infant-attained size nor the onset of menarche were affected by maternal supplementation. These findings suggest that protein-energy supplements to pregnant ...
The Journal of Nutrition Community and International Nutrition
Dietary Supplementation of Rural Gambian Women during Pregnancy Does Not Affect Body Composition in Offspring at 11–17 Years of Age1,2 Sophie Hawkesworth,3* Andrew M. Prentice,3,4 Anthony J. C. Fulford,3,4 and Sophie E. Moore4 3 Medical Research Council International Nutrition Group, London School of Hygiene and Tropical Medicine, WC1E 7HT London, UK and 4Medical Research Council Keneba, Medical Research Council Laboratories, Fajara, The Gambia
Abstract Fetal nutrition is thought to be an important determinant of later disease risk, although evidence from randomizedcontrolled trials in humans is lacking. We followed children born during a protein-energy supplementation trial to investigate to what extent this maternal supplement, which improved birth weight, influenced offspring body composition in adolescence. Subjects were 1270 Gambian children (659 boys, 611 girls) aged 11–17 y whose mothers had participated in the original cluster-randomized trial and had received the supplement during pregnancy (intervention) or postpartum (control). Basic anthropometry was measured using standard techniques and fatness was assessed by bioelectrical impedance analysis and population-specific prediction equations. For boys, mean body fat was 12.6% for both intervention and control groups. Mean trunk fat was 11.9% in the intervention group and 12.0% in the control. Intervention girls had a mean body fat of 19.5% and trunk fat of 15.2%; for control girls, it was 19.3 and 14.8%, respectively. BMI, body fat, trunk fat, fat mass index, and fat-free mass index did not differ for either sex when analyzed with generalized estimating equations adjusted for age, maternal height, maternal parity, location, season of birth, and menarche in females. Neither infant-attained size nor the onset of menarche were affected by maternal supplementation. These findings suggest that protein-energy supplements to pregnant women, compared with lactating women, do not affect offspring body composition during adolescence. J. Nutr. 138: 2468–2473, 2008.
Introduction Adverse conditions during fetal development, reflected by low birth weight, have been associated with an increased risk of developing a range of adult chronic diseases (1–3). The effect on later body composition is less clear, however, and 2 recent reviews have concluded that there is strong evidence of a positive linear relationship between size at birth and later BMI [defined as weight (kg)/height (m)2] (4,5). Studies of the early life determinants of disease have historically relied on these observational birth weight associations as a proxy measure of fetal nutrition. More direct estimates of factors influencing fetal development, such as the maternal diet, are now required to further our understanding.
1
Supported by the European Union Sixth Framework Programme for Research and Technical Development of the European Union Community Early Nutrition Programming Project (FOOD-CT-2005-007036) and the UK Medical Research Council. 2 Author disclosures: S. Hawkesworth, A. Prentice, A. Fulford, and S. Moore, no conflicts of interest. * To whom correspondence should be addressed. E-mail: sophie.hawkesworth@ lshtm.ac.uk.
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With the exception of famine studies (6–8), evidence in humans of the effect of the maternal diet on body composition in the offspring is lacking due in part to the difficulties of measuring this particular exposure. A number of animal studies have demonstrated that reduced food intake during pregnancy (either general restriction or of a particular nutrient) is associated with greater adiposity in the offspring (9,10). Two community-based trials, one from Guatemala (11) and a recent study from India (12), of protein-energy supplementation provided to pregnant women and children have published follow-up data on offspring body composition in adolescence. Both trials report that children from intervention areas were taller than those in control areas, with a higher amount of fat-free mass (FFM),5 but that adiposity associated with receiving the intervention did not differ. The Guatemalan and Indian trials provided supplements to both pregnant women (and during lactation in the case of Guatemala) and their children, making it impossible to separate
5
Abbreviations used: BIA, bioelectrical impedance analysis; %FFM, percent fat-free mass; FFMI, fat-free mass index; FM, fat mass; FMI, fat mass index; GEE, generalized estimating equation; MRC, Medical Research Council.
