Outcomes and Statistical Analysis
The primary outcome measure at 12 months follow-up is the mean change in HbA1c from baseline following the interventions. The HbA1c was measured at baseline, 3, 6 and 12 months using the established standard diagnostic test method, according to the protocols of the health facilities. HbA1c was collected at each scheduled sessions with the patients in the experimental group - viz at baseline and subsequently after the lifestyle intervention at 3 months, 6 months, and 12 months. The samples were collected at fasting state at each schedule sessions, except where determined to be random. For the control group the test were done in the facility during their normal routine health checkup.
Secondary outcome measures: Changes in
Body weight: Secondary outcome measure is the mean weight change at 3, 6 and 12 months from baseline following interventions. Height, weight, and waist circumference of participants will be measured at baseline and at the proposed intervals. Height and weight of participants will be measured according to methods adopted in the various health facilities. This will be done with participants wearing light clothing and without footwear. Weight in kilograms divided by square of height in meters will be used to derive the body mass index (BMI). Waist circumference (WC) will be measured using a flexible measuring tape at the nearest 0.1 cm.
Blood pressure, glucose, and lipids profile: Blood glucose and lipids profile at 3, 6 and 12 months from baseline following interventions will be assessed. Plasma glucose, total cholesterol, high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), triglycerides will be measured by enzymatic colorimetry (Cardiochek Professional Analyser, Polymer Technology Systems, USA). Blood pressure will be measured by automatic oscillometry (Omron, Australia) from the non-dominant arm after 5 minutes rest with the mean of two measurements recorded.
Social support, diabetes stress, and quality of life: Measures of behaviour will be collected at baseline, 3, 6 and 12 month follow-up. The Food Frequency Questionnaire (Diet Questionnaire for Epidemiological Studies, DQES)[24], social support (Multidimentional Scale of Perceived Social Support, MSPSS)[25],depression and suicidal ideation (Patient Health Questionnaire 9, PHQ9) [25], and quality of life (WHOQoL questionnaire) [26]
The required sample size to estimate the primary outcome at 12 months follow-up is 180 participants. A total number of 90 T2D participants per study arm was determined as required to detect an effect size of 0.23 assuming a within group standard deviation of 0.5 at 80% power and two-sided 95% significance level assuming an attrition rate of 15%.
Statistical Analysis
The principle of intention-to-treat was followed in the full analysis set. Trial participants will be compared according to the group which they were allocated in the main analysis. We will not impute any missing data. The per-protocol analysis will comprise participants who complied with all the sessions.
Demographic characteristics: The baseline characteristics will be reported following the Consolidated Standards of Reporting Trials (CONSORT) guideline [27]. Means and SD or median and interquartile range will be reported as appropriate for continuous data, while categorical data will be reported as counts and percentages.
Primary glycaemia outcomes: Primary glycaemia outcome is average HbA1c (%) in each of the two randomised groups at 3-, 6- and 12-month follow-up. Mixed-effects regression analysis will be used to
assess difference between the two groups at the recorded timepoints. We will report the mean difference and two-sided 95% confidence interval (CI). However, if normality assumption is not satisfied, quantile regression will be utilised and median difference between the two groups and two-sided 95% CI will be reported.
Secondary outcomes: For secondary outcomes that are measured in interval scales, we will use the same approach specified for analysing the primary outcome. Secondary outcomes that are binary or categorical, we will use binomial, multinomial or ordinal logistic regression as appropriate to compare the two groups. Estimates of risk ratios or odds ratio as appropriate will be reported and their two-sided 95% CI.