Occupational Predictors of Metabolic Profiles in Type 2 Diabetes. A Cross-Sectional Study in Nigeria

Authors

  • Ala OA Department of Medicine, College of Health Sciences, Osun State University, Osogbo, Nigeria
  • Uduagbamen PK Bowen University/Bowen University Teaching Hospital, Ogbomosho
  • Yusuf AO Department of Medicine, College of Health Sciences, Osun State University, Osogbo, Nigeria
  • Bamikefa TA Department of Medicine, College of Health Sciences, Osun State University, Osogbo, Nigeria
  • Odeyemi AO Department of Medicine, College of Health Sciences, Osun State University, Osogbo, Nigeria
  • Adedire AA Department of Surgery, College of Health Sciences, Osun State University, Osogbo, Nigeria
  • Soyoye DO Department of Medicine, College of Health Sciences, Obafemi Awolowo University, Ile-Ife, Nigeria.
  • Adeyeye AG Department of Medicine, College of Health Sciences, Osun State University, Osogbo, Nigeria
  • Kolawole B Department of Medicine, College of Health Sciences, Obafemi Awolowo University, Ile-Ife, Nigeria.

DOI:

https://doi.org/10.60787/tnhj.v24i3.855

Keywords:

Diabetes, occupation, metabolomics, physical activity, atherogenic index of plasma, cardiac risk ratio, kidney function, homocysteine

Abstract

Background: The prevalence and burden of type 2 diabetes have continued to rise globally, particularly in developing countries, driven by a growing tendency to a westernized lifestyle characterized by low physical activity and increased fat intake. The study assessed the association of on the metabolic profile of type 2 diabetic patients.

Method: The analysed data included the socio-demographic, anthropometric and clinical findings, and laboratory (metabolites) results of 187 patients with diabetes. Continuous and categorical variables were compared using student’s t-test and Chi square (or Fisher’s exact test) respectively. A p-value <0.05 was statistically significant.

Result: The mean age of the 187 (94 males and 93 females) participants was 57.85 ± 5.17 years. In participants with paid employments, the mean fasting plasma insulin and HOMA were the highest. The unemployed had the lowest levels of triglycerides and LDL-C. the eGFR was highest in the artisans and lowest in the retired population. The smokers had poor glucose control (p = 0.01). The atherogenic index of plasma was higher in poorly controlled diabetes, p=0.04. Smoking (OR-2.58, 95% CI-2.14-5.04, p=0.04) and elevated HOMA (OR-1.9, 95% CI-1.47-4.23, p-0.03), were independently associated with high physical activity.

Conclusion: High physical activity had a beneficial impact on diabetes control. This benefit, coupled with an improved lipid profile, was however overwhelmed by smoking, which increased the levels of atherogenic markers and potentially the risk of cardiovascular disease and events.

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References

Kolawole BA, Anumah FA, Unachukwu C. Health Resource Utilization among Patients with Type 2 Diabetes Mellitus in Nigeria: An Analysis from the International Diabetes Management Practice Study (IDMPS). West Afr J Med. 2023;40(11):1145-1154.

Oyewole OO, Odusan O, Oritogun KS, Idowu AO. Physical activity among type-2 diabetic adult Nigerians. Ann Afr Med. 2014; 13(4):189-94. doi: 10.4103/1596-3519.142290.

Ashtekar S, Deshmukh PP, Ghaisas N, Ashtekar C, Upasani S, Kirloskar M, et al. Effect of Two-Only-Meal Frequency and Exercise on HbA1C Outcomes, Weight, and Anti-Diabetic Medication in Type 2 Diabetes in a Popular Lifestyle Change Campaign in Maharashtra, Compared to Conventional Clinical Management: A Quasi-Experimental Multicenter Study in Maharashtra. Indian J Community Med [Internet]. 2023. Jan 1 Available from: /pmc/articles/PMC10112759/ doi: 10.4103/ijcm.ijcm_248_22

Blonde L, Umpierrez GE, Reddy SS, McGill JB, Berga SL, Bush M, et al. American Association of Clinical Endocrinology Clinical Practice Guideline: Developing a Diabetes Mellitus Comprehensive Care Plan: 2022 Update. Endocrine Practice. 2022;28(10):923-1049.

Elsayed NA, Aleppo G, Aroda VR, Bannuru RR, Brown FM, Bruemmer D, et al. 5. Facilitating Positive Health Behaviors and Well-being to Improve Health Outcomes: Standards of Care in Diabetes-2023. Diabetes Care [Internet]. 2023. Jan 1 [cited 2023 May 25];46(Supple 1):S68–96. Available from: https://pubmed.ncbi.nlm.nih.gov/36507648/

Kautzky-Willer A, Harreiter J, Pacini G. Sex and gender differences in risk, pathophysiology and complications of type 2 diabetes mellitus. Endocr Rev. 2016; 37(3):278–316. doi: 10.1210/er.2015-1137.

