9 9. Questionnaire results (2): Social and other variables · Questionnaire results (2): Social and other variables 9 While lifestyle and behavioural factors, such as nutrition and

9. Questionnaire results (2): Social and other variables

9 While lifestyle and behavioural factors, such as nutrition and physical activity, are known to

contribute directly to diabetes risk, there are social and other variables which may influence

diabetes risk, either directly, or through their impact on risk behaviours.

This chapter details the responses to the survey that were not directly nutrition- or lifestyle-

focused. All percentages, unless stated otherwise, are based on the total number of participants

within each group (women: 49 diagnosed, 15 high-risk, 47 low-risk, 12 gestational; men: 38

diagnosed, 15 high-risk, 40 low-risk). Where possible, qualitative responses have been included

verbatim. Percentages do not necessarily sum to 100, as those unable or not wishing to answer

are included in the totals.

Participant categories are abbreviated as follows: D = diagnosed, H = high-risk, L = low-risk, G

= women who have in the past had gestational diabetes but are not currently diabetic. Where

differences between groups are tested for significance, ANOVA has been used unless otherwise

stated. Some survey responses are analysed in relation to BMI, as obesity is the most tangible

modifiable risk factor.

9.1. Sociodemography

9.1.1. Place of birth and mother’s place of birth

Is place of birth associated with birthweight? Places of birth for participants and their mothers

are shown in Tables 9.1 to 9.4. The lower percentages of diagnosed diabetics with mothers who

had been born in Cherbourg is likely to be a factor of the participants’ older ages; older

participants and/or their mothers are more likely to have been removed to Cherbourg from other

parts of Queensland. As health conditions on the settlement were poor (especially with high

rates of infections), this may affect the health of newborns and infants, both directly and through

the effects on their mother’s nutritional status during pregnancy. Mothers’ birthplace was

included as the effects of poor growth in utero can be passed from mother to child.

Social and other variables 307

Table 9.1. Participants’ place of birth Frequency Percent

Beaudesert 1 .5

Brewarrina 1 .5

Brisbane 10 4.6

Charleville 2 .9

Cherbourg 131 60.6

Collinsville 1 .5

Cunnamulla 1 .5

Gympie 2 .9

Herberton 1 .5

Kilcoy 1 .5

Kingaroy 3 1.4

Maryborough 1 .5

Monto 1 .5

Murgon 1 .5

Nambour 1 .5

Rockhampton 3 1.4

Roma 1 .5

Thursday Island 1 .5

Townsville 1 .5

Wondai 9 4.2

Not stated 43 19.9

Total 216 100.0

Table 9.2. Participants’ place of birth by category Females % Males %

(n) D(49) H(15) L(40) L(47) G(12) D(38) H(15)

Cherbourg 53.1 93.3 59.6 41.7 55.3 66.7 65.0

Other 14.3 6.7 31.9 50.0 5.3 33.3 15.0

Not stated 30.6 0 8.5 8.3 39.5 0 20.0


Table 9.3. Participants’ mothers’ place of birth Frequency Percent

Blackwater 1 .5 Bogabilla NSW 1 .5

Bowen 2 .9 Brewarrina 1 .5

Burnett Downs 1 .5 Burnett Station 1 .5

Charleville 2 .9 Cherbourg 126 58.3 Childers 1 .5

Cloncurry 1 .5 Collinsville 1 .5

Cooroy 1 .5 Cunnamulla 2 .9

Dalby 1 .5 Eisvold 1 .5 Emerald 2 .9 Gayndah 1 .5

Georgetown 1 .5 Goondiwindi NSW 2 1 Gundagai, NSW 1 .5

Hervey Bay 1 .5 Ipswich 1 .5

Ival 1 .5 Kilkivan 1 .5 Kingaroy 2 .9 Mitchell 2 .9 Murgon 2 .9

NSW (no further detail) 2 .9 Palm Island 5 2.3

Queensland (no further detail) 4 1.9 Quilpie 4 1.9

Scarness 1 .5 St George 1 .5

Taroom 1 .5 Toorowm 1 .5 Warwick 1 .5 Winton 1 .5

Yandina 1 .5 Yarrabah 1 .5 Not stated 33 15.3

Total 216 100.0


Table 9.4 Participants’ mothers’ place of birth Females % Males %

(n) D(49) H(15) L(47) G(12) D(38) H(15) L(40)

Cherbourg 40.8 53.3 70.2 75.0 42.1 73.3 72.5

Other 36.7 33.3 19.1 16.7 36.8 20.0 15.0

Not stated 22.4 13.3 10.6 8.3 21.1 6.7 12.5

Approximately 35% of diagnosed participants and 10% of those who had never been diagnosed

did not state their place of birth. This is most likely a function of the age differences between

these groups.

