Statistics Major only (please dont waste my time by bidding)

Scenario/Summary

This week’s lab highlights the use of graphics, distributions, and tables to summarize and interpret data.

Follow the directions below to find one of the given academic articles from the school library and then use that to describe the graphs and tables included. Further, you will describe other ways that the same data could be presented.

Deliverables

The deliverable is a Word document with your answers to the questions posed below based on the article you find.

Required Software

• Microsoft Word
• Internet access to read articles

 

Steps to Complete Week 3 Lab

PART 1:

Step 1: For our first broad-based search, choose one of the articles listed below that interests you.  Use the underlined words in your chosen article to search and see how many articles from the Pro-Quest Nursing database contain these underlined words (see the example below the article list)

Article Titles Systolic blood pressure, diastolic blood pressure, and pulse pressure: An evaluation of their joint effect on mortality 

Step 2: Go to the school Library

Step 3: Click on the ProQuest Nursing link under the search box

Step 4: Type the underlined words from the article that you chose into the first search bar. Checkmark Full Text, Peer-Reviewed, and choose Last 12 Months from the drop-down list.  Last, choose English Language under the language section.

Step 5: Choose Search to see how many articles in the ProQuest database have those words.

Step 6: Post a screenshot of your search results (topic and the number of articles containing your search terms) to the top of a Word document [see Step 5 above]. Below the screenshot, answer the following questions:

On your search:

    A. What terms did you use?

    B. What other things did you mark on the search page before conducting your search?

    C.Why did you choose the keywords that you did?

    D. How many articles were found with these search terms [from screenshot]?

Part 2:

Step 1: For our second more narrow search, go back and search using THE ENTIRE TITLE of the article you used the keywords from in your first search.  Paste the ENTIRE title into the search bar and find the full article [Do NOT checkmark anything to narrow your search this time!].

Step 2: Find a frequency table and/or graph within the article and post a screenshot in your Word document.

Example:

 

Frequency Distribution      OR            Graph

Step 3: Answer the following questions about your table and/or graph:

    A. What type of study is used in the article (quantitative or qualitative)?

    B. What type of graph or table did you choose for your lab? What characteristics make it this type?

    C. Describe the data displayed in your frequency distribution or graph (consider class size, class width,             total frequency, list of frequencies, class consistency, etc)

    D. Draw a conclusion about the data from the graph or frequency distribution you chose.

    E. How else might this data have been displayed? Discuss pros and cons of 2 other presentation options, such as tables or different graphical displays.

    F. Give the full APA reference of the article you are using for this lab.

Running head: DESCRIPTIVE STATISTICS IN CONCUSSIONS 1

DESCRIPTIVE STATISTICS IN CONCUSSIONS 9

Descriptive Statistics in Concussions

SAMPLE WEEK 3 LAB

Chamberlain University

Descriptive Statistics in Concussions

To complete each search, the link

https://library.chamberlain.edu/home

was selected and the ProQuest Nursing option was chosen. As instructed, the first search was conducted by using the underlined word in the article selected. The article selected was, Demographic, parental, and personal factors and youth athletes’ concussion -related knowledge and beliefs. The word concussion was typed in the search box. The search options used were full text, peer reviewed, last 12 months, and English. The results were the following:

The first search using the underlined word concussion and the above listed search options resulted with 374 results.

The next two searches were completed with the same parameters (full text, peer reviewed, last 12 months, and English) and a portion of the article name. The results were the following:

The first search contained a portion of the article with the words, youth athletes’ concussion -related knowledge and beliefs.

9 results were found:

The second search contained a portion of the article with the words, demographic, parental, and personal factors and youth athletes’ concussion.

2 results were found:

To find the actual article, the 12-month date range had to be removed. Even with the full article title, 20 results were found.

Descriptive Statistics in Concussions
Appropriate diagnosis and management of children and teens with mild traumatic brain injury (TBI), including concussion, can help safeguard our youth (CDC, 2020). Unfortunately, at this time, there are no U.S. guidelines that help clinicians determine the best and appropriate care.  According to the Centers for Disease Control (CDC), in 2014 there were approximately 2.87 million TBI-related emergency department visits, hospitalizations, and deaths in the US, including over 837,000 of these health events among children (CDC, 2020). These injuries are complex and difficult to manage and keeping our youth healthy is a top priority. Being knowledgeable about sport related brain injuries and concussions can help minimize the risk of serious and deadly effects.
With significant attention focused on improving care of youth traumatic brain injuries and concussions, it is alarming that little research has been done to examine young athletes’ concussion knowledge and the factors that influence it. In article, Demographic, Parental, and Personal Factors and Youth Athletes’ Concussion-Related Knowledge and Beliefs, descriptive statistics were used to examine the concussion-knowledge totals, individual knowledge questions, and concussion-perception questions (Register-Mihalik, Williams, Marshall, Linnan Mihalik, & Guskiewicz, 2018).
The research design included a cross-sectional survey of youth athletes participating in community sport or on middle school sports teams. A convenience sample was performed on 225 North Carolina and Arizona youth athletes, ages 8 to 15, and active in boys or girl’s football, soccer, ice hockey, or lacrosse in 2012 to 2013. A total of 234 parents of the same youth athletes were also surveyed. The survey captured data on youth athletes’ and parent’s knowledge, attitudes, and beliefs about concussion, recognition, response, and the need to seek care. The basics of the study include the demographics characteristics that include the following:
Demographic characteristics broken down by state, sex, sport, concussion education, and concussion history.
Frequency percentage that included each state – Arizona and North Carolina, both sex – male and female, sport category – boys and girl’s football, boys and girls lacrosse, boys and girls ice hockey, boys and girls soccer.
Although this information is the basics of the study, the demographic characteristics and frequency is important to understand where and how the data was collected. This survey can be considered bias as it only focuses on four sports with a youth age range of 8 to 15, and participants from only two states. Also, the classes vary in size and a convenience sample was completed, meaning the type of sampling is non-probability and was taken amongst individuals that were easily accessible. The disadvantage to this type of surveying is that the results do not represent the whole population, the results may under or over represent the population, and it is considered bias, since only the individuals that agree and want to take the survey are included.
Data Displays
The data listed above is a frequency table. Frequency tables are used to organize and display data. To give a better visualization of the demographic characteristics and frequency, a bar graph could be used. Sometimes data is displayed with more or less than 100 percent. The percentage total helps determine what graph is appropriate. For example, the percentage total in this particular survey is greater than 100% with variable class sizes. A bar graph would best display the data and help give a visual representation. Depending on the study variables, a bar graph may be difficult to read. In this case, a Pareto chart could be used. This aligns the data by sorting the bars from largest to smallest, making the chart easier to read and interpret (Holmes, Illowsky, & Dean, 2017).
Personal Interest
The article, Demographic, Parental, and Personal Factors and Youth Athletes’ Concussion-Related Knowledge and Beliefs, is in my particular interest due to the context. As a mother of a twelve-year-old boy that plays football and basketball, I understand the importance of knowing the risk, signs and symptoms, and care for a sports related brain injury and/or concussion. I also understand the importance of spreading awareness and teaching not only our parents but are youth athletes, teachers, school administrators, health professionals, and coaches about the signs and symptoms of concussions. My son is laid back and has a high tolerance for pain. My fear since has always been that he gets injured and I am not aware. Teaching our youth about the importance to recognize, respond, and seek care for concussions can minimize damaging and deadly events.
References
Centers for Disease Control and Prevention (CDC). (2019). Surveillance report of traumatic brain injury-related emergency department visits, hospitalizations, and deaths—United States, 2014. https://www.cdc.gov/traumaticbraininjury/basics.html
Chamberlain University Library. (n.d.). ProQuest nursing: Nursing and allied health database. https://search-proquest-com.chamberlainuniversity.idm.oclc.org/nahs/advanced/fromDatabasesLayer?accountid=147674
Holmes, A., Illowsky, B., & Dean, S. (2017). Introductory business statistics. OpenStax. https://openstax.org/details/books/introductory-business-statistics
Register-Mihalik J, Williams, Richelle M,PhD., A.T.C., Marshall SW, PhD., Linnan LA, ScD., Mihalik, Jason P, PhD,C.A.T.(C.), A.T.C., Guskiewicz, Kevin M, PhD, ATC,F.N.A.T.A., F.A.C.S.M. (2018). Demographic, parental, and personal factors and youth athletes’ Concussion-related knowledge and beliefs. Journal of Athletic Training. 2018 08;53(8):768-75.

