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Oct 5, 2012 - 1Department of Anthropology, University of Massachusetts Boston, Boston, Massachusetts 02125 ... 4Heller School for Social Policy and Management, Brandeis .... verage trade-offs in growth through a variety of mecha-.
AMERICAN JOURNAL OF HUMAN BIOLOGY 24:730–738 (2012)

Original Research Article

Diurnal Cortisol Rhythms and Child Growth: Exploring the Life History Consequences of HPA Activation Among the Tsimane’ COLLEEN H. NYBERG,1* WILLIAM R. LEONARD,2 SUSAN TANNER,3 THOMAS MCDADE,2 TOMAS HUANCA,4 AND RICARDO A. GODOY4 TAPS BOLIVIA STUDY TEAM 1 Department of Anthropology, University of Massachusetts Boston, Boston, Massachusetts 02125 2 Department of Anthropology, Northwestern University, Evanston, Illinois 60208 3 Department of Anthropology, University of Georgia Athens, Athens, Georgia 30602 4 Heller School for Social Policy and Management, Brandeis University, Waltham, Massachusetts 02454

Objective: Although psychosocial stress has also been implicated as a contributor to growth failure by imposing energetic constraints during development, the direct physiological pathways by which these life history trade-offs are imposed are not well understood. This study explores associations between diurnal cortisol rhythms and differential patterns of linear child growth among the Tsimane, a horticulturalist and foraging society in the Bolivian Amazon. Methods: Waking and bedtime salivary cortisol samples (n 5 243) were collected from 53 Tsimane’ children ages 1.6–6 over 3 days as part of a larger study of developmental trajectories in hypothalamic–pituitary–adrenal axis dynamics. Anthropometric measurements and survey data were collected in conjunction with the Tsimane’ Amazonian panel study (TAPS). Results: Among children under the age of 6, diurnal rhythms in stunted versus nonstunted children vary dramatically: stunted children display elevated cortisol at both the AM (P 5 0.03) and PM (P 5 0.02) collection points. Multilevel regression analysis demonstrates an inverse relationship between cortisol and height-for-age z-score status (P 5 0.00), which is mediated, in part, by infection (P 5 0.00), and is strongest among male children (n.s.). Moreover, the poorest statural growth is exhibited among children with high cortisol living in more acculturated Tsimane’ communities, a proxy for a more adverse developmental milieu. Conclusions: This study reports a small, but significant, life history cost of elevated diurnal cortisol rhythms on linear growth among Tsimane’ children, and provides critical insight into the developmental origins of health differentials among an indigenous Amazonian population experiencing rapid lifestyle changes. Am. J. Hum. Biol. 24:730–738, 2012. ' 2012 Wiley Periodicals, Inc.

Perhaps nowhere is the evidence for the biological instantiation of early adversity more compelling than in studies of child growth and nutritional status in impoverished settings across the globe. For this reason, growth studies have served as a longstanding focus of human biology research, not only serving as a key barometer of past adversity and current well-being, but also foreshadowing future health and disease risk (Bogin and Loucky, 1997; Clarkin, 2011; Grantham-McGregor et al., 1991; Martorell et al., 1995; Mascie-Taylor, 1991; McDade and Nyberg, 2010; Panter-Brick, 1996; Stinson, 1980; Tanner, 1986). Though difficult to disentangle, the multiple burdens posed by marginal nutrition, infection, and socioeconomic strain may act synergistically to influence growth faltering, and rarely occur in isolation (Cameron, 2007; Evans and Kim, 2007; Johnston, 2006; Jones, 2006; Lampl and Thompson, 2007; Schell and Magnus, 2001; Scrimshaw, 2003; Worthman and Panter Brick, 2008). Despite considerable interest in developing salient models that link the sociocultural world to individual biology (Miller et al., 2009), however, with several notable exceptions (Fernald and Grantham-McGregor, 1998, 2002; Flinn and England, 1997; Worthman and Panter-Brick, 2008), scant attention has been directed toward understanding the role psychosocial stress may have on potentiating differential patterns of child growth. In concert, infection, undernutrition, and psychosocial stress may pose fundamental challenges to the allocation of energy among maintenance, growth, and reproductive C 2012 V

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life history domains, imposing constraints that may be heightened in the context of marginal energy balance (Bogin et al., 2007; Kuzawa, 2007; Lukas et al., 2005; Schell and Magnus, 2001; Worthman and Kuzara, 2005). Recent studies have made great strides in utilizing a life history approach to demonstrate the biological cost of frequent immunostimulation on child growth in varied populations (Blackwell et al., 2009; DeCaro and Worthman, 2010; McDade et al., 2008; Panter-Brick et al., 2001). Extending a similar life history framework may thus yield critical insight into assessing the somatic costs of psychosocial stress. As a central fulcrum of the stress response, the hypothalamic–pituitary–adrenal axis (HPA) comprises a dynamic interface mediating the psychosocial world, the local ecological context, and individual well-being (Miller et al., 2009; Nyberg, in press; Romero et al., 2009). Arousal of the HPA axis has been associated with a variety of energetic and ecological stressors (Dallman et al., 1993; McEwen and Wingfield, 2003; Rohleder and KirshGrant sponsor: Gran Consejo Tsimane’ *Correspondence to: Colleen H. Nyberg, Department of Anthropology, University of Massachusetts Boston, Boston, MA 02125, USA. E-mail: [email protected] Received 27 October 2011; Revision received 13 June 2012; Accepted 19 June 2012 DOI 10.1002/ajhb.22304 Published online 5 October 2012 in Wiley Online Library (wileyonlinelibrary. com).

