University students often face a multitude of health risks due to the transitional phase they experience. The lifestyles they adopt increase their susceptibility to metabolic issues that are of a public health concern. Metabolic risk factors, encompassing obesity, hypertension, dyslipidemia, and elevated glucose levels pose significant health concerns among this demographic. The cluster of these metabolic risk factors is known as a metabolic syndrome which has the potential to increase the risk of cardiovascular diseases amongst young populations who are linked with the adaptation of health risk behaviours. The objective of this cross-sectional study was to assess the prevalence and determinants of metabolic risk factors of university students in two regions that were purposively selected from mainland Tanzania. The distribution of continuous variables was tested for normality using box plots and-Q plots and the Shapiro-Wilk test. Multivariate linear regression analysis was used to assess the determinants of metabolic risk factors among variables. The metabolic risk factors that were assessed include blood pressure, glucose levels, central obesity, and lipid profiles. The most prevalent metabolic risk factor was the high levels of low-density lipoprotein among university students. The study found Low-density lipoprotein levels that were above optimal, borderline high, high and very high. The low-density lipoprotein levels found in the study were 24 (20.3%), 16 (13.6%), 13 (11%) and 17 (14.4%) for above optimal, borderline high, high, and very high respectively. Significant associations were also found in the determinants of the metabolic risk factors, for central obesity (P=0.000) and for triglyceride levels (P=0.000); (P=0.004). Factors that increase the susceptibility to metabolic risk factors include the location of the university, scholarship status and Individual dietary diversity scores. Saint John’s University in Dodoma was associated with low-density lipoprotein and Total cholesterol (β=17.01, SE=10.1, p=0.1) and (β=-0.170, SE=0.0519, p=0.01) respectively. Receiving scholarship and high dietary diversity score was associated with low-density lipoprotein (β=21.83, SE=10.4, p=0.1); (β=5.731, SE=3.14, p=0.1) respectively. University students are living with metabolic risk factors that could have future health implications. Understanding these aspects can help in devising targeted interventions and educational programs to mitigate metabolic risks and promote healthier lifestyles among university students.
| Published in | Journal of Food and Nutrition Sciences (Volume 12, Issue 1) |
| DOI | 10.11648/j.jfns.20241201.13 |
| Page(s) | 27-40 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Metabolic Risk Factors, Metabolic Syndrome, University Students, Determinants, Prevalence, Tanzania
| [1] | Olatona, F. A., Onabanjo, O. O., Ugbaja, R. N., Nnoaham, K. E., & Adelekan, D. A. (2018). Dietary habits and metabolic risk factors for non-communicable diseases in a university undergraduate population. Journal of health, population and nutrition, 37, 1-9. doi: 10.1186/s41043-018-0152-2. |
| [2] | Kassam, N., Surani, S., Hameed, K., Aghan, E., Mayenga, R., Matei, I.,... & Somji, S. (2023). Magnitude, Distribution and Contextual Risk Enhancing Predictors of High 10-Year Cardiovascular Risk Among Diabetic Patients in Tanzania. Patient Related Outcome Measures, 87-96. doi: 10.2147/PROM. S405392. |
| [3] | Florence, G. E., Derman, W. E., Popperwell, J. M., Kunorozva, L., & Gomez-Ezeiza, J. (2023). Prevalence of health risk behaviours related to non-communicable diseases amongst South African university students: a systematic review. Journal of Public Health, 45(4), 1042-1055. doi: 10.1093/pubmed/fdad106. |
| [4] | Obsa, M. S., Ataro, G., Awoke, N., Jemal, B., Tilahun, T., Ayalew, N.,... & Haji, Y. (2022). Determinants of dyslipidemia in Africa: a systematic review and meta-analysis. Frontiers in cardiovascular medicine, 8, 778891. doi: 10.3389/fcvm.2021.778891. |
| [5] | Macicame, I., Prista, A., Parhofer, K. G., Cavele, N., Manhiça, C., Nhachungue, S.,... & Rehfuess, E. (2021). Social determinants and behaviors associated with overweight and obesity among youth and adults in a peri-urban area of Maputo City, Mozambique. Journal of Global Health, 11. doi: 10.7189%2Fjogh.11.04021. |
