Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2020 Sep 1.
Published in final edited form as: Am J Hum Biol. 2019 Jul 3;31(5):e23283. doi: 10.1002/ajhb.23283

Early maturity, shortened stature, and hardship: can life history trade-offs indicate social stratification and income inequality in the U.S.?

Anna C Rivara 1, Lorena Madrigal 2
PMCID: PMC6863048  NIHMSID: NIHMS1042482  PMID: 31268232

Abstract

Objective:

Life history strategies promote reproductive fitness and survival. Limited energy availability and competing energetic demands between life history decisions may result in organismal trade-offs leading to selection for “optimal” traits that facilitate fitness and survival in present environmental conditions. Few life history analyses have been conducted in food abundant/high resource human populations. Here, we use a life history theory framework integrated with a biocultural approach to assess whether trade-offs between growth (height) and the onset of reproductive maturation (ages at menarche) were observed in a sample of adult women living in the U.S.

Methods:

Adult women (18 years and older) from the National Health and Nutrition Examination Survey (NHANES) 2005–2006 were analyzed using complex survey regression to evaluate associations between ages at menarche, height, and biological, socio-economic, demographic, and anthropometric variables.

pAssociations between stature, ages at menarche, and socio-economic status (household income and education level) suggest life history trade-offs in this populations may be mitigated by access to resources and marginalization.

Conclusions:

These study results have applied public health implications. We demonstrate that females who experience early menarche in the U.S. population achieve short stature. Our study also demonstrates the need for implementing life history analyses in Western affluent populations, where marginalization may result in life-history trade-offs.

Introduction

Life history theory (LHT) provides an analytical framework to observe and measure reproductive and development strategies in organisms (Stearns, 1992; McDade 2003). Life history decisions promote reproductive fitness and survival and include traits such as: age at menarche, growth, somatic maintenance, fertility, and senescence. The costs of these strategies within an individual is limited by the metabolic energy available to the organism (Stearns, 1992). Thereby, competing energetic demands between life history decisions can result in trade-offs (Stearns, 1992; McDade, 2003), that lead to individually and environmentally specific optimal fitness and survival chances for that organism.

Via cultural adaptations and counter-active niche construction (buffering reactions to environmental changes), human populations reduce many of the metabolic and physiological costs, and selective pressures, faced by other organisms that ultimately threaten survival, decrease reproductive fitness, and produce life history trade-offs (Laland et al., 2010; Kramer and Ellison, 2010). Therefore, major studies of human life history trade-offs have focused on populations living in adverse conditions (e.g., low resource, food limited, pathogenic) because negative energy balance and reduced capacity to offset costs is implicated in the manifestation of many life history trade-offs (Bogin et al., 2007; Walker, 2006).

There remains a relative dearth of analyses of life history trade-offs in food abundant/high resource Western populations such as the United States. These types of analyses are necessary to test how successfully resource abundance negates life history trade-offs, or whether differing types of adverse conditions instill selective pressures on these types of populations. For example, are stresses associated with marginalization, food insecurity, high food availability, or lower socio-economic status (pressures still found in many Western societies) also acting as selective forces? The purpose of this paper is to use life history theory and biocultural frameworks to determine whether trade-offs between growth (height) and the onset of reproductive maturation (age at menarche) are found in U.S. women. Additionally, we sought to identify a secular trend in ages at menarche, and discuss the probable causes of the secular trend and the trade-offs identified among U.S. women.

Background

Completed height in adults is influenced by individual genetic background, and is sensitive to environmental influences, psychosocial and nutritional stresses, and energy re-direction to reproduction and/or immune responses to infection (Cameron et al., 2007; Vercellotti et al., 2014). The metabolic costs of growth are highest during early life as increased growth velocity spurs both skeletal and organ development and slows as children age into adolescence due to programmed senescence of the growth plates (Jee and Barron, 2016). Adequate intake of macro- and micronutrients is necessary to provide the energy for bone growth and hormone production; deficiencies of zinc, vitamin A, and iron, have all been implicated in growth faltering (Rivera et al., 2003) and in restricting growth hormone (GH) and insulin-like growth factor 1 (IGF-1) production necessary for growth and collagen production (Dorup and Clausen, 1991; Nishi, 2013; Rivera et al., 2003). Overall deficiencies in caloric intake and other micronutrients, including potassium, magnesium, thiamine, copper, Vitamin D, and calcium, also impede bone formation (Rivera et al., 2003; Fontana et al., 2008; Sandstead et al. 1998).

Increased production of, and exposure to, estrogen early in life is associated with accelerated growth and senescence of growth plates, earlier ages at finalized growth and stature, and shorter stature (Jee and Barron, 2016). Under-nutrition and over-nutrition influence growth velocity during this phase. Under-nutrition is associated with decreased sex steroid and GH production leading to growth faltering, while over-nutrition, as found in cases of overweight status and obesity, increases endogenous hormone exposure and accelerates growth at younger than expected ages (Jee and Barron, 2016; Kain et al. 2009).

Immune response to infection and stress during growth phases creates energetically costly physiological stresses that disrupt macro- and micronutrient levels, and lead to life history trade-offs that can result in growth faltering and shortened stature (Rivera et al., 2003; Nabwera et al. 2017; Nataro and Guerrant, 2017). Suppressed growth and weight gain deficits are widely reported effects of disease and mounting immune responses (Lochmiller and Deerenberg, 2000; Panter-Brick et al., 2000; McDade, 2003).

