Dietary Fiber Intake and Metabolic Syndrome Risk Factors among Young South African Adults
Abstract
:1. Introduction
2. Materials and Methods
2.1. Geographical Area
2.2. Sample and Research Design
2.3. Data Collection
2.3.1. Dietary Intake
2.3.2. Anthropometric and Blood Pressure Measurements
2.3.3. Biochemical Parameters
2.4. Statistical Analysis
3. Results
4. Discussion
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
- Mchiza, Z.J.; Steyn, N.P.; Hill, J.; Kruger, A.; Schönfeldt, H.; Nel, J.; Wentzel-Viljoen, E. A review of dietary surveys in the adult South African population from 2000 to 2015. Nutrients 2015, 7, 8227–8250. [Google Scholar] [CrossRef] [PubMed]
- Jaffer, N.; Steyn, N.P.; Peer, N. Dietary Data from the Cardiovascular Risk in Black South Africans (CRIBSA) Study Conducted in 2009. Unpublished work. 2009. [Google Scholar]
- Nel, J.H.; Steyn, N.P. Report on South African Food Consumption Studies Undertaken Amongst Different Population Groups (1983–2000): Average Intakes of Foods Most Commonly Consumed; Department of Health: Pretoria, South Africa, 2002. [Google Scholar]
- Wentzel-Viljoen, E.; Kruger, A. Prospective Urban and Rural Epidemiological (PURE) Study in the North West Province of South Africa; North-West University: Potchefstroom, South Africa, 2010. [Google Scholar]
- Hoebel, S.; Malan, L.; De Ridder, H. Differences in MetS marker prevalence between black African and Caucasian teachers from the North West Province: Sympathetic activity and ambulatory blood pressure in Africans (SABPA) Study. J. Endocrinol. Metab. Diabetes S. Afr. 2011, 16, 49–56. [Google Scholar] [CrossRef]
- Erasmus, R.T.; Soita, D.J.; Hassan, M.S.; Blanco-Blanco, E.; Vergotine, Z.; Kengne, A.P.; Matsha, T.E. High prevalence of diabetes mellitus and metabolic syndrome in a South African coloured population: Baseline data of a study in Bellville, Cape Town. SAMJ S. Afr. Med. J. 2012, 102, 841–844. [Google Scholar] [CrossRef] [PubMed]
- Peer, N.; Steyn, K.; Levitt, N. Differential obesity indices identify the metabolic syndrome in Black men and women in Cape Town: The CRIBSA study. J. Public Health 2015, 38, 175–182. [Google Scholar] [CrossRef] [PubMed]
- Kalk, W.J.; Joffe, B.I. The metabolic syndrome, insulin resistance, and its surrogates in African and white subjects with type 2 diabetes in South Africa. Metab. Syndr. Relat. Disord. 2008, 6, 247–255. [Google Scholar] [CrossRef] [PubMed]
- Van Zyl, S.; Van der Merwe, L.J.; Walsh, C.M.; Groenewald, A.J.; Van Rooyen, F.C. Risk-factor profiles for chronic diseases of lifestyle and metabolic syndrome in an urban and rural setting in South Africa. Afr. J. Prim. Health Care Fam. Med. 2012, 4, 346. [Google Scholar] [CrossRef]
- Shisana, O.; Rehle, T.; Simbayi, L.C.; Zuma, K.; Jooste, S.; Zungu, N.; Labadarios, D.; Onoya, D. South African National HIV Prevalence, Incidence and Behaviour Survey, 2012; HSRC Press: Cape Town, South Africa, 2014. [Google Scholar]
- Ford, E.S. Prevalence of the metabolic syndrome defined by the International Diabetes Federation among adults in the US. Diabetes Care 2005, 28, 2745–2749. [Google Scholar] [CrossRef] [PubMed]
- Mottillo, S.; Filion, K.B.; Genest, J.; Joseph, L.; Pilote, L.; Poirier, P.; Rinfret, S.; Schiffrin, E.L.; Eisenberg, M.J. The metabolic syndrome and cardiovascular risk: A systematic review and meta-analysis. J. Am. Coll. Cardiol. 2010, 56, 1113–1132. [Google Scholar] [CrossRef] [PubMed]
