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Periodontitis and non-communicable diseases in a Brazilian population, a cross-sectional study, Vila Velha-ES, Brazil
Gustavo Vital de Mendonça, Crispim Cerutti Junior, Alfredo Carlos Rodrigues Feitosa, Brígida Franco Sampaio de Mendonça, Lucia Helena Sagrillo Pimassoni
Osong Public Health Res Perspect. 2024;15(3):212-220.   Published online June 27, 2024
DOI: https://doi.org/10.24171/j.phrp.2024.0021
  • 1,309 View
  • 32 Download
Graphical AbstractGraphical Abstract AbstractAbstract PDF
Objectives
The objective of this study was to examine the hypothesis that periodontal disease is associated with chronic non-communicable diseases. Methods: In this cross-sectional study, we evaluated the periodontal health condition of the population, based on the community periodontal index, as well as the number of missing teeth and the presence of systemic health conditions. We quantified the association between oral health and the presence of chronic diseases using simple logistic regression, adjusting for confounding factors including age, smoking, and overweight. Results: The study population consisted of 334 volunteers, aged between 19 and 81 years. In patients over 45 years old, periodontal disease was found to be significantly associated with hypertension and diabetes. Furthermore, in female patients, periodontal disease was significantly associated with hypertension, diabetes, and cancer. Conclusion: Our findings indicate that periodontal disease is positively and significantly associated with both arterial hypertension and diabetes, independent of potential confounding factors.
Estimation of the onset time of diabetic complications in type 2 diabetes patients in Thailand: a survival analysis
Natthanicha Sauenram, Jutatip Sillabutra, Chukiat Viwatwongkasem, Pratana Satitvipawee
Osong Public Health Res Perspect. 2023;14(6):508-519.   Published online November 23, 2023
DOI: https://doi.org/10.24171/j.phrp.2023.0084
  • 2,390 View
  • 109 Download
Graphical AbstractGraphical Abstract AbstractAbstract PDF
Objectives
This study aimed to identify factors associated with the onset time of diabetic complications in patients with type 2 diabetes mellitus (T2DM) and determine the best-fitted survival model. Methods: A retrospective cohort study was conducted among T2DM patients enrolled from October 1, 2016 to July 15, 2020 at the National Health Security Office (NHSO). In total, 388 T2DM patients were included. Cox proportional-hazard and parametric models were used to identify factors related to the onset time of diabetic complications. The Akaike information criterion, Bayesian information criterion, and Cox-Snell residual were compared to determine the best-fitted survival model. Results: Thirty diabetic complication events were detected among the 388 patients (7.7%). A 90% survival rate for the onset time of diabetic complications was found at 33 months after the first T2DM diagnosis. According to multivariate analysis, a duration of T2DM ≥42 months (time ratio [TR], 0.56; 95% confidence interval [CI], 0.33–0.96; p=0.034), comorbid hypertension (TR, 0.30; 95% CI, 0.15–0.60; p=0.001), mildly to moderately reduced levels of the estimated glomerular filtration rate (eGFR) (TR, 0.43; 95% CI, 0.24–0.75; p=0.003) and an eGFR that was severely reduced or indicative of kidney failure (TR, 0.38; 95% CI, 0.16–0.88; p=0.025) were significantly associated with the onset time of diabetic complications (p<0.05). Conclusion: Patients with T2DM durations of more than 42 months, comorbid hypertension, and decreased eGFR were at risk of developing diabetic complications. The NHSO should be aware of these factors to establish a policy to prevent diabetic complications after the diagnosis of T2DM.
The risk associated with psychiatric disturbances in patients with diabetes in Indonesia (2018): a cross-sectional observational study
Siti Isfandari, Betty Roosihermiatie, Sulistyowati Tuminah, Laurentia Konadi Mihardja
Osong Public Health Res Perspect. 2023;14(5):368-378.   Published online October 18, 2023
DOI: https://doi.org/10.24171/j.phrp.2023.0144
Correction in: Osong Public Health Res Perspect 2023;14(6):530
  • 2,398 View
  • 86 Download
  • 2 Web of Science
  • 2 Crossref
Graphical AbstractGraphical Abstract AbstractAbstract PDF
Objectives
The global prevalence of psychiatric disturbances is rising, detrimentally affecting the quality of care and treatment outcomes for individuals, particularly those with diabetes.This study investigated the association of risk factors for psychiatric disturbances among productive-age patients with diabetes (ages 30−59 years), considering sociodemographic characteristics and co-existing diseases. The risk factors considered included sociodemographic factors (e.g., residence, age, sex, marital status, education, and occupation) and co-existing diseases (e.g., hypertension, heart disease, stroke, renal failure, rheumatism, asthma, and cancer). Methods: This cross-sectional study utilized data from the 2018 Indonesian National Health Survey (Riskesdas). The study population comprised respondents aged between 30 and 59 years who had diabetes and had completed the 20-question self-reporting questionnaire (SRQ-20). After the exclusion of incomplete SRQ-20 data, the sample included 8,917 respondents. Data were analyzed using logistic regression. Results: Approximately 18.29% of individuals with diabetes displayed symptoms indicative of psychiatric disturbances. After adjusting for sociodemographic factors such as age, sex, education level, occupation, marital status, and place of residence, patients with diabetes who had co-existing conditions such as hypertension, heart diseases, rheumatic disorders, asthma, or cancer had a higher risk for developing psychiatric disturbances than those with diabetes alone (adjusted odds ratio, 6.67; 95% confidence interval, 4.481−9.928; p<0.001). Conclusion: The elevated risk of psychiatric disturbances among patients with diabetes who had comorbidities underscores the importance of addressing mental health issues in the management of diabetes, especially in patients with concurrent disease conditions.

