Associations between Traffic-Related Air Pollution and Cognitive Function in Australian Urban Settings: The Moderating Role of Diabetes Status
Abstract
:1. Introduction
2. Materials and Methods
2.1. Measures
2.1.1. Exposures: TRAP Measures
2.1.2. Outcomes: Cognitive Function Measures
2.1.3. Confounding Factors and Covariates
2.1.4. Diabetes Status as an Effect Modifier
2.2. Data Analytic Plan
3. Results
4. Discussion
Strengths and Limitations
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Characteristic | Total Sample n = 4141 | Diabetes Status | ||
---|---|---|---|---|
Diabetes (n = 405) | IGT/IFG (n = 620) | Normal Glucose Tolerance (n = 3003) | ||
Socio-demographics | ||||
Age (years), M ± SD | 61.1 ± 11.4 | 67.2 ± 10.1 | 64.5 ± 11.4 | 59.6 ± 11.0 |
Sex, female, % | 55.2 | 45.4 | 47.1 | 58.0 |
Educational attainment, % | ||||
Up to secondary | 32.7 | 39.3 | 41.1 | 30.1 |
Trade, associate diploma | 43.6 | 41.0 | 31.13 | 44.2 |
Bachelor degree, postgraduate | 23.1 | 18.3 | 17.1 | 25.2 |
Missing data | 0.6 | 1.5 | 0.7 | 0.5 |
Employment status, % | ||||
Not employed | 30.4 | 47.7 | 38.9 | 26.4 |
Paid employment | 52.2 | 34.8 | 45.2 | 56.3 |
Volunteer | 15.1 | 14.6 | 13.4 | 15.7 |
Missing data | 2.3 | 3.0 | 2.6 | 1.7 |
Household income (annual), % | ||||
Up to AUD 49,999 | 32.9 | 47.9 | 39.0 | 29.9 |
AUD 50,000–AUD 99,999 | 26.8 | 21.5 | 26.0 | 28.0 |
AUD 100,000 and over | 28.9 | 14.6 | 23.1 | 32.1 |
Missing data | 11.5 | 16.0 | 11.9 | 10.0 |
Living arrangements, % | ||||
Couple without children | 48.2 | 50.9 | 53.6 | 47.2 |
Couple with children | 26.8 | 15.6 | 21.1 | 29.4 |
Other | 22.4 | 30.4 | 22.6 | 21.6 |
Missing data | 2.4 | 3.2 | 2.7 | 1.8 |
English-speaking background, % | 89.9 | 83.7 | 87.4 | 91.5 |
Area-level IRSAD, M ± SD | 6.4 ± 2.7 | 5.9 ± 2.8 | 6.3 ± 2.7 | 6.5 ± 2.7 |
Residential self-selection—access to destinations, M ± SD | 3.0 ± 1.4 | 3.0 ± 1.3 | 3.0 ± 1.3 | 2.9 ± 1.3 |
Missing data, % | 9.0 | 9.4 | 10.5 | 8.0 |
Residential self-selection—recreational facilities, M ± SD | 3.1 ± 1.5 | 3.0 ± 1.6 | 3.1 ± 1.5 | 3.1 ± 1.4 |
Missing data, % | 8.7 | 9.1 | 10.2 | 7.7 |
Health-related variables | ||||
Diabetes status, % | ||||
Diabetes | 9.8 | - | - | - |
IGT/IFG | 15.0 | - | - | - |
Normal glucose tolerance | 72.5 | - | - | - |
Missing data, % | 2.7 | - | - | - |
Heart problems/stroke history, % | 8.7 | 19.8 | 10.5 | 6.8 |
Missing data, % | 1.0 | 1.5 | 0.2 | 0.0 |
Tobacco-smoking status, % | ||||
Current smoker | 7.0 | 4.2 | 8.7 | 7.2 |
Previous smoker | 35.9 | 44.0 | 37.6 | 34.4 |
Non-smoker | 54.5 | 48.6 | 51.0 | 56.6 |
Missing data, % | 2.6 | 3.2 | 2.7 | 1.8 |
Cognitive function, M ± SD | ||||
Memory, CVLT score | 6.5 ± 2.4 | 5.6 ± 2.4 | 6.2 ± 2.4 | 6.7 ± 2.4 |
Missing data, % | 2.3 | 5.2 | 1.5 | 1.7 |
Processing speed, SDMT score | 49.7 ± 11.6 | 43.6 ± 12.4 | 47.2 ± 12.1 | 51.1 ± 11.0 |
