Perceived sexism as a health determinant in Spain.
OBJECTIVE
The goals of the present study are to explore the association between perceived sexism and self-perceived health, health-related behaviors, and unmet medical care needs among women in Spain; to analyze whether higher levels of discrimination are associated with higher prevalence of poor health indicators and to examine whether these relationships are modified by country of origin and social class.


METHODS
The study is based on a cross-sectional design using data from the 2006 Spanish Health Interview Survey. We included women aged 20-64 years (n = 10,927). Six dependent variables were examined: four of health (self-perceived health, mental health, hypertension, and having had an injury during the previous year), one health behavior (smoking), and another related to the use of the health services (unmet need for medical care). Perceived sexism was the main independent variable. Social class and country of origin were considered as effect modifiers. We obtained the prevalence of perceived sexism. Logistic regression models, adjusted for potential confounders, were fitted to study the association between sexism and poor health outcomes.


RESULTS
The prevalence of perceived sexism was 3.4%. Perceived sexism showed positive and consistent associations with four poor health outcomes (poor self-perceived health, poor mental health, injuries in the last 12 months, and smoking). The strength of these associations increased with increased scores for perceived sexism, and the patterns were found to be modified by country of origin and social class.


CONCLUSIONS
This study shows a consistent association between perceived sexism and poor health outcomes in a country of southern Europe with a strong patriarchal tradition.
Borrell
Carme
C
Agència de Salut Pública de Barcelona, Barcelona, Spain.
Artazcoz
Lucia
L
Gil-González
Diana
D
Pérez
Glòria
G
Rohlfs
Izabella
I
Pérez
Katherine
K
D000328:Adult; D003430:Cross-Sectional Studies; D005260:Female; D015438:Health Behavior; D006305:Health Status Indicators; D054625:Healthcare Disparities / Q000592:standards / Q000706:statistics & numerical data*; D006801:Humans; D016015:Logistic Models; D008875:Middle Aged; D017063:Outcome Assessment, Health Care / Q000592:standards / Q000706:statistics & numerical data*; D011287:Prejudice; D012737:Sex Factors; D012923:Social Class; D013030:Spain / Q000453:epidemiology; D055815:Young Adult