- Kruger, M.J.; Nell, T.A. The prevalence of the metabolic syndrome in a farm worker community in the Boland district, South Africa. BMC Public Health 2017, 17, 61. [Google Scholar] [CrossRef] [PubMed]
- Sekokotla, M.A.; Goswami, N.; Sewani-Rusike, C.R.; Iputo, J.E.; Nkeh-Chungag, B.N. Prevalence of metabolic syndrome in adolescents living in Mthatha, South Africa. Ther. Clin. Risk Manag. 2017, 13, 131. [Google Scholar] [CrossRef] [PubMed]
- Motala, A.A.; Esterhuizen, T.; Pirie, F.J.; Omar, M.A. The prevalence of metabolic syndrome and determination of the optimal waist circumference cut off points in a rural South African community. Diabetes Care 2011, 34, 1032–1037. [Google Scholar] [CrossRef] [PubMed]
- Wei, B.; Liu, Y.; Lin, X.; Fang, Y.; Cui, J.; Wan, J. Dietary fiber intake and risk of metabolic syndrome: A meta-analysis of observational studies. Clin. Nutr. 2017. [Google Scholar] [CrossRef] [PubMed]
- Berry, K.M.; Parker, W.A.; Mchiza, Z.J.; Sewpaul, R.; Labadarios, D.; Rosen, S.; Stokes, A. Quantifying unmet need for hypertension care in South Africa through a care cascade: Evidence from the SANHANES, 2011–2012. BMJ Glob. Health 2017, 2, e000348. [Google Scholar] [CrossRef] [PubMed]
- Stokes, A.; Berry, K.M.; Mchiza, Z.; Parker, W.A.; Labadarios, D.; Chola, L.; Hongoro, C.; Zuma, K.; Brennan, A.T.; Rockers, P.C.; et al. Prevalence and unmet need for diabetes care across the care continuum in a national sample of South African adults: Evidence from the SANHANES-1, 2011–2012. PLoS ONE 2017, 12, e0184264. [Google Scholar] [CrossRef] [PubMed]
- Abrahams, Z.; Mchiza, Z.J.; Steyn, N.P. Diet and mortality rates in Sub-Saharan Africa: Stages in the nutrition transition. BMC Public Health 2011, 11, 801. [Google Scholar] [CrossRef] [PubMed]
- Steyn, N.P.; Mchiza, Z.J. Obesity and the nutrition transition in Sub-Saharan Africa. Ann. N. Y. Acad. Sci. 2014, 1311, 88–101. [Google Scholar] [CrossRef] [PubMed]
- Puoane, T.; Tsolekile, L.; Sanders, D.; Parker, W. Chronic non-communicable diseases: Primary health care: Programme areas. S. Afr. Health Rev. 2008, 1, 73–87. [Google Scholar]
- World Health Organization (WHO); Food and Agriculture Organization (FAO). Joint Expert Consultation on diet, Nutrition and the Prevention of Chronic Diseases; WHO Technical Report Series No. 916; World Health Organization: Geneva, Switzerland, 2002. [Google Scholar]
- Mchiza, Z.; Hill, J.; Steyn, N. Foods Currently Sold by Street Food Vendors in the Western Cape, South Africa, Do Not Foster Good Health. In Fast Foods: Consumption Patterns, Role of Globalization and Health Effects; Sanford, M.G., Ed.; Nova Science Publishers: Hauppauge, NY, USA, 2014. [Google Scholar]
- Hill, J.; Mchiza, Z.J.; Fourie, J.; Puoane, T.; Steyn, N.P. Consumption patterns of street food consumers in Cape Town. J. Fam. Ecol. Consum. Sci. 2016, 1, 25–35. [Google Scholar]
- Schneider, S.W.; Nuschele, S.; Wixforth, A.; Gorzelanny, C.; Alexander-Katz, A.; Netz, R.R.; Schneider, M.F. Shear-induced unfolding triggers adhesion of von Willebrand factor fibers. Proc. Natl. Acad. Sci. USA 2007, 104, 7899–7903. [Google Scholar] [CrossRef] [PubMed]
