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Karter AJ, Parker MM, Huang ES, Seligman HK, Moffet HH, Ralston JD, Liu JY, Gilliam LK, Laiteerapong N, Grant RW, Lipska KJ. Food Insecurity and Hypoglycemia among Older Patients with Type 2 Diabetes Treated with Insulin or Sulfonylureas: The Diabetes & Aging Study. J Gen Intern Med 2024:10.1007/s11606-024-08801-y. [PMID: 38767746 DOI: 10.1007/s11606-024-08801-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 05/07/2024] [Indexed: 05/22/2024]
Abstract
BACKGROUND Severe hypoglycemia is a serious adverse drug event associated with hypoglycemia-prone medications; older patients with diabetes are particularly at high risk. Economic food insecurity (food insecurity due to financial limitations) is a known risk factor for hypoglycemia; however, less is known about physical food insecurity (due to difficulty cooking or shopping for food), which may increase with age, and its association with hypoglycemia. OBJECTIVE Study associations between food insecurity and severe hypoglycemia. DESIGN Survey based cross-sectional study. PARTICIPANTS Survey responses were collected in 2019 from 1,164 older (≥ 65 years) patients with type 2 diabetes treated with insulin or sulfonylureas. MAIN MEASURES Risk ratios (RR) for economic and physical food insecurity associated with self-reported severe hypoglycemia (low blood glucose requiring assistance) adjusted for age, financial strain, HbA1c, Charlson comorbidity score and frailty. Self-reported reasons for hypoglycemia endorsed by respondents. KEY RESULTS Food insecurity was reported by 12.3% of the respondents; of whom 38.4% reported economic food insecurity only, 21.1% physical food insecurity only and 40.5% both. Economic food insecurity and physical food insecurity were strongly associated with severe hypoglycemia (RR = 4.3; p = 0.02 and RR = 4.4; p = 0.002, respectively). Missed meals ("skipped meals, not eating enough or waiting too long to eat") was the dominant reason (77.5%) given for hypoglycemia. CONCLUSIONS Hypoglycemia prevention efforts among older patients with diabetes using hypoglycemia-prone medications should address food insecurity. Standard food insecurity questions, which are used to identify economic food insecurity, will fail to identify patients who have physical food insecurity only.
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Affiliation(s)
- Andrew J Karter
- Kaiser Permanente Northern California Division of Research, Pleasanton, CA, USA.
| | - Melissa M Parker
- Kaiser Permanente Northern California Division of Research, Pleasanton, CA, USA
| | - Elbert S Huang
- Section of General Internal Medicine, Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Hilary K Seligman
- Division of General Internal Medicine at San Francisco General Hospital, University of California San Francisco Center for Vulnerable Populations, San Francisco, CA, USA
| | - Howard H Moffet
- Kaiser Permanente Northern California Division of Research, Pleasanton, CA, USA
| | - James D Ralston
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Jennifer Y Liu
- Kaiser Permanente Northern California Division of Research, Pleasanton, CA, USA
| | - Lisa K Gilliam
- Kaiser Northern California Diabetes Program, Endocrinology and Internal Medicine, Kaiser Permanente, South San Francisco Medical Center, South San Francisco, CA, USA
| | - Neda Laiteerapong
- Section of General Internal Medicine, Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Richard W Grant
- Kaiser Permanente Northern California Division of Research, Pleasanton, CA, USA
| | - Kasia J Lipska
- Section of Endocrinology, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
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Chen HF, Lin HR. Social determinants of ambulatory care sensitive conditions: a qualitative meta-synthesis based on patient perspectives. Front Public Health 2023; 11:1147732. [PMID: 37228726 PMCID: PMC10203230 DOI: 10.3389/fpubh.2023.1147732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 04/11/2023] [Indexed: 05/27/2023] Open
Abstract
