) are there individual differences in sound encoding? and 3) are there individual differences in the development of sound encoding? ResultsSubcortical auditory maturation develops linearly from 3-8 years. With age, FFRs became faster, more robust, and more consistent. Individual differences were evident in each aspect of sound processing, while individual differences in rates of change were observed for spectral coding alone. ConclusionsBy using an objective measure and a longitudinal approach, these results suggest subcortical auditory development continues throughout childhood, and that different facets of auditory processing follow distinct developmental trajectories. SignificanceThe present findings improve our understanding of auditory system development in typically-developing children, opening the door for future investigations of disordered sound processing in clinical populations.

A GROWTH CURVE MODEL FOR CO2 EMISSIONS IN G19 COUNTRIES

CO 2 emissions per capita (Emc) and CO 2 emissions intensity (Emint) are among the main metrics used to report emissions in environmental studies. The main aim of this note is to compare the evolution of Emc and Emint in the G19 countries. Comparing their varying trends is useful in benchmark analysis. Indeed, in our study of the G19 countries, we offer evidence that such metrics show different trends for the same group of countries both at the sample and the individual level. Using a growth curve modeling approach, we find that Emint has been decreasing in the G19 countries while Emc has been increasing, but at a slower pace. Further, countries with high initial Emint have achieved the greatest reduction in the period analyzed, whereas there is no evidence of such a change in the case of countries with high initial Emc. We also find that a country’s area affects its Emint growth, but not its Emc. Used together, Emint and Emc offer better insights into environmental performance as measured through these metrics. Keywords: Emissions intensity; Emissions per capita; growth curve model; G19; CO 2 reduction JEL Classifications: C15, Q53, Q56 DOI: https://doi.org/10.32479/ijeep.9725

Approaches for Modeling of Intensive Longitudinal Data to Understand Cognitive Aging

Understanding age-related change in cognition and identification of pathological changes requires sensitive and valid measurement of cognitive performance across time. Technological advances, such as ambulatory assessment of cognition using smartphones, have enabled intensive longitudinal methods where data is collected with many measurements over time. Our research group has developed novel ambulatory assessments that provide reliable, sensitive, and ecologically valid measurement of cognition across multiple timescales; from momentary changes to change across years. This symposium will present a spectrum of approaches to analysis of intensive longitudinal data that can inform models of cognitive aging. All three presentations will draw on data from measurement burst studies that apply our ambulatory cognitive assessment methods in community-based samples (i.e., systematically recruited in the Bronx, New York). For each measurement burst, participants undergo assessment consisting of brief surveys and cognitive tests via smartphone, up to 7 times per day across 14 days. Oravecz et al. will discuss the application of a Bayesian multilevel implementation of the double exponential model to account for retest effects while quantifying change in peak cognitive performance across time. Kang et al., will demonstrate a growth curve modeling approach for assessing the effects of between-person variables (i.e., loneliness) on change in cognition across measurement bursts. Harrington et al., will demonstrate a model-based cluster analysis approach, leveraging ambulatory assessments of subjective and objective cognitive function to unpack latent groups as a function of age and loneliness. Measurement, Statistics, and Research Design Interest Group Sponsored Symposium.

Neuroticism and cyberbullying among elementary school students: A latent growth curve modeling approach

The significant relation between neuroticism and cyberbullying (perpetration and victimization) has attracted increasing research attention; however, the development and possible psychological mechanisms linking neuroticism and cyberbullying (perpetration and victimization) among elementary school students require further explication. This study examined the trajectories of neuroticism and cyberbullying (perpetration and victimization) and how the changes in neuroticism were related to the changes in cyberbullying (perpetration and victimization) using latent growth curve modeling. A sample of 4327 Chinese elementary school students (55.4% boys; age: M = 9.94 years, SD = 0.73) completed measurements of the relevant constructs on five occasions across two years, using half-year intervals. The findings revealed that neuroticism, cyberbullying perpetration, and cyberbullying victimization all decreased over time. Additionally, cyberbullying (perpetration and victimization) at baseline positively correlated with neuroticism at baseline. Furthermore, cyberbullying (perpetration and victimization) decreased in parallel with decreases in neuroticism. These findings add to the literature on neuroticism and cyberbullying (perpetration and victimization) among elementary school students by demonstrating their parallel change relations. Implications for reducing the risk of cyberbullying (perpetration and victimization) among elementary school students were discussed.

Collective orientation and its implications for coordination and team performance in interdependent work contexts

Purpose This paper aims to explore the influence of collective orientation (CO) on coordination and team performance for interdependently working teams while controlling for person-related and team variables. Design/methodology/approach A total of 58 two-person-teams participated in a simulation-based firefighting task. The laboratory study took 2 h for each team. The effects of CO in tasks of increasing complexity were investigated under the consideration of control variables, and the relations between CO, coordination and team performance were assessed using a multivariate latent growth curve modeling approach and by estimating indirect effects in simple mediation models. Findings Team members high on CO performed significantly better than low-scoring members. The effect of CO on team performance was independent from an increasing task complexity, whereas the effect of CO on coordination was not. The effect of CO on team performance was mediated by coordination within the team, and the positive relation between CO and performance persists when including group efficacy into the model. Research limitations/implications As CO is a modifiable person-related variable and important for effective team processes, additional research on factors influencing this attitude during work is assumed to be valuable. Practical implications CO is especially important for highly interdependently working teams in high-risk-organizations such as the fire service or nuclear power plants, where errors lead to severe consequences for human beings or the environment. Originality/value No other studies showed the importance of CO for coordination and team performance while considering teamwork-relevant variables and the interdependence of work.

