American Journal of Epidemiology

This Article Abstract FREE Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in ISI Web of Science Similar articles in PubMed Alert me to new issues of the journal Add to My Personal Archive Download to citation manager Search for citing articles in: ISI Web of Science (190) Request Permissions Disclaimer Google Scholar Articles by McNutt, L.-A. Articles by Hafner, J. P. Search for Related Content PubMed PubMed Citation Articles by McNutt, L.-A. Articles by Hafner, J. P. Social Bookmarking          What's this?

Am J Epidemiol 2003; 157:940-943.
Copyright © 2003 by Johns Hopkins Bloomberg School of Public Health

PRACTICE OF EPIDEMIOLOGY

Estimating the Relative Risk in Cohort Studies and Clinical Trials of Common Outcomes

Louise-Anne McNutt^1,, Chuntao Wu¹, Xiaonan Xue² and Jean Paul Hafner³

¹ Department of Epidemiology, School of Public Health, University at Albany, State University of New York, Rensselaer, NY.
² Department of Environmental Medicine, Division of Biostatistics, New York University School of Medicine, New York, NY.
³ Departments of Pulmonary and General Internal Medicine, Samuel S. Stratton Department of Veterans Affairs Medical Center, Albany, NY.

Received for publication June 14, 2001; accepted for publication March 14, 2003.

	ABSTRACT

TOP ABSTRACT INTRODUCTION COMPARISON OF AVAILABLE METHODS MODEL SELECTION: STUDYING... ZHANG AND YU’S PROPOSED... STRATIFIED ANALYSIS LOG-BINOMIAL MODEL POISSON REGRESSION AND THE... CROSS-SECTIONAL STUDIES CONCLUSIONS REFERENCES

 
Logistic regression yields an adjusted odds ratio that approximates the adjusted relative risk when disease incidence is rare (<10%), while adjusting for potential confounders. For more common outcomes, the odds ratio always overstates the relative risk, sometimes dramatically. The purpose of this paper is to discuss the incorrect application of a proposed method to estimate an adjusted relative risk from an adjusted odds ratio, which has quickly gained popularity in medical and public health research, and to describe alternative statistical methods for estimating an adjusted relative risk when the outcome is common. Hypothetical data are used to illustrate statistical methods with readily accessible computer software.

clinical trials; cohort studies; odds ratio; relative risk

	INTRODUCTION

TOP ABSTRACT INTRODUCTION COMPARISON OF AVAILABLE METHODS MODEL SELECTION: STUDYING... ZHANG AND YU’S PROPOSED... STRATIFIED ANALYSIS LOG-BINOMIAL MODEL POISSON REGRESSION AND THE... CROSS-SECTIONAL STUDIES CONCLUSIONS REFERENCES

 
The study of common outcomes is becoming more frequent in medicine and public health. Studies of symptoms, health behaviors, health care utilization, and even rare diseases in high-risk populations all have the potential to occur frequently (>10 percent) in a study population. This fact becomes an important consideration in deciding on the appropriate statistical analysis for a study. Typically, researchers use statistical methods designed for studies of rare diseases, sometimes incorrectly applied to studies of common outcomes. An example of this problem is the use of logistic regression to compute an estimated adjusted odds ratio and the subsequent interpretation of this estimate as a relative risk. This relation is approximately true when the incidence of outcome is less than 10 percent but usually not true when the outcome is more common. Although logistic regression may be correctly applied to studies of common outcomes, in public health we are often interested in estimating a relative risk (e.g., the probability of the outcome for one exposure group divided by the probability of the outcome for another exposure group (referent)), not the odds ratio, and it is this inference that becomes troublesome. In studies of common outcomes, the estimated odds ratio can, and often does, substantially overestimate the relative risk.

A method proposed by Zhang and Yu (1) to correct the adjusted odds ratio in cohort studies of common outcomes was proposed in 1998 and has gained popularity in medical and public health research. A review of the Journal Citation Reports (accessed on May 15, 2001) identified 74 citations of this paper, and 56 reported studies utilized Zhang and Yu’s method in the data analysis. Unfortunately, in most cases the method was incorrectly applied. By March 28, 2003, 214 scientific publications had cited Zhang and Yu’s paper.

The purpose of this paper is to discuss the drawbacks of the Zhang and Yu method as applied by many researchers and briefly review alternative methods for estimating an adjusted relative risk and its confidence interval when the incidence of disease is common and confounding exists. The study designs we focus on include cohort studies and clinical trials with equal follow-up times for study subjects, and the cumulative incidence in at least one exposure or treatment group is greater than 10 percent.

We focus on methods that are compatible with statistical programs widely used in medical and public health research, including stratified analysis, Poisson regression, and the log-binomial model. Other methods to estimate confidence intervals of adjusted relative risks (e.g., delta method, bootstrap) have attractive properties (2, 3); however, user-friendly software is still developmental for these methods and not yet widely available to researchers. We focus here on the situation where effect modification (interaction with other factors) of the relative risk does not exist.

	COMPARISON OF AVAILABLE METHODS

TOP ABSTRACT INTRODUCTION COMPARISON OF AVAILABLE METHODS MODEL SELECTION: STUDYING... ZHANG AND YU’S PROPOSED... STRATIFIED ANALYSIS LOG-BINOMIAL MODEL POISSON REGRESSION AND THE... CROSS-SECTIONAL STUDIES CONCLUSIONS REFERENCES

 
For the purpose of illustration, we created several hypothetical studies; each focuses on the association between a specific risk factor (E) and disease (D) and needs to be adjusted for a confounder (C). The data and calculated adjusted and crude measures of the relative risk for the method reviewed are shown in table 1. Additionally, we provide results from a simulation study that highlights the potential bias that may occur with the Zhang and Yu correction method (table 2).

