Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 2 de 2
Filter
Add more filters










Database
Language
Publication year range
1.
BMC Prim Care ; 23(1): 241, 2022 09 17.
Article in English | MEDLINE | ID: mdl-36115943

ABSTRACT

BACKGROUND: Patients with diabetes who have poor health literacy about the disease may exhibit poor compliance and thus subsequently experience more complications. However, the conceptual gap of diabetes between health providers and the general population is still not well understood. Decoding concerns about diabetes on social media may help to close this gap. METHODS: Social media data were collected from the OpView social media platform. After checking the quality of the data, we analyzed the trends in people's discussions on the internet using text mining. The natural language process includes word segmentation, word counting and counting the relationships between the words. A word cloud was developed, and clustering analyses were performed. RESULTS: There were 19,565 posts about diabetes collected from forums, community websites, and Q&A websites in the summer (June, July, and August) of 2017. The three most popular aspects of diabetes were diet (33.2%), life adjustment (21.2%), and avoiding complications (15.6%). Most discussions about diabetes were negative. The negative/positive ratios of the top three aspects were avoiding complications (7.60), problem solving (4.08), and exercise (3.97). In terms of diet, the most popular topics were Chinese medicine and special diet therapy. In terms of life adjustment, financial issues, weight reduction, and a less painful glucometer were discussed the most. Furthermore, sexual dysfunction, neuropathy, nephropathy, and retinopathy were the most worrisome issues in avoiding complications. Using text mining, we found that people care most about sexual dysfunction. Health providers care about the benefits of exercise in diabetes care, but people are mostly concerned about sexual functioning. CONCLUSION: A conceptual gap between health providers and the network population existed in this real-world social media investigation. To spread healthy diabetic education concepts in the media, health providers might wish to provide more information related to the network population's actual areas of concern, such as sexual function, Chinese medicine, and weight reduction.


Subject(s)
Diabetes Mellitus , Sexual Dysfunction, Physiological , Social Media , Data Mining , Diabetes Mellitus/epidemiology , Humans , Weight Loss
2.
J Gen Intern Med ; 31(10): 1156-63, 2016 10.
Article in English | MEDLINE | ID: mdl-27255749

ABSTRACT

BACKGROUND: Although prior studies have examined BMI trajectories in Western populations, little is known regarding how BMI trajectories in Asian populations vary between adults with and without diabetes. OBJECTIVE: To examine how BMI trajectories vary between those developing and not developing diabetes over 18 years in an Asian cohort. DESIGN: Multilevel modeling was used to depict levels and rates of change in BMI for up to 18 years for participants with and without self-reported physician-diagnosed diabetes. PARTICIPANTS: We used 14,490 data points available from repeated measurements of 3776 participants aged 50+ at baseline without diabetes from a nationally representative survey of the Taiwan Longitudinal Study on Aging (TLSA1989-2007). MAIN MEASURES: We defined development of diabetes as participants who first reported diabetes diagnoses in 2007 but had no diabetes diagnoses at baseline. We defined the reference group as those participants who reported the absence of diabetes at baseline and during the entire follow-up period. KEY RESULTS: When adjusted for time-varying comorbidities and behavioral factors, higher level and constant increases in BMI were present more than 6.5 years before self-reported diabetes diagnosis. The higher BMI level associating with the development of diabetes was especially evident in females. Within 6.5 years prior to self-reported diagnosis, however, a wider range of decreases in BMI occurred (ßdiabetes = 1.294, P = 0.0064; ßdiabetes*time = 0.150, P = 0.0327; ßdiabetes*time (2) = -0.008, P = 0.0065). The faster rate of increases in BMI followed by a greater decline was especially prominent in males and individuals with BMI ≧24. CONCLUSIONS: An unintentional decrease in BMI in sharp contrast to the gradually rising BMI preceding that time may be an alarm for undiagnosed diabetes or a precursor to developing diabetes.


Subject(s)
Body Mass Index , Diabetes Mellitus, Type 2/diagnosis , Prediabetic State/diagnosis , Aged , Aged, 80 and over , Diabetes Mellitus, Type 2/epidemiology , Diabetes Mellitus, Type 2/physiopathology , Early Diagnosis , Female , Humans , Longitudinal Studies , Male , Middle Aged , Prediabetic State/epidemiology , Prediabetic State/physiopathology , Retrospective Studies , Risk Factors , Self Report , Sex Factors , Taiwan/epidemiology , Weight Loss/physiology
SELECTION OF CITATIONS
SEARCH DETAIL
...