DOI: https://doi.org/10.14710/nmjn.v14i2.56904

Predictors of Prediabetes Among Young Adults in East Java, Indonesia: A Cross-sectional Study

Ika Nur Pratiwi orcid scopus publons  -  Faculty of Nursing, Universitas Airlangga, Surabaya, Indonesia, Indonesia
*Ika Yuni Widyawati orcid  -  Research Group in Medical-Surgical Nursing, Faculty of Nursing, Universitas Airlangga, Surabaya, Indonesia, Indonesia
Nursalam Nursalam orcid  -  Advanced Nursing Department, Faculty of Nursing, Universitas Airlangga, Surabaya, Indonesia, Indonesia
Zulfayandi Pawanis orcid  -  Airlangga University Hospital, Universitas Airlangga, Surabaya , Indonesia
Arina Qonaah  -  Advanced Nursing Department, Faculty of Nursing, Universitas Airlangga, Surabaya, Indonesia, Indonesia
Bih O Lee orcid  -  College of Nursing, Kaohsiung Medical University, Kaohsiung, Taiwan, Taiwan
Open Access Copyright (c) 2024 by the Authors, Published by Department of Nursing, Faculty of Medicine, Universitas Diponegoro
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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Abstract

Background: Prediabetes is a condition that can be controlled and managed to prevent the occurrence of type-2 diabetes mellitus (T2DM). This condition can occur at all ages, especially in young adults. However, little is known about what factors increase the risk of prediabetes in young adults in East Java, Indonesia.

Purpose: This study aimed to estimate the prevalence and the influential risk factors of prediabetes among young adults in East Java, Indonesia.

Methods: This study used a cross-sectional design. The purposive sampling technique was used to recruit young adults in Surabaya, East Java Province, Indonesia. International physical activity questionnaire short-form version questionnaire (IPAQ-SF) and physical indicators for anthropometry were used to obtain data on sociodemographic characteristics, prediabetes knowledge, and physical activity. In addition, Blood pressure, impaired fasting glucose (IFG), and body mass index (BMI) were measured. Multivariable logistic regression analysis was performed to determine risk factors associated with prediabetes

Results: There were 126 participants recruited with 69 (54.8%) had prediabetes based on impaired fasting glucose (IFG) levels. Age (p=0.035), routine exercise (p=0.015), activity level (p=0.026), body weight (p=<0.001), waist circumference (p=0.002), BMI (p=<0.001) and obesity (p=<0.001) were significant factors associated with prediabetes.

Conclusion: The high prevalence of prediabetes in young adults is associated with age, routine exercise, activity level, body weight, waist circumference), BMI and obesity. It is crucial to implement strategies, for example through regular IFG testing to identify young adults with these risk factors for prediabetes screening.

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Keywords: Diabetes; Health Risk; Prevalence; Young Adult; Age
Funding: Universitas Airlangga under contract 797/UN3.1.13/PT/2023