During adolescence, metabolic expenditures are also re-directed towards pubertal development and associated growth finalization (Cameron and Demerath, 2002; Cameron 2007). In healthy females, growth velocity is expected to increase before the appearance of secondary sexual characteristics (i.e., breast development), starting at approximately 10 years of age (Cameron and Demerath, 2002), but is subsequently reduced due to heavy costs associated with menstruation (Vitzhum, 2008; Strassman, 1996; Bandini et al., 2008; Gavela-Perez et al., 2016; Bratke et al., 2017).

Sensitive to energy availability, reduced-to-absent energetic reserves can arrest reproductive cycling. Severe infectious, nutritional, and psychological stresses can disrupt the hypothalamic-pituitary-adrenal (HPA) and hypothalamic-pituitary-ovarian (HPO) axes, restricting hormone production and causing amenorrhea (Fourman and Fazeli, 2015). The metabolic costs of infection also impede reproductive maturity (Rosenstock, 1996; Khan et al., 1996 in Abrams and Miller, 2011). Even in adequately nourished individuals, activation of pro-inflammatory immune responses is associated with delayed puberty (Ballinger et al., 2003).

Due to these sensitivities to energy availability, life history trade-offs between height and reproduction are readily evident in many populations living in resource poor locations and have monopolized most evolutionary analyses. Differential environmental conditions and individual-level and population-specific stresses produce trade-offs that optimize reproductive fitness in terms of reproductive lifespans or maternal body condition (e.g., earlier sexual maturation and shorter stature vs. delayed maturation and taller stature). In chronically food limited, high-energy expenditure environments, negative energy balances can result in delayed reproduction that allows for increased time and energy directed towards growth. While delays shorten reproductive lifespans, reproductive fitness is increased by improving maternal and offspring condition. For example, in chronically stressed environments such as The Gambia, delayed ages at first birth in women were associated with taller stature, and increased reproductive fitness (Sear et al., 2004). Taller women were also found to have greater numbers of live births, faster reproductive rates, lower probabilities of stunted children, and greater numbers of children surviving until adulthood compared to shorter women (Sear et al., 2004; Addo et al., 2013).

In severely adverse environments with high rates of early-life mortality risks, accelerating maturation and growth—resulting in shorter stature--has been argued to improve reproductive fitness by increasing reproductive lifespan and parity (Walker, 2006; Devi et al., 1985; Frisancho et al., 1973 in Monden and Smits, 2008). In the Aeta and Batak peoples, increased reproductive effort was associated with shorter stature (Migliano et al., 2007 in Vitzhum 2009), and in Guatemalan indigenous women, shorter women had the greatest parity. However, their offspring faced the highest rates of infant and childhood mortality (Martorell et al., 1981). Accelerating maturity, and the consequent trade-off in shortened stature, facilitate reproduction when future conditions and survival are bleak or unknown.

The U.S. has reduced levels of early-life mortality risks and is a high-resource environment. We presume that there are still levels of adversity impacting individuals in the U.S.; thereby, we hypothesize that observable life history trade-offs will be occurring among women drawn from the National Health and Nutrition Examination Survey (NHANES). Increased food and nutrient availability, lower levels of pathogen exposure, and increased access to healthcare likely buffer many against life history trade-offs in this population; however, are these conditions directing the construction of new physiological stressors? Pervasive socioeconomic, structural, and other psychosocial stressors still occurring in the U.S. may promote fast life history strategies that instigate reproductive maturation at earlier than expected ages, and produce trade-offs between growth and reproduction. Additionally, the types of trade-offs observed will mirror those seen in other lower resource populations as life history strategies are constrained to influencing survival and fitness. With the presumption that the U.S. has developed its own set of selective pressures—though arguably less severe than many found in low resource environments—we hypothesize that life history trade-offs resulting in earlier ages at menarche and shorter adult stature may be present among some women in the NHANES.

Methods

Reproductive histories, along with anthropometric, biological, socio-economic, and demographic data were obtained from adult women (n = 2,419) in the NHANES, 2005–2006. Regularly conducted by the United States’ Department of Health and Human Services, the NHANES collects medical, nutrition, socioeconomic, and demographic data from a representational sample of the U.S. population. The analyses considered adult women (18 years or older) who participated in both the medical and qualitative data portions of the survey.

Due to the complex survey design of NHANES, our regression model used PROC SURVEYREG in SAS v9.4 with height as the dependent variable. PROC SURVEYREG, SURVEYMEANS, and SURVEYFREQ considered the specific weights, clustering, and stratification embedded within the NHANES survey design. Using these statements ensures that the results obtained are representative of the U.S. population rather than just the sample analyzed. Independent predictors included ages at menarche, weight, ethnicity, current income (dichotomized into high/low, ≥$35,000, based on median values in the sample), high school completion, and age of the participants. As noted in our limitations section, current income is not an ideal measure of income at time of menarche for these participants. However, the cross-sectional approach of the NHANES means that adolescent income values for the women surveyed were not available for analyses. Since the U.S. is known to have little intergenerational upward or downward mobility compared to Nordic countries (Corak et al., 2014; Jantti et al., 2006), we used current income status as a limited proxy for lifetime income. Body mass index was also not included in the analyses due to the high collinearity of BMI to our dependent variable, height, in our regression model. Furthermore, the use of BMI cutoffs in this population of high ethnic and age heterogeneity may not be the best measure of health status and body condition (Rubin, 2018; van Uffelen et al., 2010; Swinburn et al., 1999; Duncan et al., 2010).

