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Article

Dose–Response Association of Metformin with Parkinson’s Disease Odds in Type 2 Diabetes Mellitus

1
Department of Health Services Administration, China Medical University, Taichung 40402, Taiwan
2
Department of Pharmacology, Chung Shan Medical University, No. 110, Sec. 1, Jianguo N. Rd., Taichung 40201, Taiwan
3
Department of Pharmacy, Chung Shan Medical University Hospital, Taichung 40201, Taiwan
4
School of Medicine, Chung Shan Medical University, Taichung 40201, Taiwan
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Pharmaceutics 2022, 14(5), 946; https://doi.org/10.3390/pharmaceutics14050946
Submission received: 6 April 2022 / Revised: 21 April 2022 / Accepted: 25 April 2022 / Published: 27 April 2022
(This article belongs to the Special Issue Drugs and Drug Delivery for Diabetes Mellitus Treatment)

Abstract

:
Background. Studies have demonstrated that patients with diabetes mellitus who receive metformin have a lower risk of developing Parkinson’s disease (PD). However, studies have also suggested that metformin may increase the risk of PD. In this study, we investigated whether metformin use was associated with the risk of PD in type 2 diabetes mellitus (T2DM). Methods. In this population-based cross-sectional study, patients with T2DM diagnosed between 2001 and 2018 were enrolled. We categorized these patients as metformin users or nonusers. Participants below 50 years old were excluded. Two models were employed to evaluate the associations of metformin exposure and use intensity with PD after 3 and 5 years of follow-up. Results. Patients with T2DM who received <300 cumulative defined daily doses (cDDD) of metformin and those with metformin use intensity of <10 DDD/month had respective odds ratios (ORs) for PD of 0.88 (95% confidence interval [CI] = 0.83–0.94) and 0.87 (95% CI = 0.81–0.93) in a 3-year follow-up. In a 5-year follow-up, such patients had respective ORs for PD of 0.94 (95% CI = 0.90–0.98) and 0.93 (95% CI = 0.89–0.98). Patients with T2DM who received ≥300 cDDD of metformin or used metformin with intensity of ≥10 DDD/month experienced no neuroprotective effects after 3 or 5 years. Conclusions. Metformin was associated with PD odds in T2DM in a dose–response association manner. Patients who received low dosage and intensity of metformin use were associated with lower odds of PD, while higher dosage and intensity of metformin use had no neuroprotective effect.

1. Introduction

Aging often leads to an increased risk of neurodegenerative diseases (NDs), such as cognitive dysfunction and Parkinson’s disease (PD). PD is the second most common ND to occur with aging and is the most common movement disorder worldwide [1]. The neuropathology of PD is complex and characterized mainly by two features: the progressive loss of dopaminergic neurons in the substantia nigra pars compacta leading to a dopamine deficit in the striatum [2] and the abnormal accumulation and aggregation of alpha-synuclein in Lewy bodies [3].
An increasing body of evidence suggests that both PD and dementia are associated with insulin resistance, which is considered a modifiable risk factor [4]. Emerging evidence supports an association between PD and type 2 diabetes mellitus (T2DM) [5], and patients with T2DM were reported to be at an increased risk of PD, compared with the general population [6]. Metformin is the first-line medication for patients with T2DM, and evidence suggests that metformin can slow aging and reduce the incidence of aging-related diseases [7]. Metformin plays a key role in neuroprotection because it mediates the inhibition of inflammatory responses [8] and slows cognitive decline [9]. Metformin is often used because of its potential ability to slow aging, and it has been reported to have potential in PD treatment [10].
Patients with T2DM may have an increased risk of PD and experience faster PD progression [11]. Studies have demonstrated that patients with T2DM who receive metformin have a lower risk of PD than other patients with T2DM have. Several mechanisms that may underly this association between metformin use and the risk of PD have been proposed [10,12,13,14]. However, studies have also suggested that metformin use may increase the risk of PD [15,16,17], especially in patients with T2DM receiving high doses for a long period [18,19]. Therefore, the association between patients with T2DM receiving metformin and the risk of PD must be clarified. However, few epidemiological studies have investigated this association; even fewer have employed a nationwide database. Therefore, we investigated whether metformin use was associated with the risk of PD in patients with T2DM by using data from the Taiwanese National Health Insurance Research Database (NHIRD).

2. Materials and Methods

2.1. Data Source

This study performed a secondary analysis of data from 2001 to 2018 from the Longitudinal Health Insurance Database (LHID), a data set released by the Health and Welfare Data Science Center (HWDC) of Taiwan’s Ministry of Health and Welfare. Taiwan established the government-run, single-payer NHI program in 1995. The program covers over 99% of Taiwan’s approximately 23 million residents and has contracts with more than 20,000 medical care facilities, including hospitals, clinics, pharmacies, and medical laboratories, amounting to over 93% of the health-care facilities in Taiwan. Data in the LHID are anonymous; the HWDC uses scrambled, random identification numbers to protect the insureds’ privacy. Therefore, the requirement of informed consent was waived.

2.2. Ethical Approval

This study was conducted in accordance with the Declaration of Helsinki. The study protocol was approved by the Central Regional Research Ethics Committee of China Medical University (No. CRREC-109-001).

2.3. Study Sample

To investigate the effects of metformin on PD incidence, we enrolled patients aged over 50 years with new-onset diabetes mellitus from 2002 to 2013. Diabetes mellites was defined as three instances of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code 250 within a 1-year period. Metformin use was indicated by anatomical therapeutic chemical code A10BA02. To minimize bias, we excluded patients with type 1 diabetes mellitus, a diagnosis of PD before or within 1 year after their diagnosis of T2DM, or any hospitalization within 1 year after their T2DM diagnosis. Patients who had received metformin in the first year after their T2DM diagnosis constituted the case group, and patients who had not received metformin during this period were the comparison group. A total of 742,917 patients with new-onset T2DM between 2002 and 2013 were included. Of these patients, 384,716 did and 358,201 did not receive metformin in the first year after receiving their T2DM diagnosis. The patient selection process is illustrated in Figure 1.

