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Open Access

Peer-reviewed

Research Article

Body composition of children born HIV-exposed uninfected in rural Zimbabwe

  • Joe D. Piper ,

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

    j.piper@qmul.ac.uk

    Affiliations Zvitambo Institute for Maternal and Child Health Research, Harare, Zimbabwe, Blizard Institute, Queen Mary University of London, London, United Kingdom

    ⨯
  • Robert Ntozini,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

    Affiliation Zvitambo Institute for Maternal and Child Health Research, Harare, Zimbabwe

    ⨯
  • Idah Mapurisa,

    Roles Conceptualization, Data curation, Investigation, Methodology, Writing – review & editing

    Affiliation Zvitambo Institute for Maternal and Child Health Research, Harare, Zimbabwe

    ⨯
  • Tsitsi Mashedze,

    Roles Conceptualization, Data curation, Investigation, Methodology

    Affiliation Zvitambo Institute for Maternal and Child Health Research, Harare, Zimbabwe

    ⨯
  • Clever Mazhanga,

    Roles Conceptualization, Data curation, Investigation, Methodology, Project administration, Supervision

    Affiliation Zvitambo Institute for Maternal and Child Health Research, Harare, Zimbabwe

    ⨯
  • Florence D. Majo,

    Roles Project administration, Supervision

    Affiliation Zvitambo Institute for Maternal and Child Health Research, Harare, Zimbabwe

    ⨯
  • Bernard Chasekwa,

    Roles Data curation, Formal analysis, Validation, Writing – review & editing

    Affiliation Zvitambo Institute for Maternal and Child Health Research, Harare, Zimbabwe

    ⨯
  • Naume V. Tavengwa,

    Roles Conceptualization, Project administration, Supervision, Writing – review & editing

    Affiliation Zvitambo Institute for Maternal and Child Health Research, Harare, Zimbabwe

    ⨯
  • Kim Michaelsen,

    Roles Conceptualization, Methodology, Writing – review & editing

    Affiliation Department of Nutrition, Exercise and Sports, University of Copenhagen, Copenhagen, Denmark

    ⨯
  • Jean Humphrey,

    Roles Conceptualization, Funding acquisition, Resources, Visualization, Writing – review & editing

    Affiliations Zvitambo Institute for Maternal and Child Health Research, Harare, Zimbabwe, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America

    ⨯
  • Jonathan Wells,

    Roles Conceptualization, Formal analysis, Visualization, Writing – original draft

    Affiliation Population Policy and Practice Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, London, United Kingdom

    ⨯
  • Andrew J. Prendergast

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

    Affiliations Zvitambo Institute for Maternal and Child Health Research, Harare, Zimbabwe, Blizard Institute, Queen Mary University of London, London, United Kingdom

    ⨯

Abstract

Background

Globally, 15 million children were born HIV-exposed uninfected (CHEU) from mothers living with HIV. CHEU have increased mortality, morbidity and stunting compared to children HIV-unexposed (CHU). Our objective was to compare body composition between CHEU and CHU, which may underlie this vulnerability.

Methods

In a substudy among 223 children (36 CHEU and 187 CHU) enrolled in the Sanitation Hygiene Infant Nutrition Efficacy (SHINE) trial in rural Zimbabwe, we measured height, knee-heel length, weight, calf circumference, skinfold thicknesses (triceps, subscapular and calf), and bio-electrical impedance at 2 years of age. Generalised estimating equations were used to compare body composition between CHEU and CHU, and interactions with linear growth and birthweight.

Results

CHEU had significantly lower length-for-age, knee-heel length, weight-for-age, mid-upper arm circumference and calf circumference compared to CHU. CHEU had a lower impedance index (adjusted mean difference −0.49, 95% CI −0.87, −0.11), reflecting less lean mass, and lower skinfold thicknesses (subscapular Z-score adjusted mean difference −0.49 (95% CI −0.97, −0.02); triceps Z-score −0.48 (95% CI −0.83, −0.13)), indicating reduced subcutaneous fat. In early-life, CHEU had lower birthweight. However, no significant interaction between stunting or birthweight and HIV exposure was observed for body composition outcomes.

