Gender differences in self-reported morbidity

Evidence from a population-based study in southern Brazil

Dados Bibliográficos

ID5226955
AutoresRaul Andrés Mendoza-Sassi (0000-0002-4641-9056, Universidade Federal do Rio Grande), Jorge U Béria (0000-0002-1598-1089, Universidade Luterana do Brasil)
Ano2007
Volume23
Fascículo2
Páginas341-346
Data de publicação2007-02-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoCadernos de Saude Publica (JOURNAL)
Identificadores do periódicoISSN: 0102-311X • E-ISSN: 1678-4464
EditoraFapUNIFESP (SciELO) (PUBLISHER)
DOI10.1590/s0102-311x2007000200010
PMID17221083
OpenAlexW1975232950
SCIELO_PIDS0102-311X2007000200010
IdiomaEN
Citações recebidas14
Referências citadas17

This paper aims to assess variations in self-reported morbidity between men and women using six different measures of reported illness. The cross-sectional study was conducted in the municipality of Rio Grande, southern Brazil. Demographic, socioeconomic, and morbidity data were collected from a probabilistic sample of 1,260 persons aged 15 years or over, using a specific questionnaire. Statistical analysis included a multivariate Poisson regression analysis. Prevalence Ratios (PR) with 95% confidence intervals (95%CI) were calculated. After adjusting for some confounding variables (age, race, unemployment, marital status, income, social class, and education), women showed greater risk of any symptom (PR = 3.21; 95%CI: 2.71-3.83), three or more symptoms (PR = 4.22; 95%CI: 2.97-5.98), potentially serious symptoms (PR = 1.75; 95%CI: 1.31-2.34), poor/fair health (PR = 1.78; 95%CI: 1.37-2.32), and minor psychiatric disorders (PR = 1.76; 95%CI: 1.31-2.37). The study revealed dissimilarity in self-reported morbidity between men and women in southern Brazil, but with different degrees depending on type of morbidity. This excess can be explained by gender difference in health-seeking behavior for perceiving or reporting health problems

Confidence interval · Confounding · Cross-sectional study · Environmental health · Marital status · Multivariate analysis · Poisson regression · Population · Social class · Socioeconomic status · Unemployment · Demography · Global Health Care Issues · Global Public Health Policies and Epidemiology · Health disparities and outcomes · Medicine