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Changes in Glycemia and Serum Lipids Following a 4-Month mHealth Walking Intervention

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Walking interventions focused on increasing step counts are typically associated with salutary effects on glycemia, fasting insulin, insulin resistance and blood lipids which may be in turn associated with improvements in cardiorespiratory fitness (peak oxygen uptake – VO2peak) and vascular

Walking interventions focused on increasing step counts are typically associated with salutary effects on glycemia, fasting insulin, insulin resistance and blood lipids which may be in turn associated with improvements in cardiorespiratory fitness (peak oxygen uptake – VO2peak) and vascular stiffness. We hypothesized that a novel 4-month, behavioral economics-based walking intervention would have favorable effects on glucose homeostasis and blood lipids and that these in turn would be related to VO2peak and vascular stiffness (carotid femoral pulse wave velocity – cfPWV).

We carried out secondary analyses on a subsample of sedentary, overweight/obese adults who participated in a 4-month, 2x2, randomized-controlled walking intervention examining the effects of goal setting (static v. adaptive goals) and rewards (immediate v. delayed) on steps/day (N=96). Fasting blood samples (n=58) were collected from participants before and after the intervention. Premenopausal females were in the follicular phase of their menstrual cycles. Lipid and glucose levels were measured using an automated chemistry analyzer, while insulin was measured using radio-immunoassay. Homeostatic model of insulin resistance (HOMA-IR) was calculated using the following formula (HOMA-IR=glucose x insulin / 405). We examined associations [partial correlations (adjusted for age)] between changes in blood biomarkers and VO2peak and cfPWV, irrespective of group, and we used linear mixed models to examine between-group differences in levels of and change in biomarker outcomes.

Groups did not differ in overall levels of, or degree of change in, biomarker outcomes (all p>0.05). Mean changes, irrespective of group, in biomarkers were as follows: glucose Δ= 0.74± 4.5mg/dl; insulin Δ= 0.09 ± 4.1 µU/ml; total cholesterol Δ= 0.24 ± 20.6 mg/dl; HDL-C Δ= 0.27 ± 5.1 mg/dl; LDL-C Δ= 1.3 ± 19.9 mg/dl; triglycerides Δ= 1.7 ± 27.2 mg/dl; HOMA-IR Δ = -.0548 ± 1.05). We found no significant associations between change in biomarker levels and change in VO2peak or change in cfPWV (all correlation coefficients < 0.15; p > 0.05).

A 4-month, behavioral economics-based mHealth intervention focused on increasing steps/day did not bring about favorable changes on markers of glycemia, insulin resistance and blood lipids.

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2016-05

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Investigating the Link between Active Transportation Use and Cardiometabolic Health

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This dissertation was guided by the Ecological Model of Physical Activity and Ecological Model of Obesity and sought to determine the relationship between active transportation (AT), physical activity, and cardiometabolic health among adults and ethnic minority women. Chapter 2

This dissertation was guided by the Ecological Model of Physical Activity and Ecological Model of Obesity and sought to determine the relationship between active transportation (AT), physical activity, and cardiometabolic health among adults and ethnic minority women. Chapter 2 presents an investigation into the relationship between walking for AT and cardiometabolic health among adults through systematic review. Chapter 3 presents an exploration of the cross-sectional relationships of AT and moderate-to-vigorous physical activity (MVPA) with cardiometabolic health among African American (AA) and Hispanic/Latina (HL) women from Texas. Chapter 4 presents an investigation into the cross-sectional relationship of AT on cardiometabolic health and physical activity among primarily HL women.

In Chapter 2, walking for AT was found to be related to smaller waist circumference, lower blood pressure, and lower prevalence of abdominal obesity and hypertension, and that differences may exist based on sex. Walking for AT was not clearly defined, and criteria used to determine the presence of cardiometabolic outcomes were inconsistent. No significant relationships between AT and cardiometabolic health were found in Chapter 3 or 4; however, AT users had slightly better cardiometabolic health. AT users had significantly higher levels of self-reported total physical activity compared to those who did not use AT in Chapter 3. Furthermore, a significant relationship was found between MVPA and diastolic blood pressure. Associations differed by ethnicity, with MVPA being inversely related to body fat in both AA and HL women, but to body mass index only in AA women. AT users were found to be seven times more likely to meet 2018 national MVPA recommendations than non-AT users in Chapter 4. Across all studies, measures of AT were subjective and of low quality, potentially limiting the ability to detect significant findings.

High quality randomized controlled studies should be conducted using clearly defined, objective measures of AT, and analyzed based on sex and race/ethnicity. Clinicians should recommend AT use to promote meeting MVPA recommendations where appropriate, potentially resulting in improved cardiometabolic health. Policymakers should advocate for changes to the built environment to encourage AT use and MVPA to improve public health.

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2019