Conclusion

CHEU have a distinct pattern of body composition by 2 years of age, characterised by reduced lean and fat mass compared to CHU which was not explained by reduced linear growth or lower birthweight. This pattern of early-life growth may contribute to the increased vulnerability of CHEU to mortality, morbidity and reduced neurodevelopment.

Citation: Piper JD, Ntozini R, Mapurisa I, Mashedze T, Mazhanga C, Majo FD, et al. (2026) Body composition of children born HIV-exposed uninfected in rural Zimbabwe. PLoS One 21(9): e0319542. https://doi.org/10.1371/journal.pone.0319542

Editor: Emma K. Kalk, University of Cape Town, SOUTH AFRICA

Received: February 4, 2025; Accepted: July 27, 2026; Published: September 11, 2026

Copyright: © 2026 Piper et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The minimal dataset are within the manuscript and its Supporting Information files, specifically uploaded within the Supporting Information file “251017_CBHF_Bodycomp_SHINE_anonymise.dta”.

Funding: JP was funded by an academic clinical fellowship provided by NIHR (ACF-2015-19-002) and body composition equipment funded by Barts Charity, UK. The SHINE trial with JH as Principal Investigator was funded by the Bill & Melinda Gates Foundation (OPP1021542 to Johns Hopkins Bloomberg School of Public Health and OPP1143707 to Zvitambo Institute for Maternal and Child Health Research), the UK Department for International Development, the Swiss Agency for Development and Cooperation (8106727), UNICEF (PCA-2017-0002), and the US National Institutes of Health (R01 HD060338/HD/NICHD). AJP received funding from the Wellcome Trust, (093768/Z/10/Z and 108065/Z/15/Z).

Competing interests: The authors have declared that no competing interests exist.

Introduction

The success of prevention of mother-to-child transmission (PMTCT) of HIV has driven an increase in the number of children who are HIV-exposed uninfected (CHEU) [1]. By 2021, the number of CHEU was estimated at 16 million globally, and this population continues to grow [2]. In sub-Saharan Africa, CHEU are more likely to be born premature or small-for-gestational age [3], and have poorer postnatal growth compared to children unexposed to HIV [4–6]. In rural Zimbabwe, in the current ART era, half of all CHEU are stunted by 18 months of age [1], compared to ~30% of children who are HIV-unexposed (CHU) [7]. Stunting has effects across the life-course, and is associated with reduced educational attainment [8]. CHEU therefore represent a vulnerable group, who fail to reach their growth and developmental potential in early life.

The causes and consequences of growth failure in CHEU remain poorly understood. Mechanistic insights into the pattern and timing of growth failure would be valuable to inform interventions and to predict long-term health outcomes. Measuring body composition (i.e., fat and lean mass) provides useful insights into the quality of growth, and can inform future homeostatic reserve [9]. There is evidence that both fat and lean mass are reduced in stunting [10,11]. Fat mass provides short-term benefits for immune function [11] and survival [12]; however, it also has longer-term metabolic health costs [9]. The distribution of fat within the body is also important: genes associated with immune function are highly expressed in intra-abdominal fat [13] which helps drive inflammation [14]. An ecogeographical analysis reported that central compared to peripheral fat mass is linked more closely with pathogen load across populations, indicating its role in providing energy for immune function [15]. Lean mass is associated with increased organ size [16] and reduced cardio-metabolic risk [17]. Lean mass is also much more closely associated with neurodevelopment than is fat mass [18].

Studies that have performed more detailed body composition among CHEU in low- and middle-income countries (LMIC) have generally shown poorer growth compared to CHU. However, there are differences between studies: the sum of skinfolds was preserved in one study of 295 infants in Kenya [19], but lower skinfold thicknesses among CHEU were found in a study of 238 infants in Uganda [20], where worse food insecurity suggested a prioritisation of central skinfold thickness. In the USA, one cross-sectional study showed lower birthweight and a trend towards decreasing triceps and subscapular skinfold thicknesses in CHEU at 2 years of age, compared to CHU [21]. A recent cross-sectional study of premature CHEU infants from South Africa suggested they were smaller in weight and length at birth, gained weight more slowly and had reduced skinfold thicknesses up to 28 days of age [22]. Follow-up of CHEU birth cohorts at school-age in Zambia suggested lower height, mid-upper-arm and thigh circumference and reduced fat percentages, when estimated with bioimpedance [23]. There is a pressing need for further characterisation of CHEU compared to CHU in sub-Saharan Africa, where the majority of CHEU live, especially during the first two years after birth when stunting prevalence peaks.