There were no significant differences in birthweight among participants who were born in

Cherbourg and those who were born elsewhere (Table 9.5). Males who did not state their place

of birth had significantly higher birthweights than those who named where they were born

(p=0.031) (Table 9.6).

Table 9.5. Birthweights and birthplace: Cherbourg and elsewhere Females Males

Place of birth n mean (g) SD n mean (g) SD

Cherbourg 43 3265 494 34 3267 590

Other 15 3262 689 16 3563 783

p 0.982 0.143

Table 9.6. Birthweights and birthplace: stated and not stated Females Males

n mean (g) SD n mean (g) SD

Stated 54 3244 556 38 3248 582

Not stated 4 802 3538 261 12 3719

P 0.301 0.031

Place of birth


Mother’s place of birth was not significantly associated with participant birthweight (Tables 9.7

and 9.8), although those born in Cherbourg tended to have babies who were lighter at birth. The

absence of statistical significance here may again be due to small sample size.

Table 9.7. Birthweights and mothers’ birthplace: Cherbourg and elsewhere Females Males


Cherbourg 39 3186 498 35 3313 591

Other 14 3500 632 9 3518 969

P 0.065 0.424

Table 9.8. Birthweights and mothers’ birthplace: stated and not stated Females Males


Stated 39 3186 498 35 3313 591

Not stated 19 3426 612 15 3475 823

P 0.115 0.436

9.1.2. Parity

Does number of siblings relate to diabetes risk? Participants’ mothers had given birth to

between 2 and 19 children. The mean numbers of babies were 8.2(D♀), 8.4(H♀), 7.1(L♀),

7.0(G♀), 7.6(D♂), 7.0(H♂) and 7.3(L♂). There were no significant differences between groups

(ANOVA, p=0.227). Birth order mean of participants was 3.9(D♀), 5.0(H♀), 4.2(L♀), 4.5(G♀),

4.2 (D♂) and 3.9(H♂), 4.2(L♂) and again there were no significant differences between groups

(ANOVA, p=0.958).

9.1.3. Natural family

Is being raised by people other than family (such as in the dormitories) associated with

subsequent diabetes risk? 16.3%(D♀), 6.7%(H♀), 12.8%(L♀), 33.3%(G♀), 21.1%(D♂), and

13.3%(H♂) and 27.5(L♂) reported that they did not grow up with either of their biological

parents. These frequency differences were not significant (Chi-square, p=0.357). Those who

did not grow up with their families were significantly older than those who did (t-test: mean

ages 41.8 and 37.1 years, p=0.027). The reasons participants gave for not growing up with their


family included being ‘under the Act’ (Section 4.2), family problems, staying with relatives

elsewhere for school, mother or both parents had died, or they had been abandoned or fostered

out.

9.1.4. Education

The highest levels of education reported by participants are given in Table 9.9 below. In

contrast to the wider Australian community (Turrell et al. 1999), education level is not

significantly associated with BMI (ANOVA, females p=0.780; males p=0.441), suggesting that

there is little class difference within the community, either overall or as it is manifested in

health.

Table 9.9. Highest level of education by diabetes risk group Females % Males %

(n) D(49) H(15) L(47) G(12) D(38) H(15) L(40)

Didn’t go to school 2.4 0.0 0.0 1.9 3 0.0 2.6

Primary school 26.2 0.0 0.0 0.0 24.2 6.7 5.1

Year 8 or 9 35.7 42.9 37.0 25.0 39.4 33.3 23.1

Year 10 or 11 28.6 35.7 45.7 50.0 18.2 46.7 41.0

Year 12 2.4 14.3 13.0 8.3 3 0.0 20.5

Trade qualification 0.0 0.0 0.0 0.0 6.1 6.7 5.1

Tafe diploma / certificate 4.8 0.0 4.3 0.0 6.1 0.0 2.6

University degree 0.0 7.1 0.0 0.0 0.0 6.7 0.0

Postgraduate degree 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Among all participants over 35 years old, there is no significant association between education

level and category (Chi-square, p=0.414), but among those who are younger than 35 years the

association is significant (p=0.001) and strong (Chi-square value = 60.4) with younger

participants attaining a higher level of education. The differences between diagnosed and

never-diagnosed participants may have more to do with cohort effects than anything else, for

two related reasons. Firstly, school facilities and Indigenous access to them have improved

greatly over recent years, and secondly, extensive schooling in the past was often viewed by

authorities as unnecessary and wasteful and irrelevant to building the labouring class of


Aboriginal workers – they were deemed to be more compliant if they only had basic education

(Section 4.3.5). It was common for children in Cherbourg to leave school at 14; boys to learn a

trade, and girls to go into domestic service.