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baum, 2007), but among humans, exhibits the most marked elevations in response to social evaluative threats and unpredictability (Dickerson and Kemeny, 2004; Miller et al., 2007; Schulkin et al., 2005). Beyond navigating allostasis across diverse ecologies, the HPA coordinates the capacity for stress reactivity, and modulates developmental plasticity in life history investment across the lifespan (Crespi and Denver, 2005; Del Guidice, et al., 2011; Nyberg, In press; Power and Schulkin, 2006; Romero, 2009; Romero and Wikelski, 2010; Worthman and Kuzara, 2005). From an evolutionary perspective, the HPA axis prioritizes immediate survival by upregulating a piece of the maintenance energy elicited during the stress response, with the subsequent cascade of glucocorticoids promoting the rapid release of glucose and liberation of free fatty acids to help the body meet adaptive challenges (Brillion, 1995; Chrousos, 1992; Du et al., 2010; Hellhammer et al., 2009; Peters et al., 2004; Worthman and Kuzara, 2005). Cortisol, the major glucocorticoid produced by the human HPA axis and the biomarker of interest in this study, inhibits the production of inflammatory cytokines, and due to its suppressive effects on immune function under acute conditions, is associated with elevated infectious disease risk, further challenging growth processes (Besedovsky and del Rey, 1995; Cohen et al., 2007; Cole, 2008; Flinn and England, 1997; Miller et al., 2002, 2009; Raison and Miller, 2003; Sapolsky et al., 2000). By extension, frequent arousal of the HPA axis is thus poised to leverage trade-offs in growth through a variety of mechanisms, and emerges as a critical pathway linking macroscale socioeconomic and lifestyle change to individual health consequences. These pathways may include indirect energetic and metabolic constraints on growth (Demonacos et al., 1995; Du et al., 2009, 2010; Fernald and Grantham-McGregor, 1998); direct catabolic effects on fat, muscle, and bone (Brillon et al., 1995; Chrousos, 1998; Lukas et al., 2005); and inhibition of the pulsatile release of key endocrine mediators of growth such as growth hormone (GH) and insulin-like growth factor 1 (IGF-1), (Besedovsky and del Rey 1996; Van den Berghe, 1997, 1998). In this regard, developmental variation in stress hormones may not only alter current growth rate, but over time, may sculpt body composition, influence the timing of developmental transitions, and recalibrate thresholds for individual disease risk across the lifespan (Belsky et al., 2010; Campbell et al. 2010; Chisolm and Coall, 2008; Kuzawa and Quinn, 2009). Despite the hypothesized relationships between glucocorticoids and the metabolic correlates of growth (Johnston, 1998), few studies have evaluated the relationship between individual variation in HPA function and differential patterns of growth in humans. Several prominent studies have linked long-term elevations of basal cortisol levels in children to severe growth failure in orphans and have also identified rare cases of psychosocial dwarfism (Chrousos, 1992; Coculescu, 1989; Dobrova-Krol et al., 2008; Gunnar et al., 2001, Kertes et al., 2008). Among the few studies conducted in a nonwestern context, Fernald and Grantham-McGregor (1998, 2002) found that stunted Jamaican children aged 8–10 demonstrated higher salivary cortisol concentrations. On the other hand, a similar study by Fernald et al. (2003) in Nepal reported a compound measure of cortisol and heart rate was blunted in growth stunted children, while another study in Nepal did

not detect any such relationship (Worthman and PanterBrick, 2008). To that end, the overarching goal of this study is to clarify the relationship between diurnal HPA activity and differential patterns of child growth derived from this life history model among the Tsimane’, a foraging-horticulturalist society in the Bolivian Amazon undergoing rapid market integration. First, we hypothesize that elevated diurnal cortisol profiles will be associated with reduced stature, a relationship we expect to be mediated primarily by infectious morbidity, a major correlate of HPA activity. Second, we exclude stunted children from the analysis to test whether the relationship between cortisol and stature remains robust, as current stunting may reflect gestational insults, low birth weight, malnutrition or other endogenous early life factors that precede or interact with HPA function to alter growth trajectories. Third, we explore whether the consequences of stress on reduced stature are contingent upon sociocultural and environmental risk, with the expectation that the effects of stress on growth will be amplified by proximity to the market center, a proxy for a more adverse, stressful developmental milieu. MATERIALS AND METHODS Study sample Participants were enrolled as a part of a study exploring diurnal cortisol rhythms, market integration, and health in conjunction with the longitudinal Tsimane’ Amazonian Panel Study (TAPS) (Godoy et al., 2009; Leonard and Godoy, 2008). Here, we draw from 242 salivary cortisol samples from 53 Tsimane’ children age 1.6–6.0 from five communities encompassing a range of variation in regard to proximity to and engagement into the regional market economy (Nyberg, 2009). Previous research has demonstrated that Tsimane’ have elevated levels of infection (via the inflammatory protein CRP) (McDade et al., 2005, 2008), high parasite loads (Tanner et al., 2009), comparatively low concentrations of leptin (Sharrock et al., 2008), and intriguingly, the lowest diurnal cortisol profiles on record (Nyberg, in press). Despite the high prevalence of statural growth stunting (Foster et al., 2005; Godoy et al., 2010a), however, Tsimane children fall within the normal range for mid-arm muscularity and body fat percentiles (Foster et al., 2005; Godoy et al., 2010; McDade et al., 2005, 2008), and exhibit evidence of significant catch-up growth (Godoy et al., 2010b). All research protocols employed in this study were approved by the Institutional Review Board for human subjects research at Northwestern University, and permission was granted by the Gran Consejo Tsimane’. TAPS survey The TAPS survey on household demographics and socioeconomic factors was administered in each of the participating households during the first phase of research (Godoy et al., 2009; Leonard and Godoy, 2008), and was followed by a brief health survey. Self-reported illness days in the previous week was used as a proxy variable for infection, an important correlate of HPA axis activity, and was utilized to construct a dummy variable to represent whether the participant had experienced infectious morbidity in the week leading up to collection. The collection American Journal of Human Biology