View this table: [in this window] [in a new window]   TABLE 1. Comparison of methods to compute adjusted relative risks and confidence intervals for studies of common outcomes

 

View this table: [in this window] [in a new window]   TABLE 2. Simulation study comparing methods of estimating adjusted relative risk and coverage of confidence interval*

 

	MODEL SELECTION: STUDYING ASSOCIATION VERSUS PREDICTION

TOP ABSTRACT INTRODUCTION COMPARISON OF AVAILABLE METHODS MODEL SELECTION: STUDYING... ZHANG AND YU’S PROPOSED... STRATIFIED ANALYSIS LOG-BINOMIAL MODEL POISSON REGRESSION AND THE... CROSS-SECTIONAL STUDIES CONCLUSIONS REFERENCES

 
Rarely is there only one statistical model that adequately fits a set of data. Rather, researchers find themselves choosing among a few models that fairly summarize the information. The choice between models that adequately fit the data is based on various criteria, one of which is the research question. Relative risks are computed for studies that focus on measuring an association(s) between an exposure(s)/risk factor(s) and an outcome. Unlike predictive models where parsimony is revered, regression models for studies of association often keep several factors that may not explain large amounts of the variance in the outcome; however, these variables confound the association between exposure(s) and outcome sufficiently to warrant adjusting for them in the analysis (4, 5). Other criteria considered in model selection include the existence of influential individuals, extreme outliers, and other factors related to model fit (4).

	ZHANG AND YU’S PROPOSED METHOD

TOP ABSTRACT INTRODUCTION COMPARISON OF AVAILABLE METHODS MODEL SELECTION: STUDYING... ZHANG AND YU’S PROPOSED... STRATIFIED ANALYSIS LOG-BINOMIAL MODEL POISSON REGRESSION AND THE... CROSS-SECTIONAL STUDIES CONCLUSIONS REFERENCES

 
Zhang and Yu proposed an intriguing, simple formula to convert an odds ratio provided by logistic regression to a relative risk (1):

In this formula, P₀ is the incidence of the outcome in the nonexposed group, "OR" is an odds ratio from a logistic regression equation, and "RR" is an estimated relative risk. Most researchers apply this formula to the adjusted odds ratio to estimate an adjusted relative risk. Using the formula in this manner is incorrect and will produce a biased estimate when confounding is present. If no confounding exists, then regression analysis is not needed and simple calculations can be used to compute an estimated relative risk (6).

With logistic regression, an estimated relative risk can be computed for each covariate pattern (i):

where Y is the outcome factor of interest (dependent variable), E is the exposure of interest, and x₂, ..., x_k are confounders. Although the formula looks complicated, these probabilities are just the predicted values that statistical programs provide routinely. It should be noted that this formula cannot be used for classical case-control studies, as the intercept cannot be validly estimated.

In data from our studies on the health effects of violence, the Zhang and Yu correction, applied to the adjusted odds ratio and using the incidence among the unexposed for the entire sample, usually tends to be biased away from the null, suggesting that the strength of association is greater than is true. This bias occurs because the formula, used as one summary value, fails to take into consideration the more complex relation in the incidence of disease related to exposure for each covariate pattern. This finding also occurred in Zhang and Yu’s simulation studies (1). Although the formula can be applied to specific covariate patterns, taking the ratio of the predicted probabilities is a simpler method to obtain covariate pattern-specific relative risks.

It is also important to note that, in general, if an outcome is common, then homogeneity of the odds ratio cannot coexist with homogeneity of the relative risk. It is useful to note that more than one statistical model may adequately fit the data; however, allowance for effect modification will depend on which model is selected.

The most difficult problem in estimating an adjusted relative risk for studies of common outcomes is not the point estimate (which we discuss below), but rather the confidence interval. Zhang and Yu’s proposed confidence interval for the adjusted relative risk, computed by applying the above formula to the bounds on the adjusted odds ratio’s confidence interval, also can be biased, leading one to believe that the relative risk estimate is more precise than is true (7). This bias occurs because the proposed calculation does not take into consideration the covariance between the estimated incidence and estimated odds ratio. Yu and Zhang note that a "trade-off between simplicity and precision" (8, p. 529) is at issue with their method; however, we believe that it is important, particularly when there are policy implications, not to overstate precision. In the simulation study results presented in table 2, the computed 95 percent confidence interval coverage is only 63 percent (it should be 95 percent), suggesting that in some typical situations substantial misrepresentation of precision is possible.

	STRATIFIED ANALYSIS

TOP ABSTRACT INTRODUCTION COMPARISON OF AVAILABLE METHODS MODEL SELECTION: STUDYING... ZHANG AND YU’S PROPOSED... STRATIFIED ANALYSIS LOG-BINOMIAL MODEL POISSON REGRESSION AND THE... CROSS-SECTIONAL STUDIES CONCLUSIONS REFERENCES

 
One of the simplest and best-known techniques for calculating an adjusted relative risk is stratified analysis (9). Using stratified analysis, the relative risk between the risk factor of interest (E) and disease (D) is computed for each level of the confounder. These stratum-specific relative risks can be pooled together to create one adjusted relative risk, usually by taking a weighted average of the stratum-specific relative risks. Typically, the weights are chosen so that they are larger for strata with the most individuals and smaller for strata with fewer individuals (4).

