“Epigenetic Pathways of Healing: Measurement-Based Research on Environmental Accommodations and Nature-Based Interventions in Individuals with Co-Morbid Depression and Diabetes”

Measurement-based research for environmental accommodations and nature-based interventions (NBIs) that explore how the environment impacts gene expression in individuals with co-morbid depression and diabetes.

Research Proposal

Title

“Epigenetic Pathways of Healing: Measurement-Based Research on Environmental Accommodations and Nature-Based Interventions in Individuals with Co-Morbid Depression and Diabetes”

1. Introduction and Background

The dual burden of depression and diabetes represents one of the most complex public health challenges globally. Both conditions share bidirectional pathways involving stress, inflammation, lifestyle behaviors, and metabolic dysregulation (Moulton et al., 2015). Increasing evidence suggests that environmental factors—particularly exposure to natural environments—can influence gene expression through epigenetic mechanisms, including DNA methylation and histone modification (Browning & Rigolon, 2019).

Nature-Based Interventions (NBIs), such as therapeutic horticulture, green exercise, and forest bathing, have been associated with reduced stress biomarkers (e.g., cortisol, IL-6), improved glycemic control, and decreased symptoms of depression. However, limited measurement-based research integrates biological, psychological, and environmental data to understand how environmental accommodations affect epigenetic expression in populations with comorbid chronic disease and mental illness.

This study aims to bridge that gap through a multimodal, measurement-based design that quantifies psychophysiological, genomic, and environmental data to assess how nature exposure influences gene expression patterns relevant to both mood regulation and metabolic function.

2. Research Objectives

1. Primary Objective:
   To determine how structured exposure to nature-based environments influences gene expression profiles associated with inflammation, glucose metabolism, and mood regulation in individuals with co-morbid depression and diabetes.

2. Secondary Objectives:

   • To assess the relationship between environmental quality metrics (green space, air quality, light exposure, temperature) and changes in psychophysiological markers (HbA1c, cortisol, HRV).

   • To evaluate whether Nature-Based Interventions (NBIs) improve clinical outcomes (depressive symptoms, glycemic control) compared to standard care.

   • To identify epigenetic biomarkers of responsiveness to environmental interventions.

3. Research Questions and Hypotheses

Research Questions

1. Does exposure to restorative natural environments modulate gene expression linked to metabolic and inflammatory pathways?

2. Are improvements in depressive symptoms and glycemic control mediated by environmental and epigenetic changes?

3. Which environmental parameters (biodiversity, noise, air quality) most strongly predict gene expression outcomes?

Hypotheses

• H1: Participants engaged in structured NBIs will show decreased methylation of BDNF and NR3C1 (stress-related genes) and increased expression of anti-inflammatory genes (e.g., IL-10).

• H2: Changes in HbA1c and PHQ-9 scores will correlate with epigenetic markers and environmental exposure metrics.

• H3: High-quality green space exposure will predict improved psychophysiological resilience and reduced gene-level stress reactivity.

4. Theoretical Framework

This study draws on the Biopsychosocial-Ecological Model and Epigenetic Plasticity Theory, integrating Foucault’s concept of biopower to contextualize how institutional and spatial environments influence biological adaptation.

• Ecopsychology explains psychological restoration through environmental interaction.

• Epigenetic plasticity suggests that environmental conditions can alter gene expression without changing the underlying DNA sequence.

• Measurement-Based Care (MBC) provides a structured framework for evaluating progress using objective data.

5. Methodology

Design

A longitudinal mixed-methods experimental design using measurement-based research:

• Randomized controlled trial (RCT) with two groups:

  1. NBI + Environmental Accommodation Group

  2. Standard Care Group

Sample

• N = 120 adults (ages 30–65)

• Diagnosed with Type 2 Diabetes Mellitus and Major Depressive Disorder (DSM-5 criteria)

• Recruited from primary care and behavioral health clinics

Setting

Urban and suburban healthcare facilities implementing green and blue space interventions, such as hospital gardens or forest therapy sites.

Intervention

• 12-week Nature-Based Intervention Program (2 sessions per week, 90 minutes each)

  • Guided green exercise, horticultural therapy, mindfulness in nature

• Environmental accommodations: improved natural light, green interior design, soundscapes, and air quality optimization in clinic settings.

