Makoyoh'Sokoi - The Wolf Trail Program Expansion Project - Supporting Indigenous Women to Celebrate Good Health

Participants' engagement in their own healthcare as measured by the Patient Activation Measure (PAM™). Patient activation implies a "willingness and ability to take independent actions to manage their health and care". The PAM™ score has been used to assess effectiveness of diabetes prevention programming in Indigenous populations. It is a well-validated tool to assess effectiveness of interventions for many chronic diseases and small increases in PAM score have been shown to correlate to reduced healthcare costs and improved health status. PAM™ levels are defined as follows: Level 1 <47, Level 2 47.1 - 55.1, Level 3 55.2 - 67.0, Level 4 >67.1. To assess changes in PAM™ scores over time the analysis will focus on score changes within each level. Previous studies show that most change occurs within the lowest levels of activation (Levels 1 and 2), and patients with lower activation also tend to have higher utilization and costs. So, both the PAM™ score and PAM™.

The investigators use pedometers to track weekly step counts. Pedometers were chosen to assess physical activity because they were successfully used in the previous MKS programs, provide immediate motivational feedback to participants, and are cost effective and validated. Pedometer use will be evaluated the following ways: 1) # who are compliant with bringing their pedometers weekly and # who have kept track of their total steps, 2) average % change in weekly step count between Time 2, Time 3 and Time 4 (or last class attended) (presented as mean +/- SD, median and range). 3) % reporting continued use of their pedometer at Time 5. 4)

The Neighbourhood - International Physical Activity Questionnaire (N-IPAQ) will be completed. The N-IPAQ is a reliable, validated, and easy to administer questionnaire that measures neighbourhood-based physical activity There are two forms of output from scoring the N-IPAQ. Results can be reported in categories (low activity levels, moderate activity levels or high activity levels) or as a continuous variable (MET minutes a week). MET minutes represent the amount of energy expended carrying out physical activity. For continuous variable such as weekly step counts, MET minutes, the mean (SD) will be shown and statistical methods including paired t-test and repeated measurement ANOVA, linear (mixed effect) regression methods will be used to discover whether the program participants will have more step counts over time. For categorical data such as the level of physical activity on the N- IPAQ, the frequency distribution will be presented and Chi-square test and generalized

Change in Mental Health Continuum-Short Form (MHC-SF) category uses three categories (languishing, moderate, flourishing) coded as 0, 1, and 2. % of participants in each category at T1, T4 and T5 will be reported along with change in category over time. Statistical method for example, two proportion test, and Chi-square tests will be used to identify whether the programming will improve the participants' well-being in three components: emotional, social, and psychological. In addition, the correlation analysis between this MHC-SF measures with other outcomes will help to reveal whether this outcome is correlated to variables such as the 12-item Short Form Survey (SF-12), Canadian Health Measures Survey GEN_18, Patient Activation Measure (PAM) and BMI (kg/m2) etc. Generalized linear mixed model will also be used for the repeated measurements collected pre and post program considering other potential factors or outcomes as adjusting covariates in the model.

The Medicine Wheel is a visual tool to reflect the holistic view of balance in one's life. The four quadrants are comprised of Physical, Emotional, Mental, and Spiritual. Qualitative methods will be used to explore how the program has impacted where participants are with respect to the Medicine Wheel at the end of the program, using a Medicine Wheel Likert Scale.

A peer-researcher will be identified during the second month of each program. The peer-researcher will be trained in the photo/video-voice method. Peer-researchers will meet with participants and educate the participant on how to create a photovoice/video to answer the question. The Medicine Wheel Likert Scale is incorporated into this reflective process. The peer-researcher will support them with editing and compile the exercises.

Blood pressure, waist circumference, biochemistries, and demographic data will be collected to determine prevalence of Metabolic Syndrome (MetS) and whether this changes throughout the program.