0022-3166/08 $8.00 ª 2008 American Society for Nutrition. Manuscript received 20 August 2008. Initial review completed 27 August 2008. Revision accepted 24 September 2008. doi:10.3945/jn.108.098665.
the relative importance of the pre- or postnatal exposure. In The Gambia, we previously conducted a protein-energy supplementation trial in pregnant women, which was shown to increase birth weight (13). In the follow-up study presented here, we sought to determine the effect of this altered maternal nutrition on offspring body composition at 11–17 y of age and, in a subsample, the effect on early postnatal growth.
Materials and Methods The study was conducted in The Gambia, West Africa, between November 2005 and August 2006. Subjects were the offspring of women who had participated in a protein-energy supplementation trial in the rural West Kiang region between 1989 and 1994 (13). At followup, the children were aged between 11 and 17 y. Original trial. The original cluster-randomized controlled trial involved 28 villages in the West Kiang region of The Gambia and has been described elsewhere (13). Depending on the village assignment, all pregnant women received 2 locally produced biscuits per day, from either 20 wk of gestation to term (intervention villages) or for 20 wk postpartum (control villages). The biscuits were made from groundnuts, rice flour, sugar, and groundnut oil and 2 biscuits provided a maximum daily intake of 4250 kJ energy, 22 g protein, 56 g fat, 47 mg calcium, and 1.8 mg iron. There were 2047 live singleton births and birth weight was significantly higher among infants born to intervention mothers who had received the supplement during pregnancy than in control mothers who received the supplement postpartum. Mean birth weight in the intervention group increased by 136 g (95% CI: 79, 193; P , 0.001) overall, with a difference of 201 g (95% CI: 132, 270; P , 0.001) in the nutritionally poor ‘‘hungry’’ season. Perinatal mortality was also affected by supplementation status; the odds ratio of stillbirth in the intervention group was 0.47 (95% CI: 0.23, 0.99; P , 0.01) and for deaths in wk 1 of life it was 0.54 (95% CI: 0.35, 0.85; P , 0.001) (13). Throughout this manuscript, consistent with the original trial, children born to women who received the supplement during pregnancy will be referred to as the intervention group and those whose mothers received the supplement during lactation will be referred to as control. Present study. For the present study, we followed-up the offspring to assess any effect on body composition and on markers of cardiovascular disease risk (markers of which to be presented elsewhere). Descriptive data were missing for 44 children from the original trial (23 intervention and 21 control), making them impossible to trace and reducing the potential sample size to 2003. Children were recruited if they still resided in West Kiang or if they had moved to urban/peri-urban areas that were within a 1-h drive from the Medical Research Council (MRC) Laboratories, Fajara. In West Kiang, village meetings were held with the elders of each village to ensure that approval was obtained from the community. Scientific approval for the study was granted by the MRC. The Gambia Scientific Coordinating Committee and ethics permission was granted both by the Joint Gambian Government/MRC Ethics Committee and by the Ethics Committee at the London School of Hygiene and Tropical Medicine. Informed consent was obtained from the parent or guardian of each child before measurements were taken. Each participating child was seen on just 1 occasion, if possible in their village of residence. Both the principal investigator and all participating fieldworkers conducting the measurements were unaware of which treatment arm the subjects belonged to. Anthropometry. Height, weight, and triceps skin-fold thickness were measured by the same fully trained fieldworker in the majority (99%) of children to minimize observer bias. Weight was measured using dailycalibrated digital scales (Tanita) to the nearest 0.1 kg while subjects wore light clothing but no shoes. Standing height was measured with a dailycalibrated portable stadiometer (Leicester height measure, Seca 214) to the nearest 0.1 cm, also with the subject wearing no shoes and with head scarves removed. BMI was calculated as weight (kg)/height (m)2. Triceps skin-fold thickness was measured in triplicate on the left arm using
Holtain calipers (Holtain) and the mean reading to the nearest 0.2 mm was recorded. Mid-upper arm circumference was measured on the left arm to the nearest 0.1 cm using a waxed measuring tape while the subject’s arm was hanging by his or her side. Body composition was assessed via bioelectrical impedance analysis (BIA) using the Tanita BC-418MA analyzer (Tanita). This analyzer uses 8 electrodes to produce whole-body and segmental impedance (z) measurements. The BIA measurements were conducted after an overnight fast at a similar time point each day (between 0800 and 1000) following the manufacturer’s instructions. The analyzer measures the impedance to an alternating electric current as it passes through the body; inbuilt prediction equations convert this into an estimation of body fat. These equations are based on Caucasian populations and in a validation study, we found that they were not accurate for this population (14). We therefore predicted percentage FFM (%FFM) from our own equation (root mean square error for our equation ¼ 2.35%), which was derived previously in this population using deuterium oxide dilution as a reference method (14). Our equation: %FFM ¼ exp½7:659 1 0:709 3 lnðhtÞ 2 0:311 3 lnðzÞ 2 0:402 3 lnðwtÞ 2 0:044 3 lnðtricepsÞ 