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of salivary cortisol followed a cross-sectional wave across villages as part of the health unit, and the collection of anthropometric measurements to assess growth performance and nutritional status was performed on the final day of saliva collection.

Anthropometrics Growth performance and nutritional status were assessed using standard anthropometric techniques utilized by the TAPS project since 2002 (Foster et al., 2005; Godoy et al., 2005; Leonard and Godoy, 2008; Lohman et al., 1988; Tanner et al., 2009). A portable stadiometer was used to measure stature (cm), and weight (to the nearest 0.1 kg) was measured with a Tanita scale. Skinfold measurements (biceps, triceps, subscapular, suprailiac) were also collected to index fat buffer, and were combined into a sum of four skinfolds variable (Lohman, 1988). Sex- and age specific z-scores for anthropometric measures (HAZ, WAZ, WHZ) were generated using the NutStat program of EpiInfo v. 3.8 based on the 1978 CDC/ WHO growth reference curves, which have been used in prior TAPS studies of childhood nutritional and growth status (Fo1ster et al. 2005; Godoy et al., 2005, 2010a,b; Hamill et al., 1979; Leonard and Godoy, 2008; Tanner et al., 2009). Because of the highly ecosensitive nature of the anthropometric dimensions of weight and body fat (Leonard et al., 2002; Waterlow et al., 1977), the subsequent analyses will focus primarily on the outcome of linear growth, which reflects a more chronic exposure to adversity and provides more robust evidence of associations between HPA activity and growth faltering. Thus, the primary stature variable utilized in this study is HAZ score, representing age- and sex-specific z-scores for height, with stunting defined as falling below 22 HAZ.

Cortisol collection and analysis Cortisol samples were collected in 2-ml polypropylene vials twice a day over 3 days for a maximum of six samples per person, to emphasize the person-specific basal diurnal rhythm (Adam and Gunnar, 2001). In an effort to capture the maximum diurnal cortisol decline, the protocol recommended by Adam and Kumari (2009) and Hellhammer et al. (2009) was employed, in which participants were asked to fill the collection vials immediately upon waking, and immediately before bed. The vials were stored in the TAPS refrigeration unit in San Borja, Bolivia within 7 days of initial collection, then stored at 2308C at the Laboratory for Human Biology Research at Northwestern University. Samples were assayed in duplicate at the University of Trier using a competitive solid phase time-resolved fluorescence immunoassay with fluorometric endpoint detection (DELFIA), and exhibited a mean interassay coefficient of variation of 6.7%. Cortisol concentrations are reported here in lg dl21. As detailed elsewhere by Nyberg (2012), no significant correlations between cortisol concentrations and the duration of time between collection, storage, and assay completion were detected. Elsewhere, we have explored variation in diurnal cortisol profiles vary across the lifespan among the Tsimane’, and have reported that time of collection accounts for about 40% of the within-person variance in cortisol rhythms (Nyberg, 2012). American Journal of Human Biology