9.1.5. Occupation and hours of work

The most common occupation for women was ‘home duties’: (28.6% D♀, 33.3% H♀, 31.9%

L♀ and 58.3% G♀), and for men: office worker (15.8%) followed by heavy trade, CDEP and

those unable to work (each 10.5%) for diagnosed males, and CDEP (26.7% for high-risk and

40.0% for low-risk). Table 9.10 shows frequencies for all occupations.

Table 9.10. Occupation

Females % Males %

(n) D(49) H(15) L(47) G(12) D(38) H(15) L(40)

Office worker 6.1 6.7 4.3 16.7 15.8 20.0 5.0

Shop assistant 4.1 6.7

Light trade / labour 2.0 6.7 7.9 13.3 12.5

Heavy trade / labour 10.5 10.0

Home duties 28.6 33.3 31.9 58.3 2.6 6.7 2.5

CDEP 6.1 6.7 25.5 16.7 10.5 26.7 40.0

Unemployed 13.3 10.6 8.3 5.3 13.3 10.0

Unable to work 18.4 6.7 4.3 10.5 10.0

Other 22.4 17.0 23.7 20.0 5.0

Not stated 12.2 20.0 6.4 13.2 5.0

Hours worked per week (all jobs) ranged from 2 to 50. Divisions along gender lines were

apparent. On average, women do roughly half the number of hours of paid work that men do,

(t-test, means 8.5 hours of paid employment for females and 20.8 hours for males, p<0.001)

(Figure 9.1). This illustrates that although unemployment is fairly low, underemployment is a

significant issue.


Mean number of hours in paid work per week

malesfemales

num

ber o

f hou

rs30

25

20

15

10

5

0

diagnosed

gestational

high risk

low risk

9.2. General health

9.2.1. Self-rated general health

Overall, people with diagnosed diabetes rated their health more poorly than

never been diagnosed, and women rated their health more poorly than men in ea

(Table 9.11).

Table 9.11. Self rated health response frequencies (%) Females % Ma

(n) D(49) H(15) L(47) G(12) D(38) H

Poor 16.3 21.4 4.4 16.7 6.1 0

Fair 39.5 7.1 22.2 41.7 30.3 2

Good 27.9 57.1 40.0 25.0 48.5 2

Very good 4.7 14.3 24.2 8.3 9.1 3

Excellent 11.6 0.0 8.9 8.3 6.1 1

Figure 9.1. Mean number of hours spent in paid employment each week.

those who had

ch risk category

les %

(15) L(40)

.0 0.0

6.7 15.4

6.7 48.7

3.3 17.9

3.3 17.9


That participants with diagnosed diabetes rated their health more poorly than others is probably

due to the intrusiveness of diabetes into daily life. They are aware they have a chronic illness,

they are under pressure to manage the disease, from doctors, health workers and themselves and

family, through their diet and activity, which means that it is something they are always

thinking about, for example, whether they should eat certain foods, and the guilt associated with

eating some foods.

When health rating was considered as a score out of five, where ‘poor’ = 1 and ‘excellent’ = 5,

males in the low-risk group gave the highest rating (3.4 out of 5) for their health while

diagnosed and gestational women gave the lowest (2.6 and 2.5 out of 5) (Figure 9.2). Both

high-risk females and males rated their health as slightly worse than the low-risk of each sex,

but better than those who had been diagnosed.

Self-rated health

malesfemales

self-

rate

d he

alth

(sco

re fr

om 5

)

3.6

3.4

3.2

3.0

2.8

2.6

2.4

diagnosed

gestational

high risk

low risk

Lower self-ratings of health is not confined to people who have been diagnosed; BMI might be

more important. For example, Ferraro and Yu (1995) found higher BMI was related to lower

self-ratings of health. This association is also apparent in the present study, as undiagnosed

women and men with lower BMIs tended to rate their health as better (Figure 9.3), although

these differences were not significant (ANOVA, p=0.774 for women, 0.399 for men).

Figure 9.2. Mean self-rated health, where: poor=1 fair=2, good=3 very good=4 excellent=5.


Association between BMI and self-rated health

self-rated health

54321

BMI

36

34

32

30

28

26

females

males

Figure 9.3. Mean BMI of never-diagnosed females and males according to their self rated health (1=poor, 5=excellent).

Although not significant, this tendency is consistent with findings among young Australian

women that women with a normal BMI (i.e. <25) reported fewer morbidities than those with

higher BMIs (Brown et al. 2000). Younger age and better self-assessed health status are usually

associated (Cunningham et al. 1997), but in the present study age was not significantly

associated with self-rated health among women (ANOVA, p=0.088) or men (p=0.782).

