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Table 8 Prevalence of obesity* by age, sex, rural/urban area and income quintiles among persons aged 50 years and older across six countries

From: Common risk factors for chronic non-communicable diseases among older adults in China, Ghana, Mexico, India, Russia and South Africa: the study on global AGEing and adult health (SAGE) wave 1

 

China

Ghana

India

Mexico

Russian Federation

South Africa

%

95% CI

%

95% CI

%

95% CI

%

95% CI

%

95% CI

%

95% CI

Man

            

50-59

11.8

[10.1,13.7]

7.1

[5.4,9.3]

5.3

[3.5,8.0]

22.8

[12.8,37.4]

34.4

[21.2,50.6]

36.5

[30.8,42.5]

60-69

12.6

[10.6,14.9]

6.5

[4.6,9.1]

2.8

[1.6,5.1]

23.4

[16.8,31.4]

18.5

[9.6,32.8]

43.2

[35.0,51.7]

70-79

10.6

[8.3,13.5]

4.8

[2.8,8.3]

3.3

[1.9,5.7]

17.3

[11.2,25.7]

33.2

[20.1,49.7]

37.4

[27.3,48.7]

80+

9.9

[6.4,15.1]

5.5

[2.3,12.7]

4.0

[1.1,13.8]

16.7

[7.9,31.8]

7.7

[2.6,20.7]

30.7

[18.3,46.7]

Woman

            

50-59

19.7

[17.8,21.6]

19.5

[15.6,24.1]

10.3

[8.4,12.4]

40.4

[23.9,59.4]

46.6

[40.0,53.4]

53.2

[48.2,58.3]

60-69

19.5

[17.1,22.2]

12.3

[9.8,15.5]

8.1

[5.9,10.9]

36

[27.2,45.8]

44.0

[34.7,53.8]

55.2

[49.0,61.3]

70-79

18.2

[15.0,21.9]

8.2

[5.8,11.4]

6.0

[3.2,11.2]

23.9

[15.3,35.3]

34.1

[24.82,44.9]

40.0

[31.4,49.4]

80+

10.5

[6.8,15.8]

6.4

[3.3,12.1]

3.5

[1.7,7.0]

19.6

[12.0,30.3]

28.9

[18.3,42.5]

33.5

[23.0,46.0]

Residence

            

urban

17.4

[15.7,19.3]

17.6

[14.8,20.9]

12.1

[9.3,15.6]

30.5

[23.3,38.9]

35.9

[30.3,42.0]

47.2

[42.8,51.7]

rural

13.7

[11.8,15.9]

4.3

[3.4,5.4]

4.1

[3.4,4.9]

21.8

[15.8,29.3]

36

[25.9,47.5]

41.2

[35.1,47.6]

Income quintile **

           

Lowest

9.0

[6.8,11.9]

2.7

[1.6,4.3]

1.4

[0.8,2.4]

21.0

[14.6,29.1]

31.7

[23.9,40.8]

36.1

[28.1,44.9]

Second

12.8

[11.0,14.8]

4.0

[2.7,6.0]

4.9

[1.4,15.9]

27.9

[14.8,46.1]

31.8

[22.8,42.3]

40.5

[34.6,46.7]

Middle

16.3

[14.9,17.9]

7.0

[5.3,9.3]

4.0

[2.6,6.0]

28.8

[15.9,46.4]

29.7

[22.4,38.3]

48.6

[42.3,55.0]

Fourth

18.1

[16.5,19.8]

10.7

[8.6,13.3]

4.6

[3.4,6.4]

34.3

[24.4,45.7]

43.3

[32.0,55.3]

55.6

[49.3,61.8]

Highest

18.4

[16.4,20.6]

22.3

[18.4,26.9]

14.5

[11.7,17.9]

30.1

[19.8,42.9]

38.8

[29.1,49.6]

46.2

[38.9,53.7]

Total

15.3

[13.9,16.8]

9.7

[8.4,11.2]

6.4

[5.2,7.7]

28.6

[22.8,35.3]

36.0

[30.9,41.3]

45.2

[41.6,48.9]

  1. * BMI ≥30 kg/m2 or BMI >27.5 kg/m2 in China and India.
  2. ** Income levels were generated through a multi-step process, where asset ownership was converted to an asset ladder, a Bayesian post-estimation method used to generate raw continuous income estimates, and then transformed into quintiles. Lowest (Quintile 1) is the quintile with the poorest households and Highest (Quintile 5) the quintile with the richest households.
  3. Note: Weighted estimates.