Next Article in Journal
Improving Medication Safety Through Medication Reconciliation in Pediatric Neurology: Clinical Pharmacist Recommendations and Physician Uptake in a 13-Week Study
Previous Article in Journal
Strength Training in Children: A Systematic Review Study
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Systematic Review

Growth Patterns of HIV-Exposed and -Unexposed Infants in African Countries: A Systematic Review and Meta-Analysis

by
Perpetua Modjadji
1,2,*,
Kabelo Mokgalaboni
2,
Wendy N. Phoswa
2,
Tebogo Maria Mothiba
3 and
Sogolo L. Lebelo
2
1
Non-Communicable Diseases Research Unit, South African Medical Research Council, Tygerberg, Cape Town 7505, South Africa
2
Department of Life and Consumer Sciences, College of Agriculture and Environmental Sciences, University of South Africa, Florida Campus, Johannesburg 1709, South Africa
3
Faculty of Health Sciences, University of Limpopo, Polokwane 0700, South Africa
*
Author to whom correspondence should be addressed.
Children 2025, 12(5), 624; https://doi.org/10.3390/children12050624
Submission received: 2 April 2025 / Revised: 5 May 2025 / Accepted: 8 May 2025 / Published: 12 May 2025
(This article belongs to the Special Issue Maternal Health and the Impact on Infant Growth)

Abstract

:
Background/Objectives: The purpose of this study is to understand the prevalence and odds of poor growth patterns among HIV-exposed but uninfected (HEU) versus HIV-unexposed (HUU) infants in the era of antiretroviral therapy (ART) and prevention of mother-to-child transmission (PMTCT) in Africa. Methods: We reviewed and meta-analyzed studies on growth patterns among HEU versus HUU infants in Africa. Evidence was gathered from the PubMed and Scopus databases following PRISMA guidelines. We independently evaluated the quality of included studies using Newcastle Ottawa guidelines. Data analysis was performed using an online meta-analysis tool, and the results are reported as odds ratios (OR) and prevalence with 95% confidence intervals (CI). Results: A total of 17 studies met the inclusion criteria for this review. The odds of stunting were significantly higher among HEU infants compared to HUU infants, with an odds ratio of 1.56 (95% CI: 1.23–1.97; p < 0.01). The pooled prevalence of stunting was 25% (95% CI: 17–33%) in HEU infants and 19% (95% CI: 12–26%) in HUU infants. In contrast, no significant differences were observed for underweight and wasting. The odds of being underweight in HEU infants compared to HUU was 0.85 (95% CI: 0.47–1.56; p = 0.60), with a pooled prevalence of 11% (95% CI: 5–17%) in HEU and 14% (95% CI: 5–24%) in HUU. Similarly, the odds of wasting were 1.10 (95% CI: 0.78–1.56; p = 0.58), with a pooled prevalence of 9% (95% CI: 3–14%) in HEU and 7% (95% CI: 3–12%) in HUU. Conclusions: Stunting was the most prevalent growth deficit among HEU infants compared to their HUU counterparts, with no significant differences observed in the rates of underweight and wasting. To improve postnatal growth outcomes, especially in the evolving landscape of HIV treatment and prevention, efforts should focus on educating and supporting mothers living with HIV.

1. Introduction

The global prevalence of people living with HIV (PLWH) was estimated to be approximately (≈) 37.9 million in 2018 [1]. Most of the PLWH reside in Eastern and Southern Africa (≈20.6 million) compared to Central and Western Africa (≈4.5 million) and the Middle East and North Africa (≈180,000) [1,2]. Between 69% and 95% of pregnant women living with HIV (pWLWH) received antiretroviral therapy (ART) to prevent mother-to-child transmission of HIV (PMTCT) and to protect their own health in 2018, compared to 49% reported in 2010 in eastern and southern Africa. The rate of MTCT decreased from 18% in 2010 to 9% in 2018 [1]. The integration of HIV and antenatal care (ANC) services has significantly enhanced the coverage of the three key steps required for PMTCT of HIV, ensuring that over 95% of pregnant women received antenatal testing for HIV and received antiretroviral therapy (ART) [3,4].
This integrated approach is particularly critical in the context of fetal growth, as HIV infection has been associated with impaired placental function, which may contribute to intrauterine growth restriction (IUGR). IUGR is defined as the failure of a fetus to achieve its genetically determined growth potential and is often linked to placental insufficiency, a condition in which the placenta cannot deliver adequate oxygen and nutrients to the fetus [5]. HIV-related placental abnormalities, including inflammation and vascular dysfunction, can compromise placental circulation, thereby increasing the risk of IUGR among HIV-exposed infants [6]. Furthermore, placental insufficiency is a well-established cause of IUGR, and its prevalence is notably higher in pregnancies complicated by maternal infections, including HIV [5]. These findings highlight the importance of early HIV diagnosis and treatment during pregnancy, not only to prevent vertical transmission, but also to support optimal fetal growth and development. Although many pregnant women living with HIV now receive ART, there are still concerns about how this treatment might affect the baby during pregnancy, birth, and after delivery. As a result, more babies are being born HIV-exposed but uninfected (HEU) [7,8,9].
The influence of the maternal intrauterine environment is reflected primarily in the growth parameters (i.e., weight and length) of infants at birth and during the early months of life [10,11,12,13]. However, growth is a dynamic process that continues beyond birth, and adequate infant and childhood nutrition is essential for maintaining healthy growth trajectories. Normal growth patterns reflect overall wellbeing, including nutritional status, health, and socioeconomic conditions [14,15,16]. Conversely, growth failure, often due to undernutrition, is expressed as stunting (low height for age), underweight (low weight for age), and wasting (low weight for length), which indicate insufficient height or weight compared to age-specific standards [17,18,19]. In 2020, an estimated 149 million children under five were stunted, 85 million were underweight, and 45 million were wasted globally [20].
Furthermore, HIV-exposed but uninfected (HEU) children experience a slower phase of linear growth (i.e., stunting) [8], and have an increased risk of morbidity and mortality compared to HIV-unexposed and uninfected (HUU) children [21,22,23]. Particularly among HEU infants, growth outcomes are influenced by a complex interplay of maternal, infant, and environmental factors [24]. Maternal characteristics such as age, health status, and exposure to ART can affect fetal development and postnatal growth [24]. Infant-level factors, including birth weight, sex, and vulnerability to infections, have also been shown to significantly affect growth trajectories in this population [24]. Other factors like where a family lives, how clean their environment is, and what kind of food they have at home also play a significant role in how well these children grow [25].
Studies in Africa examining the postpartum growth of HEU infants have inconsistently reported poorer early growth, high rates of stunting, and underweight among HEU infants [26,27,28], while others reported no differences between HEU infants’ early growth versus HUU [24,29]. Notably, these changes may reflect disruption to the growth hormone axis in infants who are HEU compared with infants who are HUU [30]. From infancy to school age, HEU children experience a slower linear growth [8,31,32], and they have an increased risk of morbidity and mortality compared to their HUU counterparts [21,22,23]. Differences in how babies grow may also come from things like how healthy the mother was during pregnancy, whether she had access to HIV treatment, and whether the family had enough nutritious food [24,33].
Although the literature documents findings on growth patterns or growth failure/faltering (i.e., stunting, underweight and wasting) between HEU and HUU infants, there are inconsistent findings comparing the two groups in African countries. As stated above, HEU infants are susceptible to sub-optimal growth patterns or growth failure, a hallmark of undernutrition expressed as stunting, underweight, and wasting compared to their HUU counterparts. In view of growth failure being a complex phenomenon that carries significant morbidity and mortality implications for infants, we reviewed the existing literature and quantitatively analyzed data to find the overall prevalence and the odds of having growth failure in a comparison between HEU and HUU infants during the era of PMTCT in African countries.