Self-rated health was significantly negatively correlated with the number of times participants

reported they had been sick or unwell in the last 12 months (Pearson correlation = -0.352,

p<0.001), meaning that those who rated their health better reported fewer illness episodes. Self-

ratings of health are therefore probably a valid measure, although recall bias is possible; those

who perceive their health to be poorer may recall a greater number of illness episodes than those

who perceive their health to be relatively better. Diagnosed women reported the highest mean

number of episodes (Table 9.12).


Table 9.12. Mean number of medical visits in the previous 12 months Females % Males %

(n) D(49) H(15) L(47) G(12) D(38) H(15) L(40)

Mean number of visits 3.9 2.3 2.5 2.0 3.0 2.6 1.4

9.2.2. Family history of diabetes

The majority of participants reported one or more members of their immediate families as

having had diabetes (Table 9.13). Category and family history were not independent of each

other (Chi-square: p=0.004). The associations were not independent of age; in those over 35

years there were no significant associations between category and family history (Chi-square:

p=0.331), while in younger participants category was strongly associated with family history

(Chi-square: p<0.001, value=24.43).

Table 9.13. Positive family history of diabetes by category and age group (%)

Females Males

(n) D H(15) L(47) G(12) D(38) H(15) L(40)

<35 years % 100 100 76.5 77.8 0 83.3 29.2

positive n (total n) 4 (4) 6 (6) 26 (34) 7 (9) 0 (1) 5 (6) 7 (24)

≥35 years % 73.3 66.7 46.2 100 64.9 55.6 50.0


All % 75.5 80.0 68.1 83.3 63.2 66.7 37.5


The mean numbers of family members reported by participants as having had diagnosed

diabetes were 2.05(D♀), 1.86(H♀), 1.74(L♀), 3.00(G♀), 1.52(D♂) and 1.21(H♂) and 0.92(L♂),

but this is not adjusted for total number of family members (calculation includes those with zero

family members diagnosed).

9.2.3. Stress

Subjective total stress ratings were calculated out of a maximum of 27, based on scales of 0-3

for each of the nine variables. The group reporting the highest overall subjective stress rating

was the gestational women, followed by diagnosed women, then diagnosed men; high-risk and


low-risk women were the next most stressed, and low-risk and high-risk men were the least

stressed. (Table 9.14). The dominant identified causes of stress were different between groups.

Among those diagnosed, the variables likely to cause the most stress were the participants’ own

health (probably explaining why people with diagnosed diabetes rated the highest overall),

health of family members, and money, while among the remainder it was health of family,

relationships with partner, family and friends, and money which were the most stressful. That

few significant differences were found for ratings of subjective stress may indicate that levels of

stress within the community are fairly uniform. Overall, female and male participants differed

significantly in their subjective stress levels for work (t-test: means 0.37 and 0.67 out of 3,

p=0.020), and relationship with family (t-test: means 0.83 and 0.48 out of 3, p=0.009).

Table 9.14. Mean subjective stress ratings for health and social variables. N.B. Mean for each variable is out of 3, total is out of 27. Tests for significance were ANOVA and post-hoc Scheffe test.

Females Males ANOVA

(n) D(49) H(15) L(47) G(12) D(38) H(15) L(40) p

Own health 1.49 (43)a

0.93 (14)

0.83 (46)

1.17 (12)

1.3 (33)

0.80 (15)

0.51 (39)a 0.002

Health of family members

1.07 (43)

0.93 (14)

0.80 (46)

0.92 (12)

1.12 (33)

0.53 (15)

0.82 (39) 0.537

Work 0.37 (43)

0.50 (14)

0.26 (46)

0.87 (15)

0.64 (14)

1.25 (12)

0.76 (46)

Relationship with friends

0.67 (12)

0.94 (33)

0.36 (39) 0.007

Study 0.14 (43)

0.29 (14)

0.09 (46)

0.17 (12)

0.27 (33)

0.07 (15)

0.21 (39) 0.628

Money 1.02 (43)

0.79 (14)

0.74 (46)

1.17 (12)

0.88 (33)

0.40 (15)

0.49 (39) 0.133

Living conditions 0.86 (43)

0.57 (14)

0.39 (46)

0.75 (12)

0.42 (33)

0.40 (15)

0.38 (39) 0.160

Relationship with partner

0.58 (43)

0.63 (46)

0.64 (33)

0.33 (15)

0.51 (39) 0.437

Relationship with family members

0.98 (43)

0.86 (14)

0.58 (12)

0.70 (33)

0.13 (15)

0.44 (39) 0.062

0.30 (43)

0.14 (14)

0.37 (46)

.033 (12)

0.30 (33)

0.14 (15)

0.07 (39) 0.749

Total 6.8 (43)

5.6 (14)

4.9 (46)

7.0 (12)

6.6 (33)

3.6 (15)

4.0 (39) 0.031

a Significant difference, Scheffe: p=0.011

In coping with stress, the majority of participants felt that there was someone they could talk to,


although this may not be the action they usually take (Table 9.15). The remainder report usually

choosing other, disparate, means to cope. Examples include prayer, cleaning, exercising,

reading, drinking alcohol, or smoking cannabis.