2.4. Study Design

This study employed a cross-sectional design and 3-year and 5-year follow-up periods to investigate the risk of PD in patients with T2DM receiving metformin. The defined daily dose (DDD) is a standard measure of drug use and exposure; the World Health Organization defines the DDD as the assumed, average daily maintenance dose of a drug. However, the DDD does not always reflect the recommended or prescribed daily dose [20]. The observation period for each patient’s metformin use was 1 year after T2DM diagnosis. A DDD of 2 g of metformin [21] was used; we calculated the patients’ total metformin exposure for the first year and categorized it as nonuse or <300, 300–500, or >500 cumulative defined daily doses (cDDD) for dose–response analysis. In addition, we calculated the patients’ average monthly doses of metformin and classified them as nonuse or <10, 10–25, or >25 DDD/month to investigate the association between the intensity of metformin use and PD. All of the patients were followed for 5 years. PD was defined as three or more outpatient visit records within 1 year with ICD-9-CM code 332 or International Classification of Disease, Tenth Revision, Clinical Modification (ICD-10-CM) code G20. Comorbid hypertension (ICD-9-CM code 401–405), hyperlipidemia (ICD-9-CM code 272.0–272.4), hyperuricemia (ICD-9-CM 790.6), cerebrovascular disease (ICD-9-CM code 430–438), coronary artery disease (CAD; ICD-9-CM code 414.0), arrhythmia (ICD-9-CM code 427), heart failure (ICD-9-CM code 428.0), anxiety (ICD-9-CM code 300.0), depression (ICD-9-CM code 311), chronic obstructive pulmonary disease (COPD; ICD-9-CM code 490–492 or 494–496), chronic kidney disease (CKD; ICD-9-CM code 585), obesity (ICD-9-CM code 278.00), and alcoholism (ICD-9-CM code 303) were analyzed.

2.5. Statistical Analyses

All analyses were performed in SAS software version 9.4 (SAS Institute, Cary, NC, USA). The chi-square test was used to evaluate the distributions of the baseline characteristics of the metformin users and nonusers. The risk of PD for the metformin users and nonusers was estimated by multiple logistic regression with adjustment for relevant variables. The results are presented as odds ratios (ORs) with 95% confidence intervals (CIs). Two adjusted models were developed to estimate PD odds in metformin users based on cumulative metformin exposure (cDDD) and intensity of metformin use (DDD/month). Significance was indicated by a p value of <0.05.

3. Results

3.1. Distribution of Patient Characteristics

The mean age was 62.17 ± 8.86 years (50–64 years [64.02%], 65–74 years [24.74%], and >75 years [11.24%]), as presented in Table 1. Among the patients, 48.57% were women, and 51.43% were men. The average age of the metformin users was 61.32 ± 8.47 years). Among all patients, 168,477 (43.79%) had hypertension; 69,406 (18.04%) had hyperlipidemia; 2850 (0.74%) had hyperuricemia; 17,696 (4.60%) had CVD; 14,429 (3.75%) had arrhythmia; 6893 (1.79%) had heart failure; 34,016 (8.84%) had anxiety; 1796 (0.47%) had depression; 20,660 (5.37%) had COPD; 1546 (0.40%) had CKD; 1752 (0.46%) had obesity; and 225 (0.06%) had alcoholism. The distributions of all comorbid diseases except alcoholism differed significantly between the metformin users and nonusers (p < 0.001).

3.2. Associations between PD and Metformin Use in Patients New-Onset T2DM—3-Year Follow-Up

Table S1 is the distribution of incident PD in T2DM patients. Table 2 presents the incidence of PD after a 3 year-follow up; 3977 patients (0.54%) developed PD in the 3 years after their T2DM diagnosis. The rate of occurring PD at 3 years of among metformin nonusers was 0.62%, and that among users was 0.46%, 0.45%, and 1.27% for those with <300, 300–500, and >500 cDDD, respectively. Regarding intensity of metformin use, the incidence of PD was 0.46%, 0.43%, and 0.48% among user who averaged <10, 10–25, and ≥25 DDD/month, respectively. After 3 years, patients with T2DM who had received <300, 300–500, and >500 cDDD of metformin had ORs for PD of 0.88 (95% CI = 0.83–0.94), 1.09 (95% CI = 0.72–1.65), and 2.59 (95% CI = 0.83–8.03), respectively. Regarding the intensity of metformin use, patients with T2DM averaging <10, 10–25, and ≥25 DDD/month had ORs for PD of 0.87 (95% CI = 0.81–0.93), 0.92 (95% CI = 0.83–1.02), and 1.17 (95% CI = 0.80–1.72), respectively.
For risk factors, adjusted model 1 revealed that patients with T2DM who were 65–74 and ≥75 years old had ORs for PD of 3.95 (95% CI = 3.64–4.29) and 7.01 (95% CI = 6.42–7.65), respectively. Comparing with diabetes patients with 0 point of Diabetes Complications and Severity Index (DCSI) scores, those with higher value of 1 and ≥2 DCSI scores had ORs for PD of 1.16 (95% CI = 1.06–1.26) and 1.37 (95% CI = 6.42–7.65), respectively. Patients with comorbid CVD (OR = 1.55, 95% CI = 1.41–1.71), anxiety (OR = 1.79, 95% CI = 1.65–1.94), depression (OR = 1.93, 95% CI = 1.50–2.48), or COPD (OR = 1.15, 95% CI = 1.04–1.27) had increased odds of developing PD comparing with those without the respective comorbidities. Patients comorbid with hypertension, hyperuricemia, CAD, arrhythmia, CKD, obesity, and alcoholism did not have an associated risk of developing PD.

3.3. Associations between PD and Metformin Use in Patients New-Onset T2DM—5-Year Follow-Up

Table 3 presents the incidence of PD after 5 years. After adjustment for relevant variables, patients with T2DM who had received <300, 300–500, and >500 cDDD of metformin were discovered to have ORs for PD of 0.94 (95% CI = 0.90–0.98), 1.01 (95% CI = 0.75–1.35), and 1.24 (95% CI = 0.40–3.83), respectively. Patients averaging <10, 10–25, and >25 DDD/month had ORs for PD of 0.93 (95% CI = 0.89–0.98), 0.97 (95% CI = 0.90–1.04), and 1.02 (95% CI = 0.77–1.35), respectively. Adjusted model 1 also indicated that patients aged 65–74 and ≥75 years had respective ORs for PD of 3.88 (95% CI = 3.67–4.10) and 6.22 (95% CI = 5.86–6.60). Patients with DCSI scores of 1 and ≥2 had respective ORs for PD of 1.16 (95% CI = 1.09–1.22) and 1.35 (95% CI = 1.27–1.43). Among risk factors, comorbid CVD, anxiety, depression, and COPD were associated with greater PD odds, findings consistent with those at 3 years.

