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PHRP : Osong Public Health and Research Perspectives

OPEN ACCESS. pISSN: 2210-9099. eISSN: 2233-6052

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"diabetes mellitus type 2"

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"diabetes mellitus type 2"

Original Articles
Risk of tuberculosis in individuals with type 2 diabetes mellitus based on the tuberculosis predictive index score: a case-control study in Indonesia
Dea P. Audina, Rachel S. Aritonang, Muhammad I. Mokoagow
Osong Public Health Res Perspect 2025;16(4):406-414.
Published online June 11, 2025
DOI: https://doi.org/10.24171/j.phrp.2024.0310
Risk of tuberculosis in individuals with type 2 diabetes mellitus based on the tuberculosis predictive index score: a case-control study in Indonesia
Objectives
The co-occurrence of tuberculosis (TB) and diabetes mellitus presents a significant global health challenge, marked by a bidirectional relationship. This study aims to evaluate the effectiveness of the tuberculosis predictive index (TPI) score, developed by Isfandiari et al., in predicting TB occurrence among individuals living with type 2 diabetes mellitus. Methods: A case-control study was conducted using primary data collected through questionnaires administered to individuals with type 2 diabetes mellitus, with and without pulmonary TB, at the internal medicine outpatient clinic of Fatmawati General Hospital from June to August 2024. The study compared TPI scores between those with type 2 diabetes mellitus who had TB and those who did not. Results: TPI scores were significantly associated with TB risk. Individuals with both type 2 diabetes mellitus and TB had a 6.8-fold higher risk (95% confidence interval [CI], 2.6–17.6; p<0.001) than those without TB. Further chi-square analysis identified three significant risk factors: individuals with type 2 diabetes mellitus exhibiting TB-like symptoms had a 13.3-fold increased TB risk (95% CI, 5.1–34.3; p<0.001); those with a body mass index below 18.5 kg/m² had a 3.3-fold higher risk (95% CI, 1.0–11.0; p=0.039); and those living in poorly ventilated homes (ventilation ≤10%) had a 3.2-fold higher risk (95% CI, 1.0–9.8; p=0.035). Conclusion: This study demonstrates that individuals with type 2 diabetes mellitus who developed TB had significantly higher TPI scores, corresponding to a 6.8-fold increased risk compared to their counterparts without TB. The TPI score may serve as a valuable tool for predicting TB risk among populations living with type 2 diabetes mellitus.

Citations

Citations to this article as recorded by  Crossref logo
  • Artificial intelligence and biohealth: the Republic of Korea’s emerging priorities in health care R&D
    Jong-Koo Lee
    Osong Public Health and Research Perspectives.2025; 16(4): 309.     CrossRef
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  • 133 Download
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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
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 (<i>n</i> = 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.