Dummy variables were constructed for the ethnicities. NHANES 2005–2006 only provided five possible ethnic identities for participants: non-Hispanic Black, non-Hispanic White, Mexican American, Other Hispanic, and Other (including multi-racial). We combined the Mexican American and Other Hispanic variables due to the low sample size of the Other Hispanic category. White ethnicity was chosen as the reference category for modelling purposes. Interaction variables were created between ages at menarche and income, and ages at menarche and education, to demonstrate the impact of associations between menarche and socio-economic status on height.

Using the lsmeans statement in PROC GLM, we obtained the estimated marginal means of height controlling for ages at menarche, income, and education. The estimated marginal means are used to test the specific impact of income and education on the observed associations between ages at menarche and height in the sample analyzed. Regression analysis of only the sample population is included in the appendix in order to show the likelihood of the sample estimated marginal means as reflective of the associations likely occurring in the representative population. ANOVA tests obtained from PROC GLM tested for significance between the estimated marginal means. Results were graphed using Microsoft Excel for Windows and SAS v 9.4.

Ethical statement

This study was exempt from local Institutional Review Board review. NHANES data are publicly available and de-identified for secondary analysis, and informed consent was obtained from participants during initial data collection. The NHANES study was approved by the National Center for Health Statistics Research Ethics Review Board and is held under the requirements of the Public Health Service Act (42 USC 242k) and the Privacy Act of 1974 (5 USC 552A) to conserve the privacy of participant identities.

Results

Descriptive statistics of the women are provided in Table 1. Mean values show that a clear majority of the women had received a high school education; almost half of the women had household incomes below $35,000. Additionally, a high rate of overweight status (based on the mean weight by mean height values obtained; BMI = 28.6) was observed in the women.

Table 1:

Descriptive statistics of adult women (18 years and older) in NHANES 2005–2006 including means and frequencies, standard errors, and confidence levels. Statistics incorporate the complex survey design

Variable n Mean or weighted
frequency		 Standard error of
mean/percent		 95% Confidence
levels for mean
Age at menarche (years) 2144 12.68 0.06 12.55, 12.82
Height (cm) 2375 162.05 0.17 161.66, 162.43
Age (years) 2419 47.20 0.76 45.58, 48.82
Weight (Kg) 2382 74.71 0.79 73.01, 76.41
IgE (kU/l) 2260 102.46 8.00 85.41, 119.52
Socio-economic variables
High School graduate 2407 83.08% 1.26
Income above $35,000 2273 55.01% 2.45
Ethnicities
Other 2419 5.92% 0.88
White 2419 71.31% 2.88
Black 2419 12.33% 2.22
Hispanic 2419 10.43% 1.21
Open in a new tab

Predictors of height in U.S. women

We found that ages at menarche was a significant predictor of, and positively associated with, adult height (p˂0.015). Women with greater height recorded older ages at menarche (Table 2). Weight was positively associated with height, though only added a slight effect to overall adult height. In contrast, age at survey and the Hispanic and Other ethnic identifiers were negatively associated with height. The socioeconomic variables of income and education were not significantly associated with height in the women

Table 2:

Survey regression of adult women in NHANES 2005–2006, modeling height (cm), by biological, socio-economic, and ethnic variables

n = 2003
R = 0.234
Variables Estimate Standard error p ˂ 0.05
  Biological
Intercept 152.687 2.568 ˂0.0001
Age at survey −0.095 0.009 ˂0.0001
Age at first menarche 0.484 0.175 0.0147
Weight 0.091 0.008 ˂0.0001
 Socio-economic
High school graduate 1.607 3.022 0.602
Income above $35,000 −0.973 3.305 0.772
  Ethnicity
Black −1.117 0.524 0.050
Hispanic −5.284 0.455 ˂0.0001
Other −3.893 0.923 0.0008
  Interactions
Menarche*income 0.1666 0.254 0.522
Menarche *high school graduate −0.007 0.248 0.975
Open in a new tab

Figure 1 demonstrates the predicted adult height of women by their ages of menarche and ethnic identify. As projected below, the same positive associations between height and ages at menarche are occurring in all ethnicities.

Figure 1:

Figure 1:

Open in a new tab

Associations between stature and ages at menarche in NHANES 2005–2006, all ethnicities, controlling for high school graduation and income status.

graphic file with name nihms-1042482-f0004.jpg

Interactions between age at menarche and income, and ages at menarche and education, showed no significant association with adult height. The estimated marginal means of height from the sample data controlling for menarche, income, and the interaction of the two, show that current income has an added, but not statistically significant (p = 0.335), effect on the positive association between ages at menarche and height (Figure 2; Regression of sample data in Supplemental Table 1). A pattern is observed that generally women with higher current income had taller adult heights irrespective of their recorded ages at menarche than women with lower current income.

Figure 2:

Figure 2:

Open in a new tab

Estimated marginal means of height based on the interactions between income and ages at menarche in NHANES 2005–2006 sample.

graphic file with name nihms-1042482-f0005.jpg

Similarly, the estimated marginal means of height from the sample data and the interaction of ages at menarche and high school education, demonstrate that education also has an added but not statistically significant (p = 0.538), positive effect on the relationship between ages at menarche and height in the sample data. Women with more education at most ages at menarche were taller than women with less education (Supplemental Figure 1).

Secular changes and patterns in age at menarche

Our results also show general declines in ages of menarche in the population (Figure 3). Younger women at the time of survey had younger mean ages at menarche than did older women.

Figure 3:

Figure 3:

Open in a new tab

Secular changes in mean ages at menarche based on age in adult women from NHANES 2005–2006.