4. Discussion

Few large-scale epidemiological studies have evaluated the risk of PD among patients with T2DM receiving metformin. In our study, metformin use was associated with PD risk in T2DM in a dose–response association manner. The results suggest that <300 cDDD of metformin and metformin use of <10 DDD/month are associated with lower odds of PD at 3 and 5 years. However, exposure to ≥300 cDDD of metformin and use intensity of ≥10 DDD/month were associated with no such neuroprotective effects. Our findings also revealed that, among patients with T2DM using metformin, being older and having a high DCSI score were associated with greater odds of PD. Furthermore, metformin users living in highly urbanized areas had greater odds of PD in T2DM.
Patients with T2DM have an increased risk of PD and of experience faster PD progression [11]. PD is an ND characterized by progressive loss of dopaminergic neurons in the substantia nigra. Dysfunctional insulin signaling was reported to increase oxidative stress in PD [22], and an animal study demonstrated that chronic insulin resistance was associated with mitochondrial disruption and dopaminergic neuronal degeneration [23]. We discovered that patients with T2DM who had consumed <300 cDDD of metformin or took metformin with an intensity of <10 DDD/month had lower PD odds. Several mechanisms have been proposed by animal and physiological studies to explain the association between metformin use and PD risk. Research indicates that metformin can cross the blood–brain barrier; its concentration in cerebrospinal fluid is approximately 10% of that in plasma [12].
Metformin may have neuroprotective effects in PD. A murine model of PD demonstrated the metformin can reduce alpha-synuclein phosphorylation and aggregation; influence cellular processes associated with age-related conditions, including autophagy and inflammation [10]; and upregulate neurotrophic factors [24]. Adenosine monophosphate–activated protein kinase (AMPK) plays essential roles in the regulation of neuroenergetic metabolic plasticity and in cognitive impairment [25], and AMPK over activation can lead to the accumulation of alpha-synuclein oligomers and a decrease in neurites [13]. Metformin exerts neuroprotective regulatory effects—its main therapeutic effects in PD—through the AMPK signaling pathway [14].
A study demonstrated that 2-year metformin use was associated with a lower incidence of NDs in older patients with T2DM; however, metformin exposure did not significantly affect the risk of developing NDs during the first 2 years [26]. In our study, patients with T2DM who had received ≥300 cDDD of metformin and those who had a metformin use intensity of ≥10 DDD/month experienced no neuroprotective effects. Studies have suggested that metformin use may increase the risk of PD, with some data suggesting that metformin may cause dementia and PD [15,16,17]. Metformin was also found to increase β-amyloid production [15]. Moreover, AMPK activation by metformin has been demonstrated to induce sufficient metabolic stress to induce dendritic spine loss in hippocampal neurons [27,28]. Several studies have reported an association between prolonged metformin use and vitamin-B12-deficiency-associated peripheral neuropathy. Diabetic peripheral neuropathy may be indistinguishable from vitamin B12 deficiency and could lead to permanent nerve damage if correction of deficiency is not prompt [29]. Besides, vitamin B12 deficiency is associated with cognitive impairment [29]. A meta-analysis revealed a negative correlation between metformin use and vitamin B12 levels in patients with T2DM [30], and greater cumulative metformin exposure and duration of use were associated with increased risks of vitamin B12 deficiency [18]. Metformin use is associated with increased risk and severity of vitamin B12 deficiency in the elderly patients. Patients receiving metformin ≥1500 mg/day for >2 years are particularly at risk [29]. Although metformin can lower the risk of PD [10,12,14], the B12 deficiency associated with long-term use and high doses of metformin may outweigh the neuroprotective effects and thereby increase the risk of PD. Taken together, metformin related vitamin B12 deficiency may counteract the potential benefit of metformin in long-term therapy. Vitamin B12 deficiency play a part role of PD risk in patients receiving metformin with long-term duration and greater dosage. Our study result is consistent with an animal study show that lower dose of metformin (100 mg/kg) ameliorated scopolamine-induced cognitive deficit, while higher dose of metformin had no deleterious effect [31]. However, the actual underlying mechanism between metformin dosage and PD risk remains unclear and should be investigated in the future. Those DM patients taking longer or more intensive treatment with metformin may have more T2DM severity that can offset the neuroprotective effect.
The DCSI is a tool for predicting the risk of hospitalization and mortality in patients with diabetes mellitus [32]. The adapted DCSI, which assesses seven categories of diabetic complications without severity grading, is a modified version of a risk measure that does not consider laboratory data [32,33]. Patients with diabetes mellitus and high scores on the adapted DCSI reportedly have a higher risk of dementia [34]. Our study indicates that metformin use with a high DCSI score is associated with increased odds of PD in T2DM. Thus, the DCSI may be used as an indicator of PD risk. Our findings also revealed that older patients (particularly those older than 75 years) with T2DM who were receiving metformin had greater odds of PD. This result is consistent with others suggesting that PD risk increases with age [35]. Age is the greatest risk factor for the PD development and progression [36] and causes many cellular processes that predispose individuals to neurodegeneration. Moreover, age-related pathological alterations of cellular function can predispose individuals to PD [37]. Aging increases the risks of both T2DM and vitamin B12 deficiency [38]. Older patients with diabetes mellitus who receive metformin may have a higher risk of PD due to long treatment durations and high doses, which may lead to vitamin B12 deficiency and severe diabetic peripheral neuropathy [19,39]. Moreover, we discovered that, among patients with T2DM, metformin users who lived in areas with a high level of urbanization had greater odds of PD. This result is consistent with those of other studies, which have reported differences in PD prevalence based on region, country, and urbanization level [35,40].
Our results indicate that metformin users with comorbid CVD, anxiety, depression, or COPD have greater odds of PD in T2DM. A large, population-based study demonstrated that most cerebrovascular risk factors are also associated with subsequent PD [41], and PD is positively associated with depression and anxiety [42]. PD-related anxiety or depression may be due to Lewy body deposition in the serotonergic and noradrenergic neurons [43]. Another study discovered a higher risk of PD among patients with anxiety than among those patients without, and more severe anxiety was associated with a greater PD risk [44]. Depression has been reported to be an independent risk factor for and early symptom of PD [45,46]. Moreover, a cohort study revealed that the risk of PD was significantly higher among patients with COPD than it was in the general population [47].
Our study has several strengths; the first is its population-based design. Our sample was drawn from the entire population of Taiwan; thus, our sample is representative. The population-based design also minimized selection bias, which is common in observational studies. Furthermore, the follow-up information from health-care institutions was nearly complete for the entire sample. Second, the characteristics of the database provided sufficient statistical power to investigate the associations between metformin use and PD risk among patients with T2DM. Third, we evaluated the associations at 3 and 5 years; furthermore, metformin exposure was categorized into <300, 300–500, and >500 cDDD, and use intensity was categorized into <10, 10–25, and >25 DDD/month. Fourth, we investigated relevant risk factors (comorbidities).
Our study also has several limitations. First, behavioral data, such as tobacco smoking habits, alcohol consumption, and caffeine intake, and physical activity habits (and associated body mass index), were unavailable. These factors can affect PD development and thus may have affected our findings [48]. Second, the diagnoses of PD and other comorbidities were based solely on ICD-9-CM and ICD-10-CM codes. However, the Taiwanese Bureau of National Health Insurance randomly reviews charts and interviews patients to verify the accuracy of diagnoses. Hospitals reporting outlier charges or practices are audited, and the penalties for malpractice are severe. These processes ensure the validity and accuracy of the NHIRD. Third, the severity of PD and T2DM cannot be determined from ICD-9-CM and ICD-10-CM codes; thus, severity-based subgroup analysis was impossible. For example, the NHIRD does not provide information regarding HbA1c, which is crucial to hyperglycemia management for patients with diabetes mellitus. Therefore, the potential correlation between glycemic control and PD incidence could not be explored. Fourth, DM patients receiving >500 cDDD of metformin were relatively fewer in our study, as the small sample size may lead to bias.