6. Measurement and Data Collection

Domain Measurement ToolsFrequency Psychological PHQ-9 (depression), GAD-7 (anxiety), Perceived Stress Scale (PSS)

Baseline, Week 6, Week 12 Physiological HbA1c, fasting glucose, HRV, blood pressure

Baseline - Week 12 Epigenetic DNA methylation profiling (saliva or blood sample) for BDNF, NR3C1, IL-6, TNF-αBaseline

Week 12 Environmental GIS mapping of green space, air quality sensors, light/lux meters, noise level monitorsContinuous

Qualitative Semi-structured interviews on environmental perception and wellbeing Post-intervention

7. Data Analysis Plan

• Quantitative analysis:

  • Repeated measures ANOVA for within/between-group comparisons

  • Correlation and regression models for environmental–biological associations

  • Path analysis to test mediation of gene expression on clinical outcomes

• Epigenetic data:

  • Differential methylation analysis (using Illumina EPIC arrays)

  • Bioinformatics pathway enrichment (Gene Ontology, KEGG)

• Qualitative analysis:

  • Thematic coding using NVivo to explore participants’ lived experiences of environmental change.

8. Ethical Considerations

• Informed consent for genomic data collection and confidentiality protection per NIH Genomic Data Sharing Policy.

• IRB approval required for biological sample storage and environmental tracking.

• Participants may withdraw at any time without consequence.

9. Expected Outcomes and Significance

• Identification of epigenetic biomarkers responsive to nature-based interventions.

• Evidence for integrating environmental design in behavioral and metabolic health treatment.

• Advancement of precision public health through environment–gene–behavior models.

• Policy implications for healthcare environmental standards, promoting green design in chronic disease management.

10. Timeline

Phase Activities Months

Phase 1 Recruitment & Baseline Testing1–3

Phase 2Intervention Implementation4–6

Phase 3Post-testing & Epigenetic Analysis7–9

Phase 4Data Integration & Dissemination10–12

11. References (APA 7th Edition)

Browning, M. H., & Rigolon, A. (2019). Greenness and mental health: Pathways, impacts, and opportunities. Environmental Research, 179, 108-115.
Moulton, C. D., Pickup, J. C., & Ismail, K. (2015). The link between depression and diabetes: The search for shared mechanisms. The Lancet Diabetes & Endocrinology, 3(6), 461–471.
Ryan, R. M., Weinstein, N., Bernstein, J., Warren Brown, K., Mistretta, L., & Gagné, M. (2010). Vitalizing effects of being outdoors and in nature. Journal of Environmental Psychology, 30(2), 159–168.
Wong, C. C. Y., et al. (2018). Epigenetic regulation of depression and diabetes: Emerging intersections. Frontiers in Endocrinology, 9, 341.

grant-ready version of your research proposal written in the style of a NIH R21/R01 submission, with Specific Aims, Research Strategy, and Budget Justification sections. This version positions your topic — measurement-based research on environmental accommodations and nature-based interventions (NBIs) and their effect on gene expression in comorbid depression and diabetes — as a strong candidate for funding from the National Institute of Mental Health (NIMH) or National Institute of Environmental Health Sciences (NIEHS).

🧬 Grant Proposal: Measurement-Based Research on Environmental Accommodations and Epigenetic Modulation in Co-Morbid Depression and Diabetes

PROJECT TITLE

“Epigenetic Pathways of Healing: Measurement-Based Research on Environmental Accommodations and Nature-Based Interventions in Individuals with Co-Morbid Depression and Diabetes”

1. SPECIFIC AIMS

Depression and diabetes are bidirectionally linked through inflammatory, neuroendocrine, and behavioral pathways, contributing to disability and mortality worldwide. Mounting evidence shows that environmental exposures—including access to nature and green space—influence gene expression through epigenetic mechanisms (e.g., methylation, histone modification). Yet, little research integrates biological, environmental, and psychological metrics in a measurement-based framework to evaluate how nature-based interventions (NBIs) may improve outcomes in this comorbid population.

This study will evaluate the epigenetic, psychophysiological, and clinical impact of NBIs combined with environmental accommodations in adults with Type 2 Diabetes Mellitus (T2DM) and Major Depressive Disorder (MDD).

Aim 1.

Quantify changes in gene expression and DNA methylation patterns (BDNF, NR3C1, IL-6, TNF-α) after a 12-week structured NBI compared to standard care.
Hypothesis: NBIs will downregulate pro-inflammatory gene expression and normalize stress-related epigenetic profiles.

