OBJECTIVES: This was a comparative study between Australia and Korea that investigated whether and to what extent factors related to self-rated good health (SRGH) differ by gender among age groups. METHODS: This study was a secondary analysis of data that were collected in nationally representative, cross-sectional, and population-based surveys. We analyzed Australian and Korean participants > 20 years of age using 2011 data from the Australian National Nutritional Physical Activity Survey (n = 9,276) and the Korean National Health and Nutritional Examination Survey (n = 5,915). Analyses were based on multiple logistic regression after controlling for covariates. RESULTS: Factors associated with SRGH and the extent of their influence differed by gender among age groups within each nation. Australian SRGH was associated with more factors than Korean SRGH, except in participants > 65 years old. Many differences among adults aged 20–44 years were observed, particularly with regard to the influence of socioeconomic factors. Living with a spouse only influenced SRGH in men 20–44 years old in both countries, negatively for Korean men and positively for Australian men. In this same age group, SRGH was positively influenced by employment and attainment of a higher education level in Australian men but not among Korean men; among women, income, but not education, affected SRGH in Korea, whereas in Australia, women were more influenced by education than by income. Lack of chronic disease had a strong influence on SRGH in both countries and was influential in all Australians and Koreans except those ≥ 65 years old. CONCLUSION: Broad features of society should be considered when discussing health and differences in associated factors and their influences. For focused public health interventions of population groups, it is also necessary to consider gender and age groups within social environments.
Adult ; Australia* ; Chronic Disease ; Education ; Employment ; Female* ; Humans ; Korea ; Logistic Models ; Male* ; Motor Activity ; Population Groups ; Public Health ; Social Environment ; Socioeconomic Factors ; Spouses

Humans ; Primary Health Care ; 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.
Humans ; Prediabetic State ; Singapore/epidemiology* ; Cross-Sectional Studies ; Diabetes Mellitus/epidemiology* ; Medical Records ; Self Report

Humans ; COVID-19/epidemiology* ; Singapore/epidemiology* ; SARS-CoV-2 ; Primary Health Care