Community Health and Epidemiology Paper

Tami L. Thomas, PhD, RN, CPNP, FAANP, FAAN,
Safiya George Dalmida, PhD, APRN-BC, FAANP,
A. Hunter Threadgill, PhD, and Stephen Ungvary, PhD, SKIM
Abstract: Purpose: Examine sexual health beliefs, sexual experiences and young adults’ experience with H PV vac­
cine series completion. Method: Anonymous data was collected on approximately 1768 young people attending an
urban university in the southeastern United States from 2012-14. Binary logistic regression examined predictors
of H PV vaccination and significant demographic variables. Results: Logistic regression results showed that gender,
ethnicity, perceived barriers, perceived benefits, condom use self-efficacy related to partner disapproiml and condom
use consistency significantly predicted H PV vaccination intention. These results inform research and practice where
cultural diversity is key to implementing health programs, policy formulation and the pursuit of research.
Key Words: Beliefs; Health Habits; H P V Vaccination
B eliefs, H ealth H abits, and
H P V V accination
in t r o d u c t io n
was licensed for use in females ages 9-26 and males ages
9-15 and provides the same protection against HPV 6,11,
16 and 18 with additional protection against HPV 31,33,
45, 52 and 58 (Administration, 2014a). At the February
meeting of the ACIP, Gardasil 9 received full committee
approval.
Unfortunately, in the 12 years following the recom­
m endations of June of 2006, HPV immunization comple­
tion has remained well below the projected rates of 90
percent for both males (less than 21%), females (less than
60%), and, most alarming among ethnic minority groups
(CDC, 2011) (Pierre Joseph et al., 2014). In the United
States, the incidence and mortality rates of HPV related
cancer is m uch higher in African Americans (25% and
95% ) and Hispanics (53% and 41%) compared to Cauca­
sians and this persists into the second decade since HPV
vaccine approval for both males and females (Jemal, 2013;
Wilson, 2015). The concern regarding increasing rates of
HPV related cancers has been the subject of num erous
studies; even the 2014 President’s Cancer Panel (PCP)
m ade low rates of HPV vaccine series completion a focus
of concern and an action priority for 2015 (Azvolinsky,
2013; Simon, 2014).
The purpose of this study was to examine the sexual
health beliefs, sexual experiences and young adults’ ex­
perience with HPV vaccine series completion associated
with intention to receive the HPV vaccine. Data presented
from this study elucidates these phenomena and informs
cultural approaches to increasing HPV vaccine series
completion.
Persistently low completion rates can be attributed to
the gaps in scientific evidence for effective and culturally
competent interventions intended to increase HPV vac­
cinations should focus on cancer prevention rather than
STD prevention (Bednarczyk, Davis, Ault, Orenstein, &
Omer, 2012; Das et al., 2010; Thomas, Strickland, Dicle-
n 2006, the Food and Drug Adm inistration (FDA) ap­
proved the H um an Papillomavirus (HPV) vaccine for
females and the Advisory Committee for Imm uniza­
tion Practices (ACIP) followed with recommendations
for providers soon afterward (Prevention, 2010). In 2009,
the same vaccine was approved for use in males, again
followed by ACIP recommendations for males to be vac­
cinated with the quadrivalent HPV vaccine between the
ages of 11 to 26 (Prevention, 2010). Unfortunately, in 2018
rates of HPV vaccine series completion continue; and
persistently low rates of vaccine completion translates
into more than 79 million persons currently infected and
approximately 14 million newly infected annually in the
United States (Dunne et al., 2014).
As of February 2015, there was a 9-valent HPV vaccine
that was approved by the FDA and recommended for use
in both males and females (Administration, 2014a; Joura
et al., 2015). This new vaccine, also known as Gardasil 9,
I
Tami L. Thomas, PhD, RN, APRN-CPNP, FAANP,
FAAN, corresponding author, is Professor and Associate
Dean, Research, Faculty Development and PhD Program
Director in the Nicole Wertheim College of Nursing &
Health Sciences at Florida International University in
Miami, Florida. Dr. Thomas is a Robert Wood Johnson
Foundation Nursing Faculty Scholar Alumna and may be
reached at: E-mail: tthomas@fiu.edu; Telephone: 305-3487718; and twitter@ DOCTHOMAS58. Safiya George
Dalm ida, PhD, APRN-BC, FAANP teaches at the
University of Alabama. A. Hunter Threadgill, PhD is a
Postdoctoral Fellow at Florida State University. Stephen
Ungvary, PhD, SKIM is a Senior Research Analyst at the
University of Alabama.
Journal of Cultural Diversity • Vol. 26, No.4
cpp
Winter 2019
mente, & Higgins, 2013). There is a dearth of information
about HPV vaccine series completion and the culturally
specific attitudes toward it in young people whom selfidentify from racial/ethnic m inority communities. But
research findings reveal that cultural barriers can be ad­
dressed w ith tailored information aimed at specific ethnic
minority groups (Marlow, 2009). Data generated from a
study exploring these specific ethnic minority groups of
young adults, could provide more accurate and effective
intervention points to increase HPV vaccine series initiation
and also improve completion. Examine the sexual health
beliefs, sexual experiences and experience with HPV vac­
cine series completion in young adults four years after
HPV vaccine approval for both males and females.
The FDA approved 9-valent HPV vaccine, also known
as Gardasil 9, was licensed for use in females ages 9-26 and
males ages 9-15 and provides the same protection against
HPV 6,11,16 & 18 w ith additional protection against HPV
31,33,45,52 and 58 (Administration, 2014b). At the Febru­
ary 2015 meeting of the Advisory Council on Imm uniza­
tion Practice, Gardasil 9 received full committee approval
as the Gardasil 9 vaccine has a 97% efficacy compared to
the original Gardasil and also protects against more HPVrelated cancers for both females and males (Walker, 2015).
A systematic review by the Cochrane Collaboration in
2013 examined randomized controlled trials for the efficacy
of face-to-face interventions used for educating parents and
patients about vaccinations. Most recently in 2014, Fu and
colleagues conducted a systematic review of educational
interventions to increase HPV vaccination acceptance (Fu,
Bonhomme, Cooper, Joseph, & Zimet, 2014). They also
concluded that more studies are required to determine the
potential successfulness of culturally competent interven­
tions reaching diverse populations (Fu et ah, 2014).
The purpose of this study was to examine students’
sexual health beliefs, experiences and, most specifically,
their completion of the HPV vaccine series in the proceed­
ing years after the vaccine was approved for both males and
females. The hope was that data generated from a study
exploring the obstacles that arise from cultural influences
could provide possible intervention points to increase HPV
vaccine series initiation and also improve completion.
METHOD
Procedure
In 2013, w hen the HPV vaccine had been approved
for both males and females for over 4 years, a descriptive
project was conducted on a large urban university with an
ethnically diverse student enrollment of mostly Hispanic
and African Caribbean students. This research used an
exploratory design to determine correlates of HPV vac­
cine completion and behaviors that promote health for
individuals in this age group. After Institutional Review
Board (IRB) approval, a convenience sample of 1768 college
students was targeted for recruitment through the Depart­
m ent of Psychology research pool. In order to provide
information about the purpose, goals and eligibility for
participation in the study, an IRB approved announcement
(online information email) was dispersed to prospective
participants. Inclusion criteria were limited to anyone who
could read English. There was limited risk and no informa­
tion was obtained from a database or archive. Participants
were asked to provide confidential information about their
sexual health and HPV vaccine series completion using
an anonymous online survey, which took approximately
45 minutes to complete. There were no identifiers to link
responses to participants. If at any point in the participants
w anted to stop participating or did not w ant to answer
particular questions, they could choose to do so. As all
participation was voluntary, those who declined were not
penalized in any way. All anonymous survey data was
Table 1. Sample Demographic Descriptive Statistics
Variable
Age
Years lived in the United States
# of sexual partners in the last 12 months
# times used alcohol and engaged in sex
# times consumed 5 drinks or more at once
# of times drank alcohol in past 2 weeks
Student HPV Survey
HPV T o ta l- 1 3 Item
Perceived Vulnerability & Severity
Perceived Benefits
Perceived Barriers
MEIM
MEIM Mean
Commitment
Ethnic Identity Search
CUSE Scale
CUSES Total
Mechanics
Partner Disapproval
Assertive
Intoxicants
Journal of Cultural Diversity • Vol. 26, No.4
Mean
SD
Min
Max
22.50
17.54
1.55
3.89
8.67
2.11
5.16
1.89
10.86
24.60
18
0
0
0
0
29
28
20
111
400
1.49
2.12
0
28
__
Alpha
—
-—
—
—
41.84
32.58
24.78
15.73
5.54
4.70
3.54
3.07
21
10
8
7
52
44
32
32
.703
.593
.492
.525
2.02
1.81
2.32
0.49
0.53
0.56
1
1
1
4
4
4
.891
.900
.732
12.63
2.06
2.43
1.47
2.85
9.56
2.16
3.27
1.88
2.50
0
0
0
0
0
56
12
18
12
12
.916
.596
.848
.631
.819
Winter 2019
Table 2. Socio-Demographic Characteristics
Variable
Gender/Sex
Male
Female
Racial Identity
Black/African descent
Hispanic/Latin American
W hite non-Hispanic/Caucasian
Indigenous/Native American or Asian
Other
Ethnicity
Hispanic/Latino
Non-Hispanic
Class Standing
Freshman
Sophomore
Junior
Senior
Grad Student
Other
Is a Parent (has a child/children)
Yes
No
Relationship status
Single
In committed relationship/Engaged/Married
Previously received FIPV Vaccine
No
Not sure
Yes
Yes- but did not complete the series
Sexual Orientation
Gay or Lesbian/Homosexual
Bisexual
Straight/Heterosexual
Other
Previous History of or Current Evaluation for STI
Chlamydia
Gonorrhea
Herpes
HPV
Yeast infection
Bacterial Vaginosis
None
Frequency of condom use
Never or inconsistent condom use
Always consistent condom use
Intent to vaccinate
No
Yes
If choose not to vaccinate, reasons why
Cost
Time
Don’t know where to get vaccine
Don’t know what the vaccine is
Importance of someone to discuss health issues
Extremely Important
Very Important
Neither Important nor Unimportant
Unimportant
Journal of Cultural Diversity • Vol. 26, No.4
n
%
461
887
34.2
65.8
165
937
152
47
47
12.2
69.5
11.3
3.5
3.5
937
411
69.5
30.5
400
220
393
319
4
12
29.7
16.3
29.2
23.7
0.3
0.9
36
1312
2.7
97.3
652
696
48.4
51.6
436
382
456
74
32.3
28.3
33.8
5.5
52
54
1225
17
3.9
4.0
90.9
1.3
33
7
14
41
135
51
1057
2.4
0.5
1.0
3.0
10.0
3.8
78.4
952
396
70.6
29.4
329
1019
24.4
75.6
567
372
262
310
42.1
27.6
19.4
23.0
695
447
174
32
51.6
33.2
12.9
2.3
Winter 2019
downloaded from a locked research lab computer and kept
in a file cabinet accessible by study personnel only.