- Jenkins, D.J.; Kendall, C.W.; Axelsen, M.; Augustin, L.S.; Vuksan, V. Viscous and nonviscous fibres, nonabsorbable and low glycaemic index carbohydrates, blood lipids and coronary heart disease. Curr. Opin. Lipidol. 2000, 11, 49–56. [Google Scholar] [CrossRef] [PubMed]
- Krauss, R.M.; Eckel, R.E.; Howard, B.; Appel, L.J.; Daniels, S.R.; Deckelbaum, R.J.; Erdman, J.W., Jr.; Kris-Etherton, P.; Goldberg, I.J.; Kotchen, T.A.; et al. Dietary Guidelines Revision 2000: A Statement for Healthcare Professionals From the Nutrition Committee of the American Heart Association. Circulation 2000, 102, 2284–2299. [Google Scholar] [PubMed]
- Food and Nutrition Board, Institute of Medicine, National Academies. Recommended Intakes for Individuals; Food and Nutrition Board, Institute of Medicine, National Academies: Washington, DC, USA, 2015; p. 425. [Google Scholar]
- Van Horn, L. Fiber, lipids, and coronary heart disease: A statement for healthcare professionals from the Nutrition Committee, American Heart Association. Circulation 1997, 95, 2701–2704. [Google Scholar] [CrossRef] [PubMed]
- Brown, L.; Rosner, B.; Willett, W.W.; Sacks, F.M. Cholesterol-lowering effects of dietary fiber: A meta-analysis. Am. J. Clin. Nutr. 1999, 69, 30–42. [Google Scholar] [CrossRef] [PubMed]
- Kendall, C.W.; Esfahani, A.; Jenkins, D.J. The link between dietary fibre and human health. Food Hydrocoll. 2010, 24, 42–48. [Google Scholar] [CrossRef]
- Chandalia, M.; Garg, A.; Lutjohann, D.; von Bergmann, K.; Grundy, S.M.; Brinkley, L.J. Beneficial effects of high dietary fiber in patients with type 2 diabetes mellitus. N. Engl. J. Med. 2000, 1392–1398. [Google Scholar] [CrossRef] [PubMed]
- Gunness, P.; Gidley, M.J. Mechanisms underlying the cholesterol-lowering properties of soluble dietary fibre polysaccharides. Food Funct. 2010, 1, 149–155. [Google Scholar] [CrossRef] [PubMed]
- Gidley, M.J. Hydrocolloids in the digestive tract and related health implications. Curr. Opin. Colloid Interface Sci. 2013, 18, 371–378. [Google Scholar] [CrossRef]
- Nettleton, J.A.; Harnack, L.J.; Scrafford, C.G.; Mink, P.J.; Barraj, L.M.; Jacobs, D.R. Dietary flavonoids and flavonoid-rich foods are not associated with risk of type 2 diabetes in postmenopausal women. J. Nutr. 2006, 136, 3039–3045. [Google Scholar] [CrossRef] [PubMed]
- Testa, R.; Bonfigli, A.R.; Genovese, S.; De Nigris, V.; Ceriello, A. The Possible Role of Flavonoids in the Prevention of Diabetic Complications. Nutrients 2016, 8, 310. [Google Scholar] [CrossRef] [PubMed]
- Peterson, J.J.; Dwyer, J.T.; Jacques, P.F.; McCullough, M.L. Do Flavonoids Reduce Cardiovascular Disease Incidence or Mortality in US and European Populations? Nutr. Rev. 2012, 70, 491–508. [Google Scholar] [CrossRef] [PubMed]
- Schneider, M.; Norman, R.; Steyn, N.; Bradshaw, D. Estimating the burden of disease attributable to low fruit and vegetable intake in South Africa in 2000. S. Afr. Med. J. 2007, 97, 717–723. [Google Scholar]
- Carnethon, M.R.; Loria, C.M.; Hill, J.O.; Sidney, S.; Savage, P.J.; Liu, K. Risk factors for the metabolic syndrome: The Coronary Artery Risk Development in Young Adults (CARDIA) study, 1985–2001. Diabetes Care 2004, 27, 2707–2715. [Google Scholar] [CrossRef] [PubMed]
- Ferreira, I.; Twisk, J.W.; van Mechelen, W.; Kemper, H.C.; Stehouwer, C.D. Development of fatness, fitness, and lifestyle from adolescence to the age of 36 years: Determinants of the metabolic syndrome in young adults: The Amsterdam growth and health longitudinal study. Arch. Intern. Med. 2005, 165, 42–48. [Google Scholar] [CrossRef] [PubMed]
