Next Article in Journal
“It’s Not Healthy to Be Too Large”—A Qualitative Study Using Participatory Methods to Explore Children’s and Adolescents’ Perspectives on Obesity Treatment and Body Image
Previous Article in Journal
The Role of Appearance in Peer Interactions for Early Adolescent Cleft Lip and Palate Patients Post-Repair
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Children
Volume 12
Issue 10
10.3390/children12101352
children-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

A Combined Physical Activity and Multi-Micronutrient Supplementation Intervention in South African Primary Schools: Effects on Physical Activity, Fitness, and Cardiovascular Disease Risk Factors

by
Siphesihle Nqweniso
1,*,†,
Cheryl Walter
1,
Rosa du Randt
1,
Larissa Adams
1,
Johanna Beckmann
2,
Danielle Dolley
1,
Nandi Joubert
1,2,3,4,
Kurt Z. Long
3,4,
Ivan Müller
2,
Uwe Pühse
2,
Harald Seelig
2,
Peter Steinmann
3,4,
Jürg Utzinger
3,4,
Christin Lang
2 and
Markus Gerber
2
1
Department of Human Movement Science, Nelson Mandela University, Gqeberha 6031, South Africa
2
Department of Sport, Exercise and Health, University of Basel, CH-4052 Basel, Switzerland
3
Swiss Tropical and Public Health Institute, CH-4123 Allschwil, Switzerland
4
University of Basel, CH-4001 Basel, Switzerland
*
Author to whom correspondence should be addressed.
†
Current address: Department of Human Movement Science, University of Fort Hare, Alice 5700, South Africa.
Children 2025, 12(10), 1352; https://doi.org/10.3390/children12101352
Submission received: 4 August 2025 / Revised: 7 September 2025 / Accepted: 8 September 2025 / Published: 9 October 2025
(This article belongs to the Section Global Pediatric Health)
Versions Notes

Abstract

Highlights

What are the main findings?
  • School-based physical activity (PA) interventions, alone or combined with multi-micronutrient supplementation (MMNS), did not increase daily PA and showed mixed effects on cardiometabolic health in South African children aged 6–12 years.
  • The MMNS improved cardiorespiratory fitness (CRF) and reduced blood pressure but was linked to adverse metabolic changes (triglycerides and high-density lipo-protein).
What are the implications of the main finding?
  • Nutritional supplementation may hold potential for improving CRF and blood pressure in school-age children, though possible metabolic trade-offs require careful consideration.
  • PA interventions alone may be insufficient to change activity patterns in marginalised settings, highlighting the role of broader environmental and contextual barriers.

Abstract

Background/Objectives: Declining physical activity (PA) and cardiorespiratory fitness (CRF) in children are global public health concerns, particularly in populations experiencing urbanization and economic transition. This study investigated the effects of a school-based intervention on PA, CRF, and cardiovascular disease (CVD) risk factors in children aged 6–12 years from marginalized communities in Gqeberha, South Africa. Methods: A cluster randomized controlled trial was conducted in four schools, with participants randomly assigned to one of the following four arms: (i) PA and multi-micronutrient supplementation (MMNS); (ii) PA and placebo; (iii) MMNS; or (iv) placebo (control). A total of 1151 children were assessed at baseline (T1), 1003 at post-intervention (T2), and 549 at follow-up (T3). PA was measured using accelerometers. Secondary outcomes included CRF (20 m shuttle-run) and CVD risk factors (i.e., anthropometry, blood pressure, glycated hemoglobin [HbA1c], and lipid profile). Mixed linear models adjusted for baseline characteristics were used. Results: None of the interventions significantly improved daily PA. From T1 to T2, the MMNS arm significantly increased CRF, while PA + MMNS reduced HbA1c. However, MMNS alone increased triglycerides, and PA + placebo increased low-density lipoprotein (LDL). From post-intervention (T2) to follow-up (T3), the MMNS arms significantly reduced blood pressure. Yet, the PA + MMNS arm increased body fat percentage and decreased high-density lipoprotein (HDL). Conclusions: While MMNS showed promise for improving fitness and blood pressure and PA + MMNS reduced HbA1c, adverse metabolic changes emerged. The results should be interpreted with caution due to the short intervention span and COVID-19 disruptions during the second year of the intervention.

1. Introduction

Physical activity (PA) and cardiorespiratory fitness (CRF) levels are declining rapidly among children and adolescents [1], with significant implications for both short- and long-term health [2]. In parallel, cardiovascular diseases (CVDs) are on the rise, particularly in low- and middle-income countries (LMICs) undergoing rapid urbanization and economic transition [3]. Since PA is an independent risk factor for CVD [4], and early-life risk factors often track into adulthood [5], these trends indicate the emergence of a public health crisis in LMICs [2,6].
Childhood PA is a critical determinant of both childhood fitness and adult cardiovascular health [7]. Schools represent an optimal and often cost-effective setting for promoting PA as a component of a healthy lifestyle [8,9]. Compulsory physical education in schools ensures that all children, including those who are typically less active, overweight, or unfit and may not engage in voluntary sports, have opportunities for physical engagement. In South Africa, despite physical education being part of the school curriculum, its implementation is often inadequate, particularly in historically marginalized communities [10,11]. In these settings, physical education is often not prioritized compared to academic subjects and faces significant challenges such as insufficient funding, limited physical resources and equipment, and a scarcity of qualified physical education teachers for the large class sizes [12]. The low quality of physical education implementation in low-resourced schools places children at a higher risk of suffering the consequences associated with low PA, including overweight/obesity, low physical fitness, and compromised cardiovascular health extending into adulthood [7,13,14].
Despite improvements in PA levels reported in the 2022 Healthy Active Kids South Africa (HAKSA) report card, from 48–52% in 2018 to 60–73% children meeting PA recommendations, these figures may be overly optimistic due to the lack of nationally representative data [15]. The COVID-19 pandemic further constrained PA opportunities due to the strict lockdown measures implemented in South Africa, which adversely affected children’s opportunities to meet PA recommendations [16]. The World Health Organization (WHO) noted that the pandemic exacerbated inequalities in access and opportunities for being physically active, especially in resource-constrained communities with poor infrastructure and unsafe public spaces [17]. Nevertheless, the importance of interventions promoting PA, especially in marginalized communities has been emphasized [15], with research supporting the potential of school-based interventions to improve PA and fitness in youth [1,8,18].
While previous school-based health interventions have focused on fitness [19], body composition [20], and CVD risk profiles [21,22], most were conducted in high-income countries. South African studies have incorporated combinations of PA and nutrition [23,24,25], and some have included PA, nutrition, and hygiene [26]. The role of micronutrients in enhancing physical performance was demonstrated in a study including adult men [27], and benefits have also been observed in school-age children. For instance, in South Africa, 5–11-year-old children with mild iron and zinc deficiency from low-socioeconomic areas receiving a micronutrient powder added to a daily portion of maize porridge increased their weight-for-age, serum ferritin, and iron levels compared to the control group [28]. Healthy 7–10-year-old children from middle-socioeconomic areas in India improved aerobic capacity and endurance after receiving fortified choco-malt beverage powder [29]. In Brazil, a reduction in total cholesterol, LDL cholesterol, and glucose was reported in children aged 9–13 years after taking 2–3 micronutrient bars (Nestrovit™) for 6 weeks, suggesting micronutrients play a role in reducing CVD risk factors [30].
Yet, few studies have investigated the combined effects of PA and multi-micronutrient supplementation (MMNS) in South African schoolchildren. Multi-component health interventions are increasingly recognized as more effective in LMICs due to the dual burden of disease [31].
Owing to the paucity of evidence but considerable potential of school-based health interventions, this paper addressed this evidence gap by conducting a cluster-randomized trial which included a PA and MMNS interventions in primary schoolchildren from marginalized communities in Gqeberha, South Africa. The first aim was to assess the effectiveness of these interventions (alone or in combination) on schoolchildren’s daily moderate-to-vigorous physical activity (MVPA) levels. The second aim was to assess the effect of the interventions on CRF (VO2max) and CVD risk factors (blood pressure, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), etc.).

2. Materials and Methods

2.1. Study Design

The study was designed as a double-blind, cluster-randomized controlled trial that took place in four schools from marginalized peri-urban communities in Gqeberha, Eastern Cape, South Africa. The study forms part of a larger study (KaziAfya) that aimed to examine the effects of a school-based health intervention (PA, MMNS, or both interventions combined) on growth, health, and well-being in schoolchildren from three African countries; South Africa, Tanzania, and Côte d’Ivoire [32]. The study was registered with the International Standard Randomized Controlled Trial Number (ISRCTN), registry (ISRCTN29534081). The current study is based on data collected from South Africa, with data assessed at three time-points; baseline T1 (February–April 2019), T2 (September–November 2019), and T3 (August–November 2021).

