Relationship between temperature variability and daily hospitalisations in Hong Kong over two decades

Figures

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  Figure 1. Percentage change (%) in cause-specific hospitalizations per interquartile increase in temperature variability (°C) in exposure days from 0-1 to 0-7 days in Hong Kong. Red stars highlighted the changes in hospitalisations significant at 95% confidence level.

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  Figure 2. Percentage change (%) in all-cause and cause-specific hospitalisations per interquartile increase in temperature variability (°C) in exposure days from 0-1 to 0-7 days by age groups in Hong Kong. The points in different shapes draw the estimates with 95% CI of the associations among people aged 0-18 years (in shape square), 19-49 years (in shape circle), 50-64 years (in shape triangle), 65-79 years (in shape diamond), ≥80 years (in shape triangle down).

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  Figure 3. Percentage change (%) in all-cause and cause-specific hospitalizations per interquartile increase in temperature variability (°C) in exposure days from 0-1 to 0-7 days by seasons in Hong Kong. The points in different shapes draw the estimates with 95% CI of the associations in cold seasons (in shape circle), moderate seasons (in shape diamond), hot seasons (in shape triangle)

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  Figure 4. Sensitivity analyses for effect estimates of temperature variability (°C) in exposure days from 0-1 to 0-7 days on all-cause hospitalisations in Hong Kong. Panel A. Models with the maximum lag of daily mean temperature at 14-28 days (21 days in primary model). Panel B. Models with the degree of freedom (df) of daily mean temperature ranged 2-7 (four in primary model). Panel C. Models adjusted for cold spells and extreme heat.