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Overall, age-, gender-, and group-specific mortality rates were calculated.
We then apply the Mann Kendall statistical test (41, 42) to the annualized group-specific mortality data.
We report the results of the Mann Kendall statistic, S, for each annualized group-specific mortality trend line.
If C R functions were available for age group-specific mortality, their application would likely accentuate the importance of age distribution, because older people may be more vulnerable to air pollution.
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Both designs showed that the relationships between temperature and group-specific CHD mortality were non-linear.
Figure 2 shows the non-linear relations between temperature and group-specific CHD mortality using both time series and case-crossover analyses.
The two models gave similar group-specific temperature-mortality relations.
We used a time series regression to examine the group-specific temperature-mortality relationship.
As an alternative, time-stratified case-crossover model was used to examine the group-specific temperature-mortality relationship.
We took the following approach to estimating these probabilities: Age-group, sex-specific mortality probabilities for all causes and for AMI (ICD 10 codes I20 I25), stroke (I60 I69), lung cancer (C33, C34) and COPD (J41 J44), for 2001 for the Australian population were sourced from the AIHW GRIM books [ 13].
Similar patterns are apparent in other studies providing age (but often using different age-groups) and sex specific mortality.
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