10 American Nurse Today Volume 13, Number 5 AmericanNurseToday.com

ROBERT, a 78-year-old patient, re-

quests help getting to the bath-

room. When the nurse, Ellen, en-

ters the room, Robert’s lying in

bed, but when she introduces her-

self, he lunges at her, shoves her to

the wall, punches her, and hits her

with a footstool. Ellen gets up from

the floor and leaves the patient’s

room. She tells her colleagues what

happened and asks for help to get

the patient to the bathroom. At the

end of the shift, Ellen has a

swollen calf and her shoulder

aches. One of her colleagues asks

if she’s submitted an incident re-

port. Ellen responds, “It’s all in a

day’s work. The patient has so

many medical problems and a his-

tory of alcoholism. He didn’t in-

tend to hurt me. What difference

would it make if I filed a report?”

These kinds of nurse-patient in-

teractions occur in healthcare set-

tings across the United States, and

nurses all too frequently minimize

their seriousness. However, accord-

ing to the National Institute for Oc-

cupational Safety and Health, “…

the spectrum [of violence]…ranges

from offensive language to homi-

cide, and a reasonable working

definition of workplace violence is

Patient violence:
It’s not all in a day’s work

Strategies for reducing patient violence and
creating a safe workplace

By Lori Locke, MSN, RN, NE-BC; Gail Bromley, PhD, RN; Karen A. Federspiel, DNP, MS, RN-BC, GCNS-BC

AmericanNurseToday.com May 2018 American Nurse Today 11

as follows: violent acts, including

physical assaults and threats of as-

sault, directed toward persons at

work or on duty.” In other words,

patient violence falls along a con-

tinuum, from verbal (harassing,

threatening, yelling, bullying, and

hostile sarcastic comments) to

physical (slapping, punching, bit-

ing, throwing objects). As nurses,

we must change our thinking: It’s

not all in a day’s work.

This article focuses on physical

violence and offers strategies you

can implement to minimize the

risk of being victimized.

Consequences of patient
vio

lence

In many cases, patients’ physical vi-

olence is life-changing to the nurses

assaulted and

those who witness it.

(See Alarming statistics.) As a re-

sult, some nurses leave the profes-

sion rather than be victimized—a

major problem in this era of nurs-

ing shortages.

Too frequently, nurses consider

physical violence a symptom of the

patient’s illness—even if they sus-

tain injuries—so they don’t submit

incident reports, and their injuries

aren’t treated. Ultimately, physical

and psychological insults result in

distraction, which contributes to a

higher incidence of medication er-

rors and negative patient outcomes.

Other damaging consequences in-

clude moral distress, burnout, and

job dissatisfaction, which can lead

to increased turnover. However,

when organizations encourage

nurses to report violence and pro-

vide education about de-escalation

and prevention, they’re able to alle-

viate stress.

Workplace violence prevention
Therapeutic communication and as-

sessment of a patient’s increased

agitation are among the early clini-

cal interventions you can use to

prevent workplace violence. Use

what you were taught in nursing

school to recognize behavioral

The statistics around patient violence against nurses are alarming.

67% of all nonfatal workplace violence injuries occur in healthcare, but health-
care represents only 11.5% of the U.S. workforce.

Emergency department (ED) and psychiatric nurses are at
highest risk for patient

violence.

Hitting, kicking, beating, and shoving incidents are most reported.

25% of psychiatric nurses experience disabling injuries from patient assaults.

At one regional medical center, 70% of 125 ED nurses were
physically assaulted in 2014.

Sources: Emergency Nurses Association (ENA) Emergency department violence surveillance study 2011;
ENA Workplace violence toolkit 2010; Gates 2011; Li 2012.

Alarming statistics

Effective communication is the first line of defense against patient violence. These

tips can help:

• To build trust, establish rapport and set the tone as you respond to patients.
• Meet patients’ expectations by listening, validating their feelings, and respond-

ing to their needs in a timely manner.

• Show your patients respect by introducing yourself by name and addressing
them formally (Mr., Ms., Mrs.) unless they state another preference.

• Explain care before you provide it, and ask patients if they have questions.
• Be attentive to your body language, gestures, facial expressions, and tone of

voice. Patients’ behavior may escalate if they perceive a loss of control, and

they may not hear what you say.

• Control your emotions and maintain neutral, nonthreatening body language.
• Strive for communication that gives the patient control, when possible. Example:

“Which of your home morning routines would you like to follow while you’re in

the hospital? Would you like to wash your hands and face first, eat your break-

fast, and then brush your teeth?”

• Offer a positive choice before offering less desirable ones. Example: “Would
you prefer to talk with a nurse about why you’re upset, or do you feel as

though you will be so angry that you need to have time away from others?”

• Only state consequences if you plan to follow through.
• Listen to what patients say or ask, and then validate their requests.
• Discuss patients’ major concerns and how they can be addressed to their sat-

isfaction.

Despite these strategies, patients may still become upset. If that occurs, try these

strategies to de-escalate the situation before it turns violent.

• Nonverbal communication. “I see from your facial expression that you may
have something you want to say to me. It’s okay to speak directly to me.”

• Challenging verbal exchange. “My goal is to be helpful to you. If you have
questions or see things differently, I’m willing to talk to you more so that we

can understand each other better, even if we can’t agree with one another.”

• Perceptions of an incident or situation. “We haven’t discussed all aspects of
this situation. Would you like to talk about your perceptions?”

