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

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

Ika Nur Pratiwi orcid scopus publons  -  Fundamental of Nursing Department, Faculty of Nursing, Universitas Airlangga, Indonesia
*Ika Yuni Widyawati orcid  -  Medical-Surgical Nursing Department, Faculty of Nursing, Universitas Airlangga, Indonesia
Nursalam Nursalam orcid  -  Advanced Nursing Department, Faculty of Nursing, Universitas Airlangga, Indonesia
Zulfayandi Pawanis orcid  -  Airlangga University Hospital, Universitas Airlangga, Indonesia
Arina Qonaah  -  Advanced Nursing Department, Faculty of Nursing, Universitas Airlangga, Indonesia
Bih-O Lee orcid  -  College of Nursing, Kaohsiung Medical University, 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 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 was employed in the analysis to determine risk factors associated with prediabetes.

Results: There were 126 participants recruited, with 69 (54.8%) having prediabetes based on IFG levels. Age (p=0.035), regular 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, such as regular IFG testing, to identify young adults with these risk factors for prediabetes screening.
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Keywords: Age; diabetes; health risk; prevalence; young adult
Funding: Universitas Airlangga (No. 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), e52857. https://doi.org/10.1371/journal.pone.0052857
  2. AlSaleh, E., Alnaser, M., Alsalman, A., ALRamdhan, A., Alsalman, H., Alhamrani, O., Alhamrani, A., AlSaleh, M., AlEithan, T., AlArfaj, K., Al Sunayhir, H., & AlSaleh, M. (2021). A community-based prediabetes knowledge assessment among Saudi adults in Al-Ahsa region, 2018. Journal of Public Health Research, 10(1), 2032. https://doi.org/10.4081/jphr.2021.2032
  3. Altamash, M., Arledal, S., Klinge, B., & Engström, P. E. (2013). Prediabetes and diabetes: Medical risk factors and periodontal conditions. Acta Odontologica Scandinavica, 71(6), 1625–1631. https://doi.org/10.3109/00016357.2013.788207
  4. American Diabetes Association (2018). 5. Prevention or delay of type 2 diabetes: Standards of medical care in Diabetes-2018. Diabetes Care, 41(Suppl 1), S51–S54. https://doi.org/10.2337/dc18-S005
  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. W., & Imperatore, G. (2020). Prevalence of prediabetes among adolescents and young adults in the United States, 2005-2016. JAMA Pediatrics, 174(2), e194498. https://doi.org/10.1001/jamapediatrics.2019.4498
  7. Azwar, S. (2010). Sikap manusia: Teori dan pengukurannya [Human attitude: Theory and measurement]. 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, 4851044. https://doi.org/10.1155/2022/4851044
  9. Centers for Disease Control and Prevention. (2019). Prediabetes. National diabetes prevention program. CDC. https://www.cdc.gov/Diabetes/Prevention/about-Prediabetes.Html
  10. 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 prediabetes and risk factors associated with diabetes in Tanzania and Uganda. Global Health Action, 9, 31440. https://doi.org/10.3402/gha.v9.31440
  11. 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
  12. Craig, C. L., Marshall, A. L., Sjöström, M., Bauman, A. E., Booth, M. L., Ainsworth, B. E., Pratt, M., Ekelund, U., Yngve, A., Sallis, J. F., & Oja, P. (2003). International physical activity questionnaire: 12-country reliability and validity. Medicine and Science in Sports and Exercise, 35(8), 1381–1395. https://doi.org/10.1249/01.MSS.0000078924.61453.FB
  13. Dany, F., Dewi, R. M., Tjandrarini, D. H., Pradono, J., Delima, D., Sariadji, K., Handayani, S., & Kusumawardani, N. (2020). 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, 1509. https://doi.org/10.1186/s12889-020-09592-7
  14. DeMers, D., & Wachs, D. (2021). Physiology, mean arterial pressure [Updated 2021, 21 April. StatPearls Publishing. https://www.ncbi.nlm.nih.gov/Books/NBK538226/
