Prevalence of Diabetes Mellitus and Its Associated Factors among Registered Female Sex Workers in Belagavi, Karnataka, India: A Cross-Sectional Study Using Capillary Blood Glucose Screening
DOI:
https://doi.org/10.55489/njcm.170720266659Keywords:
Diabetes Mellitus, Female Sex Workers, Prevalence, Blood Glucose, IndiaAbstract
Background: Diabetes mellitus (DM) is an emerging public health concern among marginalized populations such as female sex workers (FSWs), who often have limited access to non-communicable disease screening despite regular engagement with HIV programs. The objectives were to estimate diabetes prevalence and its associated factors among registered female sex workers in Belagavi.
Methods: A facility-linked cross-sectional study was conducted among 306 registered female sex workers selected by simple random sampling. Data were collected using structured interviews. Random capillary blood glucose (RCBG) levels were measured using a standardized glucometer. Diabetes was defined as self-reported diagnosed diabetes or RCBG ≥200 mg/dL. Associations were assessed using Chi-square/Fisher’s exact tests.
Results: Diabetes prevalence was 5.9% (n=18; 95% CI: 3.5%-9.2%), including 8 previously diagnosed and 10 newly detected cases. Prediabetes prevalence was 16.3% (n=50; 95% CI: 12.5%-20.8%). Significant associations were observed between glucose status and age, marital status, tobacco use, alcohol use, hypertension, and work-related mental stress (p<0.05).
Conclusion: Diabetes (5.9%) and prediabetes (16.3%) were prevalent among female sex workers and were significantly associated with age, marital status, tobacco use, alcohol use, hypertension, and work-related mental stress. These findings highlight the need to integrate routine diabetes screening and targeted lifestyle interventions into existing programs for FSWs.
References
World Health Organization. Classification of diabetes mellitus. Geneva: World Health Organization; 2019. Available from: https://www.who.int/publications/i/item/classification-of-diabetes-mellitus
International Diabetes Federation. IDF Diabetes Atlas 2025 [Internet]. Brussels: International Diabetes Federation; 2025 [cited 2026 Mar 8]. Available from: https://diabetesatlas.org/resources/idf-diabetes-atlas-202
Anjana RM, Deepa M, Pradeepa R, Mahanta J, Narain K, Das HK, et al. Prevalence of diabetes and prediabetes in 15 states of India: results from the ICMR-INDIAB population-based cross-sectional study. Lancet Diabetes Endocrinol. 2017 Aug;5(8):585-596. DOI: https://doi.org/10.1016/S2213-8587(17)30174-2 PMid:28601585 PMCid:PMC10852243
Rao C, Kamath V, Shetty A, Kamath A. A study on the prevalence of type 2 diabetes in coastal Karnataka. Int J Diabetes Dev Ctries. 2010 Apr;30(2):80-85. DOI: https://doi.org/10.4103/0973-3930.62597 PMid:20535311 PMCid:PMC2878695
Jahagirdar SS, Bant DD, Bathija GV. Study of prevalence of diabetes mellitus in the rural areas of Hubballi, Karnataka, India. Int J Community Med Public Health. 2016 Dec. 21;4(1):104-109. DOI: https://doi.org/10.18203/2394-6040.ijcmph20164720
National AIDS Control Organization. Programmatic mapping and population size estimation (p-MPSE) of high-risk groups: operational manual [Internet]. New Delhi: National AIDS Control Organization; 2020 [cited 2026 Jun 13]. Available from: https://www.aidsdatahub.org/sites/default/files/resource/india-programmatic-mapping-and-population-size-estimation-high-risk-groups-2020.pdf
Kumar P, Das C, Khushwaha BS, Bhavsar SP, Purohit SK, Kumar A, et al. Programmatic mapping and population size estimation of key population in India: method and findings. PLOS Glob Public Health. 2025 May 7;5(5):e0004475. DOI: https://doi.org/10.1371/journal.pgph.0004475 PMid:40333642 PMCid:PMC12057993
Swain SN, Saggurti N, Battala M, Verma RK, Jain AK. Experience of violence and adverse reproductive health outcomes, HIV risks among mobile female sex workers in India. BMC Public Health. 2011 May 20;11:357. DOI: https://doi.org/10.1186/1471-2458-11-357 PMid:21599984 PMCid:PMC3116498
Beattie TSH, Bhattacharjee P, Suresh M, Isac S, Ramesh BM, Moses S. Personal, interpersonal and structural challenges to accessing HIV testing, treatment and care services among female sex workers, men who have sex with men and transgenders in Karnataka state, South India. J Epidemiol Community Health. 2012 Oct;66(Suppl 2):ii42-8. DOI: https://doi.org/10.1136/jech-2011-200475 PMid:22495772
National AIDS Control Organization. India National Strategic Plan for HIV/AIDS and STI 2017-2024 [Internet]. New Delhi: Ministry of Health and Family Welfare, Government of India; 2016 [cited 2026 Jun 13]. Available from: https://hivpreventioncoalition.unaids.org/en/resources/india-national-strategic-plan-hivaids-and-sti-2017-2024
Chatterjee P, Dey R, Banerjee D, Vernekar M. Point prevalence study of communicable and non-communicable diseases and cervical cancer screening in female sex workers (FSW) in an urban area of Eastern India. SAS J Surg. 2021 Apr 21;7(4):201-206. DOI: https://doi.org/10.36347/sasjs.2021.v07i04.011
Vigneswari A, Manikandan R, Satyavani K, Archana S, Rajeswari R, Viswanathan V. Prevalence of Risk Factors of Diabetes Among Urban Poor South Indian Population. J Assoc Physicians India. 2015 Oct;63(10):32-34. PMID: 27608689.
