National Endowment for the Arts

Age and arts participation: 

A case against demographic destiny

Mark J. Stern

University of Pennsylvania

National Endowment for the Arts

Age and arts participation: 

A case against demographic 

destiny

Mark J. Stern

University of Pennsylvania

Based on the 2008 Survey of 

Public Participation in the Arts
Research Report #53

February 2011

National Endowment for the Arts

1100 Pennsylvania Avenue, NW

Washington, DC 20506-0001

Telephone: 202-682-5400

Prepared by Mark J. Stern 

Produced by the Office of Research & Analysis

Sunil Iyengar, Director

Sarah Sullivan, Senior Program Analyst

Other staff contributors: Tom Bradshaw, Bonnie Nichols, Ellen Grantham, Patricia Shaffer, Nona Milstead, and Michael Acton

Designed by Roman/Thayer Design Inc. 

Front Cover Photo: Dartmouth College students get down with members of Young@Heart. Photo by Kawakahi Amina

Printed in the United States of America

Library of Congress Cataloging-in-Publication Data

Stern, Mark J.

 Age and arts participation : a case against demographic destiny / Mark J.Stern.

 p. cm. -- (Research report ; #53)

 “Based on the 2008 Survey of public participation in the arts.”

 Includes bibliographical references and indexes.

 1. Arts audiences--United States. 2. Arts surveys--United States. 3. Arts--United States--Citizen participation. 

I. Title. II. Title: Case against demographic destiny.

 NX220.S74 2011

 700.973’090511--dc22

 2010054573

Available after February 24, 2011, in the PDF version of the report at www.arts.gov.

202-682-5496 Voice/TTY

(a device for individuals who are deaf or hearing-impaired)

Individuals who do not use conventional print materials may contact the Arts Endowment’s Office for 

AccessAbility at 202-682-5532 to obtain this publication in an alternate format.

This publication is available free of charge at www.arts.gov, the website of the National Endowment for the Arts.
CHAIRMAN’S NOTE

“Art works.” Those two words — with their three 

meanings — are perhaps the simplest and clearest 

declaration of what we are about at the National 

Endowment for the Arts. They first refer to works of 

art themselves, to the creations of artists. They also 

remind us that art works on audiences, to comfort, 

challenge, and inspire us. And finally, they are a bold 

reminder of the artists and arts workers across this 

country who earn wages, pay taxes, and contribute 

toward our country’s economy.

Our 2008 Survey of Public Participation in the 

Arts seems to report that art is working for fewer 

Americans, a finding that is deeply disturbing 

to all of us who care about the arts in our country. 

It reports a 5 percentage point decline in arts 

participation by Americans. 

But as I have been traveling across this country, those 

findings did not ring true with what I was seeing: 

young people signing on to Pandora and plugged into 

all manner of mp3 players; people of all ages watching 

Dancing with the Stars and So You Think You Can 

Dance; the prevalence of etsy.com and the quarter 

of a million military families who visited one of our 

920 Blue Star Museums over 4 months this summer; 

the Kindles and Nooks in front of every airport 

passenger; Netflix and YouTube allowing all manner 

of film and media, past and present, to be consumed 

anywhere. And how about Glee?

I am witness to a voracious American appetite 

for the arts that does not seem to track with a decline 

in arts participation. Luckily, Sunil Iyengar, our 

director of research and analysis, had the foresight to 

commission a series of deeper looks at this data, 

and asked fellow researchers to interrogate this data 

about the roles that technology, arts education, 

age, and personal arts creation play in American 

arts participation. 

Each of these reports individually expands and 

shades our understanding of the arts participation 

numbers. Collectively they report that one 

factor, above all others, is the prime indicator of 

arts participation — a factor not surprising to 

any Glee-ks:

Arts education in childhood is the most significant 

predictor of both arts attendance and personal arts 

creation throughout the rest of a person’s life. 

All of us who care about the arts in this country 

have to care about arts education, about exposing 

young people, early and often, to the arts in rich, 

rigorous, and repeated ways. That is largely why, over 

the past year, we funded arts education projects in 

every Congressional district in America.

The reports on technology and personal creation 

greatly expand our institutional understanding of 

meaningful arts participation.

And the report on age shows that it’s not the 

audiences who are graying, it’s our country: the age 

distribution of audiences generally mirrors the 

adult population of the United States. Baby Boomers 

continue to dominate audiences, just as we did 

in the 1980s, when we were among the youngest 

audience members.

Taken together, the 2008 Survey of Public 

Participation in the Arts with its follow-up reports, 

present the most nuanced understanding of arts 

participation that the NEA has yet presented. I am 

pleased to share these reports with you, and proud 

of the way we are expanding our understanding 

of how art works in America.

Rocco Landesman

Chairman

National Endowment for the Arts

Photo by 

Michael Eastman
6 National Endowment for the Arts

“I was so much older then; 

I’m younger than that now.”

