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Tying it All Together: Examples of

Logistic Regression and Some Loose

Ends

John McGready

Johns Hopkins University

Lecture Topics

Examples for PH literature

Different presentation styles for results from LR

Logistic regression and case control studies

Summary

3

Examples from the Literature

Section A

Example of Logistic Regression

Predictors of Injury among Adult Recreational In-line

Skaters: A Multi-City Study

   Seldes, et al. (1999), AJPH , Vol. 89: 238–241

5

Objectives

“We conducted a cross-sectional survey of adult recreational skaters in six major cities in the U.S. to identify risk factors for injury from in-line skating, [to] estimate the prevalence of such injuries, and [to] describe the use of safety gear and skating habits of this population.”

6

Methods

“Unadjusted odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for all variables of interest.”

“Logistic regression models included all variables that were statistically significant in unadjusted analyses, were considered clinically important based on a priori hypotheses, or whose addition to the models substantially changed the estimates of the effect of other factors.”

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Results

Continued 8

Results

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Results

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Results

11

Authors’ Conclusions

“The results from this large survey indicate that skating location, performing tricks while skating, and skating more hours per week are significant predictors of injury from in-line skating.”

12

Example of Logistic Regression

Increased Cesarean Section Rates and Emergency Patterns of Health Insurance in Shanghai, China

   Cai, et al., AJPH , 1998, 88: 777–780

13

Objectives

“This study examined the trend in cesarean section deliveries and the factors associated with it in the

Minhang District of Shanghai, China.”

“This study analyzed the data from 1,959 married women of reproductive age with at least one live birth.”

14

Methods

“To determine the independent effects of variables on a woman’s likelihood of having a cesarean section, we performed a series of logistic regression analyses for the births that occurred from 1988 through 1993. . . .”

Continued 15

Methods

“. . . In these analyses, the method of delivery was treated as the dependent variable and the factors described earlier as independent variables.”

“Variables that no longer remained significant, after other variables were controlled for, were not included in the final model.”

16

Results

Continued 17

Results

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Results

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Results

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Results

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Footnote details reference groups and units for continuous predictors

Results

Continued 22

Footnote details reference groups and units for continuous predictors

Results

Continued 23

Footnote details reference groups and units for continuous predictors

Results

Continued 24

Footnote details reference groups and units for continuous predictors

Results

Continued 25

Results

“During the past three decades, the proportion of infants born by cesarean section increased from 4.7% to 22.5%.”

“Logistic regression analysis revealed that the highest cesarean section rate, which occurred in the most recent period of 1988 through 1993, was associated with the form of medical payment. . . .”

Continued 26

Results

“. . . self-reported complications during pregnancy, higher birth weight, and maternal age.”

“Government insurance pays all costs of cesarean sections and accounted for the highest proportion of the cesarean section rate.”

Continued 27

Results

“The high rates of cesarean sections in China are surprising given the lack of the factors that usually lead to cesarean sections.”

“The increasing cesarean section rates may be an early indication that emerging forms of health insurance and fee-for-service payments to physicians will lead to an excessive emphasis on costly, high-technology medical care in China.”

28

Another Example

Teenage Smoking, Attempts to Quit, and School

Performance

   Hu, et al. (1998), AJPH , 88: 940–943

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Objective

“This study examined the relationship between school performance, smoking, and quitting attempts among teenagers.”

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Methods

“A logistic regression model was used to predict the probability of being a current smoker or a former smoker.”

“Data were derived from the 1990 California Youth

Tobacco Survey.”

31

Results

 Notes Available Continued 32

Results

 Notes Available Continued 33

Results

 Notes Available Continued 34

Results

 Notes Available Continued 35

The footnote holds the keys to interpreting

Results

Continued 36

Results

 Notes Available Continued 37

The footnote holds the keys to interpreting

Results

38

Conclusion

“Developing academic or remedial classes designed to improve students’ school performance may lead to a reduction in smoking rates among teenagers while simultaneously providing a human capital investment in their futures.”

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