5. Conclusions

In conclusion, metformin use was associated with PD risk among T2DM patients in a dose–response association manner. Patients who received low dosage and intensity of metformin use were associated with lower odds of PD, while higher dosage and intensity of metformin use had no neuroprotective effect.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/pharmaceutics14050946/s1, Table S1: The distribution of incident Parkinson’s disease in new-onset diabetes mellitus patients.

Author Contributions

Conceptualization, K.-H.H., Y.-L.C., S.-Y.G., T.-H.T. and C.-Y.L.; Formal analysis, T.-H.T. and C.-Y.L.; Investigation, C.-Y.L.; Methodology, K.-H.H., T.-H.T. and C.-Y.L.; Validation, C.-Y.L.; Visualization, C.-Y.L.; Writing—original draft, K.-H.H., Y.-L.C., S.-Y.G., T.-H.T. and C.-Y.L.; Writing—review & editing, K.-H.H., Y.-L.C., S.-Y.G., T.-H.T. and C.-Y.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Chung Shan Medical University Hospital, Taiwan (CSH-2022-C-046), China Medical University Taiwan (CMU110-MF-113), and the Ministry of Science and Technology Taiwan (MOST 110-2410-H-040-002, MOST 109-2410-H-039-004-MY2).

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki, and approved as a completely ethical review by the Central Regional Research Ethics Committee of China Medical University, Taiwan (protocol code CRREC-109-001 and date of approval 12 February 2020).

Informed Consent Statement

The database is anonymous, the requirement for informed consent was waived.

Data Availability Statement

The National Health Insurance Database used to support the findings of this study were provided by the Health and Welfare Data Science Center, Ministry of Health and Welfare (HWDC, MOHW) under license and so cannot be made freely available. Requests for access to these data should be made to HWDC (https://dep.mohw.gov.tw/dos/np-2497-113.html) (accessed on 6 April 2022).