– Bob Dylan
TABLE OF CONTENTS

11 PREFACE

15 EXECUTIVE SUMMARY

25 INTRODUCTION

27 Consumption across the life cycle

28 Civic participation

33 CHAPTER 1. BENCHMARK ARTS PARTICIPATION BY AGE AND COHORT 

33 Introduction

33 Summary measures

33 Any benchmark participation

33 Number of activities

34 Events attended

34 Analysis

36 Individual activities

36 Participation rates by age

37 Participation rates by cohort

38 Audience share 

42 Educational attainment and age: a confounding relationship

43 Multivariate analysis of benchmark activities

43 Number of activities and age

46 Number of activities and cohort

47 Conclusion

49 CHAPTER 2. PATTERNS OF PARTICIPATION

49 Introduction

49 Cluster analysis

50 Patterns of participation by age and cohort

52 The impact of declining omnivore behavior on total attendance

53 Conclusion

55 CHAPTER 3. LITERARY READING

55 Introduction

55 What factors are correlated with reading?

55 Education

56 Gender, race, and ethnicity

56 Age and cohort

58 Multivariate analysis

61 CHAPTER 4. MEDIA-BASED AND PERSONAL ARTS PARTICIPATION

61 Introduction

61 Overall patterns in media-based and personal arts participation

61 Media-based and personal arts participation by age and cohort

62 Conclusion

65 CHAPTER 5. CONCLUSION AND IMPLICATIONS

69 REFERENCES

73 TECHNICAL APPENDIX
LIST OF TABLES

34 Table 1: Percent of respondents who reported attending at least one event of a given type by year

35 Table 2: Distribution of respondents by birth cohort, 1982–2008

38 Table 3: Distribution of participants by age and year, benchmark arts activities

39 Table 4: Audience share by age, benchmark participants

40 Table 5: Jazz participation: audience share by age and year of survey

40 Table 6: Ballet participation: audience share by age and year of survey

41 Table 7: Classical music participation: audience share by age and year of survey

42 Table 8: Average age of benchmark arts participants, by activity and year

43 Table 9: Benchmark participation index, by year. General linear analysis

43 Table 10: Average number of activities. General linear model, summary statistics

44 Table 11: Average number of activities. General linear model (age included), summary statistics

46 Table 12: Average number of activities. General linear model (cohort included), summary statistics

50 Table 13: Distribution of U.S. adults by arts participation patterns, by survey year

56 Table 14: Percent of respondents reporting any reading, by gender, educational attainment, ethnicity, and year

58 Table 15: Percent of respondents who read any novels or short stories, poetry, or plays in the previous year. 

General linear model analysis, summary statistics

62 Table 16: Media-based and personal arts participation rates by age and year

62 Table 17: Media-based and personal arts participation rates by birth cohort and year
LIST OF FIGURES

17 Figure A: Indices of arts participation by age, U.S. adults, 1982–2008

17 Figure B: Percent of U.S. adults who attended different types of events, by cohort, 1982–2008

18 Figure C: Percent of U.S. adults who attended any benchmark event, by age and birth cohort, 1982–2008

20 Figure D: Percent of U.S. adults classified as omnivores, by age and birth cohort, 1982–2008

27 Figure 1: Expenditures: Nondurables

34 Figure 2: Indices of arts participation by age, U.S. adults, 1982–2008

36 Figure 3: Number of activities attended and percent attending any benchmark events, U.S. adults, 

by birth cohort, 1982–2008

36 Figure 4: Percent of U.S. adults who attended different types of events, by age, 1982–2008

37 Figure 5: Percent of U.S. adults who attended different types of events, by cohort, 1982–2008

37 Figure 6: Percent of U.S. adults who attended any benchmark event, by age and birth cohort, 1982–2008

45 Figure 7: Average number of activities attended by U.S. adults, by age, uncontrolled and controlling for 

other variables, 1982–2008

45 Figure 8: Strength of relationship between age and average activities attended by U.S. adults, uncontrolled 

and controlling for other variables, 1982–2008

47 Figure 9: Average number of events attended by U.S. adults, by birth cohort, uncontrolled and controlling 

for other variables, 1982–2008

51 Figure 10: Percent of U.S. adults classified as omnivores, by age and birth cohort, 1982–2008

51 Figure 11: Percent of U.S. adults classified as highbrow participants, by age and birth cohort, 1982–2008

52 Figure 12: Percent of U.S. adults by type of participant and number of events attended

53 Figure 13: Average number of events attended by U.S. adults, by type of participant, 1982–2008

55 Figure 14: Percent of U.S. adults who read any novels or short stories, poetry, or plays in the previous year, 

1992–2008

56 Figure 15: Percent of U.S. adults who read any novels or short stories, poetry, or plays in the previous year, 

by age of respondent, 1992–2008

57 Figure 16: Percent of U.S. adults who read any novels or short stories, poetry, or plays in the previous year, 

by birth cohort, 1992–2008

57 Figure 17: Percent of U.S. adults who read any novels or short stories, poetry, or plays in the previous year, 

by age and birth cohort, 1982–2008
10 National Endowment for the Arts
Age and arts participation: A case against demographic destiny 11

PREFACE

The National Endowment for the Arts’ Survey 

of Public Participation in the Arts (SPPA) is the 

nation’s largest periodic survey of adult involvement 

in arts and cultural activities. For more than a 

quarter-century, since the survey was first 

conducted, researchers at the Arts Endowment 

have issued summary reports and key findings to 

the public. In addition to reporting the survey 

results as a whole, the NEA has made the data files 

available to other arts and cultural researchers 

for their own analyses and publications.1

The 2008 SPPA provided a fascinating glimpse into 

changing patterns of arts participation. Since the 

prior survey period of 2001–2002, rapid advances in 

technology had enabled more access to arts events 

and arts creation through portable devices and the 

Internet. Also, in 2007–2008, many representatives 

of Gen Y (or the “Millennials”) — the second largest 

generation since the Baby Boomers — became 

eligible for taking the survey.

These factors alone would have made the 2008 

SPPA data an attractive prospect for researchers. But 

in still other ways the 2007–2008 survey year 

marked an aberration. For the first time since 1982, 

attendance rates declined for virtually all art forms 

captured by the survey; also for the first time, many 

of those declines occurred for adults 45 years or 

older — an age group that historically has accounted 

for the largest share of arts audiences.

Therefore, even before the 2008 SPPA results had 

been announced, the NEA posted the survey data 

online, to allow researchers to conduct their own 

analyses. The NEA also commissioned reports on 

five cross-cutting topics: media and technology, arts 

education, arts creation, age, and race and ethnicity.2

Results from the study of media, technology, and 

arts participation appeared in June 2010.3 For the 

remaining topics, the NEA was fortunate to obtain 

the services of four researchers or research teams 

already renowned for their work in characterizing 

trends in arts participation. Those researchers 

included Mark Stern, University of Pennsylvania, 

and separate teams at WolfBrown and the National 

Opinion Research Center (NORC) at the University 

of Chicago.

Each of these researchers has added a vitally new 

dimension to the NEA’s official summary of the 

2008 data, as published in 2009.4 This report, one of 

three to become available in 2011, is a direct result 

of their efforts. 

In their analysis, NORC researchers Nick Rabkin 

and Eric Hedberg test and ultimately confirm the 

validity of an assumption made with prior SPPA 

data, that participation in arts lessons and classes is 

the most significant predictor of arts participation 

later in life, even after controlling for other 

variables. They also show that long-term declines 

in Americans’ reported rates of arts learning align 

with a period in which arts education has been 

widely acknowledged as devalued in the public 

school system. Nor are the declines distributed 

equally across all racial and ethnic groups.

Working along quite different lines, Mark Stern 

similarly concludes that arts education is the 

most important known factor in influencing arts 

participation trends. But he is much more skeptical 

about the impact of other variables, especially age. 

Practically since the SPPA began, in 1982, there has 

been much talk about the “graying” of arts audiences. 

And while it is certainly true that the audiences 
12 National Endowment for the Arts

for many art forms tracked by the SPPA are aging 

more rapidly than the U.S. population, Stern brings 

out the sobering fact that age and generational 

cohort differences account for less than 1 percent of 

the variance in the total number of arts events that 

Americans attended over the period of 1982–2008. 

Observing that arts attendance may be far less 

dependent on age than usually considered, he 

gives the lie to the notion of “demographic destiny” 

when it comes to arts engagement.

Based on their own analysis of the SPPA data, 

Jennifer Novak-Leonard and Alan Brown advance a 

“multi-modal” framework for understanding arts 

participation. Novak-Leonard and Brown challenge 

the orthodoxy of representing overall participation 

rates merely as a function of visual or performing 

arts attendance. They suggest that a more expansive 

benchmarking system — one accounting for 

participation across three modes (arts creation or 

performance; arts engagement through media; and 

attendance at a broader array of activities) — would 

produce more relevant results for arts funders, 

arts managers, and the general public. 

The NEA’s Office of Research & Analysis already has 

begun to incorporate the ideas of these report-writers 

into its deliberations about the future of the SPPA. 