Here we report body composition measurements in rural Zimbabwean CHEU compared to CHU at 2 years of age, (the end of the first 1000 days, and a time of peak stunting). These children were recruited to a sub-study within the SHINE cluster-randomised trial in Zimbabwe [24]. We used bio-impedance, skinfold thicknesses, anthropometry and knee-heel length to provide a comprehensive assessment of growth quality and future metabolic disease risk. We hypothesised that CHEU compared to CHU would have worse growth in measures of lean mass (bioimpedance), fat mass (skinfold thicknesses) and relatively shorter legs (knee-heel length), and that these differences would not entirely be explained by lower birthweight and more stunting among CHEU.

Materials and methods

Participants

Body composition measurements were performed in a substudy of the Sanitation Hygiene Infant Nutrition Efficacy (SHINE) trial (registered at Clinical trials.gov, NCT01824940). Mothers gave written informed consent to participate in the SHINE trial, and additional consent for the body composition sub-study, which was approved by the Medical Research Council of Zimbabwe (MRCZ/A/1675) and Johns Hopkins Bloomberg School of Public Health (IRB 4205). The design, methods and outcomes of SHINE have been previously reported [7,25,26] and the protocol is available on Open Science Framework (https://osf.io/w93hy/). In brief, SHINE tested the independent and combined effects of a water, sanitation and hygiene (WASH) intervention and an infant and young child feeding (IYCF) intervention on stunting and anaemia at 18 months of age. The study area comprised two rural districts of central Zimbabwe, which were divided into 212 clusters, defined as the catchment area of 1–4 Community Health Workers (CHWs) employed by the Ministry of Health and Child Care (MoHCC). Between November 2012 and March 2015, CHWs identified pregnancies through prospective surveillance; women were eligible to enroll if they permanently resided in one of the rural study clusters, were confirmed pregnant and provided written informed consent. HIV testing, definitions of CHEU and CHU are detailed in supporting information in S1 File.

Body composition substudy

Children were eligible for the body composition substudy if they i) completed the trial endpoint visit at 18 months of age; ii) lived in the catchment area of the substudy, which comprised approximately one-quarter of the total SHINE area, constituting 52 trial clusters; and iii) were between 102–112 weeks of age during the period of enrolment.

Between 20th September 2016–2nd May 2017, children had a home visit by two trained research nurses to measure anthropometry (height, weight, head circumference and mid-upper arm circumference) using standard methods [7]. Body composition was measured by bio-impedance analysis, skinfold thicknesses using Holtain calipers, and knee-heel length using a knemometer. A locally-built case ensured the equipment was protected whilst being transported between households by motorbike.

Skinfold thickness

Skinfold thickness (Fig 1a) measures the subcutaneous fat layer around the body and describes its distribution. Subscapular, triceps and maximal calf skinfold thicknesses were measured to the nearest 0.2 mm using a skinfold caliper (Holtain, Crosswell, Wales) according to a standard operating procedure (SOP), with the median of three readings used. The absolute values of the triceps and calf skinfolds were combined for a composite measure of peripheral fat, whilst subscapular skinfolds provided a central fat measurement. All three skinfolds were summed to provide the total skinfold thickness. In addition, triceps and subscapular Z-scores were calculated based on WHO Reference growth charts (calf skinfolds do not have available growth charts).

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Fig 1. Body composition measurement techniques in rural Zimbabwe.

a) Skinfold thickness (here demonstrating triceps skinfold), b) Bioimpedance analysis (BIA) showing electrodes attached to right hand and foot of the child, c) Positioning for knee-heel length measurement. Printed under a CC BY license with permission from JDP who is the original copyright holder of these images.

https://doi.org/10.1371/journal.pone.0319542.g001

Bio-impedance analysis

Bio-impedance analysis (BIA; Fig 1b) can be used to assess tissue health and estimate lean mass, using an imperceptible electrical signal between the hand and foot [27]. Tissue and cellular health are indicated by the phase angle, which provides an estimate of membrane integrity [28,29]. BIA was measured using the Bodystat 1500 MDD instrument (BodyStat, Douglas, Isle of Man). Once set up at the household, calibration was performed before each set of BIA measurements using the 500 Ohm calibration resistor provided (the acceptable range was 497–503 Ohms). The child was measured lying on a padded mat with arms and legs straight, as previously described [30,31]. The right hand and foot were cleaned and electrodes were attached. There were no restrictions on fluid intake for children to ensure they remained calm. BIA measurements were performed in duplicate according to an SOP.

