Linking Creatinine-to-Body Weight Ratio With Diabetes Incidence: A Multiethnic Malaysian Cohort Study
Noraidatulakma Abdullah
UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
Search for more papers by this authorYing-Xian Goh
UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
Search for more papers by this authorAisyatul Najihah Khuzaimi
UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
Search for more papers by this authorAzwa Shawani Kamalul Arifin
UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
Search for more papers by this authorNurul Ain Mhd Yusuf
UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
Search for more papers by this authorNazihah Abd Jalal
UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
Search for more papers by this authorNorliza Ismail
UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
Search for more papers by this authorNurul Faeizah Husin
UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
Search for more papers by this authorMohd Arman Kamaruddin
UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
Search for more papers by this authorCorresponding Author
Rahman Jamal
UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
Correspondence:
Rahman Jamal ([email protected])
Search for more papers by this authorNoraidatulakma Abdullah
UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
Search for more papers by this authorYing-Xian Goh
UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
Search for more papers by this authorAisyatul Najihah Khuzaimi
UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
Search for more papers by this authorAzwa Shawani Kamalul Arifin
UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
Search for more papers by this authorNurul Ain Mhd Yusuf
UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
Search for more papers by this authorNazihah Abd Jalal
UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
Search for more papers by this authorNorliza Ismail
UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
Search for more papers by this authorNurul Faeizah Husin
UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
Search for more papers by this authorMohd Arman Kamaruddin
UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
Search for more papers by this authorCorresponding Author
Rahman Jamal
UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
Correspondence:
Rahman Jamal ([email protected])
Search for more papers by this authorFunding: This work was supported by a top-down grant from the Ministry of Higher Education Malaysia (Grant number PDE48). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Noraidatulakma Abdullah and Ying-Xian Goh have contributed equally to this work and should be considered joint first author.
ABSTRACT
Background
Emerging evidence suggests that the creatinine-to-body weight (Cre/BW) ratio is a predictor for incident diabetes in the Asian population. This study examined the association between Cre/BW ratio and incident diabetes, as well as the relationship between Cre/BW ratio and skeletal muscle and body fat mass in a multiethnic Malaysian cohort.
Methods
A total of 13 047 eligible participants were selected from 119 560 The Malaysian Cohort participants. Of these, 750 who developed diabetes were selected as cases, while 3750 controls were chosen randomly from healthy participants. This nested case–control study included 4500 eligible participants from The Malaysian Cohort, with a 1:5 case-to-control ratio. Participants were stratified into four groups based on Cre/BW ratio quartiles. The Cox proportional hazards model evaluated the effect of Cre/BW ratio on developing incident diabetes. The association between Cre/BW ratio and body composition was assessed using the Pearson correlation coefficient.
Results
Of the 13 047 eligible participants followed up over 5.3 years, 5.75% (n = 750) developed diabetes. Diabetes incidence decreased with increasing Cre/BW ratios. The Cre/BW ratio was inversely correlated with diabetes risk (HR: 0.403, 95% CI: 0.315–0.515, p < 0.001). Additionally, males and Indians had a higher risk of developing incident diabetes. A significant correlation was observed between Cre/BW ratio and body fat mass (p < 0.001).
Conclusions
This study reveals an inverse association between the Cre/BW ratio and incident diabetes. It also found a significant moderate correlation between the Cre/BW ratio and body fat mass.
Conflicts of Interest
The authors declare no conflicts of interest.
Open Research
Data Availability Statement
The data sets generated and analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.
Supporting Information
| Filename | Description |
|---|---|
| jdb70039-sup-0001-Supplementary_file.docxWord 2007 document , 21.2 KB |
Data S1. Supporting Information. |
| jdb70039-sup-0002-Supplementary_Table_S1.docxWord 2007 document , 26.9 KB |
Table S1. Baseline characteristics of participants according to the quartiles of Cre/BW ratios, stratified based on gender. |
| jdb70039-sup-0003-Supplementary_Table_S2.docxWord 2007 document , 39.3 KB |
Table S2. Baseline characteristics participants according to the quartiles of Cre/BW ratios, stratified based on ethnicities. |
| jdb70039-sup-0004-Supplementary_Table_S3.docxWord 2007 document , 15 KB |
Table S3. The relationship between Cre/BW ratio and incident diabetes in unadjusted and adjusted proportional hazards models in overall participants. |
| jdb70039-sup-0005-Supplementary_Table_S4.docxWord 2007 document , 17 KB |
Table S4. The relationship between Cre/BW ratio and incident diabetes in unadjusted and adjusted proportional hazards models, stratified based on gender. |
| jdb70039-sup-0006-Supplementary_Table_S5.docxWord 2007 document , 21.7 KB |
Table S5. The relationship between Cre/BW ratio and incident diabetes in unadjusted and adjusted proportional hazards models, stratified based on ethnicity. |
| jdb70039-sup-0007-Supplementary_Table_S6.docxWord 2007 document , 14.9 KB |
Table S6. The relationship between BMI, waist/height and incident diabetes in unadjusted and adjusted proportional hazards models in overall participants. |
| jdb70039-sup-0008-Supplementary_Table_S7.docxWord 2007 document , 19.2 KB |
Table S7. The relationship between Cre/BW ratio, interaction with ethnicity and incident diabetes in unadjusted and adjusted proportional hazards models in overall participants. |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
References
- 1N. Abdullah, N. A. Abdul Murad, E. A. Mohd Haniff, et al., “Predicting Type 2 Diabetes Using Genetic and Environmental Risk Factors in a Multi-Ethnic Malaysian Cohort,” Public Health 149 (2017): 31–38, https://doi.org/10.1016/j.puhe.2017.04.003.