The authors offer three distinctive takes on a federal 

data source which, since 1982, has shaped much of 

the conversation about how arts and cultural policies 

and programming can engage audiences more 

effectively. By supporting independent research of 

this type, we hope to broaden the scope of that 

conversation.

Sunil Iyengar

Director, Research & Analysis

National Endowment for the Arts
Age and arts participation: A case against demographic destiny 13

NOTES

1 For example, see the National Endowment for the Arts website, 

Supplementary Materials Related to the NEA’s 2008 Survey of 

Public Participation in the Arts, www.nea.gov/research/SPPA/

index.html.

2 The report on race/ethnicity and arts participation is still in 

progress. Authored by Vincent Welch, et al. of the National 

Opinion Research Center (NORC), it will be made available 

via the NEA website in 2011.

3 This report was published in multi-media and PDF versions as 

Audience 2.0: How Technology Influences Arts Participation, 

based on research by Sameer Bawa, Kevin Williams, and 

William Dong, BBC Research & Consulting. Audience 2.0, 

Research Report #50 (Washington, DC: National Endowment for 

the Arts, 2010), available online, www.nea.gov/research/

ResearchReports_chrono.html.

4 See 2008 Survey of Public Participation in the Arts, 

Research Report #49 (Washington, DC: National Endowment 

for the Arts, 2009), available online, www.nea.gov/research/

2008-SPPA.pdf. The Executive Summary of that data appeared 

as Arts Participation 2008: Highlights from a National 

Survey (Washington, DC: National Endowment for the Arts, 

2009), available online, www.nea.gov/research/NEA-SPPAbrochure.pdf.
14 National Endowment for the Arts

The predictive powers 

of age and cohort were never 

particularly strong, and 

they declined over time.
Age and arts participation: A case against demographic destiny 15

EXECUTIVE SUMMARY

INTRODUCTION

A century ago, many Americans did not know 

exactly how old they were, so they often would 

round off their age to the nearest five years, a 

phenomenon that demographers call “age-heaping.” 

As late as 1910, for example, the U.S. Census listed 

24 percent more 20-year-olds than 19-year-olds. The 

disappearance of age-heaping and its replacement 

by age consciousness — an increased sensitivity 

to the role of age and generation on behavior — by the 

middle of the 20th century represents a profound 

change in how Americans thought about their lives 

and their relationship to the rest of society. Today, 

age consciousness has so penetrated our society 

that one’s membership in a particular generation 

or birth cohort is often offered to explain a variety 

of behaviors — from consumption decisions to 

political preferences.

Age consciousness has affected our understanding 

of arts participation as well. Differences in rates 

of arts participation of the Baby Boomers and earlier 

and later generations have been of particular 

concern. Yet we might ask: has age consciousness 

gotten out of hand? 

Specifically, does age matter to arts participation? 

The answer to that question depends on who is 

asking it. To an arts administrator who sees the 

average age of her audience increase year after year, 

it does matter, even if what she’s noting is simply the 

general aging of the population. From a sociological 

viewpoint, however, the question can be reframed: 

does knowing a person’s age or year of birth allow 

one to more accurately predict his or her level of 

arts engagement?

Age and cohort have a statistically significant —

but weak — relationship to different measures 

of arts participation. Knowing someone’s age or 

year of birth provides very little power in 

explaining his or her level of arts participation. 

In this specific sense, age does not seem to matter. 

Other influences — educational attainment 

and gender, in particular — have a much stronger 

role in explaining arts participation. 

Arts participation as consumption and civic 

engagement

Economists have long been interested in the 

influence of age, cohort, and the business cycle on 

consumption. Empirical research has produced 

general agreement that the life-cycle of individuals 

plays an important role in explaining aggregate 

trends in consumption. Consumption rises through 

one’s twenties and thirties, peaks during one’s 

forties, and then declines steadily as one ages.

Throughout this report, we classify respondents by their 

year of birth into a set of birth cohorts: 

Year of birth Birth cohort

1935–1944 World War II

1945–1954 Early Baby Boom

1955–1964 Late Baby Boom

1965–1974 Generation X

For the purpose of long-term trend analysis, we 

lack sufficient data on adults born before 1935 

and after 1975. Therefore, we have not named these 

cohorts, although they are sometimes included in 

tables and figures.
16 National Endowment for the Arts

Fears about falling rates of arts participation echo a 

broader debate over declines in Americans’ civic 

engagement. Robert Putnam has argued strenuously 

that Americans born since the 1930s have been less 

involved in community life than earlier generations. 

Other scholars — including the authors of A New 

Engagement? — have sought to counter Putnam by 

expanding the definition of engagement. They 

conclude that more conventional forms of political 

involvement rise with age, while civic engagement in 

a broader sense is highest among Baby Boomers, 

with older and younger age-groups having somewhat 

lower rates.

Certainly, it would be a mistake to ignore cohort 

effects on civic participation, but a close 

examination of data from these studies suggests 

that the influence of age and cohort may be less 

important than the authors suggest.5 The same 

observation may hold true for arts participation, if 

prior NEA research offers a clue.

In 1996, the National Endowment for the Arts issued 

a monograph exploring the influence of age and 

cohort on arts participation in the United States. 

That report, authored by Richard A. Peterson et al., 

focused on the decline of arts participation 

among Baby Boomers, compared with the preceding 

generational cohort. The study uses methods similar 

to the present report, to correct for confounding 

factors. Peterson’s analysis makes clear that other 

variables — above all, educational attainment —

have a stronger influence on arts participation than 

age and birth cohort. 

Peterson’s more important contribution to our 

understanding of arts participation patterns is 

connected with his SPPA-based analysis of cultural 

omnivores. With the first SPPA in 1982, the survey 

has included information on the musical tastes of 

respondents. In 1992 Peterson and Simkus used 

these data to test theories of cultural capital, 

particularly the correlation between individuals’ 

occupational status and their musical tastes. While 

their analysis largely confirmed the theory that 

musical tastes were a status marker, the researchers 

were surprised by one finding: respondents with 

higher occupational status not only had higher 

rates of appreciation for potentially “elite” cultural 

forms, but they had higher rates of appreciation for 

middle- and lowbrow forms as well. 

BENCHMARK ARTS PARTICIPATION BY 

AGE AND COHORT 

Age consciousness has led many scholars to 

assume that age and cohort strongly influence arts 

participation. Yet, as with civic engagement 

generally, we need to distinguish three aspects of the 

relationship of age, cohort, and arts participation. 

■ From the standpoint of description, we may find 

a pattern of relationships. Average participation 

may go up or down for older age groups or cohorts 

born earlier or later. 

■ In addition, because the Baby-Boom cohorts 

are larger than those born before or after, age has 

a compositional effect on the make-up of the 

arts audience. 

■ However, we need to distinguish these issues 

from the predictive value of age and cohort. 

