Design and Participants
A cross-sectional study carried out with a population of shift workers from an iron ore extraction company in two locations, in the Iron Quadrangle region, Minas Gerais, and the south of the state of Pará. In all three studies, the population of shift workers with the position of operators was invited to participate: a) The first was carried out in 2012, with 391 shifts workers from four mines in the Iron Quadrangle region; b) The second study was carried out in 2015 with 192 shifts workers from another mine in the Iron Quadrangle region; c) The third study was carried out in 2018 with 932 shift workers in the southern region of Pará[12]. Therefore, in total, 1461 shift workers were analyzed. This study followed reported guidelines dictated by the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE).
Participants of cross-sectional studies carried out in 2012 and 2015 had a rotating shift schedule (4x1) of the six hours of work, followed by 12 hours of rest. After finishing the weekly four-shift cycle, they receive one day off. Participants of the cross-sectional study carried out in 2018 had a rotating shift schedule of (5x2) eight hours of work, followed by 24 hours of rest. After finishing the weekly five-shift cycle, they receive two days off.
Data collect
In all studies, data collection was performed face-to-face by teams trained to administer the questionnaires, measure anthropometric data, and collect biological samples.
The social, demographic, and economic variables evaluated were: sex, age, self-reported skin color, scholarly, and shift working time. Age was categorized as 20-29 years, 30-39 years, 40-49 years, 50-59 years, and 60 years or more; the self-declared skin color was categorized as not white (black, brown-skinned yellow or indigenous) and white; scholarly was categorized into up to 1st degree complete, 2nd degree complete, technician, graduated and postgraduate; shift working time in less five and greater than five years.
The clinical evaluation was carried out employing a questionnaire about pre-existing diseases, use of medication, smoking, alcohol consumption, physicial activity; and measuring blood pressure. Smoking was classified as non-smokers, those who had never smoked or had quit smoking more than six months ago, and smokers, those who currently smoke or had quit smoking less than six months ago. Alcohol consumption was assessed using the Alcohol Use Disorders Identification Test (AUDIT) [13]. For analysis purposes, participants with no risk and low risk were grouped into the same category. The instrument used to assess the level of physical activity was the International Physical Activity Questionnaire (IPAQ) version 8 - long form. The workers were classified as low physical activity < 600 measure total energy (MET) - min/week [14].
The pre-existing diseases evaluated were: cardiovascular diseases, respiratory diseases, and chronic kidney disease. Blood pressure was measured in triplicate with a digital semi-automatic device. The measurement protocol followed the recommendations of the Brazilian Society of Cardiology and was classified as hypertension values of systolic blood pressure (SBP) >140mmHg or diastolic blood pressure (DBP) >90 mmHg [15].
Biochemical data
The evaluation of the biochemical profile was performed by analysis of the lipid profile, vitamin D, and glycemia. In the first two studies (2012 and 2015), blood samples were collected after a 10-hour fast and in 2018 it was collected without a previous fast.
Total cholesterol (TC), high-density lipoprotein-cholesterol (HDL), and triglycerides (TG), which were determined by the enzymatic-colorimetric method. Low-density lipoprotein-cholesterol (LDL) was calculated using Friedewald's Equation (1972). The TC was classified as normal < 190 mg/dL, HDL > 40 mg/dL, LDL < 130 mg/dL, and TG < 150 mg/dL with fasting and < 175 mg/dL without fasting [16]. Dyslipidemia classified when at least one of the parameters was altered, or use of lipid-lowering drugs. Blood glucose was determined by fasting plasma glucose (FPG) in first two studies, and glycated hemoglobin (HbA1c) in third study. Was classified as normoglycemia (FPG < 100 mg/dL or HbA1c < 5.7%) and hyperglycemia (FPG > 100 mg/dL or HbA1c > 5.7%) [17]. Vitamin D was determined by the chemiluminescence method and classified as deficiency 25(OH)D < 20 ng/mL to a healthy population and 25(OH)D < 30 ng/mL for groups at risk for VDD (body mass index ≥ 30 kg/m2, age ≥ 60 years, and presence of chronic kidney diseases) [18]. The seasonality of blood sample collection was classified as either autumn (March 20 to June 20), winter (June 21 to September 23), spring (September 21 to December 20), or summer (December 21 to March 19).
Anthropometric data
The assessment of body fat was performed by body mass index (BMI), waist circumference (WC), and neck circumference (NC). Height was measured using a stadiometer with a scale in centimeters and an accuracy of one millimeter. Weight was measured on a portable body composition monitor. BMI was calculated and classified according to the World Health Organization (WHO) as eutrophic (BMI 18.5-24.9 kg/m2), overweight (BMI 25.0-29.9 kg/m2) and obesity (BMI > 30.0 kg/m2) [19]. WC was measured, in triplicate, with a simple and inelastic measuring tape at the midpoint between the iliac crest and the last costal arch, and classified as central obesity values ≥ 102 cm in men and ≥ 88 cm in women [20]. NC was measured at the level of the cartilage, just above the laryngeal prominence, and classified as increased values > 40 cm [9].
NoSAS score
The NoSAS score was calculated according to Marti Soler et al. (2016): NC > 40 cm, 4 points; BMI 25–29 kg/m2 and BMI ≥ 30 kg/m2, 3 and 5 points, respectively; the presence of snoring, 2 points; age > 55 years, 4 points; and male sex, 2 points. Workers were considered to be at high risk for OSA when the NoSAS score was ≥ 8 points (0–17 points) [9].
Berlin questionnaire
The BQ was used in the adapted and validated Portuguese version [10]. The BQ has three categories: snoring (category 1), excessive daytime sleepiness (category 2), and comorbidities (category 3). Workers were considered to be at high risk for OSA when two of the three categories in the BQ were positive[10].
Statistical analysis
Statistical analyses were performed using Stata (version 15.0), with a significance level of 5%. The data were compared using the chi-square analyses with Bonferroni correction. For Chi-squared analyses, Cramer's V was used as an effect size, with 0.10, 0.30, and 0.50 as the thresholds for small, medium, and large effect sizes, respectively.
A binary logistic regression analysis was performed to investigate whether VDD was associated with OSA risk assessment by BQ and NoSAS score. Independent variables that had an association at a p-value of 0.2 were used in multivariate logistic regression with a stepwise backward elimination. Collinearity among the covariates was evaluated. Hosmer-Lemeshow test and Akaike Information Criterion (AIC) was used to assess the goodness-of-fit of the models.
Sampling power (a posteriori) was performed on proportion and sample size data of similar studies using the G*Power program (version 3.1.9.2). The analysis was performed with an alpha level of 0.05 (using a two-tailed test), with an estimated power of 0.98.
Ethical issues
This study was conducted following the guidelines by the Declaration of Helsinki, and all procedures involving human participants were approved by the Research Ethics Committee of the Federal University of Ouro Preto (2012: CAAE: 0018.0.238.00-11; 2015 CAAE: 39682014.7.0000.5150; 2018: CAAE: 93760618.5.0000.5150). Written informed consent was obtained from all participants.