Discussion

Life History Trade-offs

We found that ages at menarche in adult women in the NHANES 2005–2006 are positively associated with height. Women who experienced menarche at earlier ages are significantly shorter than women who experienced menarche at older ages; these associations are suggestive of life history trade-offs. Our results suggest women who experienced earlier ages at menarche may have experienced a life history trade-off where energy re-directed to reproductive maturation reduced the energy available to continue the development of height. This development pattern has been demonstrated in populations suffering early life mortality and severe selective pressures (Walker, 2006; Bogin et al., 2007). While these conditions are not normally expected or experienced within the U.S., other forms of adversity may be instigating these trade-offs. A high prevalence of food insecurity in the U.S. (Leung et al., 2014; Rose, 1999), often manifesting as calorically dense low-quality diets and localized in low-income populations (Leung et al., 2014), is one major factor that is likely influencing energy availability. While overall food scarcity for some may be slowing and stagnating peak growth velocities, resulting in shorter stature, a high abundance of calorie-dense low qualities foods could be spurring peak growth velocity and/or instigating reproductive maturation at earlier than expected ages.

Excess weight is linked to the early onset of menarche (Cameron and Demerath, 2002; Wattigney et al., 1999). While we cannot assess the weight of our participants in their early life, we did find that a large proportion of the women currently were of overweight or obese status. Since early ages at menarche are associated with increased risks of type 2 diabetes, cardiometabolic disease, (Mueller et al., 2014; Garn et al., 1986; Cameron and Demerath, 2002), and increased BMI and obesity in adulthood (Dreyfus et al., 2015; Prentice and Viner, 2013), we can reason that some of the heavier women may have had similar weight statuses during adolescence that increased their likelihood of early-onset maturation.

Income (at time of survey) and high school graduation is positively associated, though not significantly, with stature in this population. Research supports that greater income and education, suggestive of higher socio-economic status (SES), are associated with better nutritional and health status (Batty et al., 2009) and improved growth. Due to the low rates of intergenerational upward and downward mobility in income ranks in the U.S. (Corak et al., 2014; Jantti et al., 2006), we can speculate that women presently with lower income and less education faced similar conditions during reproductive maturation, and, thereby, faced greater adverse conditions during early life than women with higher SES. Conditions such as these could have placed increased socio-economic and psychosocial pressures on the women, spurring the instigation of sexual maturation and growth velocity at earlier ages, and reduced overall stature.

Factors such as hereditability of menarcheal ages, nutrition, environmental and/or dietary exposures to reproductive hormones (Newbold et al., 2009; Buttke et al, 2012), and inflammatory and psychosocial stresses (Joinson et al., 2011), in conjunction with improved overall nutrition, influence the instigation of menarche and the pace and completion of growth in U.S. women. These variables were unable to be captured in our analyses. However, our results demonstrated that SES plays a role in growth, as women with higher income and higher amounts of education were taller irrespective of the age at which they experienced menarche. These results suggest the known correlates between higher income, greater education, and better health and nutritional status (Larson & Story, 2015; Zimmerman et al., 2015) likely influenced growth potential in these individuals. These results support that individuals in the U.S. may face differential likelihoods of early onset pubertal development, accelerated growth completion, and/or realized growth potential.

Specifically, in the U.S., the nexus between poverty, food insecurity, and diminished economic mobility (Chetty et al., 2015; Rose, 1999; American Academy of Pediatrics, 2016) demonstrate that specific groups within the country may be at greater risk for overnutrition and exposure to conditions that are associated with the early onset of menarche and growth finalization. Therefore, associations between shortened stature and early menarche may be, and may continue to be, disproportionately prevalent in segments of the population. While our results could not effectively demonstrate this, increasing income inequality and social stratification within the U.S. ensures a cyclical transmission of poverty within specific segments of the population (Piketty et al., 2015; Braveman et al., 2010) that may create conditions where life history trade-offs become more overtly evident in these groups. Exposure at younger ages to poor diets, environmental toxins, reproductive hormones (e.g., obesogens, phytoestrogens) (Newbold et al., 2009), metabolic dysregulators (e.g., obesity-associated adipokines and cytokines) (Yuksel et al., 2012), endocrine disruptors that mimic reproductive hormone exposure (Kendig et al., 2012), and severe levels of psychological stress (Joinson et al., 2011) all influence sexual maturation and growth velocity. These exposures are associated with and exacerbated by poverty and obesity, both which are highly associated with each other in the U.S. (Biro et al., 2012; Neel and Sargis, 2011; Levine, 2011; Drewnowski, 2009). Individuals in impoverished areas are in general at reduced risk for healthy development (Emerson, 2012) and increased risk of poor health outcomes (Singh and Jemal, 2017). It is realistic therefore to hypothesize that growing inequities, exposure to poverty and obesity-associated environmental conditions, increase the risks of many to higher rates of exogenous and endogenous growth and reproductive instigating hormones. These exposures instigate reproductive maturation that will likely influence life history strategies (Bravemen et al., 2010).

We also found that ages of menarche are declining in U.S. women. A larger proportion of younger women experienced earlier ages at menarche than older women. If the frequency of individuals experiencing early menarche is maintained or increases—and recent studies affirm that ages of menarche are consistently declining in the United States (Biro et al., 2012)—it is probable to hypothesize future secular declines in height in women in the United States.