Table 9.15. Action available and action taken when feeling stressed Females % Males %

(n) D(49) H(15) L(47) G(12) D(38) H(15) L(40)

Have someone to talk to when stressed 61.2 60.0 74.5 83.3 63.2 66.7 80.0

Talk to friend or family member when stressed

28.6 26.7 38.3 16.7 21.1 33.3 25.0

Do nothing 22.4 13.3 29.8 41.7 18.4 32.5 Usu

al a

ctio

n w

hen

stre

ssed

26.7

Women and men did not differ in reporting whether or not they had someone they could talk to

(Chi-Square, p=0.883), nor did they differ on the action they usually took (p=0.577). Diagnosed

and high risk women as a group were less likely to talk to someone than low risk women, but

this did not reach statistical significance (p=0.097). No such difference was apparent for men

(p=0.491).

9.3. Body image

Participants were asked whether they were happy with their body size and shape, and whether

they thought their body size and shape were normal, healthy and attractive for someone of their

age and sex. The group that was the most confident with their bodies were the low-risk males,

rating the most positive for happy, normal and healthy, although high-risk males were more

positive about their body attractiveness. The least confident, rating the lowest for positive

responses and the highest for negative responses to all questions, were the diagnosed females

(Table 9.16). Differences between the groups were significant for happy, healthy and attractive,

but not for whether they considered their bodies to be normal (Table 9.17). Men had greater

body confidence than women overall.


Table 9.16. Participants’ body image: happy, normal, healthy, attractive Females Males

(n) D(49) H(15) L(47) G(12) D(38) H(15) L(40)

Yes 37.4 46.7 66.0 41.7 44.7 60.0 82.5

Hap

py

No 51.0 40.0 27.7 58.3 42.1 40.0 15.0

Yes 36.7 33.3 57.4 50.0 44.7 40.0 72.5

Nor

mal

No 44.9 53.3 36.2 41.0 42.1 53.3 22.5

16.3 33.3 40.0 16.7 36.8 33.3 65.0

No 49.0 33.3 29.8 33.6 28.9 46.7

Don’t know 20.4 20.0 23.4 41.7 21.1 15.0

Yes 6.1 13.3 14.9 16.7 15.8 40.0 25.0

No 51.0 33.3 38.3 50.0 36.8 20.0 12.5

Attr

activ

e

Don’t know 26.5 33.3 38.3 25.0 31.6 33.3 55.0

Yes

15.0

Hea

lthy

13.3

Table 9.17. Chi-square: significant differences between groups for body image

Chi-square value p value

Happy 30.12 0.003

Normal 23.25 0.181

Healthy 31.90 0.023

Attractive 30.89 0.030

The ‘don’t know’ option was included for the questions on healthy and attractive as they were

deemed more difficult to assess subjectively without feeling embarrassment. The high rate of

people who gave ‘don’t know’ responses, especially for the question on attractiveness, was

probably due more to embarrassment or shyness rather than an absence of a opinion. Some of

the younger men in particular were a little embarrassed (but amused) by the question (asked by

young women), and they were unsure how to respond. Men still rated themselves as attractive

at about twice the rate of women.


Body image depended very much on BMI. For women, those who were happy with their shape

had a mean BMI that was 6.2 kg/m2 lower than those who were not happy (t-test: means 28.4

and 34.6, p<0.001). Similar result were found for ‘normal’ (t-test: means 28.3 and 34.2, p =

0.002) and for both ‘healthy’ (t-test: means 28.6 and 34.1, p = 0.024) and ‘attractive’ (t-test:

means 27.0 and 32.0) although the last difference was not significant (p=0.209), possibly due to

the high percentage of ‘don’t know’ responses to this particular question (59.1%).

For men, those who were happy with their shape also had significantly lower BMIs than those

not happy (means 26.2 and 32.2, p<0.001). Again this was similar pattern as those who thought

their shape was normal (26.0 and 31.7, p<0.001), healthy (25.7 and 32.4, p<0.001) or attractive

(27.1 and 31.5) although again the latter difference was not significant (p=0.102).

Participants were also asked what would make a healthier or more attractive body shape (fatter,

thinner, taller, shorter, more muscled, less muscled). The most frequent response for women

was thinner for both healthier and more attractive respectively, and these were occasionally

coupled with more muscled and taller (Tables 9.18 and 9.19). For men, being healthier was

associated most with being thinner or being more muscled. It seems that, for men at least, the

same ideal relates to being both healthy and attractive, with men choosing thinner or more

muscled at almost the same rates. As the main differences appeared to be along gender lines,

high- and low-risk participants are combined as there was so little difference between them.

