Gaps in Health and Wealth: The relationship between trends in income inequality and breastfeeding inequalities
Bibliographic record
Abstract
ABSTRACT ObjectivesThe objective of this study was to identify whether breastfeeding inequalities have increased between 1984 and 2014 and to examine whether trends in income inequality are related to breastfeeding inequalities. MethodsWe used linkable administrative data from the Population Health Research Data Repository. Our sample included all infants born in Manitoba, 1984 to 2014. We used area-level income – derived from the Canadian Census – to stratify infants into income quintiles. Canadian Census income data were also used to quantify provincial level income inequality for each fiscal year in our study period. Data from the hospital discharge abstract database were used to classify infants according to whether or not they had initiated breastfeeding. We linked infant data to maternal data using the Manitoba health insurance registry to capture maternal characteristics – including the mother’s postal code of residence and her age at first birth. We used generalized linear models to calculate income quintile-specific breastfeeding rates for each fiscal year in our observation period for all of Manitoba. We also calculated age-adjusted breastfeeding rates to account for the changing age distribution in Manitoba mothers, over time. We measured breastfeeding inequities using the concentration index as well as the rate ratio and rate difference (comparing the breastfeeding rate between the highest and lowest income quintiles). We quantified income inequality using the Gini coefficient on income. Trend analyses and two-sided Z-tests tested for changes, over time. Time by income-quintile interactions tested whether breastfeeding rates were statistically significantly different, across socioeconomic groups. ResultsBreastfeeding rates increased from 1985 to 2014, from 72% to 81% (p<0.01). The Gini coefficient increased from 0.16 to 0.21; a linear trend test of the Gini coefficient showed income inequality increased over the study period (p<0.05). Rate differences, rate ratios, and the Concentration index showed that significant breastfeeding inequalities existed throughout the study period. Trend tests revealed that breastfeeding inequalities did not increase, over time. ConclusionsAggregate analyses may suggest overall improvement when inequality persists. Although there was improvement in breastfeeding initiation rates, children from lower socioeconomic status continue to lag behind their counterparts. Policy-focused health equity research needs to measure outcomes, overall, and inequity across time.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".