Citations

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  • Investigating the association between physical fitness and blood pressure among healthcare workers in Indonesia
    Wahyu Sulistiadi, Riswandy Wasir, Astriana, Badra Al Aufa, Sri Rahayu, Wasir Thalib, Fadilah Aulia Rahma
    Discover Social Science and Health.2024;[Epub]     CrossRef
  • Correction to “The risk associated with psychiatric disturbances in patients with diabetes in Indonesia (2018): a cross-sectional observational study” [Osong Public Health Res Perspect 2023;14(5):368–78]
    Siti Isfandari, Betty Roosihermiatie, Sulistyowati Tuminah, Laurentia Konadi Mihardja
    Osong Public Health and Research Perspectives.2023; 14(6): 530.     CrossRef
Chronic kidney disease in Indonesia: evidence from a national health survey
Puti Sari Hidayangsih, Dwi Hapsari Tjandrarini, Noor Edi Widya Sukoco, Nikson Sitorus, Ika Dharmayanti, Feri Ahmadi
Osong Public Health Res Perspect. 2023;14(1):23-30.   Published online February 14, 2023
DOI: https://doi.org/10.24171/j.phrp.2022.0290
  • 5,274 View
  • 360 Download
Graphical AbstractGraphical Abstract AbstractAbstract PDF
Objectives
Several previous studies have stated that consuming certain foods and beverages might increase the risk of chronic kidney disease (CKD). This study aimed to examine the relationships of food and beverage consumption with other risk factors for CKD. Methods: Data sources included the 2018 Basic Health Research (Riskesdas) and the National Socio-Economic Survey (Susenas), which were analyzed using a cross-sectional design. The study samples were households from 34 provinces in Indonesia, and the analysis was performed with provincial aggregates. Data were analyzed using risk factor analysis followed by linear regression to identify relationships with CKD. Results: The prevalence of CKD in Indonesia was 0.38%. The province with the highest prevalence was North Kalimantan (0.64%), while the lowest was found in West Sulawesi (0.18%). Five major groups were formed from 15 identified risk factors using factor analysis. A linear regression model presented 1 significant selected factor (p=0.006, R2 =31%). The final model of risk factors included water quality, consumption of fatty foods, and a history of diabetes. Conclusion: Drinking water quality, fatty food consumption, and diabetes are associated with CKD. There is a need to monitor drinking water, as well as to promote health education and provide comprehensive services for people with diabetes, to prevent CKD.
Insufficient weight management in pregnant women with gestational diabetes mellitus
Kyunghee Han, Dong Wook Kwak, Hyun Mee Ryu, Hyun-Young Park
Osong Public Health Res Perspect. 2022;13(4):242-251.   Published online August 31, 2022
DOI: https://doi.org/10.24171/j.phrp.2022.0182
  • 3,053 View
  • 102 Download
  • 1 Web of Science
  • 1 Crossref
Graphical AbstractGraphical Abstract AbstractAbstract PDF
Objectives
This study investigated whether weight was managed appropriately in pregnant women with gestational diabetes mellitus (GDM) and examined the association between insufficient gestational weight gain (GWG) and adverse pregnancy outcomes.
Methods
The study included 235 pregnant women with GDM from the Korean Pregnancy Outcome Study. GWG from the second to the third trimester (kg/wk) and total GWG (kg) were classified as insufficient, appropriate, or excessive according to the 2009 Institute of Medicine guidelines. Adverse pregnancy outcomes included maternal (hypertensive disorders of pregnancy, preterm birth, cesarean delivery, and delivery complications) and infant (low birth weight, high birth weight, neonatal intensive care unit admission, and congenital anomalies) outcomes.
Results
The proportion of pregnant women with GDM who had insufficient GWG from the second to the third trimester was 52.3%, and that of participants with total insufficient GWG was 48.1%. There were no significant associations between insufficient GWG from the second to the third trimester and adverse pregnancy outcomes. Participants with total insufficient GWG had a significantly lower risk of preterm birth (odds ratio [OR], 0.17; 95% confidence interval [CI], 0.05–0.60) and high birth weight (OR, 0.23; 95% CI, 0.07–0.80).
Conclusion
Our findings suggest the importance of appropriate weight management and the need for GWG guidelines for pregnant women with GDM.

Citations

Citations to this article as recorded by  
  • Risk factors and prediction model for low-birth-weight infants born to women with gestational diabetes mellitus
    Yu-qing Pan, Xin-xin Huang, Xiu-min Jiang
    Frontiers in Public Health.2024;[Epub]     CrossRef
Educational Needs Associated with the Level of Complication and Comparative Risk Perceptions in People with Type 2 Diabetes
Youngji Hwang, Dongsuk Lee, Yeon Sook Kim
Osong Public Health Res Perspect. 2020;11(4):170-176.   Published online August 31, 2020
DOI: https://doi.org/10.24171/j.phrp.2020.11.4.05
  • 6,031 View
  • 168 Download
  • 1 Crossref
AbstractAbstract PDF
Objectives

This study aimed to identify the educational needs of people with type 2 diabetes according to risk perceptions and the level of severity of complications.

Methods

There were 177 study participants who were outpatients of the internal medicine department at a university hospital located in the Republic of Korea, who consented to participate in the survey from December 10, 2016 to February 10, 2017. The data were analyzed using descriptive statistics, Pearson correlation, ANOVA with post-hoc comparison, and multiple regression analysis. Type 2 diabetes complications were classified into 3 groups: no complications, common complications, and severe complications.