That body shapes that are considered healthy and attractive are similar to each other is

consistent with findings from Craig et al. (1999) in both Tongan and Australian samples.


Table 9.18. What a healthier body would look like

Females %a Males %a

(n) D(49) H(15) L(47) G(12) D(38) H(15) L(40)

Fatter 8.1 13.4 8.5 8.3 10.5 6.7 12.5

Thinner 36.8 20.0 33.6 50.0 28.9 20.0 12.5

More muscled 4.1 26.7 6.4 8.3 23.7 40.0 22.5

Less muscled 0.0 0.0 0.0 0.0 2.6 6.7 2.5

Taller 4.1 6.7 4.3 0.0 0.0 0.0 5.0

Shorter 0.0 0.0 0.0 0.0 5.2 0.0 2.5 aAs some participants gave more than one response, totals may be greater than 100%.

Table 9.19. What a more attractive body would look like

Females %a Males %a

(n) D(49) H(15) L(47) G(12) D(38) H(15) L(40)

Fatter 6.1 20.0 4.3 0.0 13.1 6.7 5.0

Thinner 34.7 58.3

26.7 25.0

40.0 26.7 28.9 16.7 10.0

More muscled 6.1 13.4 17.0 16.6 23.7

Less muscled 4.1 0.0 4.2 0.0 2.6 6.7 5.0

Taller 4.1 6.7 4.2 8.3 0.0 0.0 7.5

Shorter 0.0 0.0 0.0 0.0 2.6 0.0 2.5

aAs some participants gave more than one response, totals may be greater than 100%.

When asked what type of body shape they would themselves prefer to have, in general women –

and diagnosed men – would rather be thinner, while men who had never been diagnosed chose

more muscled (Table 9.20). This is consistent with findings in the United States and Australia

from Sciacca et al. (1991) and Donath (2000) who found that women were about twice as likely

as men to consider themselves overweight, and with Rand and Wright (2001) (United States)

who found a bias towards a preference for thinner females across age groups, which was

particularly marked among young adults. In another United States study, Leit et al. (2001)


concluded that the cultural norms of the ideal male body were becoming more muscular. This

trend could be reflected here too, through the influence of dominant images on television and in

magazines. Pressure is not just on women to have particular body shapes, but also on men. An

additional option of ‘happy as I am’ was added to this question, which many people chose.

Table 9.20. Preferred body shape

Males %Females %a a

(n) D(49) H(15) L(47) G(12) D(38) H(15) L(40)

Fatter 4.1 13.4 4.4 0.0 7.9 0.0 7.5

Thinner 36.7 20.0 34.0 49.9 34.1 19.9 5.0

More muscled 8.1 0.0 8.5 0.0 13.1 26.7 12.5

Less muscled

0.0 2.1

0.0 0.0 0.0 0.0 2.6 6.7 0.0

Taller 4.0 0.0 4.3 0.0 0.0 0.0 2.5

Shorter 0.0 0.0 5.2 0.0 2.5

Happy as I am 38.8 46.7 38.3 41.1 31.6 46.7 67.5 aAs some participants gave more than one response, totals may be greater than 100%.

9.4. Diabetes knowledge and beliefs

This part of the questionnaire was to ascertain community understandings of diabetes. Most of

the questions in this section appeared in the section of the questionnaire aimed at diagnosed

diabetics only.

9.4.1. Perceived risk of diabetes and heart disease

Participants’ responses to how likely they thought it was that they would get diabetes and heart

disease are shown in Table 9.21. There were no significant differences between high-risk, low-

risk and gestational groups in their perceived risk of developing diabetes (Chi-square: p=0.582),

but differences were approaching significance level for heart disease (Chi-square: p=0.050,

value = 51.7).


Table 9.21. Self-rated likelihood of developing diabetes and heart disease

Females Males

(n) D(49) H(15) L(47) G(12) BMI D(38) H(15) L(40) BMI

n/a 6.7 6.4 33.3 31.2 n/a 20.0 7.5 29.5 Somewhat

likely n/a 6.7 12.8 16.7 33.0 n/a 20.0 12.5 31.9

Not very likely n/a 20.0 10.6 0.0 29.3 n/a 6.7 22.5 26.0

Not at all likely n/a 20.0 14.9 16.7 29.8 n/a 13.3 17.5 25.1

Don’t know n/a 40.0 51.1 25.0 27.7 n/a 33.3 37.5 27.0

Very likely 8.2 6.7 2.1 8.3 40.1 13.2 13.3 5.0 32.4 Somewhat

likely 4.1 13.3 2.1 16.7 30.3 15.8 20.0 17.5 30.0

Not very likely 4.1 20.0 19.1 8.3 32.4 5.3 20.0 15.0 27.5

Hea

rt di

seas

e

Not at all likely 6.1 6.7 14.9 16.7 30.0 0.0 13.3 17.5 25.3

Don’t know 46.9 40.0 53.2 25.0 30.3 42.1 26.7 40.0 27.8

Already have it 8.2 0.0 0.0 0.0 32.3 5.3 0.0 2.5 30.0

Very likely

Dia

bete

s

Among women who did not currently have diagnosed diabetes, perceived risk of diabetes