Acknowledgments

We are grateful to Chung Shan Medical University, Taiwan, China Medical University, Taiwan, and the Health Data Science Center, China Medical University Hospital, for providing administrative, technical, and funding support that has contributed to the completion of this study. This study is based, in part, on data released by the Health and Welfare Data Science Center, Ministry of Health and Welfare. The interpretation and conclusions contained herein do not represent those of the Ministry of Health and Welfare.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Lima, M.M.; Targa, A.D.S.; Noseda, A.C.D.; Rodrigues, L.S.; Marcia Delattre, A.; dos Santos, F.V.; Fortes, M.H.; Maturana, M.J.; Ferraz, A.C. Does Parkinson’s disease and type-2 diabetes mellitus present common pathophysiological mechanisms and treatments? CNS Neurol. Disord. Drug Targets 2014, 13, 418–428. [Google Scholar] [CrossRef] [PubMed]
  2. Schneider, S.A.; Obeso, J.A. Clinical and pathological features of Parkinson’s disease. Curr. Top. Behav. Neurosci. 2015, 22, 205–220. [Google Scholar] [CrossRef] [PubMed]
  3. Schapira, A.H. Etiology and pathogenesis of Parkinson disease. Neurol. Clin. 2009, 27, 583–603. [Google Scholar] [CrossRef] [PubMed]
  4. Ping, F.; Jiang, N.; Li, Y. Association between metformin and neurodegenerative diseases of observational studies: Systematic review and meta-analysis. BMJ Open Diabetes Res. Care 2020, 8, e001370. [Google Scholar] [CrossRef]
  5. Cheong, J.L.Y.; de Pablo-Fernandez, E.; Foltynie, T.; Noyce, A.J. The Association between Type 2 Diabetes Mellitus and Parkinson’s Disease. J. Parkinsons Dis. 2020, 10, 775–789. [Google Scholar] [CrossRef] [Green Version]
  6. Hu, G.; Jousilahti, P.; Bidel, S.; Antikainen, R.; Tuomilehto, J. Type 2 diabetes and the risk of Parkinson’s disease. Diabetes Care 2007, 30, 842–847. [Google Scholar] [CrossRef] [Green Version]
  7. Soukas, A.A.; Hao, H.; Wu, L. Metformin as Anti-Aging Therapy: Is It for Everyone? Trends Endocrinol. Metab. 2019, 30, 745–755. [Google Scholar] [CrossRef]
  8. Han, J.; Li, Y.; Liu, X.; Zhou, T.; Sun, H.; Edwards, P.; Gao, H.; Yu, F.S.; Qiao, X. Metformin suppresses retinal angiogenesis and inflammation in vitro and in vivo. PLoS ONE 2018, 13, e0193031. [Google Scholar] [CrossRef] [Green Version]
  9. Ahuja, S.; Uniyal, A.; Akhtar, A.; Sah, S.P. Alpha lipoic acid and metformin alleviates experimentally induced insulin resistance and cognitive deficit by modulation of TLR2 signalling. Pharmacol. Rep. 2019, 71, 614–623. [Google Scholar] [CrossRef]
  10. Rotermund, C.; Machetanz, G.; Fitzgerald, J.C. The Therapeutic Potential of Metformin in Neurodegenerative Diseases. Front. Endocrinol. 2018, 9, 400. [Google Scholar] [CrossRef]
  11. Vicente Miranda, H.; El-Agnaf, O.M.; Outeiro, T.F. Glycation in Parkinson’s disease and Alzheimer’s disease. Mov. Disord. 2016, 31, 782–790. [Google Scholar] [CrossRef] [PubMed]
  12. Koenig, A.M.; Mechanic-Hamilton, D.; Xie, S.X.; Combs, M.F.; Cappola, A.R.; Xie, L.; Detre, J.A.; Wolk, D.A.; Arnold, S.E. Effects of the Insulin Sensitizer Metformin in Alzheimer Disease: Pilot Data From a Randomized Placebo-controlled Crossover Study. Alzheimer Dis. Assoc. Disord. 2017, 31, 107–113. [Google Scholar] [CrossRef]
  13. Jiang, P.; Gan, M.; Ebrahim, A.S.; Castanedes-Casey, M.; Dickson, D.W.; Yen, S.H. Adenosine monophosphate-activated protein kinase overactivation leads to accumulation of alpha-synuclein oligomers and decrease of neurites. Neurobiol. Aging 2013, 34, 1504–1515. [Google Scholar] [CrossRef] [Green Version]
  14. Stephenne, X.; Foretz, M.; Taleux, N.; van der Zon, G.C.; Sokal, E.; Hue, L.; Viollet, B.; Guigas, B. Metformin activates AMP-activated protein kinase in primary human hepatocytes by decreasing cellular energy status. Diabetologia 2011, 54, 3101–3110. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Picone, P.; Nuzzo, D.; Caruana, L.; Messina, E.; Barera, A.; Vasto, S.; Di Carlo, M. Metformin increases APP expression and processing via oxidative stress, mitochondrial dysfunction and NF-kappaB activation: Use of insulin to attenuate metformin’s effect. Biochim. Biophys. Acta 2015, 1853, 1046–1059. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Chen, Y.; Zhou, K.; Wang, R.; Liu, Y.; Kwak, Y.D.; Ma, T.; Thompson, R.C.; Zhao, Y.; Smith, L.; Gasparini, L.; et al. Antidiabetic drug metformin (GlucophageR) increases biogenesis of Alzheimer’s amyloid peptides via up-regulating BACE1 transcription. Proc. Natl. Acad. Sci. USA 2009, 106, 3907–3912. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  17. Sridhar, G.R.; Lakshmi, G.; Nagamani, G. Emerging links between type 2 diabetes and Alzheimer’s disease. World J. Diabetes 2015, 6, 744–751. [Google Scholar] [CrossRef] [PubMed]
  18. Khattar, D.; Khaliq, F.; Vaney, N.; Madhu, S.V. Is Metformin-Induced Vitamin B12 Deficiency Responsible for Cognitive Decline in Type 2 Diabetes? Indian J. Psychol. Med. 2016, 38, 285–290. [Google Scholar] [CrossRef] [Green Version]
  19. Hashem, M.M.; Esmael, A.; Nassar, A.K.; El-Sherif, M. The relationship between exacerbated diabetic peripheral neuropathy and metformin treatment in type 2 diabetes mellitus. Sci. Rep. 2021, 11, 1940. [Google Scholar] [CrossRef]
  20. Grimmsmann, T.; Himmel, W. Discrepancies between prescribed and defined daily doses: A matter of patients or drug classes? Eur. J. Clin. Pharmacol. 2011, 67, 847–854. [Google Scholar] [CrossRef] [Green Version]
  21. Wellington, K. Rosiglitazone/Metformin. Drugs 2005, 65, 1581–1592; discussion 1584–1593. [Google Scholar] [CrossRef]
