A Hierarchical Age–Period–Cohort Analysis of Breast Cancer Mortality and Disability Adjusted Life Years (1990–2015) Attributable to Modified Risk Factors among Chinese Women
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data Source
2.2. Outcomes
2.3. Predictors
2.4. Statistical Analysis
3. Results
3.1. Mortality Rates (MRs)
3.2. Disability-Adjusted Life Years (DALYs)
3.3. Random Effects of Age, Period, Cohort, and Interaction with Risk Factors
3.4. Fixed and Random Effects Comparison
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Predictors | GLM | Mixed Effect Models | ||||
Model Estimate | Model 1 Estimate | Model 2 Estimate | Model 3 Estimate | |||
(Intercept) | −0.164 (0.591) | −1.733 (0.000) | −1.128 (0.006) | −0.164 (0.662) | ||
Age | 0.011 (0.046) | 0.042 (0.000) | 0.030 (0.001) | 0.010 (0.0450) | ||
Period (Reference 1990) | ||||||
1995 | 0.074 (0.840) | 0.057 (0.576) | 0.074 (0.797) | 0.074 (0.798) | ||
2000 | 0.209 (0.568) | 0.135 (0.186) | 0.209 (0.468) | 0.209 (0.471) | ||
2005 | 0.344 (0.349) | 0.215 (0.036) | 0.344(0.233) | 0.344 (0.236) | ||
2010 | 0.663 (0.072) | 0.392 (0.000) | 0.662 (0.022) | 0.663 (0.023) | ||
2015 | 0.950 (0.010) | 0.587 (0.000) | 0.950 (0.001) | 0.950 (0.001) | ||
Risk (Reference: alcohol use) | ||||||
HBMI | 2.155 (0.000) | 1.438 (0.000) | 1.437 (0.000) | 2.154 (0.000) | ||
Low PA | 0.096 (0.744) | −0.394 (0.191) | −0.394 (0.195) | −0.096 (0.848) | ||
Smoking | −0.354 (0.277) | −0.435 (0.160) | −0.435 (0.164) | −0.354 (0.526) | ||
Age × 1995 | 0.003 (0.705) | 0.002 (0.630) | 0.003 (0.632) | |||
Age × 2000 | 0.007 (0.321) | 0.006 (0.207) | 0.007 (0.210) | |||
Age × 2005 | 0.011 (0.108) | 0.010 (0.041) | 0.011 (0.042) | |||
Age × 2010 | 0.020 (0.003) | 0.020 (0.000) | 0.020 (0.000) | |||
Age × 2015 | 0.030 (0.000) | 0.029 (0.000) | 0.030 (0.000) | |||
Age × HBMI | 0.072 (0.000) | 0.072 (0.000) | ||||
Age × Low PA | −0.008 (0.120) | −0.008 (0.365) | ||||
Age × Smoking | 0.000 (0.962) | 0.000 (0.978) | ||||
Model Selection Parameter Estimates among GLM and Mixed-Effect Models | ||||||
Model | AIC | BIC | Log Likelihood | Test | L Ratio | p-Value |
GLM | 545.1321 | 615.1202 | −253.566 | |||
Model 1 | 573.7778 | 621.6644 | −273.889 | GLM vs. 1 | 40.64567 | <0.0001 |
Model 2 | 538.8635 | 605.0037 | −251.432 | 1 vs. 2 | 44.86496 | <0.0001 |
Model 3 | 485.8985 | 563.2537 | −221.949 | 2 vs. 3 | 59.0393 | <0.0001 |
Predictors | GLM | Mixed Effect Models | ||||
Model Estimate | Model 1 Estimate | Model 2 Estimate | Model 3 Estimate | |||
(Intercept) | 5.143 (0.635) | −24.939 (0.020) | −13.866 (0.232) | 5.143 (0.735) | ||
Age | 0.103 (0.040) | 0.698 (0.002) | 0.483 (0.029) | 0.104 (0.042) | ||
Period (Reference: 1990) | ||||||