Results

There were statistically significant positive correlations between educational needs and comparative risk perceptions, and the level of complication and comparative risk perception. Multiple regression analysis revealed that the factor predicting educational needs of type 2 diabetes people was their comparative risk perceptions, rather than the severity of diabetes complications or sociodemographic variables.

Conclusion

Since risk perception is the factor that indicates the educational needs of people with type 2 diabetes, there is a need to explore factors which increase risk perception, in order to meet educational needs. The findings suggest that a more specific and individualized educational program, which focuses on each person's risk perceptions, should be developed.

Citations

Citations to this article as recorded by  
  • Determinants of Complications of Diabetic Among Adult with Type 2 Diabetic Patients at Hubaal Specialist Hospital and Libaan Hospital in Mogadishu: Case Control Study
    Ahmed Mohamed, Ali Mohamed, Ahmed Guled, Mohamed Fuji, Abdullahi Qoryoley, Abdirahman Hassan
    American Journal of Internal Medicine.2024; 12(5): 82.     CrossRef
Enrolment Phase Results of the Tabari Cohort Study: Comparing Family History, Lipids and Anthropometric Profiles Among Diabetic Patients
Mahmood Moosazadeh, Mahdi Afshari, Kaveh Jafari, Motahareh Kheradmand, Zahra Kashi, Mohsen Aarabi, Adeleh Bahar, Mohammad Khademloo
Osong Public Health Res Perspect. 2019;10(5):289-294.   Published online October 31, 2019
DOI: https://doi.org/10.24171/j.phrp.2019.10.5.05
  • 6,073 View
  • 70 Download
  • 4 Crossref
AbstractAbstract PDF
Objectives

Different factors are responsible for the silent epidemic of diabetes mellitus in developing and developed countries. This study aimed to determine the role of demographic factors, lipid profile, family history (the estimation of genetic association) and anthropometric factors on diabetes onset.

Methods

Data from the enrolment phase of the Tabari Cohort study was applied for this study and included 10,255 participants aged between 35–70 years. Anthropometric variables were measured by trained staff using standard tools. Blood specimens were collected for lipid profile and blood glucose measurements. Data analyses were performed using SPSS version 24, with univariate and multivariate logistic regression.

Results

The prevalence of diabetes mellitus was estimated to be 17.2% in the cohort population, 15.6% in men, and 18.3% in women. The adjusted odds ratios (95% confidence intervals) for age groups 40–49, 50–59 and over 60 were 2.58 (2.20–3.69), 5.80 (4.51–7.48) and 8.72 (6.67–11.39), respectively. In addition, the odds ratios (95% confidence intervals) for 2 (or more), and 1 affected family member were 4.12 (3.55–4.90) and 2.34 (2.07–2.65), respectively. Triglyceride concentrations more than 500, and abnormal high-density lipoprotein levels increased the odds of diabetes mellitus by 3.29- and 1.18-fold, respectively.

Conclusion

The current study showed that old age and a family history were strong predictors for diabetes mellitus.

Citations

Citations to this article as recorded by  
  • The prevalence and determinants of diabetes mellitus and thyroid disorder comorbidity in Tabari cohort population
    Mahmood Moosazadeh, Saeedeh Khakhki, Adele Bahar, Akbar Hedayatizadeh-Omran, Motahareh Kheradmand, Reza Alizadeh-Navaei, Erfan Ghadirzadeh
    Scientific Reports.2024;[Epub]     CrossRef
  • Free-fatty acid receptor-4 gene polymorphism (rs61866610) and colorectal cancer risk
    Ramin Shekarriz, Maryam Hasanian, Mohadeseh Ahmadi, Versa Omrani-Nava, Reza Alizadeh-Navaei
    Nucleosides, Nucleotides & Nucleic Acids.2024; : 1.     CrossRef
  • The relationship between spiritual intelligence and self-management in patients with diabetes type 1
    Sima Rafiei, Saber Souri, Zahra Nejatifar, Mohammad Amerzadeh
    BMC Endocrine Disorders.2023;[Epub]     CrossRef
  • Prevalence and determinants of diabetes and prediabetes in southwestern Iran: the Khuzestan comprehensive health study (KCHS)
    Sanam Hariri, Zahra Rahimi, Nahid Hashemi-Madani, Seyyed Ali Mard, Farnaz Hashemi, Zahra Mohammadi, Leila Danehchin, Farhad Abolnezhadian, Aliasghar Valipour, Yousef Paridar, Mohammad Mahdi Mir-Nasseri, Alireza Khajavi, Sahar Masoudi, Saba Alvand, Bahman
    BMC Endocrine Disorders.2021;[Epub]     CrossRef
Factors that Correlate with Poor Glycemic Control in Type 2 Diabetes Mellitus Patients with Complications
Mohammad Haghighatpanah, Amir Sasan Mozaffari Nejad, Maryam Haghighatpanah, Girish Thunga, Surulivelrajan Mallayasamy
Osong Public Health Res Perspect. 2018;9(4):167-174.   Published online August 31, 2018
DOI: https://doi.org/10.24171/j.phrp.2018.9.4.05
  • 10,465 View
  • 200 Download
  • 67 Crossref
AbstractAbstract PDF
Objectives

Inadequate glycemic control amongst patients with Type 2 diabetes mellitus (T2DM) indicates a major public health problem and a significant risk factor for the progression and complications caused by diabetes. Glycemic control is the main therapeutic objective for the prevention of organ damage and other complications arising from diabetes.

