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Efthymiou D, Katsiki N, Zekakos DX, Vassiliadis P, Petrelis A, Vassilopoulou E. Gait Analysis, Metabolic Parameters and Adherence to the Mediterranean Diet in Patients with Type 2 Diabetes Mellitus Compared with Healthy Controls: A Pilot Study. Nutrients 2023; 15:3421. [PMID: 37571358 PMCID: PMC10420976 DOI: 10.3390/nu15153421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 07/30/2023] [Accepted: 07/31/2023] [Indexed: 08/13/2023] Open
Abstract
BACKGROUND AND PURPOSE Patients with type 2 diabetes mellitus (T2DM) are prone to developing diabetic peripheral neuropathy (DPN) with an increased risk of injuries while walking, potentially leading to plantar ulcers. We aimed to assess the early gait changes in T2DM patients without clinical signs of DPN in comparison to age-matched healthy controls (HC). SUBJECTS AND METHODS One hundred T2DM patients (78 women, mean age: 66.4 ± 11.5 years) and 50 age-matched HC (34 women, mean age 62.1 ± 7.9 years) were evaluated with the PODOSmart® gait analysis device. Anthropometric and biochemical data, as well as dietary habits were collected for all participants. T2DM patients also completed the Diabetes Distress (DS) self-report validated questionnaire. RESULTS One patient was excluded from the study due to lack of recent biochemical data. Among the T2DM patients, 88.9% reported little or no DS and 11.1% moderate DS. The T2DM group had higher body mass index, waist circumference, systolic blood pressure, glycated hemoglobin A1c, sodium, white blood cell count, triglycerides and low-density lipoprotein cholesterol, but lower high-density lipoprotein cholesterol than HC (p < 0.05 for all comparisons). The MedDiet score was satisfactory in both groups (p > 0.05). Significant differences were found between the two study groups in gaitline heel off, propulsion speed, foot progression angle, time taligrade phase, stride length, walking speed, angle attack, oscillation speed, pronation-supination toe off and clearance. CONCLUSIONS The T2DM patients without self-reported DS or clinical signs of DPN may exhibit significant differences in several gait parameters analyzed with PODOSmart®. Whether gait analysis can be used as an early diagnostic tool of T2DM complications should be further explored.
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Affiliation(s)
| | - Niki Katsiki
- Department of Nutritional Sciences and Dietetics, International Hellenic University, 57400 Thessaloniki, Greece;
- School of Medicine, European University Cyprus, 2404 Nicosia, Cyprus
| | | | | | | | - Emilia Vassilopoulou
- Nous Therapy Center, 1 Aggelaki Street, 54621 Thessaloniki, Greece;
- Department of Nutritional Sciences and Dietetics, International Hellenic University, 57400 Thessaloniki, Greece;
- Pediatric Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
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Wu X, Guo J, Chen X, Han P, Huang L, Peng Y, Zhou X, Huang J, Wei C, Zheng Y, Zhang Z, Li M, Guo Q. Comparison of the relationship between cognitive function and future falls in Chinese community-dwelling older adults with and without diabetes mellitus. J Formos Med Assoc 2023; 122:603-611. [PMID: 36336606 DOI: 10.1016/j.jfma.2022.10.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 10/14/2022] [Accepted: 10/17/2022] [Indexed: 11/06/2022] Open
Abstract
OBJECTIVE The aim of this study was to determine whether cognitive function is associated with future falls in older patients with diabetes mellitus (DM) compared with those without DM. Cognitive function was divided into several domains to further analyze. METHODS A total of 678 individuals met the inclusion criteria and comprised the final study population. The mean age was 74.35 ± 5.35 years, and 58.9% of the participants were female (n = 400). At the baseline, cognitive function was measured by the Mini Mental State Examination (MMSE), and DM diagnoses were determined by medical records. The self-reported any falls data were obtained via face-to-face questioning at the 1-year follow-up. RESULTS At baseline, 15.6% of participants (n = 106) were diagnosed with DM. According to whether they had any falls during 1-year follow-up, there was a significant difference between the two group in fasting plasma glucose (p = 0.012) and DM (p = 0.036) at baseline. Among the older adults with DM, those who had experienced any falls had poorer cognitive function (p = 0.014). After adjusting for various covariates, we found that MMSE (95% CI 0.790-0.991, p = 0.034), orientation to place (95% CI 0.307-0.911, p = 0.022) and registration (95% CI 0.162-0.768, p = 0.009) were significantly associated with falls in the follow-up. CONCLUSION Our study found that in patients with DM, cognitive function is related to future falls. Not only overall cognitive function, but also orientation to place and registration were all associated with future falls in older adults with DM. When completing the fall risk assessment of elderly patients with DM, clinicians should give more attention to the testing of cognitive function.
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Affiliation(s)
- Xinze Wu
- Department of Rehabilitation Medicine, Tianjin Medical University, Tianjin, China; Department of Internal Medicine and Rehabilitation Science, Tohoku University Graduate School of Medicine, Tohoku University, Sendai, Japan; Department of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Pudong New District, Shanghai, China
| | - Jinlong Guo
- Department of Rehabilitation Medicine, Tianjin Medical University, Tianjin, China
| | - Xinlong Chen
- Department of Rehabilitation Medicine, Tianjin Medical University, Tianjin, China
| | - Peipei Han
- Department of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Pudong New District, Shanghai, China
| | - Liqin Huang
- Department of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Pudong New District, Shanghai, China
| | - Youran Peng
- Department of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Pudong New District, Shanghai, China
| | - Xin Zhou
- Department of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Pudong New District, Shanghai, China
| | - Jiasen Huang
- Department of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Pudong New District, Shanghai, China
| | - Chengyao Wei
- Department of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Pudong New District, Shanghai, China
| | | | | | - Ming Li
- Department of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Pudong New District, Shanghai, China
| | - Qi Guo
- Department of Rehabilitation Medicine, Tianjin Medical University, Tianjin, China; Department of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Pudong New District, Shanghai, China.
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