The aim of this study was to develop the inpatient dietary behaviour score (IDBS) and validate its predictive performance in assessing the risk of hypoglycemia in patients with type 2 diabetes mellitus (T2DM).

The study included patients with T2DM admitted to the Endocrinology Department of the First Affiliated Hospital of Chongqing Medical University between 1 March 2021 and 1 March 2023. Patients were categorised into hypoglycemia and non-hypoglycemia groups using a paired approach, with hypoglycemia defined as any point-of-care glucose test results ≤ 3.9 mmol/L. Clinical data were collected, and the IDBS was calculated using a self-designed scale with 11 variables. Subsequently, measures for predicting hypoglycemia risk in hospitalised T2DM patients were formulated.

A total of 1478 patients were included in the survey, with 739 patients in each of the hypoglycemic and non-hypoglycemic groups after pairing. Baseline differences were observed in education, marital status, job status, DM duration, glycosylated haemoglobin A1c (HbA1c), body mass index (BMI), hypoglycemia history, diabetic peripheral artery disease (DM-PAD), diabetic foot (DF), diabetic kidney disease (DKD), and diabetic retinopathy (DR) between the hypoglycemic and non-hypoglycemic groups. Significant correlations were found between the updated and baseline changes in the IDBS. The predictive efficacy was highest in DKD patients (OR = 1.82, 95% CI: 1.69-1.97, P = 6.75E-53). In multivariate analyses, only BMI, DM duration, diabetic foot and marriage response were included in the regression model. The area under the curve (AUC) and mean squared error (MSE) of the IDBS were 0.77 and 0.00039, respectively. A linear relationship existed between the IDBS and OR values, indicating that the risk of hypoglycemia increased with higher scores.

IDBS demonstrated a robust predictive effect on hypoglycemia. The variable data were easily obtainable, and the evaluation and calculation methods were straightforward. This scoring system could serve as a valuable reference for hypoglycemia prevention and screening of hospitalised diabetic patients at high risk of hypoglycemia.

The role of smoking in the incidence of colorectal cancer (CRC) or gastric cancer (GC) in populations undergoing cholecystectomy has not been investigated.

To evaluate the effect of smoking on CRC or GC development in cholecystectomy patients.

A total of 174874 patients who underwent cholecystectomy between January 1, 2010 and December 31, 2017 were identified using the Korean National Health Insurance Service claims database. These patients were matched 1:1 with members of a healthy population according to age and sex. CRC or GC risk after cholecystectomy and the association between smoking and CRC or GC risk in cholecystectomy patients were evaluated using adjusted hazard ratios (HRs) and 95%CIs.

The risks of CRC (adjusted HR: 1.15; 95%CI: 1.06-1.25; P = 0.0013) and GC (adjusted HR: 1.11; 95%CI: 1.01-1.22; P = 0.0027) were significantly higher in cholecystectomy patients. In the population who underwent cholecystectomy, both CRC and GC risk were higher in those who had smoked compared to those who had never smoked. For both cancers, the risk tended to increase in the order of non-smokers, ex-smokers, and current smokers. In addition, a positive correlation was observed between the amount of smoking and the risks of both CRC and GC.

Careful follow-up and screening should be performed, focusing on the increased risk of gastrointestinal cancer in the cholecystectomy group, particularly considering the individual smoking habits.

Healthy lifestyles are considered important means to reduce the burden of diseases. This cross-sectional study was conducted based on the Ecological Model of Health Behavior (EMHB) to analyze the factors associated with the health-promoting lifestyles of Chinese residents.

We carried out a cross-sectional investigation in July 2023. Our investigated factors included social-demographic characteristics (including sex, age, education level, employment status, marital status, personal monthly income, and daily behavioral habits [which were measured by a questionnaire)], health literacy [which was measured by the Chinese version of the Health Literacy Scale Short-Form scale (HLS-SF12)], and family health [which was measured by the Chinese version of the Short-Form of the Family Health Scale (FHS-SF)]. Our outcome was health promoting lifestyle, which was measured by a revised version of Health Promoting Lifestyle Profile-II (HPLP-IIR). Data were analyzed using stepwise regression.

A total of 1,402 participants were enrolled. Higher scores of HLS-SF12 (β = 0.467), having regular exercise (β = 0.212), and regular physical examination (β = 0.088) were associated with better health-prompting lifestyles. However, older age (≥60 years) (β = -0.046), drinking (β = -0.066), and sleeping time (5-6 h/day) (β = -0.048) were associated lower levels of health-prompting lifestyles. Living with family (β = 0.077), FHS-SF (β = 0.104), and married (β = -0.077) were significant influencers. Unemployed (β = -0.048), receiving retirement pay (β = -0.053), and economic support provided by parents (β = 0.094) were associated with better health-prompting lifestyles. There were multiple influencing factors of the six dimensions of the HPLP-IIR. Our findings indicate that community residents with higher health literacy, better family health, and health-related behaviors tend to have better health-promoting lifestyles.

Our findings have confirmed the complex impacts of social-ecological factors on health-promoting lifestyles, which may help policy makers with health-promotion strategies making and also help researchers to control for confounding in study design.

We evaluated the prevalence and management of diabetes mellitus (DM) in elderly Korean patients based on data from the Korea National Health and Nutrition Examination Survey (KNHANES).

A total of 3,068 adults aged 65 years and older (19.8% of total population) were analyzed using KNHANES from 2019 to 2020. Prevalence, awareness, treatment, and control rates, and comorbidities were analyzed. Lifestyle behaviors and energy intake were also measured.

The prevalence of DM and prediabetes was 29.6% and 50.5%, respectively. The awareness, treatment and control rates were 76.4%, 73.3%, and 28.3%, respectively. The control rate was 77.0% if A1C <7.5% criteria was used. The mean A1C value of individuals with known DM was 7.1%, and 14.5% of the known DM patients had A1C ≥8.0%. Abdominal obesity, hypertension, and hypercholesterolemia were combined with DM in 63.9%, 71.7%, and 70.7%, respectively, and the rate of integrated management was 36.0% (A1C <7.5% criteria). A total of 40.1% of those with DM walked regularly. The percentage of energy intake from carbohydrates was higher in those with DM than in those without DM (P=0.044), while those of fat (P=0.003) and protein (P=0.025) were lower in those with DM than in those without DM in women.

In 2019 to 2020, three of 10 adults aged 65 years and older in Korea had DM, and approximately 70% of them had comorbidities. A strategy for more individualized comprehensive care for the elderly patients with DM is urgently needed.