Gender Differences In Self-Assessed Health Of Young Adults In An English-Speaking Caribbean Nation
Paul Andrew Bourne
(Health Research Scientist), Dept. of Community Health Statistics,Faculty of Medical Sciences, University of the West Indies, Mona Campus, Kingston, Jamaica, West Indies.
Telephone (876) 457 6990.
Background: Gender differences in self-assessed health in young adults (i.e. ages 15 â€“ 44 years) are under-studied in the English-speaking Caribbean. Aims: The aims of the current research were to (1) provide the demographical characteristics of young adults; (2) examine the self-assessed health of young adults; (3) identify social determinants that explained the good health status for young adults; (4) determine the magnitude of each social determinant, and (5) determine gender differences in self-assessed health. Materials and methods: The current study extracted a sub-sample of 3,024 respondents from a larger nationally cross-sectional survey of 6,782 Jamaicans. Statistical analyses were performed using the Statistical Packages for the Social Sciences v 16.0. Descriptive statistics were used to provide demographic information on the samples. Chi-square was used to examine the association between non-metric variables and an Analysis of Variance was used to test the relationships between metric and non-dichotomous categorical variables. Logistic regression examined the relationship between the dependent variable and some predisposed independent variables. Results: One percent of the sample reported injury and 8% reported illness. Self-reported diagnosed illnesses were influenza (12.7%); diarrhoea (2.9%); respiratory disease (14.1%); diabetes mellitus (7.8%); hypertension (7.8%); arthritis (2.9%) and unspecified conditions (41.2%). The mean length of illness was 26.0 days (SD = 98.9. Nine social determinants and biological conditions explained 19.2% of the variability of self-assessed health. The biological conditions accounted for 78.1% of the explanatory model. Conclusion: Injury accounts for a miniscule percentage of illness and so using it to formulate intervention policies would lack depth to effectively address the health of this cohort.