1 0:024 3 sex 1 0:007 3 age; where z is impedance (V), ht is height (m), wt is weight (kg), and triceps is triceps skin-fold thickness (mm). %FFM was used to calculate FFM (FFM ¼ %FFM 3 weight/100) and fat mass (%FM ¼ 100 2 %FFM; FM ¼ %FM 3 weight/100). We used log-log regression analysis, described by Wells et al. (15), to assess the relationship of FM and FFM with height (Ht). We generated FM/Ht and FFM/Ht indices that were uncorrelated with height, based on the value of the slope parameter from the regression; thus, FM index (FMI) was defined as FM/HT4 and FFM index (FFMI) as FFM/HT3. It was not possible to create prediction equations for the segmental impedance readings and therefore the Tanita system’s inbuilt prediction equations were used for percentage trunk fat, which is reported as an indication of central fat distribution. Impedance data were missing for 9 subjects due to a short circuit in the analyzer, which was fixed at a later date. Birth weight and length measurements, which had been measured within 48 h postpartum, were obtained from the original trial database (13). Birth weight had been measured to the nearest 20 g with spring balances and a tared sling (CMS Weighing Equipment) and length had been measured to 5 mm using neonatal length mats (TALC Teaching Aids). The Parkin score (16) was used to assess gestational age in the original trial and only those infants who were classified as term ($37 wk) were included in the analysis. Self-reported age at menarche was used to assess pubertal status among girls at follow-up. Due to a data recording error, the information on female menarche is incomplete; we have only been able to classify pubertal status for 62% of girls in the follow-up study. For girls .14 y, however, menarche was classified for 88% of subjects. Maternal height and postpartum weight were also available from the original trial database, as were data on parity. Statistical analysis. All statistical analyses were performed using Stata 9 (Stata Corporation). All variables were normally distributed as assessed by the Shapiro-Wilk test. Independent t tests were used to investigate differences between those individuals who were recruited into the present study and those who were not. Generalized estimating equations (GEE) were used to assess the effect of the intervention on later body composition (BMI, percent body fat, percent trunk fat, FMI, and FFMI) and height, taking the cluster design of the original trial into account (17). It was not possible to use GEE to examine the association between supplementation and percent trunk fat in boys; due to the distribution of the data in clusters, the model failed to converge. For this analysis, generalized least squares regression was used. We found that the results were very similar between the 2 statistical models for all other outcomes. The association between supplementation and body composition was assessed for the sexes separately, because the variation in body fat was much greater among girls than boys. Potential covariates included in the models were age, maternal height, maternal parity (coded as a binary variable), rural or urban location, and season of birth. Smoking Maternal supplements and offspring body composition
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prevalence data had not been collected in the original trial but is very uncommon in women of reproductive age in this community. Covariates that were potential intermediates of any intervention effect, such as maternal weight and birth weight, were not included in the model. Pubertal status was unrelated to the intervention and therefore this covariate was also included when analyzing female body composition. Intention-to-treat analysis was conducted, first, as a simple main effect and then separately, fitting its interaction with age, location, and season of birth. Data on the number of biscuits consumed was available for women in the intervention arm of the trial and this information was used in an ‘‘astreated’’ analysis. Exposure to the intervention was defined as more than or less than the median number of biscuits consumed and both these groups were compared with the control children. Again, GEE were used, adjusted for the covariates listed above, and interactions with age and location were assessed. The median age at menarche and the effect of the intervention on median age at menarche were estimated using logistic regression; the binary variable indicating whether the girl had reached menarche was regressed on her age when interviewed and the resulting prediction equation used to estimate the age by which 50% of girls had experienced their first menstruation. The bootstrap was used to obtain an estimate of the precision of the median. For a proportion of the subjects, weight data were available for 3, 6, 9, 12, and 36 mo of age. It was not possible to recruit the entire cohort during these studies and some individuals were present at 1 time point but not others. As a result, records were available for 80% of the study subjects at 3 mo of age, for 71–73% between 6 and 12 mo, and for 43% at 36 mo. Small proportions of length data were also available from the 12- (45%) and 36- (18%) mo time points. Within-population SD scores (value – mean/SD) were calculated for these age points as well as for the birth anthropometric variables. GEE were used to assess any effect of the intervention on size in infancy (defined as weight and length SD scores) adjusted for the same covariates as before: age, sex, maternal height, maternal parity, location, and season of birth. Values in the text are means 6 SD unless indicated otherwise. Differences were considered significant at P , 0.05).
