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Table 5 Logistical regression analysis of the variables associated with excessive gestational weight gain in 95 Swedish women

From: Food intake and gestational weight gain in Swedish women

 

Univariable

Adjusteda

Adjustedb

OR

CI lower

CI higher

OR

CI lower

CI higher

OR

CI lower

CI higher

Dairy (g/day)

1.000

0.997

1.002

1.001

0.998

1.005

1.002

0.999

1.006

Bread (g/day)

1.006

0.997

1.016

1.012

0.999

1.024

1.016

1.002

1.031

Fruit, berries and vegetables (g/day)

0.998

0.995

1.001

1.000

0.996

1.004

1.001

0.997

1.006

Red meat (g/day)

0.995

0.983

1.007

0.992

0.977

1.007

0.995

0.980

1.011

Fish (g/day)

1.005

0.992

1.018

1.018

0.999

1.038

1.023

1.002

1.044

Snacks (g/day)

1.010

1.002

1.019

1.012

1.000

1.023

1.018

1.004

1.032

Caloric beverages (g/day)

1.002

1.000

1.004

1.002

1.000

1.005

1.004

1.001

1.007

Margarine and butter (g/day)

1.015

0.967

1.065

0.959

0.894

1.030

0.968

0.896

1.045

Cheese (g/day)

1.003

0.989

1.017

0.999

0.981

1.017

1.010

0.988

1.032

Rice, pasta, grains (g/day)

0.999

0.992

1.007

0.999

0.990

1.009

1.002

0.992

1.012

Physical activity levelc

0.026

0.002

0.436

0.016

0.000

0.611

0.007

0.000

0.381

  1. aAdjusted for gestational week at weighing and pre-pregnancy body mass index (BMI)
  2. bAdjusted for gestational week at weighing, pre-pregnancy BMI and food intake level (FIL). FIL was calculated as energy intake divided by basal metabolic rate (BMR). BMR was calculated based on pre-pregnancy weight × 1.2 to account for pregnancy (Henry 2005)
  3. cIn the third trimester of pregnancy, estimated on a 10 graded scale (Bexelius et al. 2010)