Communication strategies

12 American Nurse Today Volume 13, Number 5 AmericanNurseToday.com

changes, such as anxiety, confu-

sion, agitation, and escalation of

verbal and nonverbal signs. Individ-

ually or together, these behaviors

require thoughtful responses. Your

calm, supportive, and responsive

communication can de-escalate pa-

tients who are known to be poten-

tially violent or those who are an-

noyed, angry, belligerent, demeaning,

or are beginning to threaten staff.

(See Communication strategies.)

Other strategies to prevent work-

place violence include applying

trauma-informed care, assessing for

environmental risks, and recognizing

patient triggers.

Trauma-informed care
Trauma-informed care considers the

effects of past traumas patients ex-

perienced and encourages strategies

that promote healing.

The Substance Abuse and Mental

Health Services Administration says

that a trauma-informed organization:

• realizes patient trauma experi-

ences are widespread

• recognizes trauma signs and

symptoms

• responds by integrating knowl-

edge and clinical competencies

about patients’ trauma

• resists retraumatization by being

sensitive to interventions that

may exacerbate staff-patient in-

teractions.

This approach comprises six

principles: safety; trustworthiness

and transparency; peer support;

collaboration and mutuality; em-

powerment, voice, and choice;

and cultural, historical, and gender

issues. Applying these principles

will enhance your competencies

so that you can verbally intervene

to avoid conflict and minimize pa-

tient retraumatization. For more

about trauma-informed care, visit

samhsa.gov/nctic/trauma-interventions.

Environmental risks
To ensure a safe environment, iden-

tify objects in patient rooms and

nursing units that might be used to

injure someone. Chairs, footstools,

I.V. poles, housekeeping supplies,

and glass from lights or mirrors can

all be used by patients to hurt them-

selves or others. Remove these ob-

jects from all areas where violent

patients may have access to them.

Patient triggers
Awareness of patient triggers will

help you anticipate how best to in-

teract and de-escalate. (See Patient

triggers.) Share detailed information

about specific patient triggers dur-

ing handoffs, in interdisciplinary

planning meetings, and with col-

leagues in safety huddles.

What should you do?
You owe it to yourself and your fel-

low nurses to take these steps to

ensure that your physical and psy-

chological needs and concerns are

addressed:

• Know the definition of work-

place violence.

• Take care of yourself if you’re

assaulted by a patient or witness

violence.

• Discuss and debrief the incident

with your nurse manager, clinical

supervisor, and colleagues.

• Use the healthcare setting’s inci-

dent reporting to report and doc-

ument violent incidents and in-

juries.

• File charges based on your

state’s laws.

Your organization should pro-

vide adequate support to ensure

that when a nurse returns to work

after a violent incident, he or she

is able to care for patients. After

any violent episode, staff and nurse

leaders should participate in a thor-

ough discussion of the incident to

understand the dynamics and root

cause and to be better prepared

to minimize future risks. Effective

communication about violent pa-

tient incidents includes handoffs

that identify known risks with spe-

cific patients and a care plan that

includes identified triggers and clin-

ical interventions.

Influence organizational safety
You and your nurse colleagues are

well positioned to influence your

organization’s culture and advocate

for a safe environment for staff and

patients. Share these best practices

with your organization to build a

comprehensive safety infrastructure.

• Establish incident-reporting sys-

tems to capture all violent inci-

dents.

• Create interprofessional work-

place violence steering commit-

tees.

• Develop organizational policies

and procedures related to safety

and workplace violence, as well

as human resources support.

• Provide workplace violence-pre-

vention and safety education us-

ing evidence-based curriculum.

• Design administrative, director,

and manager guidelines and re-

sponsibilities regarding commu-

nication and staff support for

victims of patient violence and

those who witness it.

• Use rapid response teams (in-

cluding police, security, and pro-

Recognizing and understanding pa-

tient triggers may help you de-esca-

late volatile interactions and prevent

physical violence.

Common triggers

• Expectations aren’t met

• Perceived loss of independence

or control

• Upsetting diagnosis, prognosis,

or disposition

• History of abuse that causes an

event or interaction to retrauma-

tize a patient

Predisposing factors

• Alcohol and substance withdrawal

• Psychiatric diagnoses

• Trauma

• Stressors (financial, relational, sit-

uational)

• History of verbal or physical vio-

lence

Patient triggers

tective services) to respond to
violent behaviors.

• Delineate violence risk indicators
to proactively identify patients
with these behaviors.

• Create scorecards to benchmark
quality indicators and outcomes.

• Post accessible resources on the
organization’s intranet.

• Share human resources contacts.

Advocate for the workplace you
deserve
Physically violent patients create
a workplace that’s not conducive
to compassionate care, creating
chaos and distractions. Nurses
must advocate for a culture of
safety by encouraging their organ-
ization to establish violence-pre-
vention policies and to provide
support when an incident occurs.

You can access violence-preven-
tion resources through the Ameri-
can Nurses Association, Emergency
Nurses Association, Centers for Dis-
ease Control and Prevention, and
the National Institute for Occupa-
tional Safety and Health. Most of
these organizations have interactive
online workplace violence-preven-
tion modules. (See Resources.) When
you advocate for safe work envi-
ronments, you protect yourself and
can provide the care your patients
deserve.

The authors work at University Hospitals of Cleve-

land in Ohio. Lori Locke is the director of psychiatry

service line and nursing practice. Gail Bromley is the

co director of nursing research and educator. Karen A.

Federspiel is a clinical nurse specialist III.

Selected references
Cafaro T, Jolley C, LaValla A, Schroeder R.

Workplace violence workgroup report. 2012.

apna.org/i4a/pages/index.cfm?pageID=4912

Emergency Nurses Association. ENA toolkit:

Workplace violence. 2010. goo.gl/oJuYsb

Emergency Nurses Association, Institute for

Emergency Nursing Research. Emergency

Department Violence Surveillance Study.

2011. bit.ly/2GvbJRc

Gates DM, Gillespie GL, Succop P. Violence

against nurses and its impact on stress and

productivity. Nurs Econ. 2011;29(2):59-66.

National Institute for Occupational Safety

and Health. Violence in the workplace:

Current intelligence bulletin 57. Updated

2014. cdc.gov/niosh/docs/96-100/introduc

tion.html

Occupational Safety and Health Administra-

tion. Guidelines for Preventing Workplace

Violence for Healthcare and Social Service

Workers. 2016. osha.gov/Publications/osha

3148

Speroni KG, Fitch T, Dawson E, Dugan L,

Atherton M. Incidence and cost of nurse

workplace violence perpetrated by hospital

patients or patient visitors. J Emerg Nurs.

2014;40(3):218-28.

Substance Abuse and Mental Health Servic-

es Administration. Trauma-informed ap-

proach and trauma-specific interventions.

Updated 2015. samhsa.gov/nctic/trauma-

interventions

Wolf LA, Delao AM, Perhats C. Nothing

changes, nobody cares: Understanding the

experience of emergency nurses physically

or verbally assaulted while providing care. J

Emerg Nurs. 2014;40(4):305-10.