Limitations

The cross-sectional study design of NHANES limits our ability to track in real-time the impacts of income, education, psychosocial stress, menarche, ethnicity, and weight, on growth. Our uses of current income as a proxy variable for adolescent income, and recalled menarcheal ages, are major limitations to our study; future analyses would be strengthened by either incorporating accurate recorded measures of early life conditions or longitudinal study designs. Nonetheless, our analyses provide a practical approach to observing potential life history trade-offs and trends in large populations using publicly available cross-sectional data. Our results are also limited by an absence of data concerning the metabolic, hormonal, and environmental, exposures of the women at the time of survey and during early life that could better support our findings. Finally, we are constrained by the NHANES instrument’s inadequate approach to defining ethnicity. Limiting participant identifiers to only five categories (four in our analysis) causes the loss of important analyses of how identity, and associated social capital and marginalization, impacts adverse conditions in the U.S. population.

Conclusion

In this paper we have demonstrated that early menarche in a sample of U.S. women is associated with shorter adult height. This association has important applied and theoretical implications. From an applied perspective, we may be looking at important health consequences of the secular trend towards earlier menarche. Thus, it is likely that, at least for many females, the secular trend towards increasing stature is being reversed. From a theoretical perspective, we have demonstrated the necessity of applying a life history perspective in the study of affluent Western populations, where socio-economic inequalities and stratification may affect growth trajectories.

Associations between stature and ages at menarche in women drawn from the NHANES, 2005–2006, can be explained using a life history framework. However, our results indicate that further investigation is needed to understand how socioeconomic factors impact reproductive maturation and growth in women in Western populations. As both local and global inequalities and stratification increase, life history trade-offs may be disproportionately prevalent in specific demographics within populations. In Western populations, we advocate that proxies of adversity, such as income, educational status, and ethnicity, may provide insight into how life history trade-offs between reproductive maturation and height are manifested in women. Additionally, we advocate for researchers to regard social stratification and marginalization as potential selective pressures in humans that direct life history trade-offs.

Supplementary Material

Supplemental Figure 1:

Estimated marginal means of height based on the interactions between education and ages at menarche in NHANES 2005–2006 sample.

graphic file with name nihms-1042482-f0006.jpg

Supp TableS1

Acknowledgments:

The authors are appreciative of the support of the departments of Anthropology at the University of Notre Dame and the University of South Florida; the department of Epidemiology of Chronic Diseases, and the department of Epidemiology of Microbial Diseases at Yale University, the NIH Fogarty Global Health Fellows program, and the Global Health Equity Scholars Program.

Sources of Support: Global Health Equity Scholars Program, #TW009338.