2. Methodology

2.1. Search Strategy and Literature Search

Due to its nature, this study was conducted and reported in accordance with preferred reporting items for systematic review and meta-analysis (PRISMA) guidelines [34], Supplementary File S1. The protocol for this study was not registered with PROSPERO; however, a thorough search on Cochrane databases was performed to ensure that there was no duplication of the same study. This study identified clinical studies that provided evidence of the prevalence of underweight, stunting, and wasting in Africa. Two independent researchers (KM and WNP) comprehensively searched for evidence on main databases, including PubMed and Scopus, without duration and language restrictions; however, the search was updated on 20 November 2024. The following keywords and MeSH terms were used to source the evidence from the databases: “HIV mother”, “HIV-exposed children”, “HIV-exposed infant”, “child malnutrition”, “infant malnutrition”, “underweight”, “under-nutrition”, “wasting”, “thinness”, and “stunting”. The terms were adapted and applied on PubMed and Scopus using Boolean operators such as “OR” and “AND”. Therefore, the exact searches made on both PubMed and Scopus are presented in Supplementary File S2 Table S1. A manual screening of relevant reviews was also performed to identify additional studies.

2.2. Eligibility and Selection Criteria

All retrieved studies were exported to the Mendeley Desktop reference manager (version 1.59.1) for the inclusion and exclusion, which subsequently identified possible duplicates. Before the retrieval of full-text articles, two independent researchers (KM and WNP) thoroughly screened the identified studies using the articles’ titles, abstracts, and keywords. Furthermore, pre-defined eligibility criteria according to the PECOS framework were followed to screen the remaining studies. Briefly, PECOS was as follows: pregnant women, exposure was HIV infection, the comparator was HIV-unexposed uninfected infants, outcomes included underweight, stunting, and wasting, while the study design included cohorts and cross-sectional studies. Any disagreements that arose were resolved with the input of a third independent researcher (PM) who made a final decision on the selection of studies in question. Therefore, all studies that reported on underweight, wasting, and stunting published in English from the database’s inception to 20 November 2024 were included. All studies on HIV-exposed children born in Africa were included. The studies included were cross-sectional and cohort. The prevalence of stunting, underweight, and wasting was defined as height for age, weight for age, and weight for height Z-scores, respectively. However, studies conducted primarily on children with other medical conditions, chronic diseases, randomized controlled trials, and studies not reporting data as numbers and prevalence were not considered. When the same study was published by the same author, we considered the initial cohorts to avoid data duplication.

2.3. Data Extraction

KM developed an Excel data extraction sheet, which included the author, year of publication, country, study design, sample size, and the proportion of underweight, stunting, and wasting infants. Two researchers (KM and PM) independently extracted data from all relevant studies in accordance with their extraction sheet. The two sheets were shared with a third independent researcher (WNP) to assess the accuracy and consistency of the extracted data, and any notable disagreements were resolved through discussion with primary researchers (KM and PM), who extracted the data to reach a final decision.

2.4. Quality Assessment

Two researchers (WNP and KM) reviewed the quality of each study on their own using the Newcastle-Ottawa checklist [35]. They rated the studies as high, moderate, or low quality based on how many stars they received: 7 or more stars meant high quality, 4 to 6 stars meant moderate quality, and fewer than 4 stars meant low quality. If they did not agree on a rating, a third researcher (PM) helped make the final decision.

2.5. Data Analysis

The extracted data were analyzed using an online meta-analysis software: https://metaanalysisonline.com/ (accessed on 11 December 2024). Random and fixed-effect models were used based on the level of heterogeneity. The number of infants in the HIV-exposed uninfected and HIV-unexposed groups that had developed growth patterns (underweight, stunting, and wasting) and the total sample sizes in both groups were used to estimate the overall effect estimates. Data are reported as the odds ratio (OR) and 95% confidence intervals. The prevalence of these growth patterns was also determined. A probability of less than 5% was considered statistically significant. Statistical heterogeneity was assessed using the I2 and Chi-square statistics [36,37]. The I2 statistic values of 0, 25, 50, and 75% indicate zero, low, moderate, and high heterogeneity, respectively. Based on the region of publication in Africa, subgroup analysis was performed to find the source of the observed heterogeneity in case I2 was above 50%. Furthermore, if more than ten studies were available, a funnel plot and Egger’s regression tests were used to assess publication bias among the included studies [38].

3. Results

3.1. Databases and Literature Search

The evidence was retrieved from two databases, with 21 records from PubMed, 79 from Scopus, and twelve retrieved via manual screening of relevant studies. Therefore, 112 records were retrieved and critically assessed for inclusion. Briefly, eight were identified by the reference manager as duplicates and were thus excluded. An additional six were excluded at the early screening stage due to irrelevant titles, abstracts, keywords, and the overall focus. In total, 3 of the 104 remaining records were unavailable; however, attempts were made to obtain these full texts by contacting the primary investigators, which proved fruitless. Amongst the 95 that were retrieved, 78 articles were excluded based on the following reasons: (1) irrelevant population, (2) single-armed study without a control group, (3) studies not conducted in Africa (2 from China and 1 from India), (4) review articles, (5) randomized controlled trials, (6) data not reported as prevalence, (7) protocols, and (8) no outcome of interest. Hence, only 17 [28,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54] were included in the meta-analysis based on the available data (Figure 1).

3.2. Quality of Studies

The studies included in the review were generally of good quality, based on the Newcastle-Ottawa Scale. Most cohort studies scored well, with eight of them earning 8 stars and one scoring 6 (see Supplementary File S2, Table S2). All the cross-sectional studies also performed well, each receiving 7 stars (see Supplementary File S2, Table S3).

3.3. General Characteristics of the Included Studies

All included studies [28,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54] were published in peer-reviewed journals between 2012 and 2023. All studies were conducted in different parts of Africa, ranging from the Southern, Eastern, and Western regions. Briefly, these included South Africa [28,40,41,48,50,52], Botswana [42], Uganda [39], Kenya [46,47], Zimbabwe [44,45], Ethiopia [49,53], Nigeria [43], and Malawi [51,54]. We included cohorts (prospective, retrospective, and longitudinal observational) as well as cross-sectional studies. A detailed overview is presented in Table 1.