Statistical analysis Statistical analyses were performed in Stata version 10 (Stata, College Station, TX). To improve normality of the distribution, Cortisol values were log transformed to improve the normality of the distribution, with hierarchical models centered at 18-h postwaking. A best fit line though the multiple measures of morning and evening cortisol was fitted using hierarchical linear regression (Adam and Kumari, 2009; Hruschka et al., 2005; Nyberg, in press). Descriptive statistics are provided for the entire sample in Table 1, and two-tailed t tests for unequal variances with a Satterthwaite’s approximation were utilized to evaluate sex differences in cortisol concentrations and anthropometric status. For the bivariate analyses, HPA parameters were calculated using the mean person-specific value over the 3-day collection period for AM, PM, and mean cortisol concentrations. To assess the impact of diurnal cortisol rhythms on HAZ, a series of multilevel models were constructed to partition fixed and random effects using Stata gllamm, which adjusts for within-person variation in salivary cortisol across multiple days by linking measurements with the TAPS subject identifier, clustered by village of residence to account for community-level effects. Because of constraints on degrees of freedom and an absence of time-varying predictors, we have not allowed slopes of upper level variables to vary, and have apportioned the variance into between person (Level 1), and village level components (Level 2). The first hierarchical regression analysis, depicted in Model 1, evaluates the effect of diurnal cortisol rhythm on HAZ, controlling for covariates such as time of collection, day of collection, age, sex, and energetic status (sum of four skinfolds); while Model 2 builds upon the initial analyses by testing the mediating role of infection on the relationship between cortisol profiles and stature; finally the village level variable distance of residence from the market center is included in Model 3, with an additional variance component added at the village level. In Model 4, 23 stunted children (HAZ < 22) are excluded from the analysis to clarify whether the effect of stress on growth remains robust among those not experiencing early life growth falTABLE 1. Descriptive statistics for anthropometrics and cortisol

parameters of Tsimane’ children age 1.6–5.9 years Females (n 5 24)

Males (n 5 29)

Measure

Mean (SD)

Mean (SD)

Cortisol samples AM cortisol lg dl21 PM cortisol lg dl21 Age (years) Height (m) Weight (kg) BMI HAZ WAZ WHZ Sum of 4 skinfolds (mm) Mid-arm circumference (cm) Mid-arm z-score Ill days within past 7 days Stunted (% HAZ < 22) Wasted (% WHZ < 22)

4.92 (1.29) 0.18 (0.17) 0.05 (0.04)** 4.34 (1.14) 96.1 (8.26) 15.2 (2.44) 16.5 (0.92) 21.6 (0.85)** 20.66 (0.64)** 0.42 (0.61) 26.52 (5.16)* 15.14 (2.15) 21.34 (1.49) 0.73 (1.25)*** 39.40% 0.00%

4.30 (1.61) 0.17 (0.11) 0.08 (0.08)** 4.1 (1.15) 94.6 (8.28) 14.9 (2.69) 16.6 (1.42) 21.9 (0.84)** 20.99 (0.82)** 0.30 (0.92) 23.67 (7.18)* 15.40 (1.08) 21.20 (0.64) 1.58 (2.4)*** 49.10% 2.42%

Significant differences in the anthropometric differences between males and females are based on two-tailed t tests P < 0.05 (*), P < 0.01 (**), P < 0.001 (***).

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tering, potentially tracking to gestational insults, low birth weight or endogenous early life factors that may contribute to elevated HPA activity. RESULTS Summary statistics for the sample are provided in Table 1. Comparisons of means and standard deviations are provided for female versus male subgroups of children under age six. Significant gender differences are denoted with an asterisk if P < 0.05 for two-tailed t tests. Overall growth status of Tsimane’ children is similar to other indigenous Amazonian populations and several recent publications have explored the topic in greater detail (Foster et al., 2005; Godoy et al., 2010a,b; Tanner et al., 2009). For this sample of children under the age of six, the overall prevalence of linear growth stunting (HAZ < 22) is 39.4% for females, and 49.1% for males. Despite the prevalence of stunting, wasting, as indexed by low weight-for height z-scores (WHZ < 22) was low, with 0% of females and 2.4% of males qualifying as wasted. Although both shorter and leaner than their age- and sex-matched US peers, measures of body fatness (sum of four skinfolds), and arm muscularity suggest that Tsimane’ children are not experiencing acute protein energy malnutrition, a finding consistent with previous TAPS studies of child growth (Foster et al., 2005; Godoy et al., 2010b). Notably, males and females in this sample differed in regard to several indica-

Fig. 1. Morning and bedtime cortisol concentrations are significantly elevated in stunted compared to nonstunted Tsimane’ children bedtime values (P 5 0.02) represented by 116-h postwaking. The difference in midday slope is also significant (P 5 0.009).

tors of anthropometric status, with boys exhibiting significantly elevated evening cortisol concentrations, lower height-for-age and age-for-height z scores, lower measures of subcutaneous body fat (sum of four skinfolds), and significantly higher self-reported morbidity within the previous 7 days compared to girls. As expected, unadjusted overall mean cortisol levels (lg dl21) were on average, 0.044 lg dl21 higher for stunted children compared to nonstunted children (t 5 2.6, df 5 238, P < 0.000). This represents a 39% increase in all times mean levels compared to nonstunted children. The disparity between stunted and nonstunted cortisol concentrations is moderately greater among stunted boys (40% elevation in mean CORT) versus girls (33% elevation in mean CORT). These marked differences in diurnal rhythms between stunted versus nonstunted children are displayed in Figure 1: the average diurnal rhythm of a stunted child is elevated at both the morning and bedtime collection points, shifting the entire diurnal rhythm upward (AM cortisol: t 5 2.08, P 5 0.03; PM cortisol t 5 2.36, df 5 108, P 5 0.02). Although not evident from the graphic depiction, the grade of the slope is also significantly steeper among stunted compared to nonstunted children (t 5 2.73, df 5 238 samples from 56 children, P 5 0.01). In the first hierarchical regression analysis including all stunted and nonstunted children presented in Model 1 of Table 2, log transformed cortisol is inversely associated with linear growth status. Specifically, a 100% increase in midday cortisol results in a 0.03 SD reduction in HAZ score, given the interpretation of a log transformed predictor on a linear dependent variable (Gujarati, 2008). Each additional 1-year increase in age results in a 0.14 improvement in HAZ score, and males have 0.81 SD lower HAZ scores compared to age-matched females. The measure for subcutaneous body fat, indexed by the sum of skinfolds, is also a significant predictor of HAZ, where each 1 mm increase in subcutaneous fat is associated with a 0.07 SD increase in HAZ. Because infectious morbidity is a major correlate of HPA activity (Cohen et al., 2007) and was significantly associated with elevated cortisol profiles in children under age 6 (regression results not shown, adjusting for age and sex, b 5 0.10; P 5 0.01), in Model 2 (Table 2), we evaluate whether infection is the primary mediator of the relationship between cortisol and HAZ, conceptually represented by: HPA elevation ? suppressed immune function ? increased infection ? reduced growth. The presence of infection was associated with 0.05 SD reduction in HAZ score and explained an additional 8% of the variance com-

