Poor dietary habits are major contributors to malnutrition globally, particularly in children living in African countries. The widespread transition from African diet of healthy indigenous foods to a nutrient-poor Western-style diet is well-documented in global societal culture.
Aim
This study aimed to assess the dietary habits and their nutritional implications among learners in public primary schools.
Setting
City of Tshwane, located in the Gauteng province of South Africa.
Methods
This was a quantitative cross-sectional study where researcher-administered questionnaire was used to collect data from 814 primary school learners in grades 4–7. Anthropometric data were also collected. The study was conducted in 10 primary schools in the City of Tshwane.
Results
Unhealthy dietary practices were observed where consumption of refined carbohydrates, sugar-filled beverages and limited protein was prevalent. The prevalence rates for overweight and obesity were 15.1% and 11.3%, respectively. Most learners (77.4%) purchased foods from street vendors and tuckshops. Also, learners who knew about healthy eating were less likely to be underweight than those who did not (OR: 0.35; 95% CI: 0.14–0.85; p = 0.020).
Conclusion
Poor dietary habits are demonstrated in this study and may be associated with the rising levels of overweight and obesity among the learners. The findings also showed that the school environment is the main source of exposure to unhealthy diet.
Contribution
Intervention strategies, such as amendment of the national school nutrition policy, need to be implemented.
learnersprimary schooldietary habitsnutrition statusnutritionobesityFunding information The authors received financial support from the Sefako Makgatho Health Science University research grant.Introduction
Poor dietary habits lead to malnutrition, which is a major public health concern contributing to the global burden of disease. It is reported that a significant number of children suffer from malnutrition because of poor eating habits worldwide (UNICEF 2019). Evidence shows that poor eating habits have been linked to life-threatening consequences such as stroke, type 2 diabetes mellitus (T2DM), different types of cancers and cardiovascular diseases in both children and adults (World Health Organization [WHO] 2023). The documented benefits of good nutrition include a delayed onset of chronic diseases of lifestyle (Centre for Disease prevention 2021).
Globalisation and urbanisation have exposed people to unhealthy, Westernised diets that are high in fats, sugars and refined carbohydrates while lacking micronutrients, fibre and whole foods (Casari et al. 2022). Highly processed foods, which contribute to the global obesity epidemic, are firm favourites among children and adolescents (WHO 2019). The disadvantages of poor nutrition are well-documented, but it is crucial for children to be taught about healthy eating regularly so that they may adopt good dietary practices early in life and carry these over into adulthood. Assessing learners’ daily dietary habits may give researchers an indication of whether they are eating healthily or not, and may contribute to the development of school-based interventions to promote healthy diets and prevent the short- and long-term consequences of poor eating habits from developing among learners.
Studies conducted in developed and developing countries have reported that the consumption of fruits and vegetables among primary school learners is low (Hong & Piaseu 2017). A recent study conducted in urban South African schools found that learners purchased unhealthy foods from street vendors and school tuckshops (Phetla & Skaal 2023). Phetla and Skaal (2023) in their study conducted in Tshwane, South Africa, further reported that the lunchboxes of most learners contained sweets, sugar-sweetened beverages and snacks, while only a few contained fruits and vegetables. Carrying a nutritious lunchbox to school contributes to good eating habits and the development of a healthy body and mind (Nathan et al. 2019). It is therefore concerning that most learners carried lunchboxes containing unhealthy food to school (Sutherland et al. 2020). Learners who brought pocket money to purchase food from school tuckshops and street vendors were prone to buying fast foods containing high fat, high salt, refined carbohydrates, high sugar and low protein (Okeyo et al. 2020). Studies show that primary school learners are exposed to the influence of fast food and take-away establishments because of their aggressive marketing and easy accessibility (Scully et al. 2020). The statistics on childhood health in South Africa indicate a progressive increase in the number of obese children (Nwosu et al. 2022). Could this be because of poor dietary habits? Do dietary habits affect the nutritional status of learners? The aim of this study was to assess the dietary habits of learners in public primary schools in the Tshwane West District of the Gauteng province in South Africa. The hypothesis of the study was that poor dietary habits were being practised by learners attending public primary schools in the Tshwane West District of Gauteng, South Africa.