2.2. Participants and Sampling

Children aged 6–12 years from four primary schools (41 classes) were invited to participate in the study. All schools were selected from quintile 3 schools in Gqeberha, with quintile 1 schools representing the “poorest” quintile and quintile 5 schools representing the “least poor”. Quintile 3 schools are the lowest ranking quintile schools in the area. Children were eligible for inclusion if they were between the ages of 6 and 12 years, in grades 1 to 4, provided written informed consent from parents/guardians, not participating in any other clinical trial or nutrition, and not suffering from any clinical condition preventing participation in physical education or absorption of the supplement, as determined by medical personnel. For sample size calculation, a total sample of 1096 children were needed as indicated by power calculations (calculations based on G*power 3.1: alpha error probability = 0.05, power = 0.80, number of groups = 12, number of measurements = 3) [32]. Based on a priori power analysis, in each country, the final target sample was increased to 1320 children, assuming a yearly dropout rate of 10%, with 330 children allocated to each of the intervention arms.
Four schools were randomly selected, and following baseline assessment, intervention and control classes were randomly allocated to one of four intervention arms using a computer-generated randomization code. The intervention arms were the following: (i) PA and MMNS; (ii) PA and placebo; (iii) MMNS only; and (iv) placebo, which served as the control group (Table 1).

2.3. Randomization to Intervention Arms

To ensure double-blinding, intervention arm randomization was conducted by the project coordinator (C.L.), who was not otherwise involved in recruitment or data collection, while the local coordinator (S.N.) remained blind to MMNS group allocation. As depicted in Table 1, children were randomly allocated by class to one of the four intervention arms via stratification to ensure equal representation at each school across the grade levels.
Children in the PA arms received the KaziKidz toolkit, which aligns with South Africa’s Curriculum Assessment Policy Statements (CAPS) [33] (see https://www.kazibantu.org/kazikidz/, accessed on 22 July 2025). This teaching and learning toolkit was developed in accordance with the criteria and guidelines of two key UNESCO programs, namely, the Quality Physical Education (QPE) (https://www.unesco.org/en/quality-physical-education, accessed on 22 July 2025) and the Fit4Life Program (https://www.unesco.org/en/fit4life, accessed on 22 July 2025), and this is freely available and downloadable.
The PA intervention comprised five components. First, teachers received training on quality physical education and use of the KaziKidz toolkit. Second, a Human Movement Science graduate was assigned as a physical education coach to each school to support lesson implementation during the first intervention year; teachers were expected to continue the regimen independently in the second intervention year. However, due to COVID-19-related school closures from March to July 2020, the second year of the intervention could not be implemented as planned. Third, the intervention included one 45 min physical education lesson and one 45 min moving-to-music session per week, plus daily in-class activity breaks. Fourth, schools were provided with basic sports equipment (e.g., skipping ropes, balls, cones, and bean bags) and playground painted games to promote active play. Fifth, teachers received KaziKidz materials, including 32 lessons for both physical education and moving-to-music per grade.
Children in the MMNS arm received a daily chewable tablet based on the MixMe™ powder sprinkle provided by DSM Nutritional Products South Africa (Johannesburg, South Africa), administered by class teachers on school days. Details of the composition of the supplement are provided as a Supplemental File (Supplemental Table S1). Children in the PA + placebo and control groups received placebo tablets identical to the MMNS in taste, color, and packaging, ensuring the blinding of participants, teachers, and researchers. All children diagnosed with helminth infections were dewormed with a single 500 mg oral dose of mebendazole prior to the intervention, in line with WHO guidelines [34].
The intervention was intended to span two academic years. Following baseline (T1) assessments (February–April 2019), the first intervention lasted 12 weeks (2 × 45 min lessons per week), interrupted only by school holidays. Post-intervention (T2) data collection occurred from September to November 2019. The second intervention commenced in February 2020 but was halted in March due to COVID-19 lockdowns, which resulted in nationwide school closures on 18 March 2020. Although schools reopened in August 2020, restrictions prevented the continuation of physical education lessons; however, the MMNS intervention resumed for 4 weeks (November–December 2020), with tablets administered 2–3 times per week. The final data collection (T3), initially planned for September–November 2020, was delayed to August 2021. The MMNS intervention continued from February–September 2021 (22 weeks), interrupted only by school holidays. Thus, the first intervention year was implemented as planned, while the second year included only the MMNS arm, extended over a longer period.

2.4. Measures

A detailed description of the study methodology has been published in the study protocol [32]. A total of 1151 children were assessed at baseline, 1003 during T2, and 549 at T3. Data were assessed identically at each of the three time-points. At baseline, demographic information (age and sex) was obtained from the school register for all participants. Anthropometric and blood pressure measurements were performed by trained personnel, and nurses collected blood samples using capillary sampling after overnight fasting.

2.4.1. Socioeconomic Status

Socioeconomic status (SES) was assessed via a parental survey with questions related to items about asset ownership (e.g., number of bedrooms and people per household). Details about the items included and the scoring used to estimate SES have been previously described [35]. Principal component analysis was used to generate a wealth index, where items possessed by >95% or <5% of the sample were excluded, with the remaining items used to generate a wealth index score [36]. A high score reflected high SES; quintiles were built based on the wealth index, with quintiles 1 and 5 representing lowest/poorest and highest/wealthiest, respectively.

2.4.2. Anthropometric Measurements

Standing height was measured to the nearest 0.1 cm using a portable Seca stadiometer (Surgical SA; Johannesburg, South Africa), with each participant standing erect with their back against the stadiometer. Body composition and weight were measured by way of bioelectrical impedance analysis (BIA) with overnight fasting using a wireless scale (Tanita MC-580, Tanita Corp; Tokyo, Japan). In light clothing, participants stood on the scale making contact with the metal plates of the machine. Personal data, such as age, sex, and height, were entered into the scale and body weight was measured to the nearest 0.1 kg. Using the impedance and personal data, the scale estimated body fat % and body mass index (BMI), with readings displayed automatically on the Tanita scale. BMI z-scores were computed using Centers for Disease Control and Prevention (CDC)/WHO growth reference data [37].

2.4.3. Device-Based Physical Activity

PA was assessed using an accelerometer device (Actigraph wGT3x-BT; Shalimar, FL, USA) worn around the hip for 7 consecutive days. Children were instructed to continue their daily routine during these 7 days and not take the device off unless they are coming into contact with water. Data were collected in raw 30 Hz acceleration, with a sampling epoch of 15 s counts. Valid wear time was defined as ≥480 min/day accumulated between 6 a.m. and midnight, and children with data for ≥4 weekdays and ≥1 weekend day were included in the analyses. Cut-offs derived from Freedson et al. [38] were used to calculate time spent in MVPA, and data were processed using ActiLife software (version 6.13.4). The present study only included MVPA, expressed in minutes per day (min/day).

2.4.4. Cardiorespiratory Fitness

The 20 m shuttle run test was used to measure CRF. Children ran on a flat surface following a pre-recorded signal, where the initial running speed was set to 8.5 km/h, increasing by 0.5 km/h at each 1 min interval until maximal voluntary exhaustion. Children’s age and the speed at which they stopped running was used to estimate maximum oxygen update (VO2max) [39].

2.4.5. CVD Risk Factors

Full lipid profiles (total cholesterol, LDL-C, HDL-C, and triglycerides) and glycated hemoglobin (HbA1c) were analyzed using the point-of-care Alere Afinion AS100 analyser (Abbott Technologies; Abbott Park, IL, USA). Capillary blood sampling was used for the analysis. Blood pressure was measured using an Omron M3 automated blood pressure monitor (Omron Healthcare Europe; Hoofddorp, The Netherlands). Prior to the assessment, children were seated and resting for 5 min. Three measurements were taken with a 1 min interval between each measurement, and the mean of the last two measurements was used for the analyses.