| [6] | Tladi, D., Mokgatlhe, L., Nell, T., Shaibu, S., Mitchell, R., Mokgothu, C.,... & Hubona, O. (2021). Prevalence of the Metabolic Syndrome Among Batswana Adults in Urban and Semi-Urban Gaborone. Diabetes, Metabolic Syndrome and Obesity, 2505-2514. doi: 10.2147/DMSO.S285898. |
| [7] | MALINDISA, E. K., Balandya, E., Njelekela, M. A., & Mashiri, F. (2019). Magnitude of Type 2 Diabetes Mellitus, Dyslipidemia and Hypertension Among Young Adults in Urban Settings: A Cross Sectional Survey in Mwanza, Tanzania. doi: 10.21203/rs.2.13177/v1. |
| [8] | Mezhal, F., Oulhaj, A., Abdulle, A., AlJunaibi, A., Alnaeemi, A., Ahmad, A.,... & Ali, R. (2023). High prevalence of cardiometabolic risk factors amongst young adults in the United Arab Emirates: the UAE Healthy Future Study. BMC CardiovascularDisorders, 23(1), 137. doi: 10.1186/s12872-023-03165-3. |
| [9] | Driggins, S. N., & Muhammad, K. M. (2019). A population at risk: a metabolic syndrome study among African American students at a historically black college and university. Athens Journal of Health & Medical Sciences, 6(4), 231-242. doi: 10.30958/ajhms.6-4-3. |
| [10] | Ibrahim, M. S., Pang, D., Pappas, Y., & Randhawa, G. (2020). Metabolic syndrome risk models and scores: a systematic review. Biomed J Sci Tech Res, 26(1), 19695-19707. doi: 10.26717/BJSTR.2020.26.004307. |
| [11] | Malindisa, E. K., Balandya, E., Mashili, F., Iddi, S., & Njelekela, M. (2022). The magnitude of type 2 diabetes mellitus and cardiovascular disease risk factors among young adults in urban settings: a cross-sectional survey in Mwanza, Tanzania. The Pan African Medical Journal, 42. doi: 10.11604%2Fpamj.2022.42.19.22184. |
| [12] | Roman, W., Martin, H., & Sauli, E. (2019). Cardiovascular diseases in Tanzania: The burden of modifiable and intermediate risk factors. doi: 10.21037/jxym.2019.07.03. |
| [13] | Faijer-Westerink, H. J., Kengne, A. P., Meeks, K. A., & Agyemang, C. (2020). Prevalence of metabolic syndrome in sub-Saharan Africa: A systematic review and meta-analysis. Nutrition, Metabolism and Cardiovascular Diseases, 30(4), 547-565. doi: 10.1016/j.numecd.2019.12.012. |
| [14] | Pori, D. B., Msigula, P., & Massawe, H. B. (2022). Assessment of the Soil Information and Analysis of Related Land Constraints to the Selected Detailed Town Planning Schemes in Morogoro Municipal. Current Urban Studies, 10(3), 479-499. doi: 10.4236/cus.2022.103029. |
| [15] | Sumari, N. S., Cobbinah, P. B., Ujoh, F., & Xu, G. (2020). On the absurdity of rapid urbanization: Spatio-temporal analysis of land-use changes in Morogoro, Tanzania. Cities, 107, 102876. doi: 10.1016/j.cities.2020.102876. |
| [16] | National Bureau of Statistics. Available from: https://www.nbs.go.tz/index.php/en/. [Accessed 6 October 2023]. |
| [17] | World Bank. “Climate Knowledge Portal”. Available from: https://climateknowledgeportal.worldbank.org/country/tanzania/climate-data-historical. [Accessed 21 October 2023]. |
| [18] | Pallangyo, P., Mkojera, Z. S., Hemed, N. R., Swai, H. J., Misidai, N., Mgopa, L.,... & Janabi, M. (2020). Obesity epidemic in urban Tanzania: a public health calamity in an already overwhelmed and fragmented health system. BMC endocrinedisorders, 20(1), 1-9. doi: 10.1186/s12902-020-00631-3. |
| [19] | Tladi, D. M., Mokgatlhe, L., Shaibu, S., Nell, T., Mitchell, R., Mokgothu, C. J.,... & Hubona, O. (2020). Determination of optimal cut-off values for waist circumferences used for the diagnosis of the metabolic syndrome among Batswana adults (ELS 32). Cardiovascular Journal of Africa, 31(6), 314-318. doi:.10520/ejc-cardio1-v31-n6-a6. |
| [20] | Khamis, A. G., Senkoro, M., Mwanri, A. W., Kreppel, K., Mfinanga, S. G., Bonfoh, B., & Kwesigabo, G. (2020). Prevalence and determinants of hypertension among pastoralists in Monduli District, Arusha region in Tanzania: a cross-sectional study. Archives of Public Health, 78(1), 1-12. doi: 10.1186/s13690-020-00485-0. |