Participants. A total of 1768 people responded to the
survey, but only participants between the ages of 18 and
29 who had complete data were retained for analyses. The
final sample consisted of 1348 participants. Demographics
data for the final sample are presented in Tables 1 and 2.
Measures
The Student HPV Survey. The Student HPV Survey
(Thomas, Dalmida, S. & Higgins, 2015 ) was designed
to assess respondents’ knowledge of and their attitudes
toward HPV vaccination. The Student HPV Survey is a
27-item measure comprised of 3 subscales. Participants are
asked to respond to each item on a scale from 1 (Disagree) to
4 (Agree). Thirteen HPV Survey items were added together
to create an overall index score (Student HPV Survey Total
-1 3 Items). Subscales were computed by adding together
the items for the following facets: Perceived Vulnerability
and Perceived Severity (11 items), Perceived Benefits (8
items) and Perceived Barriers (8 items). Higher scores
indicate higher self-efficacy related to HPV vaccination.
Condom use. The Condom Use Self-Efficacy Scale
(CUSES) was used to assess participants’ beliefs about
and usage of condoms (Brafford, 1991). The CUSES is a
27-item measure comprised of 4 of subscales. Participants
respond to each item on a scale from 1 (Strongly Disagree) to
5 (Strongly Agree). All CUSES items were averaged together
to create an overall index score (CUSES Total). Subscales
were computed by averaging together the items for the fol­
lowing facets: Mechanics (# items), Partner Disapproval (#
items), Assertive (# items) and Intoxicants (# items). Higher
scores indicate higher self-efficacy related to condom use.
Ethnic Identity. The Multigroup Ethnic Identity Mea­
sure (MEIM) was designed to assess identity development
and identity statuses of racial/ethnic minority individu­
als (Chakawa, Butler, & Shapiro, 2015). The CUSES is a
12-item measure comprised of 2 of subscales. Participants
responded to each item on a scale from 1 (Strongly Agree)
to 4 (Strongly Disagree). All MEIM items were averaged
together to create an overall index score (MEIM Total).
Additionally, seven of the items were averaged together
to create a “Commitment” subscale, and five items were
added together to create a “Ethnic Identity Search” sub­
scale. Higher scores indicate low identity development and
identity status.
ANALYSIS
All data were analyzed using IBM SPSS software pack­
age version 23. A total of 1768 participants completed the
study. Due to the age-specific nature of the HPV vaccine,
we limited analysis to data from participants between the
ages of 18 and 29. Additionally, participants who did not
have complete data used in analyses were removed. This
left us with a final sample size of 1348.
The following variables were dummy-coded for analy­
sis: gender (0 = Female, 1 = Male), ethnicity (0 = Hispanic/
Latino, 1 = non-Hispanic), relationship status (0 = Single,
1 = In a Relationship/Engaged/Married), parental status
(0 = No children, 1 = Have children), frequency of condom
usage (0 = 70% of the time or less, 1 = Always) and inten­
tion to vaccinate for HPV (Disagree/Somewhat Disagree,
1 = Somewhat Agree / Agree). Associations between social
Journal of Cultural Diversity • Vol. 26, No.4
and demographic factors and HPV vaccination intention
were examined using chi-square analyses. Correlates be­
tween HPV vaccination intention and the Student HPV
Survey, CUSES, and MEIM scores were examined using
Spearman’s rho correlations. Normality was assessed
using Shapiro-Wilk and Kolmogorov-Smirnov normality
tests, histograms and box plots. Binary logistic regression
examined predictors of HPV vaccination intention, while
accounting for demographic variables of interest. The
logistic regression model was used to estimate the factors
that influenced HIV intent to vaccinate. A 5% criterion of
statistical significance was used for all analyses (p < .05). RESULTS Sample demographic and socio-demographics char­ acteristics are presented in Tables 1 and 2. Of particular interest is that 33.8% of participants indicated that they had already received the HPV vaccine. Additionally, 75.6% of participants expressed intention to receive the HPV vac­ cine. Factors Related to HPV Vaccination Intention A series of chi-square analyses revealed that participants who intended to receive the HPV vaccination were signifi­ cantly more likely to be female than male, x2(l) = 32.25, p < .001, and were more likely to use a condom 70% of the time or more frequently than use condoms less frequently or never use condoms, x2(l) = 6.04, p = .014. Additionally, Hispanics were significantly more like to express intention to receive the HPV vaccination than non-Hispanics, x2(l) = 7.36, p = .007. The percentage of participants with an intention to vaccinate did not differ by relationship status (X2(D = 0.24, p =.623), parent status (x2(l) = 0.23, p = .633), racial identity (x2(5) = 8.08, p = .152), class standing (x2(5) = 8.54, p = .129) or successful condom use self-efficacy (x2(l) = 0.53, p = .466). Correlations showed that a number of factors were significantly associated with intentions to vaccinate for HPV (see Table 3). Specifically, intentions to vaccinate were correlated with higher scores on the Student HPV Survey Total scores, as well as the perceived vulnerability Table 3. Spearman's Rho Correlations between Intention to Vaccination and Student HPV Survey, MEIM, and CUSES Variable Student FIPV Survey HPV T otal- 1 3 Item Perceived Vulnerability & Severity Perceived Benefits Perceived Barriers MEIM MEIM Mean Commitment Ethnic Identity Search CUSE Scale CUSES Total Mechanics Partner Disapproval Assertive Intoxicants rs P .33 .21 .35 -.23 < .001 < .001 < .001 < .001 -.08 -.06 -.08 .006 .018 .004 -.09 -.06 -.10 -.08 -.10 .001 .036 < .001 .005 < .001 Winter 2019 Table 4. Logistic Regression Predicting Intention to Vaccinate from Gender, Ethnicity, Condom Use Frequency, the Student HPV Survey Total, and the CUSES Total Predictor Gender Ethnicity Condom Use Frequency Student HPV Total - 13 Item CUSES Total B Wald / 13.60 8.96 5.46 114.64 0.56 0.51 0.43 -0.37 0.15 -0.005 and severity and perceived benefits subscales. However, higher scores on the perceived barriers subscale of the Student HPV Survey, the CUSES (and its subscales), and the MEIM (and its subscales) were linked to intentions to not vaccinate. Predictors of HPV Vaccination Intention Binary logistic regressions were performed to examine predictors of an intention to vaccinate. For all logistic regressions, the effects of gender, ethnicity and condom use frequency were entered as predictors. The first logistic regression also entered the Student HPV Survey Total and CUSES Total as predictors. To explore how each of the subscales predicted intention to vaccinate, a second logistic regression entered each of the Student HPV Survey and CUSES subscales as predictors. For the first logistic regression, results indicated that the logistic regression model was statistically significant, x2(5) = 186.84, p < .001. The model explained 19.3% (Nagelkerke R2) of the variance in intention to vaccinate, exhibited adequate model fit (Hosmer & Lemeshow goodness-of-fit test) and correctly classified 76.6% of the cases. Table 4 shows the logistic regression coefficient, Wald test, and odds ratio for each of the predictors in the first logistic regression. Employing a .05 criterion for statisti­ cal significance, gender, ethnicity, condom use frequency, and the Student HPV Total score all predicted vaccination intentions. Specifically, females were 1.68 times more likely than males to express intention to receive the HPV vaccine. Hispanics were 1.54 times more likely than non-Hispanics to express intention to receive the HPV vaccine. Those P Odds Ratio < .001 .003 .019 < .001 .455 1.68 1.54 0.69 1.16 1.00 who always used condoms were 0.69 times more likely than those who rarely or never used condoms to express intention to receive the HPV vaccine. Finally, a one-point increase in Student HPV Survey Total score increased the odds of expressing intention to receive the HPV vaccine by 1.16. The CUSES Total did not predict intention to vac­ cinate. For the second logistic regression, results indicated that the logistic regression model was statistically signifi­ cant, x2(10) = 242.89, p < .001. The model explained 24.6% (Nagelkerke R2) of the variance in intention to vaccinate, exhibited adequate model fit (Hosmer & Lemeshow goodness-of-fit test) and correctly classified 78.0% of the cases. Table 5 shows the logistic regression coefficient, Wald test and odds ratio for each of the predictors in the second logistic regression. Employing a .05 criterion for statistical significance, gender, ethnicity, condom use frequency and each of the Student HPV subscales predicted vaccination intentions. Specifically, females were 1.70 times more likely than males to express intention to receive the HPV vaccine. Hispanics were 1.47 times more likely than non-Hispanics to express intention to receive the HPV vaccine. Those who always used condoms were 0.68 times more likely than those who rarely or never used condoms to express inten­ tion to receive the HPV vaccine. A one-point increase in the HPV Perceived Vulnerability and Severity and HPV Per­ ceived Benefits increased the odds of expressing intention to receive the HPV vaccine by 1.07 and 1.25, respectively. However, a one-point increase in the HPV Perceived Bar­ riers decreased the odds of expressing intention to receive Table 5. Logistic Regression Predicting Intention to Vaccinate from Gender, Ethnicity, Condom Use Frequency, the Student HPV Survey Subscales, and the CUSES Subscales Odds Ratio B Wald x2 0.53 0.38 -0.39 12.05 6.67 5.74 .001 .010 .017 1.70 1.47 0.68 0.06 0.23 0.02 16.67 98.68 12.29 < .001 < .001 < .001 1.07 1.25 0.92 Mechanics 0.04 0.24 .625 1.02 Predictor Gender Ethnicity Condom Use Student HPV Perceived Perceived Perceived CUSE Scale Frequency Survey Vulnerability & Severity Benefits Barriers P Partner Disapproval 0.03 2.07 .151 1.04 Assertive 0.05 0.008 .928 1.00 Intoxicants 0.03 1.62 .203 0.68 Journal of Cultural Diversity • Vol. 26, No.4 Winter 2019 the HPV vaccine by 0.92. None of the CUSES subscales predicted intention to vaccinate. DISCUSSION Results from this study provide needed information regarding beliefs, health habits and HPV vaccination in young adults. Our findings substantiate research in young adult populations with varied gender and socioeconomics and further indicate a need for improved communication regarding HPV as levels of knowledge and understanding (Unger, 2015). Overall knowledge of HPV was low even though there was an awareness of the vaccine and other studies substantiate that young adults in the United States know little about transmission, treatment or long-term sequelae such as cancer (Marlow, 2013). In addition, our data also substantiates other research that implies educa­ tion and information on HPV transmission and subsequent HPV vaccination rates are much lower in the southern United States (Rahman, 2015). As such, efforts to educate patients, providers and communities are imperative. Other important points of intervention were identified regarding gender, ethnicity and safer sexual practices. Research on HPV vaccination and gender over the last ten years has provided fairly consistent data with our results. Females in our study were more likely to report vaccina­ tion against HPV and intentions to receive the HPV vac­ cine compared to males. Nonetheless, our results support