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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]
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BMC Public Health

ISSN: 1471-2458

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