Methods

This was a retrospective observational study of T2DM patients with complications, who were aged 40 years and older. The study was conducted retrospectively on medical records (in-patient and out-patient) obtained from a South Indian teaching hospital, Manipal, India. The patients included in the study had fasting blood sugar, postprandial blood sugar and HbA1c measured at least twice during follow-ups the previous year. Patients’ HbA1c levels were categorized into good control ≤7% (≤53mmol/mol), and poor control >7% (>53mmol/mol), and patients’ characteristics were analyzed.

Results

A total of 657 patients were included in the study. The mean age was 59.67 (SD = 9.617) years, with 152 (23.1%) females and 505 (76.9%) males, and 514 (78.2%) patients had poor glycemic control. Most of the patients were on insulin mono-therapy [n = 271 (42.1%)], about a third of the patients were on combination therapy that included an oral hypoglycemic agent and insulin [n = 236 (36.6%)]. Patients with a history of more than 10 years of diabetes [n = 293 (44.6%)], had a family history of diabetes [n = 256 (39%)] and obesity [n = 95 (14.5%)], all had poor glycemic control.

Conclusion

This present study indicated a significant association of gender (female), age, high-density lipoprotein level, duration of diabetes and type of medication, with poor glycemic control in T2DM patients that had secondary medical complications.