• American Nurses Association (ANA) (goo.gl/NksbPW): Learn more about

different levels of violence and laws and regulations, and access the ANA posi-

tion statement on incivility, bullying, and workplace violence.

• Centers for Disease Control and Prevention (cdc.gov/niosh/topics/vio-

lence/training_nurses.html): This online course (“Workplace violence preven-

tion for nurses”) is designed to help nurses better understand workplace vio-

lence and how to prevent it.

• Emergency Nurses Association (ENA) toolkit (goo.gl/oJuYsb): This toolkit

offers a five-step plan for creating a violence-prevention program.

• The Joint Commission Sentinel Event Alert: Physical and verbal violence

against health care workers (bit.ly/2vrBnFw): The alert, released April 17,

2018, provides an overview of the issue along with suggested strategies.

Resources Screen & Intervene:

Addressing Food

Insecurity Among

Older Adults

FREE Online Course

Check out
the course today at

senior health and hunger.org

Hunger is a

health issue.

People experiencing food

insecurity are more likely to

suffer from chronic

conditions such as

diabetes, heart disease and

depression. In just 60

minutes, health care

providers and community-

based partners can learn

how to screen patients age

50 and older for food

insecurity and connect

them to key nutrition

resources.

This Enduring Material activity, Screen and

Intervene: Addressing Food Insecurity

Among Older Adults, has been reviewed

and is acceptable for up to 1.00 Elective

credit(s) by the American Academy of

Family Physicians. AAFP certification

begins 10/28/2017. Term of approval is

for one year from this date. Physicians

should claim only the credit commensurate

with the extent of their participation in the

activity.

AmericanNurseToday.com May 2018 American Nurse Today 13

http://www.feedingamerica.org/research/senior-hunger-research/spotlight-on-senior-health.html

http://www.feedingamerica.org/research/senior-hunger-research/spotlight-on-senior-health.html

Copyright of American Nurse Today is the property of HealthCom Media and its content may
not be copied or emailed to multiple sites or posted to a listserv without the copyright holder’s
express written permission. However, users may print, download, or email articles for
individual use.

Systolic Blood Pressure, Diastolic Blood Pressure, and Pulse
Pressure: An Evaluation of Their Joint Effect on Mortality
Roberto Pastor-Barriuso, PhD; José R. Banegas, MD, PhD; Javier Damián, MD, PhD; Lawrence J. Appel, MD, MPH;
and Eliseo Guallar, MD, DrPH

Background: The relative importance of blood pressure compo-
nents (systolic blood pressure, diastolic blood pressure, and pulse
pressure) on cardiovascular risk is currently being debated. Many
studies, however, are limited by inadequate statistical methods to
separate these effects.

Objective: To evaluate the joint effect of blood pressure com-
ponents on all-cause and cardiovascular mortality by using non-
parametric and change point models.

Design: Prospective cohort study.

Setting: 15-year mortality follow-up of participants in the Second
National Health and Nutrition Examination Survey.

Participants: 7830 white and African-American men and women
30 to 74 years of age, apparently free of cardiovascular disease at
baseline.

Measurements: Baseline blood pressure, corrected for measure-
ment error.

Results: Of the 1588 patients who died, 582 died of cardiovas-
cular disease. Systolic blood pressure was linearly related to all-
cause and cardiovascular mortality in younger and elderly partic-
ipants. The association of diastolic blood pressure with all-cause
and cardiovascular mortality was hockey stick–shaped (flat then
increasing) in younger participants and J-shaped in elderly partic-
ipants. Increased pulse pressure was associated with increased
risk, decreased risk, or no change in risk depending on age and
systolic and diastolic blood pressure.

Conclusions: On the basis of these and previous data, the
evidence for a monotonic association of systolic blood pressure
with all-cause and cardiovascular mortality is compelling, but a
J-shaped association for diastolic blood pressure may develop at
older age. The complexity of the association of pulse pressure
with mortality discourages its use for prognostic or therapeutic
decisions.

Ann Intern Med. 2003;139:731-739. www.annals.org
For author affiliations, see end of text.

Two aspects of the effect of blood pressure on mortalityhave been controversial. The first is the relative impor-
tance of blood pressure components (systolic blood pres-
sure, diastolic blood pressure, and pulse pressure) as deter-
minants of risk (1–5), and it has been suggested that
beyond middle age, pulse pressure is a more important
determinant of risk than systolic or diastolic blood pressure
(2). The second is the possibility of a J-shaped relationship
between blood pressure and mortality (4, 6, 7), with the
concern that lowering blood pressure below a threshold of
lowest risk would not be justified and could even be harmful.

Evaluating these 2 issues, however, is methodologically
complex. First, systolic blood pressure, diastolic blood
pressure, and pulse pressure are linearly dependent, that is,
knowledge of any 2 of them determines the third. Second,
because of the high correlation between systolic and dia-
stolic blood pressures, interpreting the effect of blood pres-
sure components is difficult. For instance, if only 1 com-
ponent (such as diastolic blood pressure) is used to model
risk, it is unclear what part of the effect is due to its cor-
relation with systolic blood pressure (4). However, if sys-
tolic and diastolic blood pressure are introduced in a re-
gression model, the interpretation of both coefficients is
uncertain because the coefficients partly reflect the effect of
pulse pressure. Third, most studies addressing the J-shape
phenomenon have used analysis strategies that did not ac-
count for the complex relationships between blood pres-
sure components and mortality.

We examined the relationship of blood pressure com-
ponents with all-cause and cardiovascular disease (CVD)

mortality in a representative population– based prospective
study. We used generalized additive models to estimate the
effect of the joint distribution of blood pressure compo-
nents, avoiding model assumptions about the underlying
dose–response relationship (8, 9). These methods take ad-
vantage of the high correlation between systolic and dia-
stolic blood pressures to estimate the risk surface for com-
binations of blood pressure measures. We also discuss how
to interpret the relative importance of each blood pressure
component based partly on graphical presentation of re-
sults.

METHODS
Study Sample

The study sample consisted of 9250 participants in the
Second National Health and Nutrition Examination Sur-
vey (NHANES II) Mortality Study (10), a prospective co-
hort study that followed participants 30 to 74 years of age.
The complex survey, conducted by the National Center for
Health Statistics between 1976 and 1980, used a stratified,
multistage sampling design to obtain a representative sam-
ple of the noninstitutionalized U.S. population (11). The
response rate among persons selected for the examination
was 73%.

Baseline Assessment
During the NHANES II baseline examination (1976

to 1980), a trained physician took 3 blood pressure mea-
surements by using a calibrated mercury sphygmomanom-
eter on the right arm, according to the American Heart

Article

© 2003 American College of Physicians 731

Association guidelines. One measurement was taken at the
beginning of the physical examination with the participant
in the sitting position, and 2 more measurements were
taken at the end of the physical examination, 1 with the
participant in the supine position and the other with the
participant in the sitting position (11). We used these 3
measurements to estimate each participant’s underlying
systolic and diastolic blood pressure (see Statistical Analysis).