When we control for other influences — especially 

the role of educational attainment — the predictive 

value of age and cohort turns out to be quite 

minor. Although they are statistically significant, 

the relationships of age and cohort to levels of 

arts participation are generally quite weak.

Summary measures

In order to get an overview of general trends, 

this report uses three measures of overall arts 

attendance: a dichotomous measure of any

involvement in the SPPA “benchmark” activities 

(attendance at jazz, classical music, opera, musical 

plays, non-musical plays, ballet, and other dance; 

and visits to art museums and galleries); the number 

of activities that a respondent did at least once; 

and the totalnumber of individual events attended, 

inclusive of frequency. (See Figure A.)

The relationships of these three summary measures 

to age exhibit the same curvilinear relationship. 

Very young and very old respondents have lower 

scores than those in the middle of the age 

distribution. The drop-off among older respondents 

appears sharper for the number of events attended 

than for the breadth of activities attended.
Age and arts participation: A case against demographic destiny 17

In aggregate, the strength of the relationships 

between age and these summary measures declined 

over time, with the most profound fall between 2002 

and 2008. While this link remained statistically 

significant, it suggests that the predictive value 

of age went through a steady decline since 

the 1980s and that this tendency accelerated 

between 2002 and 2008.

Early Baby Boomers consistently had the highest 

rate of arts participation overall. In each of 

the five survey waves, 44 percent of early Baby 

Boomers reported attending at least one benchmark 

activity during the previous year. However, the 

differences across the four central cohorts are 

hardly dramatic — ranging from 44 to 41 percent. 

The predictive powers of age and cohort were never 

particularly strong, and they declined over time. 

Age and cohort predicted between one and two 

percent of the variance in number of activities and 

any benchmark participation in the 1980s. By 2008, 

however, their predictive power had fallen to less 

than one percent. The predictive power of number 

of events never exceeded one-half of one percent.

Individual disciplines

Overall, the SPPA has tracked a precipitous decline 

in attendance at benchmark arts events since 1992. 

With the exception of attendance at musicals —

which held steady — the percent of respondents who 

reported attending at least one event in the previous 

year dropped for all of the benchmark indicators. 

EXECUTIVE SUMMARY

FIGURE A

Indices of arts participation by age, U.S. adults, 

1982-2008

Age

Proportion/average

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

Percent who attended any benchmark arts event

Average number of types of activities attended

Average number of events attended

70 and over

25–29

30–34

35–39

40–44

45–49

50–54

55–59

60–64

65–69

Less than 25

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file.

FIGURE B

Percent of U.S. adults who attended different types of 

events, by cohort, 1982–2008

Birth Cohort

Percent of U.S. adults 0%

5%

10%

15%

20%

25%

30%

Art museums

Other dance

Ballet

Plays

Musicals

Opera

Classical

Jazz

After 1975

Generation X

Early Baby Boom

Late Baby Boom

Before 1934

World War II

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file
18 National Endowment for the Arts

Jazz has historically been more youth-oriented. 

Respondents in their twenties have generally 

reported participation rates in the mid-teens, but 

those above the age of 50 have shown little 

inclination to participate. For other activities, the 

participation-age profile has tended to be curvilinear 

— rising through middle age and then declining as 

respondents reach old age; with some activities 

(like art museum attendance) peaking among those 

in their forties and others (like classical music and 

opera) peaking a bit later. All forms of participation 

declined sharply after the age of 70. All of these 

relationships are “statistically significant,” but for 

none of the benchmark measures did age explain 

more than 1 percent of the variance. Statistical 

significance estimates the likelihood that a 

relationship found in a sample will also be found in 

the general population from which the sample 

is drawn. It is a function of the strength of a 

relationship and the size of the sample. In studies 

using a large sample — like the SPPAs — one 

often finds statistically significant results even 

though the relationships are quite weak.

Overall, cultural participation declined steadily 

across the four central cohorts. Jazz attendance 

peaked at 14 percent among late Baby Boomers and 

then fell to 10 percent. For other disciplines, either 

the World War II or early Baby-Boom cohort had 

the highest rate. For five of the seven disciplines 

for which we have data since the 1980s, the 

overall trend was downward. The classical music 

attendance rate fell by 0.2 percentage points per year6

while attendance rates for musicals and plays 

fell by 0.1 percentage points per year among the four 

cohorts. The jazz attendance rate rose among the 

first three cohorts, but then fell among Generation X 

respondents. Only art museum attendance held 

its own across the four cohorts, varying between 

25 and 28 percent of respondents.

Audience share by age

Another way to look at the impact of age and cohort 

on arts participation is to track the composition of 

the audience for benchmark activities over time. As 

an earlier report noted, the arts audience, like the 

population as a whole, has grown older over the past 

decade (NEA 2009b).

Much of the shift of audience toward older age 

groups resulted from the aging of the population. 

If we correct for this factor, then audience-share 

figures show a less dramatic aging pattern. For 

example, the decline in the participation index for 

young adults was only from 28 to 25 percent, using 

corrected figures, while the increase in the older 

middle-age audience was less than one percent 

(23.6 to 24.3 percent). The increase in the older-adult 

audience remained a substantial 5 percentage points.

Overall, audience shares in 2008 more closely 

tracked the distribution of the entire population 

in 2008 than it had earlier. While the aging of 

the arts audience was real, it was less a product of 

changes in people’s tastes and behavior, than 

of the aging of the overall population. With 

a few exceptions — especially jazz and ballet —

changes in audience share by age groups for arts 

activities tracked changes in the composition 

of the population.

FIGURE C

Percent of U.S. adults who attended any benchmark 

event, by age and birth cohort, 1982–2008

Age

Percent of U.S. adults

0%

10%

20%

30%

40%

50%

60%

After 1975

Generation X

Late Baby Boom

Early Baby Boom

World War II

Before 1935

70 and over

65–69

60–64

55–59

50–54

45–49

35–3

40–44

9

30–34

25–29

Less than 25

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file.
Age and arts participation: A case against demographic destiny 19

Educational attainment and age: a confounding 

relationship

Age has a statistically significant, but weak 

relationship to our summary measures of arts 

participation. However, we can judge the 

importance of this relationship only in comparison 

to other variables that might influence participation.

As virtually all research on participation has 

demonstrated, educational attainment is the 

strongest predictor of cultural engagement 

(DiMaggio and Ostrower 1992; Peterson et al. 2000). 

Not only is education strongly correlated with 

arts participation, but before 2008, it had a strong 

relationship with age as well. During the 1980s, 

individuals with less than a high school diploma and 

those with a graduate degree were considerably 

older than those with either a high school degree or 

some college. 

Multivariate analysis allows us to answer two 

questions. First, does adjusting for age or cohort 

change our conclusions about the rapid decline 

in benchmark participation over time? Second, if 

we adjust for other factors, how strongly do age 

and cohort influence benchmark participation?