	LOG-BINOMIAL MODEL

TOP ABSTRACT INTRODUCTION COMPARISON OF AVAILABLE METHODS MODEL SELECTION: STUDYING... ZHANG AND YU’S PROPOSED... STRATIFIED ANALYSIS LOG-BINOMIAL MODEL POISSON REGRESSION AND THE... CROSS-SECTIONAL STUDIES CONCLUSIONS REFERENCES

 
The log-binomial model has been proposed as a useful approach to compute an adjusted relative risk. Like logistic regression, the log-binomial model is used for the analysis of a dichotomous outcome. Both model the probability of the outcome (e.g., probability of disease given the exposure and confounders), and both assume that the error terms have a binomial distribution. The difference between the logistic model and the log-binomial model is the link between the independent variables and the probability of the outcome: In logistic regression, the logit function is used and, for the log-binomial model, the log function is used. In general, the log-binomial model produces an unbiased estimate of the adjusted relative risk. Although it has a couple of drawbacks, these appear to pose minimal restriction on its usefulness unless adjustment for many confounders is needed. First, the confidence interval for the adjusted relative risk computed may be narrower than is true (10, 11). As seen in table 2, our simulation study results suggest that this bias is minor and similar to that found in stratified analysis. Similar coverage was seen in simulations of a range of relative risks and confounding patterns (data not shown). Second, in some situations, the log-binomial model does not converge to provide parameter estimates (10, 12). The lack of convergence may simply be due to software programs that have a default convergence criterion that is insufficient. This problem can be remedied by requiring additional iterations in the modeling fitting process. Another reason the model fits may not converge to the maximum likelihood estimate(s) is that the maximum likelihood estimates may lie near a boundary of the parameter space. When this occurs, the iteration can become stuck at the boundary, and a small adjustment of the interim fit away from the boundary may be needed to keep the iterations moving toward the value(s) that maximizes the likelihood.

	POISSON REGRESSION AND THE CONCEPT OF PLACING BOUNDS ON THE CONFIDENCE INTERVAL

TOP ABSTRACT INTRODUCTION COMPARISON OF AVAILABLE METHODS MODEL SELECTION: STUDYING... ZHANG AND YU’S PROPOSED... STRATIFIED ANALYSIS LOG-BINOMIAL MODEL POISSON REGRESSION AND THE... CROSS-SECTIONAL STUDIES CONCLUSIONS REFERENCES

 
Poisson regression is generally reserved for studies of rare diseases where patients may be followed for different lengths of time, such as cohort studies of rare outcomes conducted over many years with some patients being lost to follow-up. In contrast, unconditional logistic regression is typically utilized when every patient is followed for the same length of time or for a defined period with equal follow-up for subjects. For cohort studies where all patients have equal follow-up times, Poisson regression can be used in a similar manner as logistic regression, with a time-at-risk value specified as 1 for each subject. If the model adequately fits the data, this approach provides a correct estimate of the adjusted relative risk(s). For studies of common outcomes, Poisson regression is likely to compute a confidence interval(s) that is conservative, suggesting less precision than is true (tables 1 and 2). The reason Poisson regression produces wider confidence intervals compared with a log-binomial model and stratified analysis is that the Poisson errors are overestimates of binomial errors when the outcome is common (Poisson errors approximately equal binomial errors when the outcome (disease) is rare). As the examples in table 1 illustrate, although the confidence interval is more conservative, the actual difference compared with a stratified analysis is moderate. Conceptually, this interval can be thought of as bounding the true confidence interval.

Computer programs for the log-binomial and Poisson regression are widely available. For example, many generalized linear models’ programs (e.g., PROC GENMOD in SAS; SAS Institute, Cary, North Carolina) can be used for both log-binomial and Poisson regression analysis. Checking the fit of the model can be done using standard methods.

	CROSS-SECTIONAL STUDIES

TOP ABSTRACT INTRODUCTION COMPARISON OF AVAILABLE METHODS MODEL SELECTION: STUDYING... ZHANG AND YU’S PROPOSED... STRATIFIED ANALYSIS LOG-BINOMIAL MODEL POISSON REGRESSION AND THE... CROSS-SECTIONAL STUDIES CONCLUSIONS REFERENCES

 
For cross-sectional studies, two common measures of association are the prevalence ratio and the prevalence odds ratio (13). The mathematical computations for these measures are identical to the relative risk and the odds ratio, respectively. Thus, the methods presented in this paper can be utilized for cross-sectional studies; however, a temporal association between risk factors and "outcome" cannot be assessed.

	CONCLUSIONS

TOP ABSTRACT INTRODUCTION COMPARISON OF AVAILABLE METHODS MODEL SELECTION: STUDYING... ZHANG AND YU’S PROPOSED... STRATIFIED ANALYSIS LOG-BINOMIAL MODEL POISSON REGRESSION AND THE... CROSS-SECTIONAL STUDIES CONCLUSIONS REFERENCES

 
The use of an adjusted odds ratio to estimate an adjusted relative risk appropriate for studies of rare outcomes, however, may be misleading when the outcome is common. The overestimation may inappropriately affect clinical decision-making or policy development. Additionally, overestimation of the importance of a risk factor may lead to unintentional errors in the economic analysis of potential intervention programs or treatments. Options exist to obtain unbiased estimates of relative risks in studies of common outcomes. Two methods that have widely available user-friendly software and often are statistically appropriate (e.g., fit the data) include stratified analysis and log-binomial modeling.

	NOTES

 
Correspondence to Dr. Louise-Anne McNutt, Department of Epidemiology, School of Public Health, University at Albany, 1 University Place, Room 125, Rensselaer, NY 12144 (e-mail: lam08{at}health.state.ny.us).