1995 | 0.836 (0.949) | 1.381 (0.565) | 0.836 (0.905) | 0.836 (0.905) | ||
2000 | 3.020 (0.817) | 3.098 (0.197) | 3.019 (0.667) | 3.019 (0.669) | ||
2005 | 5.591 (0.669) | 4.953 (0.039) | 5.590(0.426) | 5.591 (0.429) | ||
2010 | 10.290 (0.043) | 8.934 (0.000) | 10.290 (0.0144) | 10.290 (0.015) | ||
2015 | 14.734(0.026) | 13.600 (0.000) | 14.734 (0.036) | 14.734 (0.037) | ||
Risk (Reference: alcohol use) | ||||||
HBMI | 37.666 (0.000) | 31.728 (0.000) | 31.728 (0.000) | 37.666 (0.006) | ||
Low PA | −2.368 (0.822) | −10.199 (0.247) | −10.198 (0.251) | −2.440 (0.909) | ||
Smoking | −10.349 (0.374) | −11.891 (0.190) | −11.891 (0.194) | −11.162 (0.641) | ||
Age × 1995 | 0.043 (0.858) | 0.042 (0.738) | 0.043 (0.739) | |||
Age × 2000 | 0.118 (0.621) | 0.118 (0.357) | 0.118 (0.360) | |||
Age × 2005 | 0.204 (0.394) | 0.203 (0.113) | 0.204 (0.115) | |||
Age × 2010 | 0.372 (0.121) | 0.371 (0.004) | 0.372 (0.004) | |||
Age × 2015 | 0.548 (0.023) | 0.547 (0.000) | 0.548 (0.000) | |||
Age × HBMI | 1.388 (0.000) | 1.388 (0.000) | ||||
Age × Low PA | −0.131 (0.497) | −0.129 (0.741) | ||||
Age × Smoking | 0.007 (0.975) | 0.0193 (0.963) | ||||
Models Selection Parameters Estimates among GLM and Mixed Effect Models | ||||||
Model | AIC | BIC | Log Likelihood | Test | L. Ratio | p-Value |
GLM | 2646.76 | 2716.74 | −1304.38 | |||
Model 1 | 2451.29 | 2499.18 | −1212.64 | GLM vs. 1 | 183.46 | <0.0001 |
Model 2 | 2434.55 | 2500.86 | −1199.27 | 1 vs. 2 | 26.73 | <0.0001 |
Model 3 | 2422.40 | 2499.76 | −1190.20 | 2 vs. 3 | 18.14 | <0.0004 |
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Mubarik, S.; Wang, F.; Malik, S.S.; Shi, F.; Wang, Y.; Nawsherwan; Yu, C. A Hierarchical Age–Period–Cohort Analysis of Breast Cancer Mortality and Disability Adjusted Life Years (1990–2015) Attributable to Modified Risk Factors among Chinese Women. Int. J. Environ. Res. Public Health 2020, 17, 1367. https://doi.org/10.3390/ijerph17041367
Mubarik S, Wang F, Malik SS, Shi F, Wang Y, Nawsherwan, Yu C. A Hierarchical Age–Period–Cohort Analysis of Breast Cancer Mortality and Disability Adjusted Life Years (1990–2015) Attributable to Modified Risk Factors among Chinese Women. International Journal of Environmental Research and Public Health. 2020; 17(4):1367. https://doi.org/10.3390/ijerph17041367
Chicago/Turabian StyleMubarik, Sumaira, Fang Wang, Saima Shakil Malik, Fang Shi, Yafeng Wang, Nawsherwan, and Chuanhua Yu. 2020. "A Hierarchical Age–Period–Cohort Analysis of Breast Cancer Mortality and Disability Adjusted Life Years (1990–2015) Attributable to Modified Risk Factors among Chinese Women" International Journal of Environmental Research and Public Health 17, no. 4: 1367. https://doi.org/10.3390/ijerph17041367