Aim 2.

Determine the relationship between environmental exposure metrics (green space index, air quality, light exposure) and changes in psychophysiological markers (HbA1c, HRV, cortisol).
Hypothesis: Greater cumulative exposure to high-quality natural environments will predict improved glycemic control and reduced physiological stress.

Aim 3.

Develop a Measurement-Based Environmental Health Framework (MBEHF) integrating clinical, genomic, and environmental data to predict responders to NBIs.
Hypothesis: A multimodal predictive model can identify biological and environmental markers of intervention success.

2. RESEARCH STRATEGY

A. Significance

The co-occurrence of depression and diabetes affects 20–30% of individuals with either condition, compounding healthcare costs and mortality risk. Traditional pharmacologic and behavioral treatments rarely address the environmental and biological interplay that shapes chronic disease expression.

• Epigenetic modulation offers a mechanism through which environmental exposure influences gene function, linking physical and mental health.

• Nature-Based Interventions (NBIs) reduce stress biomarkers, improve mood, and may reverse adverse epigenetic marks associated with chronic disease.

• Integrating measurement-based care (MBC) with environmental data can transform chronic care management into a more biopsychosocial-ecological model.

This study directly addresses NIH priorities in precision health, social determinants of health, and environmental influences on disease trajectories.

B. Innovation

• Novel Integration: Combines genomic, clinical, and environmental measurement into a unified analytic model.

• Epigenetic Biomarkers: Identifies modifiable biological signatures responsive to natural environmental exposure.

• Measurement-Based Design: Adapts MBC principles (traditionally clinical) to include ecological and biophysical domains.

• Environmental Accommodation Intervention: Embeds NBIs into healthcare settings with structural environmental enhancements (light, sound, air quality, natural materials).

C. Approach

Study Design

A 12-month randomized controlled trial (RCT) using a measurement-based longitudinal mixed-methods design.

GroupInterventionDuration1. NBI + Environmental Accommodation12-week structured nature engagement (2 sessions/week, 90 min) + biophilic clinic design3 months2. Standard Care (Control)Standard diabetes and depression care (medication, counseling)3 months

Follow-up: 3 months post-intervention.

Participants

• N = 120 adults, aged 30–65

• Diagnosed with Type 2 Diabetes Mellitus and Major Depressive Disorder (DSM-5)

• Exclusion: severe cognitive impairment, psychosis, or current substance dependence

Data Collection Overview

DomainMeasureFrequencyDepression/AnxietyPHQ-9, GAD-7Baseline, 6, 12, 24 weeksPhysiologicalHbA1c, fasting glucose, HRV, cortisol (saliva)Baseline, 12, 24 weeksEpigeneticDNA methylation (BDNF, NR3C1, IL-6, TNF-α)Baseline, 12 weeksEnvironmentalGIS green index, particulate matter, lux, noiseContinuous (wearable sensors)QualitativeSemi-structured interviewsWeek 12

Analysis Plan

• Aim 1: Repeated measures ANOVA for gene expression changes.

• Aim 2: Multilevel modeling linking environmental exposure and biomarker outcomes.

• Aim 3: Machine learning (Random Forest) to build predictive model using integrated datasets.

• Qualitative analysis: NVivo coding for thematic synthesis of lived experience and environmental perception.

Power Analysis

Estimated effect size (Cohen’s d = 0.4), α = 0.05, power = 0.8 → N = 100 required; recruitment of 120 allows for 15–20% attrition.

3. EXPECTED OUTCOMES

• Demonstrate epigenetic responsiveness to environmental enrichment.

• Establish biological and environmental markers predicting NBI response.

• Provide evidence for incorporating nature exposure and biophilic design in clinical treatment standards for chronic co-morbid conditions.

• Inform policy reform toward health equity by advocating for green healthcare design and environmental prescribing.