The revised National Cholesterol Education Program Adult Treatment Panel III criteria, state that metabolic syndrome is present if three or more of the following criteria are met: abdominal obesity (waist circumference > 102 cm for men and > 88 cm for women)- numbers vary based on ethnicity; elevated plasma triglyceride level (≥ 1.7 mmol/L); decreased high-density lipoprotein (HDL) cholesterol level (< 1.03 mmol/L for men and < 1.30 mmol/L for women); elevated blood pressure (≥ 130/85 mm Hg); or elevated fasting glucose level (≥ 6.1 mmol/L).

Report % with Met Syndrome initially for whom health improved such that they did not meet criteria at Time 4 (immediately post-program) and Time 5 (52 weeks post the end of the program).

As part of the investigators' understanding of participant cardiometabolic health, we will collect information on participant medication usage; decreasing or initiating medications for diabetes or cardiovascular risk reduction

The descriptive statistics will be presented with mean (SD) and frequency for categorical data. The changes in those measures be analyzed by using a variety of methods such as t-test, repeated ANOVA and mixed effect model for continuous data and generalized linear mixed effect model regression for any categorized variables.

Resting heart rate will be evaluated as an indicator of cardiometabolic health. A lower resting heart rate at subsequent measures will be considered a sign of improved fitness. Resting heart rate is also required as part of the calculation for the 1-mile walk test.

The descriptive statistics will be presented with mean (SD) and frequency for categorical data. The changes in those measures be analyzed by using a variety of methods such as t-test, repeated ANOVA and mixed effect model for continuous data and generalized linear mixed effect model regression for any categorized variables.

Information on smoking status, and changes to smoking status throughout the program, will be collected through a questionnaire. Reduced smoking frequency and smoking cessation will be viewed as a positive health change.

The descriptive statistics will be presented with mean (SD) and frequency for categorical data. The changes in those measures be analyzed by using a variety of methods such as t-test, repeated ANOVA and mixed effect model for continuous data and generalized linear mixed effect model regression for any categorized variables.

Canadian Diabetes Risk Questionnaire (CANRISK) score

Composed of 12 questions, CANRISK collects information on the following risk factors: age group, sex, ethnicity, education, BMI (kg/m2), waist circumference, daily physical activity, daily fruit and vegetable consumption, history of high blood pressure, blood sugar, family history of diabetes, smoking status and macrosomia.

The CANRISK Survey evaluates diabetes risk as "low risk" (a score lower than 21), "moderate risk" (a score of 21-32), and "high risk" (a score of 33 and over).

Report % of participants who did not have known Type-2 Diabetes Mellitus, who increased, decreased or experienced no change in CANRISK score.

Body-composition measures such as weight, height, and waist circumference will be collected, and then the investigators will calculate BMI (kg/m2), body adiposity index (BAI), and body fat percentage by using: body fat percentage= (1.20 X BMI) + 0.23 X age -5.4 (females with age >15). The data will be summarized with mean (SD) and median (IQR) for each time point at Time 1 (3 months pre-program) to Time 5 (1 year after the end of the program). The changes over time will also be evaluated by using longitudinal modeling methods (such as mixed effect model) as well as repeated measure ANOVA. The weight scale used uses impedance methods to calculate a % body fat but is limited at higher percentages. The investigators will compare percent body fat using both methods. Categorized BMI or body fat percentage based on WHO's method will be also presented with frequency and generalized linear mixed effect model will be applied to evaluate the changes over time from Time 1 to Time 5.

Grip strength is found to correlate to longevity and fitness, and as participants are exposed to strength-based trainings, the investigators will use handgrip dynamometer to track the changes in strength of participants. This data will be presented with mean (SD) in different age groups and the % change from the previous time points. Linear regression will be used to evaluate whether significant changes in grip strength are observed among participants throughout and after the program the program.