Results A total of 1317 subjects were recruited into the follow-up, representing 72% of the cohort who were still alive (Fig. 1). Loss to follow-up rates were similar between the 2 arms of the trial: 26% in the control arm and 31% in the intervention arm. With the exception of a small but significant difference in age (3 mo), individuals recruited into the current study and those lost to follow-up did not differ (Table 1). Three percent of the children recruited were classified as preterm and were not included in the analysis. Another individual was excluded, because it was unclear which treatment arm the mother had belonged. The majority of children had remained in the rural area, with only 22% migrating to the urban/peri-urban coastal areas. The birth weight for children recruited into the follow-up was 2874 6 417 g for the control group and 2971 6 412 g for the intervention group (Supplemental Table 1). From GEE, taking original village clustering into account, the difference in birth weight between the 2 groups was 98.3 g (95% CI: 7.5, 189.1; P ¼ 0.03). The weight for children involved in the follow-up was 37.0 6 8.5 kg for boys and 41.2 6 10.1 kg for girls. Percentage body fat estimated from BIA was 12.6 6 2.9% for boys and 19.4 6 4.5% for girls (Supplemental Table 1). Compared with UK reference data (18), the Gambian children in this study had a BMI Z-score of 21.04 6 1.17 for girls and 21.53 6 1.02 for boys. Using International Obesity Taskforce cut-offs for childhood BMI (19), 2.6% of girls and 0.3% of boys would be classified as overweight. 2470
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FIGURE 1 Flow diagram displaying subjects recruited into the follow-up study from the original trial.
Maternal supplementation and offspring body composition. Using an intention-to-treat analysis, we found no evidence for an effect of maternal prenatal vs. postnatal protein-energy supplementation on BMI, percent body fat, percent trunk fat, FMI, FFMI, or height in boys (Table 2). Similarly, there was no difference in BMI, percent body fat, percent trunk fat, FMI, or FFMI for girls whose mothers had received the intervention during pregnancy compared with those whose mothers had received the intervention during lactation. However, in the
TABLE 1
Original trial characteristics for recruited individuals compared with those lost to follow-up in the present study1
Age at start of follow-up, y % Male Birth weight, g Birth length, cm Ponderal index, g/cm3 Maternal weight, kg Maternal height, m % Term infants % Mothers with parity 1 2 3
Lost to follow-up2 (n)
Recruited (n)
P-value3
14.0 6 1.5 (686)
13.8 6 1.5 (1317)
0.001
49.3 (686) 2921 6 415 (686) 49.4 6 2.1 (575) 2.44 6 0.30 (575) 53.2 6 7.1 (685) 1.6 6 0.1 (524) 97.4 (568) 11.8 (637)
52.1 (1317) 2896 6 436 (1317) 49.4 6 2.3 (1179) 2.42 6 0.31 (1179) 53.0 6 7.0 (1315) 1.6 6 0.1 (1060) 96.1 (1168) 12.3 (1257)
0.23 0.21 0.72 0.14 0.52 0.21 0.17 0.76
Values are means 6 SD or percentages, n ¼ lost to follow-up, recruited. Data were missing on 44 children from the 2047 born into the original trial. P-value refers to t tests for continuous data or chi-square tests for categorical data.