Basiak-Rasala A, Rozanska D, Zatonsk K. Food groups in dietary prevention of type 2 diabetes RoczPanstwZaklHig 2019; 70(4): 347-357.

Coker RH, Hays RR, Williams RH, Xu L, Wolfe RR, Evans WJ. Bed rest worsens impairments in Fat and Glucose Metabolism in Older Overweight Adults.JGerontol A BiolSci Med Sci 2014; 69A(3): 363-370 doi:10.1093/Gerona/glt1.00

Gungor O, Kara AV, Hasbal NB, Kalantar-Zadeh K. Dietary protein and muscle in chronic kidney disease: new insights Curr Opin Clin Nuyr Metab Care 2023; 26(3): 226-234 doi: 10.1097/MCO.0000000000000903(4): 1351-1402.

Booth FW, Roberts CK, Thyfault JP, Ruegsegger GN, Toedebusch RG. Role of Inactivity in Chronic Diseases: Evolutionary Insight and Pathophysiological Mechanisms Physiol Rev 2017; 97

Kumar Prabhakar P, Kumar Batiha GES. Potential Therapeutic Targets for the management of Diabetes Mellitus Type 2. Curr Med Chem [Internet]. 2023. May 1 [cited 2023 May 25];30. Available from: https://pubmed.ncbi.nlm.nih.gov/37125833/ [PubMed] [Google Scholar]

Charan J, Biswas T. How to calculate sample size for different study designs in medical research Indian J Psychol Med. 2013;35(2):121–6.

Uloko AE, Musa BM, Ramalan MA, Gezawa ID, Puepet FH, Uloko AT, et al. Prevalence and Risk Factors for Diabetes Mellitus in Nigeria: A Systematic Review and Meta-Analysis. Diabetes Ther. 2018 ;9(3):1307-1316Jung SH. Stratified Fisher's exact test and its sample size calculation. Biom J. 2014;56(1):129-40. doi: 10.1002/bimj.201300048.

National Institute of Health: The practical guide to the identification, evaluation and treatment of overweight and obesity in adult. Obesity Res 1998; 89: 452-461.

Jeong TD, Park S, Hong KS. Performance Evaluation of the Bio-Rad D-100 System for Hemoglobin A1c Assay. Clin Lab. 2017 Nov 1;63(11):1923-1928. doi: 10.7754/Clin.Lab.2017.170524.

Diabetes Standards of Care: ADA guidelines (2018), Available at: http://diabetesed.net/wp-content/uploads/2017/12/2018-ADA-Standards-of-Care.pdf. Accessed22/4/ 2020

Andreacchi AT, Griffith LE, Guindon GE, Mayhew A, Bassim C, Pigeyre M, Stranges S, Anderson LN. Body mass index, waist circumference, waist-to-hip ratio, and body fat in relation to health care use in the Canadian Longitudinal Study on Aging. Int J Obes (Lond). 2021 Mar;45(3):666-676. doi: 10.1038/s41366-020-00731-z.

Chuang SY, Cheng HM, Chang WL, Yeh WY, Huang CJ, Chen CH. 130/80 mmHg as a unifying hypertension threshold for office brachial, office central, and ambulatory daytime brachial blood pressure. J ClinHypertens (Greenwich). 2023 Mar;25(3):266-274. doi: 10.1111/jch.14637.

Thelin A, Holmberg S. Type 2 diabetes among farmers and rural and urban referents: cumulative incidence over 20 years and risk factors in a prospective cohort study. Asia Pac J ClinNutr. 2014;23(2):301-8. doi: 10.6133/apjcn.2014.23.2.09.

Amanat S, Ghahri S, Dianatinasab A, Fararouei M, Dianatinasab M. Exercise and Type 2 Diabetes. AdvExp Med Biol. 2020; 1228:91-105. doi: 10.1007/978-981-15-1792-1_6.

Weng X, Liu Y, Ma J, Wang W, Yang G, Caballero B. An urban-rural comparison of the prevalence of the metabolic syndrome in Eastern China. Public Health Nutr. 2007 Feb;10(2):131-6. doi: 10.1017/S1368980007226023.

de Groot R, van den Hurk K, Schoonmade LJ, de Kort WLAM, Brug J, Lakerveld J. Urban-rural differences in the association between blood lipids and characteristics of the built environment: a systematic review and meta-analysis. BMJ Glob Health. 2019 Jan 24;4(1):e001017. doi: 10.1136/bmjgh-2018-001017.

Okobi OE, Ajayi OO, Okobi TJ, Anaya IC, Fasehun OO, et al. Diala CS,The Burden of Obesity in the Rural Adult Population of America. Cureus. 2021 Jun 20;13(6):e15770. doi: 10.7759/cureus.15770.

vanGuldener C, Stehouwer CD. Diabetes mellitus and hyperhomocysteinemia. SeminVasc Med. 2002 Feb;2(1):87-95. doi: 10.1055/s-2002-23099. PMID: 16222599.