Citations

Citations to this article as recorded by  
  • Effectiveness of Family-Based Diabetes Management Intervention on Glycated Haemoglobin Among Adults With Type 2 Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
    Margareta Teli, Ratsiri Thato, Faizul Hasan, Yohanes Andy Rias
    Biological Research For Nursing.2024; 26(2): 315.     CrossRef
  • Factors linked to poor glycemic control in an outpatient diabetic clinic: a cross-sectional study in Saint-Nicolas Hospital, Haiti
    Ludentz Dorcélus, Emmanuel R. Alexandre, Charnee M. Villemenay, Scaïde U. Benjaminel, Eddie Charles
    Journal of Global Health Reports.2024;[Epub]     CrossRef
  • The prevalence of hypogonadism in male patients with type 2 diabetes mellitus and clinically relevant factors
    Hakan Düğer
    Journal of Health Sciences and Medicine.2024; 7(1): 53.     CrossRef
  • Real-world effectiveness of iGlarLixi in individuals with T2D sub-optimally controlled on oral anti-diabetic drugs with or without basal insulin in daily practice in Saudi Arabia (EMPOWER study)
    Anwar Jammah, Nagwa Roushdy, Mohamed Gamil, Nidal Abu Diab, Naglaa Abdelmonaem, Saher Safarini, Mohamed Gadallah, Nedal Abu Zaid, Yahya Shihadeh, Mohamed Saeed, Jamaa Sadik, Yasser Akil
    Endocrine and Metabolic Science.2024; 15: 100164.     CrossRef
  • Rejuvenating Mobility: Impact of Concurrent Exercise on Functional Claudication Distance and Vascular Health among Patients with T2DM-Associated PAD
    Uroosa Amin, Qurat-ul-Ain Adnan, Dr. Tauseef Ahmad
    Allied Medical Research Journal.2024; : 138.     CrossRef
  • Exploring the Interplay of Socioeconomic and Behavioral Factors: Unraveling Gender Disparities in Glycemic Control Among Adult Type 2 Diabetic Patients in Outpatient Care
    Amar Mankar, Umesh Kawalkar, Nilesh Jadhao, Umesh Joge, Ashutosh Paldiwal, Manoj Talapalliwar, Manoj S Patil
    Cureus.2024;[Epub]     CrossRef
  • Landscape of pharmacogenetic variants associated with non-insulin antidiabetic drugs in the Indian population
    Ambily Sivadas, S Sahana, Bani Jolly, Rahul C Bhoyar, Abhinav Jain, Disha Sharma, Mohamed Imran, Vigneshwar Senthivel, Mohit Kumar Divakar, Anushree Mishra, Arpita Mukhopadhyay, Greg Gibson, KM Venkat Narayan, Sridhar Sivasubbu, Vinod Scaria, Anura V Kurp
    BMJ Open Diabetes Research & Care.2024; 12(2): e003769.     CrossRef
  • Prevalence of and factors associated with suboptimal glycemic control among patients with type 2 diabetes mellitus attending public hospitals in the Greater Male’ Region, Maldives: a hospital-based cross-sectional study
    Jeehana Shareef, Tawatchai Apidechkul, Peeradone Srichan
    BMC Public Health.2024;[Epub]     CrossRef
  • Exploring the self-efficacy of patients with diabetes: its role as a predictor of diabetes management and well-being
    Ayoub Ali Alshaikh, Faisal Saeed Al-Qahtani, Saif Aboud M. Alqahtani, Ahmad Ali AlFarhan, Ali Mushabbab Al Nuwayhidh, Ayman Mohammed Madkhali, Riyad Saeed AlQahtani, Ali Fayez AlAsmari, Abdulaziz Saeed Alserhani, Hatim Ahmed Alqubaisi, Ziyad Saad Saeed Al
    Frontiers in Endocrinology.2024;[Epub]     CrossRef
  • Dietary glycemic index and glycemic load predict longitudinal change in glycemic and cardio-metabolic biomarkers among old diabetic adults living in a resource-poor country
    Yen Nhi Hoang, Trong Hung Nguyen, Dang Khanh Ngan Ho, Chyi-Huey Bai, Wen-Ling Lin, Huong Duong Phan, Hoang Hiep Phan, Ngoc Luong Tran, Jung-Su Chang
    International Journal of Food Sciences and Nutriti.2024; 75(6): 550.     CrossRef
  • Impact of Gender and Age in HbA1c Levels among Libyan Adults Without Known Diabetes in Zeletin City, Libya: A Cross-Sectional Study
    Aisha Zaidi
    AlQalam Journal of Medical and Applied Sciences.2024; : 464.     CrossRef
  • The association between serum high-density lipoprotein and hemoglobin A1c in T2DM: Evidence from a nationwide cross-sectional study in diabetic patients
    Methavee Poochanasri, Sethapong Lertsakulbunlue, Chutawat Kookanok, Ram Rangsin, Wisit Kaewput, Boonsub Sakboonyarat, Mathirut Mungthin, Parinya Samakkarnthai
    Diabetes Epidemiology and Management.2024; 16: 100232.     CrossRef
  • Enhancing Type 2 Diabetes Treatment Decisions With Interpretable Machine Learning Models for Predicting Hemoglobin A1c Changes: Machine Learning Model Development
    Hisashi Kurasawa, Kayo Waki, Tomohisa Seki, Akihiro Chiba, Akinori Fujino, Katsuyoshi Hayashi, Eri Nakahara, Tsuneyuki Haga, Takashi Noguchi, Kazuhiko Ohe
    JMIR AI.2024; 3: e56700.     CrossRef
  • Patterns of glycaemic control and associated factors among adult patients with diabetes attending medical referral clinics in two public hospitals in North-West Ethiopia: a cross-sectional study
    Hailemariam Kassahun, Abere Genetu, Taye Abuhay, Hiwot Tesfa
    BMJ Public Health.2024; 2(2): e000828.     CrossRef
  • Prevalence and predictors of hypoglycemia in older outpatients with type 2 diabetes mellitus
    Ahmad Al-Azayzih, Roaa J. Kanaan, Shoroq M. Altawalbeh, Karem H. Alzoubi, Zelal Kharaba, Anan Jarab, Miquel Vall-llosera Camps
    PLOS ONE.2024; 19(8): e0309618.     CrossRef
  • Restriction of Rice Portion and Pre-Meal Fruit with HbA1c Levels and Abdominal Fat for Diabetics in Malang City
    Dwipajati Dwipajati, Sutomo Rum Teguh Kaswari
    Amerta Nutrition.2024; 8(1): 58.     CrossRef
  • Factors Associated with Achieving HbA1c Targets in Patients with Type 2 Diabetes
    Akram Mehrabbeik, Davood Tofighi, Saeed Hossein Khalilzadeh, Reyhaneh Azizi, Nasim Namiranian, Farzaneh Azad
    Jundishapur Journal of Chronic Disease Care.2024;[Epub]     CrossRef
  • A Long-Term Retrospective Real-World Evidence to Understand the Pattern of Insulin Prescription in Patients with Type 2 Diabetes Mellitus: Evaluating the Role of Insulin Initiation
