Historical Atmospheric Lead Concentrations (1960‐1974) and Memory Problems Half a Century Later: Findings from Two Large, Independent Representative Samples
Bibliographic record
Abstract
Abstract Background Lead exposure has adverse impacts on cognition and dementia risk factors such as hypertension. A major historical source of lead exposure was via atmospheric pollution due to leaded gasoline. Method We mapped historical atmospheric lead levels (HALL) in the contiguous US using measurements obtained by the US EPA from 1960 to 1974, a period of high leaded gasoline combustion. We extrapolated HALL by kriging and calculated mean HALL for each public use microdata area (PUMA). Our analyses include only PUMAs which contained at least one lead measurement in 1960‐74. We obtained individual‐level data of self‐reported memory problems, from the American Community Survey (ACS) in two time periods, 2012‐2017 ( n = 368,208) and 2018‐2021 ( n = 276,476). The samples were restricted to respondents aged 65 and older living in their natal state. We calculated odds ratios using HALL as the exposure variable and self‐reported memory problems as the outcome, controlling for respondents’ age, sex, race/ethnicity, and education. We used individuals in PUMAs with the lowest HALL (< 0.4 µg/m 3 ) as reference in comparison to those in PUMAs with moderate (0.4‐.79 µg/m 3 ), high (0.8‐1.19 µg/m 3 ) and extremely high HALL (>=1.2 µg/m 3 ). Result In the 2012‐2017 ACS, in comparison to older adults living in PUMAs with the lowest HALL, the odds of reported memory impairment were higher in those in PUMAs with moderate (Odds ratio (OR)=1.21; 95% CI=1.17‐1.25), high (OR=1.21; 95% CI=1.17‐1.25) and extremely high HALL levels (OR=1.19; 95% CI=1.13‐1.25). We replicated the study using 2018‐2021 ACS data and found comparable outcomes for older adults living in PUMAs with moderate (OR = 1.17; 95% CI=1.12‐1.21), high (OR=1.20; 95% CI=1.16‐1.25) and very high HALL (OR=1.22; 95% CI=1.15‐1.29). Conclusion We observed in two very large ( n >250,000) independent representative samples that older adults had approximately 20% higher odds of reporting memory problems if they lived in PUMAs that had HALL > 0.4 µg/m 3 compared to <0.4 µg/m 3 . This adds to the evidence implicating lasting health outcomes, including cognition, due to earlier life lead exposure from air pollution. The precipitous decline in atmospheric lead exposure in the last quarter of the 20 th century may help to explain the declining incidence of dementia in the US.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".