Journal of Community Medicine & Public Health

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Self-Reported Nutrition and Physical Activity Program Utilisation among Australians with Psychosis: A Cross-Sectional Analysis of Data

Doreen Mucheru1*, Mary-Claire Hanlon1,2, Linda E. Campbell2,3, Mark McEvoy1,4, Lesley MacDonald-Wicks1,5

1Faculty Health and Medicine, The University of Newcastle, Australia

2Brain and Mental Health Program, Hunter Medical Research Institute, Australia

3Faculty of Science, The University of Newcastle, Australia

4Centre for Clinical Epidemiology & Biostatistics, Hunter Medical Research Institute, Australia

5Priority Research Centre for Physical Activity and Nutrition, The University of Newcastle, Australia

*Corresponding author: Doreen Mucheru, Faculty of Health and Medicine, The University of Newcastle, Callaghan NSW 2308, Australia. Tel: +61-249854928; Email: Doreen.Mucheru@uon.edu.au

Received Date: 06 June, 2019; Accepted Date: 21 June, 2019; Published Date: 27 June, 2019

Citation: Mucheru D, Hanlon MC, Campbell LE, McEvoy M, MacDonald-Wicks L (2019) Self-Reported Nutrition and Physical Activity Program Utilisation among Australians with Psychosis: A Cross-Sectional Analysis of Data. J Community Med Public Health 3: 155. DOI: 10.29011/2577-2228.100055

Abstract

Objective: To describe the self-reported attendance of community nutrition and physical activity programs in the government and non-government sector among 1825 people from the Survey of High Impact Psychosis (SHIP), and identify demographics associated with overall self-reported program attendance. Additionally, to assess whether improved nutrition and physical activity outcomes were associated with program attendance.

Methods: In this cross-sectional analysis of data from SHIP, descriptive statistics were generated and tests-of-association applied between program attendance, and demographics, nutrition and physical activity outcomes.

Results: Just 11.6% attended a nutrition or physical activity program. Overall attendance was associated with highest education qualifications attained (p=0.004) and diagnosed disorder (p=0.022). Non-government sector attendees were more likely to consume reduced fat milk (p=0.010), and less likely to run out of food (p=0.007).

Conclusions: There is extremely low utilisation of community nutrition and physical activity programs in Australians with psychosis which is associated with certain demographics that may act as barriers. Program attendance did not show consistent association with improved nutrition or physical activity outcomes.

Implications for public health: Nutrition and physical activity program utilisation should be encouraged in people with psychosis by addressing problems related to access. These programs should be evaluated locally to ensure usefulness.

Keywords: Community programs; Nutrition; Physical activity; Psychosis



 

 

Total Sample

N = 1825

(N %) or

M (SD)

Attended Nutrition and Physical Activity Program in any Sector

n = 212

(n %) or

M (SD)

Did not Attend Nutrition and Physical Activity Program any Sector

n = 509

(n %) or

M (SD)

Test

Sex

Male

1087

(59.6%)

129

(60.8%)

298

(58.5%)

X2= 0.329, df= 1, p = 0.566

Female

738

(40.4%)

83

(39.2%)

211

(41.5%)

Age

 

38.4

(11.2)

40.0 

(11.2)

38.6

(11.1)

t=-1.590, df=719, p=0.693

Aboriginal/ Torres Strait Islander descent

No

1735

(95.1%)

202

(95.3%)

479

(94.1%)

X2= 0.396, df= 1, p = 0.529

Yes

90

(4.9%)

10

(4.7%)

30

(5.9%)

Marital status

Single/ Never Married

1117

(61.2%)

137

(64.6%)

341

(67.0%)

X2= 2.527, df= 3, p = 0.470

Married/ De facto

312

(17.1%)

22

(10.4%)

57

(11.2%)

Separated/ Divorced

376

(20.6%)

46

(21.7%)

103

(20.2%)

Widowed

20

(1.1%)

7

(3.3%)

8

(1.6%)

Highest education qualification attained

Left school with no qualifications

615

(33.7%)

54

(25.5%)

208

(40.9%)

