Dairy Consumption and Overweight and Obesity in Children and Adolescents: a Meta-analysis.
Condition: Obesity, Childhood; Overweight, Childhood; Overweight and Obesity
MeSH terms: Obesity; Overweight; Pediatric Obesity
Study type: Observational

Summary: 
      According to statistics from the European Association for the Study of Obesity (EASO), taking
      into account the definition of overweight and obesity recommended by the International
      Obesity Task Fort (IOTF), the prevalence of overweight (including obesity) in European
      children aged 7 to 17 years is 16-22% and the prevalence of obesity is 4-6%.

      Some review studies3 and meta-analysis4,5 have reported an inverse relationship between dairy
      products consumption and the prevalence or incidence of overweight and obesity. However, some
      methodological issues arise from these analyses. For instance, the combination of studies
      with different exposures (e.g. full fat milk, total milk) in the total dairy product
      analysis. Moreover, since the publication of the lasts meta-analysis in 2016, new
      epidemiological studies evaluating the association between dairy product consumption and
      overweight or obesity risk have been published.

      Objective The aim of this work is to systematically review and assess the associations
      between total dairy consumption and its different subtypes with the prevalence and incidence
      of overweight and obesity in children and adolescents.
    

Detailed description: 
      Searches: We will search the following electronic bibliographic databases: MEDLINE (PubMed)
      and The Cochrane Library (Cochrane Database of Systematic Reviews, Cochrane Central Register
      of Controlled Trials.

      The search strategy will include only terms relating to or describing the exposure. There
      will be no language restrictions.

      Data extraction (selection and coding):

      In the first step duplicate studies will be removed. Secondly, studies will be screened based
      on the title and abstract in order to exclude those that do not meet the inclusion criteria.
      In the last step, articles will be reviewed in full to select those that meet all the
      inclusion criteria.

      Two reviewers (LL and MM) will independently extract relevant data and assess the risk of
      bias following a standardize proforma. Relevant data will include:

        -  Authors, journal and year of publication

        -  Title

        -  Study design

        -  Study name

        -  Country/location of study

        -  Sample size

        -  Characteristics of the subjects

        -  Follow-up duration (for prospective cohort studies)

        -  Health status

        -  Sources of funding

        -  Type of exposure and assessment method

        -  Outcome and assessment method

        -  Odd ratios, risk ratios or hazard ratios and 95%CI

        -  Statistical analyses

      Risk of bias (quality) assessment:

      Two review authors will independently assess the risk of bias in included studies by
      considering the following tools: The New-Castle Ottawa scale will be used to assessed the
      quality of the included prospective cohort studies, whereas the NIH National Heart, Lung and
      Blood Institute. Study quality assessment tools will be used for cross-sectional studies. Any
      disagreement will be solved by consensus or consulting with a third author (NB-T).

      Strategy for data synthesis The meta-analysis will be conducted according to the Cochrane
      handbook for systematic reviews of interventions and results will be reported following the
      meta-analysis of observational studies in epidemiology (MOOSE) guidelines. The generic
      inverse-variance method with random-effects models or fixed-effects models, when at least 5
      or less than 5 comparisons are available, respectively, will be used to obtain summary
      estimates. Inter-study heterogeneity will be assessed by the Cochrane Q statistics (p<0.10
      will be considered significant) and quantified by the I2 statistic (≥ 50% will indicate
      substantial heterogeneity). Possible sources of heterogeneity will be explored by conducting
      sensitivity analyses, in which one study will be systematically removed at a time. If 10 or
      more comparisons are available, researchers will also explore sources of heterogeneity by a
      priori subgroup analyses (including, age, gender, geographical area and study quality).
      Meta-regression will assess the significance of categorical and continuous subgroup analyses.
      Linear and non-linear dose response relationship will be assessed by using generalized least
      squares trend (GLST) estimation models and spline curve modelling (MKSPLINE procedure),
      respectively. Publication bias will be assessed by visual inspection of funnel plots and the
      Egger and Begg tests when at least 10 trial comparisons are available.

      Analysis of subgroups or subsets:

      Prior subgroup analysis are planned to be conducted if at least 10 study comparisons are
      available. This will include: age (< or > of the median), gender (boys, girls and mixed),
      geographical area (America, Europe, Africa, Asia and Oceania), study quality (high vs low
      quality).
    

Intervention name(s): Dairy products
Intervention type(s): Other
Intervention description(s): Dairy consumption including total dairy, full-fat dairy, low-fat dairy, total milk, full-fat milk, low-fat milk, total yogurt, full-fat yogurt, low-fat yogurt, total cheese, hard cheese and fresh cheese
Observational model: Other
Time perspective: Cross-Sectional
Sampling method: Probability Sample
Study population: 
        All children (aged 2 years old to 21 years old), regardless of health status
      
Keywords: systematic review and meta-analysis; dairy products; prospective studies; cross-sectional studies