Why do low-income women not use food stamps? Findings from the California Women's Health Survey.
OBJECTIVE
To determine factors associated with Food Stamp Program (FSP) participation in a potentially eligible California population.


METHODS
The California Women's Health Survey is an on-going annual telephone survey that collects data about health-related attitudes and behaviours from a randomly selected sample of women. Statistical procedures included chi2 and logistic regression.


METHODS
California, USA, from 2002 to 2004.


METHODS
A total of 527 FSP female participants and 1405 potentially eligible non-participant females, aged 18 years and older.


RESULTS
The following characteristics remained independently and positively related to FSP participation: single mother with children; unemployed; on welfare; on WIC (the Special Supplemental Nutrition Program for Women, Infants, and Children); and US-born. Women under 25 years and those over 54 years were less likely to participate than women aged 25-54 years. Hispanic/Latino ethnicity was also negatively related to participation. Over 42 % of potentially eligible non-participants cited 'don't need them' as the reason for not applying for FSP, but 34.9 % either do not think they are eligible or do not know how to apply. Potentially eligible non-participants who cite 'don't need them' as a reason for not applying are less likely to be food insecure, to have inadequate income and to use alternative emergency aid, compared to women citing all other reasons. The highest level of need is among those who cite worry about citizenship or stigma as reasons for not applying.


CONCLUSIONS
Strategies to increase participation in FSP should incorporate messages that change the public's perception of the programme, in addition to simplifying the application process, raising awareness of eligibility criteria and improving customer service.
Kaiser
Lucia
L
Department of Nutrition, University of California - Davis, One Shields Ave, Davis, CA 95616, USA. llkaiser@ucdavis.edu
D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D001294:Attitude to Health; D001364:Awareness; D002140:California; D016009:Chi-Square Distribution; D004522:Educational Status; D005006:Ethnicity / Q000523:psychology / Q000706:statistics & numerical data*; D005260:Female; D005523:Food Supply; D006801:Humans; D007182:Income; D016015:Logistic Models; D017533:Marital Status; D008875:Middle Aged; D008913:Minority Groups / Q000523:psychology / Q000706:statistics & numerical data*; D009749:Nutrition Surveys; D015995:Prevalence; D011632:Public Assistance / Q000706:statistics & numerical data*; D012307:Risk Factors; D016387:Women's Health