| [21] | Byashalira, K. C., Chamba, N. G., Alkabab, Y., Mbelele, P. M., Mpolya, E. A., Ntinginya, N. E.,... & ADEPT consortium. (2022). Impact of early diagnosis of impaired glucose regulation in tuberculosis: Comparison of clinical outcomes in people with tuberculosis in Tanzania. Tropical Medicine & International Health, 27(9), 815-822. doi: 10.1111/tmi.13806. |
| [22] | Ostchega, Yechiam, Jeffery P. Hughes, Guangyu Zhang, Tatiana Nwankwo, Jessica Graber, and Duong T. Nguyen. "Differences in hypertension prevalence and hypertension control by urbanization among adults in the United States, 2013–2018." American journal of hypertension 35, no. 1 (2022): 31-41. doi: 10.1093/ajh/hpab067. |
| [23] | Manus, M. B., Bloomfield, G. S., Leonard, A. S., Guidera, L. N., Samson, D. R., & Nunn, C. L. (2018). High prevalence of hypertension in an agricultural village in Madagascar. PloS one, 13(8), e0201616. doi: 10.1371/journal.pone.0201616. |
| [24] | Rashid, N., & Dika, H. I. (2017). Casual blood pressure among Tanzanian undergraduate students: need for re-defining population specific operational threshold between normotension and hypertension. Tanzania Journal of Health Research, 19(1). doi: 10.4314/thrb.v19i1.5. |
| [25] | Wang, C., Yuan, Y., Zheng, M., Pan, A. N., Wang, M., Zhao, M.,... & Xue, H. (2020). Association of age of onset of hypertension with cardiovascular diseases and mortality. Journal of the American College of Cardiology, 75(23), 2921-2930. doi: 10.1016/j.jacc.2020.04.038. |
| [26] | Mohammed, M. A., Ali, S. H., & Al-ghareebawi, A. M. A. (2023). Evaluation Cholesterol and Triglycerides Levels for Type One Diabetes Patients. World Journal of Current Medical and Pharmaceutical Research, 168-174. doi: 10.37022/wjcmpr.v5i5.289. |
| [27] | de Groot, R., van den Hurk, K., Schoonmade, L. J., de Kort, W. L., Brug, J., & Lakerveld, J. (2019). Urban-rural differences in the association between blood lipids and characteristics of the built environment: a systematic review and meta-analysis. BMJ global health, 4(1), e001017. doi: 10.1136/bmjgh-2018-001017. |
| [28] | Sarfo, F. S., & Ovbiagele, B. (2020). Prevalence and predictors of statin utilization among patient populations at high vascular risk in Ghana. Journal of the neurological sciences, 414, 116838. doi: 10.1016/j.jns.2020.116838. |
| [29] | Davis, E. F., Lazdam, M., Lewandowski, A. J., Worton, S. A., Kelly, B., Kenworthy, Y.,... & Leeson, P. (2012). Cardiovascular risk factors in children and young adults born to preeclamptic pregnancies: a systematic review. Pediatrics, 129(6), e1552-e1561. doi: 10.1542/peds.2011-3093. |
| [30] | Al-Duais, M. A., & Al-Awthan, Y. S. (2019). Association between qat chewing and dyslipidaemia among young males. Journal of Taibah University Medical Sciences, 14(6), 538-546. doi: 10.1016/j.jtumed.2019.09.008. |
| [31] | Kasia, B. E., Nyondia, V. Y., & Oseajeh, P. O. (2020). Evaluation of lipid profile pattern among apparently healthy students of Niger Delta University. Annals of Tropical Pathology, 11(2), 146. doi: 10.4103/atp.atp_17_20. |
| [32] | Rotich, S. J., Funder, M., & Marani, M. (2023). Suburban pastoralists: Pastoral adaptation strategies at the rural-urban interface in Nairobi, Kenya. Pastoralism, 13(1), 6. doi: 10.1186/s13570-023-00268-6. |
| [33] | Mitić, N. R., & Popović, L. (2019). Assessment of the risk status of diseases associated with overweight in students of the University of Pristina-Kosovska Mitrovica. Praxis medica, 48(3-4), 5-12. doi: 10.5937/pramed1904005M. |
| [34] | Maila, G., Audain, K., & Marinda, P. A. (2021). Association between dietary diversity, health and nutritional status of older persons in rural Zambia. South African Journal of Clinical Nutrition, 34(1), 34-39. doi: 10.1080/16070658.2019.1641271. |
| [35] | Molla, M. D., Wolde, H. F., & Atnafu, A. (2020). Magnitude of central obesity and its associated factors among adults in urban areas of Northwest Ethiopia. Diabetes, Metabolic Syndrome and Obesity, 4169-4178. doi: 10.2147/DMSO.S279837. |
| [36] | Munyogwa, M. J., Gibore, N. S., Ngowi, A. F., & Mwampagatwa, I. H. (2021). Effect of nutritional education intervention to reduce anaemia during pregnancy in Dodoma City, Tanzania: protocol for a cluster randomized controlled trial. Biology Methods and Protocols, 6(1), bpab012. doi: 10.1093/biomethods/bpab012. |