TABLE 2. Hierarchical regression models predicting HAZ status Model 1 Fixed effect Log CORT Age Sex (male 5 1) Skinfolds Illness Distance Random effect Level 1 (person) Level 2 (village)

Model 2

Model 3

Model 4

Coeff. (SE)

P value

Coeff. (SE)

P value

Coeff. (SE)

P value

Coeff. (SE)

P value

20.03 (0.01) 0.14 (0.01) 20.81 (0.03) 0.07 (0.00) – – Variance 0.73 –

0.00 0.00 0.00 0.00 – – SD 0.03 –

20.02 (0.01) 0.10 (0.01) 20.17 (0.03) 0.08 (0.00) 20.05 (0.01) – Variance 0.67 –

0.01 0.00 0.00 0.00 0.00 – SD 0.02 –

20.02 (0.01) 0.13 (0.02) 20.05 (0.02) 0.08 (0.00) 20.01 (0.00) 0.03 (0.00) Variance 0.39 0.12

0.04 0.00 0.00 0.00 0.07 0.00 SD 0.01 0.01

20.02 (0.01) 0.34 (0.01) 20.47 (0.02) 0.01 (0.00) 0.02 (0.01) 0.02 (0.00) Variance 0.62 0.03

0.06 0.00 0.00 0.00 0.00 0.01 SD 0.02 0.01

Model 1 tests main effect of log cortisol on HAZ status, Model 2 tests the mediating role of illness, and Model 3 examines additional village level covariates and variance. In Model 4, stunted children are excluded from the analysis.

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pared to Model 1. Although the coefficient for log cortisol is slightly attenuated with the addition of the proxy for infection, indicating a prominent mediating role of morbidity, its predictive value remains significant. In Model 3, we incorporate the variable village distance from the market center: each 1-h increase in walking time from San Borja translates to a 0.03 SD improvement in HAZ score, and notably, 24% of the total variance is contained at the between village-level, whereas 76% is explained by the between-person component. Model 3 explained an additional 23% of the variance compared to Model 2. Because of the cross-sectional nature of the data, it is impossible to ascertain causality with certainty, and thus the possibility of quasicausality, particularly within the stunted group, must be considered. For instance, current growth stunting may reflect a suite of developmental stressors that track to fetal or postnatal development, including prenatal undernutrition, infection, exposure to maternal stress, low birth weight, or reduced thymic volume, each of which holds consequences for elevated HPA rhythms independent of stress exposures (Kajantie et al., 2007; Kuzawa and Sweet, 2009; McDade et al., 2001; Sloboda et al., 2009). In the absence of data on birthweight or gestational stressors to clarify this possibility, we next exclude children who are currently growth stunted as a proxy for latent early life insults, presented in Model 4 (Table 2). Log cortisol remains marginally associated with reduced HAZ status among children who are not stunted, although the magnitude of the effect is somewhat reduced (P 5 0.06). Specifically, a 100% increase in midday cortisol rhythm is associated with a 0.02 SD reduction in HAZ score, even after controlling for morbidity among nonstunted children. Interestingly, the coefficient for selfreported ill health days is positive and significantly associated with HAZ status in nonstunted children, a clear departure from the pattern exhibited by stunted children of the same age for whom higher rates of illness are associated with poorer relative growth status. And, with the exclusion of stunted children, the vast majority of the variance is contained at the between person level, unlike Model 3 in which village-levels effects contributed significantly. In each of the four models, males demonstrate a significant gender gap in HAZ status. To further illustrate this relationship, we modeled the probability of stunting, a dichotomous variable, by sex and log cortisol, adjusting for age, skinfolds, and illness. Although the odds ratio for the males does not reach statistical significance (P 5 0.31), boys have a 36% increase in the probability of being stunted, even at the same cortisol concentrations as their female peers (results not shown; Log likelihood 2134.5; pseudo r2 5 0.11). Although these analyses have established that HPA activation exacts a somatic cost on linear growth within this age group, significant variation exists in exposure to and integration into the regional market economy in this population, which may also contribute to differential growth patterns. Here we predict that the relationship between cortisol and growth is likely to be contingent on degree of lifestyle change and acculturation, since previous analysis presented in Model 2 (Table 2) revealed that each additional hour walk from the market center of San Borja to the village of residence is associated with a 0.25 SD increase in HAZ status. In Figure 2, a contingency matrix presents average age- and sex-standardized HAZ staAmerican Journal of Human Biology

