Background

Obesity is a metabolic condition characterized by high levels of abdominal adiposity and currently affects approximately 35% of all US adults. Obesity is commonly measured using the body mass index (BMI), measured in kg/m2, with a level ≥ 30 indicating obesity. There are significant sex and racial/ethnic disparities in obesity; the highest levels of age-adjusted obesity are seen in non-Hispanic Black women (~58%) compared to the lowest levels seen, in non-Hispanic White women (~32%). Obesity is associated with many negative health outcomes, such as atherosclerotic cardiovascular disease (CVD) and various cancers (e.g. breast, colon, and endometrial), and has also been shown to be an independent risk factor for all-cause mortality.

Given the multifactorial etiology of obesity, examining multiple pathways that incorporate biological, behavioral, and environmental effects on weight gain may provide insights that lead to the prevention of obesity. Previous studies have demonstrated modest effects of psychosocial factors (e.g. job-related demands, relationship demands, and personal health problems) on the risk of obesity. Additionally, genome-wide association studies (GWAS) on obesity have identified up to 97 genetic risk variants that are associated with a high BMI. The effects of BMI-associated genetic risk variants detected thus far have been weak, with the strongest predictor, the fat mass and obesity gene (FTO), contributing a 0.39 point increase in BMI for each copy of the risk allele, explaining only ~0.34% of total genetic variance.

Two types of research studies that might help expand on the limited findings of previous research and help incorporate the effect of psychosocial factors and genetic factors together are gene by environment interaction studies and epigenetic studies (i.e. DNA methylation (DNAm) studies). Animal models have shown that acute stressors (e.g. maltreatment or maternal neglect) alter DNAm in mice and rats. Less is known about the interaction of psychosocial factors, genetic risk factors for obesity, and epigenetic regulation of those genetic risk factors in humans. However, genetic susceptibility to obesity, together with high levels of external stressors, may increase the risk of obesity and account for a previously unexplained proportion of the variance in obesity.

Methods

This dissertation uses two analytical approaches to investigate the relationship between psychosocial risk factors and genetic risk factors and obesity: a systematic review and secondary data analyses. Chapter 2 presents a detailed systematic review of available studies of gene-environment interaction studies and epigenetic studies that focus on the effects of psychosocial and genetic risk factors for obesity. Chapters 3 and 4 use secondary data from a large population-based longitudinal cohort study, known as the Multi-Ethnic Study of Atherosclerosis (MESA).

Chapter 3 explores the interaction of three psychosocial factors (i.e. chronic burden of stress, everyday hassles, and depression) and an obesity genetic risk score on obesity. Obesity genetic risk is derived from the most recent meta-analysis, which established 97 independent genetic variants associated with body mass index (BMI). This analysis was conducted using interval-censored survival modeling using a Weibull distribution. Both multiplicative and additive effects were determined, so as to give a comprehensive assessment of genetic and psychosocial interactions.

Chapter 4 investigates the effect of three psychosocial factors (i.e. chronic burden of stress, everyday hassles, and Cohen’s perceived stress) on DNAm levels of obesity risk genes. I employed a two-level model for each unique gene (87 genes from 97 obesity GWAS SNPs), treating the CpG as the level-1 unit and the individual as the level-2 unit. For genes associated with psychosocial variables, we assess cross-sectional associations between DNAm and genetic expression levels. An association between DNAm and expression demonstrates the functional importance of DNAm as a gene regulator.

Significance

This dissertation examines the interactive relationship between genetic and non-genetic factors as they relate to obesity. Previous findings for BMI-associated genetic risk factors have been relatively weak. The effects of psychosocial factors on obesity have been primarily examined through mechanisms that involve behavior change, such as altered diet patterns or altered physical activity. Assessing the epigenetic effects and gene-environment interactions of psychosocial factors and obesity genetic risk may reveal pathways through which people develop a greater risk for obesity.

My findings provide evidence of an interaction between psychosocial factors and genetic risk for obesity in multiple subpopulations of the MESA cohort study. I identify several BMI-associated genes that are differentially methylated by levels of chronic stress. DNAm is significantly associated with genetic expression, revealing a functional mechanism by which exogenous factors affect genetic expression, not directly attributed to inherited genomic sequences. These findings suggest potential underlying biological mechanisms whereby psychosocial factors and genetic risk factors interact to cause obesity in a manner that is not mediated by altered behavioral patterns of energy intake and expenditure. As inherited genomic sequences are not easily modifiable to prevent negative health conditions, it is important to establish multiple systems where we can prevent additional cases of obesity by targeting a modifiable risk factor (e.g. psychosocial stress) that interacts with genes or affects their expression. Because obesity remains a major concern in the United States, investigators should continue to search for mechanisms through which it can occur, in order to help reduce the burden of obesity.

Background

Understanding why certain population subgroups age faster than others is a pressing public health concern. Few biomarkers consistently predict morbidity and mortality, which has made it difficult to identify high-risk population subgroups earlier in the disease cascade. Telomeres are the repeat sequence at the ends of DNA that protect the cell from damage during each replicative cycle. Telomeres shorten with age, and individual-level exposures may exacerbate telomere length attrition. There is evidence that telomere length has an inverse association with psychosocial stress, poor health behaviors, and chronic diseases. However, multilevel determinants of telomere length remain understudied despite numerous connections among physical and mental health, lifestyle, and place of residence. The extant literature exhibits that better physical and social contexts have a positive association with telomere length.