The year-to-year declines in the participation 

indices were unaffected by adjusting for cohort or 

age. For example, controlling for other variables, 

including gender, marital status, educational 

attainment, ethnicity, and year of survey, attendance 

fell by 9 percentage points between 1992 and 2008, 

three percentage points more than the uncontrolled 

figure. The decline in benchmark attendance 

was not the result of changes in the influence of 

age or cohort.

Controlling for other variables, age and cohort 

effects — which were already quite weak influences 

— grew a bit weaker. They remain statistically 

significant, but not strong determinants of these 

measures of arts participation.

PATTERNS OF PARTICIPATION

In this section we examine how age and cohort 

influence patterns of participation — that is, 

how individuals mix and match different types 

of participation. In particular, we examine 

two patterns that have been of interest to Peterson 

and other researchers. One is “highbrow,” the 

tendency of people who are active in one high-status 

cultural form to be active in one or more other 

high-status form. The other is “omnivore.” Following 

Richard A. Peterson, we define omnivores as 

individuals who are involved in both “highbrow” 

and middle- or lowbrow activities. For example, an 

omnivore might report they they attended highbrow 

disciplines such as ballet and classical music, as well 

as lesser-status art forms such as musicals, while 

a highbrow would restrict his or her attendance to 

higher-status events like art museums, ballet, and 

classical music. 

Admittedly, these categories are largely subjective. 

Yet they can shed light on the variance in arts 

participation rates for “benchmark” arts events 

tracked by the SPPA.

Approximately twice as many respondents were 

classified as omnivores than highbrows. Omnivore 

representation declined from 15 percent in 1982 to 

10 percent in 2008. Highbrows represented just over 

7 percent of all respondents in 1985 and 1992 and 

then declined to 5.3 percent in 2008. 

The omnivore pattern of cultural participation is 

associated with distinctive age and cohort features. 

First, the proportion of cultural omnivores tends 

to decline with age. Younger adults are more likely to 

be omnivores than older adults. Second, omnivores 

are more likely to have been born between 1935 

and 1954. The omnivore pattern is most associated 

with the World War II and early Baby-Boom cohorts 

than with later groups.

Highbrow participation was not as strongly 

associated with age. With the exception of an 

increase in highbrow participation among older 

members of the World War II cohort, the highbrow 

rate remained relatively flat within each cohort. 

Only those born after 1975 showed a distinctly 

lower rate of highbrow participation.

EXECUTIVE SUMMARY
20 National Endowment for the Arts

The impact of omnivore decline on total 

attendance

Omnivores represent the most active segment of 

the entire arts audience. They go to more types of arts 

activities than other groups, and they go to more 

individual events than others. In fact, although the 

omnivores represented only 13 percent of the 

population, they accounted for 58 percent of all 

events attended between 1992 and 2008. 

Between 2002 and 2008, a double blow hit cultural 

participation. First, the proportion of the population 

that we characterize as omnivores — individuals 

who attend a variety of different cultural forms 

— dropped sharply. At the same time, like the rest of 

the population, the number of events that omnivores 

attended fell as well, by more than one event 

per respondent. Taken together, the decline of 

omnivores’ share of the population and their drop 

in average events attended represented 82 percent 

of the entire decline in attendance at benchmark 

events between 2002 and 2008.

LITERARY READING

In this chapter we examine the variables on literary 

reading that have been included in the SPPA 

since 1992. The yes/no questions ask whether the 

respondent had read any novels or short stories, 

poetry, or plays during the previous 12 months. 

Since 1992, the reading rates of Americans have 

declined (NEA 2004, 2007). In 1992, 52 percent of 

SPPA respondents reported reading a novel or short 

story in the previous year. Ten years later, this 

figure had fallen to 45 percent. Although it rose to 47 

percent in 2008, the percentage was still below that 

for 1992 (NEA 2009b). In contrast, poetry and play 

reading both fell from survey to survey. The 2008 

rates for these two activities were less than half what 

they had been in 1992.

Age and birth cohort have had a relatively minor 

influence on reading rates. Educational attainment, 

gender, and ethnicity are stronger predictors of 

reading. In 1992, middle-aged adults were more likely 

to report any reading than older adults. The highest 

rates were among those in their forties — at around 

60 percent — while those in their twenties and 

sixties had rates nearer 50 percent. Rates dropped 

across the board in 2002, although the declines 

among Americans in their fifties were much smaller 

than for other age groups. 

The World War II cohort (1935–44) had the lowest 

reading rate in all three years, and the early Baby 

Boomers had the highest. The late Baby Boomers 

rate, which fell from 56 percent in 1992 to 49 percent 

in 2008, was closer to that of the World War II 

cohort in all three years. This finding is consistent 

with age-related data from the SPPA. That data 

suggest that as the early Baby Boomers aged, their 

reading rate tended to rise, while the age group 

behind them — populated by the late Baby Boomers 

— tended to fall.

FIGURE D

Percent of U.S. adults classified as omnivores, by age 

and birth cohort, 1982–2008

Age

Percent of U.S. adults

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

After 1975

Generation X

Late Baby Boom

Early Baby Boom

World War II

Before 1935

70 and over

65–69

60–64

55–59

50–54

45–49

35–3

40–44

9

30–34

25–29

Less than 25

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file.

Note: See text and appendix for explanation of classification procedure.
Age and arts participation: A case against demographic destiny 21

MEDIA AND PERSONAL PARTICIPATION

In this chapter we turn to two topics to fill in our 

portrait of participation: consumption of cultural 

content through media,7 and personal performance 

or creation of arts.8 The core conclusions of our 

analysis are similar to those we have reached 

in other aspects of this project. The most important 

determinants of participation within survey years 

are educational attainment and gender. While 

age and cohort in most cases have a statistically 

significant effect on participation, the magnitude 

of the effect is quite modest. Furthermore, when we 

control for other variables, even this apparent 

effect-size is reduced. 

Overall, media-based arts engagement and personal 

performace or creation of art have experienced 

the same declines as live attendance since 1992. 

That year, 58 percent of respondents reported some 

media-based participation and 55 percent some 

form of personal participation. The proportion of 

respondents reporting media participation fell 

sharply after 1992, from 63 to 41 percent in 2008. 

Personal participation fell from 56 in 1992 to 44 

percent in 2002 and 42 percent in 2008.

Between 1992 and 2008, neither media nor personal 

participation exhibited a distinctive relationship 

to age. Media participation was lower among those 

under the age of 25 and over the age of 70; for other 

age groups, however, it hovered between 58 and 

54 percent across the three SPPA years. Personal 

participation exhibited a somewhat stronger 

relationship. It was lower among respondents in 

their twenties, rose to about 48 percent among age 

groups between 40 and 64, and then fell off slightly. 

Age differences explained less than one-half of one 

percent of the variation in arts participation rates, 

for both media-based and personal participation.

Cohort, too, had little influence on either media or 

personal participation. The youngest and oldest 

cohorts had the lowest rates, while the World War II 

and the two Baby-Boom cohorts had the highest 

rates. Generation X’s media and personal 

participation rates were about five percentage points 

below those of the Baby-Boom generations.