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  1. Al-Maskari, F., El-Sadig, M., Al-Kaabi, J. M., Afandi, B., Nagelkerke, N., & Yeatts, K. B. (2013). Knowledge, Attitude and Practices of Diabetic Patients in the United Arab Emirates. PLoS ONE, 8(1), 1–8. https://doi.org/10.1371/journal.pone.0052857
  2. Altamash, M., Arledal, S., Klinge, B., & Engström, P. E. (2013). Pre-diabetes and diabetes: Medical risk factors and periodontal conditions. Acta Odontologica Scandinavica, 71(6), 1625–1631. https://doi.org/10.3109/00016357.2013.788207
  3. American Diabetes Association. (2018). Prevention or delay of type 2 diabetes: Standards of Medical Care in Diabetes-2018. Diabetes Care. 2018;41(Suppl 1): S51-S54.Doi: 10.2337/Dc18-S005
  4. An Effective Model of Diabetes Care and Education: Revising the AADE7 Self-Care Behaviors ®. (2020). Diabetes Educator, 46(2), 139–160. https://doi.org/10.1177/0145721719894903
  5. An, Y., Zhang, P., Wang, J., Gong, Q., Gregg, E. W., Yang, W., Li, H., Zhang, B., Shuai, Y., Chen, Y., Engelgau, M. M., Cheng, Y., Hu, Y., Bennett, P. H., & Li, G. (2015). Cardiovascular and all-cause mortality over a 23-year period among Chinese with newly diagnosed diabetes in the Da Qing IGT and diabetes study. Diabetes Care, 38(7), 1365–1371. https://doi.org/10.2337/dc14-2498
  6. Andes, L. J., Cheng, Y. J., Rolka, D. B., Gregg, E., & Imperatore, G. (2019). Prevalence of Prediabetes Among Adolescents and Young Adults in the United States, 2005-2016. JAMA Pediatr. Doi: 10.1001/Jamapediatrics.2019.4498,30341.https://doi.org/10.1001/jamapediatrics.2019.4498
  7. Azwar, S. (2010). Sikap Manusia Teori dan Pengukurannya (Human Attitude Theory and Measurement). Yogyakarta: Pustaka Pelajar
  8. Budiastutik, I., Kartasurya, M. I., Subagio, H. W., & Widjanarko, B. (2022). High Prevalence of Prediabetes and Associated Risk Factors in Urban Areas of Pontianak, Indonesia: A Cross-Sectional Study. Journal of Obesity, 2022. https://doi.org/10.1155/2022/4851044
  9. CDC. (2021). Defining Adult Overweight & Obesity. Division of Nutrition, Physical Activity, and Obesity, National Center for Chronic Disease Prevention and Health Promotion, https://www.cdc.gov/obesity/adult/defining.html
  10. Centers for Diseases Control and Prevention. (2019). Prediabetes. National Diabetes Prevention Program. Https://Www.Cdc.Gov/Diabetes/Prevention/about-Prediabetes.Html
  11. Chiwanga, F. S., Njelekela, M. A., Diamond, M. B., Bajunirwe, F., Guwatudde, D., Nankya-Mutyoba, J., Kalyesubula, R., Adebamowo, C., Ajayi, I. O., Reid, T. G., Volmink, J., Laurence, C., Adami, H. O., Holmes, M. D., & Dalal, S. (2016). Urban and rural prevalence of diabetes and pre-diabetes and risk factors associated with diabetes in Tanzania and Uganda. Global Health Action, 9(1), 1–8. https://doi.org/10.3402/gha.v9.31440
  12. Compeán, O. L. G., Trujilla, O. L. E., Valles, M. A. M., Reséndiz, G. E., García, S. B., & Pérez, B. D. A. (2018). Obesity, physical activity and prediabetes in adult children of people with diabetes. Revista Latino-Americana de Enfermagem, 25, e2981. https://doi.org/10.1590/1518-8345.2102.2981
  13. Dany, F., Dewi, R. M., Tjandrarini, D. H., Pradono, J., Delima, D., Sariadji, K., Handayani, S., & Kusumawardani, N. (2020a). Urban-rural distinction of potential determinants for prediabetes in Indonesian population aged ≥15 years: a cross-sectional analysis of Indonesian Basic Health Research 2018 among normoglycemic and prediabetic individuals. BMC Public Health, 20(1), 1509. https://doi.org/10.1186/s12889-020-09592-7