X2=17.394, df= 5, **p = 0.004

Secondary school qualifications

304

(16.7%)

46

(21.7%)

78

(15.3%)

Tertiary Qualifications

739

(40.5%)

94

(44.3%)

178

(35.0%)

Bachelor degree

92

(5.0 %)

10

(4.7%)

22

(4.3%)

Postgraduate qualifications

28

(1.5%)

3

(1.4%)

9

(1.8%)

Other

32

(1.8%)

3

(1.4%)

11

(2.2%)

Not known

15

(0.8%)

2

(0.9%)

2

(0.4%)

Current net fortnightly income

Less than $300 per fortnight

58

(3.2%)

8

(3.8%)

10

(2.0%)

X2= 2.618, df= 4, p = 0.624

Between $300 - $499 per fortnight

209

(11.5%)

16

(7.5%)

47

(9.2%)

Between $500 - $799 per fortnight

1080

(59.2%)

139

(65.6%)

321

(63.1%)

Between $800 - $1000 per fortnight

232

(12.7%)

29

(13.7%)

71

(13.9%)

More than $1000 per fortnight

139

(7.6%)

9

(4.2%)

18

(3.5%)

Not known

107

(5.9%)

11

(5.2%)

42

(8.3%)

Participation in paid employment

Employed in any job in last 12 months

596

(32.7%)

46

(21.7%)

134

(26.3%)

X2= 1.860, df= 2, p = 0.395

Home duties/ caring/ retired/ volunteer/ unpaid/ student

258

(14.1%)

30

(14.2%)

73

(14.3%)

No formal activity (includes unemployed)

971

(53.2%)

136

(64.2%)

302

(59.3%)

DIP ICD-10 diagnosis

Schizophrenia

857

(47.0%)

111

(52.4%)

236

(46.4%)

X2=14.824, df= 6, *p = 0.022

Schizoaffective

293

(16.1%)

33

(15.6%)

74

(14.5%)

Bipolar, mania

319

(17.5%)

31

(14.6%)

76

(14.9%)

Depressive psychosis

81

(4.4%)

5

(2.4%)

26

(5.1%)

Delusional disorders and other non-organic psychosis

92

(5.0%)

17

(8.0%)

23

(4.5%)

Severe depression disorder

158

(8.7%)

14

(6.6%)

60

(11.8%)

Screen-positive for psychosis but did not meet full criteria for ICD-10 psychosis

25

(1.4%)

1

(0.5%)

14

(2.8%)

Participation in any community rehabilitation or day therapy program (last 12 months)

No

1133

(62.1%)

1

(0.5%)

58

(11.4%)

NA

Yes

666

(36.5%)

211

(99.5%)

447

(87.8%)

Not known

26

(1.4%)

-

4

(0.8%)

Location of community rehabilitation or day therapy program (last 12 months)

Public

 hospital

No

605

(33.2%)

189

(89.2%)

408

(80.2%)

NA

Yes

60

(3.3%)

21

(9.9%)

39

(7.7%)

Not known

27

(1.5%)

1

(0.5%)

4

(0.8%)

Not applicable

1133

(62.1%)

1

(0.5%)

58

(11.4%)

Private hospital

No

659

(36.1%)

210 (99.1%)

441

(86.6%)

NA

Yes

6

(0.3%)

-

6

(1.2%)

Not known

27

(1.5%)

1

(0.5%)

4

(0.8%)

Not applicable

1133

(62.1%)

1

(0.5%)

58

(11.4%)

Government funded community-based centre

No

460

(25.2%)

152

(71.7%)

301

(59.1%)

NA

Yes

205

(11.2%)

58

(27.4%)

146

(28.7%)

Not known

27

(1.5%)

1

(0.5%)

4

(0.8%)

Not applicable

1133

(62.1%)

1

(0.5%)

58

(11.4%)

Non-government funded community-based centre

No

203

(11.1%)

67

(31.6%)

135 (26.5%)

NA

Yes

464

(25.4%)

143

(67.5%)

314

(61.7%)

Not known

25

(1.4%)

1

(0.5%)

2

(0.4%)