CONCLUSION AND IMPLICATIONS

Given the various dimensions of arts engagement 

examined in this report, it is striking how consistent 

the findings are. For each dimension, we discovered 

that age and cohort have statistically significant, but 

extremely modest impacts on levels of participation. 

Indeed, when educational attainment and gender are 

taken into consideration, the roles of age and cohort 

fade even more. 

This is not to say there are no patterns related to age 

and cohort. It appears that, overall, Americans born 

between 1935 and 1954 are more likely to participate 

in arts-related activities than those born since 1955. 

The strongest relationship noted in this report tied 

these cohorts to the omnivore cultural pattern. The 

decline of omnivores is a major cause of the decline 

in overall arts attendance since 1992. Generally, 

participation is higher among middle-aged persons 

than among very young adults and older Americans.

The interest with age and cohort has as much to do 

with the future as with the past. If age and cohort are 

strong predictors of arts participation, it is reasoned, 

then we may be able to better predict the future of 

cultural audiences by looking at younger cohorts and 

examining their preferences. The life-cycle literature 

with its conception of life trajectory supports this 

line of reasoning. If younger adults get into the habit 

of attending events, it is hoped, they will keep this 

habit as they age. Viewed this way, the decline of 

youth interest in a number of activities — not only 

classical music, but also jazz — may indicate that the 

future of these activities is in jeopardy.

This study suggests that such reasoning is wrong on 

two counts. First, the power of age and cohort are 

limited for explaining past and current patterns of 

participation. Factors that explain a few thousandths 

of the variation in participation will hardly define 

the future of art in America for either good or ill.

EXECUTIVE SUMMARY
22 National Endowment for the Arts

More importantly, this approach underestimates 

how broader changes in personal life are influencing 

civic and arts participation. The middle of the 20th 

century represented the high-point of processes that 

standardized the life-course of individuals. After 

1970, this uniformity gave way to a new diversity of 

personal decision-making. The transition to adulthood became more protracted and characterized by 

diversity and autonomy. Models for growing old also 

varied; workers no longer retired in their early and 

mid-sixties, and the “empty nest” life-cycle stage 

went from an exceptional to a typical household form 

for older adults.

This same pursuit of flexibility and informality has 

influenced the art world as well. If we are correct 

that the cultural omnivore is in decline, it may be 

because the omnivore represented a transitional 

stage in our cultural development. After all, the 

omnivore concept originated with the surprise that 

Peterson and his collaborators experienced in 

discovering that the straitjacket of cultural capital, 

which they had expected to define musical tastes, 

was no longer as tight as it had been (or was 

presumed to have been). Cultural participants were 

no longer willing to let their social status define 

what cultural tastes were acceptable for them. 

Although the omnivore — as measured by the SPPA 

— may be foundering, this quest for a more 

personal, flexible, and protean approach to cultural 

engagement appears to be very much alive.

The findings from this study suggest that age and 

cohort are not destiny. The ability of established or 

emerging arts groups to attract participants will 

have less to do with the age distribution of the 

population than with their ability to connect to the 

creative aspirations of their potential audiences. 
Age and arts participation: A case against demographic destiny 23

NOTES

 5 “The Strange Disappearance of Civic America,” Robert D. 

Putnam, The American Prospect 24 (Winter 1996), 44; and 

A New Engagement? Political Participation, Civic Life, and 

the Changing American Citizen, Cliff Zukin, Scott Keeter, 

Molly Andolina, Krista Jenkins, and Michael X. Delli Carpini 

(Oxford and New York: Oxford University Press, 2006).

6 Thus, between 2002 and 2008, the proportion of U.S. adults who 

attended classical music performances fell by 1.2 percentage 

points.

7 This mode of arts participation includes engaging with art 

through the Internet or watching or listening to recorded or live 

broadcasted arts performances on TV, radio, or on the computer, 

including watching or listening on portable media devices such as 

an iPod, cell phone, or portable DVD player.

8 This includes personal arts activities such as: working with 

pottery, ceramics, jewelry or any leatherwork or metalwork; 

weaving, crocheting, quilting, needlepoint, or sewing; making 

photographs, movies, or video tapes as an artistic activity; 

painting, drawing, sculpture, or printmaking; creative writing 

such as stories, poems, or plays; owning original pieces of art; 

playing a musical instrument; performing or rehearsing jazz, 

classical music, or opera; singing or acting in a musical play; 

acting in a non-musical play; singing with a chorale, choir, or glee 

club; or dancing ballet or other dance such as modern, folk, tap, 

or Broadway-style.

EXECUTIVE SUMMARY
24 National Endowment for the Arts

Knowing someone’s age or 

year of birth provides very little 

power in explaining his or 

her level of arts participation.
Age and arts participation: A case against demographic destiny 25

INTRODUCTION

A century ago, many Americans did not know 

exactly how old they were, so they often would 

round off their age to the nearest five years. As 

late as 1910, the U.S. Census listed 24 percent more 

20-year-olds than 19-year-olds — a phenomenon 

demographers refer to as “age-heaping.” By the 

middle of the 20th century, age-heaping had virtually 

disappeared. Age-heaping is not simply a technical 

data problem; its decline represented a profound 

change in how Americans thought about their lives 

and their relationship to the rest of society. Age 

consciousness has so penetrated our society that 

one’s membership in a particular generation or 

birth cohort — a group defined by the years in 

which they were born — is now often offered as an 

explanation of a variety of behaviors — from 

consumption decisions to political preferences 

(Katz and Stern 2006).9

The size of the Baby-Boom generations born in the 

20 years after the end of World War II are largely 

responsible for this heightened use of “generation” 

as the template for understanding social change. 

As Baby Boomers aged, their developmental 

challenges became the agenda for the entire society, 

whether erecting new school buildings in the 

1950s, accommodating labor force entrants in the 

1970s, or preparing for their retirement since the 

1990s (Easterlin 1978). Indeed, other cohorts have 

had to scramble to keep up with the Baby Boomers 

by defining their own identities — the “greatest 

generation,” Generation X, and the Millennials —

in contrast to Baby Boomers.

Still, the importance of age emerges in multiple, 

sometimes contradictory, ways. Sociologists often 

see people’s lives as a developmental trajectory in 

which each generation follows a similar course. 

At the same time, we know that history — the impact 

of external events on behavior — can alter the 

trajectory of particular cohorts. For example, the 

Great Depression had a profound impact on 

the generation that came of age during the 1930s, 

an impact that could be observed decades later 

(Elder 1974). Finally, age has a compositional effect 

on behavior. If a particularly large generation 

engages in a particular activity — for example, 

delaying marriage or having more children — this 

tendency can have a disproportionate effect on 

overall rates. 

Age consciousness has had an impact on our 

understanding of arts participation as well. At 

least since Peterson et al. (1996), trends in arts 

participation have been seen as a function of cohort 

and age. “Life-course influences,” they write, 

“have a direct and tangible bearing on how often 

individuals are able to attend live artistic 

performances and exhibits, and these effects vary 

with age.” Differences in rates of arts participation of 

the Baby Boomers and earlier and later generations 

have been of special concern.