2.5. Statistical Analyses

Descriptive characteristics, presented as means (M) and standard deviations (SD), were calculated to describe the sample by intervention group. Models were run for all children before and after adjusting for age, sex, and zBMI. The effect of time and association between exposure and outcome were analyzed using mixed linear models, including the random intercept of school classes to account for the cluster effect. Additionally, the mixed linear model was analyzed adjusting for baseline variables (age, sex, and zBMI), intervention groups, and using the placebo group as reference. Separate analyses were carried out from T1 to T2 and from T1 to T3 to account for the differences between the first- and second-year intervention phases due to the COVID-19 pandemic. We carried out separate analyses without and with intention-to-treat, using the last observation carried forward approach. The results of the intention-to-treat analyses are presented as supplemental files. All analyses were performed using SPSS version 26 for Windows (IBM Corporation; Armonk, NY, USA), and a p < 0.05 was considered statistically significant.

3. Results

3.1. Baseline Characteristics

A total of 1369 children aged 6–12 years from marginalized communities in Gqeberha, South Africa, were enrolled in the study. Of the enrolled participants, 65 dropped out prior to randomization. A total of 1304 children were randomized, based on school class, into one of the four intervention arms and assessed at baseline, with 153 children excluded from the analyses due to invalid PA data (main outcome). Valid data were available for the 1151 children (561 girls, 590 boys) who remained in the study, as depicted in the Consort flow diagram provided as a supplemental file (Supplemental Figure S1).
Participant characteristics are presented in Table 2. At baseline, there were significant differences regarding children’s age, height, and weight (p < 0.001) across the intervention groups, with children in the PA + placebo group having the highest mean for all three measures. There were no other significant group differences at baseline.
Table 3 presents descriptive statistics for the baseline outcome variables for the four intervention groups before and after controlling for age, sex, and zBMI. Estimated VO2max was significantly different across all four groups (p < 0.001), with the placebo group showing the highest mean. Baseline group differences were also observed for BMI and HbA1c, and these differences remained statistically significant even after controlling for age, sex, and zBMI (p = 0.001 and 0.017, respectively). Body fat % only revealed significant differences in the adjusted model (p = 0.036).

3.2. Dropout

Dropout analyses are presented in Supplemental Tables S2 and S3. Of the initial sample, 148 children (13%) dropped out between T1 and T2 and an additional 602 (52%) between T2 and T3. The majority of dropouts during the first intervention year were mainly due to school transfers and incomplete data. The high attrition in the second intervention year was largely attributed to COVID-19-related school closures and the subsequent non-return of many children after schools re-opened in August 2020. Contributing factors included parental concerns about infection risk, confusion due to rotational attendance schedules, and school dropout following the prolonged lockdown. High absenteeism during T3 further hindered follow-up assessments.
There were no significant differences in socio-demographic background at baseline between children who dropped out from T1 to T2 (p > 0.05) (Supplemental Table S2). Children who participated at T3 had significantly higher weight than children who dropped out between T1 and T3 (p = 0.048) (Supplemental Table S2). Supplemental Table S3 shows in detail the differences in outcome variables for children who did or did not drop out from T1 to T2 and from T1 to T3. Compared to children who dropped out from T1 to T2, children who participated in T2 had significantly lower MVPA and higher HbA1c (p = 0.016 and p = 0.011, respectively) before and after controlling for age, sex, and zBMI. Compared to children who dropped out from T1 to T3, those who participated at T3 had significantly lower MVPA, and higher BMI, body fat %, and diastolic blood pressure. These results remained significant after controlling for covariates for MVPA (p = 0.004) and diastolic blood pressure (p = 0.023) but not for BMI and body fat % (p > 0.05) (Supplemental Table S3).

3.3. First Intervention Year Effects on Outcome Variables (T1–T2)

Table 4 shows that none of the intervention arms had a significant effect on MVPA at T2. The MMNS intervention was associated with a significant increase in estimated VO2max and triglycerides after adjusting for baseline age, sex, and zBMI (p = 0.001 and p = 0.012, respectively). While the PA + placebo intervention was associated with a significant increase in LDL-C (p = 0.007). The combined intervention arm, PA + MMNS, significantly decreased HbA1c (p < 0.001).
Supplemental Table S4 shows separate analyses carried out with intention-to-treat. Similarly to the analyses without intention-to-treat (Table 4), we found no significant effects of the intervention arms on MVPA. Children in the MMNS group had significantly increased VO2max (p < 0.001), while those in the PA + placebo group had significantly decreased HDL-C (p = 0.043) and triglycerides (p = 0.042). The PA + MMNS intervention was associated with a significant decrease in HbA1c (p < 0.001).

3.4. Second Intervention Year Effects on Outcome Variables (T2–T3)

We found no significant effects of any of the intervention arms on MVPA and VO2max at T3. When predicting T3 scores, the PA + MMNS arm was associated with increased body fat % (p = 0.003) and decreased HDL-C (p = 0.003) (Table 5). While systolic and diastolic blood pressure decreased significantly among children receiving the MMNS (p < 0.001), there were no significant effects found for children in the PA + placebo intervention arm for any of the outcome variables compared to the placebo group (as reference).
Separate analyses were carried out with intention-to-treat from T1 to T3 and data are presented as a supplemental file (Supplemental Table S5). Again, there were no significant effects found for MVPA with children assigned to any of the intervention arms. The PA + placebo intervention arm was associated with decreased VO2max (p = 0.035). Compared to children assigned to the placebo group, peers in the PA + MMNS arm had increased body fat % (p = 0.004) at T3, while HDL-C significantly decreased in all intervention arms, PA + MMNS (p = 0.010), PA + placebo (p = 0.002), and MMNS intervention arms (p = 0.032).