	REFERENCES

TOP ABSTRACT INTRODUCTION COMPARISON OF AVAILABLE METHODS MODEL SELECTION: STUDYING... ZHANG AND YU’S PROPOSED... STRATIFIED ANALYSIS LOG-BINOMIAL MODEL POISSON REGRESSION AND THE... CROSS-SECTIONAL STUDIES CONCLUSIONS REFERENCES

 

1. Zhang J, Yu KF. What’s relative risk? A method of correcting the odds ratio in cohort studies of common outcomes. JAMA 1998;280:1690–1.[Abstract/Free Full Text]
2. Rao CR. Linear statistical inference and its applications. 2nd ed. New York, NY: John Wiley & Sons, Inc, 1965.
3. Efron B, Tibshirani R. An introduction to the bootstrap. New York, NY: Chapman & Hall, 1993.
4. Kleinbaum DG, Kupper LL, Muller KE, et al. Applied regression analysis and other multivariable methods. Pacific Grove, CA: Brooks/Cole, 1998.
5. Rothman KJ, Greenland S, eds. Modern epidemiology. 2nd ed. Philadelphia, PA: Lippincott Williams & Wilkins, 1998.
6. Kleinbaum DG, Kupper LL, Morgenstern H. Epidemiologic research: principles and quantitative methods. New York, NY: Van Nostrand Reinhold, 1982.
7. McNutt LA, Hafner JP, Xue X. Correcting the odds ratio in cohort studies of common outcomes. (Letter). JAMA 1999;282:529.[Free Full Text]
8. Yu KF, Zhang J. Correcting the odds ratio in cohort studies of common outcomes (in reply). (Letter). JAMA 1999;282:529.[Free Full Text]
9. Mantel N, Haenszel W. Statistical aspects of the analysis of data from retrospective studies of disease. J Natl Cancer Inst 1959;22:719–48.[Web of Science][Medline]
10. Skov T, Deddens J, Petersen MR, et al. Prevalence proportion ratios: estimation and hypothesis testing. Int J Epidemiol 1998;27:91–5.[Abstract/Free Full Text]
11. Ma S, Wong CM. Estimation of prevalence proportion rates. (Letter). Int J Epidemiol 1999;28:175.[Free Full Text]
12. Wacholder S. Binomial regression in GLIM: estimating risk ratios and risk differences. Am J Epidemiol 1986;123:174–84.[Abstract/Free Full Text]
13. Lee J. Odds ratio or relative risk for cross-sectional data? Int J Epidemiol 1994;23:201–3.[Free Full Text]

CiteULike    Connotea    Del.icio.us    What's this?

This article has been cited by other articles:

				M. Leinonen, P. Nieminen, L. Kotaniemi-Talonen, N. Malila, J. Tarkkanen, P. Laurila, and A. Anttila Age-Specific Evaluation of Primary Human Papillomavirus Screening vs Conventional Cytology in a Randomized Setting J Natl Cancer Inst, November 9, 2009; (2009) djp367v1. [Abstract] [Full Text] [PDF]

				A. G. Siebers, P. J. J. M. Klinkhamer, J. M. M. Grefte, L. F. A. G. Massuger, J. E. M. Vedder, A. Beijers-Broos, J. Bulten, and M. Arbyn Comparison of Liquid-Based Cytology With Conventional Cytology for Detection of Cervical Cancer Precursors: A Randomized Controlled Trial JAMA, October 28, 2009; 302(16): 1757 - 1764. [Abstract] [Full Text] [PDF]

				V. Ehrenstein, K. J. Rothman, L. Pedersen, E. E. Hatch, and H. T. Sorensen Pregnancy-associated Hypertensive Disorders and Adult Cognitive Function Among Danish Conscripts Am. J. Epidemiol., October 15, 2009; 170(8): 1025 - 1031. [Abstract] [Full Text] [PDF]

				B. A. Mueller, E. J. Chow, A. Kamineni, J. R. Daling, A. Fraser, C. L. Wiggins, G. P. Mineau, M. R. Hamre, R. K. Severson, and C. Drews-Botsch Pregnancy Outcomes in Female Childhood and Adolescent Cancer Survivors: A Linked Cancer-Birth Registry Analysis Arch Pediatr Adolesc Med, October 1, 2009; 163(10): 879 - 886. [Abstract] [Full Text] [PDF]

				E. J. Chow, A. Kamineni, J. R. Daling, A. Fraser, C. L. Wiggins, G. P. Mineau, M. R. Hamre, R. K. Severson, C. Drews-Botsch, and B. A. Mueller Reproductive Outcomes in Male Childhood Cancer Survivors: A Linked Cancer-Birth Registry Analysis Arch Pediatr Adolesc Med, October 1, 2009; 163(10): 887 - 894. [Abstract] [Full Text] [PDF]

				R. Buchbinder, R. H. Osborne, P. R. Ebeling, J. D. Wark, P. Mitchell, C. Wriedt, S. Graves, M. P. Staples, and B. Murphy A Randomized Trial of Vertebroplasty for Painful Osteoporotic Vertebral Fractures N. Engl. J. Med., August 6, 2009; 361(6): 557 - 568. [Abstract] [Full Text] [PDF]

				L. Yin, H. Wills, N. Clarke, J. Shacks, C. Bottrell, and M. K. Poulsen Cardiovascular Risk in Preschool Children ICAN: Infant, Child, & Adolescent Nutrition, August 1, 2009; 1(4): 197 - 204. [Abstract] [PDF]

				I. H. de Boer, B. Kestenbaum, A. B. Shoben, E. D. Michos, M. J. Sarnak, and D. S. Siscovick 25-Hydroxyvitamin D Levels Inversely Associate with Risk for Developing Coronary Artery Calcification J. Am. Soc. Nephrol., August 1, 2009; 20(8): 1805 - 1812. [Abstract] [Full Text] [PDF]

				M. R. Khan, J. S. Kaufman, B. W. Pence, B. N. Gaynes, A. A. Adimora, S. S. Weir, and W. C. Miller Depression, Sexually Transmitted Infection, and Sexual Risk Behavior Among Young Adults in the United States Arch Pediatr Adolesc Med, July 1, 2009; 163(7): 644 - 652. [Abstract] [Full Text] [PDF]

