Topic modeling and social network analysis approach to explore diabetes discourse on Twitter in India

IntroductionThe utilization of social media presents a promising avenue for the prevention and management of diabetes. To effectively cater to the diabetes-related knowledge, support, and intervention needs of the community, it is imperative to attain a deeper understanding of the extent and content of discussions pertaining to this health issue. This study aims to assess and compare various topic modeling techniques to determine the most effective model for identifying the core themes in diabetes-related tweets, the sources responsible for disseminating this information, the reach of these themes, and the influential individuals within the Twitter community in India.MethodsTwitter messages from India, dated between 7 November 2022 and 28 February 2023, were collected using the Twitter API. The unsupervised machine learning topic models, namely, Latent Dirichlet Allocation (LDA), non-negative matrix factorization (NMF), BERTopic, and Top2Vec, were compared, and the best-performing model was used to identify common diabetes-related topics. Influential users were identified through social network analysis.ResultsThe NMF model outperformed the LDA model, whereas BERTopic performed better than Top2Vec. Diabetes-related conversations revolved around eight topics, namely, promotion, management, drug and personal story, consequences, risk factors and research, raising awareness and providing support, diet, and opinion and lifestyle changes. The influential nodes identified were mainly health professionals and healthcare organizations.DiscussionThe study identified important topics of discussion along with health professionals and healthcare organizations involved in sharing diabetes-related information with the public. Collaborations among influential healthcare organizations, health professionals, and the government can foster awareness and prevent noncommunicable diseases

Albuminuria and Diabetic Retinopathy in Type 2 Diabetes Mellitus Sankara Nethralaya Diabetic Retinopathy Epidemiology And Molecular Genetic Study (SN-DREAMS, report 12)

<p>Abstract</p> <p>Background</p> <p>The concordance of microalbuminuria and diabetic retinopathy (DR) has been well reported in persons with type 1 diabetes; however, for type 2 diabetes, there is paucity of data especially from population-based studies. The aim of this study was to estimate the prevalence of albuminuria (micro - and macroalbuminuria) among persons with type 2 diabetes and determine its role as a risk factor for presence and severity of DR.</p> <p>Methods</p> <p>A population-based cross sectional study was conducted in cohort of 1414 subjects with type 2 diabetes from Chennai metropolis. All the subjects underwent comprehensive eye examination including 45 degrees four-field stereoscopic digital photography. DR was clinically graded using Early Treatment Diabetic Retinopathy Study scales. A morning urine sample was tested for albuminuria. Subjects were considered to have microalbuminuria, if the urinary albumin excretion was between 30 and 300 mg/24 hours, and macroalbuminuria at more than 300 mg/24 hours. The statistical software used was SPSS for Windows, Chicago, IL. Student t-test for comparing continuous variables, and <it>χ</it>²test, to compare proportions amongst groups were used.</p> <p>Results</p> <p>The prevalence of microalbuminuria in the study subjects was 15.9% (226/1414), and that of macroalbuminuria, 2.7% (38/1414). Individuals with macroalbuminuria in comparison to micro- or normoalbuminuria showed a greater prevalence of DR (60.5% vs. 31.0% vs. 14.1%, p < 0.001), and also a greater severity of the disease (60.9% vs. 21.4 vs. 9.9, p < 0.001).</p> <p>Conclusions</p> <p>Every 6^thindividual in the population of type 2 diabetes is likely to have albuminuria. Subjects with microalbuminuria were around 2 times as likely to have DR as those without microalbuminuria, and this risk became almost 6 times in the presence of macroalbuminuria.</p

Prevalence of Metabolic Syndrome and its influence on microvascular complications in the Indian population with Type 2 Diabetes Mellitus. Sankara Nethralaya Diabetic Retinopathy Epidemiology And Molecular Genetic Study (SN-DREAMS, report 14)