4. Discussion

This study assessed the effectiveness of a combined school-based PA and MMNS intervention on South African schoolchildren’s MVPA, CRF, and CVD risk factors after one academic school year (T2) and after two academic years (T3). Findings of the study revealed that none of the intervention arms had a significant impact on MVPA levels. Yet, the PA + MMNS arm was effective in reducing HbA1c, while the MMNS arm significantly increased VO2max and reduced systolic and diastolic blood pressure. We also found that the PA + MMNS arm was associated with increased body fat % and decreased HDL-C, while the PA + placebo was associated with increased LDL-C and the MMNS arm resulted in increased triglycerides.
After the first-intervention period, we found no significant effect of any of the intervention arms on daily MVPA. Similar findings were reported in a 3-year intervention study among 6–7-year-old children from Copenhagen, Denmark [21]. The study involved doubling physical education lessons (from 90 to 180 min/week), presented twice a week; training physical education teachers; upgrading physical education and play facilities; and providing health education lessons on the importance of PA and healthy eating [21]. The authors attributed the non-significant effect on MVPA to the fact that children’s MVPA was already high at baseline in both the intervention (109–123 min/day) and control group (111–125 min/day) [21]. In the current study sample, children’s mean MVPA at baseline was 81 min/day (95 min/day and 69 min/day for boys and girls, respectively) [40] which is comparable to 6–8-year-olds (80 min/day) [14] but higher compared to 14–18-year-olds in South Africa (51 min/day) [41]. However, in a recent 9-month school-based intervention (120 min of PA per week) involving adolescents from Norway, time spent in MVPA decreased in both the intervention and control groups, but the reduction was significantly smaller in the intervention group (2 vs. 6 min/day) [19]. A decline in MVPA levels during adolescence is not surprising, as PA levels generally decrease from childhood to adolescence [42]. Although some interventions have reported minimal impact on MVPA and only produced small improvements in CRF [43], these findings highlight that these school-based approaches are a start, but they are possibly not enough to have a direct effect outside children’s school life.
We also found that the MMNS intervention was effective in increasing VO2max from T1–T2, highlighting that proper nutrition is important for reaching targeted health goals as micronutrient status is known to influence health and body composition [44,45]. These findings align with a 4-month multi-micronutrient intervention study in 7–10-year-old children from India, which found a 17% increase in VO2max in the intervention group receiving a fortified choco-malt beverage powder compared to a control group receiving an energy-equivalent unfortified choco-malt beverage powder, and another group receiving no intervention [29]. This is an important finding as CRF is known to track from childhood to adolescence and adulthood [46,47], and evidence has shown that compared to PA, CRF relates more strongly to CVD risk factors in children and adolescents [48].
Regarding CVD risk factors at T2, the MMNS intervention resulted in increased triglyceride levels from the low levels observed at baseline, suggesting that the MMNS may have negatively influenced lipid metabolism, thus increasing the risk of CVD. Previous studies investigating the effects of a school-based PA intervention found that MVPA predicts lower triglycerides in 10-year-old children after a 7-month intervention [13] and after 2 years [22]. However, in our study, the PA intervention on its own did not impact lipid levels; instead, we found increased triglyceride levels in children taking the MMNS. Other studies reported that a MMNS intervention has no impact on triglycerides [30]. The PA + MMNS intervention resulted in a significant decrease in HbA1c, suggesting that a combination of PA and supplementation influenced the risk of type 2 diabetes, while the PA + placebo arm resulted in increased LDL-C. A study investigating the impact of a MMNS on lipidemia in 9–13-year-olds from Brazil found that the supplement significantly reduced total cholesterol, LDL, and glucose [30]. The supplement, consumed as a bar (Nestrovit™), was taken 5 days per week and lasted for a 6-week period and contained vitamins A, E, C, B1, B2, B6, B12, D3, and B5, folate, niacin, biotin, calcium, phosphorus, iron, magnesium, and zinc [30]. The reduction in HbA1c levels in our study in the combined PA + MMNS intervention arm is supported by other studies that reported an association between PA and HbA1c [49] and that a MMNS intervention has potential to reduce HbA1c in children [30], therefore reducing the risk of type 2 diabetes. Although we found our intervention had a negative effect on triglycerides and LDL-C, MMNS have been found to have both short- and long-term benefits on lipid metabolism, thus reducing the risk of CVD in children [30].
After the second intervention year, which was interrupted by the COVID-19 pandemic, we found no significant effects on MVPA at T3 across the different intervention arms. A policy brief on PA and health in children and adolescents in Africa reported a significant decline in activity levels and increase in sedentary behavior due to the COVID-19 pandemic [16]. The closure of schools further denied many children the opportunities to be active, especially in communities where options for PA, sport, and recreation are inaccessible outside of schools [17]. Additionally, the Global Matrix 4.0 Surveillance Study found, among other environmental changes, that COVID-19 restrictions, such as school closures, were associated with an acute decline in opportunities for PA in school-age children [1]. The reduction in PA levels in school-age children has in turn led to biological changes, including reduced physical fitness and increased body fat [1].
Similarly to MVPA, after the interrupted second-year intervention we did not find any significant group differences for VO2max between the different intervention arms at T3. Improvements in CRF have been attributed to high intensity PA [7], but there were previous studies that were also unable to report significant improvements in children’s CRF [21,26,50]. However, other interventions have reported significant effects on CRF after 9-month [19], 1-year [18], and 2-year interventions [51]. The studies that did not report a significant impact on CRF attributed their results to insufficient minutes and days per week (180 min, two times a week) allocated to physical education [21] and the low intensity of the intervention [50]. The intervention in the study by Kolle et al. [19] consisted of an additional 120 min/week of PA on top of the compulsory 120 min/week physical education lessons, while Kriemler and colleagues found in their study on Swiss children that increasing physical education volume and intensity (225 min/week) improved CRF and overall PA [18]. Similar results were reported in a 2-year intervention study in Norway implementing MVPA for 300 min/week [51]. Even though the three latter studies were successful in increasing VO2max, it should be noted that the participants in these studies came from high-income countries and that data were collected before the COVID-19 pandemic and can therefore not be directly comparable to the children in the current study. Nevertheless, we are aware that school-based interventions are needed now more than before due to declining PA levels, taking into consideration that to improve children’s fitness levels, the frequency, intensity, and duration of the activity should be considered. In our study, the two 45 min lessons allocated for physical education and moving-to-music lessons included the time needed by children to change into gym clothes and organizing the class, which usually consists of 35–50 learners. Although the intervention was designed to engage children in two 45 min lessons of PA a week, time lost in class organization could have shortened this time, meaning the intervention dose was probably lower than the allocated time. The challenge of large class sizes in schools from historically marginalized communities in South Africa has been reported as a barrier to implementing quality physical education [12]. A review of school-based PA interventions suggested that longer duration interventions are needed to effect change in the rate and duration of PA and VO2max among children and adolescents aged 6–18 years [52].
Findings of the second-year intervention regarding CVD risk factors showed that the PA + MMNS intervention significantly increased body fat % and decreased HDL-C. It is important to note that only the MMNS was implemented during this intervention period due to the COVID-19 regulations in place. The negative impact of the intervention on body fat % and HDL-C is concerning as these risk factors are relevant in determining cardiovascular health in children and adolescents [47]. Previous studies have reported a reduction in fat mass after a PA intervention [53] and lower BMI and fat mass after a multivitamin and mineral supplement in obese adults [45], suggesting that a combination of PA + MMNS has the potential to reduce body mass and BMI when implemented in an optimal manner. Children participating in the MMNS intervention arm significantly decreased systolic and diastolic blood pressure. This decrease was observed at the 3-year follow-up, which is supported by previous studies where improvements in blood pressure following a PA intervention were reported [21,22]. To our knowledge, the effects of a MMNS intervention on blood pressure in children have not been previously reported. However, MMNS interventions during pregnancy have been widely implemented to reduce low birth weights and improve child growth and health outcomes [54]. A systematic review and meta-analysis examining follow-up data from studies in which pregnant women received MMNS (containing three or more micronutrients) compared to iron and folic acid alone found no evidence of lower blood pressure in their children at follow-up [55]. These findings highlight the need for further research on the potential impact of MMNS interventions, particularly when initiated during childhood, on blood pressure, given its importance as a cardiovascular risk marker.

5. Strengths and Limitations

The limitations of the study were the drop-out rate from T1 to T3, which is consistent with previous school-based intervention studies [19,21], although exacerbated by the COVID-19 pandemic. We found that the children who dropped out of the study had higher MVPA and lower BMI, body fat %, and diastolic blood pressure compared to children who participated in T3. We did not assess maturation in our participants aged 6–12 years, which we note as a limitation given that maturation influences CRF levels, especially among girls. Moreover, the COVID-19 pandemic and the closure of schools prevented the implementation of the full second-year intervention, especially in relation to the implementation of the PA component. We were, however, able to continue providing the MMNS from November to December 2020 and again from February to September 2021, but we could not ensure the implementation of physical education at the schools. We are also aware that micronutrient fortification is difficult for school administrators to implement sustainably after the project ends. This makes it even more important that our findings are incorporated into the fortification of normal and regular school meals by school food preparers.
Apart from the limitations identified, several strengths of this study can be noted. First, to our knowledge, this is one of the few studies to investigate the combined effects of PA and MMNS interventions among primary schoolchildren in marginalized communities in Gqeberha, South Africa. Previous studies focusing on MMNS have largely been conducted in high-income settings, making this study particularly novel in its context. Second, we used an objective measure of PA, which reduces bias and enhances the validity of the findings. Third, the study employed a cluster-randomized trial design, strengthening the reliability of the results and their potential applicability to school-based interventions. Finally, our findings contribute new evidence on the relationship between PA, CRF, cardiovascular health, and MMNS in resource-constrained settings, warranting further investigation and long-term follow-up studies.

6. Conclusions

Our results indicate that a 90 min/week PA intervention involving teacher training, physical education lessons, and equipment provision may be insufficient to improve daily MVPA, especially when children already achieve MVPA of more than 60 min/day. Increasing intervention frequency, intensity, and duration is needed to improve children’s PA levels, CRF, and cardiovascular health, as shown in previous studies. While we saw some significant effects (that point toward the potential benefits of a PA and/or MMNS intervention), the pattern was not clear and not always as expected. Implementing school-based interventions in marginalized communities remains challenging, and the COVID-19 pandemic further showed the limitations of using schools as intervention settings in times of a pandemic. The pandemic also highlighted the inequalities in access to PA, sport, and recreation needed to achieve PA recommendations. Alternative channels for health promotion are therefore necessary, especially in marginalized communities. Future studies should explore efficient ways for PA and/or MMNS interventions, given the promising results on the impact of the MMNS on CRF, blood sugar, and blood pressure.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/children12101352/s1, Supplemental Figure S1. Consort flow chart; Supplemental Table S1. Composition of the multi-micronutrient supplement; Supplemental Table S2. Differences in socio-demographic background between schoolchildren who did/did not drop out from (a) T1 to T2 and (b) T1 to T3; Supplemental Table S3. Differences in outcome variables between children who did/did not drop out from (a) T1 to T2 and (b) T1 to T3; Supplemental Table S4. Mixed linear model predicting T2 scores, after controlling for T1, age, sex, zBMI, and intervention group, with intention-to-treat; Supplemental Table S5. Mixed linear model predicting T3 scores, after controlling for T1, age, sex, zBMI, and intervention group, with intention-to-treat.