- 2 International Diabetes Federation, ed., IDF Diabetes Atlas, 10th ed. (Brussels: International Diabetes Federation, 2021).
- 3 World Health Organization, “W. Diabets Fact Sheet,” 2021, https://www.who.int/news-room/fact-sheets/detail/diabetes.
- 4 National Institute of Health Malaysia, “Non-Communicable Diseases: Risk Factors and Other Health Problems (NHMS 2019),” Vol 1, 2020, http://www.iku.gov.my/nhms-2019.
- 5Y. Hashimoto, T. Okamura, M. Hamaguchi, A. Obora, T. Kojima, and M. Fukui, “Creatinine to Body Weight Ratio Is Associated With Incident Diabetes: Population-Based Cohort Study,” Journal of Clinical Medicine 9, no. 1 (2020): 227, https://doi.org/10.3390/jcm9010227.
- 6Z. Chen, Y. Zou, F. Yang, et al., “Relationship Between Creatinine to Body Weight Ratios and Diabetes Mellitus: A Chinese Cohort Study,” Journal of Diabetes 14, no. 3 (2022): 167–178, https://doi.org/10.1111/1753-0407.13248.
- 7J. He, “Creatinine-to-Body Weight Ratio Is a Predictor of Incident Diabetes: A Population-Based Retrospective Cohort Study,” Diabetology and Metabolic Syndrome 14, no. 1 (2022): 7, https://doi.org/10.1186/s13098-021-00776-8.
- 8A. C. Baxmann, M. S. Ahmed, N. C. Marques, et al., “Influence of Muscle Mass and Physical Activity on Serum and Urinary Creatinine and Serum Cystatin C,” Clinical Journal of the American Society of Nephrology 3, no. 2 (2008): 348–354, https://doi.org/10.2215/CJN.02870707.
- 9L. Viollet, S. Gailey, D. J. Thornton, et al., “Utility of Cystatin C to Monitor Renal Function in Duchenne Muscular Dystrophy,” Muscle & Nerve 40, no. 3 (2009): 438–442, https://doi.org/10.1002/mus.21420.
- 10Y. Hirasawa, R. Matsuki, T. Ebisu, T. Kurose, Y. Hamamoto, and Y. Seino, “Evaluation of Skeletal Muscle Mass Indices, Assessed by Bioelectrical Impedance, as Indicators of Insulin Resistance in Patients With Type 2 Diabetes,” Journal of Physical Therapy Science 31, no. 2 (2019): 190–194, https://doi.org/10.1589/jpts.31.190.
- 11Y. Tajiri, T. Kato, H. Nakayama, and K. Yamada, “Reduction of Skeletal Muscle, Especially in Lower Limbs, in Japanese Type 2 Diabetic Patients With Insulin Resistance and Cardiovascular Risk Factors,” Metabolic Syndrome and Related Disorders 8, no. 2 (2010): 137–142, https://doi.org/10.1089/met.2009.0043.
- 12P. Srikanthan, A. L. Hevener, and A. S. Karlamangla, “Sarcopenia Exacerbates Obesity-Associated Insulin Resistance and Dysglycemia: Findings From the National Health and Nutrition Examination Survey III,” PLoS One 5, no. 5 (2010): e10805, https://doi.org/10.1371/journal.pone.0010805.
- 13Y. Wu, D. Li, and S. H. Vermund, “Advantages and Limitations of the Body Mass Index (BMI) to Assess Adult Obesity,” International Journal of Environmental Research and Public Health 21, no. 6 (2024): 757–768, https://doi.org/10.3390/ijerph21060757.