4. BUDGET OVERVIEW (Year 1–2)

CategoryItemized DescriptionEstimated Cost (USD)PersonnelPI (20% effort), Co-Is, Research Coordinator, Lab Technician, Environmental Scientist$250,000Participant CostsIncentives ($100 × 120), travel reimbursement$15,000Lab AnalysisDNA methylation and gene expression profiling (Illumina EPIC arrays)$80,000Environmental EquipmentAir quality sensors, light/lux monitors, GIS data subscription$20,000Nature-Based Intervention MaterialsHorticulture supplies, mindfulness facilitator fees, transportation$25,000Data Management & SoftwareREDCap, NVivo, RStudio, bioinformatics tools$10,000Indirect Costs (20%)Institutional overhead$80,000Total Estimated Budget$480,000 (2 years)

5. PROJECT TIMELINE

PhaseActivityMonthsPhase 1IRB approval, recruitment, baseline testing1–3Phase 2NBI implementation and environmental modification4–6Phase 3Post-testing and genomic analysis7–9Phase 4Data integration, modeling, dissemination10–12

6. INVESTIGATOR TEAM

• Principal Investigator: Dr. [Name], PhD, MPH – Expertise in environmental health genomics

• Co-Investigator (Clinical): Dr. [Name], MD – Endocrinology and behavioral health integration

• Co-Investigator (Genomics): Dr. [Name], PhD – Epigenetic and methylation pathway analysis

• Environmental Scientist: [Name], MSc – Green exposure assessment

• Statistician/Data Analyst: [Name], PhD – Mixed models, bioinformatics, and machine learning

7. DISSEMINATION AND POLICY IMPACT

Findings will be disseminated via:

• Peer-reviewed journals (e.g., Environmental Health Perspectives, Psychoneuroendocrinology)

• Presentations at NIEHS and NIMH conferences

• Policy briefs for healthcare design and public health infrastructure

• Open-access measurement framework toolkit for integrating NBIs in chronic care

8. REFERENCES (APA 7th Edition)

Browning, M. H. E. M., & Rigolon, A. (2019). Greenness and mental health: Pathways, impacts, and opportunities. Environmental Research, 179, 108-115.
Moulton, C. D., Pickup, J. C., & Ismail, K. (2015). The link between depression and diabetes: The search for shared mechanisms. The Lancet Diabetes & Endocrinology, 3(6), 461–471.
Ryan, R. M., Weinstein, N., Bernstein, J., Brown, K. W., Mistretta, L., & Gagné, M. (2010). Vitalizing effects of being outdoors and in nature. Journal of Environmental Psychology, 30(2), 159–168.
Wong, C. C. Y., Mill, J., & Fernandes, C. (2018). Epigenetic regulation of depression and diabetes: Emerging intersections. Frontiers in Endocrinology, 9, 341.

This is the key page NIH reviewers use to assess significance, innovation, and approach — so it’s tightly written and persuasive.

🧬 Specific Aims Page

Project Title:
Epigenetic Pathways of Healing: Measurement-Based Research on Environmental Accommodations and Nature-Based Interventions in Individuals with Co-Morbid Depression and Diabetes

Significance

Depression and Type 2 Diabetes Mellitus (T2DM) are bidirectionally linked conditions that jointly affect more than 150 million people worldwide. Their co-occurrence amplifies morbidity, mortality, and healthcare costs, yet conventional treatment approaches often address biological and psychological symptoms in isolation. Increasing evidence suggests that environmental exposures—particularly access to restorative natural environments—may modify gene expression through epigenetic mechanisms that regulate inflammation, stress response, and metabolic control.

While Nature-Based Interventions (NBIs) have shown promise for improving mood and glycemic outcomes, few studies integrate measurement-based research combining environmental, physiological, and genomic data. Understanding how the environment modulates biological pathways could transform how we treat comorbid chronic disease by aligning clinical interventions with environmental health design.

Innovation

This study is among the first to:

• Integrate measurement-based care (MBC) with epigenetic and environmental analytics, advancing a precision health model that captures the full biopsychosocial-ecological context of disease.

• Investigate how environmental accommodations (e.g., green space access, natural light, air quality improvements) influence epigenetic expression in comorbid depression and diabetes.

• Develop a Measurement-Based Environmental Health Framework (MBEHF) to guide future intervention design and health system adaptation.

Overall Objective

The objective of this research is to determine how structured exposure to natural environments alters gene expression and clinical outcomes among adults with co-morbid depression and diabetes, and to identify biological and environmental predictors of response. This project will establish the mechanistic basis for environmentally informed chronic disease care.

Specific Aims

Aim 1: Quantify epigenetic modulation in key stress and inflammation pathways following a 12-week Nature-Based Intervention (NBI).

