| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
RESEARCH AND PRACTICE |
Dan Culica is with the Southwestern Medical Center Program, University of Texas Health Science Center at Houston, School of Public Health, Dallas, Tex. James Rohrer is with the Department of Health Services Research and Management, Texas Tech University, Lubbock, Tex. Marcia Ward is with the Department of Health Management and Policy, College of Public Health, University of Iowa, Iowa City. Peter Hilsenrath is with the Department of Health Management and Policy, School of Public Health, University of North Texas Health Science Center, Fort Worth, Tex. Paul Pomrehn is with the Department of Preventive Medicine, College of Public Health, University of Iowa, Iowa City.
Correspondence: Requests for reprints should be sent to Dan Culica, MD, PhD, UT Health Science Center at Houston, School of Public Health, UT-Southwestern MPH Program, 5323 Harry Hines Blvd, V8.112N, Dallas, TX 75390-9128 (e-mail: dan.culica{at}utsouthwestern.edu).
 |
ABSTRACT |
|---|
 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
|---|
Objectives. This study determined which predisposing, enabling, need, behavioral, and disease factors predict the use of medical checkups.
Methods. The Behavioral Risk Factor Surveillance System was used to obtain state estimates in Iowa.
Results. A decreased likelihood of recent checkups was noted for persons aged 25 to 44, men, and those who faced cost barriers. An increased likelihood of recent checkups was associated with married people, highest household income, health insurance, fair and poor health status, physical exercise, occasional smoking, and some chronic diseases.
Conclusions. A profile of persons not having a checkup in the past 12 months emerged from the investigation.
|
INTRODUCTION |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
|---|
The purpose of this research was to determine which predisposing, enabling, and need factors; personal health behaviors; and chronic medical conditions predicted the use of medical checkups by people in Iowa. Our intention was to develop a profile at the state level of persons not having a checkup in the past 12 months so that prevention services could be targeted.
Several research projects have used the Behavioral Risk Factor Surveillance System to draw conclusions about patterns of use of clinical prevention services.2–5 Routine medical checkups were the outcome variable in several other studies as well.6–9 The age variable was most often associated with medical checkup use in these studies3,7,8 showing an increased likelihood for people older than 50 years. Another demographic factor influencing use of medical checkups was sex3,4,7; men were less likely to be seen for periodic health examinations,4 particularly if they were poor.7 Compared with persons of other races/ethnicities, White persons had an increased likelihood of visiting a physician for routine health examination.6 Having health insurance coverage also was associated with access to medical checkups.3,5,7 Respondents with higher levels of health insurance were more likely to receive medical checkups, especially when their health plans covered most or some of their clinical prevention.3 Other factors determined by previous research to be associated with use of routine checkups were health risk factors such as smoking,3,8 drinking, and sedentary lifestyle3; residing in a rural area4; being hospitalized3; physician practice size and physician gender8; and presence of a chronic disease.8 Collectively, these studies present a confusing picture about the correlates of medical checkups, portraying inconsistent findings.
|
METHODS |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
|---|
Time since a respondent last visited a physician for a routine checkup was coded, representing visits within the past year (recent users) compared with a longer period (lapsed users). The past-year-use cutoff point was chosen for benchmarking reasons.
A modified form of the behavioral model,13 frequently applied in utilization studies, was used to create 5 groups of independent variables. The predictors of clinical prevention services were grouped into predisposing characteristics, enabling resources, perceived need, personal health behaviors,14 and chronic medical conditions. Descriptive and bivariate analyses were performed.
Logistic regression analysis, using SUDAAN (Research Triangle Institute, Research Triangle Park, NC), was performed to examine the use of medical checkups. A hierarchical model approach15 was applied in the extended behavioral model. This approach allows more realistic representations of regression functions than the conventional approaches.16,17 Adding a second-stage model to the analysis produced gains in the accuracy of predictors and effect estimates.
|
RESULTS |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
|---|
. The population of Iowa is older, has fewer employed people, is predominantly White, and has more married couples compared with the nation.18 Although the median household income in Iowa is less than that nationwide,19 fewer people lack health coverage or could not afford a physician visit in the past year.
|
). Compared with the descriptive analysis, fewer variables were significantly associated with the respondent's probability of having a periodic health examination. A reduced likelihood of having a checkup in the past 12 months was associated with being between ages 25 and 64, male, unmarried, and a daily smoker. People who perceived medical cost barriers also were less likely to obtain checkups. Checkups were more likely among persons with incomes greater than $75 000; persons with health insurance; persons whose health status was rated as very good, fair, or poor rather than good or excellent; persons involved in any physical activity; and persons with chronic diseases. Compared with nonsmokers, occasional smokers and former smokers were more likely to have a checkup.
|
|
DISCUSSION |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
|---|
Several limitations can be identified in this investigation. The cross-sectional nature of the study excluded testing for causal relations. In addition, findings from the study may not be generalizable to other states. Although in Iowa most households have telephones, a response bias might have occurred.
As a result of our analysis, a profile of the lapsed user of medical checkups emerged. The typical lapsed user is male; is aged 25 to 44; is unmarried; has an annual income less than $75 000; is in excellent health (self-rated); smokes every day; does not exercise; has not been told he has diabetes, cardiovascular disease, or hypertension; and says that he cannot afford to see a physician. However, many of these single sedentary smokers report incomes that would support occasional medical visits. We are forced to conclude that these persons have other uses for their money. They may not place a high priority on medical checkups.