Lwanga SK, Lemeshow S. Sample size determination in health studies: a practical manual [Internet]. Geneva: World Health Organization; 1991 [cited 2026 May 11]. Available from: https://iris.who.int/handle/10665/40062
Bansode B, Marbaniang SP, Prasad JB. Risk factors of diabetes and hypertension among women in Karnataka. Diabetes Metab Syndr. 2021 Jul-Aug;15(4):102139. DOI: https://doi.org/10.1016/j.dsx.2021.05.012 PMid:34186342
Mitra S, Bhanja S, Ghatak D, Roy S, De J. Risk assessment of noncommunicable diseases among commercial sex workers of a metropolitan city of India. Int Arch Health Sci. 2022;9:135-139. DOI: https://doi.org/10.4103/iahs.iahs_106_22
Jendrike N, Baumstark A, Kamecke U, Haug C, Freckmann G. ISO 15197:2013 evaluation of a blood glucose monitoring system's measurement accuracy. J Diabetes Sci Technol. 2017 Nov;11(6):1275-1276. DOI: https://doi.org/10.1177/1932296817727550 PMid:28849677 PMCid:PMC5951056
Tonyushkina K, Nichols JH. Glucose meters: a review of technical challenges to obtaining accurate results. J Diabetes Sci Technol. 2009 Jul 1;3(4):971-980. DOI: https://doi.org/10.1177/193229680900300446 PMid:20144348 PMCid:PMC2769957
Qiao Q, Keinänen-Kiukaanniemi S, Rajala U, Uusimäki A, Kivelä SL. Random capillary whole blood glucose test as a screening test for diabetes mellitus in a middle-aged population. Scand J Clin Lab Invest. 1995 Feb;55(1):3-8. DOI: https://doi.org/10.3109/00365519509075372 PMid:7624734
World Health Organization, Regional Office for the Western Pacific. The Asia-Pacific perspective: redefining obesity and its treatment. Sydney: Health Communications Australia; 2000. Available from: http://iris.wpro.who.int/handle/10665.1/5379
Rhee MK, Ho YL, Raghavan S, Vassy JL, Cho K, Gagnon D, et al. Random plasma glucose predicts the diagnosis of diabetes. PLoS One. 2019 Jul 19;14(7):e0219964. DOI: https://doi.org/10.1371/journal.pone.0219964 PMid:31323063 PMCid:PMC6641200
American Diabetes Association Professional Practice Committee. 2. Diagnosis and classification of diabetes: Standards of care in diabetes-2024. Diabetes Care. 2024 Jan 1;47(Suppl 1):S20-S42. DOI: https://doi.org/10.2337/dc24-S002 PMid:38078589 PMCid:PMC10725812
Unnikrishnan R, Pradeepa R, Joshi SR, Mohan V. Type 2 diabetes: demystifying the global epidemic. Diabetes. 2017 Jun;66(6):1432-1442. DOI: https://doi.org/10.2337/db16-0766 PMid:28533294
Maiti S, Akhtar S, Upadhyay AK, Mohanty SK. Socioeconomic inequality in awareness, treatment and control of diabetes among adults in India: Evidence from National Family Health Survey of India (NFHS), 2019-2021. Sci Rep. 2023 Feb 20;13(1):2971. DOI: https://doi.org/10.1038/s41598-023-29978-y PMid:36805018 PMCid:PMC9941485
Krupp K, Rao AP, Pope B, Ravi K, Khan A, Srinivas V, et al. Prevalence and correlates of metabolic syndrome among women living in urban slums, Mysore, India. PLOS Glob Public Health. 2023 Jul 7;3(7):e0000846. DOI: https://doi.org/10.1371/journal.pgph.0000846 PMid:37418350 PMCid:PMC10328303
Sharma K, Akre S, Chakole S, Wanjari MB. Stress-Induced Diabetes: A Review. Cureus. 2022 Sep 13;14(9):e29142. DOI: https://doi.org/10.7759/cureus.29142 PMID: 36258973 PMCID: PMC9561544
Unnikrishnan R, Anjana RM, Mohan V. Diabetes in South Asians: Is the phenotype different? Diabetes. 2014 Jan;63(1):53-55. DOI: https://doi.org/10.2337/db13-1592 PMid:24357697
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