The Protective Effects of Insulin on the Developing of Dementia in Chronic Kidney Disease Patients with hypertension and diabetes: A Population-Based Nationwide Study

The Protective Effects of Insulin on the Developing of Dementia in Chronic Kidney Disease Patients with hypertension and diabetes: A Population-Based Nationwide Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Protective Effects of Insulin on the Developing of Dementia in Chronic Kidney Disease Patients with hypertension and diabetes: A Population-Based Nationwide Study Yun-Yi Chen, Yi-Hsien Chen, Yu-Wei Fang, Jing-Tong Wang, Ming-Hsien Tsai This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4329846/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Apr, 2025 Read the published version in BMC Nephrology → Version 1 posted 12 You are reading this latest preprint version Abstract INTRODUCTION: The effects of insulin use on the incidence of dementia in chronic kidney disease (CKD) patients with diabetes and hypertension is limited. METHOD In this retrospective study, differences in the incidence of dementia between insulin users and non-users were examined with competing risk models. RESULTS In a follow-up period of 11 years, 1285 events of dementia were recorded and the multivariate-adjusted hazard ratio for dementia by insulin usage (yes versus non) and insulin usage per medication possession ratio (MPR) is 0.652 (95% confidence interval [CI]: 0.552–0.771) and 0.995 (95% CI: 0.993–0.998) respectively. Such a significantly negative association was consistent in almost the subgroups. Moreover, a dosing effect of insulins was noted that patients who had higher insulin MPRs generally benefited from better protection from dementia. DISCUSSION The CKD patients with hypertension and diabetes who received insulin therapy had a 35% decreased risk of dementia. Chronic kidney disease real-world evidence insulin hypertension diabetes dementia Figures Figure 1 Figure 2 Figure 3 Introduction Chronic kidney disease (CKD) is a global health and financial issue nowadays with an estimated prevalence of 13.4% [ 1 , 2 ]. In Taiwan, it had been reported a higher CKD (stages 1–5) prevalence 15.5% [ 3 ] and a highest incidence of end stage of kidney disease (ESKD) in the world [ 4 ]. Moreover, CKD causes a considerable financial burden because it would lead to ESKD requiring dialysis and increase the risk of cardiovascular mortality and morbidity as the decline of renal function [ 2 , 5 ]. Dementia, an allover term for neurodegeneration disease aside from normal brain aging, is a major healthy concern in the elderly worldwide[ 6 ] with an forecasted all-cause dementia prevalence to 152 million by 2050 [ 7 ]. Alzheimer's disease accounts for 60–80% of cases and vascular dementia is the second most common cause of dementia [ 8 ]. The treatment strategies includes both non-pharmacologic approaches and pharmacologic approaches, but the efficacy of treatments remains limited [ 8 , 9 ]. Currently, identifying the modifiable risk factors is the main strategy to prevent dementia according to the clinical guideline[ 10 ]. Prior studies have found CKD to be an independent risk factor for cognitive impairment and dementia developing [ 11 , 12 ]. Moreover, hypertension and diabetes were both the well-known risk factors for the development of dementia[ 13 , 14 ]. Adequate hypertension control and sugar control has been shown to lower the risk of dementia [ 15 , 16 ]. Aside from blood pressure control, the renin-angiotensin-aldosterone system blockades has been shown beneficial for the dementia development in CKD population[ 17 , 18 ]. Insulin plays a crucial role in central nervous system (CNS) health not just via the decreasing the serum sugar level [ 19 ]. The insulin dysregulation can contribute to conditions of pathological brain aging, such as Alzheimer’s disease and vascular cognitive impairment [ 19 – 21 ], suggesting that the insulin injection might be a promising therapy for the preventing of dementia. However, the relationship of insulin use and cognitive health are inconsistent in the literatures [ 22 – 24 ]. In addition, no data was available for insulin control in the prevention dementia in CKD patients. Thus, we aim to use the National Health Insurance database (NHIRD) to analyze the association of insulin use and the development of dementia within the diabetic and hypertensive CKD population in a real word performance. Materials and Methods Data source and research samples A CKD thematic data was used from the NHIRD maintained by the Health and Welfare Data Science Center, Ministry of Health and Welfare, Taiwan, of which the detail was prescribed in the previous publication [ 17 ]. NHIRD contains the claims records of health care utilization of 99.9% of Taiwan’s 23 million population enrolled in the Taiwan National Health Insurance program[ 25 ]. The deidentified information retained in the data included date of birth, sex, residency area, diagnostic codes, medical procedures, and drug prescriptions. Before the NHIRD data was released for research, the personal information of all beneficiaries was de-identification and anonymous to ensure the privacy following rigorous secrecy guidelines. Therefore, informed consent was waived by the Ethics Review of Board Shin-Kong Wu Ho-Su Memorial Hospital (IRB approval number: No. 20200806R). Study design and study population The study was designed as a population-based longitudinal cohort study. The selected population were CKD patients diagnosed with hypertension (ICD-10: I10–I15) and diabetes (ICD-10: E08–E13) from January 1, 2006, through December 31, 2006. (n = 18,434). Patients who had previously been diagnosed with malignancy (ICD-10: C00-C96,D45, D47.Z9, E31.22, Z51.12), dementia (ICD-10: F01.50, F01.51, F03.90, and F03.91), cerebrovascular diseases (ICD-10: I60- I63, I65-I69, and G45-G46) were excluded. Patients under regular hemodialysis, peritoneal dialysis, or previously underwent renal transplantation were also excluded. Moreover, patients with ages under 20 years or above 80, or with missing information were also excluded. Finally, a total 11,758 CKD patients with hypertension and diabetes were chosen into analysis (Fig. 1 ). The index date was defined as January 1, 2007. The data was analyzed from the index date to the first instance of the desired outcome, dementia, or to the end of the observation date (December 31, 2017). Exposure to study drugs We used medication possession ratio (MPR) to calculate the degree how the patients had been prescribed the medication of insulin during the following period. MPR is measured as the sum of the days of a given drug in observation period, divided by the total number of days in the observation period [ 26 ]. We also defined insulin non-users as the MPR = 0% and insulin users as the MPR > 0%. Covariates Baseline comorbidities, including ischemic heart disease (ICD-10: I10–I15), hyperlipidemia (ICD-10: E78), atrial fibrillation (ICD-10:I48), chronic heart failure (ICD-10: I50), peripheral artery disease (ICD-10: I70.2–I70.9), asthma (ICD-10: J45), chronic obstructive pulmonary disease (ICD-10: J44), major depression disease (ICD-10: F32–F33), Parkinson’s disease (ICD-10: G20–G21), rheumatic arthritis (ICD-10: M05–M06), hyperthyroidism (ICD-10: E05), hypothyroidism (ICD-10: E01.8 and E02–E03), gout (ICD-10: M10), and insomnia (ICD-10: G47.0, and F51.0) was defined as having at least 3 outpatient diagnoses or 1 inpatient diagnosis usage within 1 year before the index date. Usage of other drugs, including benzodiazepines, anticoagulants, non-steroidal anti-inflammatory drugs (NSAIDs), acetaminophen, statins, calcium channel blockers, angiotensin converting enzyme inhibitors (ACEIs), angiotensin receptor blockers (ARBs), metformin, beta-blockers, and diuretics was defined as having at least 3 months of usage within 1 year before the index date. Outcome measurement Dementia, the main outcome of this study, was identified if a person qualified for a Severe Illness IC Card for dementia from the Taiwan National Health Insurance Administration. This was based on diagnoses by a licensed neurologist or psychiatrist. Statistical analysis Continuous data of baseline characteristics is expressed as mean ± standard deviation (SD), while categorical data is expressed as counts with proportions. The difference between groups (insulin users vs non-users) was compared using Chi-squared tests for portion and t-tests for means of continuous variables. Competing risk regression analyses were conducted for dementia developing (all-cause death was considered as a competing event) using the method described by Fine and Gray [ 27 ]. The stratified proportional sub-distribution hazard ratio (HR) was calculated to estimate the exposure and covariate effects on the cumulative incidence function. To assess the robustness of our findings, we added the variables of demographic data, comorbidities, and medications into multivariable regression models step by step. We also did the analyses of dosing effect of insulin on the prevention of dementia, which a Cochran-Armitage test was used for testing the dosing effect of insulin. We stratified insulin users by MPR rates, sorting them in the following groups: those with ≤ 20% MPR, those with MPR > 80% and sorted those with 20–80% MPR into groups per 20% MPR. We used the group with ≤ 20% MPR as our reference point. Finally, we performed a subgroup analysis by the age, gender, commodities and medications to test the consistency of the insulin protective effect on dementia in CKD population with diabetes and hypertension. If the groups with a portion of patients number < 10% were excluded from subgroup analysis. All statistical analyses were created by version 9.4 of SAS (SAS Institute, Cary, NC, USA) software. For all tests, a 2-sided p-values < 0.05 was considered as indicative of statistical significance. Results Patient Characteristics We enrolled 11,758 CKD patients with hypertension and diabetes in the present study (Table 1 ). The mean age of the enrolled patients was 62.1 ± 10.9 years, while 47% were women and 52.6% were hyperlipidemic. Among them, 5,864 patients had experienced insulin prescriptions and others (5,894) were insulin nonusers. Table 1 Baseline Characteristics of CKD patients with hypertension and diabetes Total (n = 11,758) Insulin non-users (n = 5,864) Insulin users (n = 5,894) p Sex < 0.001 Male (%) 6236 (53) 3205 (54.7) 3031 (51.4) Female (%) 5522 (47) 2659 (45.3) 2863 (48.6) Age 62.1 \(\pm\) 10.9 62.6 \(\pm\) 10.9 61.7 \(\pm\) 11 < 0.001 20–39 (%) 860 (7.3) 398 (6.8) 462 (7.8) 0.001 40–64 (%) 5794 (49.3) 2829 (48.2) 2965 (50.3) 65–80 (%) 5104 (43.4) 2637 (45) 2467 (41.9) Comorbidities Ischemic Heart Disease (%) 2794 (23.8) 1352 (23.1) 1442 (24.5) 0.072 Hyperlipidemia (%) 6186 (52.6) 3075 (52.4) 3111 (52.8) 0.708 Atrial Fibrillation (%) 163 (1.4) 92 (1.6) 71 (1.2) 0.091 CHF (%) 839 (7.1) 357 (6.1) 482 (8.2) < 0.001 PAD (%) 439 (3.7) 192 (3.3) 247 (4.2) 0.008 Asthma (%) 624 (5.3) 298 (5.1) 326 (5.5) 0.277 COPD (%) 1631 (13.9) 784 (13.4) 847 (14.4) 0.116 Major Depressive Disorder (%) 129 (1.1) 70 (1.2) 59 (1) 0.315 Parkinson's Disease (%) 94 (0.8) 42 (0.7) 52 (0.9) 0.312 Rheumatoid Arthritis (%) 114 (1) 50 (0.9) 64 (1.1) 0.197 Insomnia (%) 1012 (8.6) 500 (8.5) 512 (8.7) 0.756 Hyperthyroidism (%) 102 (0.9) 53 (0.9) 49 (0.8) 0.671 Hypothyroidism (%) 91 (0.8) 54 (0.9) 37 (0.6) 0.069 Gout (%) 2019 (17.2) 1164 (1.9) 855 (14.5) < 0.001 Drugs BZDs (%) 2473 (21) 1233 (21) 1240 (21) 0.987 Anticoagulants (%) 5060 (43) 2465 (42) 2595 (44) 0.029 NSAIDs (%) 4506 (38.3) 2220 (37.9) 2286 (38.8) 0.301 Acetaminophen (%) 4189 (35.6) 1997 (34.1) 2192 (37.2) < 0.001 Statin (%) 4655 (39.6) 2100 (35.8) 2555 (43.4) < 0.001 CCB (%) 6483 (55.1) 3143 (53.6) 3340 (56.7) < 0.001 ACEIs (%) 3463 (29.5) 1662 (28.3) 1801 (30.6) 0.008 ARBs (%) 5340 (45.4) 2465 (42.0) 2875 (48.8) < 0.001 Metformin (%) 7166 (61) 3411 (58.2) 3755 (63.7) < 0.001 Beta-Blocker (%) 4106 (34.9) 1997 (34.1) 2109 (35.8) 0.049 Diuretics (%) 4269 (36.3) 1873 (31.9) 2396 (40.7) < 0.001 Abbreviation: CHF, chronic heart failure; PAD, peripheral artery disease, COPD, chronic obstructive pulmonary disease, NSAID, non-steroid anti-inflammatory drug; BZD, benzodiazepine; CCB, calcium channel blocker ACEIs, angiotensin converting enzyme inhibitors; ARBs, angiotensin receptor blockers. The difference of baseline characteristics between insulin users and nonusers were also shown in Table 1 . Those with female gender, younger age, and the comorbidities of congestive heart failure, and peripheral artery disease; and without gout were prone to be prescribed insulin therapy (all p < 0.005). Moreover, the insulin users had higher opportunity to experience the prescription of ani-coagulation agents, acetaminophen, statin, calcium channel blocker, ACEIs, ARBs, metformin, beta-blocker, and diuretics (all p < 0.005). Risk analysis for developing dementia There were 1,285 events of dementia during a 11-year observation period. The possible risk factors that may contribute to the development of dementia are shown in Table 2 . In crude analysis, the female gender with older age and those who were recorded to have the following comorbidities: atrial fibrillation and insomnia; and the usage of the following drugs: benzodiazepines and metformin are shown to be at significant risk for the development of dementia but the comorbidity of chronic heart failure; and the usage of insulin, ACEIs and diuretics have significant risk reduction of dementia (all p < 0.05). Table 2 Risk for developing dementia in the CKD population with diabetes and hypertension Crude Multivariable HR (95%CI) p aHR (95%CI) p Insulin (vs. non) 0.628 (0.0.533–0.741) < 0.001 0.652 (0.552–0.771) < 0.001 Male (vs. female) 0.524 (0.444–0.619) < 0.001 0.571 (0.481–0.677) < 0.001 Age 20–39 (reference) 1 1 40–64 15.608 (3.899–62.485) < 0.001 14.136 (3.531–56.596) < 0.001 65–80 33.374 (8.362–133.208) < 0.001 29.828 (7.473–119.051) < 0.001 Comorbidities Ischemic Heart Disease (vs. non) 1.150 (0.958–1.381) 0.134 1.047 (0.857–1.280) 0.650 Hyperlipidemia (vs. non) 1.074 (0.914–1.262) 0.387 1.133 (0.947–1.356) 0.172 Atrial fibrillation (vs. non) 1.766 (1.036–3.011) 0.036 1.647 (0.972–2.792) 0.063 CHF (vs. non) 0.569 (0.380–0.859) 0.005 0.526 (0.345–0.802) 0.002 PAD (vs. non) 1.341 (0.923–1.948) 0.123 1.203 (0.817–1.772) 0.348 Asthma (vs. non) 1.300 (0.944–1.792) 0.108 1.206 (0.799–1.819) 0.373 COPD (vs. non) 1.220 (0.982–1.516) 0.073 1.038 (0.782–1.379) 0.794 Major depression (vs. non) 1.745 (0.958–3.177) 0.068 1.557 (0.839–2.887) 0.162 Parkinson's disease (vs. non) 0.623 (0.201–1.932) 0.412 0.416 (0.134–1.294) 0.129 Rheumatoid arthritis (vs. non) 1.426 (0.707–2.876) 0.321 1.211 (0.592–2.478) 0.599 Insomnia (vs. non) 1.610 (1.267–2.045) < 0.001 1.332 (1.030–1.722) 0.028 Hyperthyroidism (vs. non) 1.780 (0.927–3.415) 0.083 1.715 (0.888–3.314) 0.108 Hypothyroidism (vs. non) 0.874 (0.325–2.353) 0.790 0.711 (0.261–1.939) 0.504 Gout (vs. non) 0.998 (0.807–1.235) 0.987 1.026 (0.825–1.277) 0.816 Drugs BZDs (vs. non) 1.463 (1.223–1.751) < 0.001 1.232 (1.005–1.510) 0.045 Anticoagulants (vs. non) 1.163 (0.99–1.367) 0.066 1.101 (0.924–1.312) 0.282 NSAIDs (vs. non) 1.105 (0.938–1.302) 0.232 0.984 (0.825–1.174) 0.860 Acetaminophen (vs. non) 1.091 (0.924–1.288) 0.305 0.963 (0.804–1.153) 0.678 Statins (vs. non) 0.947 (0.802–1.117) 0.518 0.965 (0.802–1.162) 0.707 CCB (vs. non) 1.015 (0.864–1.194) 0.852 0.919 (0.778–1.086) 0.322 ACEI (vs. non) 0.734 (0.608–0.888) 0.001 0.717 (0.588–0.875) 0.001 ARB(vs. non) 0.892 (0.758–1.05) 0.169 0.819 (0.688–0.975) 0.024 Metformin (vs non) 1.227 (1.036–1.454) 0.018 1.279 (1.075–1.522) 0.005 Beta–blocker (vs. non) 0.900 (0.757–1.068) 0.227 0.883 (0.739–1.053) 0.166 Diuretic (vs. non) 0.791 (0.665–0.942) 0.008 0.792 (0.658–0.954) 0.013 Multivariable model: put all the parameters into analysis Abbreviation: CHF, chronic heart failure; PAD, peripheral artery disease, COPD, chronic obstructive pulmonary disease, NSAID, non-steroid anti-inflammatory drug; BZD, benzodiazepine ; CCB, calcium channel blocker ACEI, angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blockers. Table 3. Competing risk analysis of insulin usage effects on dementia by stepwise adjusting confounders Insulin (users vs. nonusers) Every incremental of MPR of insulin HR (95%CI) p value HR (95%CI) p value Crude 0.628 (0.533–0.741) < 0.001 0.994 (0.992–0.996) < 0.001 Model 1 0.631 (0.535–0.744) < 0.001 0.995 (0.992–0.997) < 0.001 Model 2 0.636 (0.539–0.751) < 0.001 0.995 (0.992–0.997) < 0.001 Model 3 0.652 (0.552–0.771) < 0.001 0.995 (0.993–0.998) < 0.001 Model 1 is adjusted for age and gender. Model 2 comprises model 2 as well as adjustments for comorbidities, including ischemic heart disease, hyperlipidemia, diabetes, atrial fibrillation, congestive heart failure, peripheral artery disease, asthma, chronic obstructive pulmonary disease, major depression, Parkinson’s disease, rheumatoid arthritis, insomnia, hyperthyroidism, hypothyroidism, and gout. Model 3 comprises model 2 as well as adjustments for medications of benzodiazepine, anticoagulants, non-steroid anti-inflammatory drug, acetaminophen, statins, calcium channel blocker, angiotensin converting enzyme inhibitors, angiotensin receptor blockades, metformin, beta–blocker and diuretics. Abbreviation: MPR, medication possession ratio; HR, hazard ratio; CI, confidence interval. Table 4. The dosing effect of insulin prescription on dementia Number aHR (95%CI) P value Trend test \(\text{M}\text{P}\text{R} \le 20\text{\%} \left(\text{r}\text{e}\text{f}\text{e}\text{r}\text{e}\text{n}\text{c}\text{e}\right)\) 6990 1 p = 0.001 20% < MPR \(\le\) 40% 481 0.755 (0.491–1.161) 0.201 40% < MPR \(\le\) 60% 419 0.880 (0.567–1.344) 0.554 60% \) 80% 2129 0.653 (0.511–0.833) < 0.001 Multivariable adjusting model as model 3 in table 3. Abbreviation: MPR, medication possession ratio; aHR, adjusted hazard ratio; CI, confidence interval. However, after multivariable adjusting, only the parameters of insulin usage, gender, age, chronic heart failure, and insomnia, and the usage of benzodiazepines, ACEIs, and metformin and diuretics kept the significancy (all p < 0.05). Interestingly, the protective effects of ARBs became significant on the incidence of dementia while the crude analysis showed insignificant. The effects of insulin usage on the incidence of dementia There were 376 events of dementia for insulin users and 909 events of dementia for insulin nonusers in this study. The fine and gray method curves for the adjusted cumulative hazards of dementia between insulin users and nonusers are significant ( \(\chi\) 2 = 5.67, p = 0.017) (Fig. 2 ). Throughout all models, insulin showed protective effects on the incidence of dementia and are detailed in Table 3. The effects of insulin usage (yes versus no) was investigated using 4 stepwise variables adjusting models, which the results were consistent in all the models (HRs were 0.628 [95% confidence interval (CI): 0.533–0.741]; 0.631 [95% CI: 0.535–0.744]; 0.636 [95% CI: 0.539–0.751] and 0.652 [95% CI: 0.552–0.771] respectively). Moreover, every 1 incremental of MPR of insulin also had significantly reduced risk for the incidence of dementia in the 4 regression models (HRs were 0.994 [95% CI: 0.992–0.996); 0.995 [95% CI: 0.992–0.997); 0.995 [95% CI: 0.992–0.997); 0.995 [95% CI: 0.993–0.998) respectively). The dosing effects of insulin usage on the incidence of dementia The dose effect of insulin on the incidence of dementia is detailed in Table 4. All groups had significant results compared to the group of MPR 80% had the best protective effects with a HR of 0.653 (95%CI: 0.511–0.833) and the other group has no significant risk difference. However, the Cochran-Armitage test indicated there was a significant dosing effect of insulin use on the preventing the incidence of dementia ( p < 0.001). Subgroup analysis The association of dementia incidence and insulin usage stratified by covariates was shown in Fig. 3 . The dementia protective effect of insulin use were consistent and kept significant throughout the almost subgroups in the hypertensive and diabetic CKD population but those with age 40–64 years, gout disease and ACEIs usage lost the significancy. Discussion The main finding from this nationwide cohort study is that long-term use of insulin exerted a significant protective effect on the developing of dementia in the hypertensive and diabetic CKD cohort. Such protective effect exhibited a dosing effect pattern. Moreover, the protective effect of insulin on dementia was consistently observed in almost all the subgroups. Using real-world data, our study extends the current knowledge in the field by indicating that early initiation of insulin therapy in the diabetic CKD population would be beneficial on preventing the developing of dementia. Insulin has a multifaceted implication in the CNS aside from the regulating glucose metabolism in peripheral tissues. In normal physiology, insulin crosses the blood–brain barrier via a receptor-mediated transport process, of which the rate was modulated by some conditions such as obesity and inflammation[ 28 ]. Insulin resistance, also known as impaired insulin sensitivity, is defined as a failure of target tissues to take a normal response to insulin. Several studies have investigated the relationship between insulin resistance and dementia including Alzheimer’s disease[ 29 , 30 ] and vascular cognitive impairment[ 31 , 32 ]. Insulin affects Alzheimer’s disease pathology directly by protecting against Aβ synaptotoxicity and modulates clearance through its effect. Insulin at normal concentrations acts as a proactive factor for cognitive impairment via its vasoactive effect on cerebral and peripheral blood flow by enhancing endothelial cells to release nitric oxide that dilates blood vessels [ 21 , 33 ]. However, insulin at high concentrations can alternatively constrict blood vessels by stimulating production of endothelin-1 via the mitogen-activated protein kinase pathway and insulin resistance-associated chronic