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Efficacy of behavioral interventions in managing gestational weight gain (GWG): A component network meta-analysis.
Ranasinha, Sanjeeva; Hill, Briony; Teede, Helena J; Enticott, Joanne; Wang, Rui; Harrison, Cheryce L.
Affiliation
  • Ranasinha S; Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
  • Hill B; Health and Social Care Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
  • Teede HJ; Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
  • Enticott J; Diabetes and Vascular Medicine Unit, Monash Health, Melbourne, Australia.
  • Wang R; Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
  • Harrison CL; Department of Obstetrics and Gynaecology, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Victoria, Australia.
Obes Rev ; 23(4): e13406, 2022 04.
Article in En | MEDLINE | ID: mdl-34927351
ABSTRACT

OBJECTIVE:

To identify the most effective behavioral components within lifestyle interventions to optimize gestational weight gain (GWG) to inform guidelines, policy and translation into healthcare.

METHODS:

Behavioral components were identified from study level data of randomized antenatal lifestyle interventions using a behavioral taxonomy framework and analyzed using component network meta-analysis (NMA). The NMA ranked behavioral combinations hierarchically by efficacy of optimizing GWG. Direct and estimated indirect comparisons between study arms (i.e., control and intervention) and between different component combinations were estimated to evaluate component combinations associated with greater efficacy.

RESULTS:

Overall, 32 studies with 11,066 participants were included. Each intervention contained between 3 and 7 behavioral components with 26 different behavioral combinations identified. The majority (n = 24) of combinations were associated with optimizing GWG, with standard mean differences (SMD) ranging from -1.01 kg (95% CI -1.64 to -0.37) and -0.07 kg (-0.38 to 0.24), compared with controls. The behavioral cluster identified as most effective, included components of goals, feedback and monitoring, natural consequences, comparison of outcomes, and shaping knowledge (SMD -1.01 kg [95% CI -1.64 to -0.37]).

CONCLUSION:

Findings support the application of goal setting, feedback and monitoring, natural consequences, comparison of outcomes, and shaping knowledge as essential, core components within lifestyle interventions to optimize gestational weight gain.
Subject(s)
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Pregnancy Complications / Gestational Weight Gain Type of study: Clinical_trials / Prognostic_studies / Systematic_reviews Limits: Female / Humans / Pregnancy Language: En Journal: Obes Rev Journal subject: METABOLISMO Year: 2022 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Pregnancy Complications / Gestational Weight Gain Type of study: Clinical_trials / Prognostic_studies / Systematic_reviews Limits: Female / Humans / Pregnancy Language: En Journal: Obes Rev Journal subject: METABOLISMO Year: 2022 Document type: Article Affiliation country:
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