    Shishir Kumar
    Journal of Diabetology.2024; 15(4): 429.     CrossRef
  • DESIGN, SYNTHESIS, AND BIO PROFILING OF 2, 3-DIHYDROQUINAZOLIN-4(1H)-ONE DERIVATIVE AS TYPE II DIABETES AGENTS: A COMPREHENSIVE IN SILICO, IN VITRO, AND IN VIVO STUDY
    MINCY MATHEW, D. KILIMOZHI, SANTHOSH M. MATHEWS, ANTON SMITH
    International Journal of Applied Pharmaceutics.2024; : 329.     CrossRef
  • Determinants of poor glycemic control among type 2 diabetes mellitus patients at University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia: Unmatched case-control study
    Gebrehiwot Lema Legese, Getahun Asres, Shitaye Alemu, Tesfaye Yesuf, Yeabsira Aklilu Tesfaye, Tsegaw Amare
    Frontiers in Endocrinology.2023;[Epub]     CrossRef
  • Prevalence of Glycemic Control and Factors Associated With Poor Glycemic Control: A Systematic Review and Meta-analysis
    Zebenay Workneh Bitew, Ayinalem Alemu, Desalegn Abebaw Jember, Erkihun Tadesse, Fekadeselassie Belege Getaneh, Awole Seid, Misrak Weldeyonnes
    INQUIRY: The Journal of Health Care Organization, .2023;[Epub]     CrossRef
  • Glycemic control and diabetes complications among adult type 2 diabetic patients at public hospitals in Hadiya zone, Southern Ethiopia
    Abraham Lomboro Dimore, Zerihun Kura Edosa, Asmelash Abera Mitiku, Suman S. Thakur
    PLOS ONE.2023; 18(3): e0282962.     CrossRef
  • Using Machine Learning for the Risk Factors Classification of Glycemic Control in Type 2 Diabetes Mellitus
    Yi-Ling Cheng, Ying-Ru Wu, Kun-Der Lin, Chun-Hung Lin, I-Mei Lin
    Healthcare.2023; 11(8): 1141.     CrossRef
  • Knowledge and Awareness About Diabetes Mellitus Among Urban and Rural Population Attending a Tertiary Care Hospital in Haryana
    Dr.Lalit Kumar, Rahul Mittal, Akhil Bhalla, Ashwani Kumar, Hritik Madan , Kushagra Pandhi, Yukta Garg, Kamaldeep Singh, Arpit Jain, Surya Rana
    Cureus.2023;[Epub]     CrossRef
  • Glycemic Control and Its associated Determinants among Type II Diabetic Patients at Tertiary Care Hospital in North India
    Soorvir singh Gurger, Anshu Mittal, Gauri shankar Goel, Anuj Mittal, Deepmala Kamboj
    Healthline.2023; 14(1): 17.     CrossRef
  • Prevalence of medication adherence and glycemic control among patients with type 2 diabetes and influencing factors: A cross-sectional study
    Budi Suprapti, Zamrotul Izzah, Ade Giriayu Anjani, Mareta Rindang Andarsari, Wenny Putri Nilamsari, Cahyo Wibisono Nugroho
    Global Epidemiology.2023; 5: 100113.     CrossRef
  • The impact of pharmacist interventions, follow-up frequency and default on glycemic control in Diabetes Medication Therapy Adherence Clinic program: a multicenter study in Malaysia
    Phei Ching Lim, Hooi Hoon Tan, Nurul Ain Mohd Noor, Chee Tao Chang, Te Ying Wong, Ee Linn Tan, Chiou Ting Ong, Kalyhani Nagapa, Lee Shyong Tai, Wei Ping Chan, Yong Boey Sin, Yin Shan Tan, Shanty Velaiutham, Rohaizan Mohd Hanafiah
    Journal of Pharmaceutical Policy and Practice.2023;[Epub]     CrossRef
  • Early detection system of risk factors for diabetes mellitus type 2 utilization of machine learning-random forest
    Johannes B. Ginting, Tri Suci, Chrismis N. Ginting, Ermi Girsang
    Journal of Family and Community Medicine.2023; 30(3): 171.     CrossRef
  • Identifying Profiles of Patients With Uncontrolled Type 2 Diabetes Who Would Benefit From Referral to an Endocrinologist
    Eden Avnat, Gabriel Chodick, Varda Shalev
    Endocrine Practice.2023; 29(11): 855.     CrossRef
  • Glycemic control and associated factors among type 2 diabetes mellitus patients: a cross-sectional study of Azar cohort population
    Masoud Faghieh Dinavari, Sarvin Sanaie, Kimia Rasouli, Elnaz Faramarzi, Roghayeh Molani-Gol
    BMC Endocrine Disorders.2023;[Epub]     CrossRef
  • Metabolic Biomarkers in Adults with Type 2 Diabetes: The Role of PPAR-γ2 and PPAR-β/δ Polymorphisms
    Sandra A. Reza-López, Susana González-Gurrola, Oscar O. Morales-Morales, Janette G. Moreno-González, Ana M. Rivas-Gómez, Everardo González-Rodríguez, Verónica Moreno-Brito, Angel Licón-Trillo, Irene Leal-Berumen
    Biomolecules.2023; 13(12): 1791.     CrossRef
  • Estimation of the onset time of diabetic complications in type 2 diabetes patients in Thailand: a survival analysis
    Natthanicha Sauenram, Jutatip Sillabutra, Chukiat Viwatwongkasem, Pratana Satitvipawee
    Osong Public Health and Research Perspectives.2023; 14(6): 508.     CrossRef
  • What drives glycemic control in a person living with diabetes?
    Rajiv Singla, Geetu Gupta, Yashdeep Gupta
    International Journal of Diabetes in Developing Co.2022; 42(2): 369.     CrossRef
  • Prevalence and predictors of suboptimal glycemic control among patients with type 2 diabetes mellitus in northern Thailand: A hospital-based cross-sectional control study
    Fartima Yeemard, Peeradone Srichan, Tawatchai Apidechkul, Naphat Luerueang, Ratipark Tamornpark, Suphaphorn Utsaha, Sompop Bencharit
    PLOS ONE.2022; 17(1): e0262714.     CrossRef
  • Exploring of Determinants Factors of Anti-Diabetic Medication Adherence in Several Regions of Asia – A Systematic Review
    Much Ilham Novalisa Aji Wibowo, Nanang Munif Yasin, Susi Ari Kristina, Yayi Suryo Prabandari
    Patient Preference and Adherence.2022; Volume 16: 197.     CrossRef
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Effects of Physical Activity on Depression in Adults with Diabetes
Deok-Ju Kim
Osong Public Health Res Perspect. 2018;9(4):143-149.   Published online August 31, 2018
DOI: https://doi.org/10.24171/j.phrp.2018.9.4.02
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AbstractAbstract PDF
Objectives

