Assessing Heat-Related Mortality Risks among Rural Populations: A Systematic Review and Meta-Analysis of Epidemiological Evidence
Abstract
:1. Introduction
2. Materials and Methods
2.1. Search Strategy and Screening Criteria
- Studies not published in English;
- Studies not performed on human populations (non-epidemiological studies);
- Studies reporting no effect estimates (i.e., relative risks (RRs) or % change in mortality), those reporting effect estimates only for subpopulations, such as the elderly, but not for the entire population in the study area;
- Commentaries, review articles, and editorials;
- Studies on morbidity; and
2.2. Data Extraction
3. Results
3.1. Meta-Analysis
3.2. Sensitivity Analysis
4. Discussion
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
Appendix A
References
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Studies (Year Published) | Study Period | Location | Effect Estimate [RR per °C (95% CI)] | Potential Confounding Factors | Temperature Threshold (°C) | Mortality Outcome (s) | Study Population | Lag Period (Days) |
---|---|---|---|---|---|---|---|---|
Studies using daily mean temperature | ||||||||
Hajat et al., (2006) [33] | 1993–2003 | England & Wales | 1.020 (1.010, 1.030) | Ozone, PM2.5, seasonal varying factors, influenza epidemics | 17–18 | All-cause | N/A | 0–1 |
Hashizume et al., (2009) [15] | 1994–2002 | Matlab, Bangladesh | 1.629 (1.232, 2.152) | Seasonality | 30 | Cardiovascular | 220,000 | 0–1 |
Burkart et al., (2011) [34] | 2003–2007 | Bangladesh | 1.044 (0.990, 1.098) | Trend, season, day of the month and age | 28.9 | All-cause | ~1,000,000 | 0–1 |
Diboulo et al., (2012) [35] | 1999–2009 | Nouna, Burkina Faso | 1.026 (1.001, 1.052) | Time trends and seasonality | 30 | All-cause | 90,000 | 0–1 |
Lindeboom et al., (2012) [36] | 1983–2009 | Matlab, Bangladesh | 1.002 (1.001, 1.003) | Trend and seasonality | 29 | All-cause | 225,002 | 0–1 |
Azongo et al., (2012) [37] | 1995–2010 | Northern Ghana | 1.018 (1.007–1.029) | Time trends and seasonality | 30.7 | All-cause | N/A | 0–1 |
Urban et al., (2014) [38] | 1994–2009 | Czech Republic | 1.085 (1.05, 1.12) | Winter days during six epidemics | 23.5 | Cardiovascular | 3,400,000 | N/A |
Bai et al., (2014) [39] Bai et al., (2014) * | 2008–2012 2008–2012 | Naidong (Tibet), China Jiangzi (Tibet), China | 1.047 (0.181, 1.144) 1.063 (0.167, 2.020) 1.037 (0.222, 1.121) 1.134 (0.206, 2.217) | Seasonality and long-term trend Seasonality and long-term trend | 15.3 11.8 | All-cause and cardiovascular All-cause and cardiovascular | N/A N/A | 0–1 0–1 |
Chen et al., (2016) [20] | 2009–2013 | Jiangsu Province, China | 1.032 (1.028, 1.037) | Long-term trends and seasonality | 24.1 | All-cause | 73,900,000 | N/A |
Lee et al., (2016) [16] | 2007–2011 | Georgia, North & South Carolina, U.S. | 1.021 (0.995, 1.047) | PM2.5, age, race education, rural location | 28.0 | All-cause | N/A | N/A |
Zhang et al., (2017) [40] | 2009–2012 | Hubei, China | 1.14 (1.02, 1.26) | Long-term and seasonal trends | 27.7 | All-cause | 6,700,000 | 0–2 |
Studies using daily maximum temperature | ||||||||
Ingole et al., (2015) [41] | 2003–2012 | Vadu, India | 1.36 (1.30, 1.42) | Day of the week, secular trends and other time-varying confounding factors | 39.0 | All-cause | 131, 545 | 0 |