  14. Dany, F., Dewi, R. M., Tjandrarini, D. H., Pradono, J., Delima, D., Sariadji, K., Handayani, S., & Kusumawardani, N. (2020b). Urban-rural distinction of potential determinants for prediabetes in Indonesian population aged ≥15 years: A cross-sectional analysis of Indonesian Basic Health Research 2018 among normoglycemic and prediabetic individuals. BMC Public Health, 20(1), 1–9. https://doi.org/10.1186/s12889-020-09592-7
  15. DeMers, D., & Wachs, D. (2021). Physiology, Mean Arterial Pressure [Updated 2021 Apr 21]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2021 Jan-. Available from: Https://Www.Ncbi.Nlm.Nih.Gov/Books/NBK538226/
  16. Díaz-Redondo, A., Giráldez-García, C., Carrillo, L., Serrano, R., García-Soidán, F. J., Artola, S., Franch, J., Díez, J., Ezkurra, P., Millaruelo, J. M., Seguí, M., Sangrós, J., Martínez-Candela, J., Muñoz, P., Goday, A., Regidor, E., Alonso, M., Álvarez, B., Álvarez, F., … Villaró, M. (2015). Modifiable risk factors associated with prediabetes in men and women: A cross-sectional analysis of the cohort study in primary health care on the evolution of patients with prediabetes. BMC Family Practice, 16(1), 1–9. https://doi.org/10.1186/s12875-014-0216-3
  17. Dugani, S. B., Mielke, M. M., & Vella, A. (2021). Burden and management of type 2 diabetes in rural United States. Diabetes/Metabolism Research and Reviews, 37(5), e3410. https://doi.org/10.1002/dmrr.3410
  18. Eikenberg, J. D., & Davy, B. M. (2013). Prediabetes: A Prevalent and Treatable, but Often Unrecognized, Clinical Condition. Journal of the Academy of Nutrition and Dietetics, 113(2), 213–218. https://doi.org/10.1016/j.jand.2012.10.018
  19. Faizah, R., Efendi, F., & Suprajitno, S. (2020). A Systematic Review of Foot Exercises with Group Support to Improve the Foot Health of Diabetes Mellitus Patients. Jurnal Ners, 15(1Sp), 129–134. https://doi.org/10.20473/jn.v15i1sp.18996
  20. Fajriyah, N., Sudiana, I. K., & Dwi Wahyuni, E. (2020). The Effects from Physical Exercise on the Blood Glucose Levels, HbA1c and Quality of Life of Type 2 Diabetes Mellitus Patients: A Systematic Review. Jurnal Ners, 15(1Sp), 486–496. https://doi.org/10.20473/jn.v15i1sp.20517
  21. Fujiati, I. I., Damanik, H. A., Bachtiar, A., Nurdin, A. A., & Ward, P. (2017). Development and validation of prediabetes risk score for predicting prediabetes among Indonesian adults in primary care: Cross-sectional diagnostic study. Interventional Medicine and Applied Science, 9(2), 76–85. https://doi.org/10.1556/1646.9.2017.18
  22. Gillani, A. H., Islam, F. M. A., Hayat, K., Atif, N., Yang, C., Chang, J., Qu, Z., & Fang, Y. (2018). Knowledge, attitudes and practices regarding diabetes in the general population: A cross-sectional study from Pakistan. International Journal of Environmental Research and Public Health, 15(9), 1–13. https://doi.org/10.3390/ijerph15091906
  23. Hidayati, L., Pratiwi, I. N., Pawanis, Z., McKenna, L., & Widyawati, I. Y. (2021). Buerger exercise reduces the risk of neuropathy in people with diabetes mellitus. Open Access Macedonian Journal of Medical Sciences, 9, 94–99. https://doi.org/10.3889/oamjms.2021.6743
  24. Hosmer, D. W., & Lemeshow, S. (2013). Applied Logistic Regression Second Edition. http://resource.heartonline.cn/20150528/1_3kOQSTg.pdf
  25. Indarwati, R., Pratiwi, I. N., & Yuniarsih, N. (2019). Playing cards using the “tepuk nyamuk” method improves cognitive function and social interaction in the elderly. Indian Journal of Public Health Research and Development, 10(8). https://doi.org/10.5958/0976-5506.2019.02255.1
  26. Irenewati, S., Arkhaesi, N., & Wistiani. (2020). Association of BMI measurements to waist circumference and waist-to-height ratio in overweight and obese children. Paediatr Indones, 6(1), 131–136. https://doi.org/doi: http://dx.doi.org/10.14238/pi60.3.2020.131-6