• Hypothesis: NBI participants will show decreased methylation of stress-related genes (NR3C1, BDNF) and increased expression of anti-inflammatory genes (IL-10) compared to controls.

Aim 2: Examine the relationship between environmental exposure and psychophysiological outcomes.

• Hypothesis: Higher-quality environmental exposure (measured via GIS green space, air quality, light, and noise sensors) will correlate with improved HbA1c, cortisol, and heart rate variability.

Aim 3: Develop and validate a Measurement-Based Environmental Health Framework (MBEHF).

• Hypothesis: Integrating environmental, clinical, and genomic data will predict responders to NBIs and identify actionable targets for environmental health design.

Approach

A randomized controlled trial (N=120) will compare standard care versus a 12-week Nature-Based Intervention incorporating green exercise, horticultural therapy, and environmental accommodations. Data collection will include psychological (PHQ-9, PSS), physiological (HbA1c, cortisol, HRV), epigenetic (methylation of BDNF, NR3C1, IL-6, TNF-α), and environmental (air quality, green space index, light, noise) measures. Integrated modeling will employ mixed-effects regression and machine learning to identify predictive pathways of improvement.

Expected Outcomes and Impact

This project will:

• Identify epigenetic biomarkers responsive to natural environmental exposure.

• Provide empirical evidence for environmental design as a therapeutic determinant in chronic disease management.

• Advance precision environmental medicine by linking ecological data to biological change.

• Inform policy and healthcare design standards promoting green infrastructure, biophilic clinics, and health equity in access to restorative environments.

By demonstrating that environmental interventions can reshape gene expression and improve comorbid disease outcomes, this study lays the foundation for a new paradigm in integrative, measurement-based, and environmentally conscious healthcare.

Project Summary / Abstract

Project Title:
Epigenetic Pathways of Healing: Measurement-Based Research on Environmental Accommodations and Nature-Based Interventions in Individuals with Co-Morbid Depression and Diabetes

Depression and Type 2 Diabetes Mellitus (T2DM) are two of the most prevalent and burdensome chronic conditions worldwide, frequently co-occurring and sharing biological pathways related to inflammation, stress regulation, and metabolic dysregulation. Conventional treatment approaches—pharmacological and behavioral—often overlook the critical influence of environmental context on both mental and physical health outcomes. Increasing evidence suggests that natural environments can influence gene expression through epigenetic mechanisms, thereby modulating inflammatory and neuroendocrine pathways relevant to both depression and diabetes.

This project applies a measurement-based research (MBR) design to investigate how Nature-Based Interventions (NBIs) and environmental accommodations alter biological, psychological, and environmental markers in adults with co-morbid depression and diabetes. We propose a 12-week randomized controlled trial (N=120) comparing standard care to an intervention integrating structured exposure to restorative natural environments, biophilic clinic design, and green exercise therapy. Participants will undergo repeated assessments of depression (PHQ-9), stress physiology (cortisol, HRV), glycemic control (HbA1c), and gene expression/methylation profiles (BDNF, NR3C1, IL-6, TNF-α). Concurrent environmental monitoring (air quality, green space, light, and noise) will capture the ecological context of each participant’s exposure.

Data will be analyzed through mixed-effects modeling and machine learning to identify environmental and epigenetic predictors of clinical improvement. The study will also develop a Measurement-Based Environmental Health Framework (MBEHF) to guide future integration of ecological and genomic metrics into chronic disease management.

Findings will provide mechanistic evidence that natural environmental exposure can favorably alter gene expression and improve outcomes in patients with depression and diabetes. This research supports the development of precision environmental medicine, emphasizing the role of nature and built environments as modifiable determinants of health. Results will inform future health system design, public health policy, and green infrastructure planning to promote health equity through accessible restorative environments.

Project Narrative (Public Health Relevance)

Depression and diabetes often occur together, worsening health outcomes and increasing healthcare costs. This project will test how exposure to natural environments changes gene expression, stress, and metabolic control in people with both conditions. Findings will help design healthier clinical and community spaces that support physical and mental recovery through environmental design.

