Cardiovascular Journal of Africa: Vol 30 No 5 (October 2019)

CARDIOVASCULAR JOURNAL OF AFRICA • Volume 30, No 5, September/October 2019

264

AFRICA

Cross-tabulation procedures and Fisher’s exact tests were

used to check for statistically significant differences between

rural and urban groups. Linear regression analysis was used to

test predictive relationships for age, gender, employment status

and geographical location (rural and urban). The regression was

computed using PA METS as the continuous outcome variable.

Results

A total of 319 adult males and females aged 30 to 70 years

(females

78.4%, males

21.6%) participated in the study. The

mean age of the participants was 57

10.43 years, with rural

participants being 58

10.71 years and urban participants being

10.18 years. Among the rural and urban participants, most

were female (82.1% female vs 17.9%male, 76.2% female vs 23.8%

male, respectively).The mean PA METs for rural participants

was 6.33

3.77 METs and for urban participants 5.57

3.95

METs.  

max for rural participants was 22.17

13.19 ml/kg/

min and for urban participants 19.50

13.83 ml/kg/min. Overall,

rural participants engaged in more physical activity than urban

participants.

Regarding gender and physical activity, females had a mean

of 5.62

3.74 PA METs and  

max of 19.67

13.08 ml/kg/

min. Males, on the other hand, had a mean of 6.69

4.35 PA

METs and a  

max of 23.43

15.22 ml/kg/min. Overall, men

engaged in more physical activity than women and at a higher

intensity. However, PA METs values between genders (

0.248)

and between rural and urban participants (

0.013) were not

significantly different.

The majority of the rural participants engaged in more

than 30 minutes of exercise per day, with most engaging in

vigorous-intensity physical activity. However, most of the urban

participants engaged in less than 30 minutes of physical activity

per day, but most engaged in vigorous-intensity physical activity.

Significant differences were found (

0.000) for the duration of

physical activity per day between rural and urban participants.

Rural participants were more likely to meet the physical activity

recommendations to promote cardiovascular fitness than the

urban participants.

Table 1 shows the frequency distributions of the socio-

demographic variables for both rural and urban participants.

Table 2 shows the frequency distributions of physical activity

behaviours for both rural and urban participants

The means and standard deviations for all predictors and

outcome variables were assessed for normality. Tests for skewness

and kurtosis were not significant. Therefore the assumptions for

regression analysis were met. Table 3 shows the results of the

regression analysis.

The model combining age, gender, geographical location and

employment status tested significantly at a 0.03 alpha level. The

model explained 3.4% of the variance in physical activity. Gender

was a significant predictor of physical activity when controlling

for geographical location, age and employment status. Physical

activity increased by 0.118 METs from female to male gender.

Geographical location was a significant predictor of physical

activity, when controlling for gender, age and employment status.

Although the overall effect size was very modest, it provided

empirical support for the role of gender and geographical

location in predicting overall physical activity. Physical activity

decreased by 0.112 METs from rural to urban location.

Discussion

The results of the study reveal that the majority of rural

participants engaged in more than 30 minutes of exercise per

day, with most engaging in vigorous-intensity physical activity.

Although most of the urban participants engaged in less than 30

minutes of physical activity per day, most engaged in vigorous-

intensity physical activity. In terms of duration and intensity of

physical activity, it appears that the rural participants were more

likely to meet the physical activity recommendations to promote

cardiovascular fitness than the urban participants.

A study investigating the prevalence of sociodemographic

correlates of physical activity among rural and urban adults in

South Africa found that women engaged less in physical activity

compared to men.

An earlier study also indicated that men were

more likely to engage in physical activity than women, especially

in leisure time and occupational activities.

Similar findings

were also reported by Guthold and colleagues.

A Rwandan

study

also reported that women engaged less in physical activity

compared to men.

In the present study, gender was found to be a significant

predictor of physical activity, with men engaging in more physical

activity than women in both urban and rural environments.

The findings of the current study could be linked to the fact

that South Africa is a country in transition, with marked

infrastructural development where men are usually employed to

perform activities that are associated with moderate-to-vigorous

intensity physical activity.

On the other hand, the influence of

African culture may mean that women are employed in domestic

work, which is typically associated with minimal and light-to-

moderate intensity physical activity, which is especially so in

black township communities in South Africa.

Therefore within

low-income communities, where most men are usually involved

in unskilled manual labour, it is expected that they would have

higher levels of physical activity than the women.

Table 1 Frequency distributions of the sociodemographic variables

Sociodemographic details

Fisher’s exact

test (

-value)

Rural

(

117)

Urban

(

202)

Category

Gender

Male

21 17.9 48 23.8

0.000**

Female

96 82.1 154 76.2

Education

None

2.6 1 0.5

0.000**

Primary

51 43.6 71 35.1

Secondary

59 50.4 118 58.4

Vocational/trade school

1.7 2 1.0

Tertiary

1.7 5.0 10

Employment

Full time

4.3 29 14.4

0.000**

Part time

6.8 16 7.9

Self-employed

7.7 14 6.9

Unemployed

59 50.4 89 44.1

Retired

36 30.8 54 26.7

Total household income/month

< R2 000

85 72.6 124 61.4

0.001**

R2 000 – R5 000

29 24.8 62 30.7

R5 001 – R10 000

1.7 14 6.9

> R10 000

0.9 2 1.0

*Statistically significant at the 95% confidence level;

**statistically significant at the 99% confidence level.