TABLE 2
Effect of maternal protein-energy intervention on offspring body composition1,2 Males Unadjusted analysis
n Height, cm Weight, kg BMI, kg/m2 Body fat, % Trunk fat, % FMI, kg/m4 FFMI, kg/m3
1 2 3 4 5 6 7 8 9
659 20.983 (22.87, 0.31) 0.86 (20.13, 1.85) 0.19 (20.14, 0.52) 0.01 (20.52, 0.55)4 20.07 (20.45, 0.31)4 0.004 (20.05, 0.05)4 0.08 (20.12, 0.28)4
P-value
0.31 0.09 0.25 0.96 0.73 0.87 0.44
Females Adjusted analysis
P-value
534 0.23 (21.25, 1.72) 0.45 (20.75, 1.65) 0.18 (20.12, 0.49) 0.15 (20.38, 0.68)5 0.093 (20.42, 0.60)5 0.02 (20.04, 0.07)5 0.06 (20.11, 0.23)5
0.76 0.47 0.24 0.57 0.72 0.56 0.47
Unadjusted analysis 611 21.10 (22.36, 0.17) 0.20 (21.35, 1.74) 0.27 (20.22, 0.76) 0.19 (20.68, 1.06)6 0.33 (20.54, 1.20)7 0.06 (20.03, 0.16)6 0.14 (20.08, 0.35)6
P-value
0.09 0.80 0.28 0.67 0.46 0.21 0.22
Adjusted analysis 316 21.30 (22.03, 20.57) 0.10 (21.57, 1.77) 0.29 (20.35, 0.94) 0.06 (20.89, 1.01)8 0.51 (20.61, 1.63)9 0.06 (20.05, 0.18)8 0.16 (20.13, 0.44)8
P-value
0.001 0.91 0.37 0.91 0.37 0.27 0.29
Values are regression coefficients (95% CI) and resulting P-values from intention-to-treat analysis utilizing GEE that have taken village cluster into account. Adjusted analysis model is adjusted for age, rural or urban location, maternal height, maternal parity, season of birth, and menarche in females. Regression coefficient from generalized least squares regression rather than GEE. n ¼ 652. n ¼ 527. n ¼ 609. n ¼ 607. n ¼ 314. n ¼ 312.
adjusted analysis, girls born to mothers who received the pregnancy intervention were 1.30 cm (95% CI: 0.57, 2.03; P ¼ 0.001) shorter than girls from the alternative arm at the time of the current study (Table 2). The sample size for the adjusted analysis in females was reduced primarily because of missing menarche data (n ¼ 179), but the effect on height remained when the analysis was conducted without this variable (data not shown). The adjusted analysis did not alter any of the other relationships between body composition and maternal supplementation. There were no interactions between age, location, or season of birth and the effect of prenatal vs. postnatal supplementation on later body composition for either boys or girls (data not shown). In the as-treated analysis, we compared 2 groups of intervention children (those whose mothers consumed less than the median number of biscuits and those who consumed more) with control children (whose mothers received the biscuits during lactation). Boys whose mothers had consumed more biscuits during their pregnancy had a slightly higher BMI (0.32 kg/m2; 95% CI: 0.04, 0.60; P ¼ 0.03) than boys from the control group (Supplemental Table 2). Again, there was a suggestion that for girls the intervention was associated with shorter stature (Supplemental Table 2). The difference in height for girls whose mothers had consumed fewer than the median number of biscuits during the intervention was 21.80 cm (95% CI: 23.02, 20.59; P ¼ 0.004), and 21.10 cm (95% CI: 22.10, 20.10; P ¼ 0.03) for girls whose mothers had consumed a greater number of biscuits. Maternal supplementation and size in infancy. There was no effect of maternal prenatal vs. postnatal supplementation on offspring weight attained, as defined by SD scores, at 3, 6, 9, 12, and 36 mo of age (Fig. 2). Length SD scores at 12 and 36 mo also did not differ between control and intervention group children, albeit on the restricted sample for whom these measurements were available (data not shown).
Maternal supplementation and offspring menarche. Fiftytwo percent of girls who provided a record had started menarche by the time of the follow-up and the age of menarche was calculated as 14.9 y (95% CI: 14.7, 15.1). There was no effect of maternal intervention on offspring age at menarche; the age of menarche for girls in the control group was 14.87 y (95%CI: 14.6, 15.1) and 14.94 y (95% CI: 14.7, 15.2) for girls in the intervention group.