hyperinsulinemia promotes vasoconstriction, resulting reduced blood supply to brain [ 34 ]. Intranasal insulin administration is a non-invasive method to deliver insulin to the brain parenchyma effectively, of which reaching cerebral concentrations is 100‐fold higher than intravenous delivery [ 35 ]. One meta-analysis synthesizing 7 randomized control trial had shown an improvement in verbal memory and especially story recall of apoe4 (−) patients with Alzheimer’s disease or mild cognitive impairment after intranasal insulin admiration [ 36 ]. Such strong evidence was compatible with the finding of benefit of insulin use on the incidence of dementia in our study. However, one meta-analysis pooling 5 observational cohort studies had shown that insulin treatment may be associated with increased adverse cognitive outcomes in diabetic patients [ 23 ]. The hypothesis for this discrepancy might be the insulin-induced hypoglycemia or the pitfall of observational study. Hypoglycemia episode in diabetic patients is a crucial risk factor for dementia in a systemic review and meta-analysis of 1.4 million patients [ 37 ]. The insulin resistance would become significant as the increase of DM duration and then the oral antidiabetic agents (OADs) would be shifted to insulin injection for the better sugar control. Therefore, diabetic patients with insulin use might indicate a high insulin resistance, which this is a pitfall in the observation study. The management of hyperglycemia in patients with CKD is especially difficult, requiring adjustment of OADs and insulin doses [ 38 ] because some OADs were contraindicated in CKD and insulin resistance might increase as the decline of renal function due to the accumulation of uremic toxins and inflammatory factors [ 39 ]. In our study we found that insulin use has a benefit in preventing dementia in diabetic CKD patients, indicating early initiating insulin therapy might be needed in such population to get a better sugar control and cognitive health. Our study has some strengths. First, the results are representative due to the study design of nationwide population-based cohort study. Second, the primary outcome of dementia was adequate to the statical interpretation under a long follow-up duration of 11 years. Moreover, to make sure the diagnose of dementia reliable and avoid the overcoding, easily seen in medical claim dataset, we used the approved application for the catastrophic illness certificate of dementia in the NHIRD, of which the diagnoses were made according to a strict protocol by neurologists or psychiatrist. Despite its strengths, our study still has some limitations. Information regarding potential confounding factors that are associated with dementia, including the body mass index, blood pressure, socioeconomic status, and lifestyle, was not available in the NHI database. Second, the severity of CKD stages and sugar control could not be determined in the NHIRD, which might bias our inference. Conclusion Our study provides insights into the protective effects of insulin on dementia in the hypertensive and diabetic CKD population. Therefore, we suggest early initiating insulin therapy might be beneficial in such population. Abbreviations CKD, Chronic kidney disease; ESKD, end stage of kidney disease; CNS, central nervous system; MPR, medication possession ratio; NSAIDs, non-steroidal anti-inflammatory drugs ; ACEIs, angiotensin converting enzyme inhibitors; ARBs, angiotensin receptor blockers; SD, standard deviation; HR, hazard ratio; CI, confidence interval; OADs, oral antidiabetic agents. Declarations (a) Ethics approval and consent to participate Before the NHIRD data was released for research, the personal information of all beneficiaries was de-identification and anonymous to ensure the privacy following rigorous secrecy guidelines. Therefore, informed consent was waived by the Ethics Review of Board Shin-Kong Wu Ho-Su Memorial Hospital (IRB approval number: No. 20200806R). (b) Consent for publication Not applicable (c) Availability of data and materials . The dataset used in this study is held by the Taiwan Ministry of Health and Welfare (MOHW). Any researcher interested in accessing this dataset can apply for access. Please visit the website of the National Health Informatics Project of the MOHW (https:// dep.mohw.gov.tw/dos/np-2497-113.html). (d) Competing interests The funding source played no role in this study. The authors report no conflicts of interest. (e) Funding The study was supported by a grant under a cooperative project between Shin Kong Wu Ho-Su Memorial Hospital and National Yang Ming Chiao Tung University in Taiwan (109GB006-2) and Shin Kong Wu Ho-Su Memorial Hospital, grant number 2023SKHADR036. (f) Authors' contributions Conceptualization: C-YY , F-YW, and C-YH; Data curation: C-YY; Formal analysis: T-MH, J-TN, and C-YY; Funding acquisition: T-MH and C-YY; Investigation: C-YY and F-YW; Methodology: C-YY, T-MH and F-YW; Supervision: C-YY and F-YW; Validation: C-YY; Visualization: T-MH, W-JT; Writing – original draft: T-MH; Writing – review & editing: T-MH and C-YY. All authors discussed the results and contributed to the final manuscript. (g) Acknowledgements Not applicable References Lv JC, Zhang LX: Prevalence and Disease Burden of Chronic Kidney Disease . Adv Exp Med Biol 2019, 1165 :3-15. Collaboration GBDCKD: Global, regional, and national burden of chronic kidney disease, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017 . Lancet 2020, 395 (10225):709-733. 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Helmer C, Stengel B, Metzger M, Froissart M, Massy ZA, Tzourio C, Berr C, Dartigues JF: Chronic kidney disease, cognitive decline, and incident dementia: the 3C Study . Neurology 2011, 77 (23):2043-2051. Lee CJ, Lee JY, Han K, Kim DH, Cho H, Kim KJ, Kang ES, Cha BS, Lee YH, Park S: Blood Pressure Levels and Risks of Dementia: a Nationwide Study of 4.5 Million People . Hypertension 2022, 79 (1):218-229. Reinke C, Buchmann N, Fink A, Tegeler C, Demuth I, Doblhammer G: Diabetes duration and the risk of dementia: a cohort study based on German health claims data . Age Ageing 2022, 51 (1). Spence JD: Preventing dementia by treating hypertension and preventing stroke . Hypertension 2004, 44 (1):20-21. Crane PK, Walker R, Hubbard RA, Li G, Nathan DM, Zheng H, Haneuse S, Craft S, Montine TJ, Kahn SE et al : Glucose levels and risk of dementia . N Engl J Med 2013, 369 (6):540-548. Chen YH, Chen YY, Fang YW, Tsai MH: Protective Effects of Angiotensin Receptor Blockers on the Incidence of Dementia in Patients with Chronic Kidney Disease: A Population-Based Nationwide Study . J Clin Med 2021, 10 (21). Li NC, Lee A, Whitmer RA, Kivipelto M, Lawler E, Kazis LE, Wolozin B: Use of angiotensin receptor blockers and risk of dementia in a predominantly male population: prospective cohort analysis . BMJ 2010, 340 :b5465. Kleinridders A, Ferris HA, Cai W, Kahn CR: Insulin action in brain regulates systemic metabolism and brain function . Diabetes 2014, 63 (7):2232-2243. Folch J, Olloquequi J, Ettcheto M, Busquets O, Sanchez-Lopez E, Cano A, Espinosa-Jimenez T, Garcia ML, Beas-Zarate C, Casadesus G et al : The Involvement of Peripheral and Brain Insulin Resistance in Late Onset Alzheimer's Dementia . Front Aging Neurosci 2019, 11 :236. Kellar D, Craft S: Brain insulin resistance in Alzheimer's disease and related disorders: mechanisms and therapeutic approaches . Lancet Neurol 2020, 19 (9):758-766. Craft S, Raman R, Chow TW, Rafii MS, Sun CK, Rissman RA, Donohue MC, Brewer JB, Jenkins C, Harless K et al : Safety, Efficacy, and Feasibility of Intranasal Insulin for the Treatment of Mild Cognitive Impairment and Alzheimer Disease Dementia: A Randomized Clinical Trial . JAMA Neurol 2020, 77 (9):1099-1109. Weinstein G, Davis-Plourde KL, Conner S, Himali JJ, Beiser AS, Lee A, Rawlings AM, Sedaghat S, Ding J, Moshier E et al : Association of metformin, sulfonylurea and insulin use with brain structure and function and risk of dementia and Alzheimer's disease: Pooled analysis from 5 cohorts . PLoS One 2019, 14 (2):e0212293. Maimaiti S, Anderson KL, DeMoll C, Brewer LD, Rauh BA, Gant JC, Blalock EM, Porter NM, Thibault O: Intranasal Insulin Improves Age-Related Cognitive Deficits and Reverses Electrophysiological Correlates of Brain Aging . J Gerontol A Biol Sci Med Sci 2016, 71 (1):30-39. Hsieh CY, Su CC, Shao SC, Sung SF, Lin SJ, Kao Yang YH, Lai EC: Taiwan's National Health Insurance Research Database: past and future . Clin Epidemiol 2019, 11 :349-358. Bjarnadottir MV, Czerwinski D, Onukwugha E: Sensitivity of the Medication Possession Ratio to Modelling Decisions in Large Claims Databases . Pharmacoeconomics 2018, 36 (3):369-380. Hsu JY, Roy JA, Xie D, Yang W, Shou H, Anderson AH, Landis JR, Jepson C, Wolf M, Isakova T et al : Statistical Methods for Cohort Studies of CKD: Survival Analysis in the Setting of Competing Risks . Clin J Am Soc Nephrol 2017, 12 (7):1181-1189. Scherer T, Sakamoto K, Buettner C: Brain insulin signalling in metabolic homeostasis and disease . Nat Rev Endocrinol 2021, 17 (8):468-483. Xu WL, von Strauss E, Qiu CX, Winblad B, Fratiglioni L: Uncontrolled diabetes increases the risk of Alzheimer's disease: a population-based cohort study . Diabetologia 2009, 52 (6):1031-1039. Verdile G, Keane KN, Cruzat VF, Medic S, Sabale M, Rowles J, Wijesekara N, Martins RN, Fraser PE, Newsholme P: Inflammation and Oxidative Stress: The Molecular Connectivity between Insulin Resistance, Obesity, and Alzheimer's Disease . Mediators Inflamm 2015, 2015 :105828. Kong SH, Park YJ, Lee JY, Cho NH, Moon MK: Insulin Resistance is Associated with Cognitive Decline Among Older Koreans with Normal Baseline Cognitive Function: A Prospective Community-Based Cohort Study . Sci Rep 2018, 8 (1):650. Ekblad LL, Rinne JO, Puukka P, Laine H, Ahtiluoto S, Sulkava R, Viitanen M, Jula A: Insulin Resistance Predicts Cognitive Decline: An 11-Year Follow-up of a Nationally Representative Adult Population Sample . Diabetes Care 2017, 40 (6):751-758. Ferreira LSS, Fernandes CS, Vieira MNN, De Felice FG: Insulin Resistance in Alzheimer's Disease . Front Neurosci 2018, 12 :830. Muniyappa R, Yavuz S: Metabolic actions of angiotensin II and insulin: a microvascular endothelial balancing act . Mol Cell Endocrinol 2013, 378 (1-2):59-69. Hallschmid M: Intranasal insulin . J Neuroendocrinol 2021, 33 (4):e12934. Avgerinos KI, Kalaitzidis G, Malli A, Kalaitzoglou D, Myserlis PG, Lioutas VA: Intranasal insulin in Alzheimer's dementia or mild cognitive impairment: a systematic review . J Neurol 2018, 265 (7):1497-1510. Huang L, Zhu M, Ji J: Association between hypoglycemia and dementia in patients with diabetes: a systematic review and meta-analysis of 1.4 million patients . Diabetol Metab Syndr 2022, 14 (1):31. Betonico CC, Titan SM, Correa-Giannella ML, Nery M, Queiroz M: Management of diabetes mellitus in individuals with chronic kidney disease: therapeutic perspectives and glycemic control . Clinics (Sao Paulo) 2016, 71 (1):47-53. Kosmas CE, Silverio D, Tsomidou C, Salcedo MD, Montan PD, Guzman E: The Impact of Insulin Resistance and Chronic Kidney Disease on Inflammation and Cardiovascular Disease . Clin Med Insights Endocrinol Diabetes 2018, 11 :1179551418792257. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 25 Apr, 2025 Read the published version in BMC Nephrology → Version 1 posted Editorial decision: Revision requested 13 Feb, 2025 Reviews received at journal 01 Feb, 2025 Reviewers agreed at journal 22 Jan, 2025 Reviewers agreed at journal 21 Jan, 2025 Reviews received at journal 22 Dec, 2024 Reviewers agreed at journal 11 Dec, 2024 Reviewers agreed at journal 06 Dec, 2024 Reviewers invited by journal 04 Dec, 2024 Editor assigned by journal 03 Dec, 2024 Editor invited by journal 06 May, 2024 Submission checks completed at journal 02 May, 2024 First submitted to journal 26 Apr, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4329846","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":299233834,"identity":"f143aef0-0d32-4a07-ae93-7259a7cb8621","order_by":0,"name":"Yun-Yi Chen","email":"","orcid":"","institution":"National Yang-Ming Chiao Tung University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yun-Yi","middleName":"","lastName":"Chen","suffix":""},{"id":299233836,"identity":"9c5788ed-3f7b-4ea9-b4a2-17e42904b422","order_by":1,"name":"Yi-Hsien Chen","email":"","orcid":"","institution":"Shin-Kong Wu Ho-Su Memorial Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yi-Hsien","middleName":"","lastName":"Chen","suffix":""},{"id":299233838,"identity":"b6e0830c-e1c0-4f6a-be6a-ec5fc1322395","order_by":2,"name":"Yu-Wei Fang","email":"","orcid":"","institution":"Shin-Kong Wu Ho-Su Memorial Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yu-Wei","middleName":"","lastName":"Fang","suffix":""},{"id":299233840,"identity":"d83444c0-b3dd-48c3-be07-b9f6f77f4b4f","order_by":3,"name":"Jing-Tong Wang","email":"","orcid":"","institution":"Shin-Kong Wu Ho-Su Memorial Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jing-Tong","middleName":"","lastName":"Wang","suffix":""},{"id":299233842,"identity":"368dc913-a672-4833-a863-0c0601fb8fac","order_by":4,"name":"Ming-Hsien Tsai","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYDACCShtACI+ADEbO5FaJAwYmBkYZ4C0MJOihZkHxCSkhX9288OHP3MO15kz8B+Ttvm1TZ4PaNuHjzl4LLlzzNiYd9thCcsGZjbp3L7bhm1A2yRnbsOtxUAiwUyaEajF4AAz2+3cntuMQC1szLx4taR/k/wJ02LZc9ueCC05ZhK8MC0MP24nEtQicSOnGOiXdMkNh5nNf/Y23E5uY2ZsxusX/hnpGx/+3GbNb3C88bHBjz+3bee3Nx/88BGPFihohkQHYxuIw9hAUD0Q1EHpP8QoHgWjYBSMgpEGAIFpTDZgnouLAAAAAElFTkSuQmCC","orcid":"","institution":"Shin-Kong Wu Ho-Su Memorial Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Ming-Hsien","middleName":"","lastName":"Tsai","suffix":""}],"badges":[],"createdAt":"2024-04-26 13:23:43","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4329846/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4329846/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12882-025-04145-9","type":"published","date":"2025-04-25T15:58:28+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":56198315,"identity":"1ee10511-16d0-4419-9c9a-489346f74c0e","added_by":"auto","created_at":"2024-05-09 18:30:10","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":156422,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of patient enrollment in the study\u003c/p\u003e","description":"","filename":"Figure1flowchart.png","url":"https://assets-eu.researchsquare.com/files/rs-4329846/v1/e9f675e061c5c6849f3bf76e.png"},{"id":56198636,"identity":"9c5b3d3d-db30-456d-8c45-b7d57eedef1a","added_by":"auto","created_at":"2024-05-09 18:38:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":232590,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of the cumulative incidence of dementia between insulin users and nonusers. The curves show a lower risk of dementia diagnosis in the group of insulin users. The sub-distribution hazard ratio considered death as a competing risk. The plot was truncated at the 10th year. CI, confidence interval.\u003c/p\u003e","description":"","filename":"Figure2culmulativeindicence.png","url":"https://assets-eu.researchsquare.com/files/rs-4329846/v1/9a327c99bdfff93cbf3b3c89.png"},{"id":56199561,"identity":"f6619d23-7571-427f-bb46-7afa59837077","added_by":"auto","created_at":"2024-05-09 18:46:09","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":813427,"visible":true,"origin":"","legend":"\u003cp\u003eSubgroup analysis of the effect of insulin use on the incidence of dementia in the multivariable adjusting model*.\u003c/p\u003e\n\u003cp\u003e*The full adjusting model was the same as the full adjusting model in table 2\u003c/p\u003e","description":"","filename":"Figure3subgroup.png","url":"https://assets-eu.researchsquare.com/files/rs-4329846/v1/148f0a359eecae0d0bea1945.png"},{"id":81569985,"identity":"081e557d-5f9a-4e32-ab61-722467cc724d","added_by":"auto","created_at":"2025-04-28 16:12:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3915752,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4329846/v1/2e28715b-30a5-44c5-acd4-67f5881dfc28.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Protective Effects of Insulin on the Developing of Dementia in Chronic Kidney Disease Patients with hypertension and diabetes: A Population-Based Nationwide Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChronic kidney disease (CKD) is a global health and financial issue nowadays with an estimated prevalence of 13.4% [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In Taiwan, it had been reported a higher CKD (stages 1\u0026ndash;5) prevalence 15.5% [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] and a highest incidence of end stage of kidney disease (ESKD) in the world [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Moreover, CKD causes a considerable financial burden because it would lead to ESKD requiring dialysis and increase the risk of cardiovascular mortality and morbidity as the decline of renal function [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDementia, an allover term for neurodegeneration disease aside from normal brain aging, is a major healthy concern in the elderly worldwide[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] with an forecasted all-cause dementia prevalence to 152\u0026nbsp;million by 2050 [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Alzheimer's disease accounts for 60\u0026ndash;80% of cases and vascular dementia is the second most common cause of dementia [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The treatment strategies includes both non-pharmacologic approaches and pharmacologic approaches, but the efficacy of treatments remains limited [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Currently, identifying the modifiable risk factors is the main strategy to prevent dementia according to the clinical guideline[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePrior studies have found CKD to be an independent risk factor for cognitive impairment and dementia developing [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Moreover, hypertension and diabetes were both the well-known risk factors for the development of dementia[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Adequate hypertension control and sugar control has been shown to lower the risk of dementia [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Aside from blood pressure control, the renin-angiotensin-aldosterone system blockades has been shown beneficial for the dementia development in CKD population[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Insulin plays a crucial role in central nervous system (CNS) health not just via the decreasing the serum sugar level [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The insulin dysregulation can contribute to conditions of pathological brain aging, such as Alzheimer\u0026rsquo;s disease and vascular cognitive impairment [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], suggesting that the insulin injection might be a promising therapy for the preventing of dementia.\u003c/p\u003e \u003cp\u003eHowever, the relationship of insulin use and cognitive health are inconsistent in the literatures [\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In addition, no data was available for insulin control in the prevention dementia in CKD patients. Thus, we aim to use the National Health Insurance database (NHIRD) to analyze the association of insulin use and the development of dementia within the diabetic and hypertensive CKD population in a real word performance.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData source and research samples\u003c/h2\u003e \u003cp\u003eA CKD thematic data was used from the NHIRD maintained by the Health and Welfare Data Science Center, Ministry of Health and Welfare, Taiwan, of which the detail was prescribed in the previous publication [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. NHIRD contains the claims records of health care utilization of 99.9% of Taiwan\u0026rsquo;s 23\u0026nbsp;million population enrolled in the Taiwan National Health Insurance program[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The deidentified information retained in the data included date of birth, sex, residency area, diagnostic codes, medical procedures, and drug prescriptions. Before the NHIRD data was released for research, the personal information of all beneficiaries was de-identification and anonymous to ensure the privacy following rigorous secrecy guidelines. Therefore, informed consent was waived by the Ethics Review of Board Shin-Kong Wu Ho-Su Memorial Hospital (IRB approval number: No. 20200806R).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and study population\u003c/h2\u003e \u003cp\u003eThe study was designed as a population-based longitudinal cohort study. The selected population were CKD patients diagnosed with hypertension (ICD-10: I10\u0026ndash;I15) and diabetes (ICD-10: E08\u0026ndash;E13) from January 1, 2006, through December 31, 2006. (n\u0026thinsp;=\u0026thinsp;18,434). Patients who had previously been diagnosed with malignancy (ICD-10: C00-C96,D45, D47.Z9, E31.22, Z51.12), dementia (ICD-10: F01.50, F01.51, F03.90, and F03.91), cerebrovascular diseases (ICD-10: I60- I63, I65-I69, and G45-G46) were excluded. Patients under regular hemodialysis, peritoneal dialysis, or previously underwent renal transplantation were also excluded. Moreover, patients with ages under 20 years or above 80, or with missing information were also excluded. Finally, a total 11,758 CKD patients with hypertension and diabetes were chosen into analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The index date was defined as January 1, 2007. The data was analyzed from the index date to the first instance of the desired outcome, dementia, or to the end of the observation date (December 31, 2017).