Racial and Ethnic Disparities in Internet Use for Seeking Health Information Among Young Women

Abstract

To examine the influence of race/ethnicity on seeking health information from the Internet among women aged 16–24 years, the authors conducted a self-administered survey on 3,181 women regarding their Internet use and obtaining information on reproductive health (menstruation, contraception, pregnancy, sexually transmitted infections) and general health from the Internet. The authors performed multivariate logistic regression to examine the association between race/ethnicity and online health-related information seeking after adjusting for covariates. Racial/ethnic disparities were noted in overall Internet use and its use to locate health information. Overall, more White (92.7%) and Black (92.9%) women used the Internet than did Hispanics (67.5%). More White women (79.2%) used it to find health information than did Blacks and Hispanics (70.3% and 74.3%, respectively). Compared with White women, Blacks and Hispanics were less likely to seek information on contraception [(OR 0.73, 95% CI 0.58–0.91) and (OR 0.75, 95% CI 0.61–0.92)] and more likely to seek information on pregnancy tests [(OR 1.67, 95% CI 1.28–2.18) and (OR 1.40, 95% CI 1.09–1.81] and sexually transmitted infections [(OR 1.39, 95% CI 1.11–1.73) and (OR 1.25, 95% CI 1.01–1.54)], respectively. With regard to general health issues—such as how to quit smoking, how to lose weight, alcohol/drug use, mood disorders, and skin disorders—Blacks, but not Hispanics, were significantly less likely to seek online information than were Whites. Disparities in the way that women from different backgrounds use the Internet for health-related information could be associated with overall health awareness.

Acknowledgments

Federal support for this study was provided by the Eunice Kennedy Shriver National Institute of Child Health & Human Development with two awards: Dr. Abbey B. Berenson is supported by a mid-career investigator award in patient-oriented research (K24HD043659, PI: Berenson). Dr. Tabassum Haque Laz is supported as a National Research Service Award postdoctoral fellow under an institutional training grant (T32HD055163, PI: Berenson). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Child Health & Human Development or the National Institutes of Health.

Notes

Note. One-way analysis of variance was used to examine differences by race/ethnicity for continuous variables. Chi-square was used to examine differences by race/ethnicity for categorical variables.

*Percentages do not add up to 100 because of Internet use at multiple places.

Chi-square was used to examine the differences by race/ethnicity.

^ΦWhen significant difference was found between Blacks and Whites (p < .05).

^§When significant difference was found between Blacks and Hispanics (p < .05).

^†When significant difference was found between Hispanics and Whites (p < .05).

^a All participants (total, White, Blacks, and Hispanics); these denominators were used for “Internet use,” “having e-mail account,” and “connected with social network.”.

^b All Internet users (total, White, Blacks, and Hispanics); these denominators were used for “location of Internet access,” “duration of Internet use,” “frequency of Internet use,” “find health information for herself,” and “find health information for someone else.”.

Note. Chi-square was used to examine the differences by race/ethnicity.

^ΦWhen significant difference was found between Blacks and Whites (p < .05).

^†When significant difference was found between Hispanics and Whites (p < .05).

Note. Chi-square was used to examine the differences by race/ethnicity.

^ΦWhen significant difference was found between Blacks and Whites (p < .05).

^§When significant difference was found between Blacks and Hispanics (p < .05).

^†When significant difference was found between Hispanics and Whites (p < .05).

Note. Whites were considered as the reference. Adjusted by age (16–19 years vs. 20–24 years), education, annual income, and marital status.

^£Adjusted also by smoking status.

^ΩAdjusted also by body mass index.

*p < .05.

**p < .01.