<p>Abstract</p> <p>Background</p> <p>The Metabolic syndrome (MS) consists of central obesity, glucose intolerance, hyperinsulinemia, low high density lipoproteins, high triglycerides and hypertension. Different studies have observed that MS causes microvascular complications in patients with type 2 diabetes. The aim of the study was to find out the prevalence of MS in the Indian population with type 2 diabetes mellitus in relation to gender, duration of diabetes, and to evaluate the influence of MS and its individual components on microvascular complications such as diabetic retinopathy, diabetic nephropathy and diabetic neuropathy.</p> <p>Methods</p> <p>A population-based cross sectional survey was conducted with 1414 patients having type 2 diabetes mellitus. The International Diabetes Federation (IDF) criteria were used to identify the metabolic syndrome. Diabetic retinopathy was graded using the stereoscopic digital fundus photography. Neuropathy was assessed by measuring the vibration perception threshold through a sensitometer. Nephropathy was diagnosed by the presence of microalbuminuria in the first morning urine sample.</p> <p>Results</p> <p>The age and gender adjusted prevalence of MS, using the IDF criteria, in the South Indian population was 73.3%. The prevalence was higher in women (83.3%), compared to men (65.3%). In subjects with diabetes mellitus, without and with MS, the prevalence of retinopathy was 21.3% and 16.9% (p = 0.057); prevalence of nephropathy was 20.5% and 18.0% (p = 0.296), and prevalence of neuropathy was17.2% and 19.4% (p = 0.353) respectively. Overall and in women, the clustering of MS components led to an increase in the prevalence of diabetic nephropathy. The prevalence of retinopathy and neuropathy in MS subjects, who had diabetes for < 10 years, was more in both men and women; it was more in women but not in men when the duration of diabetes varied from 11-20 years.</p> <p>Conclusions</p> <p>The association of MS with microangiopathies decreased with an increase in the duration of diabetes. MS behaved differently in men and women. It may need to be managed differently in the two groups.</p

Diagonal ear lobe crease in diabetic south Indian population: Is it associated with Diabetic Retinopathy?. Sankara Nethralaya Diabetic Retinopathy Epidemiology And Molecular-genetics Study (SN-DREAMS, Report no. 3)

<p>Abstract</p> <p>Background</p> <p>To report the prevalence of ear lobe crease (ELC), a sign of coronary heart disease, in subjects (more than 40 years old) with diabetes and find its association with diabetic retinopathy.</p> <p>Methods</p> <p>Subjects were recruited from the Sankara Nethralaya Diabetic Retinopathy Epidemiology And Molecular-genetics Study (SN-DREAMS), a cross-sectional study between 2003 and 2006; the data were analyzed for the1414 eligible subjects with diabetes. All patients' fundi were photographed using 45° four-field stereoscopic digital photography. The diagnosis of diabetic retinopathy was based on the modified Klein classification. The presence of ELC was evaluated on physical examination.</p> <p>Results</p> <p>The prevalence of ELC, among the subjects with diabetes, was 59.7%. The ELC group were older, had longer duration of diabetes, had poor glycemic control and had a high socio-economic status compared to the group without ELC and the variables were statistically significant. There was no statistical difference in the prevalence of diabetic retinopathy in two groups. On multivariate analysis for any diabetic retinopathy, the adjusted OR for women was 0.69 (95% CI 0.51-0.93) (p = 0.014); for age >70 years, 0.49 (95% CI 0.26-0.89) (p = 0.024); for increasing duration of diabetes (per year increase), 1.11(95% CI 1.09-1.14) (p < 0.0001); and for poor glycemic control (per unit increase in glycosylated heamoglobin), 1.26 (95% CI 1.19-1.35) (p < 0.0001). For sight-threatening diabetic retinopathy, no variable was significant on multivariable analysis. In predicting any diabetic retinopathy, the presence of ELC had sensitivity of 60.4%, and specificity, 40.5%. The area under the ROC curve was 0.50 (95% CI 0.46-0.54) (p 0.02).</p> <p>Conclusion</p> <p>The ELC was observed in nearly 60% of the urban south Indian population. However, the present study does not support the use of ELC as a screening tool for both any diabetic retinopathy and sight-threatening retinopathy.</p

Data_Sheet_1_Topic modeling and social network analysis approach to explore diabetes discourse on Twitter in India.docx

IntroductionThe utilization of social media presents a promising avenue for the prevention and management of diabetes. To effectively cater to the diabetes-related knowledge, support, and intervention needs of the community, it is imperative to attain a deeper understanding of the extent and content of discussions pertaining to this health issue. This study aims to assess and compare various topic modeling techniques to determine the most effective model for identifying the core themes in diabetes-related tweets, the sources responsible for disseminating this information, the reach of these themes, and the influential individuals within the Twitter community in India.MethodsTwitter messages from India, dated between 7 November 2022 and 28 February 2023, were collected using the Twitter API. The unsupervised machine learning topic models, namely, Latent Dirichlet Allocation (LDA), non-negative matrix factorization (NMF), BERTopic, and Top2Vec, were compared, and the best-performing model was used to identify common diabetes-related topics. Influential users were identified through social network analysis.ResultsThe NMF model outperformed the LDA model, whereas BERTopic performed better than Top2Vec. Diabetes-related conversations revolved around eight topics, namely, promotion, management, drug and personal story, consequences, risk factors and research, raising awareness and providing support, diet, and opinion and lifestyle changes. The influential nodes identified were mainly health professionals and healthcare organizations.DiscussionThe study identified important topics of discussion along with health professionals and healthcare organizations involved in sharing diabetes-related information with the public. Collaborations among influential healthcare organizations, health professionals, and the government can foster awareness and prevent noncommunicable diseases.</p

Utility values associated with diabetic retinopathy in Chennai, India.

