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Zhaojun Li

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Review Open access Jul 2026

Prevalence and associated factors of insufficient vegetable and fruit intake among adults: a cross-sectional study

Insufficient intake of vegetables and fruits is a major modifiable risk factor for diet-related diseases worldwide. This study evaluated the intake patterns and associated factors among Hong Kong adults. A cross-sectional survey was conducted in 2024–2025. Data on demographic characteristics, socioeconomic status, lifestyle, and dietary habits were collected from adults aged 18 and above. The primary outcomes were insufficient vegetable intake and insufficient fruit intake, defined as not meeting the recommended daily intake for vegetables and fruits, respectively. Associations were examined using univariable and multivariable logistic regression analyses. Among 4,290 participants (mean age 41.64 years; 60.6% female), the prevalence of insufficient intake was 78.1% ( n = 3,350) for vegetables and 82.4% ( n = 3,534) for fruits. In multivariable analysis, male gender was positively associated with both insufficient vegetable intake (adjusted odds ratio [aOR] = 2.204, 95% confidence interval [CI]: 1.783–2.726, p < 0.001) and insufficient fruit intake (aOR = 1.665, 95% CI: 1.307–2.120, p < 0.001). Sufficient physical activity was negatively associated with insufficient vegetable intake (aOR = 0.624, 95% CI: 0.520–0.748, p < 0.001) and insufficient fruit intake (aOR = 0.556, 95% CI: 0.455–0.680, p < 0.001). Furthermore, older age (aOR = 0.991, 95% CI: 0.983–0.999, p = 0.033) was negatively associated with insufficient vegetable intake, although the effect size was small. For fruit intake specifically, tertiary education (aOR = 1.814, 95% CI: 1.107–2.973, p = 0.018) and smoking (aOR = 1.617, 95% CI: 1.239–2.111, p < 0.001) were associated with higher odds of insufficient fruit intake. Most adults in Hong Kong consumed vegetables and fruits below recommended levels. Insufficient intake was associated with gender, physical activity, education level, and smoking status. These findings highlight the need for targeted public health interventions, particularly for men and individuals with insufficient physical activity. Nutrition education should be integrated with broader health promotion strategies that encourage physical activity and support smoking cessation.

Jun-Jie Huang, Zhaojun Li, Ze-Huan Yang et al. · Scientific Reports · 0 citations

Open access Aug 2026

Development of a Prognostic Survival Risk Score for Lung Cancer Patients With Type 2 Diabetes Mellitus: A Territory‐Wide Retrospective Cohort Study

ABSTRACT Background Lung cancer is a leading cause of cancer‐related mortality, and its prognosis is often affected by comorbidities such as type 2 diabetes mellitus (T2DM). This study aimed to identify survival risk factors for lung cancer patients with T2DM, evaluate the predictive models, and develop a risk score system for survival prediction. Study Design and Methods We analyzed data from 5491 lung cancer patients with T2DM from the Hong Kong Hospital Authority Data Collaboration Laboratory (HADCL) (2000–2020). Prognostic factors were evaluated using Cox proportional hazards regression. Four algorithms were used to construct survival analysis models: Cox proportional hazards regression, LASSO Cox regression, survival tree, and random survival forests (RSF). An interpretable risk scoring system was subsequently derived using the selected predictors. Results Older age at cancer diagnosis, male sex, longer duration between T2DM diagnosis and lung cancer diagnosis (T2DM duration), smoking, alcohol consumption, history of stroke, and higher HbA1c were associated with increased mortality risk, whereas hypertension, coronary heart disease, insulin usage, anti‐lipid usage, and anti‐diabetic usage were associated with reduced mortality risk. Among the evaluated models, the RSF model demonstrated the best predictive performance, as indicated by the C‐index (0.71) and time‐dependent AUC (0.883). The developed risk score system included the following criteria: age at cancer diagnosis; T2DM duration; smoking status; HbA1c; HDL‐C; serum potassium (K) levels; LDL‐C. A score ≥ 75 classified 47.33% of patients as high‐risk, with a corresponding five‐year survival probability of 5.51%. Conclusions Among the evaluated models, the RSF model demonstrated the best predictive performance. The developed risk scoring system may support risk stratification and identification of high‐risk patient subgroups, potentially facilitating personalized prognostic assessment and clinical management.

Chen-Wen Zhong, Jun-Jie Huang, Zhaojun Li et al. · Cancer Medicine · 0 citations