Prevalence and risk factors of depression and anxiety in primary care.

Introduction: Anxiety and depressive disorders are highly prevalent mental health conditions worldwide. However, little is known about their specific prevalence in primary care settings. This study aimed to determine the prevalence of depression and anxiety in the primary care population and identify associated patient characteristics. Method: We conducted a cross-sectional study using stratified sampling by age with a self-administered questionnaire survey in Singapore's National Health-care Group Polyclinics from December 2021 to April 2022. A total score of Patient Health Questionnaire-9 (PHQ-9) ≥10 represents clinical depression, and a total score of Generalised Anxiety Disorder-7 (GAD-7) ≥10 indicates clinical anxiety. Multivariable logistic regression was used to identify the factors associated with depression and anxiety. Results: A total of 5694 patients were approached and 3505 consented to the study (response rate=61.6%). There was a higher prevalence of coexisting clinical depression and anxiety (DA) (prevalence=5.4%) compared to clinical depression only (3.3%) and clinical anxiety only (1.9%). The odds of having DA were higher among those aged 21-39 years (odds ratio [OR] 13.49; 95% confidence interval [CI] 5.41-33.64) and 40-64 years (OR 2.28; 95% CI 1.03-5.03) compared to those ≥65 years. Women had higher odds of having DA (OR 2.33; 95% CI 1.54-3.50) compared to men. Respondents with diabetes had higher odds of having DA (OR 1.78; 95% CI 1.07-2.94) compared to those without diabetes. Conclusion: Coexisting clinical depression and anxiety are significantly present in the primary care setting, especially among younger individuals, patients with diabetes and women. Mental health screening programmes should include screening for both depression and anxiety, and target these at-risk groups.

Concordance of self-reporting of diabetes compared with medical records: A comparative study using polyclinic data in Singapore.

INTRODUCTION: Studies of concordance between patients' self-report of diseases and a criterion standard (e.g. chart review) are usually conducted in epidemiological studies to evaluate the agreement of self-reported data for use in public health research. To our knowledge, there are no published studies on concordance for highly prevalent chronic diseases such as diabetes and pre-diabetes. The aims of this study were to evaluate the concordance between patients' self-report and their medical records of diabetes and pre-diabetes diagnoses, and to identify factors associated with diabetes concordance. METHOD: A cross-sectional, interviewer-administered survey was conducted on patients with chronic diseases after obtaining written consent to assess their medical notes. Interviewers were blinded to the participants' profiles. Concordance was evaluated using Cohen's kappa (κ). A multivariable logistic regression model was used to identify factors associated with diabetes concordance. RESULTS: There was substantial agreement between self-reported and medical records of diabetes diagnoses (κ=0.76) and fair agreement for pre-diabetes diagnoses (κ=0.36). The logistic regression model suggested that non-Chinese patients had higher odds of diabetes concordance than Chinese patients (odds ratio [OR]=4.10, 95% confidence interval [CI] 1.19-14.13, P=0.03). Patients with 3 or more chronic diseases (i.e. multimorbidity) had lower odds of diabetes concordance than patients without multimorbidity (OR=0.21, 95% CI 0.09-0.48, P<0.001). CONCLUSION: Diabetes concordance was substantial, supporting the use of self-report of diabetes by patients with chronic diseases in the primary care setting for future research. Pre-diabetes concordance was fair and may have important clinical implications. Further studies to explore and improve health literacy and patient-physician communication are needed.

Patterns of patients with multiple chronic conditions in primary care: A cross-sectional study.

OBJECTIVE: Our aim was to identify the patterns of multimorbidity among a group of patients who visited primary care in Singapore. METHODS: A cross-sectional study of electronic medical records was conducted on 437,849 individuals aged 0-99 years who visited National Healthcare Group Polyclinics from 1 Jul 2015 to 30 Jun 2016 for the management of chronic conditions. Patients' health conditions were coded with the 10th revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10), and patient records were extracted for analysis. Patients' diagnosis codes were grouped by exploratory factor analysis (EFA), and patterns of multimorbidity were then identified by latent class analysis (LCA). RESULTS: EFA identified 19 groups of chronic conditions. Patients with at least three chronic conditions were further separated into eight classes based on demographics and probabilities of various diagnoses. We found that older patients had higher probabilities of comorbid hypertension, kidney disease and ischaemic heart disease (IHD), while younger patients had a higher probability of comorbid obesity. Female patients had higher probabilities of comorbid arthritis and anaemia, while male patients had higher probabilities of comorbid kidney diseases and IHD. Indian patients presented with a higher probability of comorbid diabetes than Chinese and Malay patients. CONCLUSIONS: This study demonstrated that patients with multimorbidity in primary care could be classified into eight patterns. This knowledge could be useful for more precise management of these patients in the multiethnic Asian population of Singapore. Programmes for early intervention for at-risk groups can be developed based on the findings.