findings from other studies that encourage future studies focused on both sexes / males and females to support effec­ tive HPV vaccine completion because it is lowest among males (Newman, 2013; Rahman, 2015). Current research findings imply a gender gap in beliefs, health habits and HPV knowledge and our results sub­ stantiate these findings (Thomas et al., 2013). Men with less HPV knowledge have been shown to have higher levels of shame and to be less likely to engage in preventive health behaviors such as vaccination (Gerend & Magloire, 2008). Further, research suggests that HPV vaccine acceptability may be even lower among males from ethnic minorities, such as Latino cultural sub-groups and geographically isolated areas (Thomas, Higgins, Stephens, & JohnsonMallard, 2016). Thus, an understanding of the individual's cultural values and norms are crucial in health education regarding health habits and prior to discussing HPV vac­ cination. Since 2007, scientific evidence has shown that, despite the ongoing argument that it encourages promiscuous behavior; the HPV vaccine does not promote sexual risk­ taking (Bednarczyk et al., 2012; Gattoc, Nair, & Ault, 2013; Stewart, 2007). And yet, encouraging the health promoting use of condoms in the same breath is apt to send mixed messages. The best approach to ensure understanding in­ stead of confusion when discussing the HPV vaccine is for nurses to point out that vaccination neither condones nor leads to sexual activity as indicated by Liddon et al. (2011). Once it has been established that there is no correlation between vaccine administration and risk-taking behavior, the next important research step is to test interventions to integrate learning for providers, practice staff at clinics who serve young adults and these potential patients. Learning to incorporate these intervention points will likely lead to an increase HPV knowledge, motivation and behavioral skills to overcome barriers to HPV vaccine series initiation. Journal of Cultural Diversity • Vol. 26, No.4 CONCLUSIONS More studies are required to determine the potential intervention points to deliver culturally appropriate mes­ sages and culturally competent interventions reaching diverse populations in relation to beliefs, health habits and HPV vaccination (Fu et al., 2014). Establishing a good line of communication is the first and most important step to an effective healthcare provider/patient relationship. Fostering an environment of respect without judgment must be a priority before any healthcare discussion begins as research has shown that, without clear and open com­ munication, misinformation is extremely likely (Wilson, 2015). It is also crucial that providers and clinical practice staff familiarize themselves with up-to-date research and information concerning the HPV vaccine so that they can be the best possible resource of health promotion and cancer prevention for their patients (Thomas, 2008). Once trust is established, any interdisciplinary team of health providers may also encourage young adults to be vaccinated and complete the series, especially those culturally diverse groups that may be suffering from health disparities, such as ethnic minorities or those in geographically isolated communities or economically disadvantaged. As healthcare professionals, it is imperative that we help patients to see the HPV vaccine in the same light as the Hepatitis B series vaccine or recommended Tdap or Meningococcal vaccine: it is a normal and routine part of health promotion. The HPV vaccine is a health care innovation that can be recommended in many settings. Interdisciplinary teams focused on health and well-being of young adults can use the identified intervention points to provide individuals a future free of cancer. With these re­ sults, HPV focused studies concerning knowledge, gender, culturally-specific language, and approaches that embrace cultural diversity can lead to a HPV -related cancer free future for young adults. REFERENCES Administration, U. S. F. a. D. (2014a). FDA approves Gardasil 9 for prevention of certain cancers caused by five additional types of HPV. In U. S. D. o. H. a. H. Services (Ed.), FDA News Release (pp. 2). Silver Spring, MD U.S. Food and Drug Administration Administration, U. S. F. a. 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Vaccine, 32(17), 19011920. dokhttp://dx.doi.org/10.1016/j.vaccine.2014.01.091 Gattoc, L., Nair, N., & Ault, K. (2013). Hum an papillomavirus vaccination: current indications and future directions. Obstet Gynecol Clin North Am, 40(2), 177-197. doi:10.1016/j. ogc.2013.03.007 Gerend, M. A., & Magloire, Z. F. (2008). Awareness, knowledge, and beliefs about hum an papillomavirus in a racially diverse sample of young adults. J Adolesc Health, 42(3), 237-242. Jemal, A. S., EP, Dorell, C. (2013). Annual Report to the Nation on the Status of Cancer 1975-2009, featuring the burden and trendsin hum an papillom avirus (HPV)-asociated cancers and HPV vaccination coverage. Journal of the National Cancer Institute, 105(175). Joura, E. A., Giuliano, A. R., Iversen, O. E., Bouchard, C., Mao, C., MeJilsen, J.,... Broad Spectrum, H. P. V. V. S. (2015). A 9-valent HPV vaccine against infection and intraepithelial neoplasia in women. N Engl ] Med, 372(8), 711-723. doi:10.1056/NEJMoal405044 Marlow, L. A., Wardle, J., Forster, A.S. & Waller, J .. (2009). Ethnic differences in hum an papillomavirus awareness and vaccine acceptability Journal of Epidemiology and Coommunity Health 2009(63), 1010-1015. Marlow LAV, Z. G., McCaffery KJ, Ostini R, Waller J. . (2013). Knowledge of hum an papillom avirus (HPV) and HPV vac­ cination: An international comparison. Vaccine, 31, 763-769. Newman, P. A. L., C.H.; Doukas, N. & Asakura, K. . (2013). HPV vaccine acceptability among men: a systematic review and meta-analysis. Sexually Transmitted Infections, 2013(89), 568-574. Pierre Joseph, N., Clark, J. A., Mercilus, G., Wilbur, M., Figaro, J., & Perkins, R. (2014). Racial and ethnic differences in HPV knowledge, attitudes, and vaccination rates among lowincome African-American, Haitian, Latina, and Caucasian young adult women. ] Pediatr Adolesc Gynecol, 27(2), 83-92. doi:10.1016/j.jpag.2013.08.011 Prevention, C. f. D. C. a. (2010). 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Production Credits Publisher: Michael Brown Managing Editor: Maro Gartside Editorial Assistant: Kayla Dos Santos Editorial Assistant: Chloe Falivene Production Assistant: Alyssa Lawrence Senior Marketing Manager: Sophie Fleck Teague Manufacturing and Inventory Control Supervisor: Amy Bacus Composition: diacriTech Cover Design: Kristin E. Parker Cover Image: © W7/ShutterStock, Inc. Printing and Binding: Edwards Brothers Malloy Cover Printing: Edwards Brothers Malloy To order this product, use ISBN: 978-1-4496-6549-4 Library of Congress Cataloging-in-Publication Data Friis, Robert H. Epidemiology for public health practice / Robert H. Friis and Thomas Sellers.—5th ed. p. ; cm. Includes bibliographical references and index. ISBN 978-1-4496-5158-9 (pbk.) I. Sellers, Thomas A. II. Title. [DNLM: 1. Epidemiology. 2. Epidemiologic Methods. 3. Public Health. WA 105] 614.4—dc23 2012039130 6048 Printed in the United States of America 17 16 15 14 13 10 9 8 7 6 5 4 3 2 1 Contents New to This Edition Introduction Preface Acknowledgments About the Authors Chapter 1 History and Scope of Epidemiology Introduction Epidemiology Defined Foundations of Epidemiology Historical Antecedents of Epidemiology Recent Applications of Epidemiology Conclusion Study Questions and Exercises References Chapter 2 Practical Applications of Epidemiology Introduction Applications for the Assessment of the Health Status of Populations and Delivery of Health Services Applications Relevant to Disease Etiology Conclusion Study Questions and Exercises References Chapter 3 Measures of Morbidity and Mortality Used inEpidemiology Introduction Definitions of Count, Ratio, Proportion, and Rate Risk Versus Rate; Cumulative Incidence Interrelationship Between Prevalence and Incidence Applications of Incidence Data Crude Rates Specific Rates and Proportional Mortality Ratio Adjusted Rates Conclusion Study Questions and Exercises References Chapter 4 Descriptive Epidemiology: Person, Place, Time Introduction Characteristics of Persons Characteristics of Place Characteristics of Time Conclusion Study Questions and Exercises References Appendix 4—Project: Descriptive Epidemiology of a Selected Health Problem Chapter 5 Sources of Data for Use in Epidemiology Introduction Criteria for the Quality and Utility of Epidemiologic Data Online Sources of Epidemiologic Data Confidentiality, Sharing of Data, and Record Linkage Statistics Derived from the Vital Registration System Reportable Disease Statistics Screening Surveys Disease Registries Morbidity Surveys of the General Population Insurance Data Clinical Data Sources Absenteeism Data School Health Programs Morbidity in the Armed Forces: Data on Active Personnel and Veterans Other Sources: Census Data Conclusion Study Questions and Exercises References Chapter 6 Study Designs: Ecologic, Cross-Sectional, Case-Control Introduction Observational Versus Experimental Approaches in Epidemiology Overview of Study Designs Used in Epidemiology Ecologic Studies Cross-Sectional Studies Case-Control Studies Conclusion Study Questions and Exercises References Chapter 7 Study Designs: Cohort Studies Introduction Cohort Studies Defined Sampling and Cohort Formation Options Temporal Differences in Cohort Designs Practical Considerations Measures of Effect: Their Interpretation and Examples Summary of Cohort Studies Conclusion Study Questions and Exercises References Chapter 8 Experimental Study Designs Introduction Hierarchy of Study Designs Intervention Studies Clinical Trials Community Trials Conclusion Study Questions and Exercises References Chapter 9 Measures of Effect Introduction Absolute Effects Relative Effects Statistical Measures of Effect Evaluating Epidemiologic Associations Models of Causal Relationships Conclusion Study Questions and Exercises References Appendix 9—Cohort Study Data for Coffee Use and Anxiety Chapter 10 Data Interpretation Issues Introduction Validity of Study Designs Sources of Error in Epidemiologic Research Techniques to Reduce Bias Methods to Control Confounding Bias in Analysis and Publication Conclusion Study Questions and Exercises References Chapter 11 Screening for Disease in the Community Introduction Screening for Disease Appropriate Situations for Screening Tests and Programs Characteristics of a Good Screening Test Evaluation of Screening Tests Sources of Unreliability and Invalidity Measures of the Validity of Screening Tests Effects of Prevalence of Disease on Screening Test Results Relationship Between Sensitivity and Specificity Evaluation of Screening Programs Issues in the Classification of Morbidity and Mortality Conclusion Study Questions and Exercises References Appendix 11—Data for Problem Chapter 12 Epidemiology of Infectious Diseases Introduction Agents of Infectious Disease Characteristics of Infectious Disease Agents Host The Environment Means of Transmission: Directly or Indirectly from Reservoir Measures of Disease Outbreaks Procedures Used in the Investigation of Infectious Disease Outbreaks Epidemiologically Significant Infectious Diseases in the Community Conclusion Study Questions and Exercises References Appendix 12—Data from a Foodborne Illness Outbreak in a College Cafeteria Chapter 13 Epidemiologic Aspects of