Participants’ age, sex, race or ethnicity, smoking status,
and years of education were obtained by interview. Weight
and height were measured to calculate the body mass in-
dex. Total serum cholesterol levels were obtained from
standard blood assays. Use of antihypertensive medication
and previous diagnosis of diabetes were identified through
the medical history questionnaire. Evidence of CVD at
baseline was defined as a positive response on a modified
Rose angina questionnaire or a medical history of heart
attack or stroke (11).

Mortality Ascertainment during Follow-up
Mortality status was ascertained from 1976 to 1992 by

searching the National Death Index and the Social Security
Administration Death Master File (10). Participants not
found to be deceased by 31 December 1992 were assumed
to be alive. The causes of death were coded by nosologists
according to the International Classification of Diseases,
Ninth Revision (ICD-9). Deaths were ascribed to CVD if
any of the following conditions were coded as the under-
lying cause of death: hypertensive heart disease (402.0 to
402.9); ischemic heart disease (410.0 to 414.9); cardiac arrest
(427.5); unspecified heart failure (428.9); unspecified CVD
(429.2); cerebrovascular disease (430.0 to 438.9); or dis-
eases of the arteries, arterioles, and capillaries (440.0 to
444.9).

Statistical Analysis
Our main objective was to estimate the joint effect of

systolic and diastolic blood pressure on all-cause and CVD
mortality, that is, the risk for death for each combination
of systolic and diastolic blood pressure. This is in contrast
to usual analyses, which estimate the marginal rather than
the joint effects. The marginal effect of diastolic blood
pressure, for instance, is the effect at each level of diastolic
blood pressure “averaged” across all values of systolic blood
pressure. To estimate the joint effect of systolic and dia-
stolic blood pressure, we simultaneously fitted 2 nonpara-
metric terms (locally weighted smoothers with 40% to
50% bandwidth) for each blood pressure component in a
generalized additive logistic model (8). This technique es-
timates the smooth surface of the relative risk for death as
a function of both systolic and diastolic blood pressure. It
does not make assumptions about the shape of the associ-
ation, and it takes advantage of the correlation between
systolic and diastolic blood pressure to obtain more precise
estimates of risk over the joint distribution of observed
values.

To compare our results with previous analyses, we also
estimated the marginal effect of blood pressure compo-
nents by using Cox proportional hazards models and non-
parametric logistic regression to explore the continuous
risk trend without imposing any assumption on the shape
of the association (8). In addition, we performed statistical
tests for detecting the existence of threshold effects or
points of abrupt risk change (12). When a change point
was detected, transition logistic models were fitted to esti-
mate its location (12). Transition models are similar to
spline models (13), but in the former the change point is
estimated from the data rather than fixed in advance. In
contrast to standard analysis of the J-shape phenomenon
based on log-linear or categorical models with limited abil-
ity to detect threshold effects, nonparametric regression
and change point models correctly identify nonlinear ef-
fects and threshold levels (12–15).

Since we detected that the proportional hazards as-
sumption was applicable only after the initial 2-year
follow-up, and because of the few deaths and the possibil-
ity that early deaths at low blood pressure reflect underly-
ing disease or frailty conditions (reverse causation bias), the
first 2 years of follow-up (122 all-cause deaths, 44 of which
were CVD deaths) were analyzed separately from the
deaths after 2 years of follow-up (1466 all-cause deaths,
538 of which were CVD deaths).

To correct for regression dilution bias due to random
within-participant variability in blood pressure (16 –18),
each participant’s underlying blood pressure was estimated
from the observed measurements by using a random-effects
model for each sex (17). These underlying blood pressure
values were used subsequently in all analyses. Since the
relationship of blood pressure with CVD risk may change
with age (2), we conducted all analyses separately for 2 age
strata (�65 and �65 years). All models presented were

Context

Researchers often debate relationships between various
blood pressure components and risk for death.

Contribution

This careful analysis from a large cohort study confirmed
linear relationships between increasing systolic blood pres-
sure and increasing risk for death and, depending on age,
either hockey stick–shaped or J-shaped relationships be-
tween diastolic blood pressure and mortality. Relationships
between pulse pressure and mortality depended on
whether increased pulse pressure was due to increased
systolic or decreased diastolic blood pressure.

Implications

Pulse pressure alone, without appropriate attention to sys-
tolic and diastolic blood pressure components, is an inade-
quate indicator of mortality risk.

–The Editors

Article Blood Pressure and Mortality

732 4 November 2003 Annals of Internal Medicine Volume 139 • Number 9 www.annals.org

adjusted for age, sex, race or ethnicity, smoking status, total
serum cholesterol level, body mass index, education, anti-
hypertensive treatment, and history of diabetes mellitus.
Statistical analyses were performed by using S-plus 2000
(Mathsoft, Seattle, Washington) (19).

Role of the Funding Source
The funding source had no role in the choice of topic;

design, analysis, or interpretation of the data; or the deci-
sion to submit the manuscript for publication.

RESULTS
From the initial 9250 participants in the NHANES II

Mortality Follow-up Study, we excluded 1124 participants
who had evidence of CVD at baseline, 146 participants
with missing blood pressure values, and 150 participants
who were not white or African American. Thus, the final
study sample included 7830 individuals. Table 1 describes
the characteristics of the study participants. Systolic blood
pressure was highly correlated with diastolic blood pressure
and pulse pressure in participants younger than 65 years of
age and participants 65 years of age and older (Pearson
correlation coefficients, 0.66 to 0.85), while diastolic blood
pressure was weakly correlated with pulse pressure (Pearson
correlation coefficients, 0.20 and 0.17 for participants �65
and �65 years of age, respectively). Follow-up extended
from enrollment in 1976 to 1980 through 31 December
1992, with an average follow-up of 14.9 years among sur-
vivors (range, 12.8 to 16.9 years), and a total of 106 387
person-years of follow-up, 1588 all-cause deaths, and 582
CVD deaths.

Early Mortality Findings
During the first 2 years of follow-up, the association of

systolic blood pressure with all-cause mortality was U-shaped
(Table 2), and the risk for death was lowest for participants
with systolic blood pressure between 120 and 149 mm Hg
(P for quadratic trend � 0.03). For diastolic blood pres-

sure, the lowest risk for death during the first 2 years of
follow-up was observed at 90 to 94 mm Hg, but the over-
all U-shaped trend was not significant (P for quadratic
trend � 0.2). This pattern was similar after stratifying by
age younger than 65 years or 65 years and older. The small
number of CVD deaths during the first 2 years of fol-
low-up (n � 44) precluded a corresponding dose–response
analysis for this outcome.