				A A Al-Tayyib, M McFarlane, R Kachur, and C A Rietmeijer Finding sex partners on the internet: what is the risk for sexually transmitted infections? Sex Transm Inf, June 1, 2009; 85(3): 216 - 220. [Abstract] [Full Text] [PDF]

				H.-Y. Weng, Y.-H. Hsueh, L. L. McV. Messam, and I. Hertz-Picciotto Methods of Covariate Selection: Directed Acyclic Graphs and the Change-in-Estimate Procedure Am. J. Epidemiol., May 15, 2009; 169(10): 1182 - 1190. [Abstract] [Full Text] [PDF]

				P. Cummings The Relative Merits of Risk Ratios and Odds Ratios Arch Pediatr Adolesc Med, May 1, 2009; 163(5): 438 - 445. [Abstract] [Full Text] [PDF]

				L. H. Sansing, S. R. Messe, B. L. Cucchiara, S. N. Cohen, P. D. Lyden, S. E. Kasner, and For the CHANT Investigators Prior antiplatelet use does not affect hemorrhage growth or outcome after ICH Neurology, April 21, 2009; 72(16): 1397 - 1402. [Abstract] [Full Text] [PDF]

				References J. ICRU, April 1, 2009; 9(1): 115 - 131. [PDF]

				D. Talmor, T. Sarge, A. Malhotra, C. R. O'Donnell, R. Ritz, A. Lisbon, V. Novack, and S. H. Loring Mechanical Ventilation Guided by Esophageal Pressure in Acute Lung Injury N. Engl. J. Med., November 13, 2008; 359(20): 2095 - 2104. [Abstract] [Full Text] [PDF]

				N A. Habib, R T Lie, O Oneko, J Shao, P Bergsjo, and A K Daltveit Sociodemographic characteristics and perinatal mortality among singletons in North East Tanzania: a registry-based study J Epidemiol Community Health, November 1, 2008; 62(11): 960 - 965. [Abstract] [Full Text] [PDF]

				K. L. Chichlowska, K. M. Rose, A. V. Diez-Roux, S. H. Golden, A. M. McNeill, and G. Heiss Individual and Neighborhood Socioeconomic Status Characteristics and Prevalence of Metabolic Syndrome: The Atherosclerosis Risk in Communities (ARIC) Study Psychosom Med, November 1, 2008; 70(9): 986 - 992. [Abstract] [Full Text] [PDF]

				L M Hagel, W Pickett, P Pahwa, L Day, R J Brison, B Marlenga, T Crowe, P Snodgrass, K Ulmer, and J A Dosman Prevention of agricultural injuries: an evaluation of an education-based intervention Inj. Prev., October 1, 2008; 14(5): 290 - 295. [Abstract] [Full Text] [PDF]

				A. K. Smith, E. P. McCarthy, E. Paulk, T. A. Balboni, P. K. Maciejewski, S. D. Block, and H. G. Prigerson Racial and Ethnic Differences in Advance Care Planning Among Patients With Cancer: Impact of Terminal Illness Acknowledgment, Religiousness, and Treatment Preferences J. Clin. Oncol., September 1, 2008; 26(25): 4131 - 4137. [Abstract] [Full Text] [PDF]

				T. P. Lodise, J. Graves, A. Evans, E. Graffunder, M. Helmecke, B. M. Lomaestro, and K. Stellrecht Relationship between Vancomycin MIC and Failure among Patients with Methicillin-Resistant Staphylococcus aureus Bacteremia Treated with Vancomycin Antimicrob. Agents Chemother., September 1, 2008; 52(9): 3315 - 3320. [Abstract] [Full Text] [PDF]

				N. Patel, L.-A. McNutt, and T. P. Lodise Relationship between Various Definitions of Prior Antibiotic Exposure and Piperacillin-Tazobactam Resistance among Patients with Respiratory Tract Infections Caused by Pseudomonas aeruginosa Antimicrob. Agents Chemother., August 1, 2008; 52(8): 2933 - 2936. [Abstract] [Full Text] [PDF]

				J.-C. Roze, S. Denizot, R. Carbajal, P.-Y. Ancel, M. Kaminski, C. Arnaud, P. Truffert, S. Marret, J. Matis, G. Thiriez, et al. Prolonged Sedation and/or Analgesia and 5-Year Neurodevelopment Outcome in Very Preterm Infants: Results From the EPIPAGE Cohort Arch Pediatr Adolesc Med, August 1, 2008; 162(8): 728 - 733. [Abstract] [Full Text] [PDF]

				M R Weaver, M Myaya, K Disasi, M Regoeng, H N Matumo, M Madisa, N Puttkammer, F Speilberg, P H Kilmarx, and J M Marrazzo Routine HIV testing in the context of syndromic management of sexually transmitted infections: outcomes of the first phase of a training programme in Botswana Sex Transm Inf, August 1, 2008; 84(4): 259 - 264. [Abstract] [Full Text] [PDF]

				J A Deddens and M R Petersen Approaches for estimating prevalence ratios Occup. Environ. Med., July 1, 2008; 65(7): 501 - 506. [Full Text] [PDF]

				J. Haukka, K. Suominen, T. Partonen, and J. Lonnqvist Determinants and Outcomes of Serious Attempted Suicide: A Nationwide Study in Finland, 1996-2003 Am. J. Epidemiol., May 15, 2008; 167(10): 1155 - 1163. [Abstract] [Full Text] [PDF]

				S. S. Hawkins, K. Lamb, T. J Cole, C. Law, and the Millennium Cohort Study Child Health Group Influence of moving to the UK on maternal health behaviours: prospective cohort study BMJ, May 10, 2008; 336(7652): 1052 - 1055. [Abstract] [Full Text] [PDF]

