Women of childbearing age are at increased risk of type 2 diabetes (T2D), possibly due to metabolic alterations during pregnancy that contributes towards insulin resistance. However, limited studies assessed T2D risk specifically in Malaysian women of childbearing age. Hence, this study was conducted to determine factors associated with T2D risk in women of childbearing age at a selected public university in Malaysia. This cross-sectional study involved 83 childbearing-age women in Universiti Putra Malaysia (mean age: 37.7 ± 5.7 years; BMI: 26.6 ± 6.0 kg/m2). Weight, height and waist circumference were measured, and body mass index was calculated. Dietary intake and diabetes knowledge were assessed using a food frequency questionnaire and Diabetes Knowledge Questionnaire (DKQ-24), respectively. The Finnish Diabetes Risk Score (FINDRISC) tool predicted T2D risk within 10 years. A total of 66.3% (n = 55) respondents were at risk of T2D. The majority of the subjects (74%) had poor diabetes knowledge scores. Fibre intake was inadequate compared to the recommended range. Waist circumference, first- and second-degree family history of diabetes was significantly associated with increased T2D risk (p = 0.016, 0.001 and 0.009, respectively), whereas a daily consumption of fruits and vegetables was associated with reduced T2D risk (p = 0.024). The findings highlight the importance of public health action, including nutrition education, after delivery to prevent or delay their progression towards T2D.
Abdullah, N., Murad, N., Attia, J., Oldmeadow, C., Kamaruddin, M. A., Jalal, N. A., Ismail, N., Jamal, R., Scott, R. J., & Holliday, E. G. (2018). Differing contributions of classical risk factors to type 2 diabetes in multi-ethnic Malaysian populations. International Journal of Environmental Research and Public Health, 15(12), 2813.
https://doi.org/10.3390/ijerph15122813
Al-Rifai, R. H., Majeed, M., Qambar, M. A., Ibrahim, A., AlYammahi, K. M., & Aziz, F. (2019). Type 2 diabetes and pre-diabetes mellitus: a systematic review and meta-analysis of prevalence studies in women of childbearing age in the Middle East and North Africa, 2000-2018. Systematic Reviews, 8(1), 268. https://doi.org/10.1186/s13643-019-1187-1
Ambak, R., He, F. J., Othman, F., Michael, V., Yusoff, M. F., & Aris, T. (2021). Salt intake was higher among males and those with high BMI and waist circumference: Introduction to the Malaysian Community Salt Survey (MyCoSS), a population-based salt intake survey in Malaysia. Journal of Health, Population, and Nutrition, 40 (Suppl 1), 23. https://doi.org/10.1186/s41043-021-00229-y
Bellou, V., Belbasis, L., Tzoulaki, I., & Evangelou, E. (2018). Risk factors for type 2 diabetes mellitus: An exposure-wide umbrella review of meta-analyses. PloS One, 13(3), e0194127. https://doi.org/10.1371/journal.pone.0194127
Carter, P., Gray, L. J., Troughton, J., Khunti, K., & Davies, M. J. (2010). Fruit and vegetable intake and incidence of type 2 diabetes mellitus: systematic review and meta-analysis. BMJ, 341, c4229. https://doi.org/10.1136/bmj.c4229
Chivese, T., Werfalli, M. M., Magodoro, I., Chinhoyi, R. L., Kengne, A. P., Norris, S. A., & Levitt, N. S. (2019). Prevalence of type 2 diabetes mellitus in women of childbearing age in Africa during 2000-2016: a systematic review and meta-analysis. BMJ Open, 9(5), e024345. https://doi.org/ 10.1136/bmjopen-2018-024345
Department of Statistics Malaysia. (2020). Household income estimates and incidence of poverty report, Malaysia, 2020.
https://www.dosm.gov.my/v1/index.php?r=column/cthemeByCat&cat=493& bulid=VTNHRkdiZkFzenBNd1Y1dmg2UUlrZz09&menu_id=amVoWU54UTl0a21NWmdhMjFMMW cyZz09
Després J. P. (2012). Body fat distribution and risk of cardiovascular disease: an update. Circulation, 126(10), 1301–1313.
