| Peer-Reviewed

Key Factors on the Spotlight as Predictors of Dietary Adherence Among Patients Living with Type 2 Diabetes

Received: 12 July 2016    Accepted: 30 July 2016    Published: 5 September 2016
Views:       Downloads:
Abstract

There is a rise in prevalence of Type 2 diabetes in Kenya, and an increase in related complications, which lead to disability and death. Diet modification oriented for this group of patients includes recommendations to control blood sugar, lipid levels and pressure which are vital in lowering risk and complications development in the management of Type 2 diabetes. Studies indicate that adherence to diet therapy is weak in the midst of diet recommendations and patients’ education. There seems to be limited literature in developing countries as to the most critical factors in the prediction mix of adherence. This article attempts to display the competitiveness between socio-demographic and patient education related factors in the context of adherence. Across sectional analysis of a sample of 240 eligible diabetics was used and their dietary behaviour evaluated using a pre-tested dietary habit assessment survey tool with socio-demographic and patient-focus education factors. Linear regression preceded by principle axis factoring to categories adherences was executed. The results indicated that diet characterized by control of lipid levels was influenced by diet accessible within distance from home (β=0.211, t=2.053, ρ=0.041), while diet to control blood sugar and pressure was influenced by diet accessible from the workplace (β=0.193, t=2.027, ρ=0.044), occupation status (β=0.162, t=2.051, ρ=0.042), age (β=0.178, t=2.238, ρ=0.026), marital status (β=0.208, t=2.731, ρ=0.007) and diet found in the locality or surrounding environment (β=0.277, t=3.034, ρ=0.003). In conclusion, adherence enhancement seems to draw reference to education sessions focused on challenges faced by the unmarried, age specifics, occupation, setting specifics.

Published in European Journal of Preventive Medicine (Volume 4, Issue 5)
DOI 10.11648/j.ejpm.20160405.11
Page(s) 106-112
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

