Main Article Content

Abstract

Highlights:



  1. Interviews were conducted on the correlation between nutritional knowledge and BMI among students at Novena University, Ogume, Nigeria.

  2. Most of the students had adequate nutritional knowledge and a low obesity prevalence rate.


 


Abstract: 


Body mass index (BMI), which is calculated using height and weight, is a rough indicator of body fat. This study aimed to investigate whether there is a significant correlation between nutritional knowledge and BMI among students at Novena University, Ogume, Nigeria. This study was done using a cross-sectional survey. Interviews were conducted with 50 participants from the sample, whose nutritional knowledge and weight status were assessed. The results showed that the students' BMI ranged from 15 to 39, with a mean and standard deviation of 23.93±5.46 cm. There was a positive correlation between the students' nutritional knowledge and their BMI. In conclusion, the majority of Novena University students are knowledgeable about obesity, which likely accounts for their low obesity prevalence rate.

Keywords

Nutritional value anthropometry body mass index Nigeria

Article Details

How to Cite
Andrew, U. O., Godswill, O. O., Mamerhi, E. T., & Boma, D. (2023). Nutritional Knowledge and Body Mass Index among Students at Novena University, Ogume, Nigeria. Folia Medica Indonesiana, 59(1), 14–19. https://doi.org/10.20473/fmi.v59i1.39977

References

  1. Chen YT, Ahmad SR, Soo Quee DK (2018). Dietary habits and lifestyle practices among University Students in Universiti Brunei Darussalam. Malaysian Journal of Medical Sciences 25, 56–66. doi: 10.21315/mjms2018.25.3.6.
  2. De Craemer M, Van Stappen V, Brondeel R, et al (2022). Self-reported lifestyle behaviours in families with an increased risk for type 2 diabetes across six European countries: a cross-sectional analysis from the Feel 4Diabetes-study. BMC Endocrine Disorders 22, 213. doi: 10.1186/s12902-022-01115-2.
  3. Hammond LD, Farrington AP, Sivan M (2022). Verification of the integrative model of adjustment to chronic conditions by mapping it onto the World Health Organization's international classification of function, disability and health. Rehabillitation Process and Outcome 11, 117957272211268. doi: 10.1177/11795727221126891.
  4. Hruby A, Hu FB (2015). The epidemiology of obesity: A big picture. Pharmacoeconomics 33, 673–89. doi: 10.1007/s40273-014-0243-x.
  5. Ilori T, Sanusi R (2022). Nutrition-related knowledge, practice, and weight status of patients with chronic diseases attending a district hospital in Nigeria. Journal of Family Medicine and Primary Care 11, 1428. doi: 10.4103/jfmpc.jfmpc_607_21.
  6. Kearns K, Dee A, Fitzgerald AP, et al (2014). Chronic disease burden associated with overweight and obesity in Ireland: the effects of a small BMI reduction at population level. BMC Public Health 14, 143. doi: 10.1186/1471-2458-14-143.
  7. Lysandra AZ, Wairooy NAP, Ifadha RT, et al. (2022). Risk factor of dietary habit with cholelithiasis. Journal of Community Medicine and Public Health Res 3, 1–11. doi: 10.20473/jcmphr.v3i1.27931.
  8. Munir M, Sutjahjo A, Sustini F (2016). Profile of type II diabetes mellitus with central obesity in Dr. Soetomo Hospital. Folia Medica Indonesiana 51, 177. doi: 10.20473/fmi.v51i3.2831.
  9. Nugroho AS, Martini S (2020). The correlation between obesity and hypertension in young adults in Central Java, Indonesia. EurAsian Journal of Biosciences 14, 1645–50.
  10. Pereira DA, Costa NM da SC, Sousa ALL, et al (2012). The effect of educational intervention on the disease knowledge of diabetes mellitus patients. Revista Latino- Americana de Enfermagem 20, 478–85. doi: 10.1590/S0104-11692012000300008.
  11. Peterson CM, Thomas DM, Blackburn GL, et al. (2016). Universal equation for estimating ideal body weight and body weight at any BMI. The American Journal of Clinical Nutrition 103, 1197–203. doi: 10.3945/ajcn.115.121178.
  12. Putri ESM, Soelistijo SA, Budiarto M (2022). Risk factors of coronary heart disease in patients with type 2 diabetes mellitus. Majalah Biomorfologi 32, 13. doi: 10.20473/mbiom.v32i1.2022.13-17.
  13. Roemling C, Qaim M (2012). Obesity trends and determinants in Indonesia. Appetite 58, 1005–13. doi: 10.1016/j.appet.2012.02.053.
  14. Shimokawa S (2013). When does dietary knowledge matter to obesity and overweight prevention? Food Policy 38, 35–46. doi: 10.1016/j.foodpol.2012.09.001.
  15. Sila S, Ilić A, Mišigoj-Duraković M, et al (2019). Obesity in adolescents who skip breakfast is not associated with physical activity. Nutrients 11, 2511. doi: 10.3390/nu11102511.
  16. Teixeira J de F, Goulart MR, Busnello FM, et al (2016). Hypertensives' knowledge about high-sodium foods and their behavior. Arquivos Brasileiros Cardiologia. doi: 10.5935/abc.20160049.
  17. van den Berg VL, Okeyo AP, Dannhauser A, et al. (2012). Body weight, eating practices and nutritional knowledge amongst university nursing students, Eastern Cape, South Africa. African Journal of Primary Health Care & Family Medicine. doi: 10.4102/phcfm.v4i1.323.
  18. Valmórbida JL, Goulart MR, Busnello FM, et al. (2017). Nutritional knowledge and body mass index: A cross- sectional study. Revista da Associacao Medica Brasileira 63, 736–40. doi: 10.1590/1806-9282.63.09.736.
  19. Widjaja NA, Irawan R, Hanindita MH, et al. (2019). Anthropometric measurements and inflammatory biomarkers in obese adolescents. Carpathian Journal of Food Science and Technology 87–93. doi: 10.34302/crpjfst/2019.11.5.13.
  20. World Health Organization (2022). Noncommunicable diseases. WHO.
  21. Zhou L, Zeng Q, Jin S, et al. (2017). The impact of changes in dietary knowledge on adult overweight and obesity in China ed. Zhang H. PLoS One 12, e0179551. doi: 10.1371/journal.pone.0179551.