This is a population-based cross-sectional study using secondary data from the UAE National Diabetes and Lifestyle (UAEDIAB) Study. The UAEDIAB Study was a cross-sectional survey designed to investigate the prevalence of diabetes and associated risk factors among Emirati citizens and expatriates. Anthropometric measurements of obesity and blood samples were also collected as part of the UAEDIAB Study.
Settings
The UAEDIAB Study recruited adults living in the UAE’s Northern Emirates (Sharjah, Ajman, Ras al-Khaimah, Fujairah and Umm al-Quwain).
Participants
Participants for the UAEDIAB Study were recruited in two phases. In the first phase, adults who lived in the UAE for at least 4 years but were not citizens were approached while applying for their second or subsequent visa renewal. In the second phase, UAE citizens 18 years of age and older were recruited through a household survey following a random selection of regions and were stratified by emirate using a cluster sampling method. In both phases, participants were excluded if they had serious physical disabilities, learning disorders, severe communication barriers or were pregnant. None of the participants was involved in the development of any stage of this study. The methods for the UAEDIAB Study are described in detail elsewhere [14].
Variables
This study included variables related to participants’ demographic and lifestyle habits (e.g., gender, age, ethnicity, smoking habits and daily physical activity) and anthropometric measurements and indices (BMI, WC, WHR and NC). Systolic and diastolic blood pressures and fasting blood sample assays were used to assess comorbidities including hypertension, diabetes and dyslipidaemia.
Bias
To standardise data collection procedures, all data collectors attended a comprehensive training workshop that included interview techniques, data collection tools, practical applications and field guidelines. Two data collectors completed each participant’s physical measurements. For waist and hip measurements, each measurement was repeated twice; if the measurements were within 1 cm of one another, the average was calculated, if the difference between the two measurements exceeded 1 cm, the two measurements were repeated. For height, weight and blood pressure each measurement was repeated three times. The average of all three measurements was considered the most accurate and was recorded. Blood pressure was measured at 10-min intervals.
Data sources and measurements
Blood samples were collected in the morning after overnight fasting, stored in tubes containing the anticoagulant sodium heparin and transported to the reference laboratory. Each participant’s diabetic status was determined using the HbA1c test and the dyslipidaemia status was determined using a lipid profile test. The cutoff values for the tests were defined according to WHO criteria and the American Heart Association guidelines [15, 16].
A trained data collector obtained anthropometric measurements based on the WHO STEPwise Approach to Surveillance (STEPS) protocol [5]. Hip, neck and waist measurements were taken using a non-stretchable plastic tape. WC was measured at the midpoint between the lower margin of the lowest palpable rib and the top of the iliac crest. Hip circumference was measured around the widest portion of the buttocks, with the tape parallel to the floor [5]. NC was measured at the midpoint of the neck’s height, with participants standing upright. Weight and height were measured using a certified SECA stadiometer and weighing scale (Sonashi Mechanical, Dubai, UAE). For all measurements, the subject had to stand still, eyes looking straight ahead with feet close together and arms at the side, and would wear little clothing and no shoes [5].
BMI was calculated by dividing a participant’s weight in kilograms by height in metres squared; it was then defined as normal (18.5–25 kg/m2) or overweight/obese (≥ 25 kg/m2) and no underweight subjects (< 18.5 kg/m2) identified in our study [3]. WC was defined as normal (< 90 cm in males and < 80 cm in females of Asian ethnicity and < 94 cm for males and < 88 cm for females of other ethnicities) or overweight/obese (≥ 90 cm in males and ≥ 80 cm in females of Asian ethnicity and ≥ 102 cm in males and ≥ 88 cm in females of other ethnicities) [5]. WHR was calculated as the waist circumference in centimetres divided by the hip circumference in centimetres; it was defined as normal (< 0.95 in males and < 0.80 in females of Asian ethnicity and < 1.0 in males and < 0.85 in females of other ethnicities) or overweight/obese (≥ 0.95 in males and ≥ 0.80 in females of Asian ethnicity and ≥ 1.0 in males and ≥ 0.85 in females of other ethnicities) [5]. NC was defined as normal (< 35 cm in males and < 32 cm in females) or overweight/obese (≥ 35.5 cm in males and ≥ 32 cm in females).
The interpretation and cutoff values for the agreement between anthropometric measurements and indices were determined based on criteria set by Douglas G. Altman as follow: equal to chance (k = 0.00); poor (0.01 < k ≤ 0.20); fair (0.21 < k ≤ 0.40); moderate (0.41 < k ≤ 0.60); good (0.61 < k ≤ 0.80); excellent (0.81 < k ≤ 0.99); and perfect (k = 1) [17].
Ethics approval and consent to participate
The Ministry of Health and Prevention Research Ethics Committee approved this study (MOHP/DXB/RE-SUBC/NO-12/2016). All methods were performed in accordance with the Declaration of Helsinki guidelines and regulations. A signed informed consent from all participants was obtained.
Statistical analysis
No sample size calculation was performed specifically for this study as the study accessed a secondary data from the UAEDIAB Study. Descriptive statistics were used to describe study participants’ characteristics and anthropometric measures by gender. The statistics reported means with standard deviations (SD) for continuous variables and counts with percentages for categorical variables. In bivariate analyses, categorical variables were analysed using a chi-squared test, while continuous variables were analysed using an independent t-test. Concordance or agreement statistical test, Cohen’s kappa (k) test, was conducted to assess the level of agreement among anthropometric measurements and indices based on dichotomous categorical classifications of weight status (normal or overweight/obese). Four binary logistic regression models were conducted using the enter method to assess the association between each anthropometric measurements or indices and diabetes, hypertension and different types of dyslipidaemia. Models were developed using diabetic status (yes/no), hypertension (yes/no) and one of the lipid profiles (yes/no) as dependent variables. Each model was adjusted for one of anthropometric measurements or indices, gender, age, ethnicity, physical activity and smoking status. The statistical significance was set at p ≤ 0.05. Statistical Package for Social Science (SPSS), version 26 (IBM Corp, New York) was used to perform the analyses.
The reporting followed the Strengthening the Reporting of Observational Studies in Epidemiology statement for cross-sectional studies.