Work in the Environment Introduction Health Effects Associated with Environmental Hazards Study Designs Used in Environmental Epidemiology Toxicologic Concepts Related to Environmental Epidemiology Types of Agents Environmental Hazards Found in the Work Setting Noteworthy Community Environmental Health Hazards Conclusion Study Questions and Exercises References Chapter 14 Molecular and Genetic Epidemiology Introduction Definitions and Distinctions: Molecular Versus Genetic Epidemiology Epidemiologic Evidence for Genetic Factors Causes of Familial Aggregation Shared Family Environment and Familial Aggregation Gene Mapping: Segregation and Linkage Analysis Genome-Wide Association Studies (GWAS) Linkage Disequilibrium Revisited: Haplotypes Application of Genes in Epidemiologic Designs Genetics and Public Health Conclusion Study Questions and Exercises References Chapter 15 Social, Behavioral, and Psychosocial Epidemiology Introduction Research Designs Used in Psychosocial, Behavioral, and Social Epidemiology The Social Context of Health Independent Variables Moderating Variables Dependent (Outcome) Variables: Physical and Mental Health Conclusion Study Questions and Exercises References Chapter 16 Epidemiology as a Profession Introduction Specializations within Epidemiology Career Roles for Epidemiologists Epidemiology Associations and Journals Competencies Required of Epidemiologists Resources for Education and Employment Professional Ethics in Epidemiology Conclusion Study Questions and Exercises References Appendix A—Guide to the Critical Appraisal of an Epidemiologic/Public Health Research Article Appendix B—Answers to Selected Study Questions Glossary Index New to This Edition Chapter 1: History and Scope of Epidemiology • • • • • • New and updated images Updated chart: three presentations of epidemiologic data Updated chart: pneumonia and influenza mortality New chart on the interdisciplinary nature of epidemiology Glossary of terms used in the yearly bill of mortality for 1632 Expanded information on cholera and John Snow Chapter 2: Practical Applications of Epidemiology • Updated information on leading causes of death from 1900 to 2009 • Expanded discussion of population dynamics and predictions about the future • More information provided on the health of the community and health disparities, including the GINI index Chapter 3: Measures of Morbidity and Mortality Used in Epidemiology • Expanded coverage of epidemiologic measures (e.g., sex ratios) • More information on prevalence given with figure to show interrelationships between prevalence and incidence • Further clarification of perinatal mortality provided Chapter 4: Descriptive Epidemiology: Person, Place, Time • Updated coverage of morbidity and mortality data by descriptive epidemiologic variables provided throughout the chapter • New examples of case studies and case series • New information on age effects associated with morbidity and mortality • Many new charts added to this chapter • Updates from the 2010 Census, with current definitions of race/ethnicity Chapter 5: Sources of Data for Use in Epidemiology • Updated information on data sources including notifiable diseases • Further clarification of criteria for the quality of epidemiologic data • Rationale strengthened for the need for high-quality epidemiologic data Chapter 6: Study Designs: Ecologic, Cross-Sectional, Case-Control • • • • Clarification regarding design and applications of case-control studies More information on matching in case-control studies Clearer definitions of terms provided Further discussion of comparisons between cross-sectional and casecontrol studies Chapter 7: Study Designs: Cohort Studies • Introduction updated • Additional clarification of terminology used in cohort studies • Exhibit on life table methods updated to the most recent information Chapter 8: Experimental Study Designs • • • • • Expanded coverage of intervention studies Several new images, including an image of a scurvy victim Discussion of phase 4 clinical trials New table and a glossary of terms used in clinical trials Applications of epidemiology to vaccines and prevention: HPV vaccine Chapter 9: Measures of Effect • Introduction revised • STROBE guidelines and quality of epidemiologic studies • Meta-analysis and systematic reviews Chapter 10: Data Interpretation Issues • More information on Simpson’s Paradox, including a new figure • Information bias and screening mammography Chapter 11: Screening for Disease in the Community • New figure showing participants in a mammogram and a blood pressure screening test • New figure showing participation rates in screening for colorectal cancer, breast cancer, and cervical cancer • Updated discussion on controversies in screening • Difficulties with false positive screening test results Chapter 12: Epidemiology of Infectious Diseases • Many updated charts showing data on disease incidence and prevalence (e.g., measles, malaria, hepatitis, valley fever, Lyme disease) • Information on the cholera epidemic in Haiti • Revised exhibit on viral hepatitis Chapter 13: Epidemiologic Aspects of Work in the Environment • New information on methodologic topics (e.g., exposure assessments, clustering, and confounding) • Updated data on blood lead levels and mercury advisories • New topics include global warming, the BP oil spill, and the Japanese tsunami and its effects on the Fukushima nuclear reactor • Many new images to capture students’ interest in this topic Chapter 14: Molecular and Genetic Epidemiology • New diagram of Mendelian inheritance • Additional discussion of the population genetics concept of linkage disequilibrium • Expanded discussion of the concept of haplotypes • A thorough update of this chapter with the latest developments in the field Chapter 15: Social, Behavioral, and Psychosocial Epidemiology • Many new illustrations added to this chapter • The concept of community-based participatory research added • New information on the social context of health (e.g., poverty, the Glasgow effect) • Healthy People 2020 overarching goals included • Update on depression Chapter 16: Epidemiology as a Profession • Updated to show current professional resources and issues Other • Exciting new figures, tables, and exhibits provided throughout • Additional exercises and study questions Introduction Epidemiology is an important, exciting, and rewarding field for the public health practitioner! Almost daily, one hears dramatic media reports about flare-ups of diseases, either previously known or seemingly new conditions. These accounts demonstrate how epidemiologists help to uncover the causes of human illnesses in the population and thereby underscore the importance of epidemiology to society. Deadly outbreaks of communicable diseases, the ongoing threat of resurgent epidemics, and the possible intentional spread of pathogenic microorganisms through acts of bioterrorism present challenges to the field. By assisting the reader in understanding why and how diseases occur and how they may be prevented, epidemiology is a valuable pursuit. In this text you will learn that many epidemiologic investigations into the causes of mysterious outbreaks are similar to detective work. One of the challenges for the authors has been to distill with sufficient breadth and depth all of the fascinating components of this discipline. As the Fifth Edition is being finalized, new and resurgent health conditions challenge public health practitioners; some current examples are resurgent whooping cough, outbreaks of foodborne diseases, hantavirus infections (which normally are infrequent) in a national park, fungal meningitis associated with epidural steroid injections, and a West Nile virus epidemic. Thus, the ongoing flow of accounts of disease outbreaks (noted in the First Edition) has not been staunched and, in fact, is continuing unabated during the second decade of the 21st century. Since the publication of the earlier editions of this book, the wealth of epidemiologic research findings has continued to proliferate and win the attention of the popular media and professional journals. For example, some of these recent discoveries relate to continuing advances in genetics and molecular biology, recognition of emerging infections, and the growing use of the Internet. As a result, the Second Edition introduced several enhancements: a new chapter on molecular and genetic epidemiology, a new chapter on experimental epidemiology, material on epidemiology Internet sites, and updated charts and tables throughout the text. The Third Edition incorporated a new chapter on cohort designs, a glossary, and an expanded coverage of ecologic and case-control study designs. The Third Edition also included new material on the role of epidemiology in policy making, epidemiology and geographic information systems, and the definition of race used in Census 2000. A new Appendix A provided an extended guide to critiquing published research studies in public health and epidemiology. Several new tables summarized unadjusted measures of morbidity and mortality, contrasted different types of observational study designs, and compared observational versus intervention study designs. The Fourth Edition presented new information on infectious disease threats associated with E. coli foodborne illness and avian influenza as well as expanded coverage of the historical background of epidemiology. Chapter 3, “Measures of Morbidity and Mortality Used in Epidemiology,” was updated to reflect the use of the 2000 standard population in age standardization. A new Chapter 16, titled “Epidemiology as a Profession,” covered methods for accessing the profession and employment opportunities in the field. The Fifth Edition provides an extensive update of information from the previous editions. Examples are coverage of the 2009 H1N1 influenza epidemic, the 2010 U.S. Census, and numerous additional and updated figures, charts, and photographs throughout the book. Trends in morbidity have been updated to reflect the most recently available information. New information is presented throughout the text: for example, in Chapter 12 (infectious diseases), Chapter 13 (environmental health), and Chapter 14 (molecular and genetic epidemiology). Definitions used in the text have been aligned with the 2008 Dictionary of Epidemiology, a standard reference in the field. We intend the audience for the textbook to be beginning public health master’s degree students, undergraduate and graduate health education and social ecology students, undergraduate medical students, nursing students, residents in primary care medicine, and applicants who are preparing for medical board examinations. These students are similar to those with whom both authors have worked over the years. Students from the social and behavioral sciences also have found epidemiology to be a useful tool in medical sociology and behavioral medicine. We have included study questions and exercises at the end of each chapter; this material would be helpful to review for board examinations. Appendix B contains an expanded answer set to selected problems. Each chapter begins with a list of learning objectives and an outline to help focus the reader’s attention to key points. Some of the major issues and examples are highlighted in text boxes and tables. Chapter 1, which defines epidemiology and provides a historical background for the discipline, is complemented by Chapter 2, which provides examples of practical applications of epidemiology as well as