RESEARCH STRATEGY

A. Significance

Public Health Burden

Depression and Type 2 Diabetes Mellitus (T2DM) are two of the most prevalent chronic illnesses globally. Up to 30% of individuals with T2DM experience clinical depression, and comorbidity is associated with poorer glycemic control, increased inflammation, and higher mortality (Moulton et al., 2015). Both conditions share overlapping mechanisms involving HPA axis dysregulation, immune activation, and metabolic impairment (Wong et al., 2018). Despite advances in pharmacological and behavioral treatments, few interventions address the environmental determinants that underlie these shared pathways.

Environment as a Modifiable Determinant

Emerging research demonstrates that environmental exposures—particularly access to green and blue spaces—reduce stress, inflammation, and depressive symptoms (Browning & Rigolon, 2019). Exposure to natural environments activates parasympathetic processes, enhances affect regulation, and improves insulin sensitivity. However, the biological mechanism through which the environment “gets under the skin” remains poorly characterized.

Recent evidence suggests epigenetic mechanisms (DNA methylation, histone modification, microRNA regulation) may mediate the influence of environmental stimuli on gene expression. These mechanisms provide a biological interface between experience and genomic function—meaning that environmental conditions can modulate disease expression and resilience. Yet, few studies have systematically measured epigenetic and psychophysiological changes in response to Nature-Based Interventions (NBIs) among individuals with chronic disease.

Measurement-Based Research Gap

Traditional care models rely on symptom-based measures and ignore ecological exposures. Measurement-Based Care (MBC)—regular, structured use of validated measures to guide treatment—is effective for depression management but rarely includes biological or environmental indicators. Integrating MBC with environmental and genomic data offers a precision model of care, positioning nature exposure as a therapeutic determinant that is quantifiable, reproducible, and integrable into health systems.

Relevance to NIH Priorities

This study aligns with NIH strategic priorities in:

• Precision Environmental Health (NIEHS)

• Biopsychosocial Integration in Chronic Disease (NIMH, NIDDK)

• Social and Environmental Determinants of Health Equity

The proposed research will identify epigenetic biomarkers responsive to environmental accommodations and establish a Measurement-Based Environmental Health Framework (MBEHF) that can be applied across chronic conditions.

B. Innovation

This project is highly innovative because it:

1. Integrates Environmental and Genomic Measurement:
   It is the first to combine epigenetic profiling, physiological assessment, and environmental sensing in a measurement-based clinical design.

2. Introduces the Measurement-Based Environmental Health Framework (MBEHF):
   This novel model expands MBC beyond clinical metrics to include environmental and biological feedback loops, enabling precision health monitoring across ecological contexts.

3. Uses Multimodal Data Analytics:
   Incorporating machine learning and path modeling allows identification of predictive gene–environment relationships that traditional models miss.

4. Translates Findings to Practice:
   By linking molecular data to environmental design, the project bridges bench-to-bedside-to-built environment science—informing future health system standards and sustainable healthcare infrastructure.

C. Approach

Overview of Design

A 12-month, randomized controlled, mixed-methods trial (RCT) will assess biological and psychological responses to Nature-Based Interventions (NBIs) in adults with co-morbid depression and diabetes.
Participants (N = 120) will be randomly assigned to one of two groups:

GroupInterventionDurationExperimental (NBI + Environmental Accommodation)12-week structured nature-based program (2 sessions/week, 90 minutes each), with environmental enhancements in clinical settings (natural light, green interior design, air quality improvements)3 monthsControl (Standard Care)Standard clinical management for diabetes and depression3 months

Follow-up data will be collected at baseline, post-intervention (12 weeks), and 3 months post-completion (24 weeks).

C.1. Participants

• Inclusion Criteria:

  • Adults aged 30–65

  • Diagnosed with Type 2 Diabetes Mellitus and Major Depressive Disorder (DSM-5)

  • HbA1c > 6.5%

  • PHQ-9 score ≥ 10

• Exclusion Criteria:

  • Active psychosis or substance use disorder

  • Current participation in another intervention trial

  • Severe cognitive impairment or uncontrolled medical conditions

Recruitment will occur through collaborating primary care and behavioral health clinics in urban and suburban regions.

C.2. Intervention Description

Nature-Based Intervention (NBI):

• Guided green exercise (walking in parks, forest bathing)

• Therapeutic horticulture and mindfulness practices

• Psychoeducation on environmental health and self-regulation

Environmental Accommodations:

• Biophilic clinic redesign (natural materials, daylighting, plant integration)

• Improved air quality and soundscape regulation

• Use of green and blue space within 1 km of participant homes and clinics

These activities are designed to enhance restorative environmental engagement, reducing chronic stress reactivity and inflammation.