Background Hospitalizations or emergency department (ED) visits due to ambulatory care-sensitive conditions (ACSC) are preventable but cost billions in modern countries. The objective of the study is to use a meta-synthesis approach based on patients' narratives from qualitative studies to reveal why individuals are at risk of ACSC hospitalizations or ED visits. Methods PubMed, Embase, Cochrane Library, and Web of Science databases were utilized to identify qualified qualitative studies. The Preferred Reporting Items for Systematic Review and Meta-Analysis were used for reporting the review. The thematic synthesis was used to analyze the data. Results Among 324 qualified studies, nine qualitative studies comprising 167 unique individual patients were selected based on the inclusion/exclusion criteria. Through the meta-synthesis, we identified the core theme, four major themes, and the corresponding subthemes. Poor disease management, the core theme, turns individuals at risk of ACSC hospitalizations or ED visits. The four major themes contribute to poor disease management, including difficulties in approaching health services, non-compliance with medications, difficulties in managing the disease at home, and poor relationships with providers. Each major theme comprised 2-4 subthemes. The most cited subthemes are relative to upstream social determinants, such as financial constraints, inaccessible health care, low health literacy, psychosocial or cognitive constraints. Conclusion Without addressing upstream social determinants, socially vulnerable patients are unlikely to manage their disease well at home even though they know how to do it and are willing to do it. Trial registration National Library of Medicine, with ClinicalTrials.gov, Identifier: NCT05456906. https://clinicaltrials.gov/ct2/show/NCT05456906.
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Affiliation(s)
- Hsueh-Fen Chen
- Department of Healthcare Administration and Medical Informatics, College of Health Sciences, Kaohsiung Medical University, Kaohsiung City, Taiwan
- Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung City, Taiwan
- Center for Big Data Research, Kaohsiung Medical University, Kaohsiung City, Taiwan
| | - Hung-Ru Lin
- School of Nursing, National Taipei University of Nursing and Health Sciences, Taipei City, Taiwan
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Qi X, Xu J, Chen G, Liu H, Liu J, Wang J, Zhang X, Hao Y, Wu Q, Jiao M. Self-management behavior and fasting plasma glucose control in patients with type 2 diabetes mellitus over 60 years old: multiple effects of social support on quality of life. Health Qual Life Outcomes 2021; 19:254. [PMID: 34772424 PMCID: PMC8588678 DOI: 10.1186/s12955-021-01881-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Accepted: 10/04/2021] [Indexed: 12/26/2022] Open
Abstract
OBJECTIVE Elderly patients with type 2 diabetes mellitus are highly vulnerable due to severe complications. However, there is a contradiction in the relationship between social support and quality of life, which warrants further exploration of the internal mechanism. This study assessed the quality of life and its interfering factors in this patient population. METHODS In total, 571 patients with type 2 diabetes mellitus over 60 years old were recruited from two community clinics in Heilongjiang Province, China. We collected data on health status, quality of life, self-management behavior, fasting plasma glucose (FPG) level, and social support. Structural equation modeling and the bootstrap method were used to analyze the data. RESULTS The average quality of life score was - 29.25 ± 24.41. Poorly scored domains of quality of life were "Psychological feeling" (- 8.67), "Activity" (- 6.36), and "Emotion" (- 6.12). Of the 571 patients, 65.32% had normal FPG, 9.8% had high-risk FPG, 15.94% had good self-management behavior, and 22.07% had poor social support. Significant correlations among social support, self-management behavior, FPG level, and quality of life were noted. A multiple mediator model revealed that social support influenced quality of life in three ways: (1) directly (c' = 0.6831); (2) indirectly through self-management behavior (a1*b1 = 0.1773); and (3) indirectly through FPG control (a2*b2 = 0.1929). Self-management behavior influenced the quality of life directly and indirectly through FPG control. CONCLUSION Improving self-management behavior and monitoring hypoglycemia should become priority targets for future intervention. Scheduled social support to self-management projects should be put into the standardized management procedure. Physicians should provide substantial and individualized support to the elderly patients with type 2 diabetes mellitus regarding medication, blood glucose monitoring, and physical exercise.