For 1-Mile Walk Test, the data of total minutes and VO2_MAX will be calculated and presented with mean -/+ SD and the categorized data based on VO2_max are also be presented with their frequency distribution in different age groups. The changes in the measures will be evaluated based on repeated ANOVA methods and linear regression by adjusting for potential factors such as age, smoking status, BMI and so on. To perform the 1-mile walking test: 1) Warm up for 5-10 minutes. 2) Start your stopwatch and start walking as fast as you can. 3) At the end of 1 mile, record your time in decimals. 4) Take your heart rate immediately. 5) Calculate VO2_max with provided formula (VO2 max = 132.853 - (0.0769 x your weight in pounds) - (0.3877 x your age) + (6.315 if you are male or 0 if you are female) - (3.2649 x your walking time) - (0.1565 x your heart rate at the end of the test)) 6) Determine the different levels based on the provided table.

Improvements in quality of life will be assessed using the EQ-5D- 5L™. The investigators are going to collect three measure from EQ-5D-5L: EQ5D profile, EQ5D Vas, EQ5D measures. In addition to presenting descriptive statistics including mean (SD) and frequencies in each level for all those measures at each time points and use t-test to evaluate the changes, longitudinal analysis will be conducted to check the changes of health state before and after the intervention. Paretian Classification of Health Change (PCHC) and Health Profile Grid (HPG) will be used to summarize the change of the profile data. Linear regression models with mixed effect for both VAS and EQ5D dimension can be used to evaluate the effect of potential determinants and the effect of the programming.

The Physical Activity Neighborhood Environment Survey (PANES) provides estimates of self- reported neighbourhood, built environment supportiveness for physical activity with some degree of test-retest reliability and construct validity. The overall PANES score should have a range of 0 to 6, with higher values indicating greater environmental support for physical activity. For each item the investigators also have a dichotomized outcome to indicate whether strongly or somewhat agree with the statement. The mean and standard deviation will be presented for the overall PANES score and percentage of participants with strongly or somewhat agree with the statement in each item. Correlations of walkability index to physical activity and fitness (and changes within these categories) will be made. Indices will be compared between sites.

Social well-being will be evaluated using Canadian Health Measures Survey (CHMS) sense of belonging question: GEN_Q18: How would you describe your sense of belonging to your local community? Would you say it is?

• Very strong
• Somewhat strong
• Somewhat weak
• Very weak

Percentage of participants in each category pre and post program will be compared and correlated with other outcome measures such as attendance, BMI, percent body fat, etc. Chi-square tests will be used to identify whether the programming will significantly change the participants' sense of belonging to their local community. Generalized linear mixed model will also be used for the repeated measurements collected pre and post program considering other potential factors such as age, income, medical history, location, education level and so on.

The Healthy Eating Index (HEI) uses a scoring system to evaluate a set of foods. The score ranges from 0 to 100 points. The total HEI score is an indication of overall diet quality and changes in the HEI score will be used to determine whether dietary practices have improved throughout the intervention.

Component scores when examined together show a pattern of diet quality. The summary statistics including the mean and standard deviation for the overall HEI and each component, will be included and the index value will be used as covariates when evaluating the changes in outcomes such as weight, BMI (kg/m2), PAM. Etc.

Individual questions adapted to address Indigenous population consumption of traditional foods and changes within this category.

Nutrition knowledge: Questions developed based on the Health Education Modules with a focus on nutrition elements. Questions: Do you understand how to 'balance your diet'? Have you learned new recipes, methods of cooking, or methods for storage of food that will help you plan your meals (follow by 'give examples please')? Do you understand the difference between proteins, fats and carbohydrates and foods that provide these nutrients? Health knowledge is assessed at the end of the program and one year later to determine changes to knowledge over time.

Food security will be evaluated using the 2-Item Food Security Screen. Percentage positively responding to food security questions and change over time will be completed and correlated with other outcome measures including nutritional intake, anthropometric changes, mental health and quality of life.

Open-ended (qualitative) survey questions will assess if there are resources (ie. medical, mental health, cultural programming, recreational, food, social, etc.) that the participant faces barriers to accessing and whether their use of these resources changes with their participation in the program.

This information will be reported in a table and will be provided to communities after the project is complete.

The investigators will present attendance rates as # participants/program, # attending <25%, 25- 50%, 50-75% and >75% of classes (mean attendance with range), a participant is defined as attending a program if they attended 50% or greater of the classes.