| [37] | Elkhateeb, Y. A. M. M., & yousefkhaled Alfhied, N. (2018). A study on the prevalence of diabetes mellitus among Students of Hail University. Age (year), 18(25), 21-15. doi: 10.11648/j.ijbse.20180603.11. |
| [38] | Yaaqoob, B. Y., & Kadhem, S. A. (2023). Assessment the level of knowledge and attitude of college students regarding diabetes mellitus. Health Education and Health Promotion, 11(1), 1001-1006. doi: 10.58209/hehp.11.1.173. |
| [39] | Alghamdi, I. K., Alrefai, A. M., Alghamdi, T. A., Nawawi, A. T., Badawy, Y. A., Alghamdi, I.,... & Badawy, Y. (2023). Prevalence of Contributing Factors Leading to the Development of Insulin Resistance Among Male Medical Students at a Private College in Saudi Arabia. Cureus, 15(11). doi: 10.7759/cureus.48269. |
| [40] | Malindisa, E., Balandya, E., Njelekela, M., Kidenya, B. R., Francis, F., Mmbaga, B. T.,... & PrayGod, G. (2023). Metabolic syndrome among people living with HIV on antiretroviral therapy in Mwanza, Tanzania. BMC Endocrine Disorders, 23(1), 88. doi: 10.1186/s12902-023-01340-3. |
| [41] | Israel, E., Hassen, K., Markos, M., Wolde, K., & Hawulte, B. (2022). Central obesity and associated factors among urban adults in dire dawa administrative city, Eastern Ethiopia. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy, 601-614. doi: 10.2147/DMSO.S348098. |
| [42] | Bereka, S. G., Demisse, A. W., & Getahun, G. K. (2022). Prevalence of abdominal obesity and associated risk factors among women civil servants in Addis Ababa, Ethiopia, 2021: an institution-based study. BMC nutrition, 8(1), 119. doi: 10.1186/s40795-022-00613-9. |
| [43] | Tegegne, K. D., Wagaw, G. B., Gebeyehu, N. A., Yirdaw, L. T., Shewangashaw, N. E., Mekonen, N. A., & Kassaw, M. W. (2022). Prevalence of central obesity and associated factors in Ethiopia: A systematic review and meta-analysis. Frontiers in Endocrinology, 13, 2118. doi: 10.3389/fendo.2022.983180. |
| [44] | van der Plas, A., Antunes, M., Pouly, S., de La Bourdonnaye, G., Hankins, M., & Heremans, A. (2023). Meta-analysis of the effects of smoking and smoking cessation on triglyceride levels. Toxicology Reports, 10, 367-375. doi: 10.1016/j.toxrep.2023.03.001. |
| [45] | Studziński, K., Tomasik, T., Windak, A., Banach, M., Wójtowicz, E., Mastej, M.,... & LIPIDOGRAM2015 Investigators. (2021). The differences in the prevalence of cardiovascular disease, its risk factors, and achievement of therapeutic goals among urban and rural primary care patients in Poland: Results from the LIPIDOGRAM 2015 study. Journal of Clinical Medicine, 10(23), 5656. doi: 10.3390/jcm10235656. |
| [46] | Li, K., Ma, X., Yuan, L., & Ma, J. (2022). Age differences in the association between marital status and hypertension: a population-based study. Journal of Human Hypertension, 36(7), 670-680. doi: 10.1038/s41371-021-00558-9. |
| [47] | Chen, Q., Ma, X., Geng, Y., Liao, J., & Ma, L. (2022). Association between smoking and hypertension under different PM2. 5 and green space exposure: A nationwide cross-sectional study. Frontiers in Public Health, 10, 1026648. doi: 10.3389/fpubh.2022.1026648. |
| [48] | Rong, S., Li, B., Chen, L., Sun, Y., Du, Y., Liu, B.,... & Bao, W. (2022). Association of Low‐Density Lipoprotein Cholesterol Levels with More than 20‐Year Risk of Cardiovascular and All-Cause Mortality in the General Population. Journal of the American Heart Association, 11(15), e023690. doi: 10.1161/JAHA.121.023690. |
| [49] | Metta, E. (2023). “A disease that God has given me” patients and caregivers’ perspectives on diabetes in southeastern Tanzania. BMC Public Health, 23(1), 213. doi: 10.1186/s12889-023-15147-3. |
| [50] | International Diabetes Federation Atlas 2021. Available from: https://diabetesatlas.org/atlas/tenth-edition/. [Accessed 12 October 2023]. |
| [51] | Melin, E. O., Thulesius, H. O., Hillman, M., Svensson, R., Landin-Olsson, M., & Thunander, M. (2019). Lower HDL-cholesterol, a known marker of cardiovascular risk, was associated with depression in type 1 diabetes: a cross sectional study. Lipids in Health and Disease, 18, 1-10. doi: 10.1186/s12944-019-1009-4. |
