Level of physical activity and eating behavior: Risk factors associated with sedentariness among employees of a company in the city of Kinshasa province

Yıl 2018, , 82 - 90, 20.09.2018

Godefroid Kusuayi , Ekisawa Constant Kiama

https://doi.org/10.31459/turkjkin.439760

Cited By: 1

Öz

The objective is to determine the level of physical activity, eating behavior and risk factors associated with sedentariness among employees of the Multimodal Freight Management Office of Kinshasa (OGEFREM, acronym). Cross-sectional study of the 210 employees, of which 119 (56.7%) men and 91 (43.3%) women, aged 18 to 59 years were randomly selected. The level of physical activity was measured by the International Physical Activity Questionnaire (IPAQ) and the eating behavior by Three-Factor Eating Questionnaire (TFEQ-R 18). The Student's T test and Chi-square test were used to compare the variables according to level of physical activity and socio-professional status. Logistic regression was used to identify independent determinants of physical inactivity and sedentary behavior. Of the 210 questionnaires collected, 56.7% of men and 43.3% of women show that 59.5% of the study population has a low level of physical activity and 58.5% a cognitive restriction. The average values of the following parameters: Weight, BMI, Waist circumference, systolic blood pressure, diastolic blood pressure, mean arterial pressure, pulsed pressure, blood glucose, total cholesterol, triglyceride, total body fat , visceral fat and lean mass are respectively 85 ± 9.7 kg, 32.6 ± 2.9 kg/m², 99 ± 13.0 cm, 135.6 ± 17.0 mmHg, 92.1 ± 14.5 mmHg, 106.6 ± 14.3 mmHg, 43.5 ± 12.0 mmHg, 129 ± 23.9 mg / dl, 228 ± 18.7 mg / dl, 169 ± 19.5 mg / dl, 39.7 ± 10.8%, 8 ± 8.9% and 28.9 ± 9.4%. The probability of having a low level of physical activity and sedentary behavior was 5 times higher among employees spending more than three hours of time sitting on the computer (OR aj = 5.188 95% CI (1.389-7.318), p = 0.006), 3 times higher among employees over three hours of time sitting in front of the television (OR aj = 3.042 95% CI (1.155-8.012), p = 0.02), 3 times higher among employees who spent more than three hours of reading time (OR aj = 3.456 95% CI (1.294-5.677), p = 0.006 and with cognitive dietary restriction (OR aj = 3.188 95% CI (1.389-7.318) , p = 0.006), cognitive dietary restriction (OR = 3.188 95% CI (1.389-7.318), p = 0.006) and also 3 times higher among employees with high socio-occupational status (OR aj = 3.57 95% CI (1.77-6.68), p <0.015). The employees of the Multimodal Freight Management Office of Kinshasa have a low level of physical activity and a cognitive food restriction. Time spent more than three hours of time on the computer increases the risk of becoming inactive and sedentary 5 times. On the other hand, the time spent more than three hours watching television and cognitive restriction as well as the high socio-professional status increases it three times and is positively associated with morphological, physiological, lipid profiles and body composition. In contrast, they are associated with a decrease in muscle mass and high density lipoprotein.