- Ogbera, A.O. Prevalence and gender distribution of the metabolic syndrome. Diabetol. Metab. Syndr. 2010, 2, 1. [Google Scholar] [CrossRef] [PubMed]
- Okafor, C.I. The metabolic syndrome in Africa: Current trends. Indian J. Endocrinol. Metab. 2012, 16, 56. [Google Scholar] [CrossRef] [PubMed]
- Kylin, E. Studies of the hypertension-hyperglycemia-hyperuricemia syndrome. Zentralbl. Inn. Med. 1923, 44, 105–127. [Google Scholar]
- Vague, J. Sexual differentiation, a factor affecting the forms of obesity. Presse Med. 1947, 30, 339–340. [Google Scholar]
- Avogaro, P.; Crepaldi, G.; Enzi, G.; Tiengo, A. Associazione di iperlipemia, diabete mellito e obesita’di medio grado. Acta Diabetol. 1967, 4, 572–590. [Google Scholar] [CrossRef]
- Alberti, K.G.M.M.; Zimmet, P.; Shaw, J. Metabolic syndrome—A new world-wide definition. A consensus statement from the international diabetes federation. Diabet. Med. 2006, 23, 469–480. [Google Scholar] [CrossRef] [PubMed]
- Kelliny, C.; William, J.; Riesen, W.; Paccaud, F.; Bovet, P. Metabolic syndrome according to different definitions in a rapidly developing country of the African region. Cardiovasc. Diabetol. 2008, 7, 27. [Google Scholar] [CrossRef] [PubMed]
- Berenson, G.S.; Srinivasan, S.R.; Bao, W.; Newman, W.P.; Tracy, R.E.; Wattigney, W.A. Association between multiple cardiovascular risk factors and atherosclerosis in children and young adults. N. Engl. J. Med. 1998, 338, 1650–1656. [Google Scholar] [CrossRef] [PubMed]
- Ilanne-Parikka, P.; Eriksson, J.G.; Lindström, J.; Peltonen, M.; Aunola, S.; Hämäläinen, H.; Keinänen-Kiukaanniemi, S.; Laakso, M.; Valle, T.T.; Lahtela, J.; et al. Effect of lifestyle intervention on the occurrence of metabolic syndrome and its components in the Finnish Diabetes Prevention Study. Diabetes Care 2008, 31, 805–807. [Google Scholar] [CrossRef] [PubMed]
- Sidiropoulos, E.; Jeffery, A.; Mackay, S.; Gallocher, R.; Forgey, H.; Chips, C. South Africa Survey 1995/1996; South African Institute of Race and Relations: Johannesburg, South Africa, 1996; pp. 234–360. [Google Scholar]
- Statistics South Africa. Cause of Death in South Africa 1997–2001: Advance Release of Records of Death; Statistics South Africa: Pretoria, South Africa, 2002; pp. 18–42. [Google Scholar]
- Monyeki, K.D.; Van Lenthe, F.J.; Steyn, N.P. Obesity: Does it occur in African children in a rural community. Int. J. Epidemiol. 1999, 28, 287–292. [Google Scholar] [CrossRef] [PubMed]
- Monyeki, K.D.; Cameron, N.; Getz, B. Growth and nutritional status of rural South African children 3–10 years old: The Ellisras Growth Study. Am. J. Hum. Biol. 2000, 12, 42–49. [Google Scholar] [CrossRef]
- Langenhoven, M.L.; Conradie, P.J.; Wolmarans, P.; Faber, M. MRC Food Quantities Manual, 2nd ed.; Cape Town, Research Institute for Nutritional Diseases, South African Medical Research Council: Parow, South Africa, 1991; pp. 117–200. [Google Scholar]
- Frisancho, A.R. Anthropometric Standards for the Assessment of Growth and Nutritional Status; University of Michigan Press: Ann Arbor, MI, USA, 1990. [Google Scholar]
- FoodFinder Database. Medical Research Council of South Africa Food Composition Database. SA HealthInfo. Available online: http://www.mrc.ac.za/FoodComp/ (accessed on 16 April 2015).