Methods

This dissertation examines the associations among specific features of residential built, social, and socioeconomic environments and the 10-year change in telomere length using data from the Multi-Ethnic Study of Atherosclerosis (2000-2010). Chapter 2 presents cross-sectional findings on the relationship between the physical environment and leukocyte telomere length. Chapter 3 investigates the association between changes in physical environment features and the 10-year change in leukocyte telomere length. Chapter 4 explores the interplay among changes in neighborhood socioeconomic status, social context, and leukocyte telomere length. Physical environment features comprise of the physical activity and food environment. The social environment includes measures of aesthetic quality, safety, and social cohesion.

Significance

This dissertation presents the first studies to examine changes in neighborhood features and change in telomere length. The findings suggest that telomere length is a biological marker that is sensitive to changes in built, social, and socioeconomic contexts. Thus, health policy interventions should target specific features of the residential environment to support healthy aging trajectories.

Background: Breast cancer is the leading cancer diagnosis and the second leading cause of cancer-related death in the United States. However, the overall mortality rate declined more than 42% over the last 30 years due to advances in treatment and screening. Despite these advancements, the breast cancer mortality rate for Black women is persistently higher than any other group with a 41% gap in survival compared to White women. The cause of this disparity is complex and partially attributed to non-modifiable factors such as tumor biology and modifiable factors such as access to quality breast cancer treatment, reductions in obesity, and other chronic conditions. The purpose of this research is to examine the contributions of body mass index, comorbidity, and hospital characteristics to the breast cancer mortality disparity between Black and White women.

Methods: This dissertation assesses the contributions of comorbidity, obesity, and hospital characteristics to breast cancer mortality disparities between Black and White women. Chapter 1 provides an overview of breast cancer mortality trends, a review of the literature on the associations of modifiable factors associated with breast cancer mortality and presents the questions and hypotheses for the proceeding chapters. Chapter 2 is a systematic review of peer-reviewed articles to evaluate comorbidity as a primary contributor to breast cancer mortality disparities between Black and White women. Chapter 3 presents the findings of the evaluation of body mass index as a modifier of breast cancer and all-cause mortality disparities between Black and White women using a historical breast cancer cohort dataset. Chapter 5 presents findings from our study of the associations between hospital characteristics, breast cancer surgical volume and hospital area-level poverty, and breast cancer mortality and all-cause mortality. The final chapter provides a summary of our findings and suggestions for future research.

Significance: Identifying and addressing modifiable risk factors for breast cancer mortality is key to narrowing the breast cancer mortality gap between Black and White women. Obesity, comorbidity, and hospital quality are three such modifiable factors. This research aims to contribute to existing knowledge and elucidate the roles of obesity, comorbidity, and hospital characteristics to adverse breast cancer outcomes among Black women.

Background

Preterm birth in the U.S. is higher than other comparable countries. Babies born preterm are at higher risk of life-threatening complications in their first days as well as a range of health and educational problems over the life course. Despite recent declines in preterm birth, significant racial/ethnic disparities persist. A growing body of literature suggests conditions in the places where people live, especially during critical time periods of development, may be playing a fundamental role in shaping the development of maternal health, and disparities in birth outcomes in the subsequent generation. However, this literature is limited by cross-sectional neighborhood and health data and incomplete definition and measurement of complex historical and economic processes that shape neighborhood environments. The overarching goals of this study are 1) to expand current measurement of neighborhood contexts to capture historical and economic processes of structural marginalization that have shaped them, and to assess the relationship between these expanded measures and preterm birth 2) to develop and apply a framework informed by structural marginalization to catalyze a next-generation practice of Maternal and Child Health.

Method

The Life Course Social Context database, which contains geocoded birth records linked between mothers and babies in California, provides a unique opportunity to assess the relationship between neighborhood-level exposures experienced at two different stages of a mother’s life course (early childhood and adulthood) and preterm birth in the next generation. Using these data and other census measures, we construct histories of neighborhood poverty going back to 1970 and examine associations between these neighborhood poverty histories and preterm birth. Next, we assess the relationship between structural neighborhood inequality and preterm birth and preterm birth disparities, using measures of income inequality, racial/ethnic inequality and a combined measure of income and racial/ethnic inequality. Finally, we develop a conceptual model for understanding the broader context in which inequities in birth outcomes arise and provide case examples and lessons for future development of a next-generation MCH practice that will address the root causes of inequities in birth outcomes.

Significance

Clearer understanding of complex neighborhood processes and how they shape health through generations is vital for the development of targeted and impactful public health programs. The development and assessment of new measures that approximate structural forces underlying neighborhood conditions shaping health over the life course will help direct the scope and scale of policy and practice efforts aimed at improving health and reducing inequities in birth outcomes. This study aims to contribute to more complete definition, measurement, and intervention for historical and structural forces that shape neighborhood conditions.

Background

Methods

Results

Conclusions

Introduction

Methods

Results

Conclusion

Objective

Design

Setting

Participants

Results

Conclusions