Anahtar Kelimeler

Cognitive restriction, food behavior, physical activities, uncontrolled diet

Kaynakça

• Abrams DB, Boutwell WB, Grizzle J, Heimendinger J, Sorensen G, Varnes J. Cancer control at the workplace: the Working Well trial. Preventive Medicine, 1994, 23(1): 15-27.
• Barnett TA, Gauvin L, Craig CL, Katzmarzyk PT. Distinct trajectories of leisure time physical activity and predictors of trajectory class membership: A 22 year cohort study. Int J Behav Nutr Phys Act, 2008, 5: 57.
• Baromètre santé 2000. Cfes 2000.
• Baromètre santé nutrition, Activité physique et sédentarité en Languedoc-Roussillon, Observatoire Régional de Santé Languedoc-Roussillon, 2010.
• Bauman A, Bull F, Chey T, Craig CL, Ainsworth BE, Sallis JF, Bowles HR, Hagstromer M, Sjostrom M, Pratt M, the IPS Group. The International Prevalence Study on Physical Activity: results from 20 countries. International Journal of Behavioral Nutrition and Physical Activity, 2009; 6:21.
• Beliveau L, Leger L. L’évaluation de la condition physique où, quand, comment, pourquoi? Le Médecin du Québec, 2004; 39(4): 11.
• Bellocq A, Cabillic M. L’actimètre en pratique. Société de Pneumologie de Langue Française, 2009, p. 9.
• Bergman P, Grjibovski AM, Hagstromer M, Bauman A, Sjostrom M. Adherence to physical activity recommendations and the influence of socio-demographic correlates - a population-based cross-sectional study. BMC Public Health, 2008; 8: 367.
• Beunza JJ, Martinez-Gonzalez MA, Ebrahim S, Bes-Rastrollo M, Nunez J, Martinez JA, Alonso A. Sedentary behaviors and the risk of incident hypertension: the SUN Cohort. Am J Hypertens, 2007; 20: 1156-1162.
• Brownell KD. Matching individuals to treatments. In: Brownell KD, Fairburn CG, (eds). Eating discorders and obesity. New- York, London: The Guilford Press, 1995: pp. 552-557.
• Browning LM, Hsieh SD, Ashwell M. A systematic review of waist-to-height ratio as a screening tool for the prediction of cardiovascular disease and diabetes: 0.5 could be a suitable global boundary value. Nutr Res Rev, 2010; 23: 247-269.
• Burton NW, Turrell G. Occupation, hours worked, and leisure-time physical activity. Preventive Medicine, 2000; 31(6): 673-681.
• Coste M. Prévalence du syndrome métabolique chez les patients de 30-64 ans durant un mois de consultation. Thèse de Médecine. Université de Lyon, France, 2006: pp. 19.
• Doucet E. L’activité Physique et la maitrise du poids, Revue Formation continue. le Médecin du Québec, 2004; 39(2).
• Ekelund U, Brage S, Griffin SJ, Wareham NJ. Objectively measured moderate- and vigorous-intensity physical activity but not sedentary time predicts insulin resistance in high-risk individuals. Diabetes Care, 2009; 32: 1081-1086.
• Fung TT, Hu FB, Yu J, Chu NF, Spiegelman D, Tofler GH, Willett WC, Rimm EB. Leisure-time physical activity, television watching, and plasma biomarkers of obesity and cardiovascular disease risk. Am J Epidemiol 2000; 152: 1171-1178.
• Gamila S, Dallongeville J. Epidémiologie du syndrome métabolique en France. Med Nutr, 2003; 39: 89-94.
• Gao X, Nelson ME, Tucker KL. Television viewing is associated with prevalence of metabolic syndrome in Hispanic elders. Diabetes Care, 2007; 30: 694-700.
• Gardiner PA, Healy GN, Eakin EG, Clark BK, Dunstan DW, Shaw JE, Zimmet PZ, Owen N. Associations between television viewing time and overall sitting time with the metabolic syndrome in older men and women: the Australian Diabetes, Obesity and Lifestyle study. J Am Geriatr Soc, 2011; 59: 788-796.
• Gennuso KP, Gangnon RE, Matthews CE, Thraen-Borowski KM, Colbert LH. Sedentary behavior, physical activity, and markers of health in older adults. Med Sci Sports Exerc, 2013; 45: 1493-1500.