- 14R. Jamal, S. Z. Syed Zakaria, M. A. Kamaruddin, et al., “Cohort Profile: The Malaysian Cohort (TMC) Project: A Prospective Study of Non-Communicable Diseases in a Multi-Ethnic Population,” International Journal of Epidemiology 44, no. 2 (2015): 423–431, https://doi.org/10.1093/ije/dyu089.
- 15N. Abdullah, M. A. Kamaruddin, Y. X. Goh, et al., “Participants Attrition in a Longitudinal Study: The Malaysian Cohort Study Experience,” International Journal of Environmental Research and Public Health 18, no. 14 (2021): 7216, https://doi.org/10.3390/ijerph18147216.
- 16N. Abdullah, Y. Goh, R. Othman, et al., “Stability of Glycated Haemoglobin (HbA1c) Measurements From Whole Blood Samples Kept at −196°C for Seven to Eight Years in the Malaysian Cohort Study,” Journal of Clinical Laboratory Analysis 37, no. 8 (2023): e24898, https://doi.org/10.1002/jcla.24898.
- 17 WHO Expert Consultation, “Appropriate Body-Mass Index for Asian Populations and Its Implications for Policy and Intervention Strategies,” Lancet 363, no. 9403 (2004): 157–163, https://doi.org/10.1016/S0140-6736(03)15268-3.
- 18J. E. Schutte, J. C. Longhurst, F. A. Gaffney, B. C. Bastian, and C. G. Blomqvist, “Total Plasma Creatinine: An Accurate Measure of Total Striated Muscle Mass,” Journal of Applied Physiology 51, no. 3 (1981): 762–766, https://doi.org/10.1152/jappl.1981.51.3.762.
- 19X. Bao, Y. Gu, Q. Zhang, et al., “Low Serum Creatinine Predicts Risk for Type 2 Diabetes,” Diabetes/Metabolism Research and Reviews 34, no. 6 (2018): e3011, https://doi.org/10.1002/dmrr.3011.
- 20D. K. Song, Y. S. Hong, Y. A. Sung, and H. Lee, “Association of Serum Creatinine Levels and Risk of Type 2 Diabetes Mellitus in Korea: A Case Control Study,” BMC Endocrine Disorders 22, no. 1 (2022): 4, https://doi.org/10.1186/s12902-021-00915-2.
- 21M. E. Cleasby, S. Jarmin, W. Eilers, et al., “Local Overexpression of the Myostatin Propeptide Increases Glucose Transporter Expression and Enhances Skeletal Muscle Glucose Disposal,” American Journal of Physiology. Endocrinology and Metabolism 306, no. 7 (2014): E814–E823, https://doi.org/10.1152/ajpendo.00586.2013.
- 22M. S. Haines, L. E. Dichtel, K. Santoso, M. Torriani, K. K. Miller, and M. A. Bredella, “Association Between Muscle Mass and Insulin Sensitivity Independent of Detrimental Adipose Depots in Young Adults With Overweight/Obesity,” International Journal of Obesity 44, no. 9 (2020): 1851–1858, https://doi.org/10.1038/s41366-020-0590-y.
- 23K. Mitsuhashi, Y. Hashimoto, M. Tanaka, et al., “Combined Effect of Body Mass Index and Waist-Height Ratio on Incident Diabetes; a Population Based Cohort Study,” Journal of Clinical Biochemistry and Nutrition 61, no. 2 (2017): 118–122, https://doi.org/10.3164/jcbn.16-116.
- 24R. N. Feng, C. Zhao, C. Wang, et al., “BMI Is Strongly Associated With Hypertension, and Waist Circumference Is Strongly Associated With Type 2 Diabetes and Dyslipidemia, in Northern Chinese Adults,” Journal of Epidemiology 22, no. 4 (2012): 317–323, https://doi.org/10.2188/jea.JE20110120.
- 25E. Levelt, M. Pavlides, R. Banerjee, et al., “Ectopic and Visceral Fat Deposition in Lean and Obese Patients With Type 2 Diabetes,” Journal of the American College of Cardiology 68, no. 1 (2016): 53–63, https://doi.org/10.1016/j.jacc.2016.03.597.
- 26T. Okamura, Y. Hashimoto, M. Hamaguchi, A. Obora, T. Kojima, and M. Fukui, “Ectopic Fat Obesity Presents the Greatest Risk for Incident Type 2 Diabetes: A Population-Based Longitudinal Study,” International Journal of Obesity 43, no. 1 (2019): 139–148, https://doi.org/10.1038/s41366-018-0076-3.
- 27O. T. Hardy, M. P. Czech, and S. Corvera, “What Causes the Insulin Resistance Underlying Obesity?,” Current Opinion in Endocrinology, Diabetes, and Obesity 19, no. 2 (2012): 81–87, https://doi.org/10.1097/MED.0b013e3283514e13.