  22. Wang, S.; Zhang, C.; Sheng, X.; Zhang, X.; Wang, B.; Zhang, G. Peripheral expression of MAPK pathways in Alzheimer’s and Parkinson’s diseases. J. Clin. Neurosci. 2014, 21, 810–814. [Google Scholar] [CrossRef] [PubMed]
  23. Khang, R.; Park, C.; Shin, J.H. Dysregulation of parkin in the substantia nigra of db/db and high-fat diet mice. Neuroscience 2015, 294, 182–192. [Google Scholar] [CrossRef] [PubMed]
  24. Katila, N.; Bhurtel, S.; Shadfar, S.; Srivastav, S.; Neupane, S.; Ojha, U.; Jeong, G.S.; Choi, D.Y. Metformin lowers alpha-synuclein phosphorylation and upregulates neurotrophic factor in the MPTP mouse model of Parkinson’s disease. Neuropharmacology 2017, 125, 396–407. [Google Scholar] [CrossRef] [PubMed]
  25. Marinangeli, C.; Didier, S.; Ahmed, T.; Caillerez, R.; Domise, M.; Laloux, C.; Begard, S.; Carrier, S.; Colin, M.; Marchetti, P.; et al. AMP-Activated Protein Kinase Is Essential for the Maintenance of Energy Levels during Synaptic Activation. iScience 2018, 9, 1–13. [Google Scholar] [CrossRef] [Green Version]
  26. Shi, Q.; Liu, S.; Fonseca, V.A.; Thethi, T.K.; Shi, L. Effect of metformin on neurodegenerative disease among elderly adult US veterans with type 2 diabetes mellitus. BMJ Open 2019, 9, e024954. [Google Scholar] [CrossRef] [Green Version]
  27. Mairet-Coello, G.; Courchet, J.; Pieraut, S.; Courchet, V.; Maximov, A.; Polleux, F. The CAMKK2-AMPK kinase pathway mediates the synaptotoxic effects of Abeta oligomers through Tau phosphorylation. Neuron 2013, 78, 94–108. [Google Scholar] [CrossRef] [Green Version]
  28. Hardie, D.G. Neither LKB1 nor AMPK are the direct targets of metformin. Gastroenterology 2006, 131, 973; author reply 974–975. [Google Scholar] [CrossRef]
  29. Wong, C.W.; Leung, C.S.; Leung, C.P.; Cheng, J.N. Association of metformin use with vitamin B12 deficiency in the institutionalized elderly. Arch Gerontol. Geriatr. 2018, 79, 57–62. [Google Scholar] [CrossRef]
  30. Chapman, L.E.; Darling, A.L.; Brown, J.E. Association between metformin and vitamin B12 deficiency in patients with type 2 diabetes: A systematic review and meta-analysis. Diabetes Metab. 2016, 42, 316–327. [Google Scholar] [CrossRef] [Green Version]
  31. Mostafa, D.K.; Ismail, C.A.; Ghareeb, D.A. Differential metformin dose-dependent effects on cognition in rats: Role of Akt. Psychopharmacology 2016, 233, 2513–2524. [Google Scholar] [CrossRef]
  32. Young, B.A.; Lin, E.; Von Korff, M.; Simon, G.; Ciechanowski, P.; Ludman, E.J.; Everson-Stewart, S.; Kinder, L.; Oliver, M.; Boyko, E.J.; et al. Diabetes complications severity index and risk of mortality, hospitalization, and healthcare utilization. Am. J. Manag. Care 2008, 14, 15–23. [Google Scholar]
  33. Chang, H.Y.; Weiner, J.P.; Richards, T.M.; Bleich, S.N.; Segal, J.B. Validating the adapted Diabetes Complications Severity Index in claims data. Am. J. Manag. Care 2012, 18, 721–726. [Google Scholar]
  34. Chiu, W.C.; Ho, W.C.; Liao, D.L.; Lin, M.H.; Chiu, C.C.; Su, Y.P.; Chen, P.C. Health Data Analysis in Taiwan Research, G. Progress of Diabetic Severity and Risk of Dementia. J. Clin. Endocrinol. Metab. 2015, 100, 2899–2908. [Google Scholar] [CrossRef] [Green Version]
  35. Pringsheim, T.; Jette, N.; Frolkis, A.; Steeves, T.D. The prevalence of Parkinson’s disease: A systematic review and meta-analysis. Mov. Disord. 2014, 29, 1583–1590. [Google Scholar] [CrossRef]
  36. Collier, T.J.; Kanaan, N.M.; Kordower, J.H. Ageing as a primary risk factor for Parkinson’s disease: Evidence from studies of non-human primates. Nat. Rev. Neurosci. 2011, 12, 359–366. [Google Scholar] [CrossRef]
  37. Hindle, J.V. Ageing, neurodegeneration and Parkinson’s disease. Age Ageing 2010, 39, 156–161. [Google Scholar] [CrossRef] [Green Version]
  38. American Diabetes, A. Standards of medical care in diabetes–2010. Diabetes Care 2010, 33 (Suppl. 1), S11–S61. [Google Scholar] [CrossRef] [Green Version]
  39. Khan, A.; Shafiq, I.; Hassan Shah, M. Prevalence of Vitamin B12 Deficiency in Patients with Type II Diabetes Mellitus on Metformin: A Study from Khyber Pakhtunkhwa. Cureus 2017, 9, e1577. [Google Scholar] [CrossRef] [Green Version]
  40. Collaborators, G.B.D.P.s.D. Global, regional, and national burden of Parkinson’s disease, 1990–2016: A systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2018, 17, 939–953. [Google Scholar] [CrossRef] [Green Version]
  41. Kummer, B.R.; Diaz, I.; Wu, X.; Aaroe, A.E.; Chen, M.L.; Iadecola, C.; Kamel, H.; Navi, B.B. Associations between cerebrovascular risk factors and parkinson disease. Ann Neurol. 2019, 86, 572–581. [Google Scholar] [CrossRef]
  42. Ishihara, L.; Brayne, C. A systematic review of depression and mental illness preceding Parkinson’s disease. Acta Neurol. Scand. 2006, 113, 211–220. [Google Scholar] [CrossRef]
  43. Braak, H.; Ghebremedhin, E.; Rub, U.; Bratzke, H.; Del Tredici, K. Stages in the development of Parkinson’s disease-related pathology. Cell Tissue Res. 2004, 318, 121–134. [Google Scholar] [CrossRef]
  44. Lin, C.H.; Lin, J.W.; Liu, Y.C.; Chang, C.H.; Wu, R.M. Risk of Parkinson’s disease following anxiety disorders: A nationwide population-based cohort study. Eur. J. Neurol. 2015, 22, 1280–1287. [Google Scholar] [CrossRef]
  45. Fang, F.; Xu, Q.; Park, Y.; Huang, X.; Hollenbeck, A.; Blair, A.; Schatzkin, A.; Kamel, F.; Chen, H. Depression and the subsequent risk of Parkinson’s disease in the NIH-AARP Diet and Health Study. Mov. Disord. 2010, 25, 1157–1162. [Google Scholar] [CrossRef] [Green Version]
  46. Wirdefeldt, K.; Adami, H.O.; Cole, P.; Trichopoulos, D.; Mandel, J. Epidemiology and etiology of Parkinson’s disease: A review of the evidence. Eur. J. Epidemiol. 2011, 26 (Suppl. 1), S1–S58. [Google Scholar] [CrossRef]