3.4. Meta-Analysis Findings

3.4.1. Underweight in HIV-Exposed Infants Compared to Unexposed-Uninfected Infants

A total of 16 studies [28,39,40,41,42,43,44,45,46,47,48,49,51,52,53,54] reported underweight in both groups. Only, one study [50] reported no events in either group; thus, it was not included in the meta-analysis. The overall OR was 0.85 with a 95% CI (0.47, 1.56), p = 0.60 (Figure 2). However, the studies revealed high heterogeneity (I2 = 82%). The results for prevalence are presented in Figure 3. The prevalence in the HEU group was 11%, 95% CI (5, 17) (Figure 3A), and it was 14%, 95% CI (5, 24) in the HUU group (Figure 3B).

3.4.2. Stunting in HIV-Exposed Uninfected Infants Compared to Unexposed Infants

Fifteen studies [28,39,40,41,42,43,44,45,47,48,49,51,52,53,54] were included in the meta-analysis of stunting in HIV-exposed uninfected and HIV-unexposed infants. The overall OR was 1.56 with a 95% CI (1.23, 1.97), p ˂ 0.01 (Figure 4). The prevalence in the HEU group was 25%, 95% CI (17, 33) (Figure 5A), and it was 19%, 95% CI (12, 26) in the HUU group (Figure 5B).

3.4.3. Wasting in HIV-Exposed Infants Compared to Unexposed-Uninfected Infants

A total of nine studies were included in the meta-analysis of wasting in HEU and HUU infants. The overall OR was 1.10 with a 95% CI (0.78, 1.56), p = 0.58 (Figure 6). Significant heterogeneity was not observed (I2 = 0%, p = 0.78), suggesting that the effect sizes across studies were uniform in both magnitude and direction. The prevalence of wasting in those exposed was 9%, 95% CI (3, 14) (Figure 7A), and it was 7%, 95% CI (3, 12) (Figure 7B).

3.4.4. Graphical and Statistical Assessment of Publication Bias

For studies that assessed underweight, the funnel plot did not indicate a potential publication bias (Supplementary File S2, Figure S1A). The Egger’s test does not support the presence of funnel plot asymmetry. For those that assessed stunting, the funnel plot did not indicate a potential publication bias (Supplementary File S2, Figure S1B). The Egger’s test does not support the presence of funnel plot asymmetry. Similarly, for studies that assessed wasting, the funnel plot showed no potential publication bias (Supplementary File S2, Figure S1C). The Egger’s test also does not support the presence of funnel plot asymmetry.

4. Discussion

This study synthesizes the published evidence to evaluate the prevalence and odds of developing growth failure among HEU and HUU infants in the era of PMTCT. The findings show a significant concern: HEU infants are at a notably higher risk of stunting compared to their HUU counterparts. Recent evidence shows that HEU infants have 56% higher odds of being stunted, reflecting chronic undernutrition and long-term growth failure [55,56,57,58]. Stunting, defined as low height for age, is a cumulative indicator of poor nutrition and repeated infections, particularly during the first 1000 days of life [57,58,59]. Unlike wasting or underweight, which may reflect acute nutritional deficits, stunting is often the result of prolonged exposure to adverse conditions, including poor maternal health and inadequate infant feeding practices [56,58]. The elevated risk of stunting in HEU infants highlights the need for targeted nutritional and health interventions to mitigate these adverse outcomes.
Furthermore, this elevated risk among HEU infants may be attributed to a complex interplay of biological and environmental factors. In utero exposure to HIV ART, even in the absence of infection, may disrupt fetal growth and immune development [56,57,58,60]. Studies suggest that HIV-exposed fetuses may experience altered placental function, inflammation, or oxidative stress, which can impair nutrient transfer and fetal growth [55,58,60,61]. These biological disruptions are compounded by maternal health challenges, including ART side effects and immune dysregulation, which may further compromise fetal development.
Postnatally, the health and nutritional status of the mother continues to play a pivotal role. Mothers living with HIV often face food insecurity, limited access to healthcare, and increased susceptibility to infections, all of which can affect breastfeeding practices and caregiving environments [56,57,58,61]. Food insecurity has been shown to significantly impact maternal dietary diversity and breastfeeding outcomes, especially in low-resource settings [13,62,63,64]. These challenges are often exacerbated by broader socioeconomic disadvantages, including poverty, inadequate sanitation, and limited access to clean water and health services, all of which are known contributors to stunting [59,60,62,63]. Despite WHO recommendations supporting breastfeeding for mothers living with HIV on ART, implementation remains inconsistent in many settings due to systemic barriers and stigma [65,66,67].
Importantly, the lack of significant differences in underweight and wasting between HEU and HUU infants in recent studies suggests that the growth deficits in HEU infants are more chronic than acute [55,56,60]. This pattern emphasizes the need for early and sustained interventions that go beyond HIV prevention and treatment [57,58,59,61]. Nutritional support, maternal health services, and social protection programs tailored to the needs of HEU infants, and their families are essential to address the root causes of stunting [56,57,58,59].
This study has several strengths, including a comprehensive search strategy conducted independently across major databases and the inclusion of studies from diverse African regions. However, there are important limitations to consider when interpreting the findings. Although Africa bears a significant burden of global HIV prevalence, only 17 relevant studies met the inclusion criteria, limiting the generalizability of the results. While subgroup analyses were performed to explore regional variations, heterogeneity in outcomes remained. A key limitation is that most included studies did not specify whether the HIV in pregnant mothers was well controlled or uncontrolled, nor did they consistently report maternal viral load or CD4 count. This lack of stratification may have masked important differences in infant growth outcomes between these subgroups. Additionally, the form and timing of ART used during pregnancy were often not reported, making it difficult to assess the influence of specific ART regimens on fetal and postnatal growth. Furthermore, many studies did not account for other critical factors known to influence fetal growth, such as maternal nutritional status, co-infections, socioeconomic conditions, and environmental exposures. The absence of these variables in the analysis may have introduced residual confounding. Despite the overall good quality of studies based on the Newcastle-Ottawa Scale, these methodological gaps highlight the need for more detailed and standardized reporting in future research.