Keywords

Type 2 Diabetes, Diet Adherence, Socio-Economic Factors, Patient Factors

References
[1] ADA. (2013). Standards of Medical Care in Diabetes Management. Diabetes Care, 511-566.
[2] Adewale, B. G., Langalibalele, H. M., Malete, H. N., Govendar, I., & Ogunbanjo, A. G. (2013). Non-Adherence to Diet and Excercise Regime Amongst Patients with Type 2 Diabtes Mellitus Attending Extension II Clinic in Botswana. Care Farm Medicine, 1-6.
[3] Ayieko, W. (2011). Prevalence of Lifestlye Risk Factors Among Diabetic Patients at Kenyatta National Hospital. Nairobi: Nairobi University.
[4] Bantle, J. P., Rossett, J. W., Albright, A. L., Apovian, C. M., Clark, N. G., Franz, M. J., Wheeler, M. L. (2008). Nutrition Recommendations and Interventions for Diabetes: A Position Statement of the American Diabetes Association. Diabetes Care, 61-78.
[5] Boyle, J. P., Theodore, T. J., Gregg, E. W., Barker, L. E., & Williamson, D. F. (2010). Projection of the year 2050 Burden of Diabetes in the US Adult Poppulation: Dynamic Modeling of Incidence, Mortaltiy and Prediabetes Prevalence. Population Health Metrics, 8(29).
[6] Broadbent, E., Donkin, L., & Stroh, J. C. (2011). Illness and Treatment with Adherence to Medications, Diet and Excercise in Diabetic Patients. Diabetes Care, 34, 338-340.
[7] Chorzempa, A. (2006). Type 2 Diabetes Mellitus and It's effects on Vascular Disease. Journal of Cardiovascular Medicine, 21(6), 485-492.
[8] Ciechanowski, P. S., Katon, W. S., Russo, S. E., & Hirsh, I. B. (2003). The Relationship of Depression Symptoms to Symptoms Reporting, Self-Care and Glucose Control in Diabetes. General Hospital Psychiatry, 246-252.
[9] Copell, K. J., Kataoka, M., Williams, S. M., Chrisholm, A. W., Vorgers, M. S., & Mann, J. L. (2010, May 19). Nutrition Intervention in Patients with Type 2 Diabetes Who are Hyperglycaemic Despite Optimised Drug Treatment-Lifestyle Over and Above Drugs (LOADD) Study: Randomised Control Trial. Otago, Dunedin, New Zealand.
[10] Cornier, M.-A., Dabelea, D., Hernandez, T. L., Lindstrom, R. C., Steig, A. J., & Stob, N. R. (2008). The Metabolic Syndrome. Endocrine Review, 29(7), 777-822.
[11] Dibari, F., Bahwere, P., Gall, L., Guerro, S., Mwaniki, D., & Seal, A. (2012). A Qualitative investigation of Adherence to Nutritional Therapy in Malnourished AIDS patients in Kenya. Public Health Nutrition, 316-323.
[12] Dropkin, B. M. (2010). An approaching epidemic: Exploring Diabetes Awareness and Care in Mombasa, Kenya. Unpublished paper, School for international training, Kenya.
[13] Freita, R. W., Araujo, M. F., Marinho, N. B., Damasceno, M. M., Caetan, J. A., & Galvao, M. T. (2011). Factors Related To Nursing Diagnosis, Ineffective Self Health Management Among Diabetics . Acta Paul Enferm, 365-372.
[14] Gorsuch, R. L. (1983). Factor Analysis (2nd ed.). Hillsdale: Lawrence Erbaum Associates.
[15] Gregg, E. W., Gu, Q., Williams, D., de Rekeneire, N., Cheng, Y. J., Geiss, L., & Engelgau, M. (2007). Prevalence of Lower Extremity Associated with Normal Glucose Levels, Impaired Fasting Glucose and Diabetes among US Adults aged 40 or Older. Diabetes Resolution Clinic, 458-488.
[16] Gutschall, M. D., Miller, C. K., Mitchell, D. C., & Lawrence, F. (2009). A Randomised Behavioural Trial Targetting Glycaemic Index Improves Dietary Weight and Metabolic Outcomes in Patients with Type 2 Diabetes. Public Health Nutrition, 1-9.
[17] Gutschall, M., Onega, L. L., & Wright, W. K. (2011). Patients' Percpectives about Dietary Maintenance in Type 2 Diabetes. Tropical Clinical Nutrtion, 180-189.
[18] Hodge, A. M., English, D. R., O'dea, K., & Giles, G. G. (2004). Glycemic Index and Diet Fibre and the Risk of Type 2 diabetes. Diabetes Care, 2701-2706.
[19] IFPRI. (2016). Global Nutrition Report 2016: From Promise to Impact. Ending Malnutrition by 2030. Washington DC: International Food Policy Research Institute.