Research methods and designStudy design and setting
The authors used a quantitative approach and a cross-sectional descriptive study design to address the question: What are the dietary habits of primary school learners in 10 public primary schools in the Tshwane West District of Gauteng, South Africa? Data were collected at schools during breaks or life orientation periods for 4 months (March 2021–June 2021). School principals provided conducive areas for data collection. The multistage sampling technique was applied to sample 814 learners from 10 primary schools in the Tshwane West District. Primary schools were stratified according to socioeconomic status (SES), namely low SES, middle SES and high SES (affluent), to resemble the entire population. Two schools were randomly selected from each SES to participate in the study. Morgan and Krejcie’s sample size table was used to determine a suitable sample size, using the following formula (see Equation 1):
n=X2NP(1−P)d2(N−1)+X2P(1−P)
Where:
N = population size
X2 = table value of Chi-square at 95% CI
P = population proportion (0.50)
d = degree of accuracy.
Here, the minimum sample size was 359. The authors included 814 learners so that internal and external validity could be better determined. It was possible to increase the sample size because most of the learners managed to bring back the parental consent forms.
Study population and sampling
A total of 814 learners (boys = 360; girls = 454) from grades 4 to 7 participated in the study. The authors used the stratified random sampling technique to select the schools. Simple random sampling was used to select participants from 10 primary schools. The eligibility criteria included participants who were in grades 4 to 7 and whose parents had signed an informed consent and learners signed assent forms. Exclusion criteria were learners whose parents or guardians did not sign parental consent forms.
Data collection
Data were collected by the researcher and research assistants between March and June 2021. The school principals provided suitable spaces for data collection. The questionnaire was written in English and translated to Setswana, which is the home language of most primary school learners in the Tshwane West District of Gauteng. The questionnaire included sociodemographic data as well as questions about the food consumed by learners at home and at school. The development of questions was guided by the South African Food-Based Dietary Guidelines (SAFBDGs). After completing the questionnaire, the learners’ anthropometric (weight and height) measurements were taken.
Data analysis
Data were analysed using the statistical software package Stata version 17. AnthroPlus software was used to calculate and classify body mass index (BMI) for age, height for age (low height for age indicates stunting) and weight for age (low weight for age indicates underweight). Descriptive statistics were analysed using frequency distribution, standard deviation (s.d.) and mean. Logistic regression was applied to analyse the sociodemographic factors associated with BMI for age, height for age (stunting) and weight for age (wasting). The p-values less than 0.05 indicated the association.
Ethical considerations
The study was conducted in accordance with the Declaration of Helsinki and approved by the Turfloop Review Board (TREC/343/2019:PG). The permission to conduct this study was sought and granted from the National Department of Basic Education (DBE). The learners were provided with a participants’ information leaflet to give their parents and guardians. It was explaining the purpose, aims and objectives of the study. The parents or guardians of the participants gave their written consent, and the participating learners gave their assent. Learners were informed that they had the right to withdraw from the study without being penalised. Privacy and confidentiality were maintained.
ResultsSociodemographic profile of participants
Table 1 indicates the sociodemographic characteristics of the learners, the majority of whom were girls (55.8%). There was an almost equal number of learners under 11 years (49%) and older than 11 years (51%), with mean = 11.3 and s.d. = 1.4 years. Nearly a third of the learners were in grade 7 (30.2%). More than half of the learners resided in formal urban areas (56.8%), while 42.4% resided in peri-urban areas. Close to half (45.8%) of the learners carried lunch boxes to school. More than half (52.3%) of the learners received meals from the feeding programmes at their schools.
Sociodemographic characteristics of the participants (N = 814).
Sociodemographic characteristics
n
%
Gender
Boy
360
55.8
Girl
454
44.2
Age (years)
< 11
399
49.0
> 11
415
51.0
Urban type of residence
Peri-urban
352
43.2
Formal urban
462
56.8
A learner stays with
Parents
605
74.3
Other family members
209
25.7
Learner carries lunchbox to school
Yes
441
45.8
No
373
54.2
Learner eats from the school feeding programme
Yes
426
52.3
No
388
47.7
Table 2 indicates that the majority (70%) of the learners had normal weight, 15.1% were overweight and 11.3% were obese. It also shows that 46.4% of the learners had normal height while 45.6% were at risk of stunting. However, 3.4% of learners were in the stunting category.
Body mass index and height based on age- and gender-specific cutoff points.
BMI
%
Height
%
Obese
11.3
Severely stunted
0.5
Overweight
15.1
Moderately stunted
2.9
Normal weight
70.0
Risk of stunting
45.6
Moderate underweight
3.1
Normal height
46.4
Severe underweight
0.5
Tall
3.8
-
-
Very tall
0.7
BMI, body mass index.