Raw BIA data were used to generate two rankings of lean mass, and one of cellular quality, as follows. First, an estimate of absolute lean mass was obtained from the impedance index, calculated as (Ht2/Z), where Ht is height and Z is impedance measured at 50 kHz. In any population, there is a strong association of Ht2/Z with lean mass. If this association is calibrated, using a direct measurement of lean mass as the reference method, lean mass can be predicted from Ht2/Z, and fat mass can be estimated as the difference of lean mass and weight. However, in the absence of a calibration equation, population rankings of Ht2/Z and lean mass are near-identical, hence the raw data will provide similar epidemiological results [29]. Therefore, in this population, Ht2/Z was used as a proxy for lean mass. Second, to correct for body size, lean mass is often adjusted for the square of height to give the lean mass index, expressed in the same kg/m2 units as BMI. However, when calculating lean mass index from BIA data, the data are effectively processed as [Ht2/Z/Ht2], which simplifies to 1/Z. As demonstrated previously, rankings of 1/Z are near-identical to rankings of lean mass index [29], hence 1/Z was used as a proxy for lean mass independent of height. Third, phase angle was also used as a measure of cellular health [29]. Data were excluded if the phase angle (PA) was more than 80, which is considered implausible [32], or if there was poor repeatability (duplicate value differences  > 0.30 for PA, and ≥6.0 Ω for either resistance (R) or reactance (Xc)).

Knee-heel length

Knee-heel length (Fig 1c) was recorded using a knemometer, with the median of three readings used. Two different types of knemometer were used and their correlation compared on a Bland-Altman plot (S3 Fig in S1 File). Further detail is available in (Supporting information, supplementary methods 1 in S1 File).

Statistical analysis and sample size

Sample size was determined by the feasibility of recruitment. A detectable effect size of 0.5 SD for differences between CHEU and CHU was estimated with 80% power, assuming 52 clusters and intra-cluster correlation coefficient of 0.05, with alpha 0.05. Analysis was performed using Stata 15.0. Associations between body composition measures and length-for-age Z-score (LAZ) at 24 months were undertaken to explore how body composition varied with linear growth. Then four different models were used to evaluate differences in body composition between CHEU and CHU. Model 1 was an unadjusted analysis using generalised estimating equations (GEE) with an exchangeable working correlation structure to account for clustering. Model 2 was adjusted for trial arm only. Model 3 was adjusted for trial factors affecting body composition measurements (study nurse performing the measurement, exact child age at assessment, and calendar month of birth) in addition to trial arm. Calendar month of birth was used to adjust for seasonality. Model 4 was additionally adjusted for potential socioeconomic and demographic confounders which are not likely to be on the causal pathway leading from HIV exposure to body composition outcomes (see supporting information, Supplementary Material 1 in S1 File).

We also tested whether the associations between HIV exposure and body composition outcomes varied by i) stunting at 2 years, ii) length-for-age Z-score (LAZ) at 2 years and iii) birthweight, using P < 0.1 as evidence of an interaction. Initially, we assumed that body composition increased similarly with linear growth and birthweight across all children. We then examined the interaction between HIV exposure and linear growth (stunting at 2 years) to determine whether the relationship between body composition and postnatal growth differed by HIV exposure status. We conducted a similar analysis for LAZ at 2 years. Finally, we tested for an interaction with birthweight to assess whether the association between body composition and birthweight differed by HIV exposure. These analyses were performed to determine whether differences in body composition among HIV-exposed children could be partly explained by birthweight or postnatal growth.

