Elsevier

Metabolism

Volume 63, Issue 2, February 2014, Pages 199-206
Metabolism

Clinical Science
Detailed assessments of childhood adversity enhance prediction of central obesity independent of gender, race, adult psychosocial risk and health behaviors

https://doi.org/10.1016/j.metabol.2013.08.013Get rights and content

Abstract

Objective

This study examined whether a novel indicator of overall childhood adversity, incorporating number of adversities, severity, and chronicity, predicted central obesity beyond contributions of “modifiable” risk factors including psychosocial characteristics and health behaviors in a diverse sample of midlife adults. The study also examined whether the overall adversity score (number of adversities × severity × chronicity) better predicted obesity compared to cumulative adversity (number of adversities), a more traditional assessment of childhood adversity.

Materials/Methods

210 Black/African Americans and White/European Americans, mean age = 45.8; ± 3.3 years, were studied cross-sectionally. Regression analysis examined overall childhood adversity as a direct, non-modifiable risk factor for central obesity (waist–hip ratio) and body mass index (BMI), with and without adjustment for established adult psychosocial risk factors (education, employment, social functioning) and heath behavior risk factors (smoking, drinking, diet, exercise).

Results

Overall childhood adversity was an independent significant predictor of central obesity, and the relations between psychosocial and health risk factors and central obesity were not significant when overall adversity was in the model. Overall adversity was not a statistically significant predictor of BMI.

Conclusions

Overall childhood adversity, incorporating severity and chronicity and cumulative scores, predicts central obesity beyond more contemporaneous risk factors often considered modifiable. This is consistent with early dysregulation of metabolic functioning. Findings can inform practitioners interested in the impact of childhood adversity and personalizing treatment approaches of obesity within high-risk populations. Prevention/intervention research is necessary to discover and address the underlying causes and impact of childhood adversity on metabolic functioning.

Introduction

Obesity, especially central adiposity, and metabolic syndrome (MetS) place adults at high risk for other physical health problems, especially diabetes mellitus (DM), cardiovascular disease (CVD), and hypertension [1], [2], [3], [4], [5], [6], [7], [8], [9]. Central obesity has been associated with early stressful environments and events [10], [11], [12], [13], including intra-uterine stresses and early illnesses [14], [15], poverty [16], and specific and cumulative stresses such as physical and sexual abuse in childhood or death of a close family member [17], [18], [19], [20], in both animal models and human studies [14], [21], [22], [23]. Psychosocial factors including socioeconomic status (SES), education, and functional status (adjustment or functioning in the domains of mental health, work, leisure/interests, and close relationships) provide a mediated link between early life stressors and later health [12], [16], [24], [25], [26], [27]. Impaired psychosocial functioning is associated with health risk factors [28], [29], such as smoking, drinking, poor diet, and sedentary lifestyle that set the stage for poor health outcomes in general.

Many psychosocial factors and health risk factors are considered modifiable, with the potential to decrease obesity rates and costs [30], and are the focus of many prevention/intervention programs. However, it is rare for such programs to assess childhood adversity and its potential direct, non-mediated impact on metabolic functioning, central obesity versus overall obesity, and outcomes [12], [23], [31], [32].

Examining childhood adversity. The growing literature examining associations between early adversity and adult physical health typically uses cumulative adversity scores to assess the number of adversities an individual has experienced [10], [11], [12], [19]. This work addresses the concepts of severity and chronicity of stress [11], [12], but severity and chronicity of experiences are often inferred from the nature of the childhood adversity (e.g., maltreatment is considered to be severe and low SES chronic), rather than assessed and incorporated into measurements of adversity. The large sample sizes of many investigations preclude more in-depth assessments of these dimensions. Nevertheless, specific information on severity and chronicity could address issues of resilience and also allow for more personalized treatment plans and outcome expectations [33], [34], [35]. Unlike a large scale study, samples in which detailed, interview-based, childhood adversity histories are obtained allow for assessments of severity and chronicity. They also provide an opportunity to compare the predictive power of a cumulative score with a potentially more clinically relevant adversity score that incorporates number of adversities with severity and chronicity information.

The current study examines the impact of childhood adversity on midlife obesity in a racially and socioeconomically diverse, moderate-risk, but non-clinical sample. We explore a novel assessment of childhood adversity (number of adversities × severity × chronicity) as a direct predictor of central obesity compared with overall obesity. Additionally, we examine the contributions of current psychosocial (education, employment, social functioning) and health risk factors (smoking, drinking, diet and exercise). We hypothesize that the enhanced, interview-based overall childhood adversity score is a better predictor of central obesity than the cumulative adversity score, and will contribute to the prediction of central obesity beyond the more proximal midlife psychosocial and health risk factors.

Section snippets

Sample

Participants were 210 adults (mean age = 45.8; ± 3.3; range 35–55 years), of diverse SES backgrounds who were part of a study examining psychosocial influences on physical and mental health in midlife. The sample was generally representative of the population of Boston, MA with regard to proportion of men and women, European Americans, and those with a Bachelor's degree or higher, although it included a greater proportion of Black/African Americans [36]. The sample had an approximately equal

Results

Table 1 shows descriptive information for the entire sample. Anthropometric assessments are consistent with those described in the Third National Health and Nutrition Examination Survey [51].

Zero-order correlations are presented in Table 2. The psychosocial risk factor score was significantly associated with both WHR and BMI, but the health risk factor score was associated only with BMI.

Table 3 shows the results of two linear regression analyses predicting WHR, first with the overall adversity

Discussion

Results indicate that overall childhood adversity is an important predictor of central obesity, over and above the more proximal contributions of adult psychosocial and health risk factors. This underscores the impact of childhood adversity, taking into account its severity and chronicity, on metabolic functioning well into adulthood. We do not see the same effect of overall adversity in models predicting BMI, suggesting that overall childhood adversity is more specific to central, rather than

Conclusion

A number of large epidemiological investigations indicate that childhood adversity presents a considerable public health issue in midlife. Many studies and social policies highlight modifiable factors such as current health behaviors and social support as important contributors to physical health [61]. However, clinicians, policy makers, and researchers focusing on intervention should also take into consideration those in moderate to high-risk populations who are likely to have past experiences

Author contributions

Cynthia R. Davis: Manuscript writing, data analysis, data interpretation, data collection, data coding. Eric Dearing: Manuscript writing, data analysis, data interpretation. Nicole Usher: data collection, data coding. Sarah Trifiletti: data collection, data coding. Lesya Zaichenko: data collection. Elizabeth R. Weber: data collection, data coding. Mary T. Brinkoetter: data collection. Cindy Crowell-Doom: data coding. Kyoung Joung: Manuscript writing, data interpretation, data coding. Kyung Hee

Funding

Grant Support: This study was supported by the National Institute of Aging, grant AG032030, and National Institute of Diabetes and Digestive and Kidney Diseases grant 81913. The project described was supported by Grant Number UL1 RR025758 Harvard Clinical and Translational Science Center, from the National Center for Research Resources. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center for Research Resources or

Conflict of interest

Disclosure statement: The authors have nothing to disclose.

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