5. Conclusions and Recommendations

Despite the success of PMTCT programs in reducing vertical HIV transmission, our systematic review and meta-analysis shows that HEU infants remain significantly more vulnerable to stunting than their HUU counterparts, highlighting a critical gap in child health strategies. This persistent growth deficit emphasizes the need for a holistic response that includes targeted nutritional interventions, routine health monitoring, such as the consistent use of the Road to Health Book, and socioeconomic support to address the underlying determinants of undernutrition. Although the WHO recommends breastfeeding for mothers on ART, implementation is often hindered by stigma, misinformation, and systemic barriers, particularly in resource-limited settings. To ensure that HEU infants thrive, future policies must integrate these insights and prioritize longitudinal research to better understand and address the complex drivers of stunting in this vulnerable population. In addition, efforts should focus on educating and supporting mothers living with HIV to improve postnatal growth outcomes for their infants, especially within the evolving landscape of HIV treatment and prevention.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/children12050624/s1, Supplementary File S1: PRISMA checklist; Supplementary File S2 Table S1: Search strategy; Supplementary File S2 Table S2: Quality assessment for cohorts; Supplementary File S2 Table S3: Quality assessment for cross-sectional studies; Figure S1: Funnel plot showing assessment of publication bias. A: underweight, B: stunting, C: wasting.

Author Contributions

Conceptualization, P.M.; writing—original draft preparation, P.M. and K.M.; writing—review and editing, P.M., T.M.M., K.M., W.N.P. and S.L.L.; visualization, P.M., T.M.M., K.M., W.N.P. and S.L.L.; project administration, P.M.; funding acquisition, P.M. All authors have read and agreed to the published version of the manuscript.