Joint Effect of Blood Pressure Components
Figure 1 shows the joint effect of systolic and diastolic

blood pressure on mortality beyond 2 years of follow-up.
In younger participants, systolic blood pressure was linearly
related to all-cause and CVD mortality for all diastolic

Table 1. Baseline Characteristics of Participants in the Second National Health and Nutrition Examination Survey Mortality Study by
Age Group*

Characteristic Participants < 65 Years of Age (n � 5775)

Participants > 65 Years
of Age (n � 2055)

All Participants
(n � 7830)

Age, y 48.0 � 11.3 69.0 � 2.8 53.5 � 13.4
Women, % 52.6 56.3 53.6
White, % 89.3 89.0 89.2
Systolic blood pressure, mm Hg 128.8 � 18.2 143.4 � 19.9 132.6 � 19.7
Diastolic blood pressure, mm Hg 81.3 � 10.5 82.3 � 10.5 81.5 � 10.5
Pulse pressure, mm Hg 47.5 � 12.3 61.1 � 15.3 51.1 � 14.5
Smoking status, %

Never 37.7 51.5 41.4
Past 24.8 29.3 25.9
Current 37.5 19.2 32.7

Total serum cholesterol level, mg/dL (mmol/L) 222.1 � 47.9 (5.7 � 1.2) 234.8 � 48.7 (6.1 � 1.3) 225.4 � 48.5 (5.8 � 1.3)
Body mass index, kg/m2 25.9 � 4.9 26.2 � 4.9 26.0 � 4.9
Education � high school, % 37.9 59.4 43.5
Antihypertensive treatment, % 12.1 29.5 16.7
History of diabetes mellitus, % 3.8 8.4 5.0

* Values with plus/minus signs are means � SDs.

Table 2. Blood Pressure and Risk for All-Cause Mortality
during First 2 Years of Follow-up in the Second National
Health and Nutrition Examination Survey Mortality Study*

Blood Pressure,
mm Hg

Deaths, n Relative Risk
(95% CI)†

P Value‡

Systolic 0.03
�120 21 1.00
120–129 18 0.63 (0.33–1.20)
130–139 19 0.65 (0.34–1.23)
140–149 20 0.67 (0.35–1.29)
150–159 17 0.79 (0.39–1.59)
�160 27 1.06 (0.56–2.00)

Diastolic �0.2
�80 46 1.00
80–84 28 1.27 (0.78–2.04)
85–89 21 1.21 (0.71–2.07)
90–94 7 0.73 (0.32–1.64)
95–99 9 1.29 (0.62–2.71)
�100 11 1.82 (0.88–3.76)

* Results for cardiovascular disease mortality are not presented because of the small
number of events during first 2 years of follow-up.
† Relative risk from Cox proportional hazards model adjusted for age, sex, race or
ethnicity, smoking, total cholesterol level, body mass index, education, use of
antihypertensive medications, and history of diabetes.
‡ Tests for quadratic risk trends were performed by including an ordinal variable
with quadratic scores across blood pressure categories.

ArticleBlood Pressure and Mortality

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blood pressure levels. This can be appreciated by noting
the increasing slope of the risk surface with increasing sys-
tolic blood pressure when the surface is followed along
lines parallel to the systolic blood pressure axis. Along these
lines, the surface represents the effect of increasing systolic
blood pressure for each fixed value of diastolic blood pres-
sure, also known as the conditional effect of systolic blood
pressure. This effect can be interpreted as the effect of
increasing pulse pressure by increasing systolic blood pres-

sure and holding each value of diastolic blood pressure
constant.

The relationship of diastolic blood pressure and mor-
tality in younger participants was hockey stick–shaped,
with a flat region below 80 mm Hg and then a sharp
increase in risk. The effect of diastolic blood pressure for a
fixed systolic blood pressure can be evaluated by following
the risk surface along lines parallel to the diastolic blood
pressure axis. The flat surface below 80 mm Hg of diastolic

Figure 1. Risk surfaces for all-cause and cardiovascular mortality as a function of systolic and diastolic blood pressure by age group.

Surfaces were obtained by fitting simultaneous nonparametric terms for systolic and diastolic blood pressure in generalized additive logistic models.
Breaks in gray scale are determined by the risk levels labeled in each vertical axis. Adjusted for age, sex, race or ethnicity, smoking, total cholesterol level,
body mass index, education, use of antihypertensive medications, and history of diabetes. The surfaces represent the relative risk for all-cause and
cardiovascular mortality for each combination of systolic and diastolic blood pressure. For a fixed diastolic blood pressure, the effect of systolic blood
pressure can be evaluated by following the risk surface along lines parallel to the systolic blood pressure axis. This effect, known as the conditional effect
of systolic blood pressure, can also be interpreted as the effect of increasing pulse pressure by increasing systolic blood pressure and holding diastolic blood
pressure constant. Similarly, for a fixed systolic blood pressure, the conditional effect of diastolic blood pressure can be evaluated by following the risk
surface along lines parallel to the diastolic blood pressure axis. This effect corresponds to the effect of decreasing pulse pressure by increasing diastolic
blood pressure and holding systolic blood pressure constant.

Article Blood Pressure and Mortality

734 4 November 2003 Annals of Internal Medicine Volume 139 • Number 9 www.annals.org

blood pressure implies that increasing pulse pressure by
decreasing diastolic blood pressure below 80 mm Hg does
not increase risk, while decreasing pulse pressure by in-
creasing diastolic blood pressure above 80 mm Hg in-
creases risk for death.

In elderly participants, systolic blood pressure also
showed essentially a linear increase in risk, while diastolic
blood pressure showed a J-shaped relationship for all-cause
and CVD mortality (Figure 1). For a fixed diastolic blood
pressure, increasing systolic blood pressure (and thus pulse
pressure) was associated with increased risk, while for a
fixed systolic blood pressure, increasing diastolic blood
pressure (and thus decreasing pulse pressure) was associated
with decreased risk for diastolic blood pressure below 80 to
90 mm Hg and with increased risk for diastolic blood
pressure above 80 to 90 mm Hg.

Marginal Effects of Blood Pressure Components and
Threshold Detection

In marginal analysis, participants younger than 65
years of age showed increasing risk for all-cause mortality
with increasing systolic, diastolic, and pulse pressure (Fig-
ure 2), with no evidence of threshold effects for any of

these blood pressure measures (P � 0.2 for the existence of
change points). The risk trends for CVD and all-cause
mortality were similar (Figure 2), also without evidence of
change points (P � 0.2 for the existence of change points).

The marginal relationship of blood pressure with all-
cause mortality differed in participants 65 years of age and
older. Although the trend was also linear for systolic blood
pressure (P � 0.21 for the existence of a change point),
there was a J-shaped pattern for diastolic blood pressure
and pulse pressure (Figure 3). The existence of a change
point was marginally significant for diastolic blood pressure
(P � 0.09) and highly significant for pulse pressure
(P � 0.003). The change point estimate for diastolic blood
pressure was 79.0 mm Hg (95% CI, 68.6 to 88.7 mm Hg).
For pulse pressure, the change point estimate was 41.8 mm
Hg (CI, 34.3 to 48.5 mm Hg). There was no evidence of
change points for the association of systolic or diastolic
blood pressure and CVD mortality (P � 0.2 for both com-
parisons). However, for diastolic blood pressure, the non-
parametric analysis suggested a flat association below 80 to
90 mm Hg. The relationship of pulse pressure with CVD
mortality found a significant change point (P � 0.03), but

Figure 2. Blood pressure and relative risk for all-cause and cardiovascular mortality among participants younger than 65 years of age.

