Sedentary Behavior and Cardiometabolic Risk Factors in Middle-aged Adults Living in A Brazilian Eastern Amazon City: A Cross Sectional Study

This study investigated the association of self-reported daily time in sedentary behavior with cardiometabolic risk factors in middle-aged adults living in a Brazilian eastern Amazon city. Middle-aged public civil servant living in Palma’s city participated in this cross-sectional study. Daily sedentary behavior and physical activity were measured, and anthropometric parameters and blood biochemical biomarkers were obtained. The results showed that total daily time in sedentary behavior measured using International Physical Activity Questionnaire associated positively with waist to height ratio [β = 0.008 (95% CI = 0.001; 0.016), p = 0.023] and body adiposity index [ β = 0.570 (95% CI = 0.110; 1.020), p = 0.016] ; and the time spent in p assive transport measured using Longitudinal Aging Study Amsterdam - Sedentary Behavior Questionnaire was positively associated with neck [ β = 4.420 (95% CI = 1.360; 7.480), p = 0.005 ) and waist circumference [ β = 7.990 (95% CI = 3.490; 12.500), p = 0.005] , waist to hip ratio [ β = 0.060 (95% CI = 0.030; 0.100), p = 0.001 ), conicity index [0.050 (95% CI = 0.010; 0.080), p = 0.002] , and the concentrations of triglycerides [ β = 38.500 (95% CI = 6.640; 70.390), p = 0.019] and insulin [ β = 2.490 (95% CI = 1.030; 3.950), p = 0.001] . In conclusion, self-reported sedentary behavior is associated with anthropometric and biochemical risk factors for cardiometabolic diseases in the studied individuals.


I. INTRODUCTION
Sedentary behavior (SB) is expressed as daily sitting time and may be characterized as time spent in other low-energy spending activities in different domains of daily life [1].Sedentary behavior is associated with chronic diseases and all-cause mortality in adults, regardless the practice of moderate to vigorous physical activity [2], in different regions of the world [3], including South America.In such region, SB reaches almost 6 h/day [4] and is positively associated with the occurrence of cardiometabolic diseases in adults [5].
Specifically in Brazil, most studies on the association of SB with cardiometabolic diseases and their risk factors in middle-aged individuals focus on populations from south and southeast regions, although the presence of such diseases is relatively elevated in some cities of the north region.For example, the prevalence of obesity varies from 15.4% in Palmas-TO (i.e., Eastern Amazon) to 23.3% in Rio Branco-AC (i.e., Western Amazon), and of hypertension varies from 18.4% in Manaus -AM (i.e., Western Amazon) to 23.3% in Macapá -AP (i.e., Eastern Amazon) [6].Thus, the analysis of SB and cardiometabolic risk factors in middle-aged individuals living in the Amazon region is necessary because harmful cardiometabolic outcomes and trends in mortality rate from cardiovascular diseases are prominent in this population [7], [8].Moreover, the middle-aged together with the older-adult population exhibit the highest prevalence of chronic diseases in Brazil [9].Therefore, the aim of this study was to investigate the association of self-reported daily time in SB with cardiometabolic risk factors in middle-aged adults living in a Brazilian eastern Amazon city.

A. Study Participants
Middle-aged civil servants working in public service institutions and residing in the city of Palmas (Eastern Amazon), Brazil, were invited via e-mail or scheduled faceto-face meetings in their working sector to participate in this cross-sectional study.Prior to recruitment the present study was approved by the institutional Ethics Committee (Protocol: 2 538 024/2019) and all participants provided written informed consent.Two-hundred and thirty-eight individuals aged 40-59 years selected through convenience sampling went through a semi-structured interview between March and December 2019.Sixty-four of them (34 men; 30 women; 43.67 ± 3.87 years) were included in this study, while 174 were excluded.Individuals were excluded if they selfdeclared changes in the level of habitual physical activity, in eating habits or in total body mass > 3 kg three months prior the study were excluded.Moreover, professional athletes or individuals undergoing intense exercise ≥ 24 h/week and those using pacemaker and/or prosthesis or having thyroid, cerebrovascular, infectious and/or inflammatory, gastrointestinal, hepatic, or renal diseases, and the postmenopausal women were excluded.

B. Sociometric and Health-related Characteristics
The sociodemographic and health-related parameters were self-reported by the participants who completed a specific questionnaire [10].Information about ethnicity, smoking habits, alcohol consumption, level of education, use of medication and family history of diseases among others were obtained.