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eExposure to study drugs\u003c/h2\u003e \u003cp\u003eWe used medication possession ratio (MPR) to calculate the degree how the patients had been prescribed the medication of insulin during the following period. MPR is measured as the sum of the days of a given drug in observation period, divided by the total number of days in the observation period [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. We also defined insulin non-users as the MPR\u0026thinsp;=\u0026thinsp;0% and insulin users as the MPR\u0026thinsp;\u0026gt;\u0026thinsp;0%.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eCovariates\u003c/h2\u003e \u003cp\u003eBaseline comorbidities, including ischemic heart disease (ICD-10: I10\u0026ndash;I15), hyperlipidemia (ICD-10: E78), atrial fibrillation (ICD-10:I48), chronic heart failure (ICD-10: I50), peripheral artery disease (ICD-10: I70.2\u0026ndash;I70.9), asthma (ICD-10: J45), chronic obstructive pulmonary disease (ICD-10: J44), major depression disease (ICD-10: F32\u0026ndash;F33), Parkinson\u0026rsquo;s disease (ICD-10: G20\u0026ndash;G21), rheumatic arthritis (ICD-10: M05\u0026ndash;M06), hyperthyroidism (ICD-10: E05), hypothyroidism (ICD-10: E01.8 and E02\u0026ndash;E03), gout (ICD-10: M10), and insomnia (ICD-10: G47.0, and F51.0) was defined as having at least 3 outpatient diagnoses or 1 inpatient diagnosis usage within 1 year before the index date. Usage of other drugs, including benzodiazepines, anticoagulants, non-steroidal anti-inflammatory drugs (NSAIDs), acetaminophen, statins, calcium channel blockers, angiotensin converting enzyme inhibitors (ACEIs), angiotensin receptor blockers (ARBs), metformin, beta-blockers, and diuretics was defined as having at least 3 months of usage within 1 year before the index date.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eOutcome measurement\u003c/h2\u003e \u003cp\u003eDementia, the main outcome of this study, was identified if a person qualified for a Severe Illness IC Card for dementia from the Taiwan National Health Insurance Administration. This was based on diagnoses by a licensed neurologist or psychiatrist.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eContinuous data of baseline characteristics is expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD), while categorical data is expressed as counts with proportions. The difference between groups (insulin users vs non-users) was compared using Chi-squared tests for portion and t-tests for means of continuous variables. Competing risk regression analyses were conducted for dementia developing (all-cause death was considered as a competing event) using the method described by Fine and Gray [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The stratified proportional sub-distribution hazard ratio (HR) was calculated to estimate the exposure and covariate effects on the cumulative incidence function.\u003c/p\u003e \u003cp\u003eTo assess the robustness of our findings, we added the variables of demographic data, comorbidities, and medications into multivariable regression models step by step. We also did the analyses of dosing effect of insulin on the prevention of dementia, which a Cochran-Armitage test was used for testing the dosing effect of insulin. We stratified insulin users by MPR rates, sorting them in the following groups: those with \u0026le;\u0026thinsp;20% MPR, those with MPR\u0026thinsp;\u0026gt;\u0026thinsp;80% and sorted those with 20\u0026ndash;80% MPR into groups per 20% MPR. We used the group with \u0026le;\u0026thinsp;20% MPR as our reference point.\u003c/p\u003e \u003cp\u003eFinally, we performed a subgroup analysis by the age, gender, commodities and medications to test the consistency of the insulin protective effect on dementia in CKD population with diabetes and hypertension. If the groups with a portion of patients number\u0026thinsp;\u0026lt;\u0026thinsp;10% were excluded from subgroup analysis.\u003c/p\u003e \u003cp\u003eAll statistical analyses were created by version 9.4 of SAS (SAS Institute, Cary, NC, USA) software. For all tests, a 2-sided p-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered as indicative of statistical significance.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003ePatient Characteristics\u003c/h2\u003e \u003cp\u003eWe enrolled 11,758 CKD patients with hypertension and diabetes in the present study (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The mean age of the enrolled patients was 62.1\u0026thinsp;\u0026plusmn;\u0026thinsp;10.9 years, while 47% were women and 52.6% were hyperlipidemic. Among them, 5,864 patients had experienced insulin prescriptions and others (5,894) were insulin nonusers.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline Characteristics of CKD patients with hypertension and diabetes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;11,758)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInsulin non-users\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;5,864)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInsulin users\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;5,894)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6236 (53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3205 (54.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3031 (51.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5522 (47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2659 (45.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2863 (48.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62.1 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e 10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.6 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e 10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61.7 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;39 (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e860 (7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e398 (6.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e462 (7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;64 (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5794 (49.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2829 (48.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2965 (50.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e65\u0026ndash;80 (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5104 (43.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2637 (45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2467 (41.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidities\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIschemic Heart Disease (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2794 (23.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1352 (23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1442 (24.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperlipidemia (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6186 (52.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3075 (52.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3111 (52.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.708\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAtrial Fibrillation (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e163 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHF (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e839 (7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e357 (6.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e482 (8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAD (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e439 (3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e192 (3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e247 (4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsthma (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e624 (5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e298 (5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e326 (5.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.277\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1631 (13.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e784 (13.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e847 (14.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.116\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMajor Depressive Disorder (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e129 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.315\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParkinson's Disease (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.312\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRheumatoid Arthritis (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e114 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.197\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsomnia (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1012 (8.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e500 (8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e512 (8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.756\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperthyroidism (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e102 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.671\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypothyroidism (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGout (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2019 (17.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1164 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e855 (14.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDrugs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBZDs (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2473 (21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1233 (21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1240 (21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.987\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnticoagulants (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5060 (43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2465 (42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2595 (44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNSAIDs (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4506 (38.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2220 (37.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2286 (38.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.301\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcetaminophen (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4189 (35.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1997 (34.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2192 (37.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStatin (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4655 (39.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2100 (35.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2555 (43.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCB (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6483 (55.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3143 (53.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3340 (56.