				M. P. LaValley Logistic Regression Circulation, May 6, 2008; 117(18): 2395 - 2399. [Full Text] [PDF]

				B A Mueller, E A Sidman, H Alter, R Perkins, and D C Grossman Randomized controlled trial of ionization and photoelectric smoke alarm functionality Inj. Prev., April 1, 2008; 14(2): 80 - 86. [Abstract] [Full Text] [PDF]

				C. M. Borkhoff PhD, G. A. Hawker MD MSc, H. J. Kreder MD MPH, R. H. Glazier MD MPH, N. N. Mahomed MD ScD, and J. G. Wright MD MPH The effect of patients' sex on physicians' recommendations for total knee arthroplasty Can. Med. Assoc. J., March 11, 2008; 178(6): 681 - 687. [Abstract] [Full Text] [PDF]

				S. E. Gilman, J. Breslau, S.V. Subramanian, B. Hitsman, and K. C. Koenen Social Factors, Psychopathology, and Maternal Smoking During Pregnancy Am J Public Health, March 1, 2008; 98(3): 448 - 453. [Abstract] [Full Text] [PDF]

				D. L. Hershman, D. Buono, R. B. McBride, W. Y. Tsai, K. A. Joseph, V. R. Grann, and J. S. Jacobson Surgeon Characteristics and Receipt of Adjuvant Radiotherapy in Women With Breast Cancer J Natl Cancer Inst, February 6, 2008; 100(3): 199 - 206. [Abstract] [Full Text] [PDF]

				J S Delaney, A Al-Kashmiri, R Drummond, and J A Correa The effect of protective headgear on head injuries and concussions in adolescent football (soccer) players Br. J. Sports Med., February 1, 2008; 42(2): 110 - 115. [Abstract] [Full Text] [PDF]

				K. I. Parker, C. W. R. Compton, F. M. Anniss, C. Heuer, and S. McDougall Quarter-Level Analysis of Subclinical and Clinical Mastitis in Primiparous Heifers Following the Use of a Teat Sealant or an Injectable Antibiotic, or Both, Precalving J Dairy Sci, January 1, 2008; 91(1): 169 - 181. [Abstract] [Full Text] [PDF]

				I. H. de Boer, B. C. Astor, H. Kramer, W. Palmas, S. L. Seliger, M. G. Shlipak, D. S. Siscovick, M. Y. Tsai, and B. Kestenbaum Lipoprotein Abnormalities Associated with Mild Impairment of Kidney Function in the Multi-Ethnic Study of Atherosclerosis Clin. J. Am. Soc. Nephrol., January 1, 2008; 3(1): 125 - 132. [Abstract] [Full Text] [PDF]

				C. Willi, P. Bodenmann, W. A. Ghali, P. D. Faris, and J. Cornuz Active Smoking and the Risk of Type 2 Diabetes: A Systematic Review and Meta-analysis JAMA, December 12, 2007; 298(22): 2654 - 2664. [Abstract] [Full Text] [PDF]

				A. V Perruccio, J D. Power, and E. M Badley The relative impact of 13 chronic conditions across three different outcomes J Epidemiol Community Health, December 1, 2007; 61(12): 1056 - 1061. [Abstract] [Full Text] [PDF]

				S. Keyhani, J. S. Ross, P. Hebert, C. Dellenbaugh, J. D. Penrod, and A. L. Siu Use of Preventive Care by Elderly Male Veterans Receiving Care Through the Veterans Health Administration, Medicare Fee-for-Service, and Medicare HMO Plans Am J Public Health, December 1, 2007; 97(12): 2179 - 2185. [Abstract] [Full Text] [PDF]

				Y. B. Cheung A Modified Least-Squares Regression Approach to the Estimation of Risk Difference Am. J. Epidemiol., December 1, 2007; 166(11): 1337 - 1344. [Abstract] [Full Text] [PDF]

				T. Liukkonen, P. Rasanen, A. Ruokonen, J. Laitinen, J. Jokelainen, M. Leinonen, V. B. Meyer-Rochow, and M. Timonen C-reactive protein Levels and Sleep Disturbances: Observations Based on The Northern Finland 1966 Birth Cohort Study Psychosom Med, October 1, 2007; 69(8): 756 - 761. [Abstract] [Full Text] [PDF]

				J. Hippisley-Cox, C. Parker, C. Coupland, and Y. Vinogradova Inequalities in the primary care of patients with coronary heart disease and serious mental health problems: a cross-sectional study Heart, October 1, 2007; 93(10): 1256 - 1262. [Abstract] [Full Text] [PDF]

				C. W. R. Compton, C. Heuer, K. Parker, and S. McDougall Epidemiology of Mastitis in Pasture-Grazed Peripartum Dairy Heifers and Its Effects on Productivity J Dairy Sci, September 1, 2007; 90(9): 4157 - 4170. [Abstract] [Full Text] [PDF]

				C. W. R. Compton, C. Heuer, K. Parker, and S. McDougall Risk Factors for Peripartum Mastitis in Pasture-Grazed Dairy Heifers J Dairy Sci, September 1, 2007; 90(9): 4171 - 4180. [Abstract] [Full Text] [PDF]

				S. I. Berndt, H. B. Carter, M. P. Schoenberg, and C. J. Newschaffer Disparities in Treatment and Outcome for Renal Cell Cancer Among Older Black and White Patients J. Clin. Oncol., August 20, 2007; 25(24): 3589 - 3595. [Abstract] [Full Text] [PDF]

				D. G. Hackam and J. D. Spence Combining Multiple Approaches for the Secondary Prevention of Vascular Events After Stroke: A Quantitative Modeling Study Stroke, June 1, 2007; 38(6): 1881 - 1885. [Abstract] [Full Text] [PDF]

