Trajectories of Exposure to Neighborhood Deprivation and the Odds of Experiencing Intimate Partner Violence Among Women: Are There Sensitive Periods for Exposure?
Bibliographic record
Abstract
Neighborhood disadvantage is commonly hypothesized to be positively associated with intimate partner violence (IPV) against women. However, longitudinal investigation of this association has been limited, with no studies on whether the timing of exposure matters. We used data from 2,115 women in the UK-based Avon Longitudinal Study of Parents and Children. Exposure to neighborhood-level deprivation was measured at 10-time points from baseline (gestation) until age 18. Family-level socioeconomic characteristics were measured at baseline. At age 21, participants self-reported whether they had experienced any IPV since age 18. We used a three-step bias-adjusted longitudinal latent class analysis to investigate how different patterns of neighborhood deprivation exposure were associated with the odds of experiencing IPV. A total of 32% of women experienced any IPV between ages 18 and 21. Women who consistently lived in deprived neighborhoods (chronic high deprivation) or spent their early childhoods in more deprived neighborhoods and later moved to less deprived neighborhoods (decreasing deprivation) had higher odds of experiencing IPV compared to those who consistently lived in non-deprived neighborhoods. The odds of experiencing IPV did not consistently differ between women who lived in non-deprived neighborhoods during early childhood and later moved to deprived neighborhoods (increasing deprivation) and those stably in non-deprived neighborhoods. Living in more deprived neighborhoods during early childhood, regardless of later exposure, was associated with higher odds of experiencing later IPV. This is congruent with prior research demonstrating the persistent effects of early neighborhood disadvantage on health and well-being. Replication, and underlying mechanisms, should be assessed across contexts.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".