Association of Short-Term Exposure to Meteorological Factors and Risk of Hand, Foot, and Mouth Disease: A Systematic Review and Meta-Analysis
Abstract
:1. Introduction
2. Methods
2.1. Search Strategy
2.2. Eligibility and Selection Criteria
2.3. Data Extraction
2.4. Quality Assessment
2.5. The Selection of Lag Effects and Exposure Metrics
2.6. Statistical Analysis
3. Results
3.1. Study Selection and Characteristics
3.2. The Overall Effects
3.3. Subgroup Analyses
3.3.1. Measure of Meteorological Factors
3.3.2. Exposure Time Resolution
3.3.3. Regional Climate
3.3.4. Human Development Index (HDI)
3.3.5. Gender and Age
3.4. Sensitivity Analysis and Publication Bias
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Conflicts of Interest
References
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Reference | Study Location | Study Period | Population | Ages | Exposure Variable | Statistical Model | Temporal Lags | Resolution | Climate Group | Measure Index | HDI Rank | Quality Scores | Outcome |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Zhu et al. (2015) [29] | Shandong, China | 2007–2012 | 108,377 | 0–5 years | Cumulative maximum temperature; cumulative minimum temperature | Distributed lag non-linear model (DLNM) with Poisson distribution, adjusting for relative humidity, rainfall, sunshine duration, DOW, public holidays, seasonal trend, and long trend | 0–14 days | Daily | Temperate climate | RR | High | 8 | Reported HFMD |
Chen et al. (2014) [19] | Guangzhou, China | 2009–2011 | 34,527 | 0–14 years | Mean temperature; relative humidity | Generalized additive model (GAM), adjusting for long-term trend, seasonal trend, day of week, and public holidays | 0–10 days | Daily | Temperate climate | IRR | High | 7 | Reported HFMD |
Yang et al. (2018) [12] | Hefei, China | 2011–2016 | NA | All | Mean temperature; rainfall; cumulative mean relative humidity | DLNM, adjusting for long-term trend, seasonal trend, and day of week | 0–20 days | Daily | Temperate climate | RR | High | 8 | Reported HFMD |
Xu et al. (2015) [37] | Beijing, China | 2010–2012 | 113,475 | 6–15 years | Mean temperature; relative humidity; cumulative maximum temperature; cumulative minimum temperature | A newly developed case-crossover design with DLNM, adjusting for day of week, public holidays, long-term trend, and seasonal trend | 0–13 days | Daily | Temperate climate | RRs | High | 7 | Reported HFMD |
Yu et al. (2018) [28] | Guilin, China | 2014–2016 | 88,742 | 0–14 years | Relative humidity; sunshine duration; wind speed; rainfall; cumulative maximum temperature; cumulative minimum temperature; cumulative maximum relative humidity; cumulative minimum relative humidity; | DLNM, adjusting for long-term trends, seasonality, differences in the annual at-risk population; day of week, and public holidays | 0–14 days | Daily | Temperate climate | RR | High | 7 | Reported HFMD |
Zhang et al. (2018) [38] | Henan, China | 2012–2013 | NA | 0–5 years | Mean temperature; relative humidity; rainfall; sunshine duration; wind speed | Bayesian space–time hierarchy mode, Poisson with log link regression and GeoDetector, adjusting for long-term trend and autocorrelation | None | None | Temperate climate | RR | High | 6 | Reported HFMD |
Qi et al. (2018) [9] | Shanghai, China | 2009–2015 | 51,776 | 0–15 years | Mean temperature; relative humidity | DLNM, adjusting for potential confounders of long time trend, DOW, and public holidays | 0–14 days | Daily | Temperate climate | RR | High | 8 | Reported HFMD |
Zhu et al. (2016) [21] | Shandong, China | 2007–2012 | 504,017 | 0–5 years | Mean temperature | DLNM, adjusting for seasonal trend, long time trend, DOW, and public holidays | 0–21 days | Daily | Temperate climate | RR | High | 9 | Reported HFMD |
Bo et al. (2020) [22] | 143city, China | 2009–2014 | 3,060,450 | 0–12 years | Relative humidity | DLNM, adjusting for long-term trends, seasonality, autocorrelation, DOW public holidays | 0–18 days | Daily | None | RR | High | 9 | Reported HFMD |
Wang et al. (2016) [39] | Hong Kong, China | 2009–2014 | 1534 | All | Rainfall; wind speed; sunshine duration; cumulative mean temperature: cumulative maximum relative cumulative minimum relative humidity | A combination of negative binomial generalized additive models and DLNM, adjusting for multiple environmental factors, long-term trends, and seasonality | 0–30 days | Daily | Tropical climate | RR | High | 7 | Reported HFMD |
Yin et al. (2016) [18] | Chengdu, China | 2010–2013 | 76,403 | 0–14 years | Mean temperature | DLNM, adjusting for seasonal trend, long time trend, DOW, and holidays | 0–13 days | Daily | Temperate climate | RR | High | 7 | Reported HFMD |
Guo et al. (2016) [26] | Guangdong, China | 2009–2013 | 400,408 | 0–14 years | Relative humidity; cumulative mean temperature; cumulative mean relative humidity | A mixed generalized additive models (MGAM), adjusting for seasonal trend, long time trend, DOW, and holidays | 0–14 days | Daily | Temperate climate | RR | High | 7 | Reported HFMD |
Hao et al. (2020) [13] | Wuhan, China | 2013–2017 | NA | All | Mean temperature; cumulative maximum temperature; cumulative minimum temperature; relative humidity; cumulative maximum relative humidity; cumulative minimum relative humidity | DLNM combined with Poisson regression, adjusting for DOW, seasonality, and long-term time trend | 0–14 days | Daily | Temperate climate | RR | High | 7 | Reported HFMD |
Xuan et al. (2017) [6] | Can Tho, Vietnam | 2012–2014 | NA | All | Mean temperature; relative humidity | Time-series regression analysis, adjusting for seasonality, long-term time trend, DOW, and the offset of population | 0–6 days | Daily | Tropical climate | ER | Low | 7 | Reported HFMD |
Gou et al. (2018) [23] | Gansu, China | 2010–2014 | NA | All | Mean temperature; relative humidity | Generalized linear regression models (GLM) with Poisson link and classification and regression trees (CART), adjusting for seasonality | 0–12 weeks | Weekly | Temperate climate | ER | High | 6 | Reported HFMD |
Onozuka et al. (2011) [24] | Fukuoka, Japan | 2000–2010 | 73,684 | All | Mean temperature; relative humidity | Negative binomial regression, adjusting for seasonal and inter-annual variations | 0–3 weeks | Weekly | Temperate climate | RR | High | 7 | Reported HFMD |
Hii et al. (2011) [11] | Singapore | 2001–2008 | NA | All | Maximum temperature minimum temperature | Time series Poisson regression models, adjusting for seasonality, long-term time trend, and autocorrelation | 0–2 weeks | Weekly | Temperate climate | RR | High | 8 | Reported HFMD |
Tian et al. (2018) [40] | Beijing, China | 2010–2012 | 114,777 | 0–4 years | Mean temperature; relative humidity; wind speed; sunshine duration | Bayesian spatiotemporal Poisson regression models; adjusting for seasonality and inter-annual variations | None | None | Temperate climate | RR | High | 7 | Reported HFMD |
Kim et al. (2016) [25] | South Korea | 2010–2013 | 214,642 | All | Mean temperature; relative humidity | GAM and Poisson distribution, controlling for seasonality, long-term time trend, and autocorrelation | 0–2 weeks | Weekly | Temperate climate | RR | High | 8 | Reported HFMD |
Xuan et al. (2019) [14] | Mekong Delta region, Vietnam | 2014–2016 | NA | 0–5 years | Mean temperature; humidity; cumulative rainfall | DLNM with quasi-Poisson, controlling for long-term trend and autocorrelation | 0–20 days | Daily | Temperate climate | RR | High | 7 | Reported HFMD |
Li et al. (2014) [7] | Guangzhou, China | 2009–2012 | 166,770 | All | Mean temperature; relative humidity | Negative binomial multivariable regression, adjusting for long-term trend and autocorrelation | None | Weekly | Temperate climate | ER | High | 6 | Reported HFMD |
Xu et al. (2019) [10] | Guangdong, China | 2010–2013 | 1,048,574 | 0–5 years | Mean temperature; maximum temperature; minimum temperature; mean relative humidity; mean wind speed; rainfall; sunshine duration; cumulative maximum temperature; cumulative minimum temperature; cumulative mean temperature | DLNM with quasi-Poisson, controlling for long-term trend and autocorrelation | 0–21 days | Daily | Temperate climate | RR | High | 7 | Reported HFMD |
Yang et al. (2015) [41] | Hefei, China | 2010-2012 | 21,634 | 0–14 years | Relative humidity | Poisson linear regression model and DLNM, adjusting for mean temperature, seasonal patterns, and long-term trends, day of week | 0–21 days | Daily | Temperate climate | ER | High | 7 | Reported HFMD |
Zhu et al. (2019) [8] | Xiamen, China | 2013–2017 | 36,464 | All | Mean temperature; relative humidity; sunshine duration | DLNM with quasi-Poisson, adjusting for long-term time trend, DOW, and public holidays | 0–20 days | Daily | Temperate climate | RR | High | 7 | Reported HFMD |
Wang et al. (2019) [27] | Guangdong, China | 2009–2012 | 911,640 | All | Mean temperature; mean relative humidity; mean rainfall | Bayesian spatiotemporal model autocorrelation, adjusting for long-term time trend and autocorrelation | None | Monthly | Temperate climate | RR | High | 7 | Reported HFMD |
Zhu et al. (2020) [42] | Wuxi, China | 2011–2017 | 107,906 | All | Cumulative maximum temperature; cumulative minimum temperature | DLNM, adjusting for time-varying factors and other meteorological factors | 0–16 days | Daily | Temperate climate | RR | High | 7 | Reported HFMD |
Ji et al. (2020) [43] | Tianjin, China | 2014–2018 | 70,027 | 0–15 years | Cumulative mean temperature | DLNM and a susceptible infectious recovery models, adjusting for long-term trends, seasonality, DOW | 0–14 days | Daily | Temperate climate | RR | High | 8 | Reported HFMD |
Guo et al. (2020) [44] | Xi’an, China | 2009–2018 | 31,2018 | All | Maximum temperature; cumulative maximum temperature | DLNM, combined with the GAM, adjusting for long-term trends and seasonality, and week | 0–8 weeks | Weekly | Temperate climate | RR | High | 6 | Reported HFMD |
Subgroup Types | Ambient Temperature | Relative Humidity | ||||
---|---|---|---|---|---|---|
n | I2%, p-Value | Pooled RR (95% CI) | n | I2%, p-Value | Pooled RR (95% CI) | |
Measure | ||||||
Mean | 15 | 99.6%, p = 0.000 | 1.057 (1.030–1.084) | 13 | 95.8%, p = 0.000 | 1.017 (1.011–1.024) |