- Norton, K.; Olds, T. Anthropometrica: A Textbook of Body Measurement for Sports and Health Courses; UNSW Press: Sydney, Australia, 1996. [Google Scholar]
- National High Blood Pressure Education Program Working Group on High Blood Pressure in Children and Adolescents. The fourth report on the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents. Paediatrics 2004, 114, 555–576. [Google Scholar]
- Alberti, K.G.; Eckel, R.H.; Grundy, S.M.; Zimmet, P.Z.; Cleeman, J.I.; Donato, K.A.; Fruchart, J.; James, W.P.T.; Loria, C.M.; Smith, S.C. Harmonizing the metabolic syndrome. Circulation 2009, 120, 1640–1645. [Google Scholar] [CrossRef] [PubMed]
- Joint, FAO and World Health Organization. Vitamin and Mineral Requirements in Human Nutrition; Joint, FAO and World Health Organization: Bangkok, Thailand, 2005. [Google Scholar]
- Naicker, A. The Prevalence of Selected Risk Markers for Non-Communicable Diseases and Associations with Lifestyle Behaviours in an Indian Community in KwaZulu Natal. Ph.D. Thesis, Potchefstroom Campus of the North West University, Potchefstroom, South Africa, 2009. [Google Scholar]
- Richter, M.; Baumgartner, J.; Wentzel-Viljoen, E.; Smuts, C.M. Different dietary fatty acids are associated with blood lipids in healthy South African men and women: The PURE study. Int. J. Cardiol. 2014, 172, 368–374. [Google Scholar] [CrossRef] [PubMed]
- Slavin, J.L. Dietary fiber and body weight. Nutrition 2005, 21, 411–418. [Google Scholar] [CrossRef] [PubMed]
- Food and Agricultural Organization. Increasing Fruit and Vegetable Intake Becomes a Global Priority; Food and Agricultural Organization of the United Nations: New York, NY, USA, 2003. [Google Scholar]
- Goulder, T.J.; Alberti, K.G. Dietary fibre and diabetes. Diabetologia 1978, 15, 285–287. [Google Scholar] [CrossRef] [PubMed]
- Kolahdooz, F.; Spearing, K.; Sharma, S. Dietary Adequacies among South African Adults in Rural KwaZulu-Natal. PLoS ONE 2013, 8, 6. [Google Scholar] [CrossRef] [PubMed]
- Ahola, A.J.; Harjutsalo, V.; Thorn, L.M.; Freese, R.; Forsblom, C.; Mäkimattila, S.; Groop, P.H. The association between macronutrient intake and the metabolic syndrome and its components in type 1 diabetes. Br. J. Nutr. 2017, 117, 450–456. [Google Scholar] [CrossRef] [PubMed]
- Fezeu, L.; Balkau, B.; Kengne, A.P.; Sobngwi, E.; Mbanya, J.C. Metabolic syndrome in a sub-Saharan African setting: Central obesity may be the key determinant. Atherosclerosis 2007, 193, 70–76. [Google Scholar] [CrossRef] [PubMed]
- Food and Drug Administration (FAO). Food Labelling Health Claims, Oats and Coronary Heart Disease. Fed. Regist. 1996, 73, 9938–9947. [Google Scholar]
- Trautwein, E.A.; Kunath-Rau, A.; Erbersdobler, H.F. Increased fecal bile acid excretion and changes in the circulating bile acid pool are involved in the hypocholesterolemic and gallstone-preventive actions of psyllium in hamsters. J. Nutr. 1999, 129, 896–902. [Google Scholar] [CrossRef] [PubMed]
- Estruch, R.; Martinez-Gonzalez, M.A.; Corella, D.; Basora-Gallisá, J.; Ruiz-Gutierrez, V.; Covas, M.I.; Fiol, M.; Gómez-Gracia, E.; Lopez-Sabater, M.C.; Escoda, R.; et al. Effects of dietary fibre intake on risk factors for cardiovascular disease in subjects at high risk. J. Epidemiol. Community Health 2009, 63, 582–588. [Google Scholar] [CrossRef] [PubMed]
