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© 2003 American Public Health Association
RESEARCH AND PRACTICE |
The authors are with the Department of Health Services Research and Management, School of Medicine, Texas Tech University Health Sciences Center, Lubbock.
Correspondence: Requests for reprints should be sent to K. Tom Xu, PhD, Department of Health Services Research and Management, School of Medicine, Texas Tech University Health Sciences Center, 3601 4th St, Room 1C165, Lubbock, TX 79430 (e-mail: ke.xu{at}ttuhsc.edu).
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INTRODUCTION |
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 TOP INTRODUCTION METHODSRESULTSCONCLUSIONSReferences |
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Few studies have examined how health system, financial, social structure, or health characteristics affect the use of health services differentially by gender. Rather, the majority of studies on health behaviors assume that gender represents a set of individual differences. One notable exception is a small set of reports on the use of services by female veterans.1–3 Recently, a study found gender differences in the contributions of employment, having children, and socioeconomic factors to health care access, with access measured by whether the individual had a usual source of care and health insurance coverage.4
Of particular concern is whether there are gender differences in the likelihood of visiting a physician by disease or disorder.5,6 In addition, individuals who have a constellation of chronic diseases, such as diabetes and hypertension, undoubtedly are more likely to visit a physician than persons who have less severe health conditions. Yet it is also plausible that service use differs not only according to gender, but by both gender and health status. Using a nationally representative data set, we examined determinants of gender differences in physician visits by employing different levels of control for health status.
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METHODS |
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TOPINTRODUCTIONMETHODSRESULTSCONCLUSIONSReferences |
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Data were extracted from the Medical Expenditure Panel Survey (MEPS), a nationally representative survey.7 Descriptions and details of the MEPS can be found elsewhere.8,9 Persons younger than 18 years were excluded from our analyses. To obtain national-level estimates and take into consideration the complex sampling design of MEPS, person weights, primary sampling units, and strata used by MEPS were controlled for in the estimation. The gender distribution of the sample was approximately equal (52% of the respondents were women).
The dependent variable was the probability of having had at least one office-based physician visit in 1996. Independent variables were demographic characteristics, health conditions, nonfinancial barriers to use of services, and financial barriers to use of services (Table 1
). Multivariate logistic regressions were performed by gender. We estimated 3 models for men and 3 counterparts for women. Model 1 did not include any health measure. Model 2 included number of medical conditions, a crude measure of health. Model 3 included dummy variables representing each condition but not the number of conditions. A dummy variable was used for each condition, based on more than 200 clinically meaningful mutually exclusive categories in the Clinical Classification Software developed by the Agency for Healthcare Research and Quality (Rockville, Md). Parameter estimates from the equations for male and female samples were compared to establish whether there were any significant differences in the coefficient of each independent variable.
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RESULTS |
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TOPINTRODUCTIONMETHODSRESULTSCONCLUSIONSReferences |
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According to MEPS data, approximately 31% of adults in the United States did not have any office-based physician visit in 1996. About 59.6% of men and 76.8% of women had at least one visit. Descriptive statistics are reported in Table 1
. All proportions and means in the table are population-level estimates with the complex sampling design of MEPS controlled for. Table 2 presents the multivariate logistic regression results.
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Our results showed that some factors were significant in the models for both men and women, whereas other factors were significant only for one or the other. The number of factors significantly associated with the odds of having visited a doctor decreased as the control for health status became more detailed. Women were more affected by financial barriers than men. In particular, women who had lower incomes were consistently less likely than others to have visited a physician. In contrast, men were affected more than women by nonfinancial barriers. For example, waiting times of 30 minutes or longer in a physician’s office sharply reduced the likelihood of a man’s having visited a doctor.
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CONCLUSIONS |
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TOPINTRODUCTIONMETHODSRESULTSCONCLUSIONSReferences |
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We examined determinants of and differences in use of physicians’ services by men and women and evaluated whether there were differences in use of services by both disease or disorder and gender. Specifically, we addressed the ability of nonfinancial, financial, demographic, and health characteristics to explain differences in women’s and men’s use of physicians’ services. We found that women were more affected than men by financial barriers. Thus, when nonfinancial barriers and health status are controlled for, poorer women appear to be at risk for underutilization of physicians’ services. In contrast, men were more likely than women to be influenced by nonfinancial barriers, such as long waiting time. Also, we found that specifications of health status could change our interpretation of gender differences in the probability of use of physicians’ services. Further research should analyze gender differences in other dimensions of service utilization and access, including the intensity of use of physicians’ services and the likelihood of hospitalization, as well as gender differences in satisfaction with medical care and perceptions of accessibility.
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Footnotes |
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Contributors
K. T. Xu contributed to conceptualization, analyses, and writing of the manuscript. T.F. Borders helped to interpret the results and write the manuscript.
No protocol approval was needed for this study.
Accepted for publication August 23, 2002.
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References |
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TOPINTRODUCTIONMETHODSRESULTSCONCLUSIONSReferences |
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1. Romeis JC, Gillespie KN, Thorman KE. Female veterans’ use of health care services. Med Care.1988;26:589–595.[Medline]
2. Romeis JC, Gillespie KN, Virgo KS, Thorman KE. Female veterans’ and nonveterans’ use of health care systems. Med Care.1991;29:932–936.[Web of Science][Medline]
3. Weiss TW, Ashton CM. Access of women veterans to Veterans Affairs hospitals. Women Health.1994;21:23–38.[Medline]
4. Merzel C. Gender differences in health care access indicators in an urban, low-income community. Am J Public Health.2000;90:909–916.
5. Green CA, Pope CR. Gender, psychosocial factors and the use of medical services: a longitudinal analysis. Soc Sci Med.1999;48:1363–1372.
6. Bertakis KD, Azari R, Helms LJ, Callahan EJ, Robbins JA. Gender differences in the utilization of health care services. J Fam Pract.2000;49:147–152.[Web of Science][Medline]
7. Medical Expenditure Panel Survey. Rockville, Md: Center for Cost and Financing Studies, Agency for Healthcare Research and Quality; 1999.
8. Cohen J. Design and Methods of the Medical Expenditure Panel Survey Household Component. Rockville, Md: Agency for Health Care Policy and Research; 1997. MEPS Methodology Report No. 1. AHCPR publication 97–0026.
9. Vistnes JP, Monheit AC. Health Insurance Status of the U.S. Civilian Noninstitutionalized Population 1996. Rockville, Md: Agency for Health Care Policy and Research; 1997. MEPS Research Findings No. 1. AHCPR publication 97–0030.
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