Household income and contraceptive methods among female youth: a cross-sectional study using the Canadian Community Health Survey (2009–2010 and 2013–2014)
Bibliographic record
Abstract
BACKGROUND: Low socioeconomic status is one of many barriers that may limit access to family planning services. We aimed to examine the relation between household income and contraceptive methods among female youth in Canada. METHODS: Our study population included sexually active females aged 15-24 who were trying to avoid pregnancy. We used cross-sectional data from the 2009-2010 and 2013-2014 cycles of the Canadian Community Health Survey to compare household income and other sociodemographic covariates for those using oral contraceptives, injectable contraceptives, condoms or a dual method (condoms plus oral or injectable contraceptives). RESULTS: Of female youth at risk for unintended pregnancy, 59.2% reported using oral contraceptives, 29.0% used dual methods, 16.8% used condoms only, 2.5% used injectable contraceptives and 13.6% did not use contraception. In multiple regression models, lower annual household income (< $80 000) was associated with decreased use of oral contraceptives (relative risk [RR] 0.85, 95% confidence interval [CI] 0.80-0.91) and dual methods (RR 0.81, 95% CI 0.71-0.91), increased use of condoms (RR 1.36, 95% CI 1.11-1.67) and injectable contraceptives (RR 1.69, 95% CI 0.98-2.92), and a greater risk of contraceptive nonuse (RR 1.19, 95% CI 0.94-1.50). INTERPRETATION: We found that lower household income was associated with decreased use of oral contraceptives and increased reliance on injectable contraceptives and condoms only. Young, low-income females may face barriers to accessing the full range of contraceptive methods available in Canada. Easier access to affordable contraception may decrease the number of female youth at risk for unintended pregnancy due to financial barriers.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".