| [52] | Hamooya, B. M., Musonda, P., Mutale, W., Masenga, S. K., Halwiindi, H., Mutengo, K. H.,... & Heimburger, D. C. (2021). Prevalence of low high-density lipoprotein among young adults receiving antiretroviral therapy in Zambia: An opportunity to consider non-communicable diseases in resource-limited settings. Plos one, 16(2), e0247004. doi: 10.1371/journal.pone.0247004. |
APA Style
Mgetta, N., Muhimbula, H., Kulwa, K. (2024). Prevalence and Determinants of Metabolic Risk Factors Among University Students in Dodoma and Morogoro Regions Tanzania. Journal of Food and Nutrition Sciences, 12(1), 27-40. https://doi.org/10.11648/j.jfns.20241201.13
ACS Style
Mgetta, N.; Muhimbula, H.; Kulwa, K. Prevalence and Determinants of Metabolic Risk Factors Among University Students in Dodoma and Morogoro Regions Tanzania. J. Food Nutr. Sci. 2024, 12(1), 27-40. doi: 10.11648/j.jfns.20241201.13
AMA Style
Mgetta N, Muhimbula H, Kulwa K. Prevalence and Determinants of Metabolic Risk Factors Among University Students in Dodoma and Morogoro Regions Tanzania. J Food Nutr Sci. 2024;12(1):27-40. doi: 10.11648/j.jfns.20241201.13
Share This Article
Twitter
Linked In
Facebook
Copy
Download@article{10.11648/j.jfns.20241201.13,
author = {Neema Mgetta and Happiness Muhimbula and Kissa Kulwa},
title = {Prevalence and Determinants of Metabolic Risk Factors Among University Students in Dodoma and Morogoro Regions Tanzania},
journal = {Journal of Food and Nutrition Sciences},
volume = {12},
number = {1},
pages = {27-40},
doi = {10.11648/j.jfns.20241201.13},
url = {https://doi.org/10.11648/j.jfns.20241201.13},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jfns.20241201.13},
abstract = {University students often face a multitude of health risks due to the transitional phase they experience. The lifestyles they adopt increase their susceptibility to metabolic issues that are of a public health concern. Metabolic risk factors, encompassing obesity, hypertension, dyslipidemia, and elevated glucose levels pose significant health concerns among this demographic. The cluster of these metabolic risk factors is known as a metabolic syndrome which has the potential to increase the risk of cardiovascular diseases amongst young populations who are linked with the adaptation of health risk behaviours. The objective of this cross-sectional study was to assess the prevalence and determinants of metabolic risk factors of university students in two regions that were purposively selected from mainland Tanzania. The distribution of continuous variables was tested for normality using box plots and-Q plots and the Shapiro-Wilk test. Multivariate linear regression analysis was used to assess the determinants of metabolic risk factors among variables. The metabolic risk factors that were assessed include blood pressure, glucose levels, central obesity, and lipid profiles. The most prevalent metabolic risk factor was the high levels of low-density lipoprotein among university students. The study found Low-density lipoprotein levels that were above optimal, borderline high, high and very high. The low-density lipoprotein levels found in the study were 24 (20.3%), 16 (13.6%), 13 (11%) and 17 (14.4%) for above optimal, borderline high, high, and very high respectively. Significant associations were also found in the determinants of the metabolic risk factors, for central obesity (P=0.000) and for triglyceride levels (P=0.000); (P=0.004). Factors that increase the susceptibility to metabolic risk factors include the location of the university, scholarship status and Individual dietary diversity scores. Saint John’s University in Dodoma was associated with low-density lipoprotein and Total cholesterol (β=17.01, SE=10.1, p=0.1) and (β=-0.170, SE=0.0519, p=0.01) respectively. Receiving scholarship and high dietary diversity score was associated with low-density lipoprotein (β=21.83, SE=10.4, p=0.1); (β=5.731, SE=3.14, p=0.1) respectively. University students are living with metabolic risk factors that could have future health implications. Understanding these aspects can help in devising targeted interventions and educational programs to mitigate metabolic risks and promote healthier lifestyles among university students.