- Moreno Franco, B.; León Latre, M.; Andrés Esteban, E.M.; Ordovás, J.M.; Casasnovas, J.A.; Peñalvo, J.L. Soluble and insoluble dietary fibre intake and risk factors for metabolic syndrome and cardiovascular disease in middle-aged adults: The AWHS cohort. Nutr. Hosp. 2014, 30, 1279–1288. [Google Scholar] [PubMed]
- Hosseinpour-Niazi, S.; Mirmiran, P.; Sohrab, G.; Hosseini-Esfahani, F.; Azizi, F. Inverse association between fruit, legume, and cereal fiber and the risk of metabolic syndrome: Tehran Lipid and Glucose Study. Diabetes Res. Clin. Pract. 2011, 2, 276–283. [Google Scholar] [CrossRef] [PubMed]
- Willet, W. Implications of total energy intake for epidemiologic analysis. Nutr. Epidemiol. 1998, 273–301. [Google Scholar] [CrossRef]
- Chen, J.P.; Chen, G.C.; Wang, X.P.; Qin, L.; Bai, Y. Dietary Fiber and Metabolic Syndrome: A Meta-Analysis and Review of Related Mechanisms. Nutrients 2017, 10, 24. [Google Scholar] [CrossRef] [PubMed]
- Martin, A. The “apports nutritionnels conseilles (ANC)” for the French population. Reprod. Nutr. Dev. 2001, 4, 1119–1128. [Google Scholar] [CrossRef]
18–24 Years | 25–30 Years | 18–30 Years | ||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Total Fiber (g) | Insoluble Fiber (g) | Soluble Fiber (g) | Total Fiber (g) | Insoluble Fiber (g) | Soluble Fiber (g) | Total Fiber (g) | Insoluble Fiber (g) | Soluble Fiber (g) | ||||||||||
Males | Females | Males | Females | Males | Females | Males | Females | Males | Females | Males | Females | Males | Females | Males | Females | Males | Females | |
Median [IQR] | 5.3 [0.0–32.1] | 6.0 [0.0–32.7] | 0.0 [0.0–6.7] | 0.0 [0.0–10.9] | 0.0 [0.0–7.3] | 0.0 [0.0–32.7] | 3.6 [0.0–43.9] | 4.5 [0.0–48.9] | 0.0 [0.0–12.0] | 0.0 [0.0–18.0] | 0.0 [0.0–4.8] | 0.0 [0.0–14.9] | 4.3 [0.0–43.9] | 5.1 [0.0–48.9] | 0.0 [0.0–12.0] | 0.0 [0.0–18.0] | 0.0 [0.0–7.3] | 0.0 [0.0–14.9] |
Total | 5.3 [0.0–32.7] | 0.0 [0.0–10.9] | 0.0 [0.0–12.9] | 4.0 [0.0–48.9] | 0.0 [0.0–18.0] | 0.0 [0.0–14.9] | 4.6 [0.0–48.9] | 0.0 [0.0–18. 0] | 0.0 [0.0–15.0] | |||||||||
SD Total | 7.1 6.0 6.7 | 1.3 1.8 1.6 | 1.0 1.6 1.4 | 6.9 8.0 7.5 | 1.5 2.1 0.8 | 0.9 1.6 1.3 | 7.1 7.4 7.2 | 1.4 2.0 1.7 | 1.0 1.6 1.3 |
18–24 Years | 25–30 Years | 18–30 Years | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Males (n = 122) | Female (n = 117) | Total (n = 239) | p-Value | Males (n = 182) | Female (n = 206) | Total (n = 388) | p-Value | Males (n = 304) | Females (n = 323) | Total (n = 627) | p-Value | |
Waist circumference (cm) | 73.35 ± 8.80 | 78.11 ± 13.23 | 75.68 ± 11.42 | 0.001 | 76.23 ± 9.79 | 84.51 ± 14.49 | 80.63 ± 13.16 | <0.001 | 75.07 ± 9.50 | 82.20 ± 14.36 | 78.74 ± 12.74 | <0.001 |
HDL-C (mmol/L) | 1.19 ± 0.33 | 1.10 ± 0.28 | 1.15 ± 0.312 | 0.027 | 1.21 ± 0.40 | 1.09 ± 0.31 | 1.14 ± 0.36 | 0.001 | 1.20 ± 0.37 | 1.09 ± 0.30 | 1.15 ± 0.34 | <0.001 |
Fasting blood glucose (mmol/L) | 5.51 ± 0.90 | 5.54 ± 0.95 | 5.52 ± 0.93 | 0.806 | 5.39 ± 0.86 | 5.62 ± 1.83 | 5.51 ± 1.46 | 0.121 | 5.44 ± 0.88 | 5.59 ± 1.56 | 5.51 ± 1.28 | 0.136 |