  15. 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, 5. https://doi.org/10.1186/s12875-014-0216-3
  16. Division of Nutrition, Physical Activity, and Obesity. (2021). Obesity and weight status. CDC. https://www.cdc.gov/nccdphp/dnpao/data-trends-maps/help/npao_dtm/definitions.html
  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), e341. 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. El Meouchy, P., Wahoud, M., Allam, S., Chedid, R., Karam, W., & Karam, S. (2022). Hypertension related to obesity: Pathogenesis, characteristics and factors for control. International Journal of Molecular Sciences, 23(20), 1230. https://doi.org/10.3390/ijms232012305
  20. 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
  21. Fajriyah, N., Sudiana, I. K., & Wahyuni, E. D. (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
  22. 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
  23. 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), 1906. https://doi.org/10.3390/ijerph15091906
  24. 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(G), 94–99 . https://doi.org/10.3889/oamjms.2021.6743
  25. Hosmer, D. W., & Lemeshow, S. (2013). Applied logistic regression (Second edition). John Wiley & Son. https://doi.org/10.1002/0471722146
  26. Hyder, K. M., Mohan, J., Varma, V., Ponnusankar, S., & Raja, D. (2021). Impact of prediabetes education program on knowledge, attitude and practice among prediabetic population of south India. Preventive Medicine Reports, 23, 10139. https://doi.org/10.1016/j.pmedr.2021.101395
  27. 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), 2575-257. https://doi.org/10.5958/0976-5506.2019.02255.1
  28. Irenewati, S., Arkhaesi, N., & Wistiani. (2020). Association of BMI measurements to waist circumference and waist-to-height ratio in overweight and obese children. Paediatrica Indonesiana, 6(1), 131–136. https://doi.org/10.14238/pi60.3.2020.131-6
  29. 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, e000741. https://doi.org/10.1136/bmjdrc-2019-000741
  30. Joel, S. E., Galantino, M. L., 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
  31. 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), 1597–161. https://doi.org/10.1007/s13300-024-01602-w
  32. Kim, K. A., & Shim, J. L. (2019). Factors influencing prediabetes in middle-aged women based on the KNHANE. Korean Journal of Adult Nursing, 31(6), 62. https://doi.org/10.7475/kjan.2019.31.6.628
  33. Kusumaningrum, N. S. D., Hidayati, W., & Muin, M. (2020). Prediabetes and the contributing factors: A study in Semarang, Central Java. Jurnal Keperawatan Soedirman, 15(2), 39–48. http://doi.org/10.20884/1.jks.2020.15.2.846
  34. Kyrou, I., Tsigos, C., Mavrogianni, C., Cardon, G., Van Stappen, V., Latomme, J., Kivelä, J., Wikström, K., Tsochev, K., Nanasi, A., Semanova, C., Mateo-Gallego, R., Lamiquiz-Moneo, I., Dafoulas, G., Timpel, P., Schwarz, P. E. H., Iotova, V., Tankova, T., Makrilakis, K., & Manios, Y. (2020). Sociodemographic and lifestyle-related risk factors for identifying vulnerable groups for type 2 diabetes: A narrative review with emphasis on data from Europe. BMC Endocrine Disorders, 20, 134. https://doi.org/10.1186/s12902-019-0463-3
  35. Lee, P. H., Macfarlane, D. J., Lam, T. H., & Stewart, S. M. (2011). Validity of the International Physical Activity Questionnaire Short Form (IPAQ-SF): A systematic review. The International Journal of Behavioral Nutrition and Physical Activity, 8, 115. https://doi.org/10.1186/1479-5868-8-115
  36. 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
  37. 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
  38. Medina, N. (2019). News on the calibration of non-automatic weighing instruments. The 19th International Congress of Metrology. https://doi.org/10.1051/metrology/201927002
  39. Ministry of Health Republic of Indonesia. (2018). Riset kesehatan dasar 2018 [2018 Basic health research]. Ministry of Health Republic of Indonesia
  40. 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, 6(3), 371–381. https://doi.org/10.26699/jnk.v6i3.art.p371-381
