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Table 1 Regression coefficients used to predict the prevalence of overweight/obesity from mean BMI

From: National, regional, and global trends in adult overweight and obesity prevalences

Predictor BMI ≥ 25 kg/m2 (n=1883)b BMI ≥ 30 kg/m2 (n=1857)b
Constant -24.9 (-27.0, -22.8) -33.9 (-36.9, -31.0)
Cube of first spline segment (knot at BMI of 21.3) -.0000423 (-.000118, .0000334) -.0000632 (-.0002191, .0000927)
Cube of second spline segment (knot at BMI of 25.1) -.00522 (-.00680, -.00365) -.00619 (-.00947, -.00291)
Cube of third spline segment (knot at BMI of 28.9) -.00490 (-.00735, -.00245) -.00437 (-.00611, -.00263)
Cube of last spline segment .00168 (.00038, .00298) .00316 (.00222, .00410)
Square of mean BMI -.0182 (-.0220, -.0144) -.0280 (-.0327, -.0233)
Mean BMI 1.46 (1.27, 1.65) 1.98 (1.71, 2.25)
High-income country .0077 (-.0287, .0442) -.113 (-.181, -.0456)
Age (midpoint of age category) .00567 (.00499, .00635) .00456 (.00335, .00577)
Year of survey a .00934 (.00492, .0138) .0236 (.0157, .0314)
Female sex .91 (.62, 1.19) 1.01 (.575, 1.45)
Sex * mean BMI -.0405 (-.0517, -.0292) -.0294 (-.0455, -.0133)
County income category * year of survey a -.0120 (-.0194, -.0047) -.00128 (-.0132, .0106)
R2 0.97 0.92
  1. * denotes statistical interaction.
  2. a See methods for further details on how year of survey was used.
  3. b 1884 age-sex groups provided mean and prevalence data with sufficient sample size, but those with prevalence zero were not used in the above regression because the logit(0) is not defined.