Missing data, % | 2.0 | 4.0 | 1.3 | 1.6 |
Characteristic | Total Sample n = 4141 | Diabetes Status | ||
---|---|---|---|---|
Diabetes (n = 405) | IGT/IFG (n = 620) | Normal Glucose Tolerance (n = 3003) | ||
Road density (100 m/km2) | ||||
200 m Euclidean buffer | 117.1 ± 42.0 | 120.7 ± 42.9 | 116.8 ± 42.4 | 117.1 ± 41.8 |
300 m Euclidean buffer | 114.9 ± 40.1 | 118.9 ± 39.0 | 114.6 ± 39.7 | 114.6 ± 40.4 |
500 m Euclidean buffer | 107.4 ± 37.7 | 111.0 ± 35.5 | 107.4 ± 36.5 | 107.1 ± 38.2 |
1000 m Euclidean buffer | 95.8 ± 34.0 | 99.5 ± 33.2 | 96.6 ± 33.2 | 95.1 ± 34.2 |
1600 m Euclidean buffer | 87.6 ± 32.3 | 91.2 ± 31.9 | 89.1 ± 31.5 | 86.8 ± 32.4 |
Minor road density (100 m/km2) | ||||
200 m Euclidean buffer | 88.6 ± 36.7 | 92.1 ± 37.6 | 89.3 ± 36.4 | 88.1 ± 36.7 |
300 m Euclidean buffer | 83.0 ± 32.7 | 86.7 ± 32.4 | 84.0 ± 32.9 | 82.4 ± 32.6 |
500 m Euclidean buffer | 75.7 ± 29.1 | 79.3 ± 28.8 | 77.1 ± 28.9 | 75.0 ± 29.1 |
1000 m Euclidean buffer | 66.1 ± 26.3 | 70.0 ± 26.3 | 67.9 ± 25.8 | 65.1 ± 26.2 |
1600 m Euclidean buffer | 59.6 ± 25.2 | 63.6 ± 25.3 | 61.7 ± 24.9 | 58.5 ± 25.2 |
Major road density (100 m/km2) | ||||
200 m Euclidean buffer | 9.7 ± 16.9 | 10.6 ± 17.7 | 9.6 ± 17.5 | 9.5 ± 16.6 |
300 m Euclidean buffer | 13.3 ± 17.0 | 14.7 ± 17.2 | 13.7 ± 17.7 | 13.1 ± 16.9 |
500 m Euclidean buffer | 13.6 ± 13.3 | 14.6 ± 13.4 | 13.9 ± 13.4 | 13.4 ± 13.3 |
1000 m Euclidean buffer | 13.1 ± 8.9 | 14.0 ± 9.0 | 13.4 ± 9.0 | 13.0 ± 8.9 |
1600 m Euclidean buffer | 12.4 ± 7.4 | 12.9 ± 7.5 | 12.8 ± 7.6 | 12.2 ± 7.3 |
Distance to nearest busy road (100 m) | 4.57 ± 4.98 | 4.38 ± 5.05 | 4.48 ± 4.86 | 4.59 ± 4.91 |
NO2 (ppb) | 5.53 ± 2.05 | 5.68 ± 2.10 | 5.47 ± 1.88 | 5.50 ± 2.07 |
TRAP Measures | Memory (CVLT Score) | Processing Speed (SDMT Score) | ||||
---|---|---|---|---|---|---|
β | 95% CI | p | β | 95% CI | p | |
Road density (100 m/km2) | ||||||
200 m Euclidean buffer | 0.003 | 0.001, 0.005 | 0.008 | 0.005 | −0.002, 0.012 | 0.173 |
300 m Euclidean buffer | 0.002 | −0.0003, 0.004 | 0.088 | 0.005 | −0.003, 0.013 | 0.257 |
500 m Euclidean buffer | 0.002 | −0.0003, 0.004 | 0.084 | 0.003 | −0.006, 0.012 | 0.507 |
1000 m Euclidean buffer | 0.003 | 0.001, 0.006 | 0.018 | 0.002 | −0.008, 0.013 | 0.678 |
1600 m Euclidean buffer | 0.004 | 0.001, 0.007 | 0.015 | 0.007 | −0.005, 0.018 | 0.263 |
Minor road density (100 m/km2) | ||||||
200 m Euclidean buffer | 0.002 | −0.0001, 0.004 | 0.058 | 0.001 | −0.008, 0.010 | 0.831 |
300 m Euclidean buffer | 0.001 | −0.002, 0.004 | 0.424 | −0.0004 | −0.010, 0.010 | 0.932 |
500 m Euclidean buffer | 0.001 | −0.002, 0.004 | 0.686 | −0.009 | −0.021, 0.003 | 0.145 |
1000 m Euclidean buffer | 0.002 | −0.002, 0.005 | 0.425 | −0.012 | −0.026, 0.003 | 0.106 |
1600 m Euclidean buffer | 0.001 | −0.003, 0.006 | 0.510 | −0.008 | −0.024, 0.008 | 0.311 |
Major road density (100 m/km2) | ||||||
