Epidemiology: An IntroductionAcross the last forty years, epidemiology has developed into a vibrant scientific discipline that brings together the social and biological sciences, incorporating everything from statistics to the philosophy of science in its aim to study and track the distribution and determinants of health events. A now-classic text, the second edition of this essential introduction to epidemiology presents the core concepts in a unified approach that aims to cut through the fog and elucidate the fundamental concepts. Rather than focusing on formulas or dogma, the book presents basic epidemiologic principles and concepts in a coherent and straightforward exposition. By emphasizing a unifying set of ideas, students will develop a strong foundation for understanding the principles of epidemiologic research. |
From inside the book
Results 1-5 of 36
Page 2
... women in the survey, almost half were smokers. Oddly, proportionately fewer of the smokers died during the ensuing 20 years than nonsmokers. The data are reproduced in Table 1–1. Only 24% of the women who were smokers at the time of the ...
... women in the survey, almost half were smokers. Oddly, proportionately fewer of the smokers died during the ensuing 20 years than nonsmokers. The data are reproduced in Table 1–1. Only 24% of the women who were smokers at the time of the ...
Page 3
... women who were smokers fared better than women who were not smokers? Not necessarily. One difficulty that many researchers quickly spot is that the smoking information was obtained only once, at the start of the follow-up period ...
... women who were smokers fared better than women who were not smokers? Not necessarily. One difficulty that many researchers quickly spot is that the smoking information was obtained only once, at the start of the follow-up period ...
Page 4
... Women in Whickham, England, According to Smoking Status at the Beginning of the Period, by Age Smoking Age Vital Status Yes No Total 18–24 Dead Alive Risk 2 53 0.04 1 61 0.02 3 114 0.03 25–34 Dead Alive Risk 3 121 0.02 5 152 0.03 8 273 ...
... Women in Whickham, England, According to Smoking Status at the Beginning of the Period, by Age Smoking Age Vital Status Yes No Total 18–24 Dead Alive Risk 2 53 0.04 1 61 0.02 3 114 0.03 25–34 Dead Alive Risk 3 121 0.02 5 152 0.03 8 273 ...
Page 14
... women, for if pregnant they easily miscarry and expel the fetus prematurely and in consequence incur many ailments later on. It follows that women weavers, I mean those who are engaged wholly in this occupation, ought to be particularly ...
... women, for if pregnant they easily miscarry and expel the fetus prematurely and in consequence incur many ailments later on. It follows that women weavers, I mean those who are engaged wholly in this occupation, ought to be particularly ...
Page 16
... women admitted to the first clinic but less than 4% in the second clinic, where the midwives trained. Almost all maternal deaths were from puerperal fever. The mortality rate was so high in the first clinic that women 16 EPIDEMIOLOGY.
... women admitted to the first clinic but less than 4% in the second clinic, where the midwives trained. Almost all maternal deaths were from puerperal fever. The mortality rate was so high in the first clinic that women 16 EPIDEMIOLOGY.
Contents
1 | |
8 | |
3 What Is Causation? | 23 |
4 Measuring Disease Occurrence and Causal Effects | 38 |
5 Types of Epidemiologic Studies | 69 |
6 Infectious Disease Epidemiology | 110 |
7 Dealing with Biases | 124 |
8 Random Error and the Role of Statistics | 148 |
9 Analyzing Simple Epidemiologic Data | 164 |
10 Controlling Confounding by Stratifying Data | 176 |
11 Measuring Interactions | 198 |
12 Using Regression Models in Epidemiologic Analysis | 211 |
13 Epidemiology in Clinical Settings | 235 |
Appendix | 254 |
Index | 257 |
Other editions - View all
Common terms and phrases
age categories approach asbestos bare-metal stents biologic interaction birth order breast cancer calculated case-cohort study case-control study causal mechanism Chapter cholera clinical cohort study compared component causes confidence interval confounding factor control confounding control series curve data in Table denominator described drug-eluting stent epidemic epidemiologic epidemiologic study evaluation example experiment exposed and unexposed Figure flutamide follow-up incidence proportion incidence rate ratio induction infection influenza investigator matching measure misclassification mortality rate nonsmokers null hypothesis obtain occur odds ratio outbreak outcome P-value P-value function patients period person person-time person-years placebo population at risk predicted prevalence prevent confounding propensity score random assignment randomized trial rate difference rate ratio regression model relation reproductive number result risk data risk difference risk factor risk of death risk ratio sampling selection bias significance testing source population specific standard statistical significance strata stratified analysis subjects Suppose tion tolbutamide treatment unexposed group vaccine variable women