Author Contributions

Conceptualization: S.N., C.W., R.d.R. and M.G.; Methodology: S.N., C.W., R.d.R. and M.G.; validation and formal analysis: S.N. and M.G.; Investigation, resources, and data curation: S.N., L.A., J.B., D.D., N.J., I.M. and C.L.; Supervision, C.W., R.d.R. and M.G.; Project administration, S.N. and C.L.; Funding acquisition: C.W., K.Z.L., U.P., H.S., P.S., J.U. and M.G.; Writing—original draft preparation, S.N.; Writing—review and editing: S.N., C.W., R.d.R., L.A., J.B., D.D., N.J., K.Z.L., I.M., U.P., H.S., P.S., J.U., C.L. and M.G. All authors have read and agreed to the published version of the manuscript.

Funding

This research took place under the auspices of the UNESCO Chair on Physical Activity and Health in Educational Settings (https://unesco-chair.dsbg.unibas.ch/en/). This study was funded by the Fondation Botnar (Basel, Switzerland; project number 6071 ‘Physical activity and multi-micronutrient supplementation’), covering research expenses, staff salaries, study equipment, and laboratory analyses. The multi-micronutrient supplementation and the placebo products are sponsored by DSM Nutritional Products Ltd. (Basel, Switzerland). S.N. received funding from the Department of Research Development, Nelson Mandela University, and the German Academic Exchange Service-National Research Foundation, South Africa (DAAD-NRF), Grant UID 117629. The funders had no role in the study design, data collection, data analysis, data interpretation, preparation of the manuscript, or decision to publish. The corresponding author is responsible for the decision to submit this study for publication.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and ethics approval was obtained from the Human Research Ethics Committee at the Nelson Mandela University in Gqeberha, South Africa (reference number: H19-HEA-HMS-001, approval date 5 June 2019) and the ‘Ethikkommission Nordwest- und Zentralschweiz’ in Switzerland (EKNZ; reference number: Req-2018-00608, approval date 13 August 2018). In addition, permission to conduct research in primary schools was obtained from the Eastern Cape Department of Education and Department of Health, South Africa.

Informed Consent Statement

Written informed consent was obtained from the children’s parents/guardians after being given a detailed written and oral explanation of the aims of the study, procedure, possible harms, benefits, and the option to withdraw at any time. All children gave verbal assent before being assessed. Children’s participation was voluntary, and it was explained that withdrawal from the study was possible at any point without further obligation.

Data Availability Statement

All data relevant to the study are included in the article or as Supplementary Information. The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Acknowledgments

The authors are grateful to the school authorities, school staff, participating children, and their parents/guardians for providing consent and assent to participate in the study. Special thanks are extended to Zaahira Ismail for her administrative work and Sesethu Ncanywa for her contribution to data collection. We are also thankful and appreciative to all the postgraduate students from Switzerland who participated and dedicated their time to data collection and data entry.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of the data; in the writing of the manuscript; or in the decision to publish the results.

Abbreviations

The following abbreviations are used in this manuscript:
BMIBody mass index
zBMIBody mass index z-score
CAPSCurriculum and assessment policy statement
COVID-19Coronavirus disease 2019
CVDCardiovascular disease
Fit4LifeFit for Life Program of UNESCO
HAKSAHealthy active kids South Africa
HbA1cGlycated hemoglobin
HDLHigh-density lipoprotein cholesterol
LDL-CLow-density lipoprotein cholesterol
LMICsLow- and middle-income countries
MMeans
MVPAModerate-to-vigorous intensity physical activity
SDStandard deviation
SESSocioeconomic status
T1Baseline measurement
T2Follow-up measurement
T3End-line measurement
QPEQuality Physical Education Progamme of UNESCO
VO2maxMaximal oxygen uptake
WHOWorld Health Organization