a discussion of causal inference. Although examples of epidemiologic statistical techniques are interspersed throughout the book, Chapter 3 focuses on the “nuts and bolts” of measures of morbidity and mortality. Chapters 4 through 11 deal with the important topics of descriptive epidemiology: data sources, study designs, measures of effect, data interpretation, and screening. Chapters 12 through 15 focus on four content areas in epidemiology: infectious diseases, occupational and environmental health, molecular and genetic epidemiology, and psychosocial epidemiology. Finally, Chapter 16 covers professional issues in epidemiology. This text provides a thorough grounding in the key areas of methodology, causality, and the complex issues that surround chronic and infectious disease investigations. The authors assume that the reader will have had some familiarity with introductory biostatistics, although the text is intelligible to those who do not have such familiarity. A companion website for students is available for the text. This website provides extensive resources for students, including the student study guide that was included with the last edition. We recommend that students and instructors navigate through the site during class time. For example, the flashcards available may be used as part of an in-class activity to drill students for the class examinations. Dr. Friis uses in-class Internet navigation in order to show students how to locate resources for the project shown in the Appendix at the end of Chapter 4. Completion of the project can be one of the major assignments in an epidemiology class. In addition to completing a written version of the assignment, students may enjoy delivering a brief PowerPoint presentation of their research to the entire class. Students’ motivation and success in an epidemiology course are enhanced by reviewing the various activities provided. Preface My interest in epidemiology began during the 1960s when, as an undergraduate student at the University of California at Berkeley and a graduate student at Columbia University, I observed the student revolts and activism that occurred during that era. Student unrest was, I believed, a phenomenon that occurred in large groups and could be explained by a theoretical framework, perhaps one that would include such concepts as alienation or anomie. I became interested in studying the distribution of these psychological states in student populations. Unknowingly, I had embarked upon epidemiologic research. I find epidemiology to be a field that has great personal appeal because it is capable of impacting the health of large groups of people through improvements in social conditions and environmental modifications. My formal training in epidemiology began at the Institute for Social Research of the University of Michigan, where I spent 2 years as a postdoctoral fellow. My first professional position in epidemiology was as an assistant professor in the Division of Epidemiology at the School of Public Health, Columbia University. As a fledgling professor, I found epidemiology to be a fascinating discipline, and began to develop this textbook from my early teaching experiences. I concluded that there was a need for a textbook that would be oriented toward the beginning practitioner in the field, would provide coverage of a wide range of topics, and would emphasize the social and behavioral foundations of epidemiology as well as the medical model. This textbook has evolved from my early teaching experience at Columbia as well as later teaching and research positions at Albert Einstein College of Medicine, Brooklyn College, the University of California at Irvine, and the California State University system. Practical experience in epidemiology, as an epidemiologist in a local health department in Orange County, California, is also reflected in the book. —Robert H. Friis Like many others now reading this book, I had absolutely no idea what epidemiology was before I took my first required class in it at Tulane University School of Public Health and Tropical Medicine. What I discovered was a method to combine my training in nutrition and interest in health with an aptitude for math and analytical reasoning. This led to a change in majors and ultimately a PhD in epidemiology. My first faculty appointment was at the University of Minnesota School of Public Health. Before I knew it, I was assigned to teach the introduction to epidemiology course during the winter quarter. This was the time of year when only nonmajors enrolled. I quickly learned, as had my predecessors, that my teaching and learning style was quite different from those of my students. Moreover, most of the textbooks available at that time were geared toward epidemiology majors. For 9 years, I studied learning styles (and even co-developed and co-taught a graduate course on teaching) and experimented to find new ways to present the fundamentals of epidemiology in a nontechnical, nontheoretical, intuitive manner. This text reflects these learning experiences. —Thomas A. Sellers Acknowledgments First, I express my gratitude to my teachers and colleagues at the settings where I have worked during the past 4 decades. Their insights and suggestions have helped me clarify my thinking about epidemiology. Among these individuals are the late Dr. Sidney Cobb and the late Dr. John R. P. French, Jr., who were my postdoctoral supervisors at the University of Michigan’s Institute for Social Research. Dr. Mervyn Susser offered me my first professional employment in epidemiology at the School of Public Health, Columbia University. He and Dr. Zena Stein helped me to greatly increase my fund of knowledge about research and teaching in the field. The late Professor Anna Gelman provided me with many practical ideas regarding how to teach epidemiology. Dr. Stephen A. Richardson also contributed to my knowledge about epidemiologic research. Finally, Dr. Jeremiah Tilles, former Associate Dean, California College of Medicine, University of California at Irvine, helped to increase my insights regarding the epidemiology of infectious diseases. I also thank students in my epidemiology classes who contributed their suggestions and read early drafts of the first edition. The comments of anonymous reviewers were particularly helpful in revising the manuscript. Jonathan Horowitz, former instructor in Health Science at California State University, Long Beach, spent a great deal of time reviewing several chapters of a very early version of the text, and I acknowledge his contributions. Sherry Stock, a former student in medical sociology at Long Beach, typed the first draft and provided much additional valuable assistance in securing bibliographic research materials. Dr. Yee-Lean Lee, Professor, Infectious Disease Division in the Department of Medicine at the University of California at Irvine, reviewed and commented on the chapter dealing with the epidemiology of infectious diseases. Also, Dr. Harold Hunter, Professor Emeritus of Health Care Administration, California State University, Long Beach, reviewed several chapters of the manuscript. Finally, my wife, Carol Friis, typed the final version of the manuscript and made helpful comments. Without her support and assistance, completion of the text would not have been possible. For the second edition of the text, I again thank my epidemiology students, who continued to provide much useful feedback. Graduate students Janelle Yamashita, Cindy Bayliss, and Jocelin Sabado were extremely helpful in conducting literature searches and preparing the text. Sharon Jean assisted with typing the manuscript. With respect to the third edition, I would like to thank students at my home university and at other universities who provided many worthwhile suggestions for enhancement of the text. I am also grateful for the informal feedback I received from faculty members (across the United States and in several foreign countries) who adopted this text in their courses. Former California State University graduate student Ibtisam Khoury, now a lecturer in the Health Science Department, conducted background research, provided ideas for clarification of complex concepts, and helped to develop several new tables. Faculty members Dr. Javier Lopez-Zetina and Dr. Dennis Fisher, housed at the same university, reviewed several of the chapters. Critiques from anonymous reviewers also were instrumental in development of the third edition. Once again, I am deeply indebted to my wife, Carol Friis, who assisted with editing and typing the manuscript. Without her keen eye, writing this book would have been a much more difficult task. Regarding the fourth edition, I once again acknowledge my students’ suggestions for continued improvement of this book. Although many students are worthy of recognition, I would especially like to thank graduate student Lesley Shen. Claire Garrido-Ortega, a former student and now a lecturer in the Department of Health Science, contributed her ideas to the new edition. I have received many suggestions from the readers of the previous edition of this text; I would like to thank them also—particularly Dr. Lee Caplan at Morehouse University. Once more, I recognize the support of my wife, Carol Friis, who helped with preparation of the text. The fifth edition benefited from the input of students and faculty members in the Department of Health Science. Particularly noteworthy were the suggestions provided by faculty member Dr. Javier Lopez-Zetina and former graduate students (and now faculty members) Ibtisam Khoury, Che Wanke, and Claire Garrido-Ortega. Jaina Pallasigui, MPH graduate, helped with background research for this revision. Roxanne Garza reviewed the manuscript. —R.H.F. I have been most fortunate to receive training and guidance from a significant number of individuals. First and foremost, I thank Dr. Dorothy Clemmer, who taught me my first course in epidemiology at Tulane University School of Public Health and Tropical Medicine. Her enthusiasm and support helped me to “see the light.” The early years of my education included mentorship with Dr. Gerald Berenson and Dr. Robert C. Elston. Both have been extremely influential in my practical and theoretical understanding of this discipline. Dr. J. Michael Sprafka was a great supporter and colleague for those first precarious episodes of teaching. I owe many thanks to the numerous bright and challenging public health students at the University of Minnesota for their support, encouragement, and patience while I experimented with methods of presentation to find out what worked best for “nonmajors.” Finally, I acknowledge my father, Gene R. Sellers, who has published many fine textbooks and gave me the courage to attempt this project; my loving wife, Barbara, for her understanding and enduring belief in me; and my two sons, Jamison Thomas and Ryan Austin, who are my inspiration and loves of my life. For the second edition, I acknowledge the encouragement of the students and colleagues who had used the first edition of this text. I also thank our publisher and their staff for their professionalism. Finally, I acknowledge the drive and creativity of Bob Friis, whose energies made this book a reality and a success. For the fourth edition, I would like to particularly thank my wonderful friends and colleagues at the Moffitt Cancer Center (especially Yifan Huang, Cathy Phelan, Jong Park, and Anna Giuliano) and the Mayo Cancer Center (especially Ellen Goode, Jim Cerhan, Celine Vachon, and