Total cholesterol (mmol/L) | 3.98 ± 0.90 | 4.09 ± 1.01 | 4.03 ± 0.96 | 0.349 | 4.07 ± 0.95 | 4.36 ± 1.16 | 4.22 ± 1.08 | 0.007 | 4.03 ± 0.93 | 4.26 ± 1.11 | 4.15 ± 1.03 | 0.005 |
Triglycerides (mmol/L) | 0.98 ± 0.60 | 0.85 ± 0.45 | 0.91 ± 0.54 | 0.067 | 1.11 ± 0.66 | 1.02 ± 0.53 | 1.06 ± 0.60 | 0.145 | 1.05 ± 0.64 | 0.96 ± 0.51 | 1.00 ± 0.58 | 0.035 |
Systolic blood pressure (mmHg) | 123.25 ± 12.24 | 112.89 ± 10.26 | 118.18 ± 12.42 | <0.001 | 127.66 ± 12.46 | 114.80 ± 11.11 | 120.83 ± 13.35 | <0.001 | 125.89 ± 12.48 | 114.11 ± 10.83 | 119.82 ± 13.06 | <0.001 |
Diastolic blood pressure (mmHg) | 68.87 ± 9.51 | 68.74 ± 9.72 | 68.81 ± 9.59 | 0.916 | 73.09 ± 10.27 | 69.23 ± 9.13 | 71.04 ± 9.86 | <0.001 | 71.39 ± 10.17 | 69.05 ± 9.33 | 70.19 ± 9.81 | 0.003 |
18–24 Years | 25–30 Years | 18–30 Years | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Males (n = 122) | Female (n = 117) | Total (n = 239) | p-Value | Males (n = 182) | Female (n = 206) | Total (n = 388) | p-Value | Males (n = 304) | Females (n = 323) | Total (n = 627) | p-Value | |
Metabolic syndrome | 9.8 (12) | 30.8 (36) | 20.1 (48) | <0.001 | 7.7 (14) | 40.3 (83) | 25.0 (97) | <0.001 | 8.6 (26) | 36.8 (119) | 23.1 (145) | <0.001 |
Total fiber Male < 38 g Female < 25 g | 95.9 (117) | 100 (117) | 97.9 (234) | 0.027 | 96.7 (176) | 99.0 (204) | 97.9 (380) | 0.108 | 96.4 (293) | 99.4 (321) | 97.9 (614) | 0.008 |
Insoluble fiber < 10 g | 100.0 (122) | 99.1 (116) | 99.6 (238) | 0.308 | 99.5 (181) | 99.5 (205) | 99.5 (386) | 0.930 | 99.7 (303) | 99.4 (321) | 99.5 (624) | 0.599 |
Soluble fiber < 2.5 g | 100.0 (122) | 99.1 (116) | 99.6 (238) | 0.308 | 100.0 (182) | 99.5 (205) | 99.7 (387) | 0.348 | 100.0 (304) | 99.4 (321) | 99.7 (625) | 0.170 |
Elevated waist circumference Male > 94 cm Female > 80 cm | 4.9 (6) | 39.3 (46) | 21.8 (52) | <0.001 | 4.4 (8) | 60.2 (124) | 34.0 (132) | <0.001 | 4.6 (14) | 52.6 (170) | 29.3 (184) | <0.001 |
Low HDL-C Male < 1.0 mmol/L Female < 1.3 mmol/L | 29.5 (36) | 77.8 (91) | 53.1 (127) | <0.001 | 30.2 (55) | 79.1 (163) | 56.2 (218) | <0.001 | 29.9 (91) | 78.6 (254) | 55.0 (345) | <0.001 |
Elevated fasting blood glucose >5.6 mmol/L | 45.1 (55) | 47.9 (56) | 46.6 (111) | 0.711 | 42.9 (78) | 47.6 (98) | 45.4 (176) | 0.353 | 43.8 (133) | 47.7 (154) | 45.8 (287) | 0.343 |
High total cholesterol >5.1 mmol/L | 10.7 (13) | 17.9 (21) | 14.2 (34) | 0.108 | 11.5 (21) | 24.8 (51) | 18.6 (72) | 0.001 | 11.2 (34) | 22.3 (72) | 16.9 (106) | <0.001 |
High triglycerides >1.7 mmol/L | 8.2 (10) | 7.7 (9) | 7.9 (19) | 0.888 | 12.1 (22) | 9.7 (20) | 10.8 (42) | 0.453 | 10.5 (32) | 9.0 (29) | 9.7 (61) | 0.514 |
High systolic blood pressure >130 mmHg | 17.2 (21) | 0.9 (1) | 9.2 (22) | <0.001 | 24.7 (45) | 4.9 (10) | 14.2 (55) | <0.001 | 39.2 (100) | 7.7 (25) | 19.9 (125) | <0.001 |
High diastolic blood pressure >85 mmHg | 6.6 (8) | 6.8 (8) | 6.7 (16) | 0.931 | 10.4 (19) | 3.9 (8) | 7.0 (27) | 0.011 | 8.9 (27) | 5.0 (16) | 6.9 (43) | 0.052 |
Log Total Fiber | ||||||||
---|---|---|---|---|---|---|---|---|
Adjusted for Age and Gender | Adjusted for Age, Gender, and Energy | |||||||
β | SE (Beta) | p Value | 95% CI | β | SE (Beta) | p Value | 95% CI | |