Fig. 2. Variation in mean HAZ status by cortisol levels and distance from urban center. The poorest statural growth is observed among children with higher cortisol levels in the more acculturated villages, whereas the best growth is seen among those with lower cortisol in the more traditional communities.

tus by low vs. high cortisol (based on median split of cortisol) and by village distance from the regional market center of San Borja (near or far categorization based on median split of hours walking). On the basis of previous findings that negative emotion increases with market integration (Godoy et al., 2006) and that better selfreported health positively covaries with increased social rank (Undurraga et al., 2010), we designate ‘‘close’’ to represent an environment of greater stress/adversity due to its proximity to San Borja and higher degree of acculturation, whereas ‘‘distant’’ represents those residing in the more remote communities, a proxy for a presumably lower adversity environment. By extension, this model predicts that stature will be contingent on the interaction between cortisol activity within low versus high stress environments, with the expectation that developmental risk will be greater for children residing in the more acculturated communities near San Borja. Depicted in Figure 2, the mean HAZ was higher in both the low and high cortisol groups of children living in more distant villages compared to children living in the close villages characterized by greater adversity. The lowest developmental risk scenario for HAZ was the low cortisol/distant proximity group, whereas the highest risk was the high cortisol/close proximity group. This finding suggests that a more sensitive HPA system is poised to affect other life history domains, in this case linear growth, at a lower threshold among children living under conditions of high stress. DISCUSSION In this sample of Tsimane’ children, elevated diurnal cortisol rhythms are associated with reduced HAZ status, relationships that are independent of infectious morbidity and subcutaneous fat reserves. Notably, these findings were robust among both stunted and nonstunted children, although the actual effect size of cortisol on HAZ status was modest. Young males demonstrated an increased vulnerability to stunting compared to age-matched females, while closer proximity of residence to the market center of San Borja was significantly associated with poorer HAZ status and greater developmental risk. The findings presented in this study verify several previous studies exploring the relationship between elevated

DIURNAL CORTISOL RHYTHMS AND CHILD GROWTH AMONG THE TSIMANE

cortisol and reduced child growth (Dobrov-Krol, et al. 2008; Fernald and Grantham-McGregor, 1998), and hint at plausible proximate pathways linking cortisol to the inhibition of the somatotrophic axis, in addition to implicating energetic trade-offs resulting in reduced investment in growth. The association between elevated HPA activity and infection is well-documented (Chrousos, 1992; Cohen et al., 2007; Miller et al., 2002), and that we identified a prominent mediating role of infection on the relationship between cortisol and HAZ is thus unsurprising. In tandem, this stress-infection-nutrition synergy may potentiate constraints on child growth, especially under conditions of marginal energy balance, and during developmental periods of rapid growth velocity. For instance, protracted infection may promote a reduction in thyroidstimulating hormone (TSH)—a change mediated through GC-induced action of inflammatory cytokines on peripheral tissues—and may contribute to euthyroid sick syndrome, a condition associated with nutritional deprivation and growth faltering (Tsigos and Chrousos, 2002; Van den Berghe et al., 1997, 1998; Veile, in preparation). As discussed previously, cortisol also reduces pulsatile secretion of GH and IGF-1, a major promoter of fat oxidation, while inhibiting bone growth via the impaired formation of osteoblast and periosteal cells (Johnston, 1988). These actions not only have implications for linear growth, but may also promote downstream changes in bone density (Chrousos, 1998; Chrousos and Gold, 1992). Beyond serving as simply a proxy for ‘‘stress,’’ the role of cortisol as an important metabolic regulator is becoming increasingly recognized ( Dallman et al., 1993; McEwen and Wingfield, 2003; Nyberg, in press; Romero et al., 2009; Worthman and Kuzara, 2005). However, scant attention has been directed toward assessing the nuanced and varied costs of stress-induced energy mobilization on growth. Further exploration of these relationships sheds light on the findings that, consistent with expectations, subcutaneous fat buffers children from the catabolic effects of cortisol in this study. For instance, glucocorticoids free-up glucose and liberate glycogen stored in muscle tissue as the first response source of energy upon elicitation of HPA activation. Under conditions of marginal nutrition, however, the preferred glucose stores may be quickly exhausted, promoting a shift to fatty acid metabolism, which is also accompanied by increased glucagon, temporary insulin resistance, and elevated ketones (Brillon et al., 1995; Pace et al., 2007; Peters et al., 2004). Although this provides vital alternative fuel for the brain, and secondarily, the body, the initiation of gluconeogenesis (breakdown of protein or glycerol into glucose) elicits far more damage compared to the conversion of glycogen to glucose, and is therefore likely to confer a different risk for pathology in lean individuals compared to those with moderate fat reserves (Brillon et al., 1995; Lukas et al., 2005; Peters et al., 2004; Romero et al. 2009). For Tsimane’ children who are relatively lean and still growing their brain, low fat buffers may thus promote the breakdown of protein, a process associated with reduced fat oxidation and temporary insulin resistance, hinting at the long-term implications for metabolic dysregulation and cognitive impairment (Butte, 2005; Fernald and Grantham-McGregor, 2002; Frisancho, 2003; Leonard et al., 2009; Peters et al., 2004). Taken together, we suggest that somatic aftermath of the catabolism of protein, which requires subsequent tissue repair and removal of cytotoxic