C. Sedentary
Behavior and Physical Activity Measurements The selected individuals self-reported the total daily time in SB (sitting or lying down) in the previous week by completing the full version of the Longitudinal Aging Study Amsterdam -Sedentary Behavior Questionnaire [LASA-SBQ].The total screen time and times reading, listening to the radio, performing prayers, domestic, administrative, religious, cultural activities and in passive transport were added and the usual nighttime sleep was discounted.The weighted mean of the total daily time in SB was calculated, according to the following mathematical procedure: [(average on weekdays × 5) + (average on weekend days × 2) / 7].
The level of habitual physical activity of the participants was obtained by completing the full version of the International Physical Activity Questionnaire (IPAQ).For the ensuing analyses, insufficiently active individuals were grouped into inactive; and those active into very active.
To directly assess the level of habitual physical activity, individuals were instructed to use a digital pedometer (Digiwalker SW-200, Yamax Corporation, Tokyo, Japan) as appropriate during the entire day of wakefulness in a typical week [eight consecutive days] [11].The daily average of steps was obtained from the number of steps in the last 7 days; and 10.000 steps/day was the cutoff point to classify participants as physically active [12].For subsequent analyses, individuals having low physical activity were grouped into inactive; and those moderately active into active and very active.

D. Blood Pressure and Anthropometry Measurements
Upon scheduling, blood pressure and anthropometric data were obtained.Participants were instructed avoid moderateto vigorous-intensity physical activity, caffeine, and alcohol 48 h before.Systemic blood pressure was measured using an automatic inflation blood pressure monitor (BP3AA1-1, G-Tech, OnboElectronicCo, Schenzen, China), registered at ANVISA (No. 80275310004), according to the VII Brazilian Guidelines on Hypertension [13].Next, height and total body mass were determined using a stadiometer and a portable scale (2096PP, Toledo, São Bernardo do Campo, SP, Brazil).Circumferences were measured using a flexible, non-elastic anthropometric tape (TR4010, Sanny, São Bernardo do Campo, SP, Brazil).Neck circumference was measured in the midway of the neck, in men it was measured just below the laryngeal prominence.Waist circumference was measured at the umbilical line.Hip circumference recorded as the maximum circumference over the buttocks.The indexes of body mass (BMI; Quetelet equation), conicity [14] and body adiposity [15], as well as the waist circumference-to-height [26] and waist-to-hip circumference [17] ratios were calculated.

E. Biochemical Analyses
Upon scheduling, after 12 h fasting, the participants had venous blood samples collected from the antecubital vein, then serum was separated by centrifugation at 2.225 g for 15 min at room temperature (Sigma 2-3, Sigma Laborzentrifuzen, OsterodeamHarz, Germany).Blood glucose was measured by the glucose oxidase method (Cobas Mira Plus, Roche Diagnostics, GmbH, Montclair, NJ, USA), and insulin was measured by electrochemiluminescence (Modular Analytics, E170, Roche Diagnostics, GmbH, Mannheim, Germany).Serum total cholesterol (TC), highdensity lipoprotein cholesterol (HDL-c), and triglycerides (TG) levels were determined by an enzymatic colorimetric method (Cobas Mira Plus, Roche Diagnostics, GmbH, Montclair, NJ, USA).The plasma concentrations of apolipoproteins A-1 (apo A-1) and B (apo B) were determined using commercially available enzyme-linked immunosorbent assay (ELISA) kits (Mercodia, Uppsala, Sweden).Plasma homocysteine was determined using chemiluminescence immunoassay (Atellica IM 1600 (Siemens Health-ineers, Erlangen, Germany), whereas free fatty acids were determined by the kinetic spectrophotometry method using the kit EnzyChrom Free Fatty Acid Assay (Bioassay Systems, Hayward, CA, USA).
The homeostasis model assessment (HOMA-IR) was used to estimate IR by using the equation proposed by [23].The cutoff value used for the IR diagnosis was 2.7 as suggested by [24].The atherogenic index was calculated as the TC to HDL-c ratio [25], TG to HDL-c ratio [26], and apolipoprotein B to A-1 ratio [27].

F. Statistical Analyses
Qualitative variables were described as absolute and relative frequencies.The Shapiro-Wilk test was used to assess the distribution of quantitative variables.To evaluate the differences in time in SB according to the variables studied, the Mann-Whitney test was applied due to the lack of adherence to the observed normal distribution.The necessity to include confounding factors in the analyzes of association between time spent in SB and dependent variables was considered, for which the Mann-Whitney (qualitative variable analysis) and Spearman correlation (qualitative variable analysis) tests were used.None of the confounding variables had statistical criteria (p < 0.2) for their inclusion in the models, thus demonstrating their lack of influence on the results presented.The association between total daily time in SB measured by LASA-SBQ and IPAQ and quantitative variables was analyzed using Spearman's correlation test.To evaluate the association between total daily time in SB measured by the IPAQ and the characteristics studied, the interquartile regression was used.The analysis of the relationship between the studied characteristics and the total daily time in SB, total screen time and total time in passive transport measured by the LASA-SBQ was performed using linear regression or interquartile regression according to the distribution of data observed for each outcome variable.All analyses were performed using the Stata® software (StataCorp, LC), and the significance level adopted was P < 0.05.

