Neighbourhood income and anxiety: a study based on random samples of the Swedish population.
BACKGROUND
Few studies have investigated the association between the neighbourhood characteristics and the vast panorama of mental disorders. This study examined whether there is an association between neighbourhood income and anxiety, a common mental disorder.


METHODS
A national random sample of the entire Swedish population was used, consisting of 30 884 men and women aged 25-64 years. The sample was obtained from pooled data during the period 1995-2002 from the Swedish Annual Level of Living Survey. Small area market statistics were used in order to define neighbourhoods. The proportion of individuals with incomes in the lowest national income quartile was calculated for each neighbourhood. The distribution was then divided into quartiles. A log binomial model was applied in the estimation of prevalence ratios. Four models were calculated with stepwise inclusion of the variables. Model 4 was adjusted for all the individual variables, i.e. age, gender, marital status, immigrant status, social network, housing tenure, employment status, and income.


RESULTS
In neighbourhoods with the highest proportions of individuals with low income the prevalence ratio of anxiety was 1.33 (95% confidence interval 1.24-1.42). The association demonstrated between neighbourhood income and anxiety decreased after stepwise inclusion of the individual variables and disappeared after all the individual variables were accounted for.


CONCLUSIONS
Compositional explanations, rather than contextual explanations, lie behind the association between neighbourhood income and anxiety, a common mental disorder. However, we do not exclude the possibility that there is a contextual effect on severe mental disorders or among children with behavioural problems.
Lofors
Jonas
J
Karolinska Institute, Center for Family Medicine, Sweden.
Ramírez-León
Vania
V
Sundquist
Kristina
K
D000328:Adult; D001007:Anxiety / Q000453:epidemiology* / Q000209:etiology / Q000523:psychology; D003430:Cross-Sectional Studies; D004641:Emigration and Immigration / Q000706:statistics & numerical data; D004651:Employment / Q000706:statistics & numerical data; D005260:Female; D006306:Health Surveys; D006798:Housing / Q000706:statistics & numerical data; D006801:Humans; D007182:Income / Q000706:statistics & numerical data*; D016015:Logistic Models; D008297:Male; D017533:Marital Status / Q000706:statistics & numerical data; D008875:Middle Aged; D011159:Population Surveillance; D011204:Poverty Areas; D015995:Prevalence; D012111:Residence Characteristics / Q000706:statistics & numerical data*; D012307:Risk Factors; D012494:Sampling Studies; D017678:Sex Distribution; D012931:Social Environment; D012959:Socioeconomic Factors; D013548:Sweden / Q000453:epidemiology