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Table 1 Socio-demographic and health-related characteristics of women in the 194651 ALSWH1cohort at survey 1 in 1996 (N=12,709)

From: The impact of socioeconomic status on changes in the general and mental health of women over time: evidence from a longitudinal study of Australian women

 

Low SES (n=4,943) %

Mid SES (n=4,531) %

High SES (n=3,235) %

Total (n=12,709) %

Area of residence

    

Capital city/Other metropolitan centers

69.1

71.8

78.0

72.6

Large/Small rural centers or remote

30.9

28.2

22.0

27.4

Marital status

    

Married/De-facto

83.4

81.2

78.2

81.1

Separated/Divorced/Widowed/Single

16.6

18.9

21.8

18.9

Smoker

    

Non-smoker

51.4

51.3

58.5

53.4

Ex-smoker

26.9

30.8

29.6

29.0

Smoker

21.7

17.8

11.9

17.6

Body Mass Index (BMI)

    

Normal weight (18.5-24.9 kg/m2)

49.3

52.9

59.7

53.6

Underweight (< 18.5 kg/m2)

 1.5

 1.8

 2.6

 1.9

Overweight (25.0-30.0 kg/m2)

28.8

28.0

25.8

27.6

Obese (Obese (>30.0 kg/m2)

20.5

17.3

11.9

16.9

Ability to manage on income

    

Easy

12.6

14.6

22.8

16.2

Not too bad

40.6

43.6

43.3

42.4

Difficult sometimes

30.2

27.5

23.6

27.4

Impossible or difficult always

16.7

14.3

10.4

14.1

Age first left school

    

16 years or younger

56.7

36.0

 7.3

67.1

17 years or older

 2.6

34.9

62.7

32.9

Highest qualification attained

    

No formal qualification

88.1

11.9

 0.0

17.2

School certificate

70.3

29.7

 0.0

31.6

Higher school certificate

 8.8

79.0

12.1

16.9

Trade, apprenticeship, certificate or diploma

 0.0

52.0

48.0

19.8

Higher degree or bachelor degree

 0.0

 4.0

96.0

14.5

Main occupation (current or last)

    

Never had a paid job

92.7

 7.3

 0.0

 1.6

Machine operator, cleaner

87.0

13.1

 0.0

15.3

Advanced/Intermediate sales, clerk, personal service worker

57.0

41.5

 1.5

40.4

Associate professional or trades-person

 8.0

57.2

34.9

13.1

Manager/Administrator/Professional

 0.0

31.5

68.6

29.6

Total

38.9

35.6

25.5

100.00

  1. 1 Australian Longitudinal Study on Women’s Health.
  2. Data are weighted to adjust for oversampling in rural and remote areas.
  3. Percentages vary due to rounding.