A. Descriptive Characteristics
Table I presents the sociodemographic and health-related characteristics of the studied individuals.Most of them had higher education level, were not-current smoker, nonalcoholic, and presented family history of hypertension, diabetes, myocardial infarction, and cancer.
Most of the participants were categorized as active (IPAQ and Pedometer).Nevertheless, the total daily times spent in SB measured using either IPAQ or LASA-SBQ were high.Likewise, both screen time and passive transport time measured using LASA-SBQ were high (Table II).
The average anthropometric, hemodynamic, and biochemical parameters were within normal limits (Table III), except the waist to height ratio, BMI, and the serum concentrations of TC and LDL-c.

B. Associations of Interest
There were statistically significant positive associations between the total daily time in SB determined by the IPAQ and the waist to height ratio and with the body adiposity index (Table V).
Regarding the daily times on screen and in passive transport, self-reported in the LASA-SBQ, and cardiometabolic risk factors (Table VI), there were statistically significant positive associations between total time in passive transport and the neck and waist circumferences, the waist to hip ratio, the conicity index, the serum concentration of triglycerides and fasting plasma insulin concentration.

IV. DISCUSSION
The main findings of this study were: 1) the total daily time in SB is positively associated with the waist to body height ratio and the body adiposity index; and 2) the daily time spent in passive transport is positively associated with neck and waist circumferences, waist to hip ratio, conicity index, and serum triglyceride and plasma insulin concentrations.Such associations were independent of confounding variables, such as sociodemographic characteristics and the level of habitual physical activity.
The daily time in SB favors the accumulation of adipose tissue because of the reduction in the requirement for skeletal muscle contractions and hence energy expenditure [35].Consequently, a decrease in the action of the lipoprotein lipase (LPL) reduces HDL-c synthesis and the uptake of TG and free fatty acids, thus increasing the concentration of postprandial lipids [36] and lessening the body's ability to use fat as an energy substrate, which ends up being deposited mainly in the visceral abdominal area [37].It is noteworthy that overweight and obesity were present in 60.93% of participants and waist circumference, waist to body height ratio and body adiposity index had prevalence over 42 % among these individuals.
The associations of daily time in passive transport with serum triglyceride and plasmatic insulin concentrations observed in the present study might be explained, in part, by the association of diminished activity of the LPL enzyme with those of glucose transporting proteins, also in skeletal muscles.The reduction in the activity of these proteins inhibits the uptake of glucose into the myocyte, consequently increasing its plasma glucose [38], which may contribute to the occurrence of deleterious effects associated with the diminishment of LPL and resistance to insulin action [37].
We could be speculated that the lack of association between daily time in SB and some of the analyzed biomarkers was influenced by the level of physical activity of the individuals studied, as most of them was classified as active, regardless the mode of assessment.It is known that the regular practice of 150 min/week of moderate-to vigorousintensity physical activity or walking 10.000 steps daily can promote health benefits [39].Nevertheless, the level of physical activity did not influence the association analyzes performed here.
This study has limitations.First, it is a cross-sectional and thus the results presented must be considered with caution, as we cannot guarantee the observed associations have a causeeffect relationship, although we used validated tools and performed simple linear and interquartile regression controlled by confounding variables.Second, the participants were selected by convenience.Although non-probability methods of sampling have been used in health-related studies [40], the findings achieved here cannot be generalized to the local population of middle-aged civil servants living in Palmas city.Thus, studies using different methodological strategies specially to investigate cause-effect relationships between SB and cardiometabolic diseases in this population are warranted.

V. CONCLUSION
In conclusion, self-reported total daily time in SB, spent either in passive transport or in screen, is associated with cardiometabolic risk factors, assessed by anthropometric indicators and biochemical biomarkers in the studied individuals.These finding have some relevant implications for local public health since it gives a clue to the local public administration to manage and/or prevent the harmful consequences of a sedentary lifestyle, especially because

TABLE I :
SOCIOMETRIC AND HEALTH-RELATED CHARACTERISTICS AMONG

TABLE IV :
PREVALENCE OF CARDIOMETABOLIC RISK FACTORS AMONG PARTICIPANTS

TABLE VI :
REGRESSION COEFFICIENT (Β) FOR THE RELATIONSHIP BETWEEN TOTAL DAILY SCREEN TIME AND PASSIVE TRANSPORT MEASURED BY LASA-SBQ AND CARDIOMETABOLIC RISK FACTORS Confidence interval.HDL-c, High-density lipoprotein cholesterol.HOMA -IR, insulin resistance index.LASA-SBQ, Longitudinal Aging Study Amsterdam -Sedentary Behavior Questionnaire.LDL-c, Low-density lipoprotein cholesterol.TG = Triglycerides.a Linear regression; b Interquartile regression.