Results

Between November 2012 and March 2015, 5280 pregnant women were enrolled from 211 clusters at median 12 (IQR 9, 16) gestational weeks. Of 4845 live births, 4427 children were evaluated at 18 months, including 1004 from the substudy catchment area. At mean age 24 (SD = 0.4) months, 230 children from 52 clusters were enrolled into the body composition substudy between November 2016 and June 2017 [33]. Clusters were defined by the catchment area of 1–4 village health workers, based on the SHINE trial design [34]. Of the 230 enrolled children, 4 were excluded due to unknown maternal HIV status during pregnancy. Of the 226 remaining children, 1 was HIV-positive and 2 had unknown HIV status at 18 months, and were excluded from the analysis, leaving 223 children, of whom 36 were CHEU and 187 CHU (See supporting information, S1 Fig CONSORT diagram). There were no recorded harms from this study.

Baseline characteristics

Baseline characteristics of children who were enrolled or not enrolled in the body composition sub-study are shown (See supporting information, S1 Table in S1 File). There were no significant differences in distribution by intervention arm, maternal schooling, maternal height, household wealth quintile, infant sex or birthweight. The body composition sub-study enrolled slightly older mothers (27.9 vs 26.1 years), with some differences in the distribution of religions, and a lower Edinburgh Postnatal Depression Scale (0.9 vs 3.2). HIV-positive mothers in the body composition sub-study, compared to HIV-positive mothers not enrolled, had a lower CD4 count during pregnancy (mean 427 vs. 487 cells/mm3) but no significant differences in ART regimen. Enrolled households had a lower Coping Strategies Index (mean score 0 compared to 1) than those not enrolled, indicating improved food security. Enrolled children had a marginally higher mean length-for-age Z-score than those not enrolled (−0.78 vs −0.88), but no significant difference in birthweight.

Baseline characteristics of CHEU and CHU enrolled in the body composition substudy, together with their mothers, are shown in Table 1. There was no significant difference in trial arm distribution, household characteristics or maternal characteristics, apart from older maternal age among CHEU versus CHU. Of note, CHEU versus CHU had a significantly lower mean birthweight (2.8 vs. 3.1 kg) with a significantly higher proportion of low birthweight (<2.5 kg) than CHU.

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Table 1. Baseline characteristics of children born HIV-exposed uninfected (CHEU) compared to children HIV-unexposed (CHU).

https://doi.org/10.1371/journal.pone.0319542.t001

Body composition results

Initial plots used Least-Squares linear regression to investigate associations across the whole cohort (Fig 2). At 2 years of age, mean (SD) LAZ was −1.47 (1.07) and 36/223 (16%) were stunted. Fig 2 shows the associations between body composition parameters and LAZ in the body composition substudy. Total skinfolds were not significantly associated with unit increases in LAZ (0.35, 95%CI −0.15, 0.85, p = 0.17; Fig 2A). By contrast, the lean mass index increased by 0.23 Ohms-1 per unit rise in LAZ (95%CI 0.06, 0.38, p = 0.005; Fig 2B). This shows that even after correcting for the effect of height on lean mass, the lean mass index shows a small but significant relationship with height. Each unit increase in LAZ was associated with an increase of 0.92 cm in knee-heel length (95%CI 0.83, 1.01, p < 0.001; Fig 2C) and 0.36 Z-score increase in MUAC (95%CI 0.27, 0.46, p < 0.001). Every 1 Kg increase in birthweight was associated with a 0.70 increase in LAZ at 2 years (95% CI 0.37, 1.03, p < 0.001).

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Fig 2. Associations between body composition and LAZ at 2 years of age.

Data are shown for a total of 223 CHEU and CHU combined. Black square = CHEU, hollow circle = CHU. Line of best fit is from a linear regression model with shading representing the 95% confidence interval. A) Total skinfold thickness. B) Lean mass index. C) Knee-heel length. D) MUAC Z-score.

https://doi.org/10.1371/journal.pone.0319542.g002

Body composition of CHEU vs. CHU

Table 2 shows the absolute body composition values among CHEU and CHU. Table 3 compares body composition of CHEU versus CHU, using four different models. In the unadjusted model, CHEU had lower LAZ, WAZ, MUAC and HCZ compared to CHU, as previously reported in the whole cohort [35]. In addition, calf circumference, knee-heel length, peripheral skinfolds, total skinfolds and impedance index were all reduced in CHEU versus CHU. There was no significant difference between groups for lean mass index or phase angle. When adjusted for trial arm only (model 2), findings were similar. When adjusted for trial arm, study nurse, exact age, sex and date of visit (model 3), HCZ was no longer significantly different between groups but other findings remained similar. Model 4 included further adjustments for maternal height, maternal education, maternal MUAC during pregnancy, religion, maternal Edinburgh Postnatal Depression scale, wealth index quintile, and household size. In this model, there was only weak evidence that HCZ and calf skinfolds were significantly different between groups, while other inferences remained similar.