This tendency to interpret changes in cultural 

participation through the lens of age and cohort 

continued with the early interpretations of the 2008 

Survey of Public Participation in the Arts (SPPA). 

The first overview of the data focused on the 

aging of the arts audience and the decline in arts 

participation among both young and middle-aged 

adults (NEA 2009a).
26 National Endowment for the Arts

But the importance of age or cohort is an empirical 

question. We need to ask if demography really 

is destiny. Given the host of other influences on 

behavior, should we sustain the argument that 

one’s year of birth defines behavior, even partly? 

Indeed, there is a certain irony in the association of 

the Baby-Boom generation with the rise in ageconsciousness. While it is true that the Baby Boomers 

— at a time when they had considerably less weight 

and more hair — called on themselves to “not trust 

anyone over 30,” it was this very generation that 

spawned an identity politics, which highlighted the 

role of race, ethnicity, gender, social class, and sexual 

orientation. Given the vast literature that supports 

the influence of these factors on social behavior, 

we may want to retain a healthy skepticism about age 

and birth cohort’s influences on social behavior.

Those who argue that age and cohort have a strong 

influence on social behavior are, to some extent, 

swimming against the tide. A review of life-course 

behavior over the 20th century leads to the 

conclusion that the call to “act one’s age” has lost 

much of its power. At mid-century, it is true, the 

timing of life events — such as entering the work 

force, getting married, or having children — became 

more standardized. But at least since the 1970s, that 

standardization has given way to a new flexibility 

in life events. 

So, does age matter to arts participation? The answer 

to that question depends on who is asking it. To 

an arts administrator who sees the average age of 

her audience increase year after year, it does, 

even if what she’s noting is primarily the aging of 

the general population.

From a sociological point of view, however, the 

question can be reframed. We should ask if a 

person’s age or year of birth has an influence on 

decisions about arts participation. Specifically, 

does knowing a person’s age or year of birth allow 

one to better predict levels of arts engagement?

Age and cohort have a statistically significant 

relationship to different measures of arts 

participation. This report suggests, however, that 

those relationships are consistently quite weak. 

Knowing someone’s age or year of birth provides 

very little power in explaining his or her level of arts 

participation. In this specific sense, age does not 

seem to matter. Other influences — educational 

attainment and gender, in particular — have a much 

stronger role in explaining arts participation. 

In addition, while the present analysis confirms a 

dramatic drop in levels of arts participation over 

time, age and birth cohort shifts were not the cause 

of this decline.

Given the minor influences that age and cohort have 

on participation, why has so much attention been 

paid to them? One answer to this question is the 

“white bear” phenomenon in social psychology. This 

experimental approach to “thought suppression” 

asks subjects to not think about some trivial image 

(white bears, pink rhinoceros, etc.). Researchers find 

that such an instruction generally leads an increase 

in the subject’s attention to that image (Wegner 1989).

So it is with generation. The template of generational 

and age difference, which a century ago barely 

existed, is now so strong that we apply it to 

phenomena to which it has little relevance. And 

yet, as we become more sophisticated in our 

understanding of the forces that do influence arts 

participation, we may wish to reassess this 

automatic response and place age and cohort in 

their proper, more modest, perspective.

This report begins with a review of existing socialscience literature on age and cohort. It suggests that 

arts participation can be seen from at least two 

perspectives. On the one hand, it might be seen as a 

consumption decision — deciding to buy a ticket 

to a performance or exhibition. On the other hand, 

it can be viewed as a form of civic engagement —

a way of participating in community life. Both 

of these perspectives offer ways of thinking about 

how age influences arts participation.
Age and arts participation: A case against demographic destiny 27

After the literature review, this report then examines 

specific forms of arts participation. It begins with 

an examination of the benchmark standards of arts 

participation that form the core of the NEA’s Survey 

of Public Participation in the Arts (SPPA). It then 

turns to patterns of participation, in particular, 

using Peterson’s concepts of omnivore and highbrow

patterns of participation to examine SPPA data. 

Subsequent sections of the report focus on reading, 

media participation, and personal participation 

in the arts.

Whatever the form of participation, we conclude 

that age and cohort have two broad influences. The 

shifting size of different generations — especially 

the large size of the Baby-Boom generation and the 

smaller size of Generation X — has had an impact 

on the composition of arts audiences. At the 

same time, age and cohort have a weak impact on 

the likelihood that a respondent will participate 

in the arts.

The relationship of age to arts participation is 

informed by previous work in economics and 

sociology. For economists, arts participation is 

primarily a consumption decision. For sociologists, 

arts participation is often seen as a form of civic 

engagement. Existing literature on how age 

influences consumption and civic engagement 

provides a useful starting point for thinking through 

the relationship between age and arts participation. 

CONSUMPTION ACROSS THE LIFE CYCLE

Economists have long been interested in the 

influence of age, cohort, and the business cycle on 

consumption. Empirical research has produced 

general agreement that the life-cycle plays an 

important role in explaining aggregate trends in 

consumption. Consumption rises through one’s 

twenties and thirties, peaks during one’s forties and 

then declines steadily as one ages (Attanasio and 

Browning 1995). (See Figure 1, below.)

The economics literature makes two points of value 

to the present investigation. First, it finds a 

relatively strong relationship between education and 

consumption. On average, by the time an adult is in 

her forties, her annual expenditures will be about 

25 percent higher than when she was in her early 

twenties. However, people with a college education 

are likely to see their consumption peak at nearly 60 

percent above its starting point, while those with less 

education will see their expenditures peak at only 

about 10 percent above its starting point. Second, 

economists have generally concluded that age has, at 

best, a modest influence on aggregate consumption. 

It is not irrelevant, but hardly the strongest influence 

on levels of consumption (Fernandez-Villaverde 

and Krueger 2007).

FIGURE 1

Expenditures: Nondurables

Age

1982–84

$800

$1000

$1200

$1400

$1600

$1800

$2000

20 30 40 50 60 70 80 90

Source: Fernandez-Villaverde and Kruger 2007.

INTRODUCTION
28 National Endowment for the Arts

CIVIC PARTICIPATION

Virtually since Alexis de Tocqueville spotlighted 

the importance of civic engagement to the strength 

of our democracy, Americans have used levels 

and intensity of civic involvement as a measure 

of our overall social health. For much of that 

time, a narrative of decline has dominated this 

conversation. Today’s young people, it has been 

argued over and over again, are not as responsible 

and do not care as much as earlier generations. 

In recent years, however, the Tocquevillian question 

— how an active civil society makes democracy 

work — has gained academic interest. Both in the 

United States and abroad, scholars have pointed to 

the importance of civil society as the foundation of 

prosperous and democratic social life.