Discussion A number of recent studies have shown a positive association between birth weight and later lean mass in both children and adults (20–23), whereas there is also evidence that low birth weight may be associated with greater central adiposity (4,5). These data could be interpreted as suggesting that the early-life period is an important determinant of later body composition. In the current study, we have demonstrated that maternal dietary supplementation during pregnancy, compared with during lactation, is not associated with body composition in the offspring at 11–17 y of age, despite a positive effect of the supplement on improving birth weight in these rural Gambian infants (13). Also, the supplement was unrelated to size attained in infancy. This is some of the first trial data in humans to investigate nutritional supplementation during pregnancy as an exposure relating to later disease risk. Infants born to mothers who received a protein-energy–dense biscuit during pregnancy were significantly larger at birth than infants whose mothers received the supplement postpartum (13). However, the effect of supplementation on birth weight does not correspond to later-life differences in the detailed estimates of body composition obtained. The only effect demonstrated by this study was a small effect on height for girls; shorter stature was observed for girls born to intervention women. Maternal supplements and offspring body composition
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FIGURE 2 Effect of protein-energy supplementation to pregnant women on their offspring’s attained size in infancy, represented by internal SD score. Regression coefficient and error bars (62 3 SE) are displayed for the effect of the intervention on offspring weight SD score at different age points. The sample size at different age points differs [n ¼ 2003 (birth), 840 (3 mo), 870 (6 mo), 848 (9 mo), 874 (12 mo), 527 (36 mo), and 1029 (168 mo)].
In contrast, 2 follow-up studies investigating the effects of an early-life protein-energy supplement on body composition have reported an association with taller adolescent height (12,24). Both of these community-based interventions provided supplements to pregnant women and to children up to the age of 3 y in Guatemala (24) and 6 y in India (12). It is therefore not possible to determine whether improved pregnancy or improved childhood nutrition (or both) influenced adolescent height. In the Guatemalan data, the effect of the intervention on height in adolescent girls was explained by the difference in length attained at 3 y (24), suggesting that improved childhood nutrition, leading to increased growth in childhood, may be the important exposure. A major strength of the current study is that the influence of the maternal diet is investigated from the standpoint of a randomized controlled trial. The sample size was large and the narrow CI indicate that the study had the power to detect small differences in body composition. A total of 64% of the original trial offspring were recruited into the follow-up and there was no differential loss to follow-up between the 2 arms of the trial. From the characteristics we were able to investigate, there was no selection bias in the recruited sample, with the exception that individuals were on average 3 mo younger than those lost to follow-up. Another major strength of the study is the relatively accurate measure of body composition obtained. FFM (and hence FM) were estimated in this population using a bioelectrical impedance analyzer that had previously been validated in the population and for which population-specific equations were available for converting impedance data into %FFM (14). We were also able to determine an estimate of percent trunk fat, albeit one generated without population-specific equations. A limitation of the study is that the mothers in the control arm were given the same protein-energy biscuits during lactation rather than pregnancy. One interpretation of the lack of an effect on weight SD scores as early as 3 mo of infancy could be that providing the supplement postpartum reduced any difference between the groups almost immediately. It could be argued that 2472
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these extra nutrients were transmitted to the offspring during lactation, although in a previous trial in the same region of The Gambia, we found no evidence that protein-energy supplementation of lactating women improved their breast milk quality or quantity (25,26). The lack of association between maternal supplementation and later body composition may be related to the age at which the children were enrolled into the present study. Analyzing the NHANES in the United States, Heidger et al. (21) reported that birth weight was related to increased lean mass in infants aged 2–47 mo, but this association was no longer observed in children 3–6 y old (27). It is possible that any ‘‘programming’’ influences are only apparent at certain age points; the children in the present study were undergoing puberty, which may have obscured any possible effects In conclusion, we have shown that protein and energy supplementation provided to rural pregnant women in The Gambia did not affect the body composition of their offspring, between 11 and 17 y of age, compared with supplements given to women postpartum. Acknowledgments We thank Marijke Prins and Meaghan Kall for their help with conducting the study at various time points. We also thank Yankuba Sawo for his help with tracing the subjects. Thanks also go to Kabiru Sise, Morikebba Sanyang, Kalilu Sanneh, Saul Jarjou, and Sheriff Kolley at MRC Keneba for their enthusiastic and tireless help when collecting data in the field.
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