Not applicable

1133

(62.1%)

1

(0.5%)

58

(11.4%)

Participation in Nutrition and Physical Activity Program

Government sector and hospitals

No

170

(9.3%)

-

-

NA

Yes

97

(5.3%)

-

-

Not known

23

(1.3%)

-

-

Not applicable

1535

(84.1%)

-

-

Non-government sector

No

379

(20.8%)

-

-

NA

Yes

159

(8.7%)

-

-

Not known

29

(1.6%)

-

-

Not applicable

1258

(68.9%)

-

-


M (SD)–mean (standard deviation); ICD–International Statistical Classification of Diseases and Related Health Problems; X2–Chi Square test; t–independent sample T test; * p < 0.05; **p < 0.01; ***p< 0.001; NA–Not applicable.


Table 1: Demographic Characteristics of Participants from the Survey of High Impact Psychosis by Attendance at a Nutrition and Physical Activity Program.

 

 

Total

Sample

N = 1825

(N %) or

M (SD)

Nutrition and Physical Activity Program Attendance in the Government Sector and Hospitals

Nutrition and Physical Activity Program Attendance in the Non-Government Sector

Tests of Association with Nutrition and Physical Activity Program Participation in the Government Sector and Hospitals

Tests of Association with Nutrition and Physical Activity Program Participation in the Non-Government Sector

No

n=170

Yes

n=97

No

n=379

Yes

N=159

Meal events per day (last 4 weeks)

0-2 meal events

548 (30.0%)

48 (28.2%)

20 (20.6%)

112 (29.6%)

36 (22.6%)

X2= 2.120, df= 2, p = 0.347

X2= 2.781, df = 2, p = 0.249

3-4 meal events

826 (45.3%)

80 (47.1%)

52 (53.6%)

157 (41.4%)

71 (44.7%)

³ 5 meal events

437 (23.9%)

39 (22.9%)

25 (25.8%)

107 (28.2%)

51 (32.1%)

Not known

 

14

(0.8%)

3

(1.8%)

-

3

(0.8%)

1

(0.6%)

Eats breakfast (days per week in last 4 weeks)

0-3 days per week

877 (48.1%)

72 (42.4%)

40

(41.2%)

180 (47.5%)

66 (41.5%)

X2= 0.088, d f= 1, p = 0.766

X2= 1.683, df = 1, p = 0.195

³ 4 days per week

939 (51.5%)

95

(55.9%)

57 (58.8%)

198 (52.2%)

93 (58.5%)

Not known

9

(0.5%)

3

(1.8%)

-

1

(0.3%)

-

Milk consumed (serves per day in last 4 weeks)

Does not drink milk

98 (5.4%)

6

(3.5%)

4

(4.1%)

21 (5.5%)

7

(4.4%)

X2= 0.629, df= 3, p = 0.890

X2= 11.366, df = 3, *p = 0.010

Full cream milk

1018 (55.8%)

82 (48.2%)

43 (44.3%)

228 (60.2%)

76 (47.8%)

Low or reduced fat or skim milk

575 (31.5%)

70 (41.2%)

45 (46.4%)

93 (24.5%)

62 (39.0%)

Soy or evaporated or sweetened condensed or other type of milk

114 (6.2%)

9

(5.3%)

5

(5.2%)

30 (7.9%)

13 (8.2%)

Not known

20

(1.1%)

3

(1.8%)

-

7

(1.8%)

1

(0.6%)

Vegetables consumed (serves per day in last 4 weeks)

0-1 serves

887 (48.6%)

78 (45.9%)

46 (47.4%)

189 (49.9%)

74 (46.5%)

X2= 0 .088, df= 2, p = 0.957

X2= 0.601, df = 2, p = 0.741

2-3 serves

715 (39.2%)

68 (40.0%)

40 (41.2%)

142 (37.5%)

65 (40.9%)

4-6 serves

206 (11.3%)

21 (12.4%)

11 (11.3%)

44 (11.6%)

19 (11.9%)

Not known

17

(0.9%)

3

(1.8%)

-

4

(1.1%)

1

(0.6%)

