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Record W4235790680 · doi:10.1186/2046-4053-1-16

Tackling inequalities in obesity: a protocol for a systematic review of the effectiveness of public health interventions at reducing socioeconomic inequalities in obesity amongst children

2012· review· en· W4235790680 on OpenAlexaboutno aff
Clare Bambra, Frances Hillier-Brown, Helen Moore, Carolyn Summerbell

Bibliographic record

VenueSystematic Reviews · 2012
Typereview
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
FundersPublic Health Research ProgrammeDurham UniversityNewcastle UniversityNational Institute for Health and Care Research
KeywordsMedicineSocioeconomic statusPublic healthPsychological interventionOverweightPovertyDisadvantagedSocial inequalityObesityEnvironmental healthInequalityGerontologyEconomic growthPopulationNursing

Abstract

fetched live from OpenAlex

BACKGROUND: There is growing evidence of the impact of overweight and obesity on short- and long-term functioning, health and well-being. Internationally, childhood obesity rates continue to rise in some countries (for example, Mexico, India, China and Canada), although there is emerging evidence of a slowing of this increase or a plateauing in some age groups. In most European countries, the United States and Australia, however, socioeconomic inequalities in relation to obesity and risk factors for obesity are widening. Addressing inequalities in obesity, therefore, has a very high profile on the public health and health services agendas. However, there is a lack of accessible policy-ready evidence on what works in terms of interventions to reduce inequalities in obesity. METHODS AND DESIGN: This article describes the protocol for a National Health Service Trust (NHS) National Institute for Health Research-funded systematic review of public health interventions at the individual, community and societal levels which might reduce socioeconomic inequalities in relation to obesity amongst children ages 0 to 18 years. The studies will be selected only if (1) they included a primary outcome that is a proxy for body fatness and (2) examined differential effects with regard to socioeconomic status (education, income, occupation, social class, deprivation and poverty) or the intervention was targeted specifically at disadvantaged groups (for example, children of the unemployed, lone parents, low income and so on) or at people who live in deprived areas. A rigorous and inclusive international literature search will be conducted for randomised and nonrandomised controlled trials, prospective and retrospective cohort studies (with and/or without control groups) and prospective repeat cross-sectional studies (with and/or without control groups). The following electronic databases will be searched: MEDLINE, Embase, CINAHL, PsycINFO, Social Science Citation Index, ASSIA, IBSS, Sociological Abstracts and the NHS Economic Evaluation Database. Database searches will be supplemented with website and grey literature searches. No studies will be excluded on the basis of language, country of origin or publication date. Study inclusion, data extraction and quality appraisal will be conducted by two reviewers. Meta-analysis and narrative synthesis will be conducted. The main analysis will examine the effects of (1) individual, (2) community and (3) societal level public health interventions on socioeconomic inequalities in childhood obesity. Interventions will be characterised by their level of action and their approach to tackling inequalities. Contextual information on how such public health interventions are organised, implemented and delivered will also be examined. DISCUSSION: In this review, we consider public health strategies which reduce and prevent inequalities in the prevalence of childhood obesity, highlight any gaps in the evidence base and seek to establish how such public health interventions are organised, implemented and delivered. PROSPERO registration number: CRD42011001740.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.056
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.111
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0560.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0260.005
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.160
GPT teacher head0.422
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations24
Published2012
Admission routes1
Has abstractyes

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