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Table 2 Participant characteristics by tertile of dietary GHG emission (median (IQR))

From: Reducing GHG emissions while improving diet quality: exploring the potential of reduced meat, cheese and alcoholic and soft drinks consumption at specific moments during the day

  Men Women
Low
(n = 352)
Intermediate
(n = 352)
High
(n = 351)
Low
(n = 348)
Intermediate
(n = 350)
High
(n = 349)
Tertile cut-off points
 GHG emission (kg CO2-eq/d)a ≤3.9 3.9-5.1 ≥ 5.1 ≤3.0 3.0–4.0 ≥ 4.0
Characteristics
 Age (years) 40 (28–56) 39 (28–55) 42 (29–56) 38 (27–54) 39 (28–54) 44 (30–58)
 Low educational level (%)b 29 27 36 40 35 36
Net household income
  < 1700 euro/month (%) 29 27 28 38 37 32
 1700–2900 euro/month (%) 51 50 48 42 45 50
  > 2900 euro/month (%) 20 23 25 20 18 19
 Dutch ethnicity (%) 96 97 98 93 96 97
BMIc
 Overweight (%) 41 35 44 25 30 33
 Obesity (%) 15 16 10 22 22 21
MET score (hours/week) 142 (88–197) 160 (111–223) 167 (112–229) 146 (94–210) 154 (101–211) 157 (117–226)
BMR (kJ/h/kg body mass)d 7.7 (7.2–8.3) 7.7 (7.3–8.3) 7.7 (7.3–8.1) 6.0 (5.6–6.5) 6.1 (5.8–6.6) 6.0 (5.7–6.6)
  1. BMR basal metabolic rate, CO 2 -eq carbon dioxide equivalent, GHG greenhouse gas, MET metabolic equivalent
  2. aAverage GHG emission for a day’s consumption based on two 24-h recalls used to define low (≤ P33), intermediate (> P33 and ≤ P66) and high (> P66) dietary GHG emission
  3. bLow education was defined as primary education/lower vocational education/low or intermediate secondary education
  4. cOverweight was defined as a BMI ≥25 and < 30; and obesity as a BMI ≥30 [19]
  5. dBMR calculated from standard equations based on weight, age and sex [20]