References

  1. Aubert, S.; Barnes, J.D.; Demchenko, I.; Hawthorne, M.; Abdeta, C.; Abi Nader, P.; Adsuar Sala, J.C.; Aguilar-Farias, N.; Aznar, S.; Bakalár, P.; et al. Global Matrix 4.0 Physical Activity Report Card Grades for Children and Adolescents: Results and Analyses From 57 Countries. J. Phys. Act. Health 2022, 19, 700–728. [Google Scholar] [CrossRef] [PubMed]
  2. Reilly, J.J.; Aubert, S.; Brazo-Sayavera, J.; Liu, Y.; Cagas, J.Y.; Tremblay, M.S. Surveillance to improve physical activity of children and adolescents. Bull. World Health Organ. 2022, 100, 815. [Google Scholar] [CrossRef]
  3. Popkin, B.M.; Corvalan, C.; Grummer-Strawn, L.M. Dynamics of the double burden of malnutrition and the changing nutrition reality. Lancet 2020, 395, 65–74. [Google Scholar] [CrossRef]
  4. Andersen, L.B.; Sardinha, L.B.; Froberg, K.; Riddoch, C.J.; Page, A.S.; Anderssen, S.A. Fitness, fatness and clustering of cardiovascular risk factors in children from Denmark, Estonia and Portugal: The European Youth Heart Study. Int. J. Pediatr. Obes. 2008, 3 (Suppl. S1), 58–66. [Google Scholar] [CrossRef] [PubMed]
  5. Andersen, L.B.; Harro, M.; Sardinha, L.B.; Froberg, K.; Ekelund, U.; Brage, S.; Anderssen, S.A. Physical activity and clustered cardiovascular risk in children: A cross-sectional study (The European Youth Heart Study). Lancet 2006, 368, 299–304. [Google Scholar] [CrossRef]
  6. Guthold, R.; Stevens, G.A.; Riley, L.M.; Bull, F.C. Global trends in insufficient physical activity among adolescents: A pooled analysis of 298 population-based surveys with 1· 6 million participants. Lancet Child. Adolesc. Health 2020, 4, 23–35. [Google Scholar] [CrossRef] [PubMed]
  7. Rendo-Urteaga, T.; de Moraes, A.C.; Collese, T.S.; Manios, Y.; Hagströmer, M.; Sjöström, M.; Kafatos, A.; Widhalm, K.; Vanhelst, J.; Marcos, A.; et al. The combined effect of physical activity and sedentary behaviors on a clustered cardio-metabolic risk score: The Helena study. Int. J. Cardiol. 2015, 186, 186–195. [Google Scholar] [CrossRef]
  8. Demetriou, Y.; Höner, O. Physical activity interventions in the school setting: A systematic review. Psychol. Sport. Exerc. 2012, 13, 186–196. [Google Scholar] [CrossRef]
  9. CDC. School-based Programs to Increase Physical Activity. Available online: https://archive.cdc.gov/www_cdc_gov/policy/hi5/physicalactivity/index.html (accessed on 3 January 2024).
  10. Roux, K.C. The delivery of primary school physical education in South African public schools: The perceptions of educators. S. Afr. J. Child. Educ. 2020, 10, 1–10. [Google Scholar] [CrossRef]
  11. Stroebel, L. Opportunities for all? The impact of resources on the implementation of Physical Education in Free State schools. Afr. J. Phys. Act. Health Sci. (AJPHES) 2020, 26, 67–81. [Google Scholar] [CrossRef]
  12. Burnett, C. A national study on the state and status of physical education in South African public schools. Phys. Educ. Sport. Pedagog. 2021, 26, 179–196. [Google Scholar] [CrossRef]
  13. Skrede, T.; Stavnsbo, M.; Aadland, E.; Aadland, K.N.; Anderssen, S.A.; Resaland, G.K.; Ekelund, U. Moderate-to-vigorous physical activity, but not sedentary time, predicts changes in cardiometabolic risk factors in 10-y-old children: The Active Smarter Kids Study. Am. J. Clin. Nutr. 2017, 105, 1391–1398. [Google Scholar] [CrossRef]
  14. Sedumedi, C.M.; Janssen, X.; Reilly, J.J.; Kruger, H.S.; Monyeki, M.A. Association between Objectively Determined Physical Activity Levels and Body Composition in 6-8-Year-Old Children from a Black South African Population: BC-IT Study. Int. J. Environ. Res. Public Health 2021, 18, 6453. [Google Scholar] [CrossRef]
  15. Nyawose, Z.Z.; Naidoo, R.; Christie, C.; Bassett, S.; Coetzee, D.; Van Gent, M.; Monyeki, A.; Gradidge, P.; van Rensburg, C.J.; Cozett, C. Results From South Africa’s 2022 Healthy Active Kids’ Report Card on Physical Activity, Body Composition Proxies, and Nutritional Status in Children and Adolescents. J. Phys. Act. Health 2024, 21, 861–871. [Google Scholar] [CrossRef]
  16. Naidoo, R.; Chetty, V.; Draper, C.; Cook, C.; Wadende, P.; Alaba, O.; Buck, R.; Smith, B.; Sissing, N.; Lambert, E. Policy Brief: Physical Activity for Health in Children and Adolescents in Africa: COVID-19 and Beyond-Home, School and Communities. Available online: https://www.sasma.org.za/wp-content/uploads/2020/10/Policy-Brief-Physical-activity-for-children-during-COVID-19-WEB2.pdf (accessed on 17 November 2022).
  17. WHO. Global Status Report on Physical Activity 2022. Available online: https://www.who.int/teams/health-promotion/physical-activity/global-status-report-on-physical-activity-2022 (accessed on 9 January 2023).
  18. Kriemler, S.; Zahner, L.; Schindler, C.; Meyer, U.; Hartmann, T.; Hebestreit, H.; Brunner-La Rocca, H.; van Mechelen, W.; Puder, J. Effect of school based physical activity programme (KISS) on fitness and adiposity in primary schoolchildren: Cluster randomised controlled trial. BMJ 2010, 340, c785–c792. [Google Scholar] [CrossRef] [PubMed]
  19. Kolle, E.; Solberg, R.B.; Säfvenbom, R.; Dyrstad, S.M.; Berntsen, S.; Resaland, G.K.; Ekelund, U.; Anderssen, S.A.; Steene-Johannessen, J.; Grydeland, M. The effect of a school-based intervention on physical activity, cardiorespiratory fitness and muscle strength: The School in Motion cluster randomized trial. Int. J. Behav. Nutr. Phys. Act. 2020, 17, 154. [Google Scholar] [CrossRef] [PubMed]
  20. Li, X.-H.; Lin, S.; Guo, H.; Huang, Y.; Wu, L.; Zhang, Z.; Ma, J.; Wang, H.-J. Effectiveness of a school-based physical activity intervention on obesity in school children: A nonrandomized controlled trial. BMC Public Health 2014, 14, 1282. [Google Scholar] [CrossRef]
  21. Bugge, A.; El-Naaman, B.; Dencker, M.; Froberg, K.; Holme, I.M.; McMurray, R.G.; Andersen, L.B. Effects of a three-year intervention: The Copenhagen School Child Intervention Study. Med. Sci. Sports Exerc. 2012, 44, 1310–1317. [Google Scholar] [CrossRef]
  22. Resaland, G.K.; Aadland, E.; Nilsen, A.K.O.; Bartholomew, J.B.; Andersen, L.B.; Anderssen, S.A. The effect of a two-year school-based daily physical activity intervention on a clustered CVD risk factor score-The Sogndal school-intervention study. Scand. J. Med. Sci. Sports 2018, 28, 1027–1035. [Google Scholar] [CrossRef]
  23. Naidoo, R.; Coopoo, Y.; Lambert, E.; Draper, C. Impact of a primary school-based nutrition and physical activity intervention on learners in KwaZulu-Natal, South Africa: A pilot study. S. Afr. J. Sports Med. 2009, 21, 7–12. [Google Scholar] [CrossRef]
  24. Draper, C.; de Villiers, A.; Lambert, E.; Fourie, J.; Hill, J.; Dalais, L.; Abrahams, Z.; Steyn, N. HealthKick: A nutrition and physical activity intervention for primary schools in low-income settings. BMC Public Health 2010, 10, 398–409. [Google Scholar] [CrossRef]
  25. Jacobs, K.; Mash, B. Evaluation of a school-based nutrition and physical activity programme for Grade 4 learners in the Western Cape province. S. Afr. Fam. Pract. 2013, 55, 391–397. [Google Scholar] [CrossRef]
  26. Müller, I.; Schindler, C.; Adams, L.; Endes, K.; Gall, S.; Gerber, M.; Htun, N.S.N.; Nqweniso, S.; Joubert, N.; Probst-Hensch, N.; et al. Effect of a Multidimensional Physical Activity Intervention on Body Mass Index, Skinfolds and Fitness in South African Children: Results from a Cluster-Randomised Controlled Trial. Int. J. Environ. Res. Public Health 2019, 16, 232. [Google Scholar] [CrossRef]
  27. van der Beek, E.J.; van Dokkum, W.; Wedel, M.; Schrijver, J.; van den Berg, H. Thiamin, riboflavin and vitamin B6: Impact of restricted intake on physical performance in man. J. Am. Coll. Nutr. 1994, 13, 629–640. [Google Scholar] [CrossRef]
  28. Troesch, B.; van Stuijvenberg, M.E.; Smuts, C.M.; Kruger, H.S.; Biebinger, R.; Hurrell, R.F.; Baumgartner, J.; Zimmermann, M.B. A micronutrient powder with low doses of highly absorbable iron and zinc reduces iron and zinc deficiency and improves weight-for-age Z-scores in South African children. J. Nutr. 2011, 141, 237–242. [Google Scholar] [CrossRef] [PubMed]
  29. Vaz, M.; Pauline, M.; Unni, U.S.; Parikh, P.; Thomas, T.; Bharathi, A.V.; Avadhany, S.; Muthayya, S.; Mehra, R.; Kurpad, A.V. Micronutrient supplementation improves physical performance measures in Asian Indian school-age children. J. Nutr. 2011, 141, 2017–2023. [Google Scholar] [CrossRef] [PubMed]
  30. Chakrabarti, A.; Eiden, M.; Morin-Rivron, D.; Christinat, N.; Monteiro, J.P.; Kaput, J.; Masoodi, M. Impact of multi-micronutrient supplementation on lipidemia of children and adolescents. Clin. Nutr. 2020, 39, 2211–2219. [Google Scholar] [CrossRef] [PubMed]
  31. Mukamana, O.; Johri, M. What is known about school-based interventions for health promotion and their impact in developing countries? A scoping review of the literature. Health Educ. Res. 2016, 31, 587–602. [Google Scholar] [CrossRef]
  32. Gerber, M.; Ayekoé, S.A.; Beckmann, J.; Bonfoh, B.; Coulibaly, J.T.; Daouda, D.; du Randt, R.; Finda, L.; Gall, S.; Mollel, G.J. Effects of school-based physical activity and multi-micronutrient supplementation intervention on growth, health and well-being of schoolchildren in three African countries: The KaziAfya cluster randomised controlled trial protocol with a 2 × 2 factorial design. Trials 2020, 21, 22. [Google Scholar] [CrossRef]
  33. South African Department of Basic Education. Curriculum and Assessment Policy Statement (CAPS): Life Skills Intermediate Phase Grades 4–6; Department of Basic Education: Pretoria, South Africa, 2011. [Google Scholar]
  34. WHO. Helminth Control in School-Age Children: A Guide for Managers of Control Programmes. Available online: https://apps.who.int/iris/handle/10665/44671 (accessed on 15 November 2021).
  35. Gerber, M.; Lang, C.; Beckmann, J.; Degen, J.; du Randt, R.; Gall, S.; Long, K.Z.; Müller, I.; Nienaber, M.; Steinmann, P.; et al. Associations Between Household Socioeconomic Status, Car Ownership, Physical Activity, and Cardiorespiratory Fitness in South African Primary Schoolchildren Living in Marginalized Communities. J. Phys. Act. Health 2021, 18, 883–894. [Google Scholar] [CrossRef]
  36. Filmer, D.; Pritchett, L.H. Estimating wealth effects without expenditure data—Or tears: An application to educational enrollments in states of India. Demography 2001, 38, 115–132. [Google Scholar] [CrossRef]
  37. Ogden, C.L.; Flegal, K.M.; Carroll, M.D.; Johnson, C.L. Prevalence and trends in overweight among US children and adolescents, 1999–2000. JAMA 2002, 288, 1728–1732. [Google Scholar] [CrossRef]
  38. Freedson, P.S.; Melanson, E.; Sirard, J. Calibration of the Computer Science and Applications, Inc. accelerometer. Med. Sci. Sports Exerc. 1998, 30, 777–781. [Google Scholar] [CrossRef] [PubMed]
  39. Léger, L.A.; Mercier, D.; Gadoury, C.; Lambert, J. The multistage 20 metre shuttle run test for aerobic fitness. J. Sports Sci. 1988, 6, 93–101. [Google Scholar] [CrossRef]
  40. Nqweniso, S.; Walter, C.; du Randt, R.; Adams, L.; Beckmann, J.; Degen, J.; Gall, S.; Joubert, N.; Lang, C.; Long, K.Z.; et al. Physical Activity, Cardiorespiratory Fitness and Clustered Cardiovascular Risk in South African Primary Schoolchildren from Disadvantaged Communities: A Cross-Sectional Study. Int. J. Environ. Res. Public Health 2021, 18, 2080. [Google Scholar] [CrossRef] [PubMed]