Funding

The Article Processing Charge will be funded by the Non-Communicable Diseases Research Unit (NCDRU), South African Medical Research Council (SAMRC).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article/Supplementary Materials, further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. UNAIDS. UNAIDS Data 2019. UNAIDS. 2019. Available online: https://www.unaids.org/sites/default/files/media_asset/2019-UNAIDS-data_en.pdf (accessed on 12 December 2023).
  2. Statista.com. HIV/AIDS in Africa—Statistics and Facts. 2021. Available online: https://www.statista.com/topics/8660/hiv-aids-in-africa/#topicOverview (accessed on 18 December 2023).
  3. Ritchie, L.M.P.; van Lettow, M.; Pham, B.; Straus, S.E.; Hosseinipour, M.C.; Rosenberg, N.E.; Phiri, S.; Landes, M.; Cataldo, F.; on behalf of the the PURE consortium. What interventions are effective in improving uptake and retention of HIV-positive pregnant and breastfeeding women and their infants in prevention of mother to child transmission care programmes in low-income and middle-income countries? A systematic review and meta-analysis. BMJ Open 2019, 9, e024907. [Google Scholar] [CrossRef]
  4. Goga, A.; Chirinda, W.; Ngandu, N.; Ngoma, K.; Bhardwaj, S.; Feucht, U.; Davies, N.; Ntloana, M.; Mhlongo, B.; Silere-Maqetseba, T.; et al. Closing the gaps to eliminate mother-to-child transmission of HIV (MTCT) in South Africa: Understanding MTCT case rates, factors that hinder the monitoring and attainment of targets, and potential game changers. S. Afr. Med. J. 2018, 108, 17. [Google Scholar] [CrossRef]
  5. Bertino, E.; Oggè, G.; Di Nicola, P.; Giuliani, F.; Coscia, A.; Todros, T. Intrauterine Growth Restriction: Obstetric and Neonatal Aspects. Intervention Strategies. In Neonatology: A Practical Approach to Neonatal Diseases; Buonocore, G., Bracci, R., Weindling, M., Eds.; Springer International Publishing: Cham, Switzerland, 2016; pp. 1–23. [Google Scholar]
  6. Suhag, A.; Berghella, V. Intrauterine Growth Restriction (IUGR): Etiology and Diagnosis. Curr. Obstet. Gynecol. Rep. 2013, 2, 102–111. [Google Scholar] [CrossRef]
  7. Modjadji, P.; Mokgalaboni, K.; Nonterah, E.A.; Lebelo, S.L.; Mchiza, Z.J.-R.; Madiba, S.; Kengne, A.P. A Systematic Review on Cardiometabolic Risks and Perinatal Outcomes among Pregnant Women Living with HIV in the Era of Antiretroviral Therapy. Viruses 2023, 15, 1441. [Google Scholar] [CrossRef] [PubMed]
  8. Nyemba, D.C.; Kalk, E.; Vinikoor, M.J.; Madlala, H.P.; Mubiana-Mbewe, M.; Mzumara, M.; Moore, C.B.; Slogrove, A.L.; Boulle, A.; Davies, M.A.; et al. Growth patterns of infants with in- utero HIV and ARV exposure in Cape Town, South Africa and Lusaka, Zambia. BMC Public Health 2022, 22, 55. [Google Scholar] [CrossRef] [PubMed]
  9. Ramokolo, V.; Goga, A.; Lombard, C.; Doherty, T.; Jackson, D.; Engebretsen, I. In Utero ART Exposure and Birth and Early Growth Outcomes Among HIV-Exposed Uninfected Infants Attending Immunization Services: Results From National PMTCT Surveillance, South Africa. Open Forum Infect. Dis. 2017, 4, ofx187. [Google Scholar] [CrossRef]
  10. Touwslager, R.N.; Gielen, M.; Derom, C.; Mulder, A.L.; Gerver, W.J.; Zimmermann, L.J.; Houben, A.J.; Stehouwer, C.D.; Vlietinck, R.; Loos, R.J.; et al. Determinants of infant growth in four age windows: A twin study. J. Pediatr. 2011, 158, 566–572.e2. [Google Scholar] [CrossRef]
  11. Joung, K.E.; Lee, J.; Kim, J.H. Long-Term Metabolic Consequences of Intrauterine Growth Restriction. Curr. Pediatr. Rep. 2020, 8, 45–55. [Google Scholar] [CrossRef]
  12. Sodje, J.D.K. Fetal Growth Abnormalities: Intrauterine Growth Restriction and Macrosomia. In Contemporary Obstetrics and Gynecology for Developing Countries; Okonofua, F., Balogun, J.A., Odunsi, K., Chilaka, V.N., Eds.; Springer International Publishing: Cham, Switzerland, 2021; pp. 103–115. [Google Scholar]
  13. Yang, L.; Feng, L.; Huang, L.; Li, X.; Qiu, W.; Yang, K.; Qiu, J.; Li, H. Maternal Factors for Intrauterine Growth Retardation: Systematic Review and Meta-Analysis of Observational Studies. Reprod. Sci. 2023, 30, 1737–1745. [Google Scholar] [CrossRef]
  14. Modjadji, P.; Madiba, S. The Multidimension of Malnutrition among School Children in a Rural Area, South Africa: A Mixed Methods Approach. Nutrients 2022, 14, 5015. [Google Scholar] [CrossRef]
  15. Nambiar, A.; Arunachalam, D. Child Food Deficiency in India: Socio-demographic and Regional Patterns. Child Indic. Res. 2025, 18, 241–265. [Google Scholar] [CrossRef]
  16. Modjadji, P.; Molokwane, D.; Ukegbu, P.O. Dietary Diversity and Nutritional Status of Preschool Children in North West Province, South Africa: A Cross Sectional Study. Children 2020, 7, 174. [Google Scholar] [CrossRef] [PubMed]
  17. Modjadji, P.; Madiba, S. The double burden of malnutrition in a rural health and demographic surveillance system site in South Africa: A study of primary schoolchildren and their mothers. BMC Public Health 2019, 19, 1087. [Google Scholar] [CrossRef] [PubMed]
  18. Modjadji, P.; Madiba, S. Childhood Undernutrition and Its Predictors in a Rural Health and Demographic Surveillance System Site in South Africa. Int. J. Environ. Res. Public Health 2019, 16, 3021. [Google Scholar] [CrossRef]
  19. WHO. Prevalence of Stunting in Children Under 5 Years of Age (%). WHO Global Health Observatory. 2024. Available online: https://data.who.int/indicators/i/A5A7413/5F8A486 (accessed on 1 May 2025).
  20. UNICEF; WHO; World Bank Group. Levels and Trends in Child Malnutrition; UNICEF/WHO/The World Bank Group Joint Child Malnutrition Estimates: Key Findings of the 2023 Edition; World Health Oragnization (WHO): Geneva, Switzerland, 2023. Available online: https://www.who.int/publications/i/item/9789240025257 (accessed on 12 December 2024).
  21. Chilyabanyama, O.N.; Chilengi, R.; Laban, N.M.; Chirwa, M.; Simunyandi, M.; Hatyoka, L.M.; Ngaruye, I.; Iqbal, N.T.; Bosomprah, S. Comparing growth velocity of HIV exposed and non-exposed infants: An observational study of infants enrolled in a randomized control trial in Zambia. PLoS ONE 2021, 16, e0256443. [Google Scholar] [CrossRef] [PubMed]
  22. Ejigu, Y.; Magnus, J.H.; Sundby, J.; Magnus, M.C. Differences in Growth of HIV-exposed Uninfected Infants in Ethiopia According to Timing of In-utero Antiretroviral Therapy Exposure. Pediatr. Infect. Dis. J. 2020, 39, 730–736. [Google Scholar] [CrossRef]
  23. le Roux, S.M.; Abrams, E.J.; Donald, K.A.; Brittain, K.; Phillips, T.K.; Nguyen, K.K.; Zerbe, A.; Kroon, M.; Myer, L. Growth trajectories of breastfed HIV-exposed uninfected and HIV-unexposed children under conditions of universal maternal antiretroviral therapy: A prospective study. Lancet Child Adolesc. Health 2019, 3, 234–244. [Google Scholar] [CrossRef]
  24. Wedderburn, C.J.; Evans, C.; Yeung, S.; Gibb, D.M.; Donald, K.A.; Prendergast, A.J. Growth and Neurodevelopment of HIV-Exposed Uninfected Children: A Conceptual Framework. Curr. HIV AIDS Rep. 2019, 16, 501–513. [Google Scholar] [CrossRef]
  25. Altfeld, M.; Bunders, M.J. Impact of HIV-1 infection on the feto-maternal crosstalk and consequences for pregnancy outcome and infant health. Semin. Immunopathol. 2016, 38, 727–738. [Google Scholar] [CrossRef]
  26. Sofeu, C.L.; Warszawski, J.; Ateba Ndongo, F.; Penda, I.C.; Tetang Ndiang, S.; Guemkam, G.; Makwet, N.; Owona, F.; Kfutwah, A.; Tchendjou, P.; et al. Low birth weight in perinatally HIV-exposed uninfected infants: Observations in urban settings in Cameroon. PLoS ONE 2014, 9, e93554. [Google Scholar] [CrossRef]
  27. Fowler, M.G.; Aizire, J.; Sikorskii, A.; Atuhaire, P.; Ogwang, L.W.; Mutebe, A.; Katumbi, C.; Maliwichi, L.; Familiar, I.; Taha, T.; et al. Growth deficits in antiretroviral and HIV-exposed uninfected versus unexposed children in Malawi and Uganda persist through 60 months of age. AIDS 2022, 36, 573–582. [Google Scholar] [CrossRef]
  28. Pillay, L.; Moodley, D.; Emel, L.M.; Nkwanyana, N.M.; Naidoo, K. Growth patterns and clinical outcomes in association with breastfeeding duration in HIV exposed and unexposed infants: A cohort study in KwaZulu Natal, South Africa. BMC Pediatr. 2021, 21, 183. [Google Scholar] [CrossRef]
  29. Khoza-Shangase, K.; Nesbitt, J. Case history factors and audiological screening outcomes in HEU and HIV unexposed neonates at a district level hospital in Gauteng, South Africa. Discov. Health Syst. 2023, 2, 34. [Google Scholar] [CrossRef]