				J. Ahnquist, P. Fredlund, and S. P Wamala Is cumulative exposure to economic hardships more hazardous to women's health than men's? A 16-year follow-up study of the Swedish Survey of Living Conditions J Epidemiol Community Health, April 1, 2007; 61(4): 331 - 336. [Abstract] [Full Text] [PDF]

				F. K. Winston, M. J. Kallan, M. R. Elliott, D. Xie, and D. R. Durbin Effect of Booster Seat Laws on Appropriate Restraint Use by Children 4 to 7 Years Old Involved in Crashes Arch Pediatr Adolesc Med, March 1, 2007; 161(3): 270 - 275. [Abstract] [Full Text] [PDF]

				T. P. Lodise, C. D. Miller, J. Graves, J. P. Furuno, J. C. McGregor, B. Lomaestro, E. Graffunder, and L.-A. McNutt Clinical Prediction Tool To Identify Patients with Pseudomonas aeruginosa Respiratory Tract Infections at Greatest Risk for Multidrug Resistance Antimicrob. Agents Chemother., February 1, 2007; 51(2): 417 - 422. [Abstract] [Full Text] [PDF]

				F. A. Masoudi, J. M. Foody, E. P. Havranek, Y. Wang, M. J. Radford, R. M. Allman, J. Gold, R. T. Wiblin, and H. M. Krumholz Trends in Acute Myocardial Infarction in 4 US States Between 1992 and 2001: Clinical Characteristics, Quality of Care, and Outcomes Circulation, December 19, 2006; 114(25): 2806 - 2814. [Abstract] [Full Text] [PDF]

				A. Mehrotra, A. M. Epstein, and M. B. Rosenthal Do Integrated Medical Groups Provide Higher-Quality Medical Care than Individual Practice Associations? Ann Intern Med, December 5, 2006; 145(11): 826 - 833. [Abstract] [Full Text] [PDF]

				E Waltermaurer, L-A McNutt, and M J Mattingly Examining the effect of residential change on intimate partner violence risk. J Epidemiol Community Health, November 1, 2006; 60(11): 923 - 927. [Abstract] [Full Text] [PDF]

				K.P. Wright, J.R. Trimarchi, J. Allsworth, and D. Keefe The effect of female tobacco smoking on IVF outcomes Hum. Reprod., November 1, 2006; 21(11): 2930 - 2934. [Abstract] [Full Text] [PDF]

				R. A. Hubner, K. R. Muir, J.-F. Liu, R. F.A. Logan, M. Grainge, N. Armitage, V. Shepherd, S. Popat, R. S. Houlston, and the United Kingdom Colorectal Adenoma Prevention C Genetic Variants of UGT1A6 Influence Risk of Colorectal Adenoma Recurrence. Clin. Cancer Res., November 1, 2006; 12(21): 6585 - 6589. [Abstract] [Full Text] [PDF]

				J. S. A. Stringer, I. Zulu, J. Levy, E. M. Stringer, A. Mwango, B. H. Chi, V. Mtonga, S. Reid, R. A. Cantrell, M. Bulterys, et al. Rapid scale-up of antiretroviral therapy at primary care sites in Zambia: feasibility and early outcomes. JAMA, August 16, 2006; 296(7): 782 - 793. [Abstract] [Full Text] [PDF]

				K. A. Katz The (relative) risks of using odds ratios. Arch Dermatol, June 1, 2006; 142(6): 761 - 764. [Abstract] [Full Text] [PDF]

				K M Smith and P Cummings Passenger seating position and the risk of passenger death in traffic crashes: a matched cohort study. Inj. Prev., April 1, 2006; 12(2): 83 - 86. [Abstract] [Full Text] [PDF]

				M. C. Nelson and P. Gordon-Larsen Physical Activity and Sedentary Behavior Patterns Are Associated With Selected Adolescent Health Risk Behaviors Pediatrics, April 1, 2006; 117(4): 1281 - 1290. [Abstract] [Full Text] [PDF]

				G. H. Dayan, K. M. Shaw, A. L. Baughman, L. C. Orellana, R. Forlenza, A. Ellis, J. Chaui, S. Kaplan, and P. Strebel Assessment of Delay in Age-appropriate Vaccination Using Survival Analysis Am. J. Epidemiol., March 15, 2006; 163(6): 561 - 570. [Abstract] [Full Text] [PDF]

				D. E. Hall Religious Attendance: More Cost-Effective Than Lipitor? J Am Board Fam Med, March 1, 2006; 19(2): 103 - 109. [Abstract] [Full Text] [PDF]

				K. M. Flegal, D. F. Williamson, and B. I. Graubard USING ADJUSTED RELATIVE RISKS TO CALCULATE ATTRIBUTABLE FRACTIONS Am J Public Health, March 1, 2006; 96(3): 398 - 398. [Full Text] [PDF]

				M. H. Samore, K. Bateman, S. C. Alder, E. Hannah, S. Donnelly, G. J. Stoddard, B. Haddadin, M. A. Rubin, J. Williamson, B. Stults, et al. Clinical Decision Support and Appropriateness of Antimicrobial Prescribing: A Randomized Trial JAMA, November 9, 2005; 294(18): 2305 - 2314. [Abstract] [Full Text] [PDF]

				K. K. Ness, A. C. Mertens, M. M. Hudson, M. M. Wall, W. M. Leisenring, K. C. Oeffinger, C. A. Sklar, L. L. Robison, and J. G. Gurney Limitations on Physical Performance and Daily Activities among Long-Term Survivors of Childhood Cancer Ann Intern Med, November 1, 2005; 143(9): 639 - 647. [Abstract] [Full Text] [PDF]

