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The new multilevel logistic regression research has also been conducted since an allergy analysis, and Logit(p
where ?00k is the random intercept, ?0tk is the regression coefficient for Xjk (each individual-level variable), and u0jk is the random effect for participant j in household k. ?10k-?12k are coefficients to predict ?1jk (the regression coefficient for TempInto the ijk).
where ? is the fixed effect, Zk stands for each household-level variable and ?00k is the random effect for household k.
ijk) was used as an objective variable instead of HBPijk in the above equation. pijk is the probability of observed BP measurement increasing to ?135 mm Hg (diagnostic threshold for hypertension or normotension) for participant j in household k on day i.
Day-level variables were centered around each participants’ mean, while household-level and individual-level variables were centered around the overall mean. Regression coefficients were estimated using the maximum likelihood method. List-wise deletion was used for missing values, after confirming that the results on indoor temperature from list-wise deletion were almost the same as the results from multiple imputation (Table S3). All P values were 2 sided, and a 2-sided P value <0.05 was considered statistically significant. All analyses were performed using SPSS Version 24 (SPSS Inc, Chicago, IL).
Data Profile regarding set up a baseline Questionnaire in the Cold temperatures
Figure 1 shows the flow for the selection of valid samples in the winter survey. A total of 2095 households and 3775 participants throughout Japan responded to the survey (the average age was 57 years, the ratio of men was 47%, and the average body mass index was 22.8 kg/m 2 ).
