Using the General Social Survey – National Death Index cohort to study the relationship between neighbourhood fear and mortality in the USA
Bibliographic record
Abstract
OBJECTIVES: Fear of crime is associated with adverse mental health outcomes and reduced social interaction independent of crime. Because mental health and social interactions are associated with poor physical health, fear of crime may also be associated with death. The main objective is to determine whether neighbourhood fear is associated with time to death. SETTING AND PARTICIPANTS: Data from the 1978-2008 General Social Survey were linked to mortality data using the National Death Index (GSS-NDI) (n=20 297). METHODS: GSS-NDI data were analysed to assess the relationship between fear of crime at baseline and time to death among adults after removing violent deaths. Fear was measured by asking respondents if they were afraid to walk alone at night within a mile of their home. Crude and adjusted HRs were calculated using survival analysis to calculate time to death. Analyses were stratified by sex. RESULTS: Among those who responded that they were fearful of walking in their neighbourhood at night, there was a 6% increased risk of death during follow-up in the adjusted model though this was not significant (HR=1.06, 95% CI 0.99 to 1.13). In the fully adjusted models examining risk of mortality stratified by sex, findings were significant among men but not women. Among men, in the adjusted model, there was an 8% increased risk of death during follow-up among those who experienced fear at baseline in comparison with those who did not experience fear (HR=1.08, 95% CI 1.02 to 1.14). CONCLUSIONS: Research has recently begun examining fear as a public health issue. With an identified relationship with mortality among men, this is a potential public health problem that must be examined more fully.
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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 | 0.010 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".