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Gender Differences In Self-Assessed Health Of Young Adults In An English-Speaking Caribbean Nation
2384-2397
Correspondence
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.
Email: paulbourne1@yahoo.com
Telephone (876) 457 6990.
Background: Gender differences in self-assessed health in young adults (i.e. ages 15 – 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.