References

  1. Abrams ET, & Miller EM (2011). The roles of the immune system in women’s reproduction: Evolutionary constraints and life history trade‐offs.American Journal of Physical Anthropology, 146(S53), 134–154. 10.1002/ajpa.21621 Retrieved from https://onlinelibrary.wiley.com/doi/abs/10.1002/ajpa.21621 [DOI] [PubMed] [Google Scholar]
  2. Addo OY, Stein AD, Fall CH, Gigante DP, Guntupalli AM, Horta BL, Kuzawa CW, Lee N, Norris SA, Prabhakaran P, Richter LM, Sachdev HS, Martorell R, & Consortium on Health Orientated Research in Transitional Societies (COHORTS) Group (2013). Maternal height and child growth patterns. J Pediatr 163 (2): 549–554. doi: 10.1016/j.jpeds.2013.02.002. Epub 2013 Mar 7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Ballinger AB, Savage MO, & Sanderson IR (2003). Delayed puberty associated with inflammatory bowel disease. Pediatr Res 53(2): 205–210. DOI: 10.1203/01.PDR.0000047510.65483.C9 [DOI] [PubMed] [Google Scholar]
  4. Bandini L, Must A, Naumova E, Anderson S, Caprio S, Spadano-Gasbarro J, & Dietz W (2008). Change in leptin, body composition and other hormones around menarche –a visual representation. Acta Paediatrica (Oslo, Norway : 1992), 97(10), 1454–1459. 10.1111/j.1651-2227.2008.00948.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Batty GD, Shipley MJ, Gunnell D, Huxley R, Kivimaki M, Woodward M, . . . Smith GD (2009). Height, wealth, and health: An overview with new data from three longitudinal studies. Economics and Human Biology, 7(2), 137–152. 10.1016/j.ehb.2009.06.004 Retrieved from https://www.sciencedirect.com/science/article/pii/S1570677X09000495 [DOI] [PubMed] [Google Scholar]
  6. Biro FM, L. C. Greenspan, & Galvez Maida P.. (2012). Puberty in girls of the 21st century. Journal of Pediatric and Adolescent Gynecology, 25(5), 289–294. 10.1016/j.jpag.2012.05.009 Retrieved from https://www.clinicalkey.es/playcontent/1-s2.0-S1083318812000927 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Bogin B, Silva MIV, & Rios L (2007a). Life history trade‐offs in human growth: Adaptation or pathology? American Journal of Human Biology, 19(5), 631–642. 10.1002/ajhb.20666 Retrieved from https://onlinelibrary.wiley.com/doi/abs/10.1002/ajhb.20666 [DOI] [PubMed] [Google Scholar]
  8. Bogin B, Silva MIV, & Rios L (2007b). Life history trade‐offs in human growth: Adaptation or pathology? American Journal of Human Biology, 19(5), 631–642. 10.1002/ajhb.20666 Retrieved from https://onlinelibrary.wiley.com/doi/abs/10.1002/ajhb.20666 [DOI] [PubMed] [Google Scholar]
  9. Bratke H, Bruserud Ingvild Saervold, Brannsether Bente, Aßmus Jorg, Bjerknes Robert, Roelants Mathieu, & Juliusson Petur B. (2017). Timing of menarche in norwegian girls: Associations with body mass index, waist circumference and skinfold thickness. BMC Pediatrics, 1710.1186/s12887–017-0893-x Retrieved from https://search.proquest.com/docview/1915352286 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Braveman PA, Cubbin C, Egerter S, Williams DR, & Pamuk E (2010). Socioeconomic Disparities in Health in the United States: What the Patterns Tell Us. American Journal of Public Health, 100(Suppl 1), S186–S196. 10.2105/AJPH.2009.166082 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Buttke DE, Sircar K, & Martin C (2012). Exposures to Endocrine-Disrupting Chemicals and Age of Menarche in Adolescent Girls in NHANES (2003–2008). Environmental Health Perspectives, 120(11), 1613–1618. 10.1289/ehp.1104748 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Cameron N. l., & Demerath EW (2002). Critical periods in human growth and their relationship to diseases of aging. American Journal of Physical Anthropology, 119(S35), 159–184. 10.1002/ajpa.10183 Retrieved from https://search.proquest.com/docview/197244780 [DOI] [PubMed] [Google Scholar]
  13. Cameron N (2007). Growth patterns in adverse environments. American Journal of Human Biology, 19(5), 615–621. 10.1002/ajhb.20661 Retrieved from https://onlinelibrary.wiley.com/doi/abs/10.1002/ajhb.20661 [DOI] [PubMed] [Google Scholar]
  14. Chetty R, Hendren N, Kline P, & Saez E (2014). Where is the land of opportunity? the geography of intergenerational mobility in the united states.The Quarterly Journal of Economics, 129(4), 1623 10.1093/qje/qju022 Retrieved from http://www.fachportal-paedagogik.de/fis_bildung/suche/fis_set.html?FId=1058439 [DOI] [Google Scholar]
  15. Corak M, Lindquist MJ, & Bhashkar Mazumder. (2014). A comparison of upward and downward intergenerational mobility in Canada, Sweden and the United States. Labour Economics 30: 185–200. [Google Scholar]
  16. Dorup I, Flyvbjerg A, Everts ME, & Clausen T (1991). Role of insulin-like growth factor-1 and growth hormone in growth inhibition induced by magnesium and zinc deficiencies. Br J Nutr 66(3): 505–521. [DOI] [PubMed] [Google Scholar]
  17. Drewnowski A (2009), Obesity, diets, and social inequalities. Nutrition Reviews, 67: S36–S39. doi: 10.1111/j.1753-4887.2009.00157.x [DOI] [PubMed] [Google Scholar]
  18. Dreyfus J, Jacobs DR, Mueller N, Schreiner PJ, Moran A, Carnethon MR, & Demerath EW (2015). Age at menarche and cardiometabolic risk in adulthood: the Coronary Artery Risk Development in Young Adults Study. The Journal of Pediatrics, 167(2), 344–352.e1. 10.1016/j.jpeds.2015.04.032 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Emerson E (2007), Poverty and people with intellectual disabilities. Ment. Retard. Dev. Disabil. Res. Rev, 13: 107–113. doi: 10.1002/mrdd.20144 [DOI] [PubMed] [Google Scholar]
  20. Fontana L, Weiss EP, Villareal DT, Klein S, & Holloszy JO (2008). Long-term effects of calorie or protein restriction on serum IGF-1 and IGFBP-3 concentration in humans. Aging Cell 7(5): 681–687. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Fourman LT, & Fazeli PK (2015). Neuroendocrine causes of amenorrhea—an update. J Clin Endocrinol Metab 100(3): 812–824. doi: 10.1210/jc.2014-3344. Epub 2015 January 12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Garn SM, LaVelle M, Rosenberg KR, & Hawthorne VM (1986). Maturational timing as a factor in female fatness and obesity. American Journal of Clinical Nutrition 43(6): 879–883. DOI: 10.1093/ajcn/43.6.879 [DOI] [PubMed] [Google Scholar]