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and acidic byproducts, represents a significant hidden cost associated with prolonged stress, and is therefore a compelling avenue for future study. Beyond its effects on the hormonal architecture of growth and differential effects on body tissues, cortisol also precipitates epigenetic modifications of transcription factors within the mitochondria—actions that are contingent on the duration of stress. Once a cortisol molecule is bound by a cellular glucocorticoid receptor (GR) and translocates to the nucleus, the complex modulates mitochondrial gene expression through the control of calcium release and oxidation in a moment-to-moment context (Psarra and Sekeris, 2009, 2011). In the short term, this serves the adaptive function of monitoring metabolic checkpoints, stimulating ATP production in response to acute or moderate GC exposure, and temporarily increasing metabolism (Du et al. 2009; Peters et al., 2004). In contrast, chronic or prolonged GC exposure not only reduces cellular metabolism (Du et al. 2009), but also may promote downstream adipogenesis in visceral adipose tissue through preadipocyte differentiation (Campbell et al., 2010). To extrapolate, the metabolic consequences of acute to moderate stress in a lean population such as the Tsimane’ may be distinct from the effects of chronic stress occurring in the context of positive energy balance. Moreover, these developmental contingencies shed light on why Tsimane’ boys, who are at greater initial risk of stunting and exhibit lower fat reserves, appear especially vulnerable to the somatic costs of HPA activation during childhood, complementing the growing body of evidence that linear growth in males is more sensitive to changes in environmental (Godoy et al., 2010b; Gray and Wolfe, 1980; Kuzawa and Adair, 2003; Oyhenart et al., 1998; Stinson, 1985; Thayer et al., 2012). Although we do not explicitly engage a discussion of the political–economics of rapid lifestyle change in this study, (Hicks and Leonard, 2009; Undurraga et al., 2010), these results do underscore the importance of considering village-level effects in evaluating health outcomes (McDade and Nyberg, 2010). Previous TAPS research evaluating the social gradient in health have demonstrated that increased village income inequality is significantly associated with negative emotions, particularly sadness and anger (Godoy et al., 2006), whereas increased rank, though not village income inequality, predicts moderate improvement in self-reported health among adults (Reyes-Garcia et al., 2009; Undurraga et al., 2010). The village level effects of stress on growth presented here may be mediated by disruptions in family dynamics and kin networks, or potentially through an increase in stressors associated with novelty or unpredictability (Godoy et al., 2005; Miller et al., 2007; Nyberg, 2009). Regardless of the upstream factors, our findings indicate that HPA activation is poised to leverage tradeoffs in other life history domains, in this case growth, at a lower threshold among children experiencing rapid lifestyle changes and environmental adversity. Stress may thus represent a critical pathway by which rapid lifestyle change erodes child health, especially among indigenous populations in the Global South, for whom sharply emerging inequalities unfold within a context of deep historic and political economic marginalization (Painter and Durham, 1995; Santos and Coimbra, 1998). Several limitations to this study also warrant careful consideration. First, as with all cross-sectional studies, causality between HPA elevation and growth faltering American Journal of Human Biology

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cannot be inferred in the absence of longitudinal data. Moreover, the use of self-reported morbidity as a proxy for infection may be less reliable than an objective biomarker of immune activation. As previously noted, the absence of data on birth weight, ponderal index, or other proxies for early developmental insults also precludes a thorough understanding of early life HPA programming and child growth trajectories. Finer grained details of dietary composition and energy expenditure would also help to clarify the complex relationship between nutritional status, infection, HPA activity, and metabolism in this population of forager-horticulturalists, particularly since diurnal cortisol rhythms are the lowest of any population based study on record, and it might be expected that cortisol would covary with fluctuating energetic status (Dallman et al., 2003; Nyberg, 2012; Rohleder and Kirschbaum, 2007). While our sample size is limited, the statistical power is augmented by the collection of salivary cortisol measures across 3 days, and a wealth of prior TAPS research provides a comprehensive picture of growth over the course of the panel study (Foster et al., 2005; Godoy et al., 2010a,b; Leonard and Godoy, 2008; Tanner et al., 2009). Finally, while previous evidence for recovery from early insults and growth faltering in this population underscores the dynamic plasticity of this developmental period (Godoy et al., 2010a; West-Eberhard, 2003), the long term costs associated with differential HPA trajectories have yet to be explored (Del Giudice et al., 2011; Gluckman and Hanson, 2007). We hypothesize that elevated HPA activity may impose greater constraints on development early in life, when juxtaposed against a developing immune system, the challenge of the weaning transition, burgeoning brain growth and synaptic proliferation (Campbell, 2011; Chugani et al., 1998; Gluckman and Pinal, 2003; Scrimshaw, 2003). Intriguingly, the diurnal cortisol rhythms among growth stunted children aged 6 through 11 (not presented in this study) are markedly different from those presented here among children under 6 years of age, although a lengthy discussion of findings is beyond the scope of the current study. It is also increasingly recognized that early exposure to adversity may have incubation effects, in which signatures of HPA axis dysfunction do not emerge until later in life (Danese et al. 2007; Heim et al., 2000; Miller et al., 2009), although when and where the costs of elevated HPA activity are incurred remains to be clarified. Is elevated HPA activity early in life associated with a flattened diurnal rhythm in later years, with reduced morning cortisol and elevated evening cortisol reflecting hyporesponsivity, impaired HPA feedback, or even glucocorticoid resistance (Miller et al., 2002, 2007)? Do the downstream costs emerge in differential patterns of reduced lean muscle to increased visceral adiposity in adulthood (Baker et al., 2009; Clarkin et al., 2008; Epel et al., 2000)? Do they instead manifest in metabolic dysregulation—and how might this intersect with the nutrition transition within a small scale foraging-horticulturalist society undergoing rapid market integration (Leonard et al., 2009)? Or, given the known role of GCs in regulating developmental timing of maturation across taxa (Belsky et al., 2010; Chisholm and Coall, 2008; Crespi and Denver, 2005; Power and Schulkin, 2006), might variation in HPA activity in this population influence the timing of the pubertal transition, with imporAmerican Journal of Human Biology