  30. Evans, C.; Chasekwa, B.; Ntozini, R.; Majo, F.D.; Mutasa, K.; Tavengwa, N.; Mutasa, B.; Mbuya, M.N.N.; Smith, L.E.; Stoltzfus, R.J.; et al. Mortality, Human Immunodeficiency Virus (HIV) Transmission, and Growth in Children Exposed to HIV in Rural Zimbabwe. Clin. Infect. Dis. Off. Publ. Infect. Dis. Soc. Am. 2021, 72, 586–594. [Google Scholar] [CrossRef]
  31. Moseholm, E.; Helleberg, M.; Sandholdt, H.; Katzenstein, T.L.; Storgaard, M.; Pedersen, G.; Johansen, I.S.; Weis, N. Children Exposed or Unexposed to Human Immunodeficiency Virus: Weight, Height, and Body Mass Index During the First 5 Years of Life-A Danish Nationwide Cohort. Clin. Infect. Dis. Off. Publ. Infect. Dis. Soc. Am. 2020, 70, 2168–2177. [Google Scholar] [CrossRef] [PubMed]
  32. Rosala-Hallas, A.; Bartlett, J.W.; Filteau, S. Growth of HIV-exposed uninfected, compared with HIV-unexposed, Zambian children: A longitudinal analysis from infancy to school age. BMC Pediatr. 2017, 17, 80. [Google Scholar] [CrossRef] [PubMed]
  33. WHO. Kangaroo Mother Care Started Immediately After Birth Critical for Saving Lives; WHO: Geneva, Switzerland, 2021. Available online: https://www.who.int/news/item/26-05-2021-kangaroo-mother-care-started-immediately-after-birth-critical-for-saving-lives-new-research-shows (accessed on 1 May 2025).
  34. Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E.; et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ Clin. Res. Ed. 2021, 372, n71. [Google Scholar] [CrossRef]
  35. Wells, G.A.; Wells, G.; Shea, B.; Shea, B.; O’Connell, D.; Peterson, J.; Welch; Losos, M.; Tugwell, P.; Ga, S.W.; et al. The Newcastle-Ottawa Scale (NOS) for Assessing the Quality of Nonrandomised Studies in Meta-Analyses; Ottawa Hospital Research Institute: Ottawa, ON, Canada, 2011. [Google Scholar]
  36. Huedo-Medina, T.B.; Sánchez-Meca, J.; Marín-Martínez, F.; Botella, J. Assessing heterogeneity in meta-analysis: Q statistic or I2 index? Psychol. Methods 2006, 11, 193–206. [Google Scholar] [CrossRef]
  37. Schroll, J.B.; Moustgaard, R.; Gøtzsche, P.C. Dealing with substantial heterogeneity in Cochrane reviews. Cross-sectional study. BMC Med. Res. Methodol. 2011, 11, 22. [Google Scholar] [CrossRef]
  38. Doleman, B.; Freeman, S.C.; Lund, J.N.; Williams, J.P.; Sutton, A.J. Funnel plots may show asymmetry in the absence of publication bias with continuous outcomes dependent on baseline risk: Presentation of a new publication bias test. Res. Synth. Methods 2020, 11, 522–534. [Google Scholar] [CrossRef]
  39. Arinaitwe, E.; Gasasira, A.; Verret, W.; Homsy, J.; Wanzira, H.; Kakuru, A.; Sandison, T.G.; Young, S.; Tappero, J.W.; Kamya, M.R.; et al. The association between malnutrition and the incidence of malaria among young HIV-infected and -uninfected Ugandan children: A prospective study. Malar. J. 2012, 11, 90. [Google Scholar] [CrossRef] [PubMed]
  40. Bertran-Cobo, C.; Wedderburn, C.J.; Robertson, F.C.; Subramoney, S.; Narr, K.L.; Joshi, S.H.; Roos, A.; Rehman, A.M.; Hoffman, N.; Zar, H.J.; et al. A Neurometabolic Pattern of Elevated Myo-Inositol in Children Who Are HIV-Exposed and Uninfected: A South African Birth Cohort Study. Front. Immunol. 2022, 13, 800273. [Google Scholar] [CrossRef] [PubMed]
  41. Brink, J.; Pettifor, J.M.; Lala, S.G. The prevalence of malnutrition in children admitted to a general paediatric ward at the Chris Hani Baragwanath Academic Hospital: A cross-sectional survey: Research. S. Afr. J. Child Health 2014, 8, 112–116. [Google Scholar] [CrossRef]
  42. Chalashika, P.; Essex, C.; Mellor, D.; Swift, J.A.; Langley-Evans, S. Birthweight, HIV exposure and infant feeding as predictors of malnutrition in Botswanan infants. J. Hum. Nutr. Diet. Off. J. Br. Diet. Assoc. 2017, 30, 779–790. [Google Scholar] [CrossRef] [PubMed]
  43. Jumare, J.; Datong, P.; Osawe, S.; Okolo, F.; Mohammed, S.; Inyang, B.; Abimiku, A. Compromised Growth Among HIV-exposed Uninfected Compared With Unexposed Children in Nigeria. Pediatr. Infect. Dis. J. 2019, 38, 280–286. [Google Scholar] [CrossRef]
  44. Kandawasvika, G.Q.; Kuona, P.; Chandiwana, P.; Masanganise, M.; Gumbo, F.Z.; Mapingure, M.P.; Nathoo, K.; Stray-Pedersen, B. The burden and predictors of cognitive impairment among 6- to 8-year-old children infected and uninfected with HIV from Harare, Zimbabwe: A cross-sectional study. Child Neuropsychol. J. Norm. Abnorm. Dev. Child. Adolesc. 2015, 21, 106–120. [Google Scholar] [CrossRef]
  45. Mabaya, L.; Matarira, H.T.; Tanyanyiwa, D.M.; Musarurwa, C.; Mukwembi, J. Growth Trajectories of HIV Exposed and HIV Unexposed Infants. A Prospective Study in Gweru, Zimbabwe. Glob. Pediatr. Health 2021, 8, 2333794X21990338. [Google Scholar] [CrossRef]
  46. Nabakwe, E.C.; Ettyang, G.A.; Egesah, O.B.; Mwangi, A. Anemia and nutritional status of HIV-exposed infants and HIV-infected mothers in Busia County, Western Kenya. East Afr. Med. J. 2018, 95, 1535–1547. [Google Scholar]
  47. Neary, J.; Langat, A.; Singa, B.; Kinuthia, J.; Itindi, J.; Nyaboe, E.; Ng’anga, L.W.; Katana, A.; John-Stewart, G.C.; McGrath, C.J. Higher prevalence of stunting and poor growth outcomes in HIV-exposed uninfected than HIV-unexposed infants in Kenya. AIDS 2022, 36, 605–610. [Google Scholar] [CrossRef]
  48. Rossouw, M.E.; Cornell, M.; Cotton, M.F.; Esser, M.M. Feeding practices and nutritional status of HIV-exposed and HIV-unexposed infants in the Western Cape. South. Afr. J. HIV Med. 2016, 17, 398. [Google Scholar] [CrossRef]
  49. Szanyi, J.; Walles, J.K.; Tesfaye, F.; Gudeta, A.N.; Björkman, P. Intrauterine HIV exposure is associated with linear growth restriction among Ethiopian children in the first 18 months of life. Trop. Med. Int. Health 2022, 27, 823–830. [Google Scholar] [CrossRef] [PubMed]
  50. Springer, P.E.; Slogrove, A.L.; Kidd, M.; Kalk, E.; Bettinger, J.A.; Esser, M.M.; Cotton, M.F.; Zunza, M.; Molteno, C.D.; Kruger, M. Neurodevelopmental and behavioural outcomes of HIV-exposed uninfected and HIV-unexposed children at 2-3 years of age in Cape Town, South Africa. AIDS Care 2020, 32, 411–419. [Google Scholar] [CrossRef] [PubMed]
  51. Struyf, T.; Dube, Q.; Cromwell, E.A.; Sheahan, A.D.; Heyderman, R.S.; Van Rie, A. The effect of HIV infection and exposure on cognitive development in the first two years of life in Malawi. Eur. J. Paediatr. Neurol. EJPN Off. J. Eur. Paediatr. Neurol. Soc. 2020, 25, 157–164. [Google Scholar] [CrossRef] [PubMed]
  52. Tshiambara, P.; Hoffman, M.; Legodi, H.; Botha, T.; Mulol, H.; Pisa, P.; Feucht, U. Comparison of Feeding Practices and Growth of Urbanized African Infants Aged 6–12 Months Old by Maternal HIV Status in Gauteng Province, South Africa. Nutrients 2023, 15, 1500. [Google Scholar] [CrossRef]
  53. König Walles, J.; Balcha, T.T.; Winqvist, N.; Björkman, P. Growth pattern in Ethiopian infants—The impact of exposure to maternal HIV infection in relation to socio-economic factors. Glob. Health Action 2017, 10, 1296726. [Google Scholar] [CrossRef]
  54. Floridia, M.; Orlando, S.; Andreotti, M.; Mphwere, R.; Kavalo, T.; Ciccacci, F.; Scarcella, P.; Marazzi, M.C.; Giuliano, M. A 12-month Prospective Study of HIV-infected and HIV-uninfected Women and Their Infants in Malawi: Comparative Analysis of Clinical Events and Infant Growth. Am. J. Trop. Med. Hyg. 2023, 108, 394–402. [Google Scholar] [CrossRef]
  55. Brennan, A.T.; Bonawitz, R.; Gill, C.J.; Thea, D.M.; Kleinman, M.; Useem, J.; Garrison, L.; Ceccarelli, R.; Udokwu, C.; Long, L.; et al. A meta-analysis assessing all-cause mortality in HIV-exposed uninfected compared with HIV-unexposed uninfected infants and children. AIDS 2016, 30, 2351–2360. [Google Scholar] [CrossRef]
  56. Evans, C.; Jones, C.E.; Prendergast, A.J. HIV-exposed, uninfected infants: New global challenges in the era of paediatric HIV elimination. Lancet Infect. Dis. 2016, 16, e92–e107. [Google Scholar] [CrossRef]
  57. UNICEF. State of the World’s Children 2021: On My Mind—Promoting, Protecting and Caring for Children’s Mental Health; United Nations Children’s Fund: New York, NY, USA, 2022; Available online: https://www.unicef.org/reports/state-worlds-children-2021 (accessed on 2 May 2025).
  58. WHO. Malnutrition in Children; World Health Organization: Geneva, Switzerland, 2023. Available online: https://www.who.int/data/nutrition/nlis/info/malnutrition-in-children (accessed on 2 May 2025).