  23. Gavela-Perez T, Navarro P, Soriano-Guillén L, & Garcés C (2016). High prepubertal leptin levels are associated with earlier menarcheal age. Journal of Adolescent Health 59(2): 177–181. [DOI] [PubMed] [Google Scholar]
  24. Jasienska G, Bribiescas Richard G, Furberg Anne-Sofie, Helle Samuli, & la Mora Alejandra Núñez-de. (2017). Human reproduction and health: An evolutionary perspective. The Lancet, 390(10093), 510 10.1016/S0140-6736(17)30573-1 Retrieved from https://search.proquest.com/docview/1924515036 [DOI] [PubMed] [Google Scholar]
  25. Jäntti M, Bratsberg B, RÃȩd K, Raaum O, Naylor R, Österbacka E, . . . Eriksson T(2006). American exceptionalism in a new light: A comparison of intergenerational earnings mobility in the nordic countries, the United Kingdom and the united states [Google Scholar]
  26. Jee YH, & Baron J (2016). The biology of stature. The Journal of Pediatrics, 173, 32–38. 10.1016/j.jpeds.2016.02.068 Retrieved from https://www.clinicalkey.es/playcontent/1-s2.0-S0022347616002912 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Joinson C, Heron J, Lewis G, Croudace T, & Araya R (2011). Timing of menarche and depressive symptoms in adolescent girls from a UK cohort. Br J Psychiatry 198(1): 17–23 [DOI] [PubMed] [Google Scholar]
  28. Jones JH (2015). Resource transfers and human life-history evolution. Annual Review of Anthropology, 44, 513–531. 10.1146/annurev-anthro-102214-013938 Retrieved from https://search.proquest.com/docview/1728704961 [DOI] [Google Scholar]
  29. Kain J, Corvalán C, Lera L, Galván M, & Uauy R (2009). Accelerated growth in early life and obesity in preschool chilean children. Obesity, 17(8), 1603–1608. 10.1038/oby.2009.37 Retrieved from 10.1038/oby.2009.37 [DOI] [PubMed] [Google Scholar]
  30. Kendig EL, Buesing DR, Christie SM, Cookman CJ, Gear RB, Hugo ER, . . . Belcher SM (2012). Estrogen-like disruptive effects of dietary exposure to bisphenol A or 17α-ethinyl estradiol in CD1 mice. International Journal of Toxicology, 31(6), 537–550. 10.1177/1091581812463254 Retrieved from http://journals.sagepub.com/doi/full/10.1177/1091581812463254 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Khanna G, & Kapoor S (2004). Secular trend in stature and age at menarche among punjabi aroras residing in new delhi, india. Collegium Antropologicum, 28(2), 571 Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/15666587 [PubMed] [Google Scholar]
  32. Kramer KL, & Ellison PT (2010). Pooled energy budgets: Resituating human energy -allocation trade-offs. Evolutionary Anthropology: Issues, News, and Reviews, 19(4), 136–147. 10.1002/evan.20265 Retrieved from https://search.proquest.com/docview/1752626631 [DOI] [Google Scholar]
  33. Laland KN, Odling-Smee J, & Myles S (2010). How culture shaped the human genome: Bringing genetics and the human sciences together.Nature Reviews Genetics, 11(2), 137–148. 10.1038/nrg2734 Retrieved from 10.1038/nrg2734 [DOI] [PubMed] [Google Scholar]
  34. Larson N, & Story M (2015). Barriers to equity in nutritional health for U.S. children and adolescents: a review of the literature. Current Nutrition Reports 4(1): 102–110. 10.1007/s13668-014-0116-0 [DOI] [Google Scholar]
  35. Leung CW, Epel ES, Ritchie LD, Crawford PB, & Laraia BA (2014). Food insecurity is inversely associated with diet quality of lower-income adults. J Acad Nutr Diet 114(12): 1943–53 e2 doi: 10.1016/j.jand.2014.06.353 [DOI] [PubMed] [Google Scholar]
  36. Levine JA (2011). Poverty and obesity in the U.S. Diabetes 60 (11) 2667–2668; DOI: 10.2337/db11-1118 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Martorell R, Delgado HL, Valverde V, & Klein RE (1981). Maternal stature, fertility, and infant mortality. Human Biology 53(3). 303–312 [PubMed] [Google Scholar]
  38. McDade TW (2003). Life history theory and the immune system: Steps toward a human ecological immunology. American Journal of Physical Anthropology, 122(S37), 100–125. 10.1002/ajpa.10398 [DOI] [PubMed] [Google Scholar]
  39. McEvoy BP, & Visscher PM (2009). Genetics of human height. Economics and Human Biology, 7(3), 294–306. 10.1016/j.ehb.2009.09.005 Retrieved from https://www.sciencedirect.com/science/article/pii/S1570677X09000793 [DOI] [PubMed] [Google Scholar]
  40. Mueller NT, Duncan BB, Barreto SM, Chor D, Bessel M, Aquino EM, … Schmidt MI (2014). Earlier age at menarche is associated with higher diabetes risk and cardiometabolic disease risk factors in Brazilian adults: Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Cardiovascular Diabetology, 13, 22 10.1186/1475-2840-13-22 [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Nabwera HM, Fulford AJ, Moore SE, & Prentice AM (2016). Growth faltering in rural gambian children after four decades of interventions: A retrospective cohort study. Retrieved from http://researchonline.lshtm.ac.uk/3400923/ [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Nataro JP, & Guerrant RL (2017). Chronic consequences on human health induced by microbial pathogens: Growth faltering among children in developing countries. Vaccine 10.1016/j.vaccine.2017.05.035 [DOI] [PubMed] [Google Scholar]
  43. Neel BA, & Sargis RM (2011). The paradox of progress: Environmentaldisruption of metabolism and the diabetes epidemic. Diabetes, 60(7), 1838–1848. 10.2337/db11-0153 Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/21709279 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Newbold RR, Jefferson WN, & Padilla-Banks E (2009). Prenatal Exposure to Bisphenol A at Environmentally Relevant Doses Adversely Affects the Murine Female Reproductive Tract Later in Life. Environmental Health Perspectives, 117(6), 879–885. 10.1289/ehp.0800045 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Nishi Y (2013) Zinc and growth., Journal of the American College of Nutrition, 15:4, 340–344, DOI: 10.1080/07315724.1996.10718608 [DOI] [PubMed] [Google Scholar]