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Affiliation(s)
- Xinye Qi
- Department of Health Policy, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, Heilongjiang China
- Department of Social Medicine, School of Public Health, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, Heilongjiang China
| | - Jiao Xu
- Department of Health Policy, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, Heilongjiang China
- Department of Social Medicine, School of Public Health, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, Heilongjiang China
| | - Guiying Chen
- Department of Cardiology, First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang China
| | - Huan Liu
- Department of Health Policy, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, Heilongjiang China
- Department of Social Medicine, School of Public Health, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, Heilongjiang China
| | - Jingjing Liu
- Department of Health Policy, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, Heilongjiang China
- Department of Social Medicine, School of Public Health, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, Heilongjiang China
| | - Jiahui Wang
- Department of Health Policy, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, Heilongjiang China
- Department of Social Medicine, School of Public Health, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, Heilongjiang China
| | - Xin Zhang
- Department of Health Policy, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, Heilongjiang China
- Department of Social Medicine, School of Public Health, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, Heilongjiang China
| | - Yanhua Hao
- Department of Health Policy, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, Heilongjiang China
- Department of Social Medicine, School of Public Health, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, Heilongjiang China
| | - Qunhong Wu
- Department of Health Policy, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, Heilongjiang China
- Department of Social Medicine, School of Public Health, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, Heilongjiang China
| | - Mingli Jiao
- Department of Health Policy, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, Heilongjiang China
- Department of Social Medicine, School of Public Health, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, Heilongjiang China
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Zhang M, Yan W, Yu Y, Cheng J, Yi X, Guo T, Liu N, Shang J, Wang Z, Hu H, Chen L. Liraglutide ameliorates diabetes-associated cognitive dysfunction via rescuing autophagic flux. J Pharmacol Sci 2021; 147:234-244. [PMID: 34507632 DOI: 10.1016/j.jphs.2021.07.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Revised: 06/28/2021] [Accepted: 07/15/2021] [Indexed: 01/16/2023] Open
Abstract
The incidence of diabetes-associated cognitive dysfunction is increasing. However, few clinical interventions are available to prevent the disorder. Several researches have shown that liraglutide, as a glucagon-like peptide-1 analog, has protective effects on various neurodegenerative diseases, but its roles in diabetic cognitive dysfunction are rarely reported. This study aims to investigate the protective effects of liraglutide on diabetic cognitive dysfunction and its underlying mechanisms. In vivo, the effects of liraglutide treatment were investigated in a mouse model of type 2 diabetes mellitus (T2DM). In vitro, we investigated the effects of liraglutide on the high-glucose-induced rat primary neurons. The results showed that liraglutide reduced the escape latency and increased the time in effective area in the Morris water maze test, improved the damage of hippocampal and synaptic ultrastructure, and decreased the accumulation of amyloid β protein in hippocampus of T2DM mice. Furthermore, liraglutide increased the ratio of microtubule-associated protein light 1 chain Ⅱ/Ⅰ, the expression of Beclin1 protein and Lysosome-associated membrane protein 2 in vivo and vitro. Additionally, Bafilomycin A1 which can inhibit the fusion of autophagosome and lysosome partially abolished the effects of liraglutide. These findings indicate liraglutide ameliorates diabetes-associated cognitive dysfunction by rescuing autophagic flux.
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Affiliation(s)
- Meng Zhang
- Department of Pharmacology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Wenhui Yan
- Department of Pharmacology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Ye Yu
- Department of Pharmacology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Jie Cheng
- Department of Pharmacology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Xinyao Yi
- Department of Pharmacology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Tingli Guo
- Department of Pharmacology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Na Liu
- Department of Pharmacology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Jia Shang
- Department of Pharmacology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Zhuanzhuan Wang
- Department of Pharmacology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Hao Hu
- Department of Pharmacology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Lina Chen
- Department of Pharmacology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China; Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University), Ministry of Education, Xi'an 710061, China.
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