Table 3 shows that the majority (78.9%) of the learners ate breakfast and half (49.9%) of these ate breakfast every day. Nearly half (48.8%) of the learners ate cereal in the morning. For those learners who skipped breakfast, a lack of time was the main reason (36.8%). The majority (77.4%) of the learners bought food or snacks at school, and almost half (45.6%) bought food from street vendors. The majority (68.1%) of the learners bought food or snacks at school during break and only a few (23.6%) bought them every school day. Less than half (39.4%) of the learners carried pocket money every school day.
The frequency distribution of eating breakfast and carrying pocket money.
Variables
n
%
Eat breakfast before going to school (n = 814)
No
172
21.1
Yes
642
78.9
Breakfast food (n = 642)
Cereal
313
48.8
Bread
181
28.2
Soft porridge
127
19.7
Others
21
3.3
Frequency of eating breakfast (n = 642)
School days
65
10.1
Everyday
320
49.9
Sometimes
257
40.0
Reason for not eating breakfast daily (n = 494)
Lack time
182
36.8
No reason stated
95
19.2
Not hungry
109
22.0
No food
108
21.9
The child buys food at school (n = 814)
No
184
22.6
Yes
630
77.4
Outlet where the learner buys at school (n = 630)
School tuckshop
180
28.6
Street vendor
287
45.6
Street vendor and tuckshop
163
25.9
Carry pocket money (n = 814)
No
184
22.6
Yes
630
77.4
Table 4 shows that almost all learners (98.9%) were consuming fruits, with the majority (86.2%) consuming less than four fruits daily. Most learners never ate fruits (64.5%) or vegetables (47.2%) because they were not available. Most of the learners (95%) consumed vegetables, with most (87.4%) consuming less than four vegetables per day, and over a third (34.9%) of the learners consumed vegetables every day.
The frequency distribution of fruits and vegetables consumption.
Variables
n
%
Eat fruits (n = 814)
No
9
1.1
Yes
805
98.9
Number of fruits eaten daily (n = 805)
Less than four
694
86.2
More than four
111
13.8
Frequency of eating fruits (n = 805)
Daily
278
34.5
Weekends
59
7.3
Sometimes
468
58.1
Reasons for not eating fruits daily (n = 536)
Not available
348
64.9
Expensive
50
9.3
Dislike fruits
60
11.2
Not necessary
11
2.0
No reason
67
12.5
Eat vegetables (n = 814)
No
41
5.0
Yes
773
95.0
Number of vegetables eaten daily (n = 773)
Less than four
676
87.4
More than four
97
12.5
Frequency of eating vegetables (n = 773)
Daily
270
34.9
Weekends
162
20.9
Sometimes
341
44.1
Reasons for not eating vegetables daily (n = 544)
Not available
257
47.2
Expensive
45
8.3
Dislike
110
20.2
Not necessary
19
3.5
No reason
113
20.8
Sociodemographic and food habits associated with stunting
Bivariate logistic regression was used to determine the relationship between sociodemographic data, healthy eating knowledge and stunting status. Learners over 11 years were three times more likely to be stunted than those who were younger (OR: 2.8; 95% CI: 1.18–6.78; p = 0.019). Participating learners who consumed breakfast everyday had a lower prevalence of stunting than those who did not have breakfast before going to school (OR: 2.4; 95% CI: 1.06–5.59; p = 0.035). The rest of the factors did not show any association with stunting (Table 5). However, the rate of stunting in this cohort of children was low at 3.4%.
Factors associated with stunting.
Variable
Details
%
OR
95% CI
p
Gender
Girl
44.2
1.00
1.00
1.000
Boy
55.8
0.62
0.29–1.35
0.230
Age category (years)
< 11
49.0
1.00
1.00
1.000
> 11
51.0
2.80
1.18–6.78
0.019*
Eat breakfast
No
52.7
1.00
1.00
1.000
School days
7.7
1.50
0.32–7.24
0.590
Everyday
39.6
2.40
1.06–5.59
0.035*
School feeding programme
No
47.7
1.00
1.00
1.000
Yes
52.3
0.72
0.33–1.55
0.400
Taught healthy eating
No
10.9
1.00
1.00
1.000
Yes
89.1
1.55
0.36–6.67
0.550
Perform sports at school
No
50.9
1.00
1.00
1.000
Yes
49.1
0.81
0.38–1.73
0.590
Eat vegetables
No
6.4
-
-
-
Yes
93.6
0.50
0.14–1.70
0.270
Eat fruits
No
5.6
1.00
1.00
1.000
Yes
94.4
1.36
0.24–7.67
0.730
Play outside
No
58.2
1.00
1.00
1.000
Yes
41.8
1.30
0.6–2.81
0.500
Carry lunchbox
No
45.8
1.00
1.00
1.000
Yes
54.2
1.06
0.49–2.29
0.880
Note: *, Signifies significance @95% CI.