https://doi.org/10.1161/CIRCULATIONAHA.111.067264
Dugee, O., Janchiv, O., Jousilahti, P., Sakhiya, A., Palam, E., Nuorti, J. P., & Peltonen, M. (2015). Adapting existing diabetes risk scores for an Asian population: a risk score for detecting undiagnosed diabetes in the Mongolian population. BMC Public Health, 1 – 9. https://doi.org/10.1186/s12889-015-2298-9
Fan, Y., Wang, L., Liu, H., Zhang, S., Tian, H., Shen, Y., Tuomilehto, J., Yu, Z., Yang, X., Hu, G., & Liu, M. (2020). ?-Cell function or insulin resistance was associated with the risk of type 2 diabetes among women with or without obesity and a history of gestational diabetes. BMJ Open Diabetes Research & Care, 8(1), e001060. https://doi.org/10.1136/bmjdrc-2019-00 1060
Garcia, A. A., Villagomez, E. T., Brown, S. A., Kouzekanani, K., & Hanis, C. L. (2001). The Starr County Diabetes Education Study: development of the Spanish-language diabetes knowledge questionnaire. Diabetes Care, 24(1), 16–21.
https://doi.org/10.2337/diacare.24.1.16
Guasch-Ferré, M., Bhupathiraju, S. N., & Hu, F. B. (2018). Use of metabolomics in improving assessment of dietary intake. Clinical Chemistry, 64(1), 82–98. https://doi.org/10.1373 /clinchem.2017.272344
Gunderson, E. P., Lewis, C. E., Lin, Y., Sorel, M., Gross, M., Sidney, S., Jacobs, D. R., Jr, Shikany, J. M., & Quesenberry, C. P., Jr (2018). Lactation duration and progression to diabetes in women across the childbearing years: The 30-year CARDIA study. JAMA Internal Medicine, 178(3), 328–337. https://doi.org/10.1001/jamainternmed.2017.7978
Harrison, T. A., Hindorff, L. A., Kim, H., Wines, R. C., Bowen, D. J., McGrath, B. B., & Edwards, K. L. (2003). Family history of diabetes as a potential public health tool. American Journal of Preventive Medicine, 24(2), 152–159. https://doi.org/10.1016/s0749-3797(02)00588-3
Hasbullah, F. Y., Fong, K. Y., Ismail, A., Mitri, J., & Mohd Yusof, B. N. (2021). A comparison of nutritional status, knowledge and type 2 diabetes risk among Malaysian young adults with and without family history of diabetes. Malaysian Journal of Medical Sciences, 28(1),75–86. https://doi.org/ 10.21315/mjms2021.28.1.10
Hashim, J. H., Adman, M. A., Hashim, Z., Mohd Radi, M. F., & Kwan, S. C. (2021). COVID-19 epidemic in Malaysia: Epidemic progression, challenges, and response. Frontiers in Public Health, 9, 560592. https://doi.org/10.3389/fpubh.2021.560592
Institute for Public Health. (2014). National Health and Morbidity Survey 2014: Malaysian Adult Nutrition Survey (MANS). Volume I: Methodology and general findings. IPH.
International Diabetes Federation. (2019). IDF diabetes atlas (9th ed.). IDF.
Iversen, D. S., Støy, J., Kampmann, U., Voss, T. S., Madsen, L. R., Møller, N., & Ovesen, P. G. (2016). Parity and type 2 diabetes mellitus: a study of insulin resistance and ?-cell function in women with multiple pregnancies. BMJ Open Diabetes Research & Care, 4(1), e000237. https://doi.org /10.1136/bmjdrc-2016-000237
Jannasch, F., Kröger, J., & Schulze, M. B. (2017). Dietary patterns and type 2 diabetes: A systematic literature review and meta-analysis of prospective studies. The Journal of Nutrition, 147(6), 1174–1182. https://doi.org/10.3945/jn.116.242552
Lim, H. M., Chia, Y. C., & Koay, Z. L. (2020). Performance of the Finnish Diabetes Risk Score (FINDRISC) and Modified Asian FINDRISC (ModAsian FINDRISC) for screening of undiagnosed type 2 diabetes mellitus and dysglycaemia in primary care. Primary Care Diabetes, 14(5), 494- 500.
