Perceived symptoms in people living with impaired glucose tolerance

Risk factors for prediabetes in community-dwelling adults: A generalized estimating equation logistic regression approach with natural language processing insights

The global prevalence of prediabetes is expected to reach 8.3% (587 million people) by 2045, with 70% of people with prediabetes developing diabetes during their lifetimes. We aimed to classify community-dwelling adults with a high risk for prediabetes based on prediabetes-related symptoms and to identify their characteristics, which might be factors associated with prediabetes. We analyzed homecare nursing records (n = 26,840) of 1628 patients aged over 20 years. Using a natural language processing algorithm, we classified each nursing episode as either low-risk or high-risk for prediabetes based on the detected number and category of prediabetes-symptom words. To identify differences between the risk groups, we employed t-tests, chi-square tests, and data visualization. Risk factors for prediabetes were identified using multiple logistic regression models with generalized estimating equations. A total of 3270 episodes (12.18%) were classified as potentially high-risk for prediabetes. There were significant differences in the personal, social, and clinical factors between groups. Results revealed that female sex, age, cancer coverage as part of homecare insurance coverage, and family caregivers were significantly associated with an increased risk of prediabetes. Although prediabetes is not a life-threatening disease, uncontrolled blood glucose can cause unfavorable outcomes for other major diseases. Thus, medical professionals should consider the associated symptoms and risk factors of prediabetes. Moreover, the proposed algorithm may support the detection of individuals at a high risk for prediabetes. Implementing this approach could facilitate proactive monitoring and early intervention, leading to reduced healthcare expenses and better health outcomes for community-dwelling adults.

Developing a Classification Algorithm for Prediabetes Risk Detection From Home Care Nursing Notes: Using Natural Language Processing

This study developed and validated a rule-based classification algorithm for prediabetes risk detection using natural language processing from home care nursing notes. First, we developed prediabetes-related symptomatic terms in English and Korean. Second, we used natural language processing to preprocess the notes. Third, we created a rule-based classification algorithm with 31 484 notes, excluding 315 instances of missing data. The final algorithm was validated by measuring accuracy, precision, recall, and the F1 score against a gold standard testing set (400 notes). The developed terms comprised 11 categories and 1639 words in Korean and 1181 words in English. Using the rule-based classification algorithm, 42.2% of the notes comprised one or more prediabetic symptoms. The algorithm achieved high performance when applied to the gold standard testing set. We proposed a rule-based natural language processing algorithm to optimize the classification of the prediabetes risk group, depending on whether the home care nursing notes contain prediabetes-related symptomatic terms. Tokenization based on white space and the rule-based algorithm were brought into effect to detect the prediabetes symptomatic terms. Applying this algorithm to electronic health records systems will increase the possibility of preventing diabetes onset through early detection of risk groups and provision of tailored intervention.

Attitudes Regarding Participation in a Diabetes Screening Test among an Assyrian Immigrant Population in Sweden

Immigrants from the Middle East have higher prevalence and incidence of type 2 diabetes (T2D) compared with native Swedes. The aim of the study was to describe and understand health beliefs in relation to T2D as well as attitudes regarding participation in a screening process in a local group of Assyrian immigrants living in Sweden. A qualitative and quantitative method was chosen in which 43 individuals participated in a health check-up and 13 agreed to be interviewed. Interviews were conducted, anthropometric measurements and blood tests were collected, and an oral glucose tolerance test was performed. In total, 13 of the 43 participants were diagnosed with impaired glucose metabolism, 4 of these 13 had TD2. The interviewed participants perceived that screening was an opportunity to discover more about their health and to care for themselves and their families. Nevertheless, they were not necessarily committed to taking action as a consequence of the screening. Instead, they professed that their health was not solely in their own hands and that they felt safe that God would provide for them. Assyrians' background and religion affect their health beliefs and willingness to participate in screening for TD2.

The association between self-reported lack of sleep, low vitality and impaired glucose tolerance: a Swedish cross-sectional study

Background

The increased incidence of impaired glucose tolerance (IGT), are serious public health issues, and several studies link sleeping disorders with increased risk of developing type 2 diabetes, impaired glucose tolerance and insulin resistance (IR). This study explore how self-reported lack of sleep and low vitality, are associated with IGT in a representative Swedish population.

Methods

A cross-sectional survey conducted in two municipalities in South-western Sweden. Participants aged 30–75 were randomly selected from the population in strata by sex and age. Altogether, 2,816 participants were surveyed with a participation rates at 76%. Participants with normal glucose tolerance (n=2,314), and those with IGT (n=213) were retained for analyses. The participants answered a questionnaire before the oral glucose tolerance test (OGTT). Associations for questions concerning sleeping disorders, vitality and IGT were analysed using logistic regression and were expressed as odds ratios (OR) with 95% CI.

Results

In men a statistically significant age-adjusted association was found between self-reported lack of sleep and IGT: OR 2.4 (95% CI: 1.1-5.4). It did not weaken after further adjustment for body mass index (BMI), smoking, education, and leisure time physical activity 2.3 (1.0-5.5, p=0.044). No such associations were found in females. Corresponding age-adjusted associations between low vitality and IGT in both men 2.8 (1.3-5.8), and women 2.0 (1.2-3.4) were successively lost with increasing adjustment.

Conclusions

Insufficient sleep seems independently associated with IGT in men, while low vitality was not independently associated with IGT neither in men nor women, when multiple confounders are considered. IGT should be considered in patients presenting these symptoms, and underlying mechanisms further explored.

The association between self-rated health and impaired glucose tolerance in Swedish adults: a cross-sectional study

OBJECTIVE

To investigate gender differences in the association between self-rated health (SRH) and impaired glucose tolerance (IGT) in subjects unaware of their glucose tolerance.

DESIGN

A cross-sectional population-based study.

SETTING

The two municipalities of Vara and Skövde in south-western Sweden.

SUBJECTS

A total of 2502 participants (1301 women and 1201 men), aged 30-75, were randomly selected from the population.

MAIN OUTCOME MEASURES

IGT was regarded as the outcome measure and SRH as the main risk factor.

RESULTS

The prevalence of IGT was significantly higher in women (11.9%) than in men (10.1%), (p = 0.029), as was the prevalence of low SRH (women: 35.4%; men: 22.1%, p = 0.006). Both men and women with low SRH had a poorer risk factor profile than those with high SRH, and a statistically significant crude association between SRH and IGT was found in both men (OR = 2.8, 95% CI 1.8-4.4) and women (OR = 1.5, 95% CI 1.0-2.2, p = 0.033). However, after controlling for several lifestyle factors and biomedical variables, the association was attenuated and remained statistically significant solely in men (OR = 2.3, 95% CI 1.2-4.3).

CONCLUSION

The gender-specific associations found between SRH and IGT suggest that SRH may be a better indicator of IGT in men than in women. Future studies should evaluate the utility of SRH in comparison with objective health measures as a potential aid to health practitioners when deciding whether to screen for IGT and T2DM.