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Am J Health Promot. 1994 Nov-Dec;9(2):115-24.

Relationship between cumulative exposure to health messages and awareness and behavior-related drinking during pregnancy.

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1
California Pacific Medical Center Research Institute, Alcohol Research Group, Berkeley, California 94709-2176, USA.

Abstract

PURPOSE:

This paper describes the relationship between exposure to multiple sources of health messages about the risk of drinking during pregnancy and respondents' awareness and behavior related to this risk.

DESIGN:

Observational study using telephone interview data.

SETTING:

Exposure to this message occurs via a government warning on alcoholic beverage containers, warning posters in restaurants and bars, and media advertisements.

SUBJECTS:

Representative nationwide samples of adults were interviewed in 1990 (n = 2,000) and 1991 (n = 2,017), with response rates of 64% and 62%, respectively.

MEASURES:

Outcomes assessed are knowledge of the alcohol-related risk of birth defects, conversations about drinking during pregnancy, and self-reported reduction of alcohol consumption due to health concerns.

RESULTS:

Multivariate logistic regression models were used. In the total sample, respondents exposed to one, two, and three different message sources were more likely to converse about drinking during pregnancy than those exposed to no messages (odds ratio = 2.6, 3.8, and 4.1, respectively), while reduced alcohol consumption due to health concerns associated with exposure to two and three different sources (odds ratio = 1.6 and 2.0, respectively). Among women aged 18 to 40, a similar relationship is found for conversations, but it was only among those seeing all three message types that a reduction in consumption was observed (odds ratio = 2.8). Interpretation of these findings are limited because of respondent bias in alcohol consumption, message source exposure, and the cross-sectional nature of the data employed.

CONCLUSIONS:

These findings support the public health approach of implementing multi-faceted strategies to maximize risk reduction interventions.

PMID:
10150712
[Indexed for MEDLINE]
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