Risk trends were estimated from linear (solid lines) and nonparametric logistic models (dashed lines) adjusted for age, sex, race or ethnicity, smoking, total
cholesterol level, body mass index, education, use of antihypertensive medications, and history of diabetes. The bars represent the frequency distribution
of systolic, diastolic, and pulse pressure among study participants younger than 65 years of age.

ArticleBlood Pressure and Mortality

www.annals.org 4 November 2003 Annals of Internal Medicine Volume 139 • Number 9 735

it was estimated at a very low level (35.5 mm Hg, corre-
sponding to the 2.3rd percentile of the pulse pressure dis-
tribution).

DISCUSSION
Table 3 summarizes the association of blood pressure

components with mortality for the different analytical
models. Systolic blood pressure showed a consistent linear
increase in long-term all-cause and CVD mortality in
younger and elderly participants in all analyses. The rela-
tionship of diastolic blood pressure with mortality was
hockey stick–shaped in younger participants but was J-
shaped in elderly participants. This dose–response relation-
ship was evident when both systolic and diastolic blood
pressures were modeled simultaneously, but it was unclear
in marginal analyses of diastolic blood pressure. The asso-
ciation of pulse pressure with mortality was complex. In
joint analyses, increasing pulse pressure by increasing sys-
tolic blood pressure was consistently associated with in-
creased risk, while increasing pulse pressure by decreasing
diastolic blood pressure could be associated with increased
risk, decreased risk, or no change in risk depending on age
and blood pressure level. In our view, this result does not

support using pulse pressure as a single risk indicator for
prognostic and therapeutic decisions.

Our study has several limitations. Blood pressure was
based on 3 measurements taken on a single day. Even
though we tried to control for short-term variability by
estimating each participant’s underlying blood pressure,
more measurements taken over a longer period probably
would have provided more precise estimates. The effect of
these measurement errors on complex risk surfaces is un-
known, although there is evidence that measurement error
limits detecting threshold effects and biases their location
(20). Estimating change points is also limited by the size of
the study and the location of the change point, particularly
if change points are close to the extremes of the data dis-
tribution. We identified a significant change point in the
relationship of pulse pressure with CVD mortality at a very
low pulse pressure (35.5 mm Hg, the 2.3rd percentile of
the pulse pressure distribution), but its clinical implications
are uncertain because there are not enough observations
with which to reliably estimate the risk trend below the
change point. In addition, we did not have follow-up data
on blood pressure and medication patterns or data on more
newly identified risk factors, which may modify the effect

Figure 3. Blood pressure and relative risk for all-cause and cardiovascular mortality among participants 65 years of age or older.

Risk trends were estimated from linear or transition logistic models (solid lines) and nonparametric logistic models (dashed lines) adjusted for age, sex, race
or ethnicity, smoking, total cholesterol level, body mass index, education, use of antihypertensive medications, and history of diabetes. The bars represent
the frequency distribution of systolic, diastolic, and pulse pressure among study participants 65 years of age or older.

Article Blood Pressure and Mortality

736 4 November 2003 Annals of Internal Medicine Volume 139 • Number 9 www.annals.org

of blood pressure on mortality. Finally, we also did not have
data on nonfatal events, which may show a different rela-
tion to blood pressure components than mortality end points.

Evaluating the joint effect of correlated continuous
variables is sometimes based on estimating the risk for each
combination of prespecified categories of the variables and
presenting the results in 3-dimensional bar plots (3). This
approach is useful if there are enough cases to define nar-
row categories, and it assumes that the cutoffs for the cat-
egories correctly identify points of risk change. For com-
plex dose–response relationships, such as blood pressure
and mortality, smooth surfaces are a flexible alternative
that avoid categorization and make no assumption about
the shape of the association (8, 9). However, modeling
smooth surfaces is a complex process, with several method-
ologic alternatives that may affect the results. Furthermore,
the risk surface may be difficult to interpret quantitatively
(8). In this paper, we used additive surfaces, obtained by
fitting simultaneous nonparametric terms for systolic and
diastolic blood pressure and adding them to form the
smooth surface. Although we did not include an interac-
tion term in the model, additive surfaces adequately esti-
mated the joint effect of blood pressure components be-
cause of their high correlation (8, 9). To avoid overfitting,
we restricted the estimation of smooth surfaces to 8 to
9 degrees of freedom, which, in terms of the effective
number of parameters, corresponds approximately to a 3-
dimensional bar plot with 3 categories for systolic and
diastolic blood pressure.

A linear, monotonically increasing association of sys-
tolic blood pressure to mortality has been identified in a
pooled data analysis of 61 prospective observational studies

totaling 12.7 million person-years at risk (4) and in the
22-year follow-up of 342 815 participants of the Multiple
Risk Factor Intervention Trial (3). These results are com-
patible with our analysis of the marginal effect of systolic
blood pressure in NHANES II and are supported by our
analyses of the joint effect of systolic and diastolic blood
pressure. In contrast, Port and colleagues (6) reassessed the
Framingham data and, contrary to the graded increase in
risk obtained from previous analyses of this cohort (2, 21,
22), found no increased risk for death for systolic blood
pressure below certain prespecified age- and sex-dependent
thresholds. Unfortunately, they used strong model assump-
tions (linear–linear splines with the left slope constrained
to be 0) with apparently arbitrary location of the points of
risk change.

A J-shaped relationship between diastolic blood pres-
sure and CVD risk or mortality is evident in some (7, 23)
but not all prospective studies in the elderly. Several stud-
ies, however, show a flat association with low diastolic
blood pressure that may extend up to a diastolic blood
pressure of 80 to 85 mm Hg (24, 25). In fact, although the
pooled analysis of 61 prospective studies described the
marginal association of diastolic blood pressure with coro-
nary and stroke mortality as linear (4), their graphs of the
marginal effect of diastolic blood pressure are similar to our
marginal analysis of diastolic blood pressure in NHANES
II—that is, the association of diastolic blood pressure and
mortality for low diastolic blood pressure became flat with
advancing age. As we have shown in this paper, this flat
marginal association may be reflecting a J-shaped relation-
ship for diastolic blood pressure once its correlation with
systolic blood pressure is accounted for. In addition, a

Table 3. Conclusions of the Association of Blood Pressure Components with Long-Term Mortality for the Different
Analytical Models*

Blood Pressure Joint Analysis Marginal Analysis

Parametric Nonparametric

Age � 65 y
Systolic blood pressure Linear

Linear Linear

Diastolic blood pressure Hockey stick–shaped Linear Hockey stick–shaped for all-cause

mortality and linear for
cardiovascular mortality

Pulse pressure Increased risk for increasing pulse pressure by
increasing systolic blood pressure;
decreased risk or no change in risk for
increasing pulse pressure by decreasing
diastolic blood pressure

Linear Linear

Age � 65 y
Systolic blood pressure Linear Linear Linear
Diastolic blood pressure J-shaped J-shaped for all-cause mortality

and linear for cardiovascular
mortality

J-shaped for all-cause mortality
and hockey stick–shaped for
cardiovascular mortality

Pulse pressure Increased risk for increasing pulse pressure by
increasing systolic blood pressure; increased
risk, decreased risk, or no change in risk for
increasing pulse pressure by decreasing
diastolic blood pressure

J-shaped J-shaped

* The conclusions apply both to all-cause and cardiovascular mortality, unless explicitly stated.