Sociodemographic and food habits associated with underweight and overweight Bivariate logistic regression was used to determine the relationship between sociodemographic data, healthy eating knowledge and underweight status. Learners who were taught about healthy eating habits were less likely to be underweight compared to those who were not taught (OR: 0.35; 95% CI: 0.14–0.85; p = 0.020). None of the other factors showed any association with underweight (Table 6). Similarly, no factors identified in this study showed any association with overweight.
Factors associated with underweight.
Variable
Details
%
OR
95% CI
p
Gender
Girl
44.2
1.00
1.00
1.000
Boy
55.8
1.23
0.57–2.67
0.590
Age category (years)
< 11
49.0
1.00
1.00
1.000
> 11
51.0
2.10
0.92–4.65
0.075
Eat breakfast often
No
52.7
1.00
1.00
1.000
School days
7.7
0.37
0.048–2.8
0.330
Everyday
39.6
0.27
0.29–1.40
0.310
School feeding programme
No
47.7
1.00
1.00
1.000
Yes
52.3
1.05
0.49–2.24
0.890
Taught healthy eating
No
10.9
1.00
1.00
1.000
Yes
89.1
0.35
0.14–0.85
0.020*
Perform sports at school
No
50.9
1.00
1.00
1.000
Yes
49.1
0.56
0.26–1.24
0.150
Eat vegetables
No
6.4
1.00
1.00
1.000
Yes
93.6
0.66
0.20–3.82
0.870
Eat fruits
No
5.6
1.00
1.00
1.000
Yes
94.4
1.64
0.22–12.34
0.630
Play outside
No
58.2
1.00
1.00
1.000
Yes
41.8
1.90
0.89–4.1
0.098
Carry lunch box
No
45.8
1.00
1.00
1.000
Yes
54.2
0.84
0.39–1.79
0.650
Note: *, Signifies significance @95% CI.
Discussion
The aim of this study was to determine the dietary habits and nutritional status of school learners. The rate of stunting was low (3.4%) and within the WHO recommended reference value ranges (WHO 2022). However, close to a quarter of the learners were overweight and obese, with the figures being above those reported in previous literature (Casari et al. 2022). This finding is not unique to Tshwane West or Gauteng. Studies conducted in other provinces in South Africa have reported similar findings (Negash et al. 2017; Otitoola et al. 2021). A systematic review and meta-analysis conducted in African countries, including Ghana, Tunisia, Uganda and Morocco, indicated an overall estimate of 9.5% – 11% of overweight and 4% – 6.9% obesity among learners (Ochola & Masibo 2014). These findings confirm that poor dietary habits negatively affect the nutritional status of learners.
Urbanisation is characterised by limited access to healthy foods, which is demonstrated by learners having easy access to nutrient-poor food such as bunny chows and deep-fried chips from tuckshops and street vendors (Garcia et al. 2018). It is not surprising that the current study found that primary school learners had poor eating habits. Other studies reported similar findings in South Africa, where poor eating habits were found in urban settings (Nkambule et al. 2019; Ochola & Masibo 2014). Global studies have yielded interesting results. Russia reported a high consumption of ultra-processed foods and confectionery among learners (Podchinenova et al. 2023). Learners in a study conducted in Saudi Arabia reported that they skipped meals, and only half of them ate breakfast daily. This is a public health concern because breakfast is considered an important meal of the day, providing energy to children for optimal performance of activities of daily living (Wijayanti et al. 2017). Skipping breakfast is associated with the development of obesity (Ma et al. 2020).
The current study revealed that approximately half of the learners carried pocket money to school and used it to buy unhealthy food from street vendors and tuckshop outlets. Previous studies conducted in South Africa indicated that more than 50% of schoolchildren carried pocket money and used it to buy unhealthy food from street vendors (Faber & Fonseca 2014). Several studies showed a significant association between pocket money and obesity, as learners tend to buy what is readily available and affordable, without considering the nutritional value of the items purchased (Güven & Öncü 2022).