Shane Pankratz) for their brilliance and dedication. I’ve learned that the application of the epidemiologic method can be fun if you work with the right team. I have certainly benefited from being around such a wonderful cast of bright and stimulating people. This has translated into exciting research projects, new knowledge, and practical insights added to this edition. Moreover, they share my hope and dream for an end to cancer and the terrible impact of this disease. For the fifth edition, I want to add a posthumous note of love and appreciation to my mother for always believing in me and for encouraging my pursuit of an academic career dedicated to cancer research. That she lost her life to the disease has reconfirmed my determination to make an impact through application of the epidemiologic method. —T.A.S. About the Authors Robert H. Friis, PhD, is a Professor Emeritus of Health Science and Chair Emeritus of the Department of Health Science at California State University, Long Beach, and former Director of the CSULB-VAMC, Long Beach, Joint Studies Institute. He is also a former Clinical Professor of Community and Environmental Medicine at the University of California at Irvine. Previously, he was an Associate Clinical Professor in the Department of Medicine, Department of Neurology, and School of Social Ecology, University of California at Irvine. His entire professional career has been devoted to the field of epidemiology. He has conducted research and taught epidemiology and related subjects for more than 4 decades at universities in New York City and Southern California. In addition to previous employment in a local health department as an epidemiologist, he has conducted research and has published and presented numerous papers related to mental health, chronic disease, disability, minority health, and psychosocial epidemiology. His textbook, Essentials of Environmental Health, Second Edition, is also published by Jones & Bartlett Learning. Dr. Friis has been principal investigator or co-investigator on grants and contracts from University of California’s Tobacco-Related Disease Research Program, from the National Institutes of Health, and from other agencies for research on geriatric health, depression in Hispanic populations, nursing home infections, and environmental health issues. His research interests have led him to conduct research in Mexico City and European countries. He has been a visiting professor at the Center for Nutrition and Toxicology, Karolinska Institute, Stockholm, Sweden; the Max Planck Institute, Munich, Germany; and Dresden Technical University, also in Germany. He reviews articles for scientific journals and is a member of the editorial board of Public Health. Dr. Friis is a member of the Society for Epidemiologic Research, the American Public Health Association (epidemiology section), is a past president of the Southern California Public Health Association, and is a fellow of the Royal Academy of Public Health. Among his awards are a postdoctoral fellowship (for study at the Institute for Social Research, University of Michigan), and the Achievement Award for Scholarly and Creative Activity from California State University, Long Beach. His biography is listed in Who’s Who in America. Thomas A. Sellers, PhD, MPH, is Director of the Moffitt Cancer Center & Research Institute and Executive Vice President of the H. Lee Moffitt Cancer Center and Research Institute. Prior to this position in sunny, warm Tampa, Florida, he was Professor of Epidemiology in the Department of Health Sciences Research at the Mayo Clinic and the Deputy Director of the Mayo Clinic Cancer Center. He began his career at the University of Minnesota School of Public Health, where he taught the Introduction to Epidemiology course to nonmajors for 9 years. His primary research interests include understanding the etiology of common adult cancers, particularly breast and ovarian cancer. He has published more than 300 peer-reviewed scientific articles, reviews, and book chapters, and now serves as a Deputy Editor of Cancer Epidemiology, Biomarkers, and Prevention and as Associate Editor of the American Journal of Epidemiology. Dr. Sellers is a long-standing member of the American Association for Cancer Research and the American Society for Preventive Oncology, and is a founding member of the International Genetic Epidemiology Society. Dr. Sellers has been an invited member of Advisory Committees to the National Cancer Institute, has provided invited lectures worldwide, and has served on numerous grant review panels. CHAPTER 1 History and Scope of Epidemiology LEARNING OBJECTIVES By the end of this chapter the reader will be able to: • define the term epidemiology • define the components of epidemiology (determinants, distribution, morbidity, and mortality) • name and describe characteristics of the epidemiologic approach • discuss the importance of Hippocrates’ hypothesis and how it differed from the common beliefs of the time • discuss Graunt’s contributions to biostatistics and how they affected modern epidemiology • explain what is meant by the term natural experiments, and give at least one example CHAPTER OUTLINE I. Introduction II. Epidemiology Defined III. Foundations of Epidemiology IV. Historical Antecedents of Epidemiology V. Recent Applications of Epidemiology VI. Conclusion VII. Study Questions and Exercises Introduction Controversies and speculations regarding the findings of epidemiologic research are frequent topics of media reports; these findings sometimes arouse public hysteria. Examples of the questions raised by media reports include: “Is it more dangerous to vaccinate an entire population against smallpox (with resulting complications from the vaccine) or to risk infection with the disease itself through a terrorist attack?” “Is Ebola virus a danger to the general public?” “Should I give up eating fatty foods?” “Is it safe to drink coffee or alcoholic beverages?” “Will chemicals in the environment cause cancer?” “Should one purchase bottled water instead of consuming tap water from public drinking supplies?” “Will medications for chronic diseases (long-standing illnesses that are difficult to eradicate) such as diabetes cause harmful side effects?” “Will the foods that I purchase in the supermarket make me sick?” “When can we expect the next global pandemic influenza and what shall be the response?” Consider the 2009–2010 episode of influenza first identified in the United States1 and eventually called 2009 H1N1 influenza. Ultimately the 2009 H1N1 outbreak threatened to become an alarming pandemic that public health officials feared could mimic the famous 1918 “killer flu.” In April 2009, 2 cases of 2009 H1N1 came to the attention of the Centers for Disease Control and Prevention (CDC), which investigates outbreaks of infectious diseases such as influenza. Thereafter, the number of cases expanded rapidly in the United States and then worldwide. When the epidemic eventually subsided during summer 2010, an estimated 60 million cases had occurred in the United States. According to the CDC, people in the age range of 18–64 years were most heavily affected by the virus; less affected were those 65 years of age and older. Exhibit 1–1 provides an account of the pandemic. EXHIBIT 1–1 The 2009 H1N1 Pandemic During spring 2009, a 10-year-old California child was diagnosed with an unusual variety of influenza. Soon afterwards a case of the same flu strain was identified in an 8-year-old who lived approximately 130 miles from the first patient. This was an alarming event in several respects. The type of influenza virus was usually found among swine. However, the newly identified virus appeared to have been transmitted among humans. Secondly, the appearance of these two unusual cases raised public health officials’ suspicions that a deadly flu pandemic similar to the 1918 pandemic might be under way. Scientists named the new virus 2009 H1N1. The agent was “… a unique combination of influenza virus genes never previously identified in either animals or people.”1 The genes of the new virus were closely related to North American swine-lineage H1N1 influenza viruses. Before this outbreak, human-to-human spread of swine-origin influenza viruses was highly unusual. During the previous three years (from December 2005 to January 2009), only 12 U.S. cases of swine influenza had been reported. The vast majority (n = 11) had indicated some contact with pigs. One of the unusual features of infections with the 2009 H1N1 virus were reports of a high prevalence of obesity among influenza-affected patients in intensive care units. Following the identification of the initial cases in California, swine flu spread across the United States and jumped international borders. In response to a potential widespread epidemic, some schools and public health officials implemented pandemic preparedness plans, which included school closures and social distancing. In June, the World Health Organization (WHO) declared that a global pandemic was under way. Here is a brief chronology of the events that transpired during the pandemic. • April 15, 2009—first case of pandemic influenza (2009 H1N1) identified in a 10-year-old California patient. • April 17—eight-year-old child living 130 miles away from first case develops influenza. • April 21—Centers for Disease Control and Prevention (CDC) began work on a vaccine against the virus. • April 22—three new cases are identified in San Diego County and Imperial County. • April 23—two new cases identified in Texas. • April 23—seven samples from Mexico were positive for 2009 H1N1. • April 25—WHO declares a “Public Health Emergency of International Concern.” • April 25—cases diagnosed in New York City, Kansas, and Ohio. • April 29—WHO raises the influenza pandemic alert from phase 4 to phase 5. • May 6—CDC recommends prioritized testing and antiviral treatment for people at high risk of complications from flu. • June 11—WHO raises the worldwide pandemic alert level to phase 6 and declares the global pandemic is under way. • June 11—more than 70 countries have reported cases of pandemic influenza. • June through July—the number of countries reporting influenza has nearly doubled; all 50 states in the U.S. have reported cases. • Summer and fall—extraordinary influenza-like illness activity reported in the U.S. • September 30—initial supplies of 2009 H1N1 vaccine distributed on a limited basis. • December—vaccine made available to all who wanted it. • Summer 2010—flu activity reaches normal summer time levels in the U.S. According to the CDC approximately 60 million people became infected with 2009 H1N1 between April 2009 and March 13, 2010. The estimated range of the number of cases was between 43 million and 88 million. The process of estimating the number of flu cases is imprecise because many patients who become ill do not seek medical care, and those who do are not tested for the virus. Figure 1–1 reports CDC estimates of 2009 H1N1 cases in the US by age group. Source: Data from Centers for Disease Control and Prevention. The 2009 H1N1pandemic: summary highlights, April 2009—April 2010. Available at: http://www.cdc.gov/h1n1flu/cdcresponse.htm. Accessed July 19, 2012. FIGURE 1–1 CDC estimates of 2009 H1N1 cases in the United States by age group. Source: Reproduced from Centers for Disease Control and Prevention. The CDC Estimates of 2009 H1N1 Influenza Cases, Hospitalizations and Deaths in the United States, April 2009–March 13, 2010. Available at: http://www.cdc.gov/h1n1flu/estimates/April_March_13.htm. Accessed August 23, 2012. Another example of a disease that elicited public hysteria was the outbreak of Escherichia coli (E. coli) infections during late summer and fall 2006. The outbreak affected multiple states in the United States and captured media headlines for several months. Known as E. coli O157:H7, this bacterial agent can be ingested in contaminated food. The agent is an enteric pathogen, which can produce bloody diarrhea, and in some instances, the hemolyticuremic syndrome (HUS), a type of kidney failure. Severe cases of E. coli O157:H7 can be fatal. The 2006 outbreak was a mysterious event that gradually unfolded over time. The outbreak sickened 199 persons across United States and caused 3 deaths (as of October 6, 2006, when the outbreak appeared to have subsided). Figure 1–2 shows the affected states. The 2006 outbreak caused 102 (51%) of the ill persons to be hospitalized; in all, 31 patients (16%) were afflicted with HUS. The majority of cases (141, 71%) were female. A total of 22 children 5 years of age and younger were affected.2 FIGURE 1–2 Distribution of Escherichia coli serotype O157:H7 cases across the United States, September 2006. Source: Reproduced from Centers for Disease Control and Prevention. Ongoing multistate outbreak of Escherichia coli serotype O157:H7 infections associated with consumption of fresh spinach—United States, September 2006. MMWR. 2006;55:1045– 1046. Tracking down the mysterious origins of the outbreak required extensive detective work. The outbreak was linked to prepackaged spinach as the most likely vehicle. Investigators traced the spinach back to its source, Natural Selection Foods near Salinas, California. The producer announced a recall of spinach on September 15, 2006.3 The FDA and State of California conducted a trace-back investigation, which implicated four ranches in Monterey and San Benito Counties. Cattle feces from one of the four ranches contained a strain of E. coli O157:H7 that matched the strain that had contaminated the spinach and also matched the strain found in the 199 cases.4 The mechanism for contamination of the spinach with E. coli bacteria was never established definitively. Noteworthy is the fact that subsequent to this major outbreak, E. coli O157:H7 continues to threaten the food supply of the United States, not only from spinach but also from other foods.5 During November and December 2006, Taco Bell restaurants in the northeastern United States experienced a major outbreak that caused at least 71 persons to fall ill. Contamination of Topp’s brand frozen ground beef patties and Totino’s or Jeno’s brand frozen pizzas with E. coli O157:H7 is believed to have sickened more than 60 residents of the eastern half of the United States during summer and early fall 2007. In 2008 and 2009, E. coli outbreaks were associated with ground beef and prepackaged cookie dough. Ground beef, cheese, romaine lettuce, bologna, and hazelnuts caused outbreaks during 2010 and 2011. A major outbreak of E. coli O104 occurred in Germany in 2011; 6 travelers from the United States were made ill, with one of the six dying. During summer 2012, a multistate outbreak caused by E. coli O145 sickened 18 persons and caused 9 deaths. In summary, the 2009 H1N1 flu pandemic (Exhibit 1–1) and the E. coli spinach-associated outbreak illustrate that epidemiologic research methods are a powerful tool for studying the health of populations. In many instances, epidemiology resembles detective work, because the causes of disease occurrence are often unknown. Both examples raise several issues that are typical of many epidemiologic research studies: • • • • • When there is a linkage or association between a factor (i.e., contaminants in food and water; animal reservoirs for disease agents) and a health outcome, does this observation mean that the factor is a cause of disease? If there is an association, how does the occurrence of disease vary according to the demographic characteristics and geographic locations of the affected persons? Based on the observation of such an association, what practical steps should individuals and public health departments take? What should the individual consumer do? Do the findings from an epidemiologic study merit panic or a measured response? How applicable are the findings to settings other than the one in which the research was conducted? What are the policy implications of the findings? In this chapter we answer the foregoing questions. We discuss the stages that are necessary to unravel mysteries about diseases, such as those due to environmental exposures or those for which the cause is entirely unknown. Epidemiology is a discipline that describes, quantifies, postulates causal mechanisms for diseases in populations, and develops methods for the control of diseases. Using the results of epidemiologic studies, public health practitioners are aided in their quest to control health problems such as foodborne disease outbreaks and influenza pandemics. The investigation into the spinach-associated E. coli outbreak illustrates some of the classic methods of epidemiology; first, describing all of the cases, enumerating them, and then following up with additional studies. Extensive detective work was involved in identifying the cause of the outbreak. The hypothesized causal mechanism that was ultimately linked to contaminated spinach was the bacterium E. coli. All of the features described in the investigation are hallmarks of the epidemiologic approach. In this example, the means by which E. coli contaminated the spinach remains an unresolved issue. The 2009 H1N1 pandemic demonstrated the use of epidemiologic data to identify the source of the initial outbreaks, describe pandemic spread, and mount a public health response to control a pandemic. Officials created public awareness of the need to be vaccinated against the virus and to prevent spread of the virus by covering up one’s mouth when coughing and washing one’s hands frequently. Epidemiology Defined The word epidemiology derives from epidemic, a term that provides an immediate clue to its subject matter. Epidemiology originates from the Greek words epi (upon) + demos (people) + logy (study of). Although some conceptions of epidemiology are quite narrow, we suggest a broadened scope and propose the following definition: Epidemiology is concerned with the occurrence, distribution, and determinants of “health-related states or events”6 (e.g., health and diseases, morbidity, injuries, disability, and mortality in populations). Epidemiologic studies are applied to the control of health problems in populations. The key aspects of this definition are determinants, distribution, population, and health phenomena (e.g., morbidity and mortality). Determinants Determinants are factors or events that are capable of bringing about a change in health. Some examples are specific biologic agents (e.g., bacteria) that are associated with infectious diseases or chemical agents that may act as carcinogens. Other potential determinants for changes in health may include less specific factors, such as stress or adverse lifestyle patterns (lack of exercise or a diet high in saturated fats). The following four vignettes illustrate the concern of epidemiology with disease determinants. For example, consider the steps taken to track down the source of the bacteria that caused anthrax and were sent through the mail; contemplate the position of an epidemiologist once again. Imagine a possible scenario for describing, quantifying, and identifying the determinants for each of the vignettes. Case 1: Intentional Dissemination of Bacteria That Cause Anthrax After the United States experienced its worst terrorist attack on September 11, 2001, reports appeared in the media about cases of anthrax in Florida beginning in early October. In the United States, anthrax usually affects herbivores (livestock and some wild animals); human cases are unusual. Anthrax is an acute bacterial disease caused by exposure to Bacillus anthracis. Cutaneous anthrax affects the skin, producing lesions that develop into a black scab. Untreated cutaneous anthrax has a case-fatality rate of 5–20%. The much more severe inhalational form, which affects the lungs and later becomes disseminated by the bloodstream, has a high case fatality rate.7 Observations of an alert infectious disease specialist along with the support of laboratory staff led to the suspicion that anthrax had been deliberately sent through the postal system.8 The CDC, in collaboration with officials at the state and local levels, identified a total of 21 anthrax cases (16 confirmed and 5 suspected) as of October 31, 2001. The majority of the cases occurred among employees located in four areas: Florida, New York City, New Jersey, and the District of Columbia.9–12 Figure 1–3 portrays the distribution of the 21 cases in 4 geographic areas of the United States. FIGURE 1–3 Occurrence of anthrax cases during the 2001 terrorist incident according to the investigation by the Centers for Disease Control and Prevention. Case 2: Outbreak of Fear When a 36-year-old lab technician known as Kinfumu checked into the general hospital in Kikwit, Zaire, complaining of diarrhea and a fever, anyone could have mistaken his illness for the dysentery that was plaguing the city. Nurses, doctors, and nuns did what they could to help the young man. They soon saw that his disease wasn’t just dysentery. Blood began oozing from every orifice in his body. Within 4 days he was dead. By then the illness had all but liquefied his internal organs. That was just the beginning. The day Kinfumu died, a nurse and a nun who had cared for him fell ill. The nun was evacuated to another town 70 miles to the west where she died—but not until the contagion had spread to at least three of her fellow nuns. Two subsequently died. In Kikwit, the disease raged through the ranks of the hospital’s staff. Inhabitants of the city began fleeing to neighboring villages. Some of the fugitives carried the deadly illness with them. Terrified health officials in Kikwit sent an urgent message to the World Health Organization. The Geneva-based group summoned expert help from around the globe: a team of experienced virus hunters composed of tropical-medicine specialists, microbiologists, and other researchers. They grabbed their lab equipment and their bubble suits and clambered aboard transport planes headed for Kikwit.13 Case 3: Fear on Seventh Avenue On normal workdays, the streets of New York City’s garment district are lively canyons bustling with honking trucks, scurrying buyers, and sweating rack boys pushing carts loaded with suits, coats, and dresses. But during September 1978 a tense new atmosphere was evident. Sanitation trucks cruised the side streets off Seventh Avenue flushing pools of stagnant water from the gutters and spraying out disinfectant. Teams of health officers drained water towers on building roofs. Air conditioners fell silent for inspection, and several chilling signs appeared on 35th Street: “The New York City Department of Health has been advised of possible cases of Legionnaires’ disease in this building.” By the weekend, there were 6 cases of the mysterious disease, 73 more suspected, and 2 deaths. In the New York City outbreak, three brothers were the first victims. Carlisle, Gilbert, and Joseph Leggette developed the fever, muscle aches, and chest congestion that make the disease resemble pneumonia. Joseph and Gilbert