},
year = {2024}
}
TY - JOUR T1 - Prevalence and Determinants of Metabolic Risk Factors Among University Students in Dodoma and Morogoro Regions Tanzania AU - Neema Mgetta AU - Happiness Muhimbula AU - Kissa Kulwa Y1 - 2024/01/08 PY - 2024 N1 - https://doi.org/10.11648/j.jfns.20241201.13 DO - 10.11648/j.jfns.20241201.13 T2 - Journal of Food and Nutrition Sciences JF - Journal of Food and Nutrition Sciences JO - Journal of Food and Nutrition Sciences SP - 27 EP - 40 PB - Science Publishing Group SN - 2330-7293 UR - https://doi.org/10.11648/j.jfns.20241201.13 AB - University students often face a multitude of health risks due to the transitional phase they experience. The lifestyles they adopt increase their susceptibility to metabolic issues that are of a public health concern. Metabolic risk factors, encompassing obesity, hypertension, dyslipidemia, and elevated glucose levels pose significant health concerns among this demographic. The cluster of these metabolic risk factors is known as a metabolic syndrome which has the potential to increase the risk of cardiovascular diseases amongst young populations who are linked with the adaptation of health risk behaviours. The objective of this cross-sectional study was to assess the prevalence and determinants of metabolic risk factors of university students in two regions that were purposively selected from mainland Tanzania. The distribution of continuous variables was tested for normality using box plots and-Q plots and the Shapiro-Wilk test. Multivariate linear regression analysis was used to assess the determinants of metabolic risk factors among variables. The metabolic risk factors that were assessed include blood pressure, glucose levels, central obesity, and lipid profiles. The most prevalent metabolic risk factor was the high levels of low-density lipoprotein among university students. The study found Low-density lipoprotein levels that were above optimal, borderline high, high and very high. The low-density lipoprotein levels found in the study were 24 (20.3%), 16 (13.6%), 13 (11%) and 17 (14.4%) for above optimal, borderline high, high, and very high respectively. Significant associations were also found in the determinants of the metabolic risk factors, for central obesity (P=0.000) and for triglyceride levels (P=0.000); (P=0.004). Factors that increase the susceptibility to metabolic risk factors include the location of the university, scholarship status and Individual dietary diversity scores. Saint John’s University in Dodoma was associated with low-density lipoprotein and Total cholesterol (β=17.01, SE=10.1, p=0.1) and (β=-0.170, SE=0.0519, p=0.01) respectively. Receiving scholarship and high dietary diversity score was associated with low-density lipoprotein (β=21.83, SE=10.4, p=0.1); (β=5.731, SE=3.14, p=0.1) respectively. University students are living with metabolic risk factors that could have future health implications. Understanding these aspects can help in devising targeted interventions and educational programs to mitigate metabolic risks and promote healthier lifestyles among university students. VL - 12 IS - 1 ER -
Department of Human Nutrition and Consumer Sciences, Sokoine University of Agriculture, Morogoro, Tanzania
Department of Human Nutrition and Consumer Sciences, Sokoine University of Agriculture, Morogoro, Tanzania
Department of Human Nutrition and Consumer Sciences, Sokoine University of Agriculture, Morogoro, Tanzania