Platt DE, Hariri E, Salameh P, Merhi M, Sabbah N, Helou M, Mouzaya F, Nemer R, Al-Sarraj Y, El-Shanti H, Abchee AB, Zalloua PA. Type II diabetes mellitus and hyperhomocysteinemia: a complex interaction. DiabetolMetabSyndr. 2017 Mar 21; 9:19. doi: 10.1186/s13098-017-0218-0.

Boettcher C, Tittel SR, Meissner T, et al Sex differences over time for glycemic control, pump use and insulin dose in patients aged 10–40 years with type 1 diabetes: a diabetes registry study BMJ Open Diabetes Research and Care 2021;9:e002494. doi: 10.1136/bmjdrc-2021-002494

Adeniyi AF, Fasanmade AA, Aiyegbusi OS, Uloko AE. Physical activity levels of type 2 diabetes patients seen at the outpatient diabetes clinics of two tertiary health institutions in Nigeria. Nig Q J Hosp Med. 2010 Oct-Dec;20(4):165-70.

Jamal Shahwan M, Hassan NAG, Shaheen RA. Assessment of kidney function and associated risk factors among type 2 diabetic patients. Diabetes MetabSyndr. 2019 Jul-Aug;13(4):2661-2665. doi: 10.1016/j.dsx.2019.07.025. Epub 2019 Jul 11. PMID: 31405691.

Majumder M, Mollah FH, Hoque M, Ferdous SA. Serum Homocysteine and its Association with Glycemic Control in Type 2 Diabetic Patients. Mymensingh Med J. 2017 Oct;26(4):921-926.

Florez JC, Udler MS, Hanson RL. Genetics of Type 2 Diabetes. In: Cowie CC, Casagrande SS, Menke A, Cissell MA, Eberhardt MS, Meigs JB, Gregg EW, Knowler WC, Barrett-Connor E, Becker DJ, Brancati FL, Boyko EJ, Herman WH, Howard BV, Narayan KMV, Rewers M, Fradkin JE, editors. Diabetes in America. 3rd ed. Bethesda (MD): National Institute of Diabetes and Digestive and Kidney Diseases (US); 2018. Chapter 14. PMID: 33651556.

Yu AS, Pak KJ, Zhou H, Shaw SF, Shi J, Broder BI, Sim JJ. All-Cause and Cardiovascular-Related Mortality in CKD Patients with and Without Heart Failure: A Population-Based Cohort Study in Kaiser Permanente Southern California. Kidney Med. 2023 Mar 9;5(5):100624. doi: 10.1016/j.xkme.2023.100624.

Premaratne E, Verma S, Ekinci EI, Theverkalam G, Jerums G, MacIsaac RJ. The impact of hyperfiltration on the diabetic kidney. Diabetes Metab. 2015 Feb;41(1):5-17. doi: 10.1016/j.diabet.2014.10.003.

Uduagbamen PK, Ogunkoya JO, AdebolaYusuf AO, Oyelese AT. Nwogbe CI. Ofoh, C, Anyaele C. Hyperuricemia in Hypertension and Chronic Kidney Disease: Risk Factors, Prevalence and Clinical Correlates: A Descriptive Comparative Study. Intl J Clin Med, 2021; 12: 386-401.

Ikem RT, Enikuomehin AC, Soyoye DO, Kolawole BA. The burden of diabetic complications in subjects with type 2 diabetes attending the diabetes clinic of the ObafemiAwolowo University Teaching Hospital, Ile-Ife, Nigeria - a cross-sectional study. Pan Afr Med J. 2022, ;43:148. doi: 10.11604/pamj.2022.43.148.36586. PMID: 36785682; PMCID: PMC9922079

Henning RJ. Obesity and obesity-induced inflammatory disease contribute to atherosclerosis: a review of the pathophysiology and treatment of obesity. Am J Cardiovasc Dis. 2021 Aug 15;11(4):504-529.

Jiang Y, Pang T, Shi R, Qian WL, Yan WF, Li Y, Yang ZG. Effect of Smoking on Coronary Artery Plaques in Type 2 Diabetes Mellitus: Evaluation with Coronary Computed Tomography Angiography. Front Endocrinol (Lausanne). 2021 Nov 3; 12:750773. doi: 10.3389/fendo.2021.750773.

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Published

2024-10-05

How to Cite

Ala, O., Uduagbamen, P., Yusuf, A. O., Bamikefa, T. A., Odeyemi, A. O., Adedire, A. A., … Kolawole, B. (2024). Occupational Predictors of Metabolic Profiles in Type 2 Diabetes. A Cross-Sectional Study in Nigeria. The Nigerian Health Journal, 24(3), 1486 – 1495. https://doi.org/10.60787/tnhj.v24i3.855

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