The purpose of this study was to identify the current state of physical activity in adults with diabetes and to investigate the effect of physical activity on depression.

Methods

The present study was conducted using data from the 2nd year of the 6th Korea National Health and Nutritional Examination Survey. From the total of 7,550 individuals, 418 adults diagnosed with diabetes were selected as participants, and their physical activity and depression levels were examined.

Results

The physical activity status of the participants showed that they did not usually engage in physical activities at work, and only a few participants were involved in moderate intensity physical leisure activity. Apart from walking for 10 minutes each day, which accounted for 1/3 of the participants, most of the participants did not engage in specific forms of exercise. An examination of the effects of physical activity on depression revealed that moderate intensity physical activity at work and leisure influenced depression. In terms of demographic characteristics, gender, occupation, income quintile, and subjective health status were all found to affect depression.

Conclusion

For elderly (60 years or older) patients with diabetes, which accounted for the majority of the diabetic population, a systematic leisure program and professional education are necessary to help them to manage stress and depression in daily life. Additionally, provision of community and family support should encourage regular, moderate intensity exercise and promote lifestyle changes to encourage increased physical activity.

Citations

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    A.H. Abdelhafiz, P.C. Davies, A.J. Sinclair
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Depression among Korean Adults with Type 2 Diabetes Mellitus: Ansan-Community-Based Epidemiological Study
Chan Young Park, So Young Kim, Jong Won Gil, Min Hee Park, Jong-Hyock Park, Yeonjung Kim
Osong Public Health Res Perspect. 2015;6(4):224-232.   Published online August 31, 2015
DOI: https://doi.org/10.1016/j.phrp.2015.05.004
  • 3,742 View
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  • 24 Crossref
AbstractAbstract PDF
Objectives
There are an increasing number of studies being carried out on depression in patients with diabetes. Individuals with diabetes have been reported as having a higher prevalence of depression compared to those without diabetes. However, only a few studies involving Korean patients have been conducted. The aims of this study were to examine the prevalence of depression and to find various risk factors according to the degree of depression among Korean patients with Type 2 diabetes mellitus (T2DM).
Methods
An Ansan-community-based epidemiological study was conducted from 2005 to 2012. The total number of participants in this study was 3,540, from which patients with diabetes (n = 753) have been selected. The presence of depression was evaluated using the Beck Depression Inventory total score.
Results
The prevalence of depression was 28.8%. The mean age of participants was 55.5 ± 8.2 years. We divided the participants into three groups (without-depression, moderate-depression, and severe-depression groups) to examine the depression prevalence among Korean T2DM patients. The unemployed participants had 2.40 [95% confidence interval (CI) 1.21–4.76], the low-income participants had 2.57 (95% CI 1.52–4.35), the participants using an oral diabetes medicine or insulin had 2.03 (95% CI 1.25–3.32), the participants who are currently smoking had 2.03 (95% CI 1.10–3.73), and those without regular exercise had 1.91 (95% CI 1.17–3.14) times higher odds of depression in the severe-depression group, compared with the without-depression group.
Conclusion
There was a significant association between depression prevalence and diabetes, and we found various risk factors according to the degree of depression in Korean patients with T2DM.

Citations

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  • Risk of Depression according to Cumulative Exposure to a Low-Household Income Status in Individuals with Type 2 Diabetes Mellitus: A Nationwide Population- Based Study
    So Hee Park, You-Bin Lee, Kyu-na Lee, Bongsung Kim, So Hyun Cho, So Yoon Kwon, Jiyun Park, Gyuri Kim, Sang-Man Jin, Kyu Yeon Hur, Kyungdo Han, Jae Hyeon Kim
    Diabetes & Metabolism Journal.2024; 48(2): 290.     CrossRef
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    Godwin Abah Akor, Nndunno Ashaku Akwaras, David Aondona Daniel, Laadi Swuende, Onuh Friday, Aganyi Paul
    International Journal of Innovative Science and Re.2024; : 1972.     CrossRef
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    Abdulrhman H. Alkhormi, Mohamed Salih Mahfouz, Najim Z. Alshahrani, Abdulrahman Hummadi, Wali A. Hakami, Doha H. Alattas, Hassan Q. Alhafaf, Leena E. Kardly, Mulook A. Mashhoor
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    Thelma Beatriz González-Castro, Yudy Merady Escobar-Chan, Ana Fresan, María Lilia López-Narváez, Carlos Alfonso Tovilla-Zárate, Isela Esther Juárez-Rojop, Jorge L Ble-Castillo, Alma Delia Genis-Mendoza, Pedro Iván Arias-Vázquez
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Evidence Gap on the Prevalence of Non-conventional Risk Factors for Type 2 Diabetes in Iran
Abdolreza Shaghaghi, Ali Ahmadi
Osong Public Health Res Perspect. 2014;5(5):292-297.   Published online October 31, 2014
DOI: https://doi.org/10.1016/j.phrp.2014.08.002
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AbstractAbstract PDF
Objectives
Robust scientific evidence exists about the role of non-conventional risk factors in type 2 diabetes worldwide. The current epidemiological pattern of the disease in Iran suggests a precipitating role for these non-conventional risk factors. This review was performed to examine the research evidence suggesting a higher prevalence of non-conventional type 2 diabetes risk factors in Iran.
Methods
MeSH keywords were applied to search several databases, including PUBMED, MEDLINE, AMED, EMBASE, Iran DOC, and the Scientific Information Database without a time limit from inception to September 2011. The quality of the non-interventional and population-based studies on Iranians included in these databases was assessed by the authors and any disagreement was resolved with consensus.
Results
The literature search yielded 1847 publications, of which 62 were included in this study after eliminating non-relevant and overlapping papers. No study was found that verified a higher prevalence of the non-conventional type 2 diabetes risk factors in the Iranian population.
Conclusion
The identified evidence gap about the role of prominent non-conventional risk factors of type 2 diabetes in the Iranian population could be a major caveat in the application of an evidence-based approach to endorse or reject existing hypothesis about these risk factors. Studies on the prevalence of non-conventional biomarkers of type 2 diabetes among Iranians could be a promising area of research.