  59. Victora, C.G.; Christian, P.; Vidaletti, L.P.; Gatica-Domínguez, G.; Menon, P.; Black, R.E. Revisiting maternal and child undernutrition in low-income and middle-income countries: Variable progress towards an unfinished agenda. Lancet 2021, 397, 1388–1399. [Google Scholar] [CrossRef]
  60. Slogrove, A.L.; Powis, K.M.; Johnson, L.F.; Stover, J.; Mahy, M. Estimates of the global population of children who are HIV-exposed and uninfected, 2000–2018: A modelling study. Lancet Glob. Health 2020, 8, e67–e75. [Google Scholar] [CrossRef]
  61. Filteau, S. The HIV-exposed, uninfected African child. Trop. Med. Int. Health 2009, 14, 276–287. [Google Scholar] [CrossRef] [PubMed]
  62. FAO; IFAD; UNICEF; WFP; WHO. The State of Food Security and Nutrition in the World 2020: Transforming Food Systems for Affordable Healthy Diets; FAO: Rome, Italy, 2020; Available online: https://www.unicef.org/reports/state-of-food-security-and-nutrition-2020 (accessed on 3 May 2025).
  63. Modjadji, P. Socio-demographic Determinants of Overweight and Obesity Among Mothers of Primary School Children Living in a Rural Health and Demographic Surveillance System Site, South Africa. Open Public Health J. 2020, 13, 518–528. [Google Scholar] [CrossRef]
  64. Seabela, E.S.; Modjadji, P.; Mokwena, K.E. Facilitators and barriers associated with breastfeeding among mothers attending primary healthcare facilities in Mpumalanga, South Africa. Front. Nutr. 2023, 10, 1062817. [Google Scholar] [CrossRef] [PubMed]
  65. Augustino, G.; Anaeli, A.; Sunguya, B.F. Barriers to exclusive breastfeeding practice among HIV-positive mothers in Tanzania. An exploratory qualitative study. PLoS ONE 2024, 19, e0296593. [Google Scholar] [CrossRef]
  66. Modjadji, P.; Seabela, E.S.; Ntuli, B.; Madiba, S. Beliefs and Norms Influencing Initiation and Sustenance of Exclusive Breastfeeding: Experiences of Mothers in Primary Health Care Facilities in Ermelo, South Africa. Int. J. Environ. Res. Public Health 2023, 20, 1513. [Google Scholar] [CrossRef]
  67. Samburu, B.M.; Kimiywe, J.; Young, S.L.; Wekesah, F.M.; Wanjohi, M.N.; Muriuki, P.; Madise, N.J.; Griffiths, P.L.; Kimani-Murage, E.W. Realities and challenges of breastfeeding policy in the context of HIV: A qualitative study on community perspectives on facilitators and barriers related to breastfeeding among HIV positive mothers in Baringo County, Kenya. Int. Breastfeed. J. 2021, 16, 39. [Google Scholar] [CrossRef]
Figure 1. A Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) flow chart representing the selection of studies.
Figure 1. A Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) flow chart representing the selection of studies.
Children 12 00624 g001
Figure 2. Odds ratio in weight for age Z-score (WAZ)/underweight in HIV-exposed uninfected versus HIV-unexposed infants in Africa [28,39,40,41,42,43,44,45,46,47,48,49,51,52,53,54].
Figure 2. Odds ratio in weight for age Z-score (WAZ)/underweight in HIV-exposed uninfected versus HIV-unexposed infants in Africa [28,39,40,41,42,43,44,45,46,47,48,49,51,52,53,54].
Children 12 00624 g002
Figure 3. Prevalence of underweight in HEU and HUU infants. (A) Random effect meta-analysis showing the prevalence of underweight in HEU infants. (B) Random effect meta-analysis showing the prevalence of underweight in HUU infants [28,39,40,41,42,43,44,45,46,47,48,49,51,52,53,54].
Figure 3. Prevalence of underweight in HEU and HUU infants. (A) Random effect meta-analysis showing the prevalence of underweight in HEU infants. (B) Random effect meta-analysis showing the prevalence of underweight in HUU infants [28,39,40,41,42,43,44,45,46,47,48,49,51,52,53,54].
Children 12 00624 g003
Figure 4. Odds ratio of length for age Z-score (LAZ)/stunting in HEU versus HUU infants [28,39,40,41,42,43,44,45,47,48,49,51,52,53,54].
Figure 4. Odds ratio of length for age Z-score (LAZ)/stunting in HEU versus HUU infants [28,39,40,41,42,43,44,45,47,48,49,51,52,53,54].
Children 12 00624 g004
Figure 5. Prevalence of stunting in HEU and HUU. (A) Random effect meta-analysis showing the prevalence of stunting in HEU infants. (B) Random effect meta-analysis showing the prevalence of stunting in HUU infants [28,39,40,41,42,43,44,45,47,48,49,51,52,53,54].
Figure 5. Prevalence of stunting in HEU and HUU. (A) Random effect meta-analysis showing the prevalence of stunting in HEU infants. (B) Random effect meta-analysis showing the prevalence of stunting in HUU infants [28,39,40,41,42,43,44,45,47,48,49,51,52,53,54].
Children 12 00624 g005
Figure 6. The odds ratio on weight for length Z-score (WLZ)/wasting in HEU versus HUU infants in Africa [28,41,42,43,45,46,49,52,54].
Figure 6. The odds ratio on weight for length Z-score (WLZ)/wasting in HEU versus HUU infants in Africa [28,41,42,43,45,46,49,52,54].
Children 12 00624 g006
Figure 7. Prevalence of wasting in HEU and HUU. (A) Random effect meta-analysis showing the prevalence of wasting in HEU infants. (B) Random effect meta-analysis showing the prevalence of wasting in HUU infants [28,41,42,43,45,46,49,52,54].
Figure 7. Prevalence of wasting in HEU and HUU. (A) Random effect meta-analysis showing the prevalence of wasting in HEU infants. (B) Random effect meta-analysis showing the prevalence of wasting in HUU infants [28,41,42,43,45,46,49,52,54].
Children 12 00624 g007
Table 1. The characteristics of the included studies on growth patterns between HIV-exposed and -unexposed uninfected infants.
Table 1. The characteristics of the included studies on growth patterns between HIV-exposed and -unexposed uninfected infants.
AuthorCountryStudy DesignSample Size and Participant
Characteristics
OutcomesPrevalence in HEU (%)Prevalence in HUU
n (%)
Arinaitwe
et al., 2012 [39]
UgandaProspective,
longitudinal cohort
202 HIV-exposed
uninfected (HEU)
followed for 2 years.
99 HIV-unexposed
uninfected (HUU)
Underweight52 (26)23 (23)
Stunting71 (35)38 (38)
WastingNRNR
Bertran-Cobo
et al., 2022 [40]
South AfricaComplete case–cohort36 HEU followed
for 2 years.
47 HUU
Underweight2 (6.45)1 (2.44)
Stunting5 (16.13)5 (12.19)
Wasting0 (0)0 (0)
Brink
et al., 2014 [41]
South AfricaCross-sectional56 HEU followed
for 18 months.
77 HUU
Underweight32 (57.1)16 (20.8)
Stunting35 (62.5)34 (44.2)
Wasting14 (25)21 (27.3)
Chalashika
et al., 2017 [42]
BotswanaCross-sectional154 HEU followed
for 24 months.
259 HUU
Underweight24 (15.6)18 (6.9)
Stunting24 (15.6)19 (7.3)
Wasting23 (14.9)26 (10)
Floridia
et al., 2023 [54]
MalawiProspective
cohort
HEU 124, 120, 122
after 12 months of
follow-up
24 HUU followed
for 12 months
Underweight10 (8.1)1 (4.2)
Stunting27 (22.5)6 (25)
Wasting5 (4.1)1 (4.2)
Jumare
et al., 2019 [43]
NigeriaProspective
cohort
303 HEU followed
for 188 months.
108 HUU
Underweight48 (15.8)7 (6.2)
Stunting132 (44.3)33 (30.9)
Wasting12 (4.9)5 (4.9)
Kandawasvika et al., 2015 [44]ZimbabweCross-sectional121 HEU
153 HUU
Underweight13 (11)23 (15)
Stunting25 (21)32 (21)
WastingNRNR
Mabaya
et al., 2021 [45]
ZimbabweProspective
cohort
52 HEU followed
for 16 weeks.
57 HUU
Underweight2 (3.85)1 (1.75)
Stunting15 (28.85)0 (0)
Wasting2 (3.85)0 (0)
Nabakwe
et al., 2018 [46]
KenyaCross
Sectional
349 HEU
22 HUU
Underweight25 (89.3)3 (10.7)
StuntingNRNR
Wasting82 (94.3)5 (5.7)
Neary
et al., 2022 [47]
KenyaCross-sectional225 HEU with a
9-month follow-up
823 HUU
Underweight12 (27)66 (8)
Stunting45 (20)82 (10)
WastingNRNR
Pillay
et al., 2021 [28]
South AfricaCohort123 HEU with a
9-month follow-up
49 HUU
Underweight1 (0.82)0 (0)
Stunting7 (5.74)1 (20)
Wasting2 (1.64)2 (40)
Rossouw
et al., 2016 [48]
South AfricaProspective
cohort
18 HEU with an
18-month follow-up
21 HUU
Underweight0 (0)2 (10)
Stunting0 (0)4 (19)
Wasting0 (0)0 (0)
Szanyi
et al., 2022 [49]
EthiopiaProspective
Cohort
115 HEU with
18 months follow-up
1161 HUU
Underweight5 (4.35)46 (3.96)
Stunting32 (27.83)217 (18.69)
Wasting4 (3.48)55 (4.74)
Springer
et al., 2020 [50]
South AfricaProspective
Cohort
32 HEU
27 HUU
Underweight0 (0)0 (0)
Stunting2 (6)4 (14.8)
WastingNRNR
Struyf
et al., 2020 [51]
MalawiProspective
Cohort
289 HEU
170 HUU
Underweight44 (15.2)15 (8.5)
Stunting137 (46)62 (36.5)
WastingNRNR
Tshiambara
et al., 2023 [52]
South AfricaCross-sectional75 HEU with
12 months follow-up
80 HUU
Underweight4 (5.5)4 (5.1)
Stunting9 (12.3)3 (3.8)
Wasting4 (5.5)3 (3.9)
Walles
et al., 2017 [53]
EthiopiaCross-sectional302 HEU
358 HUU
Underweight17 (5.7)27 (6.7)
Stunting72 (25.1)73 (20.5)
WastingNRNR
HEU: HIV-exposed uninfected, HUU: HIV-unexposed uninfected, NR: not reported.
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