tended to be lower among those with lower BMIs, but this was not significant (ANOVA:

p=0.589). Among men who did not have diagnosed diabetes, the trend was similar, but again

not significant (ANOVA: p=0.180). There was no such trend for perceived risk of heart disease

among female (p=0.111) or male (p=0.131) participants. This does suggest, though, that there is

some understanding that being overweight increases a person’s risk for these diseases, but that

overweight is not seen by most people as sufficient in itself to put a person at risk.

The following sections refer only to those participants with diagnosed diabetes, who were asked

to complete an additional section of the survey, about their knowledge, beliefs and behaviour to

do with diabetes.

9.4.2. Time since diagnosis

The mean time since diagnosis (as recalled by participant) was 4.2 years for women and 3.9

years for men. The responses ranged from two weeks to 14 years.


9.4.3. Causal beliefs

Participants were asked open-ended questions about both what their doctor had said had caused

their diabetes, and also what they personally thought caused it. These responses were then

categorised into two primary themes: lifestyle or heredity. Results are presented in Table 9.22.

Table 9.22. Participants’ recall: what did the doctor tell you caused your diabetes?

(n) Examples of participant responses Females % (49)

Males % (38)

Heredity

Hereditary

It’s come from your mother

It’s in the family my mother had it

Through family history

Genes

Runs in the family

8.2 15.8

Lifestyle

Sweets, fats, stress

Too much sugar in my foods and fatty foods

Too much sugar

Unhealthy eating habits

Due to alcohol

Obesity

8.2 21.1

Both lifestyle and hereditary factors Overweight, family history 2.9 0.0

No explanation given

The doctor said nothing

Never said anything 25.4 13.2

Explanation given but cannot

remember what they said

Can’t remember

Forgot what he said 2.0 3.6

Did not answer - 53.3 46.3

There was no mention of physical inactivity in the patient’s recall of contributing lifestyle

factors.


Participants were also asked what they thought had caused their diabetes. Participants were

about twice as likely to say they thought their lifestyle caused their diabetes than to think it was

hereditary (Table 9.23).

Table 9.23. Participants’ beliefs: what do you think caused your diabetes?

(n) Examples of participant responses Females % (49)

Males % (38)

Heredity

Mum or Dad

Hereditary

Family history

Reckon it’s through the blood - mother, brothers and sister have it. Through the family

tree I s’pose

8.2 13.2

Lifestyle

Eating the wrong food

Drinking grog a lot

Fat and sugar

Being overweight

I was overweight for my age

Too fat

Too much beer

Wrong food and drink

16.3 31.6

Both lifestyle and hereditary factors Too much salt, runs in the family 4.1 2.6

Don’t know - 16.3 7.9

Did not answer - 55.1 44.7

9.4.4. Complications

The most frequently reported complications from diabetes were eye problems followed by feet,

breathing and kidneys (Table 9.24). Problems with ‘skin’ refers to ulcers, while ‘breathing’

refers to feeling out of breath, most likely due to a general lack of fitness or a side effect of

some blood pressure lowering medications. These categories do not exclude other, non-diabetes


related health problems, such as asthma or emphysema (‘breathing’) or ringworm, scabies or

boils (‘skin’) which were most likely alluded to in the responses. Females were significantly

more likely than males to report breathing difficulties that they associated with diabetes (Chi-

square: p=0.025, value=5.058). There were no significant differences in reported frequencies

between females and males for any other diabetes associated problem.

Table 9.24. Diabetes complications reported by participants

Females % (49) Males % (38)

Eyes 32.7 42.1

Feet 26.5 26.3

Breathing 30.6 10.5

Kidneys 22.4 13.2

Heart 16.3 10.5

Skin 16.3 18.4

9.4.5. Medication

Participants were asked whether they were taking medication for their diabetes, whether they

took it exactly as prescribed, and whether they knew how it was meant to help (Table 9.25).

The types of medication people were taking varied, and included blood-pressure-lowering

medication, and metformin (Glucophage) to improve insulin sensitivity, and in the few months

leading up to the survey, a newly arrived doctor had placed several participants on insulin.