PURPOSE: The aim of this study was to estimate utility values associated with different severity stages of diabetic retinopathy (DR) in India by a direct elicitation method (time-trade off, TTO) and indirectly by questionnaire. METHODS: People with diabetes aged 40 years and over were recruited from an on-going DR epidemiology study and a laser clinic in Chennai, India. Utility values were elicited using the direct TTO method and indirectly through a validated questionnaire (EQ-5D). RESULTS: Of 249 participants, 30 had no DR, 73 had non-proliferative DR, 114 had sight-threatening DR, and 32 were blind from DR (bilateral visual acuity <6/60). The mean TTO utility value was 0.73 (standard deviation, SD, 0.31). TTO utility values decreased with increasing severity of DR (p < 0.001) and were significantly lower among participants with sight threatening DR (0.70, SD 0.33) and blindness (0.55, SD 0.24) compared to those with no DR (0.89, SD 0.25) after adjustment for sociodemographic and clinical factors. Blindness from DR was independently associated with a lower EQ-5D utility value. The utility value derived from EQ-5D (0.06) associated with being blind from DR was substantially lower than that of the TTO utility value (0.55). CONCLUSIONS: This study provides estimates of utility values that can be used in economic evaluations of DR screening strategies in India. The relatively low utility values associated with blindness highlights the importance of screening programs for early detection of the sight-threatening stages to prevent vision loss from DR in this setting

Awareness, behavior, and determinants of dietary salt intake in adults: results from the National NCD Monitoring Survey, India

Abstract A diet high in sodium contributes to a significant proportion of Disability Adjusted Life Years (DALYs) due to cardiovascular diseases. This paper describes the awareness, behaviour and determinants related to dietary salt intake in an adult population of 18–69 years that were assessed as part of the National NCD Monitoring Survey (NNMS) in India. A sub-sample of 3000 adults selected through simple random sampling from 150 nationally representative Primary Sampling Units (PSUs) was included. Data regarding awareness and behaviour related to dietary salt intake were collected. Urinary sodium excretion in spot urine samples was estimated and used to calculate dietary salt intake. The dietary salt intake’s sociodemographic, behavioural and metabolic determinants were also analysed. Less than one-third of the adults of both genders in all age groups in rural and urban areas were aware that daily high salt intake could affect health. The estimated mean daily salt intake was 8.0 g (8.9 g/day for men and 7.1 g/day for women). The salt intake was significantly higher in men [Adjusted OR = 17.66 (5.24–59.46)], rural areas [Adjusted OR = 6.14 (1.83–20.60)], overweight and obese respondents [Adjusted OR = 17.62 (3.17–98.07)]. The perception of the harmful effects of high salt intake and practices to limit salt intake was low in the study population. The mean daily salt intake was higher than the WHO recommendation of up to 5 g daily. The mean dietary salt intake is high in the Indian population, which calls for planning and implementing control of dietary salt consumption measures

Color vision abnormalities in type II diabetes: Sankara Nethralaya Diabetic Retinopathy Epidemiology and Molecular Genetics Study II report no 2

Purpose: The purpose of this study is to assess color vision abnormalities in a cohort of subjects with type II diabetes and elucidate associated risk factors. Methods: Subjects were recruited from follow-up cohort of Sankara Nethralaya Diabetic Retinopathy Epidemiology and Molecular Genetics Study I. Six hundred and seventy-three eyes of 343 subjects were included from this population-based study. All subjects underwent detailed ophthalmic evaluation, including the Farnsworth-Munsell 100 hue test. Results: The prevalence of impaired color vision (ICV) was 43% (CI: 39.2–46.7). Risk factors for ICV were higher heart rate (odds ratio [OR]: 1.043, [1.023–1.064]) and a higher intraocular pressure (IOP) (OR: 1.086, [1.012–1.165]). Subjects with clinically significant macular edema (CSME) had three times higher chance of having ICV. C1, C2, and C3 are the commonly found Early Treatment Diabetic Retinopathy Study (ETDRS) patterns. The moment of inertia method showed that the angle did not reveal any specific pattern of color vision defect. Although the major and minor radii were high in those with ICV, we did not observe polarity. Confusion index was high in subjects with ICV, indicating a severe color vision defect. Conclusions: The prevalence of ICV was 43% among subjects with type II diabetes. The most commonly observed patterns were increasing severities of the blue–yellow defect on ETDRS patterns, but no specific pattern was observed at the moment of inertia analysis. The presence of CSME, a higher heart rate, and IOP was significant risk factors for ICV. This functional impairment in color vision could significantly contribute to morbidity among subjects with diabetes