  46. Onland-Moret NC, Peeters PHM, van Gils CH, Clavel-Chapelon F, Key TJ, Tjonneland A, . . . Riboli E (2005). Age at menarche in relation to adult height: The EPIC study. American Journal of Epidemiology, 162(7), 623–632. 10.1093/aje/kwi260 Retrieved from http://www.narcis.nl/publication/RecordID/oai:dspace.library.uu.nl:1874%2F11565 [DOI] [PubMed] [Google Scholar]
  47. Panter-Brick C, Lunn PG, Baker R, & Todd A (2001). Elevated acute-phase protein in stunted Nepali children reporting low morbidity: different rural and urban profiles. Br J Nutr 85(1): 125–131. [DOI] [PubMed] [Google Scholar]
  48. Prentice P, & Viner RM (2013). Pubertal timing and adult obesity and cardiometabolic risk in women and men: a systematic review and meta-analysis. Int J Obes (Lond) 37(8): 1036–1043. doi: 10.1038/ijo.2012.177. Epub 2012 November 20 [DOI] [PubMed] [Google Scholar]
  49. Onland-Moret NC, Peeters PHM, van Gils CH, Clavel-Chapelon F, Key TJ, Tjonneland A, . . . Riboli E (2005a). Age at menarche in relation to adult height: The EPIC study. American Journal of Epidemiology, 162(7), 623–632. 10.1093/aje/kwi260 Retrieved from http://www.narcis.nl/publication/RecordID/oai:dspace.library.uu.nl:1874%2F11565 [DOI] [PubMed] [Google Scholar]
  50. Piketty Thomas. 2015. ”About Capital in the Twenty-First Century.” American Economic Review, 105 (5): 48–53.DOI: 10.1257/aer.p20151060 [DOI] [Google Scholar]
  51. Poverty and Child Health in the United States. COUNCIL ON COMMUNITY PEDIATRICS. (2016). Pediatrics, 137 (4) e20160339; DOI: 10.1542/peds.2016-0339 Rivera et al., 2003 [DOI] [PubMed] [Google Scholar]
  52. Rose D (1999). Economic determinants and dietary consequences of food insecurity in the United States. J Nutr 129( 2S suppl) 517S–520S. doi: 10.1093/jn/129.2.517S. [DOI] [PubMed] [Google Scholar]
  53. Rosenstock SJ, Andersen LP, Rosenstock CV, Bonnevie O, & Jorgensen T (1996). Socioeconomic factors in Helicobacter pylori infection among Danish adults. Am J Public Health 86: 1539–1544. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Sandstead HH, Penland JG, Alcock NW, Dayal HH, Chen XC, Li JS, Zhao F & Yang JJ (1998) Effects of repletion with zinc and other micronutrients on neuropsychologic performance and growth of Chinese children. Am. J. Clin. Nutr. 68:470S–475S. [DOI] [PubMed] [Google Scholar]
  55. Sear R, Allal N, & Mace R (2004). Height, marriage and reproductive success in gambian women Socioeconomic aspects of human behavioral ecology (pp. 203–224) Emerald Group Publishing Limited; 10.1016/S0190-1281(04)23008-6 Retrieved from http://www.emeraldinsight.com/10.1016/S0190-1281(04)23008-6 [DOI] [Google Scholar]
  56. Singh GK, Jemal A (2017). Socioeconomic and racial/ethnic disparities in cancer mortality, incidence, and survival in the United States, 1950–2014: Over six decades of changing patterns and widening inequalities. Journal of Environmental and Public Health, 2017(138), 1–19. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Stearns SC (1992). The evolution of life histories Oxford: Oxford University Press, 249. [Google Scholar]
  58. Strassman BI (1996). The evolution of endometrial cycles and menstruation. The Quarterly Review of Biology 71(2): 181–220. [DOI] [PubMed] [Google Scholar]
  59. Vercellotti G, Piperata BA, Agnew AM, Wilson WM, Dufour DL, Reina JC, . . . Sciulli PW (2014). Exploring the multidimensionality of stature variation in the past through comparisons of archaeological and living populations. American Journal of Physical Anthropology, 155(2), 229–242. 10.1002/ajpa.22552 Retrieved from https://onlinelibrary.wiley.com/doi/abs/10.1002/ajpa.22552 [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Vitzthum VJ (2008). Evolutionary models of women’s reproductive functioning. Annual Review of Anthropology, 37, 53–73. 10.1146/annurev.anthro.37.081407.085112 Retrieved from https://www.jstor.org/stable/20622613 [DOI] [Google Scholar]
  61. Vitzthum VJ, Thornburg J, & Spielvogel H (2009). Seasonal modulation of reproductive effort during early pregnancy in humans. American Journal of Human Biology: The Official Journal of the Human Biology Council, 21(4), 548–558. 10.1002/ajhb.20936 Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/19402035 [DOI] [PubMed] [Google Scholar]
  62. Walker R, Gurven M, Hill K, Migliano A, Chagnon N, De Souza R, . . . Yamauchi T (2006a). Growth rates and life histories in twenty-two small-scale societies. American Journal of Human Biology : The Official Journal of the Human Biology Council, 18(3), 295–311. 10.1002/ajhb.20510 Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/16634027 [DOI] [PubMed] [Google Scholar]
  63. Wattigney WA, Srinivasan SR, Chen W, Greenlund KJ, & Berenson GS (1999). Secular trend of earlier onset of menarche with increasing obesity in black and white girls: the Bogalusa Heart Study. Ethn Dis 9(2), 181–189. [PubMed] [Google Scholar]
  64. Yuksel H, Sogut A, Yilmaz O, Onur E, & Dinc G (2012). Role of adipokines and hormones of obesity in childhood asthma. Allergy Asthma Immunol Res 4(2): 98–103. doi: 10.4168/aair.2012.4.2.98. Epub 2011 November 29. [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Zimmerman EB, Woolf SH, & Haley A (2015). Understanding the relationship between education and health: a review of the evidence and an examination of community perspectives Content last reviewed September 2015. Agency for Healthcare Research and Quality, Rockville, MD: http://www.ahrq.gov/professionals/education/curriculum-tools/population-health/zimmerman.html [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental Figure 1:

Estimated marginal means of height based on the interactions between education and ages at menarche in NHANES 2005–2006 sample.

graphic file with name nihms-1042482-f0006.jpg

NIHMS1042482-supplement-Supp_FigS1.pdf (111.2KB, pdf)
Supp TableS1
NIHMS1042482-supplement-Supp_TableS1.docx (18.3KB, docx)

RESOURCES