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Table 2. Body composition values of CHU and CHEU at 2 years of age.

https://doi.org/10.1371/journal.pone.0319542.t002

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Table 3. Comparison of body composition of CHEU with CHU at 2 years of age.

https://doi.org/10.1371/journal.pone.0319542.t003

Taken together, CHEU at 2 years of age had evidence of poorer growth across a range of measures in all models. We did not find any evidence of interaction between HIV-exposure and stunting, LAZ or birthweight on any body composition outcome at 2 years (P > 0.10). Therefore, HIV exposure appears to be independently associated with outcomes of reduced growth, lean mass and skinfold thicknesses at age 2 years, and these findings cannot be attributed solely to restricted antenatal growth (i.e., lower birthweight) or poor postnatal linear growth (i.e., reduced LAZ) among CHEU.

Discussion

CHEU are a vulnerable population with reduced growth, development and survival [1]. This study characterised CHEU body composition measurements in a cohort of rural Zimbabwean children to gain further insight into markers of long-term growth and health. We found significant differences in body composition at 2 years of age among CHEU compared to CHU, as summarised in supporting information, S2 Fig in S1 File. CHEU had evidence of reduced weight, height and mid-upper arm circumference, accompanied by lower lean mass and skinfold thicknesses, even after adjusting for multiple social and environmental confounders. There was no significant interaction with stunting, LAZ or birthweight. Together, these body composition measurements indicate a restricted pattern of growth which may contribute to the disparities in morbidity, mortality and neurodevelopment between CHEU and CHU. Collectively, our findings highlight how HIV exposure shapes the pattern and prioritisation of growth in the first thousand days, and indicate the need for longer-term follow-up of CHEU in sub-Saharan Africa to evaluate non-communicable disease (NCD) risks at older ages.

The effects of antenatal HIV exposure in this cohort were evident in early life: CHEU had lower birthweights and a two-fold higher proportion of stunting at 2 years (52.8%) compared to CHU (26.2%). However, the higher prevalence of stunting did not entirely explain the body composition differences between CHEU and CHU at 2 years of age, since we did not find any evidence of interaction between HIV exposure and stunting or LAZ on any growth or body composition outcome. We also found no evidence of interaction between HIV exposure and birthweight on any body composition outcomes at 2 years of age. Therefore, whilst CHEU were lighter at birth (Table 1), this lack of a statistically significant interaction on 2 year body composition outcomes suggested these differences were not solely due to antenatal growth restriction. Instead, there appears to be a distinct growth phenotype in CHEU, characterised by reduced lean and fat mass compared to CHU.

Lean mass as estimated by the impedance index was reduced in CHEU [11]. This is important as lean mass is associated with improved physical function [36], cognitive function [37] and reduced risk of chronic disease [38,39]. Low lean mass suggests a reduced ‘metabolic capacity’ for homeostasis of key physiological parameters including glucose and blood pressure [9]. With later exposure to a ‘metabolic load’ caused by obesogenic factors such as diet or reduced exercise, this causes greater susceptibility to chronic diseases such as diabetes and hypertension, in the so-called capacity-load model [9]. For example, survivors of severe malnutrition in childhood have been observed to have shorter height [40], as well as higher waist circumference and risk of metabolic syndrome [41]. Lean mass is itself an important marker of quality of growth in response to nutrition, particularly in the first 1000 days. After this, organ growth becomes increasingly canalised by growth hormone so it closely follows growth in linear stature [9,42,43]. In this cohort, the knee-heel length was reduced by approximately one-third of the overall length. This knee-heel length to total length ratio is similar to that previously measured among HIV-unexposed children in Denmark [44], suggesting that knee-heel length to total length proportions are conserved for both CHEU and CHU. Knee-heel length may provide further insights into the quality of growth. A study among older stunted children in Nepal has shown relative leg length or total height may be a proxy of organ (kidney) size and later cardio-metabolic risk factors such as higher blood pressure, so this may be an early indicator of future vulnerability to NCD risk [16].