Lindström, J., & Tuomilehto, J. (2003). The diabetes risk score: a practical tool to predict type 2 diabetes risk. Diabetes Care, 26(3), 725–731.
https://doi.org/10.2337/diacare.26.3.725
McRae, M. P. (2017). Dietary fiber is beneficial for the prevention of cardiovascular disease: An umbrella review of meta-analyses. Journal of Chiropractic Medicine, 16(4), 289–299. https://doi.org/10.1016/j.jcm.2017.05.005
Milton, S. (1986). A sample size formula for multiple regression studies. Public Opinion Quarterly, 50, 112-118.
Mueller, N. T., Mueller, N. J., Odegaard, A. O., Gross, M. D., Koh, W. P., Yuan, J. M., & Pereira, M. A. (2013). Higher parity is associated with an increased risk of type-II diabetes in Chinese women: the Singapore Chinese Health Study. BJOG: An International Journal of Obstetrics and Gynaecology, 120(12), 1483–1489. https://doi.org/10.1111/1471-0528.12364
National Coordinating Committee on Food and Nutrition. (2017). Recommended nutrient intakes for Malaysia: A report of the technical working group on nutritional guidelines. NCCFN.
Norimah, A. K., Jr, Safiah, M., Jamal, K., Haslinda, S., Zuhaida, H., Rohida, S., Fatimah, S., Norazlin, S., Poh, B. K., Kandiah, M., Zalilah, M. S., Wan Manan, W. M., Fatimah, S., & Azmi, M. Y. (2008). Food consumption patterns: Findings from the Malaysian Adult Nutrition Survey (MANS). Malaysian Journal of Nutrition, 14(1), 25–39.
Oh, S.H., Ku, H., & Park, K.S. (2021). Prevalence and socioeconomic burden of diabetes mellitus in South Korean adults: a population-based study using administrative data. BMC Public Health, 21(1), 548.
Oo, A., Al-abed, Lwin, O., Sham, S., Sim, T., Mukti, N., Zahariluddin, A., & Jaffar, Faizul. (2020). Type 2 diabetes mellitus prediction in Malaysia using modified diabetes risk assessment tool. Malaysian Journal of Public Health Medicine, 20(1), 15-21. https://doi.org/10.37268/mjphm/vol. 20/no.1/art.442
Osterrieder, A., Cuman, G., Pan-Ngum, W., Cheah, P. K., Cheah, P. K., Peerawaranun, P., Silan, M., Orazem, M., Perkovic, K., Groselj, U., Schneiders, M. L., Poomchaichote, T., Waithira, N., Asarath, S. A., Naemiratch, B., Ruangkajorn, S., Skof, L., Kulpijit, N., Mackworth-Young, C., Ongkili, D., & Cheah, P. Y. (2021). Economic and social impacts of COVID-19 and public health measures: results from an anonymous online survey in Thailand, Malaysia, the UK, Italy and Slovenia. BMJ Open, 11(7), e046863. https://doi.org/10.1136/bmjopen-2020-046863
Qamar, M., Iqubal, R. R. M., Ahmad, S., Shaikh, F. A., & Ismail, N. E. (2017) Awareness of diabetes mellitus among general public in Shah Alam, Malaysia: A cross-sectional study. Asian Journal of Pharmaceutical and Clinical research, 10(9), 192–196.
Saleem, S. M., Khan, S. M. S., & Jan, S. S. (2017). Finnish Diabetic Risk Score: A Tool for Predicting Risk of Undiagnosed Type 2 Diabetes Mellitus. Annals of Medical and Health Sciences Research, 7, 295- 298.