  27. Jiang, J., Cai, X., Pan, Y., Du, X., Zhu, H., Yang, X., Zheng, D., Gaisano, H., Wei, T., & He, Y. (2020). Relationship of obesity to adipose tissue insulin resistance. BMJ Open Diabetes Research and Care, 8(1), 1–9. https://doi.org/10.1136/bmjdrc-2019-000741
  28. Joel, S. E., Galantino, M. Lou, Hutchinson, J., & Jeffrey, M. G. (2019). Health coaching for healthcare employees with chronic disease: A pilot study. Work, 63(1), 49–56. https://doi.org/10.3233/WOR-192907
  29. Kalra, S., Anjana, R. M., Verma, M., Pradeepa, R., Sharma, N., Deepa, M., Singh, O., Venkatesan, U., Elangovan, N., Aggarwal, S., Kakkar, R., & Mohan, V. (2024). Urban–Rural Differences in the Prevalence of Diabetes Among Adults in Haryana, India: The ICMR-INDIAB Study (ICMR-INDIAB-18). Diabetes Therapy, 15(7), 1597–1613. https://doi.org/10.1007/s13300-024-01602-w
  30. Kim, K. A., & Shim, J. L. (2019). Factors Influencing Pre-Diabetes in Middle-aged Women based on the KNHANES. Korean Journal of Adult Nursing, 31(6), 628. https://doi.org/10.7475/kjan.2019.31.6.628
  31. Kusumaningrum, N. S. D., Hidayati, W., & Muin, M. (2020). Prediabetes and the contributing factors: A study in Semarang, Central Java. Jurnal Keperawatan Soedirman (The Soedirman Journal of Nursing), 15(2), 39–48. http://www.jks.fikes.unsoed.ac.id/index.php/jks/article/view/846/504
  32. Lemeshow S., Lwanga S. K., & Organization W. H. (1997). Sample size determination in health studies : a practical manual / S. K. Lwanga and S. Lemeshow. World Health Organization. https://iris.who.int/handle/10665/40062
  33. Mainous, A. G., Tanner, R. J., Baker, R., Zayas, C. E., & Harle, C. A. (2014). Prevalence of prediabetes in England from 2003 to 2011: Population-based, cross-sectional study. BMJ Open, 4(6), 4–11. https://doi.org/10.1136/bmjopen-2014-005002
  34. Medina, N. (2019). News on the Calibration of Non-Automatic Weighing Instruments (Vol. 0, Issue 18). https://doi.org/10.1051/metrology/201927002
  35. Meriane, F. (2014). Description of Community Knowledge Aged Over 30 Years About Risk Factors for Type 2 Diabetes Mellitus From Several Areas In Surabaya City
  36. Ministry of Health Indonesia. (2018). Riset Kesehatan Dasar 2018 (Kementrian, Kesehatan, Republik, & Indonesia (Eds.))
  37. Noventi, I., Rusdianingseh, R., & Khafid, M. (2019). Prevalensi, Karakteristik dan Faktor Resiko Prediabetes di Wilayah Pesisir, Pegunungan dan Perkotaan (Prevalence, Characteristics and Risk Factors for Prediabetes in Coastal, Mountainous and Urban Areas). Jurnal Ners Dan Kebidanan (Journal of Ners and Midwifery), 6(3), 371–381. https://doi.org/10.26699/jnk.v6i3.art.p371-381
  38. Okosun, I. S., & Lyn, R. (2015). Prediabetes awareness, healthcare provider’s advice, and lifestyle changes in American adults. International Journal of Diabetes Mellitus, 3(1), 11–18. https://doi.org/10.1016/j.ijdm.2010.12.001
  39. Perng, W., Conway, R., Mayer-Davis, E., & Dabelea, D. (2023). Youth-Onset Type 2 Diabetes: The Epidemiology of an Awakening Epidemic. Diabetes Care, 46(3), 490–499. https://doi.org/10.2337/dci22-0046
  40. Pratiwi, I. N., Nursalam, N., Widyawati, I. Y., & Ramoo, V. (2024). Spousal Involvement in Collaborative Management and Glycemic Behavior Change among Patients with Diabetes Mellitus: A Systematic Review. SAGE Open Nursing, 10. https://doi.org/10.1177/23779608241245196
  41. Pratiwi, I. N., Pawanis, Z., Hidayati, L., Widyawati, I. Y., Ni’Mah, L., Sukartini, T., Bakar, A., & Mariyanti, H. (2018). The role of a healthy-eating educational module during Ramadan in a community health centre. Journal of Diabetes Nursing, 22(2). https://www.diabetesonthenet.com/resources/details/healthy-eating-educational-module-ramadan
  42. Pratiwi, I. N., Purwaningsih, & Ramahwati, S. (2019). The correlation between family support and quality of life in mothers with positive HIV in Surabaya. Indian Journal of Public Health Research and Development, 10(8). https://doi.org/10.5958/0976-5506.2019.02278.2
  43. Quang Binh, T., Tran Phuong, P., Thi Nhung, B., Dinh Thoang, D., Van Thang, P., Khanh Long, T., & Van Thanh, D. (2012). Prevalence and correlates of hyperglycemia in a rural population, Vietnam: Implications from a cross-sectional study. BMC Public Health, 12(1), 1. https://doi.org/10.1186/1471-2458-12-939
  44. Rahim, F. F., Abdulrahman, S. A., Maideen, S. F. K., & Rashid, A. (2020). Prevalence and factors associated with prediabetes and diabetes in fishing communities in Penang, Malaysia: A cross-sectional study. PLoS ONE, 15(2), 1–17. https://doi.org/10.1371/journal.pone.0228570
  45. Rodriguez-Segade, S., Rodriguez, J., Camiña, F., Sanmartín-Portas, L., Gerpe-Jamardo, J., Pazos-Couselo, M., García-López, J. M., Alonso-Sampedro, M., González-Quintela, A., & Gude, F. (2019). Prediabetes defined by HbA 1c and by fasting glucose: differences in risk factors and prevalence. Acta Diabetologica, 56(9), 1023–1030. https://doi.org/10.1007/s00592-019-01342-5
  46. Sinawang, G. W., Kusnanto, K., & Pratiwi, I. N. (2020). Systematic Review of Family Members in Improving the Quality of Life of People with T2DM. Jurnal Ners, 15(2), 107–112. http://dx.doi.org/10.20473/jn.v15i2.18975
  47. Subramaniam, S., Dhillon, J. S., & Wan Ahmad, W. F. (2021). Behavioral theory-based framework for prediabetes self-care system—design perspectives and validation results. International Journal of Environmental Research and Public Health, 18(17). https://doi.org/10.3390/ijerph18179160
  48. Surabaya City Health Office. (2022). profil kesehatan tahun 2021 (health profile in 2021). https://drive.google.com/drive/folders/1Py81H1C0aN0ezmginLoLXfHYxqjuTHZ5
  49. Tanoey, J., & Becher, H. (2021). Diabetes prevalence and risk factors of early-onset adult diabetes: results from the Indonesian family life survey. Global Health Action, 14(1). https://doi.org/10.1080/16549716.2021.2001144
  50. Thojampa, S., Sarnkhaowkhom, C., Klankhajhon, S., Puraya, A., & Sahattecho, W. (2020). Self-Efficacy of Exercise in Older Adults with Diabetes: A Concept Analysis. Jurnal Ners, 15(1), 105–112
  51. Ureña-Bogarín, E. L., Martínez-Ramírez, H. R., Torres-Sánchez, J. R., Hernández-Herrera, A., Cortés-Sanabria, L., & Cueto-Manzano, A. M. (2015). Prevalence of pre-diabetes in young Mexican adults in primary health care. Family Practice, 32(2), 159–164. https://doi.org/10.1093/fampra/cmu047
  52. van Wissen, K., & Blanchard, D. (2021). The ‘work’ of self-care for people with cardiovascular disease and prediabetes: An interpretive description. International Journal of Nursing Studies, 116, 103548. https://doi.org/https://doi.org/10.1016/j.ijnurstu.2020.103548
  53. Zhao, M., Lin, H., Yuan, Y., Wang, F., Xi, Y., & Wen, L. M. (2016). Prevalence of Pre-Diabetes and Its Associated Risk Factors in Rural Areas of Ningbo , China. International Journal of Environmental Research and Public Health 13(8):808, 1–14. https://doi.org/10.3390/ijerph13080808
  54. Zhao, X., Zhao, W., Zhang, H., Li, J., Shu, Y., Li, S., Cai, L., Zhou, J., Li, Y., & Hu, R. (2013). Fasting capillary blood glucose: An appropriate measurement in screening for diabetes and pre-diabetes in low-resource rural settings. Journal of Endocrinological Investigation, 36(1), 33–37. https://doi.org/10.3275/8304
  55. Zhu, J., Xing, G., Shen, T., Xu, G., Peng, Y., Rao, J., & Shi, R. (2019). Postprandial Glucose Levels Are Better Associated with the Risk Factors for Diabetes Compared to Fasting Glucose and Glycosylated Hemoglobin ( HbA1c ) Levels in Elderly Prediabetics : Beneficial Effects of Polyherbal Supplements — A Randomized , Double-Bl. 2019

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