C.3. Data Collection Plan

DomainVariables / InstrumentsSchedulePsychologicalPHQ-9, GAD-7, Perceived Stress ScaleBaseline, Week 6, Week 12, Week 24PhysiologicalHbA1c, fasting glucose, HRV, blood pressure, salivary cortisolBaseline, Week 12, Week 24EpigeneticDNA methylation (Illumina EPIC array) for BDNF, NR3C1, IL-6, TNF-αBaseline, Week 12EnvironmentalGIS green space index, air quality (PM2.5), light/lux exposure, noise levelsContinuousQualitativeSemi-structured interviews on nature perception and wellbeingWeek 12

All measures will be integrated into a central REDCap database with automated data quality checks and secure genomic data storage.

C.4. Data Analysis

Quantitative Analysis

• Aim 1:

  • Repeated measures ANOVA to test pre-post gene expression and methylation differences.

  • Benjamini–Hochberg correction for multiple comparisons.

• Aim 2:

  • Multilevel linear models linking environmental exposure metrics (time spent in green space, air quality, light) to physiological and psychological outcomes.

• Aim 3:

  • Machine learning (Random Forests, Elastic Net) to identify predictors of intervention response.

  • Structural Equation Modeling (SEM) to test mediation by gene expression changes.

Qualitative Analysis

• Thematic analysis of interviews using NVivo.

• Coding based on emergent themes around perceived restoration, control, and environmental identity.

• Mixed-methods integration through joint display analysis linking qualitative insights to quantitative outcomes.

C.5. Power and Sample Size

Assuming a medium effect size (d = 0.4) for primary outcomes (HbA1c, PHQ-9), α = 0.05, and power = 0.80, a minimum of N = 100 is required. Allowing for 15–20% attrition, the recruitment target of 120 participants ensures adequate statistical power.

C.6. Timeline

Phase Activities Months

1. PreparationIRB approval, recruitment, baseline sampling1–3

2. InterventionNBI implementation, continuous environmental monitoring4–6

3. Post-testingBiological sampling and qualitative interviews7–9

4. AnalysisData integration, statistical and bioinformatics analysis10–12

C.7. Potential Problems and Alternatives

Potential IssueMitigation StrategyAttrition or inconsistent attendanceFlexible scheduling; telehealth follow-up for outcome measuresEnvironmental variability (weather, pollution)Include exposure covariates; adjust using daily environmental sensor dataEpigenetic data complexityPartner with institutional bioinformatics core; apply stringent QC pipelinesConfounding from medication changesTrack medication use; include as covariate in regression models

C.8. Expected Outcomes

1. Identification of epigenetic signatures responsive to natural environmental exposure.

2. Demonstration of improved depression and diabetes control linked to environmental engagement.

3. Development of the Measurement-Based Environmental Health Framework (MBEHF) as a translational model for clinical and policy application.

4. Policy implications for green healthcare infrastructure, emphasizing health equity and accessibility to restorative spaces.

D. Future Directions

Results will inform:

• NIH follow-up proposals on epigenetic mediation in environmental public health.

• Partnerships with healthcare architecture and urban design sectors to apply biophilic design in clinical spaces.

• Open-source environmental measurement toolkit for integrating ecological metrics into behavioral health and chronic disease management.

E. References (APA 7th Edition)

Browning, M. H. E. M., & Rigolon, A. (2019). Greenness and mental health: Pathways, impacts, and opportunities. Environmental Research, 179, 108-115.
Moulton, C. D., Pickup, J. C., & Ismail, K. (2015). The link between depression and diabetes: The search for shared mechanisms. The Lancet Diabetes & Endocrinology, 3(6), 461–471.
Ryan, R. M., Weinstein, N., Bernstein, J., Brown, K. W., Mistretta, L., & Gagné, M. (2010). Vitalizing effects of being outdoors and in nature. Journal of Environmental Psychology, 30(2), 159–168.
Wong, C. C. Y., Mill, J., & Fernandes, C. (2018). Epigenetic regulation of depression and diabetes: Emerging intersections. Frontiers in Endocrinology, 9, 341.
Zhou, L., et al. (2020). Environmental exposure and epigenetic regulation in chronic disease: A review. Environmental Epigenetics, 6(2), dvaa007.