CHEU had reduced skinfold thicknesses but this was not associated with height. Given the higher mortality among CHEU in this population [45], conserved skinfold thickness may confer a short-term survival benefit for children who are HIV-unexposed. These effects are also important for later health as the first thousand days is a crucial window for generating the trajectory of both adipocyte number and adipose depots [46,47]. Reduced skinfold thicknesses have been previously observed in CHEU in infancy; [48] we extend these findings in the current cohort by confirming that this difference is still evident at 2 years of age. Furthermore, the lack of any significant interaction of 2 year-old body composition with birthweight or LAZ suggests this is an ongoing postnatal restriction in subcutaneous fat. The reduction of subcutaneous adipose tissue in CHEU may reflect the metabolic cost of ongoing inflammation [49]. There is evidence of both innate and adaptive immune activation in CHEU, reflecting a metabolically costly pro-inflammatory milieu [1], as well as the presence of other inflammatory drivers such as cytomegalovirus [50]. Reduced fat mass may be partly mediated by leptin which controls lipoprotein functions, acute phase reactants, glucocorticoid metabolism, inflammation and immune function [51]. In one South African study, CHEU aged 7–11 years were 50% less likely to have excess fat compared to CHU, whilst breastfeeding was protective against obesity for both CHEU and CHU [52]. Trajectories of CHEU compared to CHU have shown some variability, with a study in Zambia suggesting poor growth was universal for both CHEU and CHU [53]. However, a South African study suggested CHEU have significantly worse growth trajectories [54], similar to the SHINE cohort [35]. It is also plausible that the antenatal exposures of CHEU to both HIV and ART may set a trajectory for body composition similar to children who are living with HIV. With HIV infection, patterns of abnormal fat distribution vary from peripheral fat wasting alone or in combination with central fat accumulation [55]. For children living with HIV, lipoatrophy has been observed with reduced skinfold thicknesses, arm and leg circumferences [56], similar to that observed in this study. The intrauterine exposure to antiretrovirals also represent a plausible mechanism for the differences in body composition observed. Antiretrovirals have been associated with mitochondrial [57], neurologic and other toxicities [57] that may contribute to low birthweight [58,59], increased stunting in children [60] and therefore also altered body composition. For example, in an American cohort of CHEU, reduced skinfolds were postulated to be partly due to mitochondrial changes induced by antenatal HIV or ART exposures [61]. Future work characterising these biological mechanisms would be valuable, including measuring mitochondrial function and stability within CHEU [62] as well as indirect calorimetry to calculate resting energy expenditure, which is higher in children living with HIV (CLWH) [63]. Inflammatory and growth markers perturbed in early life among CHEU, such as CRP, IGF-1 [64] and leptin/adiponectin [65], should be monitored alongside other body composition drivers such as insulin sensitivity [66] and bone mineral density, which is also perturbed in CLWH [67]. Further insights from breast milk [68], gut inflammation, microbiota [69] and metabolomics [70] may also illuminate the drivers for these body composition differences. There is some evidence that differences in CHEU body composition may reduce by school-age [71], but long-term CHEU outcomes remain poorly understood.