No scholar is more responsible for this equation of 

civic health, democratic institutions, and economic 

prosperity than Robert Putnam. In Making 

Democracy Work (Putnam 1993), Putnam argued 

that inter-regional patterns of civic engagement in 

Italy were the best predictor of economic and 

political development over the past five centuries.

He then turned to the United States where, 

in Bowling Alone (Putnam 2000), he argued 

that decline was the dominant pattern of civic 

participation, from 4-H clubs to the Kiwanis.

Putnam concluded that the decline in civic 

engagement was the result of generational shifts —

a cohort effect. Using data from the General Social 

Survey (GSS), Putnam argued that a “long civic 

generation” including people born before World War 

II had propped up participation rates for a long 

time, but that as it had aged, younger birth cohorts 

exhibited progressively lower rates of engagement.

Putnam believes that a variety of social phenomena 

— civic involvement, social trust, voting, and reading 

newspapers — are all involved in the generational 

shift. The consistency of this pattern led Putnam to 

conclude:

By any standard, these intergenerational 

differences are extraordinary. Compare, for 

example, the generation born in the early 1920s 

with the generation of their grandchildren born 

in the late 1960s. Controlling for educational 

disparities, members of the generation born in the 

1920s belong to almost twice as many civic 

associations as those born in the late 1960s 

(roughly 1.9 memberships per capita, compared 

to roughly 1.1 memberships per capita). The 

grandparents are more than twice as likely to 

trust other people (50–60 percent compared with 

25 percent for the grandchildren). They vote at 

nearly double the rate of the most recent cohorts 

(roughly 75 percent compared with 40–45 

percent), and they read newspapers almost three 

times as often (70–80 percent read a paper daily 

compared with 25–30 percent). And bear in mind 

that we have found no evidence that the youngest 

generation will come to match their grandparents’ 

higher levels of civic engagement as they grow 

older (Putnam 1996: 44).

Zukin et al. (2006) sought to counter Putnam in their 

study of civic engagement by widening the forms 

of civic involvement examined. Their study focused 

on four cohorts: Dutifuls (people born before 

the end of World War II); Boomers (born between 

1945 and 1964); GenXers (born between 1965 and 

1976); and DotNets (born after 1976). Based on the 

National Civic Engagement Survey 1, conducted in 

2002, the authors examined four dimensions of 

engagement — electoral engagement, political voice, 

cognitive engagement, and civic engagement.10

They concluded that more conventional forms of 

political involvement rose with age, while civic 

engagement — the form most relevant for this study 

— was highest among Baby Boomers, with older and 

younger groups having somewhat lower rates. 
Age and arts participation: A case against demographic destiny 29

The authors concluded that among the oldest age 

group, nearly a third of respondents were “political 

specialists,” meaning they were politically, but not 

civically, involved. Younger age groups — GenXers 

and DotNeters — had higher numbers of “civic 

specialists,” but fewer who were both politically and 

civically involved. Although the authors argued 

that “simple claims that today’s youth...are apathetic 

and disengaged from civic life are simply wrong,” 

their data shows a much higher number of totally 

disengaged respondents among the young than 

among older groups (Zukin et al, 2006: 189). 

Putnam and Zukin et al. take opposing views of the 

narrative of civic decline, but they agree that 

generations matter. It is curious, however, that in 

both cases, the authors did not report standard 

summary statistics to support their contention that 

cohort or age is an important determinant of 

participation. A re-analysis of their data, moreover, 

demonstrates that age and cohort’s influences on 

participation are much more modest that the authors’ 

assertions would suggest.

Do the data support Putnam’s assertion that cohort 

differences are “extraordinary”?11 A multivariate 

analysis supports Putnam’s assertion that, 

after education, cohort had the largest impact on 

memberships, but the magnitudes of the two types 

of impact are quite different. In fact, educational 

attainment had a partial eta-square of 0.12, 

indicating that educational attainment “explains” 

12 percent of the variance in group memberships. 

Cohort’s partial eta-square was 0.007, about 

one-seventeenth as strong as education.12

This re-analysis of the GSS data parallels our 

analysis of the SPPA in a number of important ways. 

First, educational attainment is by far the most 

important influence on participation. Second, age 

and cohort have statistically significant influences 

on participation. Finally, although statistically 

significant, age and birth cohorts’ influences are 

decidedly modest. “Extraordinary” is ultimately in 

the eyes of the beholder, but a reasonable person 

might conclude that a more modest characterization 

is in order.

The National Civic Engagement Survey on which 

Zukin et al. based their conclusions was a single 

survey, so it is impossible to differentiate age 

and birth cohort effects. Still, as with Putnam, a 

secondary analysis of the data suggests that age 

had relatively modest explanatory power.13 The 

respondent’s age/cohort explained 1 percent of 

variance in the scale when controlling for education. 

For the sake of comparison, the explanatory power 

of educational attainment was 8 percent in the same 

analysis.

Indeed, variation in participation by education 

within generational categories tended to dwarf the 

generation differences, except among the very 

youngest respondents (many of whom may 

still finish a college degree). For example, on a 

4-point civic engagement scale, among Boomers, 

the college-educated had an average score of 1.9, 

high-school graduates a score of 0.9, and those 

without a high-school degree, a score of 0.5. The 

range of generational scores — from 0.9 among 

the older respondents to 1.3 among Boomers — was 

much smaller.14

These two studies of civic participation have 

important lessons for the study of arts participation. 

The same forces that shape civic engagement 

influence arts participation. In particular, the 

dominant role of educational attainment in 

both forms of participation frames the far more 

modest influence of age and cohort. The most 

important lesson to draw from this analysis is to 

resist the reflex to see social differences through a 

generational lens. It would be a mistake to ignore 

cohort’s influences on participation, but at the same 

time, to view it as dominant hardly seems justified. 

Yet, as these important studies suggest, the 

generational narrative is difficult to resist.

INTRODUCTION
30 National Endowment for the Arts

This same tendency is apparent in a previous full 

monograph devoted to the influence of age and 

cohort on arts participation in the United States — a 

1996 study for the National Endowment for the Arts.15

Authored by Richard A. Peterson et al., the report 

focused on the decline of arts participation among 

Baby Boomers compared to the cohort before them. 

It uses methods similar to the present study, to 

correct for confounding influence. The analysis 

makes it clear that other variables — above all, 

educational attainment — influence rates of cultural 

participation more than one’s generational identity. 

The report was important in establishing the 

waning involvement in many art forms by younger 

respondents, a pattern that was obscured to some 

extent by the bulge of middle-aged participants 

because of the Baby Boom. 

Peterson’s more important contribution to our 

understanding of patterns of arts participation is 

associated with his analysis of cultural omnivores. 

Since the first SPPA in 1982, the survey has included 

information on the musical tastes of respondents. 

In 1992, Peterson and Simkus used these data to test 

theories of cultural capital, particularly the 

correlation between individuals’ occupational status 

and their musical tastes. While their analysis 

largely confirmed the theory that musical tastes are a 

status-marker, the researchers were surprised by one 

finding: respondents with higher occupational status 

not only had higher rates of appreciation