  41. Wushe, S.N.; Moss, S.J.; Monyeki, M.A. Objectively determined habitual physical activity in South African adolescents: The PAHL study. BMC Public Health 2014, 14, 471. [Google Scholar] [CrossRef]
  42. Hanson, S.K.; Munthali, R.J.; Micklesfield, L.K.; Lobelo, F.; Cunningham, S.A.; Hartman, T.J.; Norris, S.A.; Stein, A.D. Longitudinal patterns of physical activity, sedentary behavior and sleep in urban South African adolescents, Birth-To-Twenty Plus cohort. BMC Pediatr. 2019, 19, 241. [Google Scholar] [CrossRef] [PubMed]
  43. Hartwig, T.B.; Sanders, T.; Vasconcellos, D.; Noetel, M.; Parker, P.D.; Lubans, D.R.; Andrade, S.; Ávila-García, M.; Bartholomew, J.; Belton, S.; et al. School-based interventions modestly increase physical activity and cardiorespiratory fitness but are least effective for youth who need them most: An individual participant pooled analysis of 20 controlled trials. Br. J. Sports Med. 2021, 55, 721–729. [Google Scholar] [CrossRef]
  44. García, O.P.; Long, K.Z.; Rosado, J.L. Impact of micronutrient deficiencies on obesity. Nutr. Rev. 2009, 67, 559–572. [Google Scholar] [CrossRef]
  45. Li, Y.; Wang, C.; Zhu, K.; Feng, R.N.; Sun, C.H. Effects of multivitamin and mineral supplementation on adiposity, energy expenditure and lipid profiles in obese Chinese women. Int. J. Obes. (Lond.) 2010, 34, 1070–1077. [Google Scholar] [CrossRef]
  46. Bugge, A.; El-Naaman, B.; McMurray, R.G.; Froberg, K.; Andersen, L.B. Tracking of clustered cardiovascular disease risk factors from childhood to adolescence. Pediatr. Res. 2013, 73, 245–249. [Google Scholar] [CrossRef] [PubMed]
  47. Ruiz, J.R.; Cavero-Redondo, I.; Ortega, F.B.; Welk, G.J.; Andersen, L.B.; Martinez-Vizcaino, V. Cardiorespiratory fitness cut points to avoid cardiovascular disease risk in children and adolescents; what level of fitness should raise a red flag? A systematic review and meta-analysis. Br. J. Sports Med. 2016, 50, 1451–1458. [Google Scholar] [CrossRef]
  48. Hurtig-Wennlöf, A.; Ruiz, J.R.; Harro, M.; Sjöström, M. Cardiorespiratory fitness relates more strongly than physical activity to cardiovascular disease risk factors in healthy children and adolescents: The European Youth Heart Study. Eur. J. Cardiovasc. Prev. Rehabil. 2007, 14, 575–581. [Google Scholar] [CrossRef]
  49. O’Donovan, G.; Hillsdon, M.; Ukoumunne, O.C.; Stamatakis, E.; Hamer, M. Objectively measured physical activity, cardiorespiratory fitness and cardiometabolic risk factors in the Health Survey for England. Prev. Med. 2013, 57, 201–205. [Google Scholar] [CrossRef]
  50. Uys, M.; Draper, C.E.; Hendricks, S.; de Villiers, A.; Fourie, J.; Steyn, N.P.; Lambert, E.V. Impact of a South African School-based Intervention, HealthKick, on Fitness Correlates. Am. J. Health Behav. 2016, 40, 55–66. [Google Scholar] [CrossRef]
  51. Resaland, G.K.; Andersen, L.B.; Mamen, A.; Anderssen, S.A. Effects of a 2-year school-based daily physical activity intervention on cardiorespiratory fitness: The Sogndal school-intervention study. Scand. J. Med. Sci. Sports 2011, 21, 302–309. [Google Scholar] [CrossRef]
  52. Dobbins, M.; Husson, H.; DeCorby, K.; LaRocca, R.L. School-Based Physical Activity Programs for Promoting Physical Activity and Fitness in Children and Adolescents Aged 6 to 18. Cochrane Database Syst. Rev. 2013, CD007651. [Google Scholar] [CrossRef] [PubMed]
  53. Long, K.Z.; Beckmann, J.; Lang, C.; Seelig, H.; Nqweniso, S.; Probst-Hensch, N.; Müller, I.; Pühse, U.; Steinmann, P.; du Randt, R.; et al. Impact of a school-based health intervention program on body composition among South African primary schoolchildren: Results from the KaziAfya cluster-randomized controlled trial. BMC Med. 2022, 20, 27. [Google Scholar] [CrossRef]
  54. Bhutta, Z.A.; Ahmed, T.; Black, R.E.; Cousens, S.; Dewey, K.; Giugliani, E.; Haider, B.A.; Kirkwood, B.; Morris, S.S.; Sachdev, H.P.; et al. What works? Interventions for maternal and child undernutrition and survival. Lancet 2008, 371, 417–440. [Google Scholar] [CrossRef] [PubMed]
  55. Devakumar, D.; Fall, C.H.; Sachdev, H.S.; Margetts, B.M.; Osmond, C.; Wells, J.C.; Costello, A.; Osrin, D. Maternal antenatal multiple micronutrient supplementation for long-term health benefits in children: A systematic review and meta-analysis. BMC Med. 2016, 14, 90. [Google Scholar] [CrossRef]
Table 1. Allocation of classes to intervention arms.
Table 1. Allocation of classes to intervention arms.
School 1School 2School 3School 4
Grade 1PA + placeboPlaceboPA + MMNSMMNS
Grade 2MMNSPA + placeboPlaceboPA + MMNS
Grade 3PA + MMNSMMNSPA + placeboPlacebo
Grade 4PlaceboPA + MMNSMMNSPA + placebo
PA = physical activity; MMNS = multi-micronutrient supplementation.
Table 2. Sample characteristics for the total sample (sociodemographic background) and differences between intervention groups at baseline.
Table 2. Sample characteristics for the total sample (sociodemographic background) and differences between intervention groups at baseline.
Intervention Group
Overall
(n = 1151)		PA + MMNS
(n = 258)		PA + Placebo
(n = 307)		MMNS
(n = 283)		Placebo
(n = 303)		Fp-Value
Child CharacteristicsM (SD)M (SD)M (SD)M (SD)M (SD)
Age (years)8.3 (1.4)8.4 (1.3)8.8 (1.5)8.1 (1.5)7.9 (1.3)23.47<0.001 **
Sex, girls, n (%)561 (49)130 (23)159 (28)129 (23)143 (26)2.840.416
SES0.75 (0.16)0.73 (0.15)0.77 (0.16)0.76 (0.15)0.75 (0.16)1.610.187
Height (cm)124.7 (9.3)125.2 (9.1)127.5 (9.9)123.5 (8.2)122.5 (9.0)17.40<0.001 **
Weight (kg)25.4 (6.8)25.8 (6.8)27.4 (8.4)24.6 (5.4)23.7 (5.5)16.82<0.001 **
PA = Physical activity; MMNS = Multi-micronutrient supplementation; SES = Socioeconomic status. ** p < 0.001.
Table 3. Descriptive statistics for outcome variables in the total sample and differences between intervention groups.
Table 3. Descriptive statistics for outcome variables in the total sample and differences between intervention groups.
Intervention and Control Groups
Overall
(n = 1151)		PA + MMNS
(n = 258)		PA + Placebo
(n = 307)		MMNS
(n = 283)		Placebo
(n = 303)		Unadjusted ModelAdjusted Model a
Outcome VariablesM (SD)M (SD)M (SD)M (SD)M (SD)Fp-ValueFp-Value
MVPA (min/day)82.37 (28.00)82.48 (27.90)79.60 (29.24)83.69 (28.73)83.85 (25.98)1.500.2140.530.659
Estimated VO2max (mL/kg/min)47.52 (3.85)47.21 (3.65)46.89 (4.18)47.78 (3.70)48.16 (3.70)6.44<0.001 **0.750.522
BMI (kg/m2)16.08 (2.62)16.22 (2.61)16.47 (3.26)16.03 (2.27)16.63 (2.12)5.44<0.001 **5.76<0.001 **
zBMI−0.12 (1.25)−0.06 (1.29)−0.11 (1.36)−0.04 (1.18)−0.25 (1.17)1.630.1821.890.129
Body fat (%)22.61 (5.30)22.45 (5.13)23.14 (6.23)22.71 (4.87)22.12 (4.75)1.920.1252.850.036 *
Total cholesterol (mmol/L)3.63 (0.64)3.59 (0.61)3.68 (0.64)3.70 (0.64)3.58 (0.65)2.050.1061.160.325
LDL-C (mmol/L)2.07 (0.53)2.01 (0.52)2.11 (0.54)2.10 (0.51)2.05 (0.54)1.710.1641.020.385
HDL-C (mmol/L)1.23 (0.31)1.23 (0.29)1.23 (0.32)1.26 (0.31)1.21 (0.32)1.100.3491.050.369
Triglycerides (mmol/L)0.76 (0.31)0.79 (0.31)0.77 (0.25)0.74 (0.27)0.74 (0.39)1.550.1990.720.540
HbA1c (%)5.42 (0.26)5.43 (0.24)5.44 (0.31)5.37 (0.23)5.44 (0.24)3.430.017 *3.430.017 *
Systolic blood pressure (mmHg)102.0 (11.9)102.6 (11.5)101.9 (11.8)102.6 (12.3)101.0 (11.8)1.110.3450.910.438
Diastolic blood pressure (mmHg)63.9 (9.4)63.9 (8.4)63.8 (8.9)64.1 (9.5)63.6 (10.6)0.140.9370.380.768
PA = Physical activity; MMNS = Multi-micronutrient supplementation; MVPA = Moderate-to-vigorous physical activity; VO2max = Maximal oxygen uptake; BMI = Body mass index; zBMI = BMI-for-age z-score; LDL-C = Low-density lipoprotein cholesterol; HDL-C = High-density lipoprotein cholesterol; HbA1c = Glycated hemoglobin. a Models adjusted for age, sex, and zBMI. * p < 0.05, ** p < 0.001.
Table 4. Mixed linear model to predict T2 outcomes for each intervention arm in comparison with placebo.
Table 4. Mixed linear model to predict T2 outcomes for each intervention arm in comparison with placebo.
Intervention Groups a
PA + MMNSPA + PlaceboMMNS
Outcome VariablesCoefficient95% CICoefficient95% CICoefficient95% CI
MVPA (min/day)2.31(−1.26; 5.87)−1.28(−4.82; 2.26)−1.42(−4.94; 2.10)
Estimated VO2max (mL/kg/min)−0.00(−0.54; 0.53)−0.19(−0.72; 0.34)1.21(0.68; 1.73) **
Body fat (%)0.35(−0.09; 0.80)−0.31(−0.76; 0.14)−0.04(−0.48; 0.41)
Total cholesterol (mmol/L)−0.01(−0.10; 0.09)0.04(−0.07; 0.14)0.02(−0.08; 0.12)
LDL-C (mmol/L)0.05(−0.03; 0.13)0.11(0.03; 0.20) *0.05(−0.03; 0.13)
HDL-C (mmol/L)−0.02(−0.08; 0.03)−0.04(−0.10; 0.01)−0.04(−0.10; 0.01)
Triglycerides (mmol/L)0.03(−0.03; 0.08)−0.03(−0.09; 0.03)0.07(0.02; 0.13) *
HbA1c (%)−0.07(−0.11; −0.03) **−0.04(−0.08; 0.00)−0.00(−0.04; 0.04)
Systolic blood pressure (mmHg)−0.47(−2.57; 1.64)0.53(−1.56; 2.61)−1.87(−3.94; 0.21)
Diastolic blood pressure (mmHg)0.91(−0.85; 2.67)1.64(−0.11; 3.39)−1.36(−3.10; 0.37)
PA = Physical activity; MMNS = Multi-micronutrient supplementation; MVPA = Moderate-to-vigorous physical activity; VO2max = Maximal oxygen uptake; LDL-C = Low-density lipoprotein cholesterol; HDL-C = High-density lipoprotein cholesterol; HbA1c = Glycated hemoglobin. a The placebo group is used as a reference, controlling for baseline age, sex, and zBMI. Class considered as random intercept. * p < 0.05, ** p < 0.001.
Table 5. Mixed linear model to predict T3 outcomes for each intervention arm in comparison with placebo.
Table 5. Mixed linear model to predict T3 outcomes for each intervention arm in comparison with placebo.
Intervention Groups a
PA + MMNSPA + PlaceboMMNS
Outcome VariablesCoefficient95% CICoefficient95% CICoefficient95% CI
MVPA (min/day)−1.99(−7.31; 3.34)1.33(−4.04; 6.69)3.51(−2.01; 9.03)
Estimated VO2max (mL/kg/min)0.04(−0.68; 0.75)−0.17(−0.88; 0.54)0.19(−0.55; 0.92)
Body fat (%)1.58(0.55; 2.61) *−0.06(−1.11; 1.00)0.48(−0.58; 1.53)
Total cholesterol (mmol/L)−0.12(−0.26; 0.03)−0.12(−0.26; 0.03)−0.04(−0.18; 0.11)
LDL-C (mmol/L)0.06(−0.05; 0.17)−0.04(−0.15; 0.07)0.02(−0.09; 0.14)
HDL-C (mmol/L)−0.12(−0.19; −0.04) *−0.07(−0.15; 0.01)−0.08(−0.16; 0.00)
Triglycerides (mmol/L)0.01(−0.15; 0.16)0.05(−0.11; 0.21)0.06(−0.10; 0.22)
HbA1c (%)0.01(−0.04; 0.06)−0.00(−0.05; 0.05)0.03(−0.02; 0.08)
Systolic blood pressure (mmHg)10.03(−7.52; 27.58)−13.01(−30.40; 4.39)−36.53(−53.83; −19.23) **
Diastolic blood pressure (mmHg)7.97(−6.02; 21.95)−10.47(−24.34; 3.40)−29.18(−42.96; −15.40) **
PA = Physical activity, MMNS = Multi-micronutrient supplementation, MVPA = Moderate-to-vigorous physical activity, VO2max = Maximal oxygen uptake, LDL-C = Low-density lipoprotein cholesterol, HDL-C = High-density lipoprotein cholesterol, HbA1c = Glycated hemoglobin. a The placebo group is used as a reference, controlling for baseline age, sex, zBMI. Class considered as random intercept. * p < 0.05, ** p < 0.001.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Nqweniso, S.; Walter, C.; Randt, R.d.; Adams, L.; Beckmann, J.; Dolley, D.; Joubert, N.; Long, K.Z.; Müller, I.; Pühse, U.; et al. A Combined Physical Activity and Multi-Micronutrient Supplementation Intervention in South African Primary Schools: Effects on Physical Activity, Fitness, and Cardiovascular Disease Risk Factors. Children 2025, 12, 1352. https://doi.org/10.3390/children12101352