Modjadji, P.; Mokgalaboni, K.; Phoswa, W.N.; Mothiba, T.M.; Lebelo, S.L. Growth Patterns of HIV-Exposed and -Unexposed Infants in African Countries: A Systematic Review and Meta-Analysis. Children 2025, 12, 624. https://doi.org/10.3390/children12050624

AMA Style

Modjadji P, Mokgalaboni K, Phoswa WN, Mothiba TM, Lebelo SL. Growth Patterns of HIV-Exposed and -Unexposed Infants in African Countries: A Systematic Review and Meta-Analysis. Children. 2025; 12(5):624. https://doi.org/10.3390/children12050624

Chicago/Turabian Style

Modjadji, Perpetua, Kabelo Mokgalaboni, Wendy N. Phoswa, Tebogo Maria Mothiba, and Sogolo L. Lebelo. 2025. "Growth Patterns of HIV-Exposed and -Unexposed Infants in African Countries: A Systematic Review and Meta-Analysis" Children 12, no. 5: 624. https://doi.org/10.3390/children12050624

APA Style

Modjadji, P., Mokgalaboni, K., Phoswa, W. N., Mothiba, T. M., & Lebelo, S. L. (2025). Growth Patterns of HIV-Exposed and -Unexposed Infants in African Countries: A Systematic Review and Meta-Analysis. Children, 12(5), 624. https://doi.org/10.3390/children12050624

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