Small for gestational age trends in Canada from 2000-2016 : an analysis of individual-level factors and the minimum wage
Bibliographic record
Abstract
Background Earlier studies investigating birthweight trends in Canada indicated a downward trend in SGA births. Today, evidence suggests an unexplained upward trend, as well as regional differences, in SGA births from 2005-2014. These variations, over time and across jurisdictions, might be explained through downstream individual-level risk factors and/or more upstream contextual factors such as the minimum wage. Recent studies in the US found that higher minimum wages were associated with fewer adverse birth outcomes. Given the differences between the two countries, it is unclear if similar effects might be observed in Canada. Objective Describe and analyze trends in SGA births across Canada from 2000 to 2016 using individual and contextual-level data and then explore the association between minimum wage and SGA outcomes. Methods Retrospective cross-sectional analyses of all singleton births in Canada from 2000-2016 modeled SGA births through logistic regression, adjusting for individual and contextual risk factors. These models were then further adjusted for real minimum wage lagged by nine months. Analyses in both studies were stratified by four provinces (Ontario, Quebec, Alberta, and BC). Two subgroup analyses on single and all mothers residing in low income neighborhoods were further conducted. Results A secular upward trend in SGA births extended from 2000-2016 and was not completely explained by changes in maternal age, parental birthplace, marital status, community size and neighborhood income quintile. A dollar increase in real minimum wage was associated with 2% lower odds of an SGA birth (95% CI 0.97, 0.99), when adjusting for all other confounders. Provincially-stratified analyses and subgroup analysis of mothers in low income neighbourhoods, however, had null findings. For single mothers residing in low income neighbourhoods, a dollar increase in real minimum wage was associated with 3.0% [95% CI: 1.01, 1.05] higher odds of an SGA birth, adjusting for all other confounders. Conclusion SGA trends in Canada result from complex interactions of many variables. Not all of these variables, including risk factors such as smoking, were available at an individual level for analysis. Intermediate income and employment pathways between real minimum wage and SGA births, specifically for low income single mothers, require further exploration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".