200 m Euclidean buffer | 0.003 | −0.002, 0.007 | 0.268 | 0.005 | −0.012, 0.023 | 0.558 |
300 m Euclidean buffer | 0.001 | −0.003, 0.006 | 0.614 | 0.006 | −0.012, 0.024 | 0.535 |
500 m Euclidean buffer | 0.005 | −0.001, 0.011 | 0.097 | 0.020 | −0.005, 0.044 | 0.116 |
1000 m Euclidean buffer | 0.010 | 0.001, 0.020 | 0.038 | 0.034 | −0.007, 0.079 | 0.101 |
1600 m Euclidean buffer | 0.014 | 0.002, 0.026 | 0.026 | 0.055 | 0.004, 0.105 | 0.036 |
Distance to nearest busy road (100 m) | −0.0004 | −0.017, 0.016 | 0.963 | −0.054 | −0.118, 0.011 | 0.102 |
TRAP Measures | Memory (CVLT Score) | Processing Speed (SDMT Score) | ||
---|---|---|---|---|
F (2, 4114) | p | F (2, 4114) | p | |
Road density (100 m/km2) | ||||
200 m Euclidean buffer | 0.75 | 0.472 | 0.27 | 0.766 |
300 m Euclidean buffer | 0.96 | 0.383 | 0.57 | 0.566 |
500 m Euclidean buffer | 0.56 | 0.573 | 0.61 | 0.542 |
1000 m Euclidean buffer | 1.18 | 0.307 | 1.93 | 0.145 |
1600 m Euclidean buffer | 1.51 | 0.221 | 2.60 | 0.074 |
Minor road density (100 m/km2) | ||||
200 m Euclidean buffer | 0.22 | 0.800 | 0.30 | 0.741 |
300 m Euclidean buffer | 0.20 | 0.818 | 0.28 | 0.753 |
500 m Euclidean buffer | 0.36 | 0.701 | 0.20 | 0.819 |
1000 m Euclidean buffer | 0.20 | 0.815 | 1.46 | 0.231 |
1600 m Euclidean buffer | 0.08 | 0.921 | 2.94 | 0.053 |
Major road density (100 m/km2) | ||||
200 m Euclidean buffer | 2.22 | 0.108 | 0.61 | 0.543 |
300 m Euclidean buffer | 4.80 | 0.008 | 2.98 | 0.050 |
500 m Euclidean buffer | 2.28 | 0.102 | 1.16 | 0.314 |
1000 m Euclidean buffer | 1.76 | 0.172 | 0.57 | 0.567 |
1600 m Euclidean buffer | 3.16 | 0.043 | 1.66 | 0.190 |
Distance to nearest busy road (100 m) | 0.84 | 0.432 | 1.33 | 0.265 |
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Tham, R.; Wheeler, A.J.; Carver, A.; Dunstan, D.; Donaire-Gonzalez, D.; Anstey, K.J.; Shaw, J.E.; Magliano, D.J.; Martino, E.; Barnett, A.; et al. Associations between Traffic-Related Air Pollution and Cognitive Function in Australian Urban Settings: The Moderating Role of Diabetes Status. Toxics 2022, 10, 289. https://doi.org/10.3390/toxics10060289
Tham R, Wheeler AJ, Carver A, Dunstan D, Donaire-Gonzalez D, Anstey KJ, Shaw JE, Magliano DJ, Martino E, Barnett A, et al. Associations between Traffic-Related Air Pollution and Cognitive Function in Australian Urban Settings: The Moderating Role of Diabetes Status. Toxics. 2022; 10(6):289. https://doi.org/10.3390/toxics10060289
Chicago/Turabian StyleTham, Rachel, Amanda J. Wheeler, Alison Carver, David Dunstan, David Donaire-Gonzalez, Kaarin J. Anstey, Jonathan E. Shaw, Dianna J. Magliano, Erika Martino, Anthony Barnett, and et al. 2022. "Associations between Traffic-Related Air Pollution and Cognitive Function in Australian Urban Settings: The Moderating Role of Diabetes Status" Toxics 10, no. 6: 289. https://doi.org/10.3390/toxics10060289