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACEIs (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3463 (29.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1662 (28.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1801 (30.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARBs (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5340 (45.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2465 (42.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2875 (48.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetformin (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7166 (61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3411 (58.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3755 (63.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeta-Blocker (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4106 (34.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1997 (34.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2109 (35.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiuretics (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4269 (36.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1873 (31.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2396 (40.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eAbbreviation: CHF, chronic heart failure; PAD, peripheral artery disease, COPD, chronic obstructive pulmonary disease, NSAID, non-steroid anti-inflammatory drug; BZD, benzodiazepine; CCB, calcium channel blocker ACEIs, angiotensin converting enzyme inhibitors; ARBs, angiotensin receptor blockers.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe difference of baseline characteristics between insulin users and nonusers were also shown in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Those with female gender, younger age, and the comorbidities of congestive heart failure, and peripheral artery disease; and without gout were prone to be prescribed insulin therapy (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.005). Moreover, the insulin users had higher opportunity to experience the prescription of ani-coagulation agents, acetaminophen, statin, calcium channel blocker, ACEIs, ARBs, metformin, beta-blocker, and diuretics (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.005).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRisk analysis for developing dementia\u003c/h2\u003e \u003cp\u003eThere were 1,285 events of dementia during a 11-year observation period. The possible risk factors that may contribute to the development of dementia are shown in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. In crude analysis, the female gender with older age and those who were recorded to have the following comorbidities: atrial fibrillation and insomnia; and the usage of the following drugs: benzodiazepines and metformin are shown to be at significant risk for the development of dementia but the comorbidity of chronic heart failure; and the usage of insulin, ACEIs and diuretics have significant risk reduction of dementia (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRisk for developing dementia in the CKD population with diabetes and hypertension\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCrude\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eMultivariable\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eaHR (95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsulin (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.628 (0.0.533\u0026ndash;0.741)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.652 (0.552\u0026ndash;0.771)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale (vs. female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.524 (0.444\u0026ndash;0.619)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.571 (0.481\u0026ndash;0.677)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;39 (reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.608 (3.899\u0026ndash;62.485)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.136 (3.531\u0026ndash;56.596)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e65\u0026ndash;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.374 (8.362\u0026ndash;133.208)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.828 (7.473\u0026ndash;119.051)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidities\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIschemic Heart Disease (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.150 (0.958\u0026ndash;1.381)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.047 (0.857\u0026ndash;1.280)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.650\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperlipidemia (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.074 (0.914\u0026ndash;1.262)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.133 (0.947\u0026ndash;1.356)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.172\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAtrial fibrillation (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.766 (1.036\u0026ndash;3.011)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.647 (0.972\u0026ndash;2.792)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHF (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.569 (0.380\u0026ndash;0.859)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.526 (0.345\u0026ndash;0.802)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAD (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.341 (0.923\u0026ndash;1.948)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.203 (0.817\u0026ndash;1.772)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.348\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsthma (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.300 (0.944\u0026ndash;1.792)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.206 (0.799\u0026ndash;1.819)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.373\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.220 (0.982\u0026ndash;1.516)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.038 (0.782\u0026ndash;1.379)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.794\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMajor depression (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.745 (0.958\u0026ndash;3.177)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.557 (0.839\u0026ndash;2.887)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.162\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParkinson's disease (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.623 (0.201\u0026ndash;1.932)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.416 (0.134\u0026ndash;1.294)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRheumatoid arthritis (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.426 (0.707\u0026ndash;2.876)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.211 (0.592\u0026ndash;2.478)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.599\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsomnia (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.610 (1.267\u0026ndash;2.045)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.332 (1.030\u0026ndash;1.722)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperthyroidism (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.780 (0.927\u0026ndash;3.415)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.715 (0.888\u0026ndash;3.314)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypothyroidism (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.874 (0.325\u0026ndash;2.353)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.790\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.711 (0.261\u0026ndash;1.939)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.504\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGout (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.998 (0.807\u0026ndash;1.235)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.987\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.026 (0.825\u0026ndash;1.277)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.816\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDrugs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBZDs (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.463 (1.223\u0026ndash;1.751)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.232 (1.005\u0026ndash;1.510)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnticoagulants (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.163 (0.99\u0026ndash;1.367)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.101 (0.924\u0026ndash;1.312)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.282\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNSAIDs (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.105 (0.938\u0026ndash;1.302)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.984 (0.825\u0026ndash;1.174)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.860\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcetaminophen (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.091 (0.924\u0026ndash;1.288)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.963 (0.804\u0026ndash;1.153)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.678\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStatins (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.947 (0.802\u0026ndash;1.117)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.965 (0.802\u0026ndash;1.162)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.707\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCB (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.015 (0.864\u0026ndash;1.194)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.852\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.919 (0.778\u0026ndash;1.086)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.322\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACEI (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.734 (0.608\u0026ndash;0.888)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.717 (0.588\u0026ndash;0.875)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARB(vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.892 (0.758\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.819 (0.688\u0026ndash;0.975)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetformin (vs non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.227 (1.036\u0026ndash;1.454)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.279 (1.075\u0026ndash;1.522)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeta\u0026ndash;blocker (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.900 (0.757\u0026ndash;1.068)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.883 (0.739\u0026ndash;1.053)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.166\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiuretic (vs. non)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.791 (0.665\u0026ndash;0.942)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.792 (0.658\u0026ndash;0.954)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eMultivariable model: put all the parameters into analysis\u003c/p\u003e \u003cp\u003eAbbreviation: CHF, chronic heart failure; PAD, peripheral artery disease, COPD, chronic obstructive pulmonary disease, NSAID, non-steroid anti-inflammatory drug; BZD, benzodiazepine ; CCB, calcium channel blocker ACEI, angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blockers.