  47. Li, C.H.; Chen, W.C.; Liao, W.C.; Tu, C.Y.; Lin, C.L.; Sung, F.C.; Chen, C.H.; Hsu, W.H. The association between chronic obstructive pulmonary disease and Parkinson’s disease: A nationwide population-based retrospective cohort study. QJM 2015, 108, 39–45. [Google Scholar] [CrossRef] [Green Version]
  48. Ascherio, A.; Schwarzschild, M.A. The epidemiology of Parkinson’s disease: Risk factors and prevention. Lancet Neurol. 2016, 15, 1257–1272. [Google Scholar] [CrossRef]
Figure 1. Patient selection process.
Figure 1. Patient selection process.
Pharmaceutics 14 00946 g001
Table 1. Baseline characteristics of patients with new-onset diabetes mellitus.
Table 1. Baseline characteristics of patients with new-onset diabetes mellitus.
VariablesTotalMetformin
Non-UsersUsersp-Value
N%N%N%
Total742,917 100.00 358,201 48.22 384,716 51.78
Gender <0.001
 Female382,065 51.43 189,612 52.93 192,453 50.02
 Male360,852 48.57 168,589 47.07 192,263 49.98
Age (year) (Mean ± SD)62.17 ± 8.8663.08 ± 9.1861.32 ± 8.47<0.001
 50–64475,631 64.02 215,040 60.03 260,591 67.74
 65–74183,801 24.74 93,963 26.23 89,838 23.35
 ≥7583,485 11.24 49,198 13.73 34,287 8.91
Income level (NTD) a <0.001
 ≤21,000385,214 51.85 189,933 53.02 195,281 50.76
 21,001–33,000176,301 23.73 79,224 22.12 97,077 25.23
 ≥33,001181,402 24.42 89,044 24.86 92,358 24.01
Urbanization b <0.001
 Level 1205,119 27.61 104,737 29.24 100,382 26.09
 Level 2240,126 32.32 115,045 32.12 125,081 32.51
 Level 3115,321 15.52 52,993 14.79 62,328 16.20
 Level 4104,346 14.05 49,332 13.77 55,014 14.30
 Level 517,554 2.36 8569 2.39 8985 2.34
 Level 631,709 4.27 14,535 4.06 17,174 4.46
 Level 728,742 3.87 12,990 3.63 15,752 4.09
DCSI score c <0.001
 0449,726 60.54 212,961 59.45 236,765 61.54
 1158,619 21.35 76,184 21.27 82,435 21.43
 ≥2134,572 18.11 69,056 19.28 65,516 17.03
Hypertension <0.001
 No407,559 54.86 191,320 53.41 216,239 56.21
 Yes335,358 45.14 166,881 46.59 168,477 43.79
Hyperlipidemia <0.001
 No584,466 78.67 269,156 75.14 315,310 81.96
 Yes158,451 21.33 89,045 24.86 69,406 18.04
Hyperuricemia <0.001
 No736,469 99.13 354,603 99.00 381,866 99.26
 Yes6448 0.87 3598 1.00 2850 0.74
Cerebrovascular disease <0.001
 No704,412 94.82 337,392 94.19 367,020 95.40
 Yes38,505 5.18 20,809 5.81 17,696 4.60
Coronary artery disease <0.001
 No678,208 91.29 323,771 90.39 354,437 92.13
 Yes64,709 8.71 34,430 9.61 30,279 7.87
Arrhythmia <0.001
 No711,085 95.72 340,798 95.14 370,287 96.25
 Yes31,832 4.28 17,403 4.86 14,429 3.75
Heart failure <0.001
 No728,751 98.09 350,928 97.97 377,823 98.21
 Yes14,166 1.91 7273 2.03 6893 1.79
Anxiety <0.001
 No669,132 90.07 318,432 88.90 350,700 91.16
 Yes73,785 9.93 39,769 11.10 34,016 8.84
Depression <0.001
 No739,016 99.47 356,096 99.41 382,920 99.53
 Yes3901 0.53 2105 0.59 1796 0.47
COPD c <0.001
 No697,869 93.94 333,813 93.19 364,056 94.63
 Yes45,048 6.06 24,388 6.81 20,660 5.37
Chronic kidney disease <0.001
 No736,925 99.19 353,755 98.76 383,170 99.60
 Yes5992 0.81 4446 1.24 1546 0.40
Obesity 0.008
 No739,680 99.56 356,716 99.59 382,964 99.54
 Yes3237 0.44 1485 0.41 1752 0.46
Alcoholism 0.824
 No742,478 99.94 357,987 99.94 384,491 99.94
 Yes439 0.06 214 0.06 225 0.06
a The premium-based salary of the patient which is according to the payroll bracket table of the National Health Insurance Administration Taiwan. NTD is New Taiwan Dollar. NTD 1 ≈ USD 0.034). b Level 1 denoted the highest degree of urbanization, whereas level 7 denoted the lowest degree of urbanization. c Abbreviations: DCSI, diabetes complications severity index; COPD, chronic obstructive pulmonary disease.
Table 2. Three-year follow-up of incident Parkinson’s disease in new-onset diabetes mellitus patients with metformin medication.
Table 2. Three-year follow-up of incident Parkinson’s disease in new-onset diabetes mellitus patients with metformin medication.
VariablesThree-Year Follow-Up
Events%Adjusted Model 1Adjusted Model 2
OR95% CIp-ValueOR95% CIp-Value
Total3977 0.54
cDDD of metformin use
 Non-users2223 0.62 1
 <300 1728 0.46 0.88 0.83–0.94<0.001---
 300–50023 0.45 1.09 0.72–1.65 0.676 ---
 ≥5003 1.27 2.59 0.83–8.03 0.100 ---
Intensity of metformin use
 Non-users2223 0.62 1
 <101292 0.46 ---0.87 0.81–0.93 <0.001
 10–25436 0.43 ---0.92 0.83–1.02 0.127
 ≥2526 0.48 ---1.17 0.80–1.72 0.426
Gender
 Female2078 0.54 1 1
 Male1899 0.53 1.04 0.98–1.11 0.205 1.04 0.98–1.11 0.215
Age (year)
 50–64940 0.20 1 1
 65–741617 0.88 3.95 3.64–4.29 <0.0013.96 3.64–4.30 <0.001
 ≥751420 1.70 7.01 6.42–7.65 <0.0017.02 6.43–7.67 <0.001
Income level (NTD) a
 ≤21,0002475 0.64 1 1
 21,001–33,000803 0.46 0.96 0.88–1.04 0.272 0.96 0.88–1.04 0.274
 ≥33,001699 0.39 0.91 0.83–0.99 0.033 0.91 0.83–0.99 0.033
Urbanization b
 Level 1919 0.45 1 1
 Level 21167 0.49 1.09 1.00–1.18 0.066 1.09 1.00–1.18 0.066
 Level 3599 0.52 1.09 0.98–1.21 0.098 1.09 0.98–1.21 0.098
 Level 4712 0.68 1.25 1.13–1.38 <0.0011.25 1.13–1.38 <0.001
 Level 5169 0.96 1.47 1.25–1.74 <0.0011.47 1.25–1.74 <0.001
 Level 6230 0.73 1.20 1.04–1.39 0.014 1.20 1.04–1.39 0.013
 Level 7181 0.63 1.10 0.94–1.29 0.239 1.10 0.94–1.30 0.236
DCSI score c
 01735 0.39 1 1
 1890 0.56 1.16 1.06–1.26 <0.0011.16 1.06–1.26 <0.001
 ≥21352 1.00 1.49 1.37–1.63 <0.0011.49 1.37–1.63 <0.001
Hypertension
 No1747 0.43 1 1
 Yes2230 0.66 0.98 0.91–1.05 0.531 0.98 0.91–1.05 0.529
Hyperlipidemia
 No3107 0.53 1 1
 Yes870 0.55 0.90 0.83–0.98 0.010 0.90 0.83–0.98 0.010
Hyperuricemia
 No3931 0.53 1 1
 Yes46 0.71 1.12 0.84–1.50 0.436 1.12 0.84–1.50 0.435
Cerebrovascular disease