Waist circumference (cm) | 0.000 | 0.001 | 0.899 | (−0.003; 0.003) | 0.001 | 0.001 | 0.788 | (−0.002; 0.003) |
HDL-C (mmol/L) | −0.028 | 0.052 | 0.592 | (−0.128; 0.074) | −0.085 | 0.044 | 0.051 | (−0.173; 0.002) |
Fasting blood glucose (mmol/L) | −0.028 | 0.014 | 0.039 | (−0.054; −0.001) | −0.019 | 0.012 | 0.044 | (−0.042; 0.003) |
Total cholesterol (mmol/L) | −0.007 | 0.017 | 0.687 | (−0.040; 0.036) | −0.008 | 0.015 | 0.593 | (−0.036; 0.021) |
Triglycerides (mmol/L) | 0.007 | 0.030 | 0.814 | (−0.053; 0.067) | 0.008 | 0.026 | 0.754 | (−0.043; 0.59) |
Systolic blood pressure (mmHg) | −0.003 | 0.001 | 0.033 | (−0.006; 0.000) | −0.002 | 0.001 | 0.045 | (−0.050; 0.002) |
Diastolic blood pressure (mmHg) | −0.002 | 0.002 | 0.323 | (−0.005; 0.002) | −0001 | 0.002 | 0.440 | (−0.004; 0.002) |
log insoluble fiber | ||||||||
Waist circumference (cm) | 0.001 | 0.001 | 0.512 | (−0.001; 0.002) | 0.001 | 0.001 | 0.394 | (−0.001; 0.002) |
HDL-C (mmol/L) | −0.038 | 0.031 | 0.224 | (−0.099; 0.023) | −0.055 | 0.030 | 0.071 | (−0.114; 0.005) |
Fasting blood glucose (mmol/L) | −0.013 | 0.008 | 0.103 | (−0.019; 0.002) | −0.011 | 0.008 | 0.170 | (−0.027; 0.005) |
Total cholesterol (mmol/L) | −0.002 | 0.010 | 0.867 | (−0.022; 0.018) | −0.002 | 0.010 | 0.840 | (−0.021; 0.017) |
Triglycerides (mmol/L) | 0.005 | 0.018 | 0.765 | (−0.031; 0.042) | 0.006 | 0.018 | 0.745 | (−0.029; 0.041) |
Systolic blood pressure (mmHg) | −0.002 | 0.001 | 0.039 | (−0.004; 0.000) | −0.002 | 0.001 | 0.061 | (−0.003; 0.000) |
Diastolic blood pressure (mmHg) | −0.001 | 0.001 | 0.317 | (−0.003; 0.001) | −0.001 | 0.001 | 0.383 | (−0.003; 0.001) |
log soluble fiber | ||||||||
Waist circumference (cm) | 0.001 | 0.001 | 0.465 | (−0.001; 0.002) | 0.001 | 0.001 | 0.353 | (−0.001; 0.002) |
HDL-C (mmol/L) | −0.035 | 0.026 | 0.179 | (−0.087; 0.016) | −0.049 | 0.026 | 0.050 | (−0.099; 0.001) |
Fasting blood glucose (mmol/L) | −0.001 | 0.007 | 0.100 | (−0.025; 0.002) | −0.009 | 0.007 | 0.166 | (−0.022; 0.004) |
Total cholesterol (mmol/L) | −0.004 | 0.009 | 0.676 | (−0.020; 0.013) | −0.004 | 0.008 | 0.646 | (−0.020; 0.031) |
Triglycerides (mmol/L) | 0.010 | 0.015 | 0.509 | (−0.020; 0.041) | 0.010 | 0.015 | 0.486 | (−0.019; 0.040) |
Systolic blood pressure (mmHg) | −0.002 | 0.001 | 0.018 | (−0.003; 0.000) | −0.002 | 0.001 | 0.029 | (−0.003; 0.000) |
Diastolic blood pressure (mmHg) | −0.001 | 0.001 | 0.197 | (−0.003; 0.001) | −0.001 | −0.001 | 0.242 | (−0.003; 0.001) |
© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Sekgala, M.D.; Mchiza, Z.J.; Parker, W.-a.; Monyeki, K.D. Dietary Fiber Intake and Metabolic Syndrome Risk Factors among Young South African Adults. Nutrients 2018, 10, 504. https://doi.org/10.3390/nu10040504
Sekgala MD, Mchiza ZJ, Parker W-a, Monyeki KD. Dietary Fiber Intake and Metabolic Syndrome Risk Factors among Young South African Adults. Nutrients. 2018; 10(4):504. https://doi.org/10.3390/nu10040504
Chicago/Turabian StyleSekgala, Machoene D., Zandile J. Mchiza, Whadi-ah Parker, and Kotsedi D. Monyeki. 2018. "Dietary Fiber Intake and Metabolic Syndrome Risk Factors among Young South African Adults" Nutrients 10, no. 4: 504. https://doi.org/10.3390/nu10040504