Oral Presentation Australian and New Zealand Obesity Society Annual Scientific Conference 2023

Associations between season at entry, diet and lifestyle factors, and 6-month outcomes in a multi-disciplinary intervention programme for weight issues. (97718)

Kima Costelloe 1 , Cervantée Wild 1 , José Derraik 1 , Paul Hofman 2 , Yvonne Anderson 1 3
  1. Department of Paediatrics, The University of Auckland, Auckland, New Zealand
  2. Liggins Institute, The University of Auckland, Auckland, New Zealand
  3. Child and Adolescent Health Service | Curtin University | Telethon Kids Institute, Perth, WA, Australia

 

Background: Evidence suggests seasonal fluctuations in weight in childhood, but New Zealand data are lacking. We examined whether changes in BMI standard deviation score (BMISDS) varied by season at entry into Whānau Pakari, a multidisciplinary assessment and intervention programme for obesity in Taranaki. Further, we assessed if potential seasonal differences were explained by dietary and lifestyle factors.

Methods: Participants were 397 children and adolescents, 51% females, with median age of 10.1 years (range 3.7–16.8 years), median BMI SDS=3.07, who entered the programme in Autumn (n=89), Spring (n=69), Summer (n=112), and Winter (n=127). Primary outcome was change in BMISDS at six months.

Results: At 6 months, 255 participants (64.2%) had a BMISDS reduction compared to baseline [mean=-0.10 SDS; p<0.0001), which was achieved by starters in Summer (-0.11 SDS; p<0.001), Autumn (-0.12 SDS; p<0.0001), and Winter (-0.11 SDS; p<0.001), but not Spring (p=0.33). There was evidence of seasonal differences among starters with BMISDS below the median (<3.07 SDS), with Autumn starters displaying greater BMISDS reductions than starters in Winter [adjusted mean difference (aMD)=-0.12 SDS; p=0.044)], Spring (aMD=-0.18 SDS; p=0.007), and Summer (aMD=-0.16 SDS; p=0.008). At entry, increased sugar-sweetened beverage (SSB) intake was associated with higher BMISDS, and youth consuming ≥500 ml/day had BMI 0.38 SDS greater than those consuming no SSB (p=0.001). At 6 months, there was a reduction in sugar-sweetened drink intake (-100 ml/day; p<0.0001), increased physical activity (+15 min/day; p<0.001), reduced screen time (-16 min/day; p=0.003), and increased intake of fruit and vegetables (+0.2 items/day; p=0.019); however, there were no observed associations between dietary and lifestyle factors and BMI SDS changes.

Conclusions: Among Whānau Pakari participants, there was some evidence of seasonal differences in achieved BMISDS reductions at 6 months. Although exploratory, our findings suggest that seasonal differences could influence the outcome of obesity interventions, requiring further investigation.