 No3398 0.48 1 1
 Yes579 1.50 1.55 1.41–1.71 <0.0011.55 1.41–1.71 <0.001
Coronary artery disease
 No3376 0.50 1 1
 Yes601 0.93 1.05 0.95–1.15 0.351 1.05 0.95–1.15 0.351
Arrhythmia
 No3683 0.52 1 1
 Yes294 0.92 1.01 0.89–1.14 0.909 1.01 0.89–1.14 0.905
Heart failure
 No3831 0.53 1 1
 Yes146 1.03 0.83 0.70–0.99 0.039 0.83 0.70–0.99 0.039
Anxiety
 No3208 0.48 1 1
 Yes769 1.04 1.79 1.65–1.94 <0.0011.79 1.65–1.94 <0.001
Depression
 No3914 0.53 1 1
 Yes63 1.61 1.93 1.50–2.48 <0.0011.93 1.50–2.48 <0.001
COPD c
 No3527 0.51 1 1
 Yes450 1.00 1.15 1.04–1.27 0.006 1.15 1.04–1.27 0.006
Chronic kidney disease
 No3897 0.53 1 1
 Yes80 1.34 1.19 0.95–1.49 0.142 1.19 0.95–1.49 0.140
Obesity
 No3963 0.54 1 1
 Yes14 0.43 1.09 0.64–1.84 0.761 1.09 0.64–1.84 0.759
Alcoholism
 No3974 0.54 1 1
 Yes3 0.68 1.51 0.49–4.69 0.475 1.51 0.49–4.69 0.476
a The premium-based salary of the patient which is according to the payroll bracket table of the National Health Insurance Administration Taiwan. NTD is New Taiwan Dollar. NTD 1 ≈ USD 0.034). b Level 1 denoted the highest degree of urbanization, whereas level 7 denoted the lowest degree of urbanization. c Abbreviations: DCSI, diabetes complications severity index; COPD, chronic obstructive pulmonary disease.
Table 3. Five-year follow-up of incident Parkinson’s disease in new-onset diabetes mellitus patients with metformin medication.
Table 3. Five-year follow-up of incident Parkinson’s disease in new-onset diabetes mellitus patients with metformin medication.
VariablesFive-Year Follow-Up of Incident Parkinson’s Disease
Events%Adjusted Model 1Adjusted Model 2
OR95% CIp-ValueOR95% CIp-Value
Total8488 1.14
cDDD of metformin use
 Non-users4584 1.28 1
 <300 3856 1.02 0.94 0.90–0.98 0.006 ---
 300–50045 0.88 1.01 0.75–1.35 0.969 ---
 ≥5003 1.27 1.24 0.40–3.86 0.706 ---
Intensity of metformin use
 Non-users4584 1.28 1
 <102890 1.04 ---0.93 0.89–0.98 0.003
 10–25966 0.96 ---0.97 0.90–1.04 0.365
 ≥2548 0.90 ---1.02 0.77–1.35 0.900
Gender
 Female4463 1.17 1 1
 Male4025 1.12 1.03 0.99–1.08 0.138 1.03 0.99–1.08 0.144
Age (year)
 50–642161 0.45 1 1
 65–743560 1.94 3.88 3.67–4.10 <0.0013.88 3.67–4.10 <0.001
 ≥752767 3.31 6.22 5.86–6.60 <0.0016.22 5.86–6.61 <0.001
Income level (NTD) a
 ≤21,0005239 1.36 1 1
 21,001–33,0001728 0.98 0.96 0.90–1.01 0.099 0.96 0.90–1.01 0.101
 ≥33,0011521 0.84 0.90 0.84–0.95 <0.0010.90 0.84–0.95 <0.001
Urbanization b
 Level 12093 1.02 1 1
 Level 22466 1.03 1.01 0.95–1.07 0.879 1.01 0.95–1.07 0.878
 Level 31297 1.12 1.04 0.97–1.11 0.323 1.04 0.97–1.11 0.322
 Level 41453 1.39 1.12 1.05–1.20 <0.0011.12 1.05–1.20 <0.001
 Level 5308 1.75 1.19 1.06–1.34 0.005 1.19 1.06–1.35 0.004
 Level 6482 1.52 1.11 1.01–1.23 0.040 1.11 1.01–1.23 0.039
 Level 7389 1.35 1.04 0.94–1.16 0.456 1.04 0.94–1.16 0.452
DCSI score c
 03889 0.86 1 1
 11970 1.24 1.16 1.09–1.22 <0.0011.16 1.09–1.22 <0.001
 ≥22629 1.95 1.35 1.27–1.43 <0.0011.35 1.27–1.43 <0.001
Hypertension
 No3785 0.93 1 1
 Yes4703 1.40 1.00 0.95–1.04 0.818 1.00 0.95–1.04 0.816
Hyperlipidemia
 No6633 1.13 1 1
 Yes1855 1.17 0.91 0.86–0.96 <0.0010.91 0.86–0.96 <0.001
Hyperuricemia
 No8402 1.14 1 1
 Yes86 1.33 1.01 0.81–1.25 0.944 1.01 0.81–1.25 0.941
Cerebrovascular disease
 No7375 1.05 1 1
 Yes1113 2.89 1.50 1.40–1.61 <0.0011.50 1.40–1.61 <0.001
Coronary artery disease
 No7259 1.07 1 1
 Yes1229 1.90 1.04 0.97–1.11 0.249 1.04 0.97–1.11 0.250
Arrhythmia
 No7856 1.10 1 1
 Yes632 1.99 1.08 0.99–1.17 0.073 1.08 0.99–1.17 0.073
Heart failure
 No8193 1.12 1 1
 Yes295 2.08 0.87 0.77–0.98 0.027 0.87 0.77–0.98 0.026
Anxiety
 No6917 1.03 1 1
 Yes1571 2.13 1.74 1.64–1.84 <0.0011.74 1.64–1.84 <0.001
Depression
 No8376 1.13 1 1
 Yes112 2.87 1.67 1.38–2.01 <0.0011.67 1.38–2.01 <0.001
COPD c
 No7583 1.09 1 1
 Yes905 2.01 1.13 1.05–1.21 <0.0011.13 1.05–1.21 <0.001
Chronic kidney disease
 No8351 1.13 1 1
 Yes137 2.29 1.06 0.89–1.26 0.502 1.06 0.89–1.26 0.499
Obesity
 No8465 1.14 1 1
 Yes23 0.71 0.81 0.54–1.22 0.314 0.81 0.54–1.22 0.313
Alcoholism
 No8483 1.14 1 1
 Yes5 1.14 1.18 0.49–2.83 0.718 1.18 0.49–2.83 0.717
a The premium-based salary of the patient which is according to the payroll bracket table of the National Health Insurance Administration Taiwan. NTD is New Taiwan Dollar. NTD 1 ≈ USD 0.034). b Level 1 denoted the highest degree of urbanization, whereas level 7 denoted the lowest degree of urbanization. c Abbreviations: DCSI, diabetes complications severity index; COPD, chronic obstructive pulmonary disease.
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Huang, K.-H.; Chang, Y.-L.; Gau, S.-Y.; Tsai, T.-H.; Lee, C.-Y. Dose–Response Association of Metformin with Parkinson’s Disease Odds in Type 2 Diabetes Mellitus. Pharmaceutics 2022, 14, 946. https://doi.org/10.3390/pharmaceutics14050946

AMA Style

Huang K-H, Chang Y-L, Gau S-Y, Tsai T-H, Lee C-Y. Dose–Response Association of Metformin with Parkinson’s Disease Odds in Type 2 Diabetes Mellitus. Pharmaceutics. 2022; 14(5):946. https://doi.org/10.3390/pharmaceutics14050946

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Huang, Kuang-Hua, Ya-Lan Chang, Shuo-Yan Gau, Tung-Han Tsai, and Chien-Ying Lee. 2022. "Dose–Response Association of Metformin with Parkinson’s Disease Odds in Type 2 Diabetes Mellitus" Pharmaceutics 14, no. 5: 946. https://doi.org/10.3390/pharmaceutics14050946

APA Style

Huang, K. -H., Chang, Y. -L., Gau, S. -Y., Tsai, T. -H., & Lee, C. -Y. (2022). Dose–Response Association of Metformin with Parkinson’s Disease Odds in Type 2 Diabetes Mellitus. Pharmaceutics, 14(5), 946. https://doi.org/10.3390/pharmaceutics14050946

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