No open-access location is known for this record yet.
No open-access location is known for this record yet.
BACKGROUND: Self-rated health and the factors that influence it have never been described in Singapore before. This paper presents a descriptive study of self-rated health in a nationally representative cross-sectional survey of 6236 persons. METHODS: As part of the National Health Surveillance Survey 2001, 6236 subjects aged 18 years and above were interviewed in the homes of participants by trained interviewers. The subjects were asked "In general, how would you rate your health today?", and given 5 possible responses. These were then categorized as "Good" (very good and good) and "Poor" (moderate, bad and very bad) self-rated health. The association of socio-economic and health behaviour risk factors with good self-rated health was studied using univariate and multivariate logistic regression analysis. RESULTS: Univariate analyses suggest that gender, ethnicity, marital status, education, household income, age, self-reported doctor-diagnosed illnesses, alcohol intake, exercise and BMI are all associated with poor self-rated health. In multivariate regression analyses, gender, ethnicity, household income, age, self-reported illness and current smoking and BMI were associated with poor self-rated health. There are gender differences in the association of various factors such as household income, smoking and BMI to self-rated health. CONCLUSION: Socioeconomic factors and health behaviours are significantly associated with self-rated health, and gender differences are striking. We discuss why these factors may impact self-rated health and why gender differences may have been observed, propose directions for further research and comment on the public policy implications of our findings.
Loading…
Stored only when both papers are in the corpus — 113 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.