People aged 25 to 44 years represent a majority of the active and productive population. Single men in this age group who smoke and lack physical exercise are at high risk for acute and fatal cardiovascular accidents. This risk is increased by their perception of apparent good health status, comfortable socioeconomic status, and lack of knowledge about the existence of chronic diseases. Therefore, the single sedentary male smoker may require aggressive outreach programs, or he may have to receive his screenings when seeing health professionals for other reasons.
Routine medical checkups were studied in this evaluation because they provide an opportunity to deliver clinical prevention services. The US Preventive Services Task Force does not suggest any particular periodicity for these health examinations.20 Often, health insurance or managed care plans decide the periodicity of routine examinations. The findings of this study suggest that people with a chronic medical condition could receive their periodic health examination during a health maintenance visit, but a routine medical checkup should be periodically provided to men between ages 25 and 44 years regardless of health coverage. This periodicity needs to be established at the national level, following a similar protocol used for prenatal care.
It appears that the determinants of medical checkup use may vary by state. This may be a result of differences in the availability of these services among states. Therefore, similar studies are needed in each state to correct for these discrepancies.
|
Footnotes |
|---|
Accepted for publication December 13, 2000.
|
References |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
|---|
2. Hagdrup NA, Simoes EJ, Brownson RC. Health care coverage: traditional and preventive measures and associations with chronic disease risk factors. J Community Health. 1997;22:387–399.[Medline]
3. Faulkner LA, Schauffler HH. The effect of health insurance coverage on the appropriate use of recommended clinical preventive services. Am J Prev Med. 1997;13:453–458.[Medline]
4. Friedman C, Brownson RC, Peterson DE, Wilkerson JC. Physician advice to reduce chronic disease risk factors. Am J Prev Med. 1994;10:367–371.[Medline]
5. Hopkins CE, Hetherington RW, Parsons PE. Quality of medical care: a factor analysis approach using medical records. Health Serv Res. 1975;10:199–208.[Medline]
6. Flocke SA, Stange KC, Zyzanski SJ. The association of attributes of primary care with the delivery of clinical preventive services. Med Care. 1998;36(suppl 8):AS21–AS30.[Medline]
7.
Saver BG, Peterfreund N. Insurance, income, and access to ambulatory care in King County, Washington. Am J Public Health. 1993;83:1583–1588.
8.
Preisser JS, Cohen SJ, Wofford J, et al. Physician and patient predictors of health maintenance visits. Arch Fam Med. 1998;7:346–351.
9.
Fontana SA, Baumann LC, Helberg C, Love RR. The delivery of preventive services in primary care practices according to chronic disease status. Am J Public Health. 1997;87:1190–1196.
10.
Stein AD, Lederman RI, Shea S. The Behavioral Risk Factor Surveillance System questionnaire: its reliability in a statewide sample. Am J Public Health. 1993;83:1768–1772.
11. Giles WH, Croft JB, Keenan NL, Wheeler FC. The validity of self-reported hypertension and correlates of hypertension awareness among blacks and whites within the stroke belt. Am J Prev Med. 1995;11:163–169.[Medline]
12. Brownson RC, Jackson-Thompson J, Wilkerson JC, Kiani F. Reliability of information on chronic disease risk factors collected in the Missouri Behavioral Risk Factor Surveillance System. Epidemiology. 1994;5:545–549.[Medline]
13. Andersen RM. Revisiting the behavioral model and access to medical care: does it matter? J Health Soc Behav. 1995;36:1–10.[Medline]
14. Andersen RM, Davidson PL. Measuring access and trends. In: Andersen R, Rice TH, Kominski GF, eds. Changing the US Health Care System: Key Issues in Health Services, Policy, and Management. San Francisco, Calif: Jossey-Bass Publishers; 1996:13–40.
15. Kleinbaum DG, Kupper LL, Muller KE. Applied Regression Analysis and Other Multivariate Methods. 3rd ed. Belmont, Calif: Duxbury Press; 1997.
16. Rothman KJ, Greenland S. Modern Epidemiology. 2nd ed. Philadelphia, Pa: Lippincott-Raven; 1998.
17. Phillips KA, Morrison KR, Andersen R, Aday LA. Understanding the context of healthcare utilization: assessing environmental and provider-related variables in the behavioral model of utilization. Health Serv Res. 1998;33(3 pt 1):571–596.[Medline]
18. The University of Iowa and the Iowa Department of Public Health. The 2001 Iowa Health Fact Book. Iowa City: The University of Iowa College of Public Health; June 2001.
19. Statistical Abstract of the United States: 2000. 120th ed. Washington, DC: US Census Bureau; 2000.
20. US Preventive Services Task Force. Guide to Clinical Preventive Services. 2nd ed. Alexandria, Va: International Medical Publishing; 1996.
This article has been cited by other articles:
|
|
 |
|
  D. W. L. Lai and S. Kalyniak Use of Annual Physical Examinations by Aging Chinese Canadians J Aging Health, October 1, 2005; 17(5): 573 - 591. [Abstract] [PDF]
|
|
|
|
 |
|
 S. M. Yu, H. A. Bellamy, M. D. Kogan, J. L. Dunbar, R. H. Schwalberg, and M. A. Schuster Factors That Influence Receipt of Recommended Preventive Pediatric Health and Dental Care Pediatrics, December 1, 2002; 110(6): e73 - 73. [Abstract] [Full Text] [PDF]
|
|
Read all eLetters
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