[20] Kalyango, J., Owino, E., & Nambuya, A. (2008). Non-Adherence to Diabetes Treatment at Mualgo Hospitals in Uganda: Prevalence and Associated Factors. African Health Services, 67-73.
[21] Kayima, J. K. (2002). The Changing Spectrum of Type 2 Diabetes Mellitus. East African Medical Journal, 397-399.
[22] Kessler, R. C. (2003). Epidemiology of Women Depression. Journal of Affected Disorders, 5-13.
[23] Khan, A. R., Al-Abdul, L. Z., Al Aithan, M. A., Bu-Khamseen, M. A., Al Ibrahim, I., & Khan, S. A. (2012). Factors Contributing to a Non Compliance Among Diabetics Attending Primary Health Centres in the Al Hasa District of Saudi Arabia. Journal of Family and Community Medicine, 26-32.
[24] Mario, A., & Sridavi, A. (2008). Diabetes in Sub Saharan Africa: Kenya, Mali, Mozambique, Nigeria, South Africa and Zambia. International Journal of Diabetes in Developing Countries, 101-108.
[25] Mayberry, L. S., & Osborn, C. Y. (2012). Family Support, Medical Adherence and Glycemic Control Among Adults with Type 2 Diabetes. Diabetes Care, 1239-1245.
[26] McFerran, L. (2008). Obstacles to Diabetes Care in Kenya. Medical Journal of Therapeutics Africa, 2(2), 127-129.
[27] Miller, C. K., Edwards, L., Kissling, G., & Sanville, L. (2002). Evaluation of a Theory- Based Nutrtion Intervention for Older Adults with Diabetes Mellitus. Journal of America Medical Association, 1069-1074, 1079-1081.
[28] Musee, C. N., Okeyo, D. O., & Odiwuor, W. H. (2016). Dietary Adherence Pattern in The Context of Type 2 Diabetic Management within Clinical Setting, Kenya. International Journal of Diabetes Research, 26-34.
[29] National Diabetes Control Programme. (2010, July). Kenya National Diabetes Strategy 2010-2015. Nairobi, Nairobi, Kenya: Ministry of Public Health and Sanitation.
[30] Peyrot, M., Rubin, R. R., Lauritzen, T., Snoek, F. J., Mathews, D. R., & Skovland, S. E. (2005). Psychological Barriers to Improve Diabetes Management: Results of the Cross- National Diabetes Attitudes, Wishes and Needs (DAWN) Study. Diabetic Medication, 1379-1385.
[31] PPOA. (2010). New Nyanza Provincial General Hospital Procurement Review. Nairobi: Public Procurement Oversight Authority.
[32] Roglic, G., & Unwin, N. (2010). Mortality Attributable to Diabetes: Estimates for the Year 2010. Diabetes Resolution Clinic Practice, 87(1), 15-19.
[33] Sabate, E. (2003). Adherence to Long Term Therapies: Evidence for Action. Geneva: World Health Organisation.
[34] Steyn, N. P., Lambert, E. V., & Tabana, H. (2009). Nutrition Interventions for the Prevention of Type 2 Diabetes. Conference on 'Multidiscplinary Approaches to Nutritional Problems' Symposium on “Diabetes and Health” (pp. 55-70). Cape Town: Nutrition Society.
[35] Silva, L., Ribeiro, P., & Cardoso, H. (2006). Diabetes Mellitus Treatment Adherence; The Relevance of Demographic and Clinical Characterisitics. Science Medicine, 33-41.
[36] Tabachnick, B. G., & Fidell, L. S. (1996). Using Multivariate Statisitics (3rd ed.). New York: Harper Collins.
[37] Turcatto, H., Faria, G., Fernanda, F., Rodriguez, L., Zanetti, M. L., Flavio, M., . . . Damasceno, C. (2013). Factors Associated with Adherence to Treatment of Patients with Diabetes Mellitus. Acta Paul Enferm, 231-237.
[38] Yamane, T. (1967). Statistics: An Introductory Analysis. New York: Harper and Row.
[39] Yang, Y., Thumula, V., Pace, P. F., Banahan, B. F., Wilken, N. E., & Lobb, W. B. (2009). Predictors of Medicine Non-Adherence Among Patients with Diabetes in Medicare Part D Program; A Retrospective Cohort Study. Clinical Therapy, 2178-2188.
[40] Zepeda, E., Leigh, F., Ndirangu, L., Omollo, J., & Wainaina, S. (2013). Discussion Paper: Kenya's Youth Employment Challenge. New York: UNDP.
[41] Zhu, V. S., Tu, W., Marrero, D. J., Rosenman, M. B., & Overhage, J. M. (2011). Race and Medication Adherence and Glycemic Control; Findings from an Operational Health Information Exchange. AMIA Annual Syposium, 1649-57.
Cite This Article
  • APA Style