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eTable\u0026nbsp;3. Competing risk analysis of insulin usage effects on dementia by stepwise adjusting confounders\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eInsulin (users vs. nonusers)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eEvery incremental of MPR of insulin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrude\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.628 (0.533\u0026ndash;0.741)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.994 (0.992\u0026ndash;0.996)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.631 (0.535\u0026ndash;0.744)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.995 (0.992\u0026ndash;0.997)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.636 (0.539\u0026ndash;0.751)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.995 (0.992\u0026ndash;0.997)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.652 (0.552\u0026ndash;0.771)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.995 (0.993\u0026ndash;0.998)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eModel 1 is adjusted for age and gender. Model 2 comprises model 2 as well as adjustments for comorbidities, including ischemic heart disease, hyperlipidemia, diabetes, atrial fibrillation, congestive heart failure, peripheral artery disease, asthma, chronic obstructive pulmonary disease, major depression, Parkinson\u0026rsquo;s disease, rheumatoid arthritis, insomnia, hyperthyroidism, hypothyroidism, and gout. Model 3 comprises model 2 as well as adjustments for medications of benzodiazepine, anticoagulants, non-steroid anti-inflammatory drug, acetaminophen, statins, calcium channel blocker, angiotensin converting enzyme inhibitors, angiotensin receptor blockades, metformin, beta\u0026ndash;blocker and diuretics.\u003c/p\u003e \u003cp\u003eAbbreviation: MPR, medication possession ratio; HR, hazard ratio; CI, confidence interval.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eTable\u0026nbsp;4. The dosing effect of insulin prescription on dementia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eaHR (95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTrend test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\text{M}\\text{P}\\text{R} \\le 20\\text{\\%} \\left(\\text{r}\\text{e}\\text{f}\\text{e}\\text{r}\\text{e}\\text{n}\\text{c}\\text{e}\\right)\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20% \u0026lt; MPR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\le\\)\u003c/span\u003e\u003c/span\u003e 40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.755 (0.491\u0026ndash;1.161)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40% \u0026lt; MPR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\le\\)\u003c/span\u003e\u003c/span\u003e 60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e419\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.880 (0.567\u0026ndash;1.344)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60% \u0026lt; MPR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\le\\)\u003c/span\u003e\u003c/span\u003e 80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.676 (0.422\u0026ndash;1.081)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMPR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\u0026gt;\\)\u003c/span\u003e\u003c/span\u003e 80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.653 (0.511\u0026ndash;0.833)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eMultivariable adjusting model as model 3 in table 3.\u003c/p\u003e \u003cp\u003eAbbreviation: MPR, medication possession ratio; aHR, adjusted hazard ratio; CI, confidence interval.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eHowever, after multivariable adjusting, only the parameters of insulin usage, gender, age, chronic heart failure, and insomnia, and the usage of benzodiazepines, ACEIs, and metformin and diuretics kept the significancy (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Interestingly, the protective effects of ARBs became significant on the incidence of dementia while the crude analysis showed insignificant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eThe effects of insulin usage on the incidence of dementia\u003c/h2\u003e \u003cp\u003eThere were 376 events of dementia for insulin users and 909 events of dementia for insulin nonusers in this study. The fine and gray method curves for the adjusted cumulative hazards of dementia between insulin users and nonusers are significant (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\chi\\)\u003c/span\u003e\u003c/span\u003e\u003csup\u003e2\u003c/sup\u003e = 5.67, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.017) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Throughout all models, insulin showed protective effects on the incidence of dementia and are detailed in Table\u0026nbsp;3. The effects of insulin usage (yes versus no) was investigated using 4 stepwise variables adjusting models, which the results were consistent in all the models (HRs were 0.628 [95% confidence interval (CI): 0.533\u0026ndash;0.741]; 0.631 [95% CI: 0.535\u0026ndash;0.744]; 0.636 [95% CI: 0.539\u0026ndash;0.751] and 0.652 [95% CI: 0.552\u0026ndash;0.771] respectively). Moreover, every 1 incremental of MPR of insulin also had significantly reduced risk for the incidence of dementia in the 4 regression models (HRs were 0.994 [95% CI: 0.992\u0026ndash;0.996); 0.995 [95% CI: 0.992\u0026ndash;0.997); 0.995 [95% CI: 0.992\u0026ndash;0.997); 0.995 [95% CI: 0.993\u0026ndash;0.998) respectively).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eThe dosing effects of insulin usage on the incidence of dementia\u003c/h2\u003e \u003cp\u003eThe dose effect of insulin on the incidence of dementia is detailed in Table\u0026nbsp;4. All groups had significant results compared to the group of MPR\u0026thinsp;\u0026lt;\u0026thinsp;20%. The group with MPR of \u0026gt;\u0026thinsp;80% had the best protective effects with a HR of 0.653 (95%CI: 0.511\u0026ndash;0.833) and the other group has no significant risk difference. However, the Cochran-Armitage test indicated there was a significant dosing effect of insulin use on the preventing the incidence of dementia (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup analysis\u003c/h2\u003e \u003cp\u003eThe association of dementia incidence and insulin usage stratified by covariates was shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The dementia protective effect of insulin use were consistent and kept significant throughout the almost subgroups in the hypertensive and diabetic CKD population but those with age 40\u0026ndash;64 years, gout disease and ACEIs usage lost the significancy.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe main finding from this nationwide cohort study is that long-term use of insulin exerted a significant protective effect on the developing of dementia in the hypertensive and diabetic CKD cohort. Such protective effect exhibited a dosing effect pattern. Moreover, the protective effect of insulin on dementia was consistently observed in almost all the subgroups. Using real-world data, our study extends the current knowledge in the field by indicating that early initiation of insulin therapy in the diabetic CKD population would be beneficial on preventing the developing of dementia.\u003c/p\u003e \u003cp\u003eInsulin has a multifaceted implication in the CNS aside from the regulating glucose metabolism in peripheral tissues. In normal physiology, insulin crosses the blood\u0026ndash;brain barrier via a receptor-mediated transport process, of which the rate was modulated by some conditions such as obesity and inflammation[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Insulin resistance, also known as impaired insulin sensitivity, is defined as a failure of target tissues to take a normal response to insulin. Several studies have investigated the relationship between insulin resistance and dementia including Alzheimer\u0026rsquo;s disease[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] and vascular cognitive impairment[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Insulin affects Alzheimer\u0026rsquo;s disease pathology directly by protecting against Aβ synaptotoxicity and modulates clearance through its effect. Insulin at normal concentrations acts as a proactive factor for cognitive impairment via its vasoactive effect on cerebral and peripheral blood flow by enhancing endothelial cells to release nitric oxide that dilates blood vessels [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. However, insulin at high concentrations can alternatively constrict blood vessels by stimulating production of endothelin-1 via the mitogen-activated protein kinase pathway and insulin resistance-associated chronic hyperinsulinemia promotes vasoconstriction, resulting reduced blood supply to brain [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIntranasal insulin administration is a non-invasive method to deliver insulin to the brain parenchyma effectively, of which reaching cerebral concentrations is 100‐fold higher than intravenous delivery [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. One meta-analysis synthesizing 7 randomized control trial had shown an improvement in verbal memory and especially story recall of apoe4 (\u0026minus;) patients with Alzheimer\u0026rsquo;s disease or mild cognitive impairment after intranasal insulin admiration [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Such strong evidence was compatible with the finding of benefit of insulin use on the incidence of dementia in our study. However, one meta-analysis pooling 5 observational cohort studies had shown that insulin treatment may be associated with increased adverse cognitive outcomes in diabetic patients [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The hypothesis for this discrepancy might be the insulin-induced hypoglycemia or the pitfall of observational study. Hypoglycemia episode in diabetic patients is a crucial risk factor for dementia in a systemic review and meta-analysis of 1.4\u0026nbsp;million patients [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The insulin resistance would become significant as the increase of DM duration and then the oral antidiabetic agents (OADs) would be shifted to insulin injection for the better sugar control. Therefore, diabetic patients with insulin use might indicate a high insulin resistance, which this is a pitfall in the observation study.