Citations

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  • Application of Pender’s health promotion model for type 2 diabetes treatment adherence: protocol for a mixed methods study in southern Iran
    Nahid Shahabi, Zahra Hosseini, Teamur Aghamolaei, Amin Ghanbarnejad, Ahmad Behzad
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    Sanam Hariri, Zahra Rahimi, Nahid Hashemi-Madani, Seyyed Ali Mard, Farnaz Hashemi, Zahra Mohammadi, Leila Danehchin, Farhad Abolnezhadian, Aliasghar Valipour, Yousef Paridar, Mohammad Mahdi Mir-Nasseri, Alireza Khajavi, Sahar Masoudi, Saba Alvand, Bahman
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Knowledge of Diabetes Mellitus: Does Gender Make a Difference?
Patrício Fernando Lemes dos Santos, Poliana Rodrigues dos Santos, Graziele Souza Lira Ferrari, Gisele Almeida Amaral Fonseca, Carlos Kusano Bucalen Ferrari
Osong Public Health Res Perspect. 2014;5(4):199-203.   Published online August 31, 2014
DOI: https://doi.org/10.1016/j.phrp.2014.06.004
  • 3,799 View
  • 28 Download
  • 20 Crossref
AbstractAbstract PDF
Objective Diabetes mellitus (DM) is a chronic disease considered an important public health problem. In recent years, its prevalence has been exponentially rising in many developing countries. Chronic complications of DM are important causes of morbidity and mortality among patients, which impair their health and quality of life. Knowledge on disease prevention, etiology, and management is essential to deal with parents, patients, and caregivers. The aim of this study was to evaluate the knowledge regarding DM in an adult population from a Middle-western Brazilian city.
Methods
This was a cross-sectional study covering 178 adults, aged 18–64 years, who answered a diabetes knowledge questionnaire. In order to identify the difference between groups, analysis of variance was used.
Results
Higher knowledge scores were found regarding the role of sugars on DM causality, diabetic foot care, and the effects of DM on patients (blindness, impaired wound healing, and male sexual dysfunction). However, lower scores were found amongst types of DM, hyperglycemic symptoms, and normal blood glucose levels. Females tended to achieve better knowledge scores than males.
Conclusion
Women had better knowledge regarding types of DM, normal blood glucose values, and consequences of hyperglycemia revealed that diabetes education should be improved.

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Prevalence of Dyslipidemia and Hypertension in Indian Type 2 Diabetic Patients with Metabolic Syndrome and its Clinical Significance
Dhananjay Yadav, Meerambika Mishra, Arvind Tiwari, Prakash Singh Bisen, Hari Mohan Goswamy, G.B.K.S. Prasad
Osong Public Health Res Perspect. 2014;5(3):169-175.   Published online June 30, 2014
DOI: https://doi.org/10.1016/j.phrp.2014.04.009
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AbstractAbstract PDF
Objectives
The present study was designed to estimate the prevalence of dyslipidemia and hypertension based on the National Cholesterol Educational Programme Adult Treatment Panel III definition of metabolic syndrome (MetS). The study also focuses on prevalence for MetS with respect to the duration of disease in Gwalior–Chambal region of Madhya Pradesh, India.
Methods
Type 2 diabetic patients (n = 700) were selected from a cross-sectional study that is regularly being conducted in the School of Studies in Biochemistry, Jiwaji University Gwalior, India. The period of our study was from January 2007 to October 2009. Dyslipidemia and hypertension were determined in type 2 diabetic patients with MetS as per National Cholesterol Educational Programme Adult Treatment Panel III criteria.
Results
The mean age of the study population was 54 ± 9.3 years with 504 (72%) males and 196 (28%) females. The prevalence of MetS increased with increased duration of diabetes in females; however, almost constant prevalence was seen in the males. Notable increase in the dyslipidemia (64.1%) and hypertension (49%) in type 2 diabetic patients were seen. The steep increase in dyslipidemia and hypertension could be the reason for the growing prevalence of diabetes worldwide. The study also noted a close association between age and occurrence of MetS.
Conclusion
Individual variable of MetS appears to be highly rampant in diabetic population. Despite treatment, almost half of patients still met the criteria for MetS. Effective treatment of MetS components is required to reduce cardiovascular risk in diabetes mellitus hence accurate and early diagnosis to induce effective treatment of MetS in Indian population will be pivotal in the prevention of cardiovascular disease and type 2 diabetes.

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Development of a Predictive Model for Type 2 Diabetes Mellitus Using Genetic and Clinical Data
Juyoung Lee, Bhumsuk Keam, Eun Jung Jang, Mi Sun Park, Ji Young Lee, Dan Bi Kim, Chang-Hoon Lee, Tak Kim, Bermseok Oh, Heon Jin Park, Kyu-Bum Kwack, Chaeshin Chu, Hyung-Lae Kim
Osong Public Health Res Perspect. 2011;2(2):75-82.   Published online June 30, 2011
DOI: https://doi.org/10.1016/j.phrp.2011.07.005
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AbstractAbstract PDFSupplementary Material
Objectives
Recent genetic association studies have provided convincing evidence that several novel loci and single nucleotide polymorphisms (SNPs) are associated with the risk of developing type 2 diabetes mellitus (T2DM). The aims of this study were: 1) to develop a predictive model of T2DM using genetic and clinical data; and 2) to compare misclassification rates of different models.
Methods
We selected 212 individuals with newly diagnosed T2DM and 472 controls aged in their 60s from the Korean Genome and Epidemiology Study. A total of 499 known SNPs from 87 T2DM-related genes were genotyped using germline DNA. SNPs were analyzed for significant association with T2DM using various classification algorithms including Quest (Quick, Unbiased, Efficient, Statistical tree), Support Vector Machine, C4.5, logistic regression, and K-nearest neighbor.
Results
We tested these models using the complete Korean Genome and Epidemiology Study cohort (n = 10,038) and computed the T2DM misclassification rates for each model. Average misclassification rates ranged at 28.2–52.7%. The misclassification rates for the logistic and machine-learning algorithms were lower than the statistical tree algorithms. Using 1-to-1 matched data, the misclassification rate of the statistical tree QUEST algorithm using body mass index and SNP variables was the lowest, but overall the logistic regression performed best.
Conclusions
The K-nearest neighbor method exhibited more robust results than other algorithms. For clinical and genetic data, our “multistage adjustment” model outperformed other models in yielding lower rates of misclassification. To improve the performance of these models, further studies using warranted, strategies to estimate better classifiers for the quantification of SNPs need to be developed.

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