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Table 4 Relationship between movement patterns and CVD risk

From: Association between movement behavior patterns and cardiovascular risk among Chinese adults aged 40–75: a sex-specific latent class analysis

 

Model 1

Model 2

Model 3

Intermediate-risk

High-risk

Intermediate-risk

High-risk

Intermediate-risk

High-risk

Male latent class

     

Class 1

Ref

Ref

Ref

Class 2

   

OR (95%CI)

1.507 (1.359, 1.671)

2.194 (1.868, 2.576)

1.765 (1.587, 1.962)

2.782 (2.36, 3.28)

1.203 (1.066, 1.357)

1.462 (1.212, 1.764)

P-value

< 0.001

< 0.001

< 0.001

< 0.001

< 0.05

< 0.001

Class 3

      

OR (95%CI)

1.379 (1.220, 1.558)

2.026 (1.688, 2.431)

1.585 (1.398, 1.797)

2.438 (2.021, 2.940)

1.225 (1.060, 1.415)

1.504 (1.211, 1.868)

P-value

< 0.001

< 0.001

< 0.001

< 0.001

< 0.05

< 0.001

Female latent class

     

Class 1

Ref

Ref

Ref

Class 2

      

OR (95%CI)

1.085 (0.919, 1.279)

1.541 (1.144, 2.075)

1.29 (1.09, 1.527)

1.942 (1.437, 2.624)

0.941 (0.768, 1.152)

1.045 (0.734, 1.488)

P-value

0.336

< 0.05

< 0.05

< 0.001

0.555

0.806

Class 3

      

OR (95%CI)

1.181 (0.972, 1.435)

1.844 (1.322, 2.573)

1.472 (1.206, 1.796)

2.507 (1.787, 3.516)

0.954 (0.748, 1.218)

1.151 (0.768, 1.726)

P-value

0.093

< 0.001

< 0.001

< 0.001

0.705

0.496

Class 4

      

OR (95%CI)

1.127 (0.954, 1.332)

1.375 (1.017, 1.858)

1.226 (1.035, 1.452)

1.531 (1.129, 2.077)

0.983 (0.803, 1.205)

1.024 (0.717, 1.461)

P-value

0.159

< 0.05

< 0.05

< 0.05

0.872

0.898

  1. China-PAR predicted the 10-year ASCVD risk across different movement patterns. Multinomial logistic regression was analyzed for the association between movement patterns and CVDs in male and female participants. Model 1 was unadjusted. Model 2 was adjusted for education, drinking, and tea consumption frequency. Model 3 was adjusted for education, drinking, tea consumption frequency and age