Do Differences in Social Environments Explain Gender Differences in Recreational Walking across Neighbourhoods?
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design and Data Collection
2.2. Measures
2.2.1. Outcome Variable
2.2.2. Independent Variable
2.2.3. Measures of the Neighbourhood Social Environment
- Creating a mean score of the exposure for each neighbourhood ();
- Using an ANOVA model of the exposure, fitted using maximum likelihood to obtain estimates of the between –and within– neighbourhood variance. This was then used to obtain an estimate of the reliability of the exposure estimate for each neighbourhood, using Equation (1), where is the between-neighbourhood variance, the within-neighbourhood variance, and the number of informants within the neighbourhood;
- Estimating the exposure intercept ; and
- Calculating the EBE estimate using Equation (2)
2.2.4. Covariates
2.3. Statistical Analyses
2.4. Modelling Strategy
3. Results
3.1. The Relationship between Gender and Recreational Walking
3.2. Variation of the Average Gender Differences in Recreational Walking across Neighbourhoods
3.3. Between-Neighbourhood Variation in the Probability of Recreational Walking for Men and Women
3.4. The Contribution of the Social Environment to Explaining Neighbourhood Differences in the Gender and Walking for Recreation Relationship
3.5. The Contribution of the Social Environment to Explaining Between-Neighbourhood Variation in Walking for Recreation for Men and Women
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Sociodemographic Characteristics | Men | Women | ||||
---|---|---|---|---|---|---|
Total | 0 mins | 1–840 mins | Total | 0 mins | 1–840 mins | |
Total (n) | 2844 | 859 | 1985 | 3799 | 1011 | 2788 |
n | % | % | n | % | % | |
Age | ||||||
42–50 years | 1152 | 30.8 | 69.2 | 1349 | 26.9 | 73.1 |
51–59 years | 997 | 31.2 | 68.8 | 1416 | 26.6 | 73.4 |
60–67 years | 695 | 27.8 | 72.2 | 1034 | 26.3 | 73.7 |
Education | ||||||
Bachelor’s degree or higher | 988 | 24.6 | 75.4 | 1203 | 23.1 | 76.9 |
Diploma/associate degree | 340 | 25.0 | 75.0 | 421 | 21.4 | 78.6 |
Certificate | 620 | 34.2 | 65.8 | 548 | 24.6 | 75.4 |
No post-school qualification | 896 | 35.6 | 64.4 | 1627 | 31.2 | 68.8 |
Occupation | ||||||
Professional | 1071 | 26.3 | 73.7 | 1077 | 22.7 | 77.3 |
White collar | 336 | 25.6 | 74.4 | 980 | 28.0 | 72.0 |
Blue collar | 630 | 42.2 | 57.8 | 204 | 35.8 | 64.2 |
Not in workforce | 506 | 26.1 | 73.9 | 1055 | 25.4 | 74.6 |
Not easily classifiable | 301 | 30.9 | 69.1 | 483 | 31.5 | 68.5 |
Income | ||||||
$130,000+ | 664 | 23.8 | 76.2 | 580 | 23.3 | 76.7 |
$72,800–129,999 | 811 | 27.4 | 72.6 | 889 | 26.5 | 73.5 |
$52,000–72,799 | 395 | 35.2 | 64.8 | 519 | 27.4 | 72.6 |
$26,000–51,999 | 465 | 32.9 | 67.1 | 702 | 25.6 | 74.4 |
Less than $25,999 | 234 | 34.2 | 65.8 | 478 | 34.1 | 65.9 |
Not classified | 275 | 38.9 | 61.1 | 631 | 24.6 | 75.4 |
Effects | Baseline | Perception of Social Cohesion | Perception of Incivilities | Perception of Safety from Crime | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
M1 | M2 | M3 | M4 | M5 | M6 | M7 | ||||||||
Fixed Effects a | OR | 95% CrI | OR | 95% CrI | OR | 95% CrI | OR | 95% CrI | OR | 95% CrI | OR | 95% CrI | OR | 95% CrI |
Men | 1.00 | -- | 1.00 | -- | 1.00 | -- | 1.00 | -- | 1.00 | -- | 1.00 | -- | 1.00 | -- |
Women | 1.12 | 0.99, 1.27 | 1.12 | 0.99, 1.28 | 1.12 | 0.98, 1.27 | 1.12 | 0.99, 1.28 | 1.12 | 0.98, 1.28 | 1.12 | 0.98, 1.27 | 1.12 | 0.98, 1.27 |
L2 exposure b | -- | -- | 0.99 | 0.91, 1.07 | 0.96 | 0.87, 1.06 | 1.17 | 1.06, 1.29 | 1.17 | 1.04, 1.32 | 0.91 | 0.83, 1.01 | 0.91 | 0.81, 1.03 |
Interactions | ||||||||||||||
Males | -- | -- | -- | -- | 1 | -- | -- | -- | 1 | -- | -- | -- | 1 | -- |
L2 * women c | -- | -- | -- | -- | 1.07 | 0.94, 1.21 | -- | -- | 1.00 | 0.87, 1.14 | -- | -- | 1.00 | 0.88, 1.14 |
Random effects | ||||||||||||||
Random coefficients (s.e.) d | ||||||||||||||
Men | -- | -- | -- | -- | -- | -- | -- | |||||||
Women | 0.080 (0.036) | 0.083 (0.038) | 0.081 (0.036) | 0.083 (0.036) | 0.081 (0.036) | 0.084 (0.036) | 0.082 (0.036) | |||||||
p-value | 0.013 | 0.014 | 0.012 | 0.011 | 0.013 | 0.011 | 0.016 | |||||||
Variance functions (s.e.) e | ||||||||||||||
Men | 0.050 (0.018) | 0.051 (0.019) | 0.050 (0.018) | 0.049 (0.017) | 0.049 (0.018) | 0.051 (0.019) | 0.051 (0.018) | |||||||
Women | 0.109 (0.025) | 0.110 (0.025) | 0.110 (0.025) | 0.107 (0.024) | 0.107 (0.025) | 0.109 (0.025) | 0.109 (0.025) |
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Ghani, F.; Rachele, J.N.; Loh, V.H.; Washington, S.; Turrell, G. Do Differences in Social Environments Explain Gender Differences in Recreational Walking across Neighbourhoods? Int. J. Environ. Res. Public Health 2019, 16, 1980. https://doi.org/10.3390/ijerph16111980
Ghani F, Rachele JN, Loh VH, Washington S, Turrell G. Do Differences in Social Environments Explain Gender Differences in Recreational Walking across Neighbourhoods? International Journal of Environmental Research and Public Health. 2019; 16(11):1980. https://doi.org/10.3390/ijerph16111980
Chicago/Turabian StyleGhani, Fatima, Jerome N Rachele, Venurs HY Loh, Simon Washington, and Gavin Turrell. 2019. "Do Differences in Social Environments Explain Gender Differences in Recreational Walking across Neighbourhoods?" International Journal of Environmental Research and Public Health 16, no. 11: 1980. https://doi.org/10.3390/ijerph16111980