Scavini, M., Rossi, M. C., Scardapane, M., Nicolucci, A., Manicardi, V., Russo, G., Di Bartolo, P., Giorda, C. B., Musacchio, N., Ceriello, A., Genovese, S., Molinari, C., Dozio, N., & AMD-Annals Study Group (2018). Portrait of women with type 1 or type 2 diabetes of childbearing age attending diabetes clinics in Italy: the AMD-Annals initiative. Acta Diabetologica, 55(2), 193–199. https://doi.org/10.1007 /s00592-017-1076-9
Seligman, H. K., & Schillinger, D. (2010). Hunger and socioeconomic disparities in chronic disease. The New England Journal of Medicine, 363(1), 6–9. https://doi.org/10.1056/NEJMp1000072
Sharma, S. V., Chuang, R. J., Rushing, M., Naylor, B., Ranjit, N., Pomeroy, M., & Markham, C. (2020). Social determinants of health-related needs during COVID-19 among low income households with children. Preventing Chronic Disease, 17, E119. https://doi.org/10.5888/pcd17.200322
Szumilas M. (2010). Explaining odds ratios. Journal of the Canadian Academy of Child and Adolescent Psychiatry. 19(3), 227–229.
Takeuchi, M., Wu, B., Honda, M., Tsuboi, A., Kitaoka, K., Minato, S., Kurata, M., Kazumi, T., & Fukuo, K. (2020). Decreased arterial distensibility and postmeal hyperinsulinemia in young Japanese women with family history of diabetes. BMJ Open Diabetes Research & Care, 8(1), e001244. https://doi.org/10.1136/bmjdrc-2020-001244
Tian, Y., Shen, L., Wu, J., Chen, W., Yuan, J., Yang, H., Wang, Y., Liang, Y., & Wu, T. (2014). Parity and the risk of diabetes mellitus among Chinese women: A cross-sectional evidence from the Tongji-Dongfeng cohort study. PloS One, 9(8), e104810. https://doi.org/10.1371/journal.pone.0104810
Vézina-Im, L. A., Nicklas, T. A., & Baranowski, T. (2018). Associations Among Sleep, Body Mass Index, Waist Circumference, and Risk of Type 2 Diabetes Among U.S. Childbearing-Age Women: National Health and Nutrition Examination Survey. Journal of Women's Health, 27(11), 1400–1407. https://doi.org/10.1089/jwh.2017.6534
Vounzoulaki, E., Khunti, K., Abner, S. C., Tan, B. K., Davies, M. J., & Gillies, C. L. (2020). Progression to type 2 diabetes in women with a known history of gestational diabetes: systematic review and meta- analysis. BMJ, 369, m1361.
https://doi.org/10.1136/bmj.m1361
World Health Organization, International Association for the Study of Obesity, International Obesity Task Force (WHO/IASO/IOTF). (2000). The Asia-Pacific perspective: redefining obesity and its treatment. Health Communications Australia.
World Health Organization. (2008). STEPwise approach to NCD risk factor surveillance (STEPS). https://www.who.int/teams/noncommunicable-diseases/surveillance/systemstools/steps
World Health Organization. (2020). Women of reproductive age (15-49 years) population. https://www.who.int/data/gho/indicator-metadata-registry/imr-details/women-of-reproductive- age-(15-49-years)-population-(thousands)
World Health Organization. (2021). Body mass index – BMI.
https://www.euro.who.int/en/health- topics/disease-prevention/nutrition/a-healthylifestyle/body-mass-index-bmi
In-Text Citation: (Hasbullah et al., 2021)
To Cite this Article: Hasbullah, F. Y., Yusof, B. N. M., & Badrudin, S. N. (2021). Factors Associated with the Risk of Type 2 Diabetes in Women of Childbearing Age in A Selected Community in Malaysia. International Journal of Academic Research in Business and Social Sciences, 11(19), 191–206.
Copyright: © 2021 The Author(s)
Published by Knowledge Words Publications (www.kwpublications.com)
This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at: http://creativecommons.org/licences/by/4.0/legalcode