• Ginsberg HN, Stalenhoef AF. The metabolism syndrome: targeting dyslipidaemia to reduce coronary risk. J Cardiovasc Risk, 2003; 10: 121-128.
• Godefroid KM, Constant NE, Christophe D, Francois LB, Alosha NN. Effect of a structured physical exercises program on cardiovascular risk factors related to the metabolic syndrome in obese workers of Kinshasa in Democratic Republic of Congo. Sports and Science, 2018; 33(3): 115-122.
• Gomez-Cabello A, Pedrero-Chamizo R, Olivares PR, Hernandez-Perera R, Rodriguez-Marroyo JA, Mata E, Aznar S, Villa JG, Espino-Toron L, Gusi N, Gonzalez-Gross M, Casajus JA, Ara I, Vicente-Rodriguez G. Sitting time increases the overweight and obesity risk independently of walking time in elderly people from Spain. Maturitas, 2012; 73: 337-343.
• Helmerhorst HJ, Wijndaele K, Brage S, Wareham NJ, Ekelund U. Objectively measured sedentary time may predict insulin resistance independent of moderate- and vigorous intensity physical activity. Diabetes, 2009; 58: 1776-1779.
• IPAQ Research Committee. Guidelines for data processing and analysis of the international physical activity (21st December 2005), 2005.
• Kantomaa MT, Tammelin TH, Nayha S, Taanila AM. Adolescents’physical activity in relation to family income and parents’education. Preventive Medicine, 2007; 44(5): 410-415.
• Kohl HW, Craig CL, Lambert EV, Inoue S, Alkandari JR, Leetongin G, Kahlmeier S. The pandemic of physical inactivity: global action for public health. Lancet, 2012; 380: 294-305.
• Kusuayi MG, Constant NE, Christophe D, Teddy BL, Nicias KN, Francois LB. Effects of a physical exercise program on the level of physical activity and energy expenditure of obese workers in Kinshasa in the Democratic Republic of Congo. International Journal of Kinesiology & Sports Science, 2018; 6(2): 1-6.
• Lafay L, Bénetier C, Berin M. Étude individuelle nationale des consommations alimentaires: 2006-2007 (INCA- 2), 2009, p. 227.
• Muller L. La pratique sportive des jeunes dépend avant tout de leur milieu socioculturel. Insee Première, 2003, n: 932.
• OMS. Recommandations mondiales sur l'activité physique pour la santé. OMS, 2010, p. 57.
• Ozen KB, Sarac F, Sarac S, Uluer H, Yilmaz C. Metabolic Syndrome insulin resistance, fibrinogen, hemocysteine, leptin, and C-reative protein in obese patients with obstructive sleep apnea syndrome; Ann Thorac Med, 2011; 6(3): 120-125.
• Prévention des Maladies Chroniques: Un investissement vital. Genève, Organisation mondiale de la Santé, 2005.
• Rossner S. Factors determining long-term outcome of obesity treatment. In: Björntorp P, Brodoff BN eds. Obesity. Philadelphia: Lippincott, 1992: 712-719.
• Salanave B, Verdot C, Deschamps V, Vernay M, Hercberg S, Castetbon K. La pratique de jeux en plein air chez les enfants de 3 à 10 ans dans l’Étude nationale nutrition santé (ENNS, 2006-2007). Bull Epidémiol Hebd, 2015; (30-31): 561-570.
• Sjöström M, Oja P, Hagsträmer M, Smith B, Bauman A. Health-enhancing physical activity across European Union countries: The Euro barometer study. J Publ Health, 2006; 14: 291-300.
• Stamatakis E, Davis M, Stathi A, Hamer M. Associations between multiple indicators of objectively-measured and self-reported sedentary behaviour and cardiometabolic risk in older adults. Prev Med, 2012; 54: 82-87.
• USEN. Unité de surveillance et d’épidémiologie nutritionnelle. Étude nationale nutrition santé (ENNS, 2006) – Situation nutritionnelle en France en 2006 selon les indicateurs d’objectif et les repères du Programme national nutrition santé (PNNS). Institut de veille sanitaire, Université de Paris 13, Conservatoire national des arts et métiers, 2007, p. 74.