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Table 4 Modification by individual characteristics of temperature effects using the case-only approach

From: Daily temperature and mortality: a study of distributed lag non-linear effect and effect modification in Guangzhou

 

Factors

Hot effect modification

Cold effect modification

 

OR(95%CI)

OR(95%CI)

Sex

Male(Reference group)

_

_

 

Female

1.192(1.134 to 1.253)

0.951(0.838 to 1.064))

Age

0-64 years(Reference group)

_

_

 

65-74 years

1.083(1.006 to 1.161)

1.075(0.891 to 1.259)

 

75-84 years

1.103(1.008 to 1.198)

1.069(0.857 to 1.319)

 

85 years or above

1.195(1.099 to 1.298)

1.187(1.068 to 1.306)

Education

None (reference group)

_

_

 

Primary education

0.933(0.867 to 1.005)

0.903(0.757 to 1.049)

 

Secondary or higher education

0.862(0.797 to 0.931)

0.849(0.702 to 0.996)

Occupation

White collar (reference group)

_

_

 

Blue collar workers

1.095(1.027 to 1.163)

1.104(1.043 to1.166)

 

Unemployed

1.080 (0.912 to 1.246)

0.953(0.748 to 1.158)

  1. Odds ratio (OR) larger than 1 indicates positive effect modification, that is, the increased risk of mortality associated with hot or cold temperatures was larger for persons who had this characteristic compared to the reference group.