    Nekesa Carolyne Musee, David Omondi Okeyo, Wycliffe Odiwuor. (2016). Key Factors on the Spotlight as Predictors of Dietary Adherence Among Patients Living with Type 2 Diabetes. European Journal of Preventive Medicine, 4(5), 106-112. https://doi.org/10.11648/j.ejpm.20160405.11

    Copy | Download

    ACS Style

    Nekesa Carolyne Musee; David Omondi Okeyo; Wycliffe Odiwuor. Key Factors on the Spotlight as Predictors of Dietary Adherence Among Patients Living with Type 2 Diabetes. Eur. J. Prev. Med. 2016, 4(5), 106-112. doi: 10.11648/j.ejpm.20160405.11

    Copy | Download

    AMA Style

    Nekesa Carolyne Musee, David Omondi Okeyo, Wycliffe Odiwuor. Key Factors on the Spotlight as Predictors of Dietary Adherence Among Patients Living with Type 2 Diabetes. Eur J Prev Med. 2016;4(5):106-112. doi: 10.11648/j.ejpm.20160405.11

    Copy | Download

  • @article{10.11648/j.ejpm.20160405.11,
      author = {Nekesa Carolyne Musee and David Omondi Okeyo and Wycliffe Odiwuor},
      title = {Key Factors on the Spotlight as Predictors of Dietary Adherence Among Patients Living with Type 2 Diabetes},
      journal = {European Journal of Preventive Medicine},
      volume = {4},
      number = {5},
      pages = {106-112},
      doi = {10.11648/j.ejpm.20160405.11},
      url = {https://doi.org/10.11648/j.ejpm.20160405.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ejpm.20160405.11},
      abstract = {There is a rise in prevalence of Type 2 diabetes in Kenya, and an increase in related complications, which lead to disability and death. Diet modification oriented for this group of patients includes recommendations to control blood sugar, lipid levels and pressure which are vital in lowering risk and complications development in the management of Type 2 diabetes. Studies indicate that adherence to diet therapy is weak in the midst of diet recommendations and patients’ education. There seems to be limited literature in developing countries as to the most critical factors in the prediction mix of adherence. This article attempts to display the competitiveness between socio-demographic and patient education related factors in the context of adherence. Across sectional analysis of a sample of 240 eligible diabetics was used and their dietary behaviour evaluated using a pre-tested dietary habit assessment survey tool with socio-demographic and patient-focus education factors. Linear regression preceded by principle axis factoring to categories adherences was executed. The results indicated that diet characterized by control of lipid levels was influenced by diet accessible within distance from home (β=0.211, t=2.053, ρ=0.041), while diet to control blood sugar and pressure was influenced by diet accessible from the workplace (β=0.193, t=2.027, ρ=0.044), occupation status (β=0.162, t=2.051, ρ=0.042), age (β=0.178, t=2.238, ρ=0.026), marital status (β=0.208, t=2.731, ρ=0.007) and diet found in the locality or surrounding environment (β=0.277, t=3.034, ρ=0.003). In conclusion, adherence enhancement seems to draw reference to education sessions focused on challenges faced by the unmarried, age specifics, occupation, setting specifics.},
     year = {2016}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - Key Factors on the Spotlight as Predictors of Dietary Adherence Among Patients Living with Type 2 Diabetes
    AU  - Nekesa Carolyne Musee
    AU  - David Omondi Okeyo
    AU  - Wycliffe Odiwuor
    Y1  - 2016/09/05
    PY  - 2016
    N1  - https://doi.org/10.11648/j.ejpm.20160405.11
    DO  - 10.11648/j.ejpm.20160405.11
    T2  - European Journal of Preventive Medicine
    JF  - European Journal of Preventive Medicine
    JO  - European Journal of Preventive Medicine
    SP  - 106
    EP  - 112
    PB  - Science Publishing Group
    SN  - 2330-8230
    UR  - https://doi.org/10.11648/j.ejpm.20160405.11
    AB  - There is a rise in prevalence of Type 2 diabetes in Kenya, and an increase in related complications, which lead to disability and death. Diet modification oriented for this group of patients includes recommendations to control blood sugar, lipid levels and pressure which are vital in lowering risk and complications development in the management of Type 2 diabetes. Studies indicate that adherence to diet therapy is weak in the midst of diet recommendations and patients’ education. There seems to be limited literature in developing countries as to the most critical factors in the prediction mix of adherence. This article attempts to display the competitiveness between socio-demographic and patient education related factors in the context of adherence. Across sectional analysis of a sample of 240 eligible diabetics was used and their dietary behaviour evaluated using a pre-tested dietary habit assessment survey tool with socio-demographic and patient-focus education factors. Linear regression preceded by principle axis factoring to categories adherences was executed. The results indicated that diet characterized by control of lipid levels was influenced by diet accessible within distance from home (β=0.211, t=2.053, ρ=0.041), while diet to control blood sugar and pressure was influenced by diet accessible from the workplace (β=0.193, t=2.027, ρ=0.044), occupation status (β=0.162, t=2.051, ρ=0.042), age (β=0.178, t=2.238, ρ=0.026), marital status (β=0.208, t=2.731, ρ=0.007) and diet found in the locality or surrounding environment (β=0.277, t=3.034, ρ=0.003). In conclusion, adherence enhancement seems to draw reference to education sessions focused on challenges faced by the unmarried, age specifics, occupation, setting specifics.
    VL  - 4
    IS  - 5
    ER  - 

    Copy | Download

Author Information
  • Department of Nutrition and Health, Maseno University, Kisumu, Kenya

  • Department of Nutrition and Health, Maseno University, Kisumu, Kenya

  • Department of Education Psychology, Maseno University, Kisumu, Kenya

  • Sections