tant implications for patterns of fertility (Kramer and Greaves, 2010)? CONCLUSION In sum, this study has been among the first to document an association between elevated diurnal cortisol rhythms and reduced linear growth in a population with marginal nutrition, elevated levels of physical activity, and high infectious disease loads. Additional longitudinal analyses in conjunction with the Tsimane Amazonian Panel Study will greatly illuminate the complexities of child growth under multiple adversities (Leonard and Godoy, 2008), and will advance an understanding of the downstream health consequences of psychosocial stress for a population experiencing rapid lifestyle changes. Finally, as demonstrated in this study, a life history approach that incorporates the modulating role of HPA activity into the maintenance budget is well positioned to quantify the somatic costs of stress, highlight the complexities and contingencies of these trade-offs on energetic status and environmental adversity, and reveal critical insight into the developmental origins of variation in health. ACKNOWLEDGMENTS The authors thank Roman Durvano, whose translation skills and assistance in the field were vital to the success of this study, and to the TAPS Bolivia study team. LITERATURE CITED Adam EK, Gunnar MR. 2001. Relationship functioning and home and work demands predict individual differences in diurnal cortisol patterns in women. Psychoneuroendocrinology 26:189–208. Adam EK, Kumari M. 2009. Assessing salivary cortisol in large-scale, epidemiological research. Psychoneuroendocrinology 34:1423–1436. Baker J, Hurtado AM, Pearson OM, Hill KR, Jones T, Frey MA. 2009. Developmental plasticity in fat patterning of Ache children in response to variation in interbirth intervals: a preliminary test of the roles of external environment and maternal reproductive strategies. Am J Hum Biol 21:77–83. Belsky J, Houts RM, Fearon RM. 2010. Infant attachment security and the timing of puberty: testing an evolutionary hypothesis. Psychol Sci 21:1195–1201. Besedovsky HO, del Rey A. 1996. Immune-neuro-endocrine interactions: facts and hypotheses. Endocr Rev 17:64–102. Blackwell AD, Pryor G III, Pozo J, Tiwia W, Sugiyama LS. 2009. Growth and market integration in Amazonia: a comparison of growth indicators between Shuar, Shiwiar, and nonindigenous school children. Am J Hum Biol 21:161–171. Bogin B, Loucky J. 1997. Plasticity, political economy, and physical growth status of Guatemala Maya children living in the United States. Am J Phys Anthropol 102:17–32. Bogin B, Silva MI, Rios L. 2007. Life history trade-offs in human growth: adaptation or pathology? Am J Hum Biol 19:631–642. Brillon DJ, Zheng B, Campbell RG, Matthews DE. 1995. Effect of cortisol on energy expenditure and amino acid metabolism in humans. Am J Physiol 268:E501–E513. Butte NF. 2005. Energy requirements of infants. Public Health Nutr 8:953–967. Cameron N. 2007. Growth patterns in adverse environments. Am J Hum Biol 19:615–621. Campbell B. 2011. Adrenarche in comparative perspective. Am J Hum Biol 23:44–52. Campbell JE, Peckett AJ, D’Souza AM, Hawke TJ, Riddell MC. 2011 Adipogenic and lipolytic effects of chronic glucocorticoid exposure. Am J Physiol Cell Physiol 300:C198–C209. Chisholm JS, Coall DA. 2008. Not by bread alone: the role of psychosocial stress in age at first reproduction and health inequalities. In: Trevathan W, Smith EO, McKenna JJ, editors. Evolutionary medicine and health: new perspectives. Oxford: Oxford University Press. p 134–148. Chrousos GP. 1998. Stressors, stress, and neuroendocrine integration of the adaptive response. The 1997 Hans Selye memorial lecture. Ann N Y Acad Sci 851:311–335.

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