Explo loring th the Associati tion Between Affect Varia iabil ilit ity and Dail ily Activ ivit ity Patt ttern Metrics in in Chil ildren Chih-Hsiang (Jason) Yang, PhD Eldin Dzubur, PhD Jaclyn. P. Maher, PhD Britni. R. Belcher, PhD, MPH Donald Hedeker, PhD Genevieve. F. Dunton, PhD, MPH Presenting at the Society for Ambulatory Assessment, Syracuse University, NY. 01/30/19
Background • Prevalent inactivity level among children - global health issue 1-2 • Novel activity pattern metrics also can lead to health benefits 4-7 ▪ Sporadic (i.e., intermittent) moderate-to-vigorous physical activity (MVPA) ▪ Sedentary breaks • Variations in affect may impact everyday activity patterns 3 Whether children’s within -person mean and variability in momentary affect Potential moderation effects? predict daily activity pattern metrics?
Mothers’ and Their Children’s Health (MATCH) Study Funding: R01HL119255 (Dunton, PI) ▪ 6-wave EMA cohort study across 3 years • 192 Children ▪ Age: 8-14 (SD=1.25) ▪ 51% female ▪ 50% Hispanic
Children’s EMA data collection protocol EMA design for children: ▪ 3 random prompts on weekdays ▪ 7 random prompts on weekend days EMA platform: ▪ A customized Android app 8:00 00 10:00 :00 5:55 4:25 7:33 11:29 2:01 8:06 12:36 AM AM PM PM PM PM PM AM AM PM PM Random prompt for children on a weekend day At least 60 minutes between 2 consecutive prompts
EMA items measuring children’s momentary a ffect Positive affect items: ▪ Happy ▪ Joyful Negative affect items: ▪ Mad ▪ Sad ▪ Stressed On a 4-point Response Scale • Averaged scores created for positive and negative affect (Ebesutani et al., 2012)
Some children have relatively more erratic affect than others
Some children have relatively higher/lower mean affect
Accelerometry data provide rich information for studying the pattering of movement behaviors Day 1 Day 2 Day 3 ActiGraph GT2M / GT3X Day 4 Day 5
Two activity outcome measures Daily sporadic MVPA events Daily sedentary breaks (bursts lasting <10 mins) Mean=84.58 Mean=27.59 SD =12.20 SD =7.85 Sedentary breaks Sporadic MVPA
Applying MIXWILD Program MIXed models With Intensive Longitudinal Data • Novel statistical software that allows for the subject-level random effects of time-varying variables to influence subject-level outcomes • Two-stage data analysis approach: ▪ Stage 1: Mixed Effects Location Scale Model ▪ Estimate subject-level mean and variation in affect ▪ Stage 2: Multiple Linear Regression Model ▪ Predict mean daily sporadic MVPA and sedentary breaks Hedeker and Nordgren (2013)
Stage 1 – Mixed-effects location scale (Mixregls) model Modeling Momentary Positive / Negative Affect (Level-1 variable) Random scale (variability) Random intercept (mean) of positive / negative affect of positive / negative affect Predicting Daily Averaged Activity Pattern Metrics (Level-2 variable) Stage 2 – Multiple linear regression model
Testing Potential Moderation Effects in Stage 2 • Children with similar levels of variations in momentary affect may have different daily activity patterns ▪ Depending on demographics or mean levels of affect Sex / Hispanic / Mean Affect Affect Activity Variations Patterns • Add interaction terms in the Stage 2 model
Stage 1 Stage 2 Control Random variables Model 1 Intercept of Children’s Negative EMA Averaged Stage 1 time-varying covariates Affect • Weekend vs weekday Momentary Daily • EMA prompt delivery time Negative Sporadic Random • Children’s age Affect MVPA Scale of Events Negative Stage 2 time-invariant covariates Affect • Children’s sex • Hispanic vs non-Hispanic Random • Model 2 Interactions: Intercept of Children’s Random intercept x sex EMA Positive Averaged Random intercept x Hispanic Affect Momentary Daily Random scale x sex Positive Random scale x Hispanic Sporadic Random Random intercept x random scale Affect MVPA Scale of Positive Events Affect
Stage 1 Stage 2 Control Random variables Model 3 Intercept of Children’s Negative EMA Stage 1 time-varying covariates Averaged Affect • Weekend vs weekday Momentary Daily • EMA prompt delivery time Negative Random Sedentary • Children’s age Affect Scale of Breaks Negative Stage 2 time-invariant covariates Affect • Children’s sex • Hispanic vs non-Hispanic Random • Model 4 Interactions: Intercept of Random intercept x sex Children’s EMA Positive Random intercept x Hispanic Averaged Affect Momentary Random scale x sex Daily Positive Random scale x Hispanic Random Sedentary Random intercept x random scale Affect Scale of Breaks Positive Affect
Stage 2 estimates – Linear regression modeling (outcome=short MVPA bouts) Negative affect a predicting Positive affect predicting Variable Daily short MVPA bouts Daily short MVPA bouts Intercept 43.164*** 29.030*** Sex (male=1) -0.113 -1.368 Hispanic (=1) 1.211 -1.519 Random intercept (mean) 0.222 0.144 Random intercept x sex 2.564 1.012 Random intercept x Hispanic -3.062 -1.031 Random scale (variability) 5.445* -0.852 Random scale x sex -3.500 2.830* Random scale x Hispanic -4.027 0.811 Random intercept x random scale -1.070 -1.229* Number of level-2 clusters = 192; a Log-transformed at stage 1; * p <.05, *** p <.001.
Stage 2 estimates – Linear regression modeling (outcome=sedentary breaks) Negative affect predicting Positive affect predicting Variable Daily sedentary breaks Daily sedentary breaks Intercept 84.760*** 85.591*** Sex (male=1) -2.530 -2.983 Hispanic (=1) 0.678 -0.021 Random intercept (mean) 1.699 0.553 Random intercept x sex -1.085 -0.588 Random intercept x Hispanic -2.274 0.961 Random scale (variability) 3.663 0.181 Random scale x sex 0.902 3.633 Random scale x Hispanic -2.944 -0.144 Random intercept x random scale -1.456 -1.241 Number of level-2 clusters = 192
Sex and mean levels of positive affect moderate the relation between positive affect variability and sporadic MVPA events (mean positive affect) (variability in positive affect) (variability in positive affect)
Conclusions • High mean levels and more consistency in momentary positive affect were associated with more sporadic MVPA events in children. • Sex moderated the relation between positive affect variability & sporadic MVPA : ▪ Girls: more consistency in positive affect -> more sporadic MVPA • More variability in negative affect predicted more sporadic MVPA events in children. • Mean levels and variability in momentary affect (both positive and negative) did not predict sedentary breaks. • These preliminary results should be interpreted with caution.
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