We genuinely thank Dr. Alsarwani for his insights [1]. Our study is the first large analysis that has utilized electronic sources to examine significant population health predictors and outcomes [2]. Similar to most published studies, it has some strengths, limitations, and some potential bias which we have acknowledged. Our role as researchers is to determine truer estimates and reduce the magnitude of bias.
As for the first point about medications, some medications are indeed used to treat conditions other than diabetes. However, removing all patients with these medications would remove sizeable true diabatic patients and drastically underestimate the true prevalence. This is because ICD-10 coding is not mature enough to locally identify all patients with a specific disease. In addition, many patients come to clinics to treat one condition (i.e., asthma) while also being diabetics. The systems will not capture the primary coding of these patients because it was not the main reason the patients visited the hospital. From the most reliable national study conducted in 2013, we know that the national prevalence rates of diabetes and hypertension are 13.4% and 15.2%, respectively [3,4]. This estimate is about one decade old. We know that with increased risk factors, such as obesity and a sedentary lifestyle, diabetes and hypertension will likely increase in subsequent years. In fact, the recent PURE study, cited in our paper, indicated that the diabetes and hypertension prevalence rates were 25.1% and 30.3%, respectively, among older adults [5]. Finally, as part of the limitations, we have acknowledged that these estimates are based on hospital visits, which reflect those who sought medical treatment. Therefore, even if there was some overestimation of cases, it is likely to be minimal. We are currently working on a study to explore what percentage of diabetes is captured via all available sources such as ICD, medications, HA1C, or even using the progress note (written by the physician) alone. We hope that such a study will shed more light on the path to better capture all patients with a specific diagnosis with high sensitivity and specificity.
As for the second point, it is unlikely that we missed those with type 1 diabetes because we included all those with a diabetes diagnosis. In fact, this was one of the limitations we stated in our study—we were unable to differentiate between type 1 and type 2 diabetes (page 8).
As for the last point, this study examined the independent association between these variables and the outcome. Although many consider hypertension to be a confounder in obesity–diabetes associations, hypertension is likely also a mediator or a collider in that relationship. Therefore, adjusting for hypertension will bias that association [6].
Study concept and design: S.A. (Suliman Alghnam), M.A. and R.A. Reviewed the literature and interpret the findings: S.A. (Sarah Alzahrani), S.A.A., M.B., A.A., M.A.D. and I.A.A. Statistical analysis and the introduction and methods: S.A. (Suliman Alghnam) and M.B. The result section was written by S.A. (Sarah Alzahrani). Wrote part of the discussion section: S.A.A. and S.A. (Suliman Alghnam). All authors have read and agreed to the published version of the manuscript.
This study was reviewed and approved by the Institutional Review Board (IRB) of King Abdulah International Medical Research Center (KAIMRC) study number: 19/189/R.
Not applicable.
All data are available from the corresponding author upon reasonable request.
The authors declare no conflict of interest.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
1. Alsarwani, R.M. Comment on Alghnam et al. The Association between Obesity and Chronic Conditions: Results from a Large Electronic Health Records System in Saudi Arabia. Int. J. Environ. Res. Public Health 2021, 18, 12361. Int. J. Environ. Res. Public Health; 2022; 19, 9846. [DOI: https://dx.doi.org/10.3390/ijerph19169846]
2. Alghnam, S.; Alessy, S.A.; Bosaad, M.; Alzahrani, S.; Al Alwan, I.I.; Alqarni, A.; Alshammari, R.; Al Dubayee, M.; Alfadhel, M. The Association between Obesity and Chronic Conditions: Results from a Large Electronic Health Records System in Saudi Arabia. Int. J. Environ. Res. Public Health; 2021; 18, 12361. [DOI: https://dx.doi.org/10.3390/ijerph182312361] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/34886087]
3. El Bcheraoui, C.; Basulaiman, M.; Tuffaha, M.; Daoud, F.; Robinson, M.; Jaber, S.; Mikhitarian, S.; Memish, Z.A.; Al Saeedi, M.; AlMazroa, M.A. et al. Status of the diabetes epidemic in the Kingdom of Saudi Arabia, 2013. Int. J. Public Health; 2014; 59, pp. 1011-1021. [DOI: https://dx.doi.org/10.1007/s00038-014-0612-4] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/25292457]
4. El Bcheraoui, C.; Memish, Z.A.; Tuffaha, M.; Daoud, F.; Robinson, M.; Jaber, S.; Mikhitarian, S.; Al Saeedi, M.; Almazroa, M.A.; Mokdad, A.H. et al. Hypertension and Its Associated Risk Factors in the Kingdom of Saudi Arabia, 2013: A National Survey. Int. J. Hypertens.; 2014; 2014, 564679. [DOI: https://dx.doi.org/10.1155/2014/564679] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/25170423]
5. Alhabib, K.F.; Batais, M.A.; Almigbal, T.H.; Alshamiri, M.Q.; Altaradi, H.; Rangarajan, S.; Yusuf, S. Demographic, behavioral, and cardiovascular disease risk factors in the Saudi population: Results from the Prospective Urban Rural Epidemiology study (PURE-Saudi). BMC Public Health; 2020; 20, 1213. [DOI: https://dx.doi.org/10.1186/s12889-020-09298-w] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32770968]
6. Hossain, M.B.; Khan, J.R.; Das Gupta, R. Role of hypertension in the association of overweight and obesity with diabetes among adults in Bangladesh: A population-based, cross-sectional nationally representative survey. BMJ Open; 2021; 11, e050493. [DOI: https://dx.doi.org/10.1136/bmjopen-2021-050493] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/34330863]
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Abstract
[...]the recent PURE study, cited in our paper, indicated that the diabetes and hypertension prevalence rates were 25.1% and 30.3%, respectively, among older adults [5]. [...]this was one of the limitations we stated in our study—we were unable to differentiate between type 1 and type 2 diabetes (page 8). [...]adjusting for hypertension will bias that association [6].
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
Details



1 Population Health Section, King Abdullah International Medical Research Centre (KAIMRC), King Saud Bin Abdulaziz University for Health Sciences (KSAU-HS), Riyadh 11426, Saudi Arabia
2 Public Health Department, College of Health Sciences, Saudi Electronic University, Riyadh 11673, Saudi Arabia
3 Department of Epidemiology, School of Public Health, University of Pittsburg, Pittsburg, PA 15261, USA
4 Division of Endocrinology, Department of Pediatrics, King Abdulaziz Medical City, King Abdullah Specialist Children’s Hospital, MNG-HA, Riyadh 11426, Saudi Arabia; College of Medicine, King Saud Bin Abdulaziz University for Health Sciences, King Abdulaziz Medical City, MNG-HA, Riyadh 11426, Saudi Arabia
5 King Abdullah International Medical Research Centre, King Saud Bin Abdulaziz University for Health Sciences (KSAU-HS), King Abdulaziz Medical City, MNG-HA, Alahsa 11426, Saudi Arabia
6 School of Public Health, King Saud Bin Abdulaziz University for Health Sciences (KSAU-HS), Riyadh 11426, Saudi Arabia
7 College of Medicine, King Saud Bin Abdulaziz University for Health Sciences, King Abdulaziz Medical City, MNG-HA, Riyadh 11426, Saudi Arabia; Medical Genomic Research Department, King Abdullah International Medical Research Centre, King Abdulaziz Medical City, MNG-HA, Riyadh 11426, Saudi Arabia; Genetics and Precision Medicine Department (GPM), King Abdulaziz Medical City, King Abdullah Specialist Children’s Hospital, MNG-HA, Riyadh 11426, Saudi Arabia