A statistical framework for culturally competent inflammation assessment: Interactions between culture, geography, and biology

Cox, Maria

Permalink

https://hdl.handle.net/2142/125771 Copy

Description

Title

A statistical framework for culturally competent inflammation assessment: Interactions between culture, geography, and biology

Author(s)

Cox, Maria

Issue Date

2024-07-02

Director of Research (if dissertation) or Advisor (if thesis)

Clancy, Kathryn

Doctoral Committee Chair(s)

• Clancy, Kathryn
• Malhi, Ripan

Committee Member(s)

• Allan, Brian
• Stadtmueller, Beth
• Inoue, Makoto

Department of Study

School of Integrative Biology

Discipline

Ecol, Evol, Conservation Biol

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Inflammation
• Statistics
• Modeling Framework
• Poland
• Method
• Immunology
• Public Health
• C-Reactive Protein
• Interleukin 6
• Cortisol
• C-peptide
• Physiology
• Psychosocial

Abstract

Inflammation response and resolution are complex processes that are heavily influenced by external input. Inflammation outcomes are a result of complex interactions between geography, culture, and evolutionarily conserved biological processes. Geography and culture produce spatial distributions in inflammation patterns as a result of environmental constraints, resource availability, and cultural values and practices. There is a lack of comprehensive statistical treatment that includes cultural factors in inflammation research. This dissertation presents a statistical framework for evaluating inflammation contributors that is inherently culturally competent. This framework integrates cultural, geographical, and biological factors and consists of three stages. The first stage focuses on biological confounding in the dataset and robust model building. The second stage assesses broad trends in how overarching inflammation stressors and buffers are functioning in the sample. This stage is a cost- and time-saving measure, providing efficient hypothesis generation so that incorrect associations and interventions are not pursued. Stage Three is the standard hypotheses testing and intervention development currently employed in inflammation research and public health. This dissertation provides an example of how to apply Stages One and Two on longitudinal samples with both biomarker and questionnaire data. The example sample consists of 88 rural Polish women. These women did not have reported health conditions and were considered a low-inflammation sample. Data were collected in the Beskid Wyspowy region of southern Poland. This area has been undergoing a transition from subsistence farming to market economy since the fall of the Soviet Union. Application of Stage One to this sample identified biomarker values, age, and length of the luteal phase of the menstrual cycle as confounding variables to be included as controls in model refitting. Physiological and psychosocial stressors and buffers were divided in the demonstration of Stage Two. Higher inflammation status was associated with higher body fat percentage, dehydration, parity of one or four, not currently working, marriage, and the presence of an adverse childhood event. Lower inflammation status was associated with higher time spent asleep, engaging in sweat-inducing physical activity, not owning a dog, and higher perception of daily happiness and satisfaction. Alcohol consumption was associated with varied inflammation status depending on biomarker. There was also a U-shaped pattern identified in cortisol results that may provide evidence for a narrow optimal window for homeostatic cortisol regulation. All of these represent hypotheses that can be developed in Stage Three application. Some of these trends run counter to what is found in the literature, likely due to cultural factors such as political landscape, highlighting the need for culturally competent assessment.

Graduation Semester

2024-08

Type of Resource

Thesis

Handle URL

https://hdl.handle.net/2142/125771

Copyright and License Information

Copyright 2024 Maria Cox

Owning Collections