Study area, design, period and participants
The study was conducted from February to April, 2018 by using cross-sectional study design in Mekelle public hospitals, Tigray, Ethiopia. All type 2 DM patients who were available at the time of data collection period were included and patients who had severe illness or physical disability, pregnant mothers and patients with edema were excluded from this study.
Sample size determination and sampling technique
A single population proportion formula was used. The estimated proportion of overweight among type 2 DM patients was 31.5% . Accordingly, the required sample size (n) was estimated with a confidence level of 95%, 5% margin of error and by adding 10% non-response rate the final sample size was 365.
Systematic random sampling method was used to select the study participants from a total of 2442 type 2 DM patients who were on treatment follow up in Mekelle public hospitals. To select the required sample size the total sample size was proportionally allocated to the three public hospitals. Accordingly, the list of the patients was taken from the follow up unit of the three public hospitals and sampling frame was developed. Then the first study subject was randomly selected from the sampling frame by using lottery method and based on the sampling interval (k = 6) every six interval was selected from the sampling frame. Finally, 365 of patients with type 2 DM were included in our study.
Data collection tools and procedures
The tools for data collection include a portable Stadiometer, stretch-resistant tape meter and structured questionnaire. The questionnaire was composed of questions on socio-demographic data, behavioral and health-related factors, dietary factors and anthropometric measurement (weight, height and waist circumference).
The data was collected using a structured questionnaire through face to face interview and physical measurements of weight, height, waist circumferences using standardized techniques and calibrated equipment. Weight and height were measured with participants standing without shoes and wearing light clothing. Participants were standing upright with the head, shoulder, buttock, lower limb and heal of the foot touches the height board for height measurement. Waist circumference was measured midway between the lower rib margin and the iliac crest in the horizontal plane using a tape meter by following the standard procedure.
Data quality control
The questionnaire was initially prepared in English and translated to Tigrigna language then back to the English language. One day training was given on the objective of the study, instrument and data collection procedures by the principal investigator for the data collectors and supervisors. The weight measurement scale was checked if it is at zero before each measurement. Five percent of the questionnaire was tested before the actual data collection period outside of the study area. Data collectors were instructed to check the completeness of the instrument just after its completion. The principal investigator checked out the questionnaire for completeness each night. Moreover, the collected data were coded, cleaned and explored before analysis to check missing items and completeness of the collected data.
Overweight BMI greater than or equals to 25 kg/m2.
Central obesity waist circumference greater than 88 cm for females and greater than 102 cm for males was considered as having abdominal obesity.
Low level of physical exercise individual activity less than 150 min per week was considered as low level of physical activities.
Adequate level of physical exercise individual activity above 150 min per week was considered as adequate level of physical activities.
Dietary intake level of dietary intake was determined based on dietary factors questionnaire. Six items were asked and based on the mean value of those questions individuals who score below the mean value were classified as poor and those who score above the mean value were classified as good dietary practices.
Data processing and analysis
The collected data were entered and cleaned using Epi-data manager. Two items of dietary questions were reversely coded to explain total score to be interpreted as higher scores meaning better outcomes. Then it was exported to SPSS version 21 for statistical analysis. Descriptive statistics were computed using the frequency table and numerical summary measures. Binary logistic regression was done to determine the magnitude, direction and strength of association between a set of independent variables and the outcome variable at p < 0.25 significance level. Then those variables that were significant at p < 0.25 with the outcome variable were selected for multivariable analysis. Odds ratio with 95% confidence level was computed and significant association was declared at p-value < 0.05. Finally, the result was presented using text and tables.