\u003c/p\u003e \u003cp\u003eThe management of hyperglycemia in patients with CKD is especially difficult, requiring adjustment of OADs and insulin doses [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] because some OADs were contraindicated in CKD and insulin resistance might increase as the decline of renal function due to the accumulation of uremic toxins and inflammatory factors [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. In our study we found that insulin use has a benefit in preventing dementia in diabetic CKD patients, indicating early initiating insulin therapy might be needed in such population to get a better sugar control and cognitive health.\u003c/p\u003e \u003cp\u003eOur study has some strengths. First, the results are representative due to the study design of nationwide population-based cohort study. Second, the primary outcome of dementia was adequate to the statical interpretation under a long follow-up duration of 11 years. Moreover, to make sure the diagnose of dementia reliable and avoid the overcoding, easily seen in medical claim dataset, we used the approved application for the catastrophic illness certificate of dementia in the NHIRD, of which the diagnoses were made according to a strict protocol by neurologists or psychiatrist. Despite its strengths, our study still has some limitations. Information regarding potential confounding factors that are associated with dementia, including the body mass index, blood pressure, socioeconomic status, and lifestyle, was not available in the NHI database. Second, the severity of CKD stages and sugar control could not be determined in the NHIRD, which might bias our inference.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study provides insights into the protective effects of insulin on dementia in the hypertensive and diabetic CKD population. Therefore, we suggest early initiating insulin therapy might be beneficial in such population.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCKD, Chronic kidney disease; ESKD, end stage of kidney disease; CNS, central nervous system; MPR, medication possession ratio; NSAIDs, \u0026nbsp;non-steroidal anti-inflammatory drugs ; ACEIs, angiotensin converting enzyme inhibitors; ARBs, angiotensin receptor blockers; SD, standard deviation; HR, hazard ratio; CI, confidence interval; OADs, oral antidiabetic agents.\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e(a) Ethics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBefore the NHIRD data was released for research,\u0026nbsp;the personal information of all beneficiaries was de-identification and anonymous to ensure the privacy following rigorous secrecy guidelines. Therefore, informed consent was waived by the Ethics Review of Board\u0026nbsp;Shin-Kong Wu Ho-Su Memorial Hospital\u0026nbsp;(IRB approval number: No. 20200806R).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(b) Consent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(c) Availability of data and materials .\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset used in this study is held by the Taiwan Ministry of Health and Welfare (MOHW). Any researcher interested in accessing this dataset can apply for access. Please visit the website of the National Health Informatics Project of the MOHW (https:// dep.mohw.gov.tw/dos/np-2497-113.html).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(d) Competing interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe funding source played no role in this study.\u0026nbsp;The authors report no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(e) Funding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was supported by a grant under a cooperative project between Shin Kong Wu Ho-Su Memorial Hospital and National Yang Ming Chiao Tung University in Taiwan (109GB006-2) and Shin Kong Wu Ho-Su Memorial Hospital, grant number 2023SKHADR036.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003e(f) Authors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConceptualization:\u0026nbsp;\u003c/strong\u003eC-YY , F-YW, and C-YH; \u003cstrong\u003eData curation:\u0026nbsp;\u003c/strong\u003eC-YY; \u003cstrong\u003eFormal analysis:\u0026nbsp;\u003c/strong\u003eT-MH, J-TN, and C-YY; \u003cstrong\u003eFunding acquisition:\u0026nbsp;\u003c/strong\u003eT-MH and C-YY; \u003cstrong\u003eInvestigation:\u0026nbsp;\u003c/strong\u003eC-YY and F-YW; \u003cstrong\u003eMethodology:\u0026nbsp;\u003c/strong\u003eC-YY, T-MH and F-YW; \u003cstrong\u003eSupervision:\u0026nbsp;\u003c/strong\u003e C-YY and F-YW; \u003cstrong\u003eValidation:\u0026nbsp;\u003c/strong\u003eC-YY; \u003cstrong\u003eVisualization:\u0026nbsp;\u003c/strong\u003eT-MH, W-JT; \u003cstrong\u003eWriting \u0026ndash; original draft:\u003c/strong\u003e T-MH; \u003cstrong\u003eWriting \u0026ndash; review \u0026amp; editing:\u0026nbsp;\u003c/strong\u003eT-MH and C-YY. \u0026nbsp;All authors discussed the results and contributed to the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e(g) Acknowledgements\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLv JC, Zhang LX: \u003cstrong\u003ePrevalence and Disease Burden of Chronic Kidney Disease\u003c/strong\u003e. \u003cem\u003eAdv Exp Med Biol \u003c/em\u003e2019, \u003cstrong\u003e1165\u003c/strong\u003e:3-15.\u003c/li\u003e\n\u003cli\u003eCollaboration GBDCKD: \u003cstrong\u003eGlobal, regional, and national burden of chronic kidney disease, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017\u003c/strong\u003e. \u003cem\u003eLancet \u003c/em\u003e2020, \u003cstrong\u003e395\u003c/strong\u003e(10225):709-733.\u003c/li\u003e\n\u003cli\u003eTsai MH, Hsu CY, Lin MY, Yen MF, Chen HH, Chiu YH, Hwang SJ: \u003cstrong\u003eIncidence, Prevalence, and Duration of Chronic Kidney Disease in Taiwan: Results from a Community-Based Screening Program of 106,094 Individuals\u003c/strong\u003e. \u003cem\u003eNephron \u003c/em\u003e2018, 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\u003cstrong\u003e33\u003c/strong\u003e(4):e12934.\u003c/li\u003e\n\u003cli\u003eAvgerinos KI, Kalaitzidis G, Malli A, Kalaitzoglou D, Myserlis PG, Lioutas VA: \u003cstrong\u003eIntranasal insulin in Alzheimer\u0026apos;s dementia or mild cognitive impairment: a systematic review\u003c/strong\u003e. \u003cem\u003eJ Neurol \u003c/em\u003e2018, \u003cstrong\u003e265\u003c/strong\u003e(7):1497-1510.\u003c/li\u003e\n\u003cli\u003eHuang L, Zhu M, Ji J: \u003cstrong\u003eAssociation between hypoglycemia and dementia in patients with diabetes: a systematic review and meta-analysis of 1.4 million patients\u003c/strong\u003e. \u003cem\u003eDiabetol Metab Syndr \u003c/em\u003e2022, \u003cstrong\u003e14\u003c/strong\u003e(1):31.\u003c/li\u003e\n\u003cli\u003eBetonico CC, Titan SM, Correa-Giannella ML, Nery M, Queiroz M: \u003cstrong\u003eManagement of diabetes mellitus in individuals with chronic kidney disease: therapeutic perspectives and glycemic control\u003c/strong\u003e. \u003cem\u003eClinics (Sao Paulo) \u003c/em\u003e2016, \u003cstrong\u003e71\u003c/strong\u003e(1):47-53.\u003c/li\u003e\n\u003cli\u003eKosmas CE, Silverio D, Tsomidou C, Salcedo MD, Montan PD, Guzman E: \u003cstrong\u003eThe Impact of Insulin Resistance and Chronic Kidney Disease on Inflammation and Cardiovascular Disease\u003c/strong\u003e. \u003cem\u003eClin Med Insights Endocrinol Diabetes \u003c/em\u003e2018, \u003cstrong\u003e11\u003c/strong\u003e:1179551418792257.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Chronic kidney disease, real-world evidence, insulin, hypertension, diabetes, dementia","lastPublishedDoi":"10.21203/rs.3.rs-4329846/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4329846/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eINTRODUCTION:\u003c/h2\u003e \u003cp\u003eThe effects of insulin use on the incidence of dementia in chronic kidney disease (CKD) patients with diabetes and hypertension is limited.\u003c/p\u003e\u003ch2\u003eMETHOD\u003c/h2\u003e \u003cp\u003eIn this retrospective study, differences in the incidence of dementia between insulin users and non-users were examined with competing risk models.\u003c/p\u003e\u003ch2\u003eRESULTS\u003c/h2\u003e \u003cp\u003eIn a follow-up period of 11 years, 1285 events of dementia were recorded and the multivariate-adjusted hazard ratio for dementia by insulin usage (yes versus non) and insulin usage per medication possession ratio (MPR) is 0.652 (95% confidence interval [CI]: 0.552\u0026ndash;0.771) and 0.995 (95% CI: 0.993\u0026ndash;0.998) respectively. Such a significantly negative association was consistent in almost the subgroups. Moreover, a dosing effect of insulins was noted that patients who had higher insulin MPRs generally benefited from better protection from dementia.\u003c/p\u003e\u003ch2\u003eDISCUSSION\u003c/h2\u003e \u003cp\u003eThe CKD patients with hypertension and diabetes who received insulin therapy had a 35% decreased risk of dementia.\u003c/p\u003e","manuscriptTitle":"The Protective Effects of Insulin on the Developing of Dementia in Chronic Kidney Disease Patients with hypertension and diabetes: A Population-Based Nationwide Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-09 18:29:56","doi":"10.21203/rs.3.rs-4329846/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-02-13T09:56:14+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-01T18:41:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"230633739980020735032223774104141071632","date":"2025-01-22T05:13:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"154156475834898622051996604575406406346","date":"2025-01-22T02:17:57+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-22T13:38:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"165921170964998003811419427814457404726","date":"2024-12-12T04:33:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"83534278285212910481382208031829072456","date":"2024-12-07T02:25:44+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-12-04T15:44:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-12-04T03:59:36+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-05-06T12:06:34+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-02T16:40:45+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nephrology","date":"2024-04-26T13:01:18+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"299be36a-6ff2-4a38-a627-5e3c1f4fc1f0","owner":[],"postedDate":"May 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-04-28T16:07:41+00:00","versionOfRecord":{"articleIdentity":"rs-4329846","link":"https://doi.org/10.1186/s12882-025-04145-9","journal":{"identity":"bmc-nephrology","isVorOnly":false,"title":"BMC Nephrology"},"publishedOn":"2025-04-25 15:58:28","publishedOnDateReadable":"April 25th, 2025"},"versionCreatedAt":"2024-05-09 18:29:56","video":"","vorDoi":"10.1186/s12882-025-04145-9","vorDoiUrl":"https://doi.org/10.1186/s12882-025-04145-9","workflowStages":[]},"version":"v1","identity":"rs-4329846","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4329846","identity":"rs-4329846","version":["v1"]},"buildId":"ApUGefWb6u5IBVtyqm6d5","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}