The findings of the current study indicate that most of the foods purchased at the school tuckshop and street vendors were unhealthy food items, such as bunny chows, fried chips, fat cakes, cookies and sweets. Documented reasons for the purchase of unhealthy foods include the fact that children are influenced by the sweet taste, availability and affordability of these foods and snacks (Kigaru et al. 2015). The current study found a significant association between underweight and learning about healthy foods. Further studies are needed to investigate why food outlets around schools continue to sell unhealthy foods. Street vendors and tuckshop operators need to be educated about the sale of tasty, healthy snacks with a long shelf life. The researcher recommends that schools communicate the National School Nutrition Programme Guidelines for Tuck Shop Operators and monitor the goods sold by street vendors and tuckshop operators as stipulated in the DBE policy.
Although most learners in the current study reportedly consumed fruits and vegetables every day, the portions were less than four per day. This consumption rate did not meet the recommendation of the SAFBDGs (Temple & Steyn 2013). The most cited reason they provided for not eating enough fruits and vegetables was their lack of availability. The lack of fruits and vegetables in the school feeding programme also deviates from the DBE guidelines, which stipulate that the school feeding programme should always provide at least one fruit to learners per day. For a long time, parents have struggled to force children to consume vegetables; in the current study, approximately 20% of learners reported that they dislike vegetables and therefore do not consume them daily. The researcher recommends that schools run campaigns like ‘bring your own vegetable to school’ to create a hype around healthy eating among learners.
In New Zealand and Spain, barriers to eating vegetables and fruits were recorded as follows: very expensive, no time to prepare vegetables and poor cooking skills compared to buying junk foods from food outlets (Karki et al. 2019). Studies have also shown that fast food marketing is aggressive, compared to a scant marketing of the benefits of consuming fruits and vegetables (Draper et al. 2019). Interestingly, most learners consumed fruits and vegetables, albeit not as frequently as they should. A low consumption of fruits and vegetables was recorded in Thailand and Kenya (Kigaru et al. 2015) despite evidence that the consumption of fruits and vegetables prevents cancer, cardiovascular disease, T2DM, obesity and adiposity among school-age children (Naudé 2013).
Study limitations
The study relied entirely on the self-reported food habits of learners. The reliability of the data may therefore be interpreted with caution, particularly when seeking the relationship between these food habits and nutritional status.
Conclusion and recommendations
Poor dietary habits are evident in this cohort of learners, which ultimately affect their nutritional status. The school environment plays an enormous role in exposing learners to poor dietary habits. Therefore, it is recommended that school nutrition programmes are implemented by dietitians. The DBE should collaborate with the Nutrition Directorate, universities, and Department of Agriculture, to craft a user-friendly nutritional programme that encourages healthy dietary practices.
Acknowledgements
The authors acknowledge the learners who participated in the study. They also would like to acknowledge parents and guardians of learners for giving parental consent and principals for granting permission for this study in their schools. This article is based on the author’s thesis entitled ‘Development and Implementation of Nutrition and exercise programme at primary schools in Tshwane West District, Gauteng, South Africa’ towards the degree of Doctor of Philosophy in Public Health in the Faculty of Health Sciences (School of Health Care Sciences) at the University of Limpopo with Supervisor Prof. L. Skaal & Co-supervisor Prof. T.M. Mothiba.
Competing interests
The authors declare that they have no financial or personal relationship(s) that may have inappropriately influenced them in writing this article.
Authors’ contributions
M.C.P. and L.S. contributed to conceptualisation and data curation; M.C.P. also contributed to the writing of original draft preparation, methodology, investigation, resources, software, project administration, funding acquisition, visualisation, and validation. M.C.P., L.S., and K.P.C. contributed to formal analysis, writing, reviewing, and editing: M.C.P., L.S., and K.P.C., supervision was done by L.S. and K.P.C. M.C.P., L.S., and K.P.C. have all read and agreed to the published version of the article.
Data availability
The data that support the findings of this study are available from the corresponding author, M.C.P. upon reasonable request.
Disclaimer
The views and opinions expressed in this article are those of the authors and are the product of professional research. It does not necessarily reflect the official policy or position of any affiliated institution, funder, agency or that of the publisher. The authors are responsible for this article’s results, findings and content.
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How to cite this article: Phetla, M.C., Skaal, L. & Chelule, K.P., 2024, ‘Dietary habits among primary school learners in the Tshwane West District of Gauteng, South Africa’, Health SA Gesondheid 29(0), a2746. https://doi.org/10.4102/hsag.v29i0.2746