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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.