This study provides additional information on early-life growth among CHEU and CHU, suggesting reduced lean mass in addition to reduced skinfold thickness. This supports the reduced length and skinfolds previously observed in Uganda at 12 months, which similarly had a high burden of childhood stunting [20]. We used a range of standardized techniques to characterise the quality of growth, and deployed rigorous HIV testing algorithms to correctly identify CHEU and CHU. We also demonstrated the techniques were fully portable and suitable for remote areas accessible by motorbike. This study also has some limitations. Gestational age was not available due to a lack of ultrasound dating scans. Therefore, it was not possible to explore if size-for-gestational-age was different by HIV status in this sample. The small number of CHEU (36) was also a limitation, particularly for the covariates included in adjusted models. The duration of breastfeeding was also not available, although reported breastfeeding rates >96% across all arms [7]. Children were recruited from a convenience sample in one part of the study area, so there may be some unintentional selection bias. However, baseline characteristics were broadly similar between those enrolled into the body composition sub‐study and the larger SHINE trial cohort. At baseline, only 40% of SHINE households met the minimum dietary diversity score, but by 12 months the IYCF arm had improved dietary diversity and iron-rich foods [7]. Of note, CHEU and CHU responded differently to the trial interventions, with CHEU randomised to IYCF showing average LAZ gains of 0·26 (95% CI 0·09–0·43) [26] compared to 0·16 (95% CI 0·08–0·23) among CHU [7]. Trial intervention arm was included in all adjusted analyses, but the study was not powered to examine the effect of the IYCF and WASH interventions on body composition. Evidence from the whole SHINE cohort suggested that the IYCF intervention improved growth across the cohort [7], particularly in CHEU [26]. Therefore it is plausible that postnatal factors such as nutritional supplements can improve growth, and mitigate stunting, as supported by a recent meta-analysis [72]. We extrapolate from this sub-study that improved linear growth could plausibly improve lean mass and knee-heel length but not skinfold thickness (given skinfold thickness was not associated with LAZ), but further studies of the effect of IYCF on body composition are needed. Finally, there were too few ART‐unexposed CHEU to explore the impact of ART (or specific regimens) on body composition or birthweight [59]. Most HIV‐positive mothers in SHINE received ART during the antenatal period, three‐quarters of whom were on a tenofovir‐based regimen. Furthermore, mothers were not randomized to ART use or regimen, so it would be difficult to ascertain whether any associations were due to specific ART.

Conclusions

In conclusion the body composition of CHEU compared to CHU at 2 years of age shows clear reductions in subcutaneous fat and lean mass, which may illustrate both short-term vulnerabilities in health and mortality risk as well as long-term health outcomes. These differences were not wholly explained by the observed lower birthweight and reduced linear growth in CHEU, suggesting that other factors further restrict the quality of growth observed at 2 years, which may include HIV and ART exposure, or household socio-environmental factors. These results highlight the importance of the early-life environment in setting growth and body composition trajectories which are observable at 2 years of age. Future work exploring biological mechanisms includes further characterising the mitochondrial, gut, metabolic and inflammatory perturbations that may alter growth in CHEU. Longer term follow-up is required to monitor these trajectories further and to ascertain differences in NCD risk between CHEU and CHU. As the global population of CHEU grows and matures, there is clear need to adopt a life-course approach to identifying and supporting children at all stages [2], to promote long-term health, wellbeing and human capital.

Supporting information

S1 File. S1 Fig. Consort diagram for study.

212 clusters were randomized, 53 in each of the four trial arms. After randomization, one cluster was excluded as it was determined to be in an urban area, one cluster was excluded as the VHW covering it mainly had clients outside the study area, and one more was merged into a neighbouring cluster based on subsequent data on VHW coverage. Three new cluster designations were created due to anomalies in the original mapping; for two of these, the trial arm was clear—the third contained areas that were in two trial arms, and was assigned to the underrepresented arm, resulting in 53 clusters in each arm. All of this occurred before enrolment began. When enrolment was completed, however, there were two clusters (SOC, and WASH+IYCF) in which no women were enrolled, leaving a total of 210 clusters available for analysis. 2SOC=Standard of Care; IYCF = Infant and Young Child Feeding; WASH = Water and Sanitation/Hygiene. S2 Fig. Summary of overall findings. Skinfold thickness, bioimpedance and knee-heel length provided measures of fat mass, lean mass and growth proportions. Children born HIV-exposed uninfected (CHEU) had reduced growth, fat, lean and knee-heel length compared to children born unexposed to HIV (CHU). S3 Fig. Comparison of knemometer types. Bland-Altman plot comparing custom-built and adapted knemometers, showing mean difference and 95% limits of agreement. S1 Table. Baseline characteristics of children enrolled or not enrolled into the body composition substudy.

https://doi.org/10.1371/journal.pone.0319542.s001

(DOCX)

S1 Data. Anonymised dataset of the body composition substudy.

https://doi.org/10.1371/journal.pone.0319542.s002

(DTA)

Acknowledgments

We thank Zvitambo staff for their help with this study, particularly Virginia Sauramba and Sandisiwe Ndlovu (compliance), Stephen Moyo (logistics), Theo Chidawanyika (IT) and Joice Tome for statistical assistance.

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