Study design and population
This was a cross-sectional prospective survey conducted from February to March 2015 in a rural and urban population of the littoral region Cameroon. Urban participants were recruited in the Douala V health district and rural participants were recruited in the Njombe-Penja health district. A total of 499 participants (249 in urban area and 250 in rural area) were randomly selected from the two communities using a three-stage cluster sampling with above-mentioned health districts as first stage, neighborhoods as second stage and households as third stage. Participants from both genders aged 18 years and older were included in the study. Other participants with the following characteristics were excluded: pregnant women, participants with previous diagnosis of obstructive sleep apnea syndrome or restless leg syndrome and those who were unable to cooperate with physical examination or interview due to mental disorder or physical disability. We finally included 499 participants; 249 participants in the rural area and 250 participants in the urban area.
Data collection and parameters measurements
Data were collected using a structured questionnaire administered to participants face to face. The following informations were collected: age, status of smoking and drinking, physical activity, fruits and vegetables consumption and profile of sleep. Status of smoking and drinking was evaluated from self-reported information. Physical activity was evaluated from responses to questions about type and frequency of physical exercise at work and during leisure time and was categorized into “active” (≥150 min/week aerobic exercise such as
jogging, swimming, climbing, etc.) and “inactive”. Fruit and vegetables intake was considered insufficient if consumption of either fruit or vegetables was < 5 servings per day (19). Sleep quality was evaluated using the standard Pittsburgh Sleep Quality Index (PSQI), which is a widely used measure of sleep quality (20). This questionnaire is self-rated and evaluates sleep quality and disturbances over a 1-month period. It has 19 individual items with seven “component” scores. The scores of each item of the index vary between 0 and 3. Total score of these seven components makes one score of 0–21. Poor sleep quality was defined for a total score >5 (20). Sleep duration was evaluated from responses to relevant questions about the actual sleep duration every day in the past month and was classified into “short” (≤ 6 h), “normal” (7 h ≤ sleep duration ≤ 8h) and “long” (>8 h) based on previous reports (21–22).
Physical examination included blood pressure (BP), waist circumference (WC), weight and height. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meter (kg/m²). Overweight was defined as BMI ≥ 25 kg/m², and obesity as BMI >30 kg/m². Abdominal obesity was defined as WC ≥ 102 cm for men and ≥ 88 cm for women (23).
BP was measured after 15 minutes in the sitting position and in standardized conditions. Three consecutive BP measurements were taken at 5 minutes intervals using a validated automated sphygmomanometer (HEM–705 CP, Omron Corporation, Tokyo, Japan) with cuff’s width adjusted to arm’s circumference. A fourth measurement was obtained if the first three readings differed by ≥10 mmHg. The averages of the nearest three BP readings were considered in this study. Hypertension was defined as systolic BP ≥140 mmHg and/or diastolic BP ≥90 mmHg, and/or ongoing antihypertensive medication (23).
Participants were instructed to fast for at least 8 hours overnight and fasting blood glucose (FBG) was determined using a glucometer (Accu-Chek Aviva, Roche, Mannheim, Germany). Diabetes was defined according to American Diabetes Association (ADA) criteria (24). Diabetes mellitus was defined as FBG ≥ 126 mg/dL (≥7.0 mmol/L) and/or being on glucose-lowering medication(s),
Continuous variables were presented as mean ±1 standard deviation, and categorical data as percentages. Prevalence rates were presented with 95% confidence interval (CI). The significance of differences between proportions was assessed using Chi squared test (for categorical variables), whereas the significance of differences between continuous variables was assessed using Student’s t test. Multivariable logistic regression was used to assess the association between diabetes and sleep quality and duration. Odd ratios were adjusted for age and gender. Statistical significance was set at p<0.05. All analyses were performed using SPSS 20 software (SSPS Inc, Chicago, Illinois, USA).