Table 9.25. Participants on medication for diabetes

Females (49) Males (38)

% of diagnosed participants currently

on medication for diabetes

57.1 (28) 57.9 (22)

Of those taking medication, % who

report taking it exactly as prescribed

71.4 (20) 72.7 (16)

Of those taking medication, % who were able to give a

simple explanation of how the medication

helps

42.9 (12) 31.8 (7)

Examples of explanations given by participants of

how their medication helps

Helps me to lose weight

Keeps my sugar levels down

It slows down the sugar build up in my body

Keeps my sugar at a even level

Controls sugar and blood pressure

9.4.6. Lifestyle advice and behaviour change

Participants were asked open-ended questions about the advice on diet and exercise they had

been given. Responses were categorised into general advice (for example ‘eat healthy’ or ‘do

more exercise’), specific advice (for example ‘eat high fibre foods, less sugar and salt’ or to

‘walk for 20 minutes a day’), and no advice.

Diet

General advice for changing their diet was recalled by 10 (20.4%) women and 11 (28.9%) men,

and specific advice by 11 (22.4%) women and six (15.8%) men. Four (8.2%) women and four

(10.5%) men stated that they were not given any advice about diet at all.


When asked if they had implemented any changes to their diet since finding out they had

diabetes, 17 (34.7%) women and 16 (42.1%) men said they had. Among those who had made

dietary changes, the perceived health benefits were widespread, with 14 (88.2%) of the women

and 100% of men who had made dietary changes reporting that it had improved their health.

Exercise

Receiving general advice on exercise was recalled by 10 (20.4%) women and 11 (28.9%) men,

while specific advice was recalled by 11 (22.4%) women and five (13.2%) men. Four (8.2%)

women and five (13.2%) of men said they had not been given any advice about exercise.

Changes to exercise had been made by fewer people than changes to diet, with only five

(10.2%) women and nine (23.7%) men reporting that they had implemented changes since

diagnosis to improve their health. Again, these changes were perceived to be beneficial, with

four of the five women (80.0%) and eight of the nine men (88.9%) who had made changes

reporting that these had improved their health.

Receiving specific advice may increase the likelihood of changes being implemented. Only one

person from nine (11%) who said they had not been given any dietary advice had made some

changes to their diet, while 10 (47.6%) of those recalling general advice and 15 (88.2%) of

those recalling specific advice had made some changes. Seven (33.3%) who recalled general

advice and four (25%) who recalled specific advice had implemented changes to their exercise

regime. These results suggest that people are more willing to make changes to their diet than to

how much exercise they do. Of course, with both diet and exercise it may be that those who

have made changes that are more likely to recall having received advice than those who did not

make changes.

9.5. Women

To determine whether reproductive history was linked with diabetes risk among women, female

participants were asked additional questions regarding their experiences relating to pregnancy,

how many children they had and how old they were when they had their first baby.

Of the 123 women who took part in the survey, 79.7% had had at least one baby. The ages at

which they had their first baby ranged from 13 years to 29 years (mean =18.46) and the number

of children ranged from 1 to 14 (mean 4.15) (Table 9.26).


Table 9.26. Mean number of babies (of those who had given birth at least once), mean age at first birth and mean age at time of survey

(n) Number of babies Age at first birth (years) Age at time of survey

(years)

Diagnosed (49) 4.4 18.7 46.5

High-risk (15) 3.9 16.9 34.5

Low-risk (47) 3.9 19.0 31.1

Gestational (12) 4.4 17.7 31.3

Given their relatively older ages, women in the diagnosed group are more likely to have

completed their families at the time of the survey. Interestingly, women who had been

diagnosed with gestational diabetes began having their children at a slightly younger age, and

had given birth to more children at the time of the survey than other, currently undiagnosed,

women. This may be because each pregnancy provides an additional opportunity to develop

gestational diabetes, or there may be some other relationship, such as where risk of gestational

diabetes in subsequent pregnancy increases.

Seven of the women who currently had diabetes reported that they had been diagnosed with

gestational diabetes (in addition to the 12 others who had had gestational diabetes in the past but

who were not currently diagnosed with diabetes).

Female participants were asked whether they received enough advice from doctors and health

care workers when they were pregnant about having a healthy pregnancy. About 10% of

women in each group stated that they had not been given enough advice. One woman in the

gestational diabetes category, who was 15 when she had her first child, responded: ‘I was so

young and they just used too many big words for me and I just nodded if they asked if I

understood’.

9.6. Conclusions

These descriptive results from the questionnaire part of the survey go some way to illustrate

some of the lifestyle and behavioural features that may be contributing to diabetes in Cherbourg,

and where improvements in health education might be made. In the following chapter, the main

findings of the study are presented and discussed in their social context.

Documents

9 9. Questionnaire results (2): Social and other variables · Questionnaire results (2): Social and other variables 9 While lifestyle and behavioural factors, such as nutrition and