Life course socioeconomic position and body composition in adulthood: a systematic review and narrative synthesis
Bibliographic record
Abstract
INTRODUCTION: Multiple systematic reviews have investigated the relation between socioeconomic position (SEP) and body mass index (BMI) throughout the life course. However, BMI does not capture quantity and distribution of fat and muscle, which are better indicators of obesity than BMI, and have been independently linked to adverse health outcomes. Less is known about the relation between SEP and body composition, and the literature has not been reviewed. We therefore systematically reviewed the literature on the association between life course SEP and body composition in adulthood. METHODS: A protocol was registered on PROSPERO (CRD42019119937), and the review followed PRISMA guidelines. An electronic search of three databases (MEDLINE, Embase Classic + Embase and SPORTDiscus) was conducted. Original studies in the English language were included that examine the association between any recognised measure of SEP at any age and body composition (fat mass, fat-free mass, ratio and distribution) in adulthood, measured using a direct technique, i.e., not an anthropometric measure. A narrative synthesis was conducted. RESULTS: A total of 47 papers were included in the final review, none were from low-income countries (LICs). Greater advantage in childhood and adulthood was associated with lower fat levels in high-income countries (HICs). Associations in the opposite direction were found exclusively in middle-income countries (MICs). No studies in MICs reported associations for childhood SEP. For measures of lean mass, the majority of papers reported no association, or greater advantage in adulthood associated with higher lean mass, with little variation between HICs and MICs. Associations in HICs are more often observed in women than men. CONCLUSION: The results indicate that fat measures follow similar patterns to those seen for BMI, and that women in HICs are more likely to experience inequalities in both fat and lean measures. Further research in LICs and MICs is needed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".