AMA Style

Nqweniso S, Walter C, Randt Rd, Adams L, Beckmann J, Dolley D, Joubert N, Long KZ, Müller I, Pühse U, et al. A Combined Physical Activity and Multi-Micronutrient Supplementation Intervention in South African Primary Schools: Effects on Physical Activity, Fitness, and Cardiovascular Disease Risk Factors. Children. 2025; 12(10):1352. https://doi.org/10.3390/children12101352

Chicago/Turabian Style

Nqweniso, Siphesihle, Cheryl Walter, Rosa du Randt, Larissa Adams, Johanna Beckmann, Danielle Dolley, Nandi Joubert, Kurt Z. Long, Ivan Müller, Uwe Pühse, and et al. 2025. "A Combined Physical Activity and Multi-Micronutrient Supplementation Intervention in South African Primary Schools: Effects on Physical Activity, Fitness, and Cardiovascular Disease Risk Factors" Children 12, no. 10: 1352. https://doi.org/10.3390/children12101352

APA Style

Nqweniso, S., Walter, C., Randt, R. d., Adams, L., Beckmann, J., Dolley, D., Joubert, N., Long, K. Z., Müller, I., Pühse, U., Seelig, H., Steinmann, P., Utzinger, J., Lang, C., & Gerber, M. (2025). A Combined Physical Activity and Multi-Micronutrient Supplementation Intervention in South African Primary Schools: Effects on Physical Activity, Fitness, and Cardiovascular Disease Risk Factors. Children, 12(10), 1352. https://doi.org/10.3390/children12101352

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop