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NL888 Posted 13 years ago
Grammar
What does "first percentile of temperature" and "over lags" mean?
Context:
Both low and high temperature may increase the risk of stroke mortality
Objective: To examine temperature in relation to stroke mortality in a multicity time series study in China.
Methods: We obtained data on daily temperature and mortality from 8 large cities in China. We used quasi-Poisson generalized additive models and distributed lag nonlinear models to estimate the accumulative effects of temperature on stroke mortality across multiple days, adjusting for long-term and seasonal trends, day of the week, air pollution, and relative humidity. We applied the Bayesian hierarchical model to pool city-specific effect estimates.
Results: Both cold and hot temperatures were associated with increased risk of stroke mortality. The potential effect of cold temperature might last more than 2 weeks. The pooled relative risks of extreme cold (first percentile of temperature) and cold (10th percentile of temperature) temperatures over lags0–14 days were 1.39 (95% posterior intervals
1.18–1.64) and 1.11 (95% PI 1.06–1.17), compared with the 25th percentile of temperature. In contrast, the effect of hot temperature was more immediate. The relative risks of stroke mortality over lags 0–3 days were 1.06 (95% PI 1.02–1.10) for extreme hot temperature (99th percentile of temperature) and 1.14 (95% PI 1.05–1.24) for hot temperature (90th percentile of temperature), compared with the 75th percentile of temperature.
Conclusions: This study showed that both cold and hot temperatures were associated with increased risk of stroke mortality in China. Our findings may have important implications for stroke prevention in China.
Both low and high temperature may increase the risk of stroke mortality
Objective: To examine temperature in relation to stroke mortality in a multicity time series study in China.
Methods: We obtained data on daily temperature and mortality from 8 large cities in China. We used quasi-Poisson generalized additive models and distributed lag nonlinear models to estimate the accumulative effects of temperature on stroke mortality across multiple days, adjusting for long-term and seasonal trends, day of the week, air pollution, and relative humidity. We applied the Bayesian hierarchical model to pool city-specific effect estimates.
Results: Both cold and hot temperatures were associated with increased risk of stroke mortality. The potential effect of cold temperature might last more than 2 weeks. The pooled relative risks of extreme cold (first percentile of temperature) and cold (10th percentile of temperature) temperatures over lags0–14 days were 1.39 (95% posterior intervals
1.18–1.64) and 1.11 (95% PI 1.06–1.17), compared with the 25th percentile of temperature. In contrast, the effect of hot temperature was more immediate. The relative risks of stroke mortality over lags 0–3 days were 1.06 (95% PI 1.02–1.10) for extreme hot temperature (99th percentile of temperature) and 1.14 (95% PI 1.05–1.24) for hot temperature (90th percentile of temperature), compared with the 75th percentile of temperature.Conclusions: This study showed that both cold and hot temperatures were associated with increased risk of stroke mortality in China. Our findings may have important implications for stroke prevention in China.
Top answer
This is my interpretation: First percentile: the 1% of the cases that are in the extreme low of the temperature range. Suppose you have 10,000 cases that are in the study. Then each 1% percentile contains 100 of these cases.
- This is my interpretation: First percentile: the 1% of the cases that are in the extreme low of the temperature range.
- Suppose you have 10,000 cases that are in the study.
- Then each 1% percentile contains 100 of these cases.
- The first percentile are the 100 cases which are at the very lowest temperatures.
- The percentiles are in order of temperature range, so the range has a low cut-off and a high cut-off.
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1 Answers
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This is my interpretation:
First percentile: the 1% of the cases that are in the extreme low of the temperature range.
Suppose you have 10,000 cases that are in the study. Then each 1% percentile contains 100 of these cases. The first percentile are the 100 cases which are at the very lowest temperatures. The percentiles are in order of temperature range, so the range has a low
First percentile: the 1% of the cases that are in the extreme low of the temperature range.
Suppose you have 10,000 cases that are in the study. Then each 1% percentile contains 100 of these cases. The first percentile are the 100 cases which are at the very lowest temperatures. The percentiles are in order of temperature range, so the range has a low
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