				L. Hong, S. M. Levy, J. J. Warren, D. V. Dawson, G. R. Bergus, and J. S. Wefel Association of Amoxicillin Use During Early Childhood With Developmental Tooth Enamel Defects Arch Pediatr Adolesc Med, October 1, 2005; 159(10): 943 - 948. [Abstract] [Full Text] [PDF]

				R D Ampon, M Williamson, P K Correll, and G B Marks Impact of asthma on self-reported health status and quality of life: a population based study of Australians aged 18-64 Thorax, September 1, 2005; 60(9): 735 - 739. [Abstract] [Full Text] [PDF]

				M. C. Beach, J. Sugarman, R. L. Johnson, J. J. Arbelaez, P. S. Duggan, and L. A. Cooper Do Patients Treated With Dignity Report Higher Satisfaction, Adherence, and Receipt of Preventive Care? Ann. Fam. Med, July 1, 2005; 3(4): 331 - 338. [Abstract] [Full Text] [PDF]

				R. J. Hancox, B. J. Milne, and R. Poulton Association of Television Viewing During Childhood With Poor Educational Achievement Arch Pediatr Adolesc Med, July 1, 2005; 159(7): 614 - 618. [Abstract] [Full Text] [PDF]

				A. C. Celi, J. W. Rich-Edwards, M. K. Richardson, K. P. Kleinman, and M. W. Gillman Immigration, Race/Ethnicity, and Social and Economic Factors as Predictors of Breastfeeding Initiation Arch Pediatr Adolesc Med, March 1, 2005; 159(3): 255 - 260. [Abstract] [Full Text] [PDF]

				B. K. Nallamothu, S. Saint, T. P. Hofer, S. Vijan, K. A. Eagle, and S. J. Bernstein Impact of Patient Risk on the Hospital Volume-Outcome Relationship in Coronary Artery Bypass Grafting Arch Intern Med, February 14, 2005; 165(3): 333 - 337. [Abstract] [Full Text] [PDF]

				K. M. Rose, A. P. Carson, C. P. Sanford, P. E. Stang, C. A. Brown, A. R. Folsom, and M. Szklo Migraine and other headaches: Associations with Rose angina and coronary heart disease Neurology, December 28, 2004; 63(12): 2233 - 2239. [Abstract] [Full Text] [PDF]

				Y. S Hannestad, R. T. Lie, G. Rortveit, and S. Hunskaar Familial risk of urinary incontinence in women: population based cross sectional study BMJ, October 16, 2004; 329(7471): 889 - 891. [Abstract] [Full Text] [PDF]

				M. Silverstein, C. Mack, N. Reavis, T. D. Koepsell, G. S. Gross, and D. C. Grossman Effect of a Clinic-Based Referral System to Head Start: A Randomized Controlled Trial JAMA, August 25, 2004; 292(8): 968 - 971. [Abstract] [Full Text] [PDF]

				S. Greenland Model-based Estimation of Relative Risks and Other Epidemiologic Measures in Studies of Common Outcomes and in Case-Control Studies Am. J. Epidemiol., August 15, 2004; 160(4): 301 - 305. [Abstract] [Full Text] [PDF]

				W. C. Miller, C. A. Ford, M. Morris, M. S. Handcock, J. L. Schmitz, M. M. Hobbs, M. S. Cohen, K. M. Harris, and J. R. Udry Prevalence of Chlamydial and Gonococcal Infections Among Young Adults in the United States JAMA, May 12, 2004; 291(18): 2229 - 2236. [Abstract] [Full Text] [PDF]

				G. Zou A Modified Poisson Regression Approach to Prospective Studies with Binary Data Am. J. Epidemiol., April 1, 2004; 159(7): 702 - 706. [Abstract] [Full Text] [PDF]

				P. Cummings RE: "ESTIMATING THE RELATIVE RISK IN COHORT STUDIES AND CLINICAL TRIALS OF COMMON OUTCOMES" Am. J. Epidemiol., January 15, 2004; 159(2): 213 - 213. [Full Text] [PDF]

				L.-A. McNutt, C. Wu, X. Xue, and J. P. Hafner THE AUTHORS REPLY Am. J. Epidemiol., January 15, 2004; 159(2): 214 - 215. [Full Text] [PDF]

				J. A. Deddens and M. R. Petersen RE: "ESTIMATING THE RELATIVE RISK IN COHORT STUDIES AND CLINICAL TRIALS OF COMMON OUTCOMES" Am. J. Epidemiol., January 15, 2004; 159(2): 213 - 214. [Full Text] [PDF]

				J. Page and J. Attia Using Bayes' nomogram to help interpret odds ratios Evid. Based Med., September 1, 2003; 8(5): 132 - 134. [Full Text] [PDF]

This Article Abstract FREE Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in ISI Web of Science Similar articles in PubMed Alert me to new issues of the journal Add to My Personal Archive Download to citation manager Search for citing articles in: ISI Web of Science (190) Request Permissions Disclaimer Google Scholar Articles by McNutt, L.-A. Articles by Hafner, J. P. Search for Related Content PubMed PubMed Citation Articles by McNutt, L.-A. Articles by Hafner, J. P. Social Bookmarking          What's this?

Online ISSN 1476-6256 - Print ISSN 0002-9262

Copyright © 2009 Johns Hopkins Bloomberg School of Public Health

Oxford Journals Oxford University Press

• Site Map
• Privacy Policy
• Frequently Asked Questions

Other Oxford University Press sites: Oxford University Press Oxford Journals China Oxford Journals Japan American National Biography Booksellers' Information Service Children's Fiction and Poetry Children's Reference Corporate & Special Sales Dictionaries Dictionary of National Biography Digital Reference English Language Teaching Higher Education Textbooks Humanities International Education Unit Law Medicine Music Online Products Oxford English Dictionary Reference Rights and Permissions Science School Books Social Sciences Very Short Introductions World's Classics