Madrigano et al., (2015) [42] | 1988–1999 | New York, New Jersey, Connecticut, U.S. | 1.007 (1.006, 1.008) | Ozone | 21.1 | All-cause | N/A | N/A |
Studies using weekly mean temperature | ||||||||
Alam et al., (2012) [43] | 1983–2009 | Abhoynagar, Bangladesh | 1.0 (no risk) | Rainfall | 23.0 | All-cause | 34,774 | 0–3 weeks |
Study (Year) | Location (Country) | Effect Size (95% Confidence Interval) | Weight% | ||
---|---|---|---|---|---|
Hajat (2006) | England & Wales | 1.020 | 1.010 | 1.030 | 14.20 |
Burkart (2011) | Bangladesh | 1.044 | 0.990 | 1.098 | 6.43 |
Diboulo (2012) | Nouna, Burkina Faso | 1.026 | 1.001 | 1.052 | 11.72 |
Lindeboom (2012) | Matlab, Bangladesh | 1.002 | 1.001 | 1.003 | 14.86 |
Azongo (2012) | Northern Ghana | 1.018 | 1.007 | 1.029 | 14.06 |
Bai (2014) | Naidong, China | 1.047 | 0.20 | 1.144 | 2.75 |
Bai (2014) * | Jiangzi, China | 1.037 | 0.222 | 1.121 | 3.52 |
Chen (2016) | Jiangsu Province, China | 1.032 | 1.028 | 1.037 | 14.35 |
Lee (2016) | Southeast U.S. | 1.021 | 0.995 | 1.047 | 13.77 |
Zhang (2017) | Hubei, China | 1.140 | 1.020 | 1.260 | 4.35 |
Pooled (I2 = 0.0%; p = 0.001) | 1.030 | 1.013 | 1.048 | 100 |
Study (Year) | Location | Effect Size (95% Confidence Interval) | Weight% | ||
---|---|---|---|---|---|
Hashizume (2009) | Matlab, Bangladesh | 1.629 | 1.232 | 2.152 | 5.10 |
Urban (2014) | Czech Republic | 1.085 | 1.05 | 1.12 | 32.28 |
Bai (2014) | Naidong, China | 1.063 | 0.20 | 2.02 | 23.80 |
Bai (2014) * | Jiangzi, China | 1.134 | 0.206 | 2.217 | 38.82 |
Pooled (I2 = 59.4%; p = 0.001) | 1.111 | 1.045 | 1.181 | 100 |
Study (Country) | Effect Size (95% Confidence Interval) | Weight% | ||
---|---|---|---|---|
Burkart (Bangladesh) | 1.044 | 0.990 | 1.098 | 18.29 |
Diboulo (Burkina Faso) | 1.026 | 1.001 | 1.052 | 4.79 |
Lindeboom (Bangladesh) | 1.002 | 1.001 | 1.003 | 5.99 |
Azongo (Ghana) | 1.018 | 1.007 | 1.029 | 10.08 |
Bai (China) | 1.047 | 0.200 | 1.144 | 18.55 |
Bai * (China) | 1.037 | 0.222 | 1.121 | 16.09 |
Chen (China) | 1.032 | 1.028 | 1.037 | 18.99 |
Zhang (China) | 1.140 | 1.020 | 1.260 | 7.23 |
Pooled (I2 = 0.0%; p = 0.004) | 1.036 | 1.012 | 1.061 | 100 |
Study (Country) | Effect Size (95% Confidence Interval) | % Weight | ||
---|---|---|---|---|
Hajat (England & Wales) | 1.020 | 1.010 | 1.030 | 87.1 |
Lee (USA) | 1.021 | 0.995 | 1.047 | 12.9 |
Pooled (I2 = 0.0%; p = 0.000) | 1.02 | 1.011 | 1.03 | 100 |
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Odame, E.A.; Li, Y.; Zheng, S.; Vaidyanathan, A.; Silver, K. Assessing Heat-Related Mortality Risks among Rural Populations: A Systematic Review and Meta-Analysis of Epidemiological Evidence. Int. J. Environ. Res. Public Health 2018, 15, 1597. https://doi.org/10.3390/ijerph15081597
Odame EA, Li Y, Zheng S, Vaidyanathan A, Silver K. Assessing Heat-Related Mortality Risks among Rural Populations: A Systematic Review and Meta-Analysis of Epidemiological Evidence. International Journal of Environmental Research and Public Health. 2018; 15(8):1597. https://doi.org/10.3390/ijerph15081597
Chicago/Turabian StyleOdame, Emmanuel A., Ying Li, Shimin Zheng, Ambarish Vaidyanathan, and Ken Silver. 2018. "Assessing Heat-Related Mortality Risks among Rural Populations: A Systematic Review and Meta-Analysis of Epidemiological Evidence" International Journal of Environmental Research and Public Health 15, no. 8: 1597. https://doi.org/10.3390/ijerph15081597