Longitudinal patterns of cocaine use among patients receiving injectable hydromorphone or diacetylmorphine for the treatment of opioid use disorder: A growth curve modeling approach

Background and aimsCocaine use is prevalent among people receiving injectable opioid agonist treatment. Investigations of cocaine use in this population have been descriptive and the potential heterogeneity existing in patterns of use have not been characterized. As such, among patients receiving injectable opioid agonist treatment, this study aimed to: 1) quantify intra- and inter-individual variation in cocaine use over 24-months and; 2) determine how predictors of interest explained this variation. MethodsParticipants were patients receiving injectable opioid agonist treatment for opioid use disorder. Study visits were completed at baseline prior to receiving treatment, and 3,6,9,12,18, and 24 months after baseline. A multi-level regression approach to growth curve modeling was employed to estimate and explain intra- (within-person) and inter-individual (between-person) variation in cocaine use. ResultsSignificant intra and inter-individual variation in cocaine use was identified over 24-months. Treatment engagement was on average associated with reductions in the prior month number of days of cocaine use (range: 0–30)(Estimate (standard error): -0.05(0.02), p = 0.003). On average, men reported less cocaine use compared to women (Estimate (standard error): -5.91(1.57), p=<0.001), and participants reporting ever regularly using cocaine at baseline reported more cocaine use over 24-months compared to participants reporting never regularly using cocaine (Estimate (standard error): 4.72 (1.91), p = 0.013). ConclusionsSignificant reductions in cocaine use were observed and significant heterogeneity in patterns of cocaine use was identified. These heterogeneous cocaine use profiles suggest that an individualized approach to care will be critical in responding to patients’ cocaine use in injectable opioid agonist treatment.

Amenable Mortality and Neighborhood Inequality: An Ecological Study of São Paulo

This article uses an ecological study design to explore intraurban health inequality in São Paulo by examining neighborhood‐level changes in mortality amenable to medical care. We use 2003–2013 data for 95 city districts of São Paulo and apply a random coefficient growth curve modeling approach. We find that improved access to health‐care services is associated with reduced amenable mortality. Despite these overall improvements, the magnitude of population health disparities, as measured by amenable mortality, did not diminish. The effects of social, economic, and health system factors on amenable mortality depend on the income level of the district. Persistent disparities in amenable mortality within São Paulo suggests that neighborhood‐level differences in social determinants of health and access to health services require further investment from the Brazilian government.

Longitudinal association between body mass index and physical activity among adolescents with different parental risk: a parallel latent growth curve modeling approach

BackgroundData available on the association between physical activity (PA) and body mass index (BMI) in different periods of life is controversial. Using a parallel latent growth curve modeling (LGCM) approach, the current study aimed to investigate the influence of daily PA on adolescents’ BMI over a 12 year follow-up, taking into account their parental risk.MethodParticipants comprised 1323 adolescents (53.5% girls), aged 12–18 years who had participated in the baseline phase of Tehran Lipid and Glucose Study (TLGS) (2001–2003), and were followed for an average period of 12 years. Physical activity, including leisure time and occupational activities, was assessed using the reliable and validated Iranian version of the Modifiable Activity Questionnaire (MAQ). Weight and height were objectively measured in order to calculateBMI.Atwo-step cluster analysis was conducted to classify parents into two high- and low-risk clusters. Parallel LGCM was fitted to estimate cross-sectional, prospective and parallel associations, which assessed the longitudinal association between simultaneous changes in PA and BMI during the study period. Analyses were stratified by gender and parental clusters.ResultsA rising trend of BMI per 3 years was observed in boys 1.39 kg.m2(95% CI; 1.32, 1.48) and girls 0.9 kg.m2(95% CI; 0.82, 0.98), as well as in the low risk 1.11 kg.m2(95% CI; 1.03, 1.18) and high-risk 1.12 kg.m2(95% CI; 1.03, 1.22) clusters. Moreover, a positive prospective association between PA at baseline and BMI change over the 12 year follow-up, was observed in adolescents in the low-risk parental cluster 0.27(95% CI; 0.14, 0.41) indicating that higher levels of PA at baseline may lead to greater BMI in adolescents over time. However, examining longitudinal parallel association between simultaneous changes of PA and BMI per 3 years revealed adverse associations for adolescents in the low-risk parental cluster − 0.07 (95% CI; − 0.13, − 0.01) and in boys − 0.06 (95% CI; − 0.11, − 0.01).ConclusionDespite a positive prospective association between BMI and PA at baseline, there was a weak inverse parallel association between these variables over time, particularly in boys and adolescents with low parental risk. These findings imply the potential role of other influential factors indetermining adolescents’ weight status which need to be considered in the future plannings.