Citations

Citations to this article as recorded by  Crossref logo
  • Prescription Patterns and Drug Utilization in Contemporary ST-segment Elevation Myocardial Infarction Management: A Multicenter Prospective Observational Study from South India
    P B Jayagopal, A Jabir, A Gopi, P R Vaidyanathan, K S Ravindranath, B S Arun, B C Srinivas, M K Nayak
    Journal of Indian College of Cardiology.2026; 16(2): 62.     CrossRef
  • Mapping multimorbidity from diabetes mellitus and its association with depressive symptoms among older people of India: a cross-sectional study from a nationally representative survey
    Gayatri Khanal, Y. Selvamani, J. Kezia Angeline
    International Journal of Diabetes in Developing Co.2025; 45(1): 111.     CrossRef
  • Effect of Akkermansia muciniphila on GLP-1 and Insulin Secretion
    Ananta Prasad Arukha, Subhendu Nayak, Durga Madhab Swain
    Nutrients.2025; 17(15): 2516.     CrossRef
  • Complete blood count inflammation derived indexes as predictors of metabolic syndrome in type 2 diabetes mellitus
    Almir Fajkić, Rijad Jahić, Edin Begić, Amela Dervišević, Avdo Kurtović, Orhan Lepara
    Technology and Health Care.2024; 32(4): 2321.     CrossRef
  • Metabolic Syndrome Frequency in Type 2 Diabetics Using International Diabetes Federation (IDF) Criteria Analysis
    Sheena Kumari, Disha K Kataria, Sona Kumari, Riya Rani, Neha Ahuja, FNU Partab, Sooraj Raja, Hafsa Asif, FNU Sanam, Mohsin Ali
    Cureus.2024;[Epub]     CrossRef
  • Prevalence of metabolic syndrome and its risk factors among newly diagnosed type 2 diabetes mellitus patients – A hospital-based cross-sectional study
    S Teja Rama Krishna, Yogesh Bahurupi, Ravi Kant, Pradeep Aggarwal, Athulya V. Ajith
    Journal of Family Medicine and Primary Care.2024; 13(8): 3325.     CrossRef
  • Metabolic and genetic risk factors associated with pre-diabetes and type 2 diabetes in Thai healthcare employees: A long-term study from the Siriraj Health (SIH) cohort study
    Pichanun Mongkolsucharitkul, Apinya Surawit, Thamonwan Manosan, Suphawan Ophakas, Sophida Suta, Bonggochpass Pinsawas, Tanyaporn Pongkunakorn, Sureeporn Pumeiam, Winai Ratanasuwan, Mayuree Homsanit, Keerati Charoencholvanich, Yuthana Udomphorn, Bhoom Sukt
    PLOS ONE.2024; 19(6): e0303085.     CrossRef
  • Real-World Effectiveness of Oral Semaglutide in Indian Adult Diabetic Patients: Evaluation of EMR-based Data
    Sandeep Gudibanda, Sharayu Govardhane, Supriya Kaloo, Snehal Shah, Vaibhav Miglani, Garima Verma
    Journal of Diabetology.2024; 15(4): 421.     CrossRef
  • Utilization of Hypolipidemic Drugs, Patterns, and Factors Affecting Dyslipidemia Among Type 2 Diabetes Mellitus at a Tertiary Care Teaching Hospital in South India
    Sandeep Khot, Ananya Chakraborty, Savitha Vijaykumar
    Cureus.2023;[Epub]     CrossRef
  • Real-World Observational Study on Vildagliptin With Insulin (VIL-INS) or Vildagliptin and Metformin With Insulin (VIL-MET-INS) Therapy in Indian Patients With Type 2 Diabetes Mellitus
    P Panneerselvam, Dibakar Biswas, Hema Singh, K Dilip Kumar, P Ravi Kumar, Pramila Kalra, Santosh Revankar, Sona Warrier
    Cureus.2023;[Epub]     CrossRef
  • Magnitude and Determinants of Diabetic Retinopathy Among Indian Diabetic Patients Undergoing Telescreening in India
    Rajiv Khandekar, Tamilarasan Senthil, Malathi Nainappan, Deepak P. Edward
    Telemedicine and e-Health.2022; 28(2): 176.     CrossRef
  • An experimental study of rosuvastatin’s analgesic effect and its interaction with etoricoxib, tramadol, amlodipine, and amitriptytline in albino mice
    Prafull Mohan, Ashok Kumar Sharma, Sharmila Sinha, R. Sabarad
    Medical Journal Armed Forces India.2022; 78: S61.     CrossRef
  • Receptor for Advanced Glycation End Product, Organ Crosstalk, and Pathomechanism Targets for Comprehensive Molecular Therapeutics in Diabetic Ischemic Stroke
    Nivedita L. Rao, Greeshma B. Kotian, Jeevan K. Shetty, Bhaskara P. Shelley, Mackwin Kenwood Dmello, Eric C. Lobo, Suchetha Padar Shankar, Shellette D. Almeida, Saiqa R. Shah
    Biomolecules.2022; 12(11): 1712.     CrossRef
  • Metabolic and Energy Imbalance in Dysglycemia-Based Chronic Disease
    Sanjay Kalra, Ambika Gopalakrishnan Unnikrishnan, Manash P Baruah, Rakesh Sahay, Ganapathi Bantwal
    Diabetes, Metabolic Syndrome and Obesity: Targets .2021; Volume 14: 165.     CrossRef
  • Association between diet quality scores, adiposity, glycemic status and nutritional biomarkers among Indian population with type 2 diabetes mellitus: A cross-sectional study
    Aamir Bashir, Krishna Pandey, Md Azharuddin, Anjali Kumari, Ishfaq Rashid, N.A. Siddiqui, Chandra Shekhar Lal, Krishna Murti
    Clinical Epidemiology and Global Health.2020; 8(1): 53.     CrossRef
  • The Impact of BMI Categories on Metabolic Abnormality Development in Chinese Adults Who are Metabolically Healthy: A 7-Year Prospective Study


    Xiangtong Liu, Jingbo Zhang, Jingwei Wu, Xiaolin Xu, Lixin Tao, Yue Sun, Shuo Chen, Yumei Han, Yanxia Luo, Xinghua Yang, Xiuhua Guo
    Diabetes, Metabolic Syndrome and Obesity: Targets .2020; Volume 13: 819.     CrossRef
  • Metabolic syndrome in north Indian type 2 diabetes mellitus patients: A comparison of four different diagnostic criteria of metabolic syndrome
    Deepak Gahlan, Rajesh Rajput, Vandana Singh
    Diabetes & Metabolic Syndrome: Clinical Research &.2019; 13(1): 356.     CrossRef
  • Prevalence of Type 2 Diabetes and Prediabetes in the Gwalior-Chambal Region of Central India
    Senthil Kumar Subramani, Dhananjay Yadav, Meerambika Mishra, Umamaheswari Pakkirisamy, Prakesh Mathiyalagen, GBKS Prasad
    International Journal of Environmental Research an.2019; 16(23): 4708.     CrossRef
  • A PROSPECTIVE STUDY OF DYSLIPIDAEMIA AND OBESITY IN HYPERTENSION PATIENTS
    Ponnana Raja Kumar, Siripurapu Sasikala
    Journal of Evidence Based Medicine and Healthcare.2018; 5(1): 43.     CrossRef
  • Prevalence and pattern of co morbidity among type2 diabetics attending urban primary healthcare centers at Bhubaneswar (India)
    Sandipana Pati, F. G. Schellevis, Alessandra Marengoni
    PLOS ONE.2017; 12(8): e0181661.     CrossRef
  • Dyslipidemia Prevalence in Iranian Adult Men: The Impact of Population-Based Screening on the Detection of Undiagnosed Patients
    Abolfazl Mohammadbeigi, Esamil Moshiri, Narges Mohammadsalehi, Hossein Ansari, Ali Ahmadi
    The World Journal of Men's Health.2015; 33(3): 167.     CrossRef
  • Association of high-density lipoprotein with development of metabolic syndrome components: a five-year follow-up in adults
    Xiangtong Liu, Lixin Tao, Kai Cao, Zhaoping Wang, Dongning Chen, Jin Guo, Huiping Zhu, Xinghua Yang, Youxin Wang, Jingjing Wang, Chao Wang, Long Liu, Xiuhua Guo
    BMC Public Health.2015;[Epub]     CrossRef
  • 6,860 View
  • 44 Download
  • Crossref
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