Fruit consumed (serves per day in last 4 weeks)

0-1 serves

1297 (71.1%)

99 (58.2%)

63 (64.9%)

265 (69.9%)

102 (64.2%)

X2= 0.831, df= 2, p = 0.660

X2= 1.952, df = 2, p = 0.377

2-3 serves

452 (24.8%)

62 (36.5%)

31 (32.0%)

97 (25.6%)

49 (30.8%)

4-6 serves

59 (3.2%)

6

(3.5%)

3

(3.1%)

13 (3.4%)

7

(4.4%)

Not known

17

(0.9%)

3

(1.8%)

-

4

(1.1%)

1

(0.6%)

Salt added to food (last 4 weeks)

Never

650 (35.6%)

62 (36.5%)

28 (28.9%)

152 (40.1%)

57 (35.8%)

X2= 3.090, df= 3, p = 0.378

X2= 4.013, df = 3, p = 0.260

Rarely

252 (13.8%)

33 (19.4%)

19 (19.6%)

47 (12.4%)

26 (16.4%)

Sometimes

348 (19.1%)

27 (15.9%)

23 (23.7%)

71 (18.7%)

38 (23.9%)

Usually

560 (30.7%)

45 (26.9%)

27 (27.8%)

104 (27.4%)

37 (23.3%)

Not known

15

(0.8%)

3

(1.8%)

-

5

(1.3%)

1

(0.6%)

Ran out of food (last 12 months)

No

1296 (71.0%)

114 (67.1%)

75 (77.3%)

258 (68.1%)

127 (79.9%)

X2= 2.474, df = 1, p = 0.116

X2= 7.232, df= 1, **p= 0.007

Yes

519 (28.4%)

53 (31.2%)

22 (22.7%)

119 (31.4%)

32 (20.1%)

Not known

10

(0.5%)

3

(1.8%)

-

2

(0.5%)

-

Physical activity (min/week)

Walking

214.8 (334.7)

211.3

(342.5)

167.3

(174.9)

227.1

(376.3)

220.5

(279.9)

Mean rank for No=135.55 & Yes=131.28

U= 7981, Z= -0.436

p= 0.663

Mean rank for No=264.42 & Yes=281.62

U= 28204, Z= -1.174

p= 0.240

Moderate activity

76

(241.0)

74.2

(191.4)

51.5

(107.5)

51.3

(180.5)

42.5

(123.2)

Mean rank for No=133.97 & Yes=134.05

U= 8240, Z= -0.010          p= 0.992

Mean rank for No=266.08 & Yes=277.64

U= 28835.50, Z= -1.003   p= 0.316

Vigorous activity

55.6 (193.8)

34.0

(110.5)

43.5

(96.8)

35.4

(127.8)

43.4

(106.5)

Mean rank for No=130.25 & Yes=140.57

U=7607.50, Z= -1.508  p= 0.131

Mean rank for No=263.92 & Yes=282.79

U= 28017, Z= -1.893    p= 0.058


M (SD)–mean (standard deviation); X2–Chi Square test; U– Mann-Whitney U test; df–degrees of freedom; * p < 0.05; **p < 0.01; ***p< 0.001


Table 2: Nutrition and Physical Activity Characteristics by Nutrition and Physical Activity Program Attendance in the Government Sector and Hospitals, and Non-Government Sector.

 

 

Government Sector and Hospitals

n = 97 (n %)

M (SD)

Non-government Sector

n = 159 (n %)

M (SD)

Duration of program in weeks

 

19.4

(19.6)

31.6

(21.1)

Completed program

No

10

(10.3%)

20

(12.6%)

Still on

39

(40.2%)

101

(63.5%)

Yes

48

(49.5%)

30

(18.9%)

Not known

-

8

(5.0%)

Benefit

No

8

(8.2%)

6

(3.8%)

Some

38

(39.2%)

49

(30.8%)

A lot

51

(52.6%)

98

(61.6%)

Not known

-

6

(3.8%)

Table 3: Characteristics of Nutrition and Physical Activity Program Attendance in the Government Sector and Hospitals, and Non-Government Sector.

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