- 28Y. T. Wondmkun, “Obesity, Insulin Resistance, and Type 2 Diabetes: Associations and Therapeutic Implications,” Diabetes, Metabolic Syndrome and Obesity 13 (2020): 3611–3616, https://doi.org/10.2147/DMSO.S275898.
- 29H. Eshima, Y. Tamura, S. Kakehi, et al., “Long-Term, but Not Short-Term High-Fat Diet Induces Fiber Composition Changes and Impaired Contractile Force in Mouse Fast-Twitch Skeletal Muscle,” Physiological Reports 5, no. 7 (2017): e13250, https://doi.org/10.14814/phy2.13250.
- 30P. M. Badin, K. Louche, A. Mairal, et al., “Altered Skeletal Muscle Lipase Expression and Activity Contribute to Insulin Resistance in Humans,” Diabetes 60, no. 6 (2011): 1734–1742, https://doi.org/10.2337/db10-1364.
- 31S. H. Kim, H. W. Kang, J. B. Jeong, et al., “Association of Obesity, Visceral Adiposity, and Sarcopenia With an Increased Risk of Metabolic Syndrome: A Retrospective Study,” PLoS One 16, no. 8 (2021): e0256083, https://doi.org/10.1371/journal.pone.0256083.
- 32A. Kautzky-Willer, J. Harreiter, and G. Pacini, “Sex and Gender Differences in Risk, Pathophysiology and Complications of Type 2 Diabetes Mellitus,” Endocrine Reviews 37, no. 3 (2016): 278–316, https://doi.org/10.1210/er.2015-1137.
- 33B. S. Nayak, D. M. Butcher, S. Bujhawan, et al., “Association of Low Serum Creatinine, Abnormal Lipid Profile, Gender, Age and Ethnicity With Type 2 Diabetes Mellitus in Trinidad and Tobago,” Diabetes Research and Clinical Practice 91, no. 3 (2011): 342–347, https://doi.org/10.1016/j.diabres.2010.12.017.
- 34B. Tramunt, S. Smati, N. Grandgeorge, et al., “Sex Differences in Metabolic Regulation and Diabetes Susceptibility,” Diabetologia 63, no. 3 (2020): 453–461, https://doi.org/10.1007/s00125-019-05040-3.
- 35A. M. Lundsgaard and B. Kiens, “Gender Differences in Skeletal Muscle Substrate Metabolism - Molecular Mechanisms and Insulin Sensitivity,” Front Endocrinol (Lausanne) 5 (2014): 195–210, https://doi.org/10.3389/fendo.2014.00195.
- 36A. Nordström, J. Hadrévi, T. Olsson, P. W. Franks, and P. Nordström, “Higher Prevalence of Type 2 Diabetes in Men Than in Women Is Associated With Differences in Visceral Fat Mass,” Journal of Clinical Endocrinology and Metabolism 101, no. 10 (2016): 3740–3746, https://doi.org/10.1210/jc.2016-1915.
- 37S. Akhtar, J. A. Nasir, A. Ali, M. Asghar, R. Majeed, and A. Sarwar, “Prevalence of Type-2 Diabetes and Prediabetes in Malaysia: A Systematic Review and meta-Analysis,” PLoS One 17, no. 1 (2022): e0263139, https://doi.org/10.1371/journal.pone.0263139.
- 38K. K. Yeo, B. C. Tai, D. Heng, et al., “Ethnicity Modifies the Association Between Diabetes Mellitus and Ischaemic Heart Disease in Chinese, Malays and Asian Indians Living in Singapore,” Diabetologia 49, no. 12 (2006): 2866–2873, https://doi.org/10.1007/s00125-006-0469-z.
- 39P. Deurenberg, M. Deurenberg-Yap, and S. Guricci, “Asians Are Different From Caucasians and From Each Other in Their Body Mass Index/Body Fat per Cent Relationship,” Obesity Reviews 3, no. 3 (2002): 141–146, https://doi.org/10.1046/j.1467-789X.2002.00065.x.
- 40K. M. V. Narayan and A. M. Kanaya, “Why Are South Asians Prone to Type 2 Diabetes? A Hypothesis Based on Underexplored Pathways,” Diabetologia 63, no. 6 (2020): 1103–1109, https://doi.org/10.1007/s00125-020-05132-5.
- 41P. Sedgwick, “Nested Case-Control Studies: Advantages and Disadvantages,” BMJ 348 (February 2014): g1532, https://doi.org/10.1136/bmj.g1532.
10.1136/bmj.g1532 Google Scholar