ArticleBlood Pressure and Mortality

www.annals.org 4 November 2003 Annals of Internal Medicine Volume 139 • Number 9 737

meta-analysis of 8 trials reported that diastolic blood pres-
sure in elderly control patients with isolated systolic hyper-
tension was inversely correlated with mortality (26), a find-
ing compatible with the J-shape hypothesis. In this age
group, the J-shape phenomenon for diastolic blood pres-
sure may be related to the progressive stiffening of the
elastic arteries, which reduces subepicardial coronary flow,
particularly in the presence of coronary atherosclerosis. In
these patients, low diastolic blood pressure may precipitate
coronary events and increase mortality.

The short-term, U-shaped association of blood pres-
sure with mortality in our data is consistent with previous
studies that observe either the same pattern (27) or the
disappearance of the increased mortality in the low blood
pressure groups after controlling for concurrent illnesses
(28). This is also evident in studies that update blood pres-
sure measurements periodically instead of using baseline
measurements for risk analysis (29, 30). Despite the exclu-
sion of participants with self-reported CVD at baseline,
our short-term results might be affected by other condi-
tions (such as noncardiovascular diseases and frailty) or
occult CVD. This short-term, U-shaped relationship is
probably another source of variability in the association of
blood pressure with mortality across studies.

Our findings may have important clinical conse-
quences for risk stratification (Table 4). Several studies
have focused on identifying the main predictor of risk
among systolic blood pressure, diastolic blood pressure, or
pulse pressure. However, both systolic and diastolic blood
pressures (and implicitly pulse pressure) must be accounted
for to correctly identify the risk surface (3). Moreover, in-
terpreting pulse pressure as a standalone measurement is
complex: Although reducing pulse pressure by decreasing
systolic blood pressure is consistently associated with de-
creased risk, the overall effect of pulse pressure will depend
on both systolic and diastolic blood pressures. Clinical de-
cision making should then be based on combinations of
systolic and diastolic blood pressures rather than systolic,
diastolic, or pulse pressure alone. With current technology,
it is feasible to incorporate these complex risk surfaces into

Framingham-type risk scores to obtain a more accurate risk
profile.

The evidence for a monotonic association of systolic
blood pressure with mortality is compelling, but the
changes in the risk shape and the J-shaped curve for dia-
stolic blood pressure with advancing age are still open to
debate. We also show that the effect of pulse pressure is
complex, and we do not recommend using this measure
alone for prognostic or therapeutic decisions. The shape of
the association between blood pressure and mortality is
critical for individual treatment and public policy strate-
gies. Our results indicate that a simultaneous, rather than
marginal, analysis of systolic and diastolic blood pressure is
needed to properly assess blood pressure–related risk.

From National Center for Epidemiology, Instituto de Salud Carlos III,
Madrid, Spain; Universidad Autónoma de Madrid, Madrid, Spain; and
Johns Hopkins Medical Institutions, Baltimore, Maryland.

Grant Support: By a grant from the Instituto de Salud Carlos III (EPY
1261/02) (R. Pastor-Barriuso).

Potential Financial Conflicts of Interest: None disclosed.

Requests for Single Reprints: Eliseo Guallar, MD, DrPH, Department
of Epidemiology and Welch Center for Prevention, Epidemiology and
Clinical Research, Johns Hopkins Medical Institutions, 2024 East
Monument Street, Room 2-639, Baltimore, MD 21205; e-mail, eguallar
@jhsph.edu.

Current author addresses and author contributions are available at www
.annals.org.

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Table 4. Key Summary Points

Systolic blood pressure, diastolic blood pressure, and pulse pressure are
highly correlated blood pressure components.

Rather than assessing the effects of each blood pressure component
separately, it is more effective and appropriate to evaluate the joint effect
of all components on clinical outcomes.

In joint analysis: 1) systolic blood pressure is linearly related to all-cause and
cardiovascular mortality at all ages; 2) diastolic blood pressure shows a
“flat then increasing” risk trend in younger participants and a J-shaped
trend in elderly participants; and 3) increased pulse pressure is associated
with increased risk, decreased risk, or no change in risk depending on age
and systolic and diastolic blood pressure levels.

The complexity of the association of pulse pressure with mortality limits its
use for prognostic or therapeutic decisions.

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ArticleBlood Pressure and Mortality

www.annals.org 4 November 2003 Annals of Internal Medicine Volume 139 • Number 9 739

Current Author Addresses: Drs. Pastor-Barriuso and Damián: Epide-
miology and Biostatistics Section, National Center for Epidemiology,
Instituto de Salud Carlos III, Sinesio Delgado 6, 28029 Madrid, Spain.
Dr. Banegas: Department of Preventive Medicine and Public Health,
Universidad Autónoma de Madrid, 28029 Madrid, Spain.
Dr. Appel: Welch Center for Prevention, Epidemiology and Clinical
Research, Johns Hopkins Medical Institutions, 2024 East Monument
Street, Room 2-630, Baltimore, MD 21205.
Dr. Guallar: Welch Center for Prevention, Epidemiology and Clinical
Research, Johns Hopkins Medical Institutions. 2024 East Monument
Street, Room 2-639, Baltimore, MD 21205.

Author Contributions: Conception and design: R. Pastor-Barriuso, J.R.
Banegas, J. Damián, E. Guallar.
Analysis and interpretation of the data: R. Pastor-Barriuso, J.R. Banegas,
J. Damián, L.J. Appel, E. Guallar.
Drafting of the article: R. Pastor-Barriuso, J.R. Banegas, J. Damián,
L.J. Appel, E. Guallar.
Critical revision of the article for important intellectual content: R. Pas-
tor-Barriuso, J.R. Banegas, J. Damián, L.J. Appel, E. Guallar.
Final approval of the article: R. Pastor-Barriuso, J.R. Banegas, J. Damián,
L.J. Appel, E. Guallar.
Statistical expertise: R. Pastor-Barriuso, E. Guallar.
Obtaining of funding: R. Pastor-Barriuso.
Administrative, technical, or logistic support: E. Guallar.

E-740 Annals of Internal Medicine Volume • Number www.annals.org

Copyright © American College of Physicians 2003.