Maximum | 4 | 94.5%, p = 0.000 | 1.771 (1.355–2.315) | 5 | 94.7%, p = 0.000 | 1.015 (1.005–1.026) |
Minimum | 3 | 93.0%, p = 0.000 | 1.288 (0.896–1.853) | 4 | 95.0%, p = 0.000 | 0.899 (0.782–1.034) |
Time resolution | ||||||
Daily | 8 | 92.8%, p = 0.000 | 1.074 (1.038–1.111) | 15 | 93.7%, p = 0.000 | 1.009 (1.004–1.014) |
Weekly | 12 | 99.7%, p = 0.000 | 1.121 (1.084–1.161) | 5 | 96.4%, p = 0.000 | 1.018 (1.008–1.028) |
Monthly | 1 | 1.045 (1.021–1.069) | 1 | 1.015 (1.006–1.024) | ||
Regional climate | ||||||
Tropical | 4 | 99.6%, p = 0.000 | 1.093 (0.917–1.303) | 3 | 89.8%, p = 0.000 | 1.004 (0.999–1.009) |
Temperate | 15 | 99.6%, p = 0.000 | 1.103 (1.074–1.133) | 18 | 95.1%, p = 0.000 | 1.017 (1.012–1.022) |
HDI * | ||||||
High | 21 | 99.6%, p = 0.000 | 1.114 (1.085–1.144) | 20 | 95.5%, p = 0.000 | 1.016 (1.011–1.022) |
Low | 2 | 49.1%, p = 0.161 | 1.028 (0.994–1.063) | 3 | 89.8%, p = 0.000 | 1.004 (0.999–1.009) |
Gender | ||||||
Male | 5 | 97.2%, p = 0.000 | 1.195 (1.085–1.317) | 5 | 86.3%, p = 0.007 | 1.008 (1.002–1.014) |
Female | 5 | 96.8%, p = 0.000 | 1.196 (1.073–1.334) | 5 | 84.3%, p = 0.007 | 1.006 (1.000–1.012) |
Age | ||||||
0–5 year | 10 | 95.1%. p = 0.000 | 1.101 (1.052–1.152) | 10 | 83.9%, p = 0.000 | 1.010 (1.004–1.016) |
>5 year | 8 | 77.9%, p = 0.000 | 1.037 (0.996–1.080) | 6 | 16.7%, p = 0.306 | 1.002 (0.999–1.006) |
Subgroup Types | Rainfall | Wind Speed | Sunshine Duration | ||||||
---|---|---|---|---|---|---|---|---|---|
n | I2%, p-Value | Pooled RR (95%CI) | n | I2%, p-Value | Pooled RR (95%CI) | n | I2%, p-Value | Pooled RR (95% CI) | |
Measure | |||||||||
Mean | 10 | 97.6%, p = 0.000 | 1.001 (1.000–1.001) | 5 | 95.6%, p = 0.000 | 1.075 (1.023–1.129) | |||
Maximum | 1 | 1.001 (1.000–1.002) | 1 | 1.040 (1.030–1.050) | |||||
Minimum | 1 | 1.010 (1.006–1.014) | |||||||
Time resolution | |||||||||
Daily | 4 | 84.3%, p = 0.000 | 0.999 (0.998–1.001) | 2 | 88.1%, p = 0.004 | 1.001 (0.792–1.265) | 2 | 95.0%, p = 0.000 | 0.984 (0.951–1.018) |
Weekly | 6 | 98.6%, p = 0.000 | 1.001 (1.001–1.002) | 1 | 1.016 (1.006–1.026) | 1 | 1.200 (1.054–1.366) | ||
Monthly | 1 | 1.004 (1.001–1.008) | 1 | 0.990 (0.982–0.998) | 1 | 0.997 (0.985–1.009) | |||
Regional climate | |||||||||
Tropical | 2 | 76.5%, p = 0.039 | 1.003 (0.999–1.007) | ||||||
Temperate | 10 | 97.6%, p = 0.000 | 1.001 (1.000–1.001) | ||||||
HDI * | |||||||||
High | 9 | 97.8%, p = 0.000 | 1.001 (1.000–1.001) | ||||||
Low | 2 | 76.5%, p = 0.039 | 1.003 (0.999–1.007) |
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Liu, Z.; Meng, Y.; Xiang, H.; Lu, Y.; Liu, S. Association of Short-Term Exposure to Meteorological Factors and Risk of Hand, Foot, and Mouth Disease: A Systematic Review and Meta-Analysis. Int. J. Environ. Res. Public Health 2020, 17, 8017. https://doi.org/10.3390/ijerph17218017
Liu Z, Meng Y, Xiang H, Lu Y, Liu S. Association of Short-Term Exposure to Meteorological Factors and Risk of Hand, Foot, and Mouth Disease: A Systematic Review and Meta-Analysis. International Journal of Environmental Research and Public Health. 2020; 17(21):8017. https://doi.org/10.3390/ijerph17218017
Chicago/Turabian StyleLiu, Zhihui, Yongna Meng, Hao Xiang, Yuanan Lu, and Suyang Liu. 2020. "Association of Short-Term Exposure to Meteorological Factors and Risk of Hand, Foot, and Mouth Disease: A Systematic Review and Meta-Analysis" International Journal of Environmental Research and Public Health 17, no. 21: 8017. https://doi.org/10.3390/ijerph17218017