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Eating behaviour, physical activity, TV exposure and sleeping habits in five year olds: a latent class analysis
Molly Mattsson1,2, Deirdre M Murray3, Mairead Kiely4
1Division of Population Health Sciences, Royal College of Surgeons in Ireland, Dublin, Ireland. mollymattsson@rcsi.ie.
Insights
Childhood eating behaviors, not just activity levels, significantly impact overweight and obesity risk. Understanding these patterns early is crucial for effective interventions against childhood obesity.
Area of Science:
- Pediatric Health
- Behavioral Science
- Public Health
Background:
- Childhood overweight and obesity are rising public health concerns.
- Diet, physical activity, sedentary behaviors, and sleep are key lifestyle factors.
- Understanding behavioral patterns in early childhood is essential for prevention.
Purpose of the Study:
- Identify distinct lifestyle behavior clusters in 5-year-old children.
- Explore determinants linked to these behavioral clusters.
- Assess the association between behavioral clusters and body measures.
Main Methods:
- Latent class analysis of lifestyle behaviors in 1229 children.
- Multinomial logistic regression for determinant analysis.
- Multivariate regression for body measure associations.
Main Results:
- Three behavioral clusters identified: normative, food avoidance, and food approach.
- Food approach behaviors linked to higher fat mass index and obesity risk.
- Low socioeconomic index and maternal education associated with specific clusters.
Conclusions:
- Eating behaviors may be more influential than activity levels in early childhood obesity risk.
- Further research on tracking obesogenic behaviors is vital.
- Informing intervention timing requires understanding early life influences on adiposity.
Background:
Diet, physical activity, sedentary behaviours, and sleep time are considered major contributory factors of the increased prevalence of childhood overweight and obesity. The aims of this study were to (1) identify behavioural clusters of 5 year old children based on lifestyle behaviours, (2) explore potential determinants of class membership, and (3) to determine if class membership was associated with body measure outcomes at 5 years of age.
Methods:
Data on eating behaviour, engagement in active play, TV watching, and sleep duration in 1229 5 year old children from the Cork BASELINE birth cohort study was obtained through in-person interviews with parent. Latent class analysis was used to identify behavioural clusters. Potential determinants of cluster membership were investigated using multinomial logistic regression. Associations between the identified classes and cardio metabolic body measures were examined using multivariate logistic and linear regression, with cluster membership used as the independent variable.
Results:
51% of children belonged to a normative class, while 28% of children were in a class characterised by high scores on food avoidance scales in combination with low enjoyment of food, and 20% experienced high scores on the food approach scales. Children in both these classes had lower conditional probabilities of engaging in active play for at least 1 hour per day and sleeping for a minimum of 10 h, and higher probability of watching TV for 2 hours or more, compared to the normative class. Low socioeconomic index (SEI) and no breastfeeding at 2 months were found to be associated with membership of the class associated with high scores on the food avoidance scale, while lower maternal education was associated with the class defined by high food approach scores. Children in the class with high scores on the food approach scales had higher fat mass index (FMI), lean mass index (LMI), and waist-to-height ratio (WtHR) compared to the normative class, and were at greater risk of overweight and obesity.
Conclusion:
Findings suggest that eating behaviour appeared to influence overweight and obesity risk to a greater degree than activity levels at 5 years old. Further research of how potentially obesogenic behaviours in early life track over time and influence adiposity and other cardio metabolic outcomes is crucial to inform the timing of interventions.
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