recovered; Carlisle did not. “He just got sick and about a week later he was dead,” said John Leggette, a fourth brother who warily returned to his own job in the garment district the next week. “I’m scared,” he said. “But what can you do?”14 Case 4: Red Spots on Airline Flight Attendants From January 1 to March 10, 1980, Eastern Airlines received 190 reports of episodes of red spots appearing on the skin of flight attendants (FAs) during various flights. Complaints of symptoms accompanying the spots were rare, but some FAs expressed concern that the spots were caused by bleeding through the skin and might indicate a serious health hazard. On March 12, investigators from the CDC traveled to Miami to assist in the investigation. No evidence of damage to underlying skin was noted on these examinations, nor was any noted by consultant dermatologists who examined affected FAs after the spots had disappeared. Chemical tests on clinical specimens for the presence of blood were negative. Airline personnel had investigated the ventilation systems, cleaning materials and procedures, and other environmental factors on affected aircraft. Airflow patterns and cabin temperatures, pressures, and relative humidity were found to be normal. Cleaning materials and routines had been changed, but cases continued to occur. Written reports by FAs of 132 cases occurring in January and February showed that 91 different FAs had been affected, 68 once and 23 several times. Of these cases, 119 (90%) had occurred on a single type of aircraft. Of the 119 cases from implicated aircraft, 96% occurred on north- or southbound flights between the New York City and Miami metropolitan areas, flights that are partially over water. Only rarely was a case reported from the same airplane when flying transcontinental or other east-west routes.15 Solution to Case 4: Red Spots The investigation then concentrated on defining the clinical picture more clearly. An Eastern Airlines (EAL) physician, a consultant dermatologist, and a physician from the National Institute for Occupational Safety and Health (NIOSH) rode on implicated flights on March 14 and examined three new cases considered by the EAL physician and other flight attendants (FAs) to be typical cases. Although the spots observed consisted of red liquid, they did not resemble blood. To identify potential environmental sources of red-colored material, investigators observed the standard activities of FAs on board implicated flights. At the beginning of each flight FAs routinely demonstrated the use of life vests, required in emergency landings over water. Because the vests used for demonstration were not actually functional, they were marked in bright red ink with the words “Demo Only.” When the vests were demonstrated, the red ink areas came into close contact with the face, neck, and hands of the demonstrator. Noting that on some vests the red ink rubbed or flaked off easily, investigators used red material from the vests to elicit the typical clinical picture on themselves. On preliminary chemical analyses, material in clinical specimens of red spots obtained from cases was found to match red-ink specimens from demonstration vests. On March 15 and 16, EAL removed all demonstration model life vests from all its aircraft and instructed FAs to use the standard, functional, passenger-model vests for demonstration purposes. The airline … continue[d] to request reports of cases to verify the effectiveness of this action. Although all demonstration vests were obtained from the same manufacturer, the vests removed from specific aircraft were noted to vary somewhat in the color of fabric and in the color and texture of red ink, suggesting that many different production lots may have been in use simultaneously on any given aircraft.15 Health departments, the CDC in Atlanta, and epidemiologic researchers frequently confront a problem that has no clear determinants or etiologic basis. The methods and findings of epidemiologic studies may direct one to, or suggest, particular causal mechanisms underlying health-related events or conditions, such as the four examples cited in the vignettes: anthrax, the suspected outbreak of Ebola virus, Legionnaires’ disease, and red spots on airline flight attendants. Read the solution to Case 4 to clear up the mystery of Case 4. Distribution Frequency of disease occurrence and mortality rates vary from one population group to another in the United States. For example, in 2006 death rates from coronary heart disease (CHD) and stroke were higher among African-Americans (blacks) than among American Indians/Alaskan natives, Asian/Pacific islanders, or whites.16 In comparison with other racial/ethnic groups, Hispanics have lower mortality rates for CHD than nonHispanics.16,17 Such variations in disease frequency illustrate how disease may have different distributions depending upon the underlying characteristics of the populations being studied. Population subgroups that have higher occurrence of adverse health outcomes are defined as having health disparities, which need to be targeted for appropriate interventions. Population Epidemiology examines disease occurrence among population groups rather than among individuals. Lilienfeld18 noted that this focus is a widely accepted feature of epidemiology. For this reason, epidemiology is often referred to as “population medicine.” As a result, the epidemiologic and clinical descriptions of a disease are quite different. Sometimes, when a new disease is first recognized, clinical descriptions of the condition are the first data available. These initial clinical descriptions can lead to subsequent epidemiologic investigations. Note the different descriptions of toxic shock syndrome (TSS), a condition that showed sharp increases during 1980 in comparison with the immediately previous years. TSS is a severe illness that in the 1980 outbreak was found to be associated with vaginal tampon use. The clinical description of TSS would include specific signs and symptoms, such as high fever, headache, malaise, and other more dramatic symptoms, such as vomiting and profuse watery diarrhea. The epidemiologic description would indicate which age groups would be most likely to be affected, time trends, geographic trends, and other variables that affect the distribution of TSS. A second example is myocardial infarction (MI; heart attack). A clinical description of MI would list specific signs and symptoms, such as chest pain, heart rate, nausea, and other individual characteristics of the patient. The epidemiologic description of the same condition would indicate which age groups would be most likely to be affected, seasonal trends in heart attack rates, geographic variations in frequency, and other characteristics of persons associated with the frequency of heart attack in populations. Referring again to the vignettes, one may note that the problem that plagued Kinfumu in Case 2 was recognized as a particularly acute problem for epidemiology when similar complaints from other patients were discovered and the disease began to spread. If more than one person complains about a health problem, the health provider may develop the suspicion that some widespread exposure rather than something unique to an individual is occurring. The clinical observation might suggest further epidemiologic investigation of the problem. Health Phenomena As indicated in the definition, epidemiology is used to investigate many different kinds of health outcomes. These range from infectious diseases to chronic diseases and various states of health, such as disability, injury, limitation of activity, and mortality.19 Other health outcomes have included individuals’ positive functioning and active life expectancy as well as adverse health-related events, including mental disorders, suicide, substance abuse, and injury. Epidemiology’s concern with positive states of health is illustrated by research into active life expectancy among geriatric populations. This research seeks to determine the factors associated with optimal mental and physical functioning as well as enhanced quality of life and ultimately aims to limit disability in later life. Morbidity and Mortality Two other terms central to epidemiology are morbidity and mortality. The former, morbidity, designates illness, whereas the latter, mortality, refers to death. Note that most measures of morbidity and mortality are defined for specific types of morbidity or causes of death. Aims and Levels The preceding sections hinted at the complete scope of epidemiology. As the basic method of public health, epidemiology is concerned with efforts to describe, explain, predict, and control. The term levels denotes the hierarchy of tasks that epidemiologic studies seek to accomplish (e.g., description of the occurrence of diseases is a less-demanding task and therefore ranks lower on the hierarchy of levels than explaining the causes of a disease and predicting and controlling them). More information will be provided later in the chapter. • To describe the health status of populations means to enumerate the cases of disease, to obtain relative frequencies of the disease within subgroups, and to discover important trends in the occurrence of disease. • To explain the etiology of disease means to discover causal factors as well as to determine modes of transmission. • To predict the occurrence of disease is to estimate the actual number of cases that will develop as well as to identify the distribution within populations. Such information is crucial to planning interventions and allocation of healthcare resources. • To control the distribution of disease, the epidemiologic approach is used to prevent the occurrence of new cases of disease, to eradicate existing cases, and to prolong the lives of those with the disease. The implication of these aims is that epidemiology has two different goals: one related to the distribution of health outcomes and the second to controlling diseases. The first goal is to achieve an improved understanding of the natural history of disease and the factors that influence its distribution. With the knowledge that is obtained from such efforts, one can then proceed to accomplish the second goal, which is control of disease via carefully designed interventions. Foundations of Epidemiology Epidemiology Is Interdisciplinary Refer to Figure 1–4, which characterizes the interdisciplinary foundations of epidemiology. As an interdisciplinary field, epidemiology draws from biostatistics and the social and behavioral sciences as well as from the medically related fields such as toxicology, pathology, virology, genetics, microbiology, and clinical medicine. Terris20 pointed out that epidemiology is an extraordinarily rich and complex science that derives techniques and methodologies from many disciplines. He wrote that epidemiology “must draw upon and synthesize knowledge from the biological sciences of man and of his parasites, from the numerous sciences of the physical environment, and from the sciences concerned with human society.”20(p 203) FIGURE 1–4 The interdisciplinary foundations of epidemiology. Here are some illustrations of the contributions of other disciplines to epidemiology. Microbiology, the science of microorganisms, yields information about specific disease agents, including their morphology and modes of transmission. Related fields are bacteriology and virology. The previously discussed investigatio...

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