Evidence map›Paper›PMID 31391516›Full record

ArticleInternational journal of obesity (2005)2019

Microsimulation model of child and adolescent overweight: making use of what we already know.

Nichola Shackleton, Kevin Chang, Roy Lay-Yee, Stephanie D'Souza, Peter Davis, Barry Milne

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Article in International journal of obesity (2005), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Nichola ShackletonCentre of Methods and Policy Application in the Social Sciences, Faculty of Arts, University of Auckland, Auckland, New Zealand. n.shackleton@auckland.ac.nz.
Kevin ChangCentre of Methods and Policy Application in the Social Sciences, Faculty of Arts, University of Auckland, Auckland, New Zealand.
Roy Lay-YeeCentre of Methods and Policy Application in the Social Sciences, Faculty of Arts, University of Auckland, Auckland, New Zealand.
Stephanie D'SouzaCentre of Methods and Policy Application in the Social Sciences, Faculty of Arts, University of Auckland, Auckland, New Zealand.
Peter DavisCentre of Methods and Policy Application in the Social Sciences, Faculty of Arts, University of Auckland, Auckland, New Zealand.
Barry MilneCentre of Methods and Policy Application in the Social Sciences, Faculty of Arts, University of Auckland, Auckland, New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNew Zealand has high rates of child overweight and obesity when compared with other countries. Despite an abundance of research documenting the problem, it is unclear what the most effective policy changes or interventions are, and how policy changes might unfold over time within complex systems.

methodsWe use estimates derived from meta-analyses to create a dynamic microsimulation model of child overweight (including obesity). Using census records we created a synthetic birth cohort of 10,000 children. Information on parental education, ethnicity and father's socio-economic position at birth were taken from census records. We used the New Zealand Health Survey to estimate population base rates for the prevalence of overweight and obesity. Information on other modifiers (such as maternal smoking, breastfeeding, preterm birth, regular breakfast consumption and so forth) were taken from three birth cohorts: Christchurch Health and Development Study, The Dunedin Multidisciplinary Health and Development Study and the Pacific Islands Families Study. Published intervention studies were used to derive plausible estimates for changes to modifiers.

resultsReducing the proportion of mothers classified as overweight and obesity (-3.31(95% CI -3.55; -3.07) percentage points), reducing the proportion of children watching two or more hours of TV (-3.78(95% CI -4.01; -3.54)), increasing the proportion of children eating breakfast regularly (-1.71(95% CI -1.96; -1.46)), and reducing the proportion of children born with high birth weights (-1.36(95% CI -1.61; -1.11)), lead to sizable decreases in the estimated prevalence of child overweight (including obesity). Reducing the proportion of mothers giving birth by caesarean (-0.23(95% CI -0.49; -0.23)) and increasing parental education (-0.07(95% CI -0.31; 0.18)) did not impact upon child overweight rates.

conclusionsWe created a working simulation model of New Zealand children that can be accessed by policy makers and researchers to determine known relationships between predictors and child overweight, as well as potential gains from targeting specific pathways.

Indexed as

Computer SimulationAdolescentBirth WeightChildChild, PreschoolFemaleHumansMaleMeta-Analysis as TopicMothersNew ZealandOverweightPediatric ObesityPrevalence

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.