  41. Nurwanti, E., Hadi, H., Chang, J. S., Chao, J. C., Paramashanti, B. A., Gittelsohn, J., & Bai, C. H. (2019). Rural-urban differences in dietary behavior and obesity: Results of the Riskesdas study in 10-18-year-old Indonesian children and adolescents. Nutrients, 11(11), 281. https://doi.org/10.3390/nu11112813
  42. 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
  43. Pakpour, V., Molayi, F., & Nemati, H. (2024). Knowledge, attitude, and practice of prediabetic older people regarding prediabetes. BMC Geriatrics, 24, 264. https://doi.org/10.1186/s12877-024-04864-y
  44. 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
  45. Poltavskiy, E., Kim, D. J., & Bang, H. (2016). Comparison of screening scores for diabetes and prediabetes. Diabetes Research and Clinical Practice, 118, 146–153. https://doi.org/10.1016/j.diabres.2016.06.022
  46. 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, 1-16 https://doi.org/10.1177/23779608241245196
  47. 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), JDN013. https://www.diabetesonthenet.com/resources/details/healthy-eating-educational-module-ramadan
  48. 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), 2703-270. https://doi.org/10.5958/0976-5506.2019.02278.2
  49. 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, 939. https://doi.org/10.1186/1471-2458-12-939
  50. 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), e0228570. https://doi.org/10.1371/journal.pone.0228570
  51. 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
  52. Shiyanbola, O. O., Ward, E. C., & Brown, C. M. (2018). Utilizing the common sense model to explore African Americans’ perception of type 2 diabetes: A qualitative study. PLoS ONE, 13(11), e0207692. https://doi.org/10.1371/journal.pone.0207692
  53. 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://doi.org/10.20473/jn.v15i2.18975
  54. 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), 916. https://doi.org/10.3390/ijerph18179160
  55. Surabaya City Health Office. (2022). Profil kesehatan tahun 2021 [Health profile in 2021]. Surabaya City Health Offic https://dinkes.jatimprov.go.id/userfile/dokumen/PROFIL%20KESEHATAN%202021%20JATIM.pdf
  56. 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), 2001144. https://doi.org/10.1080/16549716.2021.2001144
  57. 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. https://doi.org/10.20473/jn.v15i1.19184
  58. 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 prediabetes in young Mexican adults in primary health care. Family Practice, 32(2), 159–164. https://doi.org/10.1093/fampra/cmu047
  59. 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, 10354 . https://doi.org/https://doi.org/10.1016/j.ijnurstu.2020.103548
  60. Wang, X., & Cheng, Z. (2020). Cross-sectional studies: Strengths, weaknesses, and recommendation. Chest, 158(1S), S65–S71. https://doi.org/10.1016/j.chest.2020.03.012
  61. Zhao, M., Lin, H., Yuan, Y., Wang, F., Xi, Y., & Wen, L. M. (2016). Prevalence of prediabetes and its associated risk factors in rural areas of Ningbo , China. International Journal of Environmental Research and Public Health 13(8), 808. https://doi.org/10.3390/ijerph13080808
  62. 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 prediabetes in low-resource rural settings. Journal of Endocrinological Investigation, 36(1), 33–37. https://doi.org/10.3275/8304
  63. 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-blind, placebo controlled trial. Evidence-Based Complementary and Alternative Medicine: eCAM, 2019, 792373. https://doi.org/10.1155/2019/7923732
  64. Zhu, P., Lao, G., Li, H., Tan, R., Gu, J., & Ran, J. (2023). Replacing of sedentary behavior with physical activity and the risk of mortality in people with prediabetes and diabetes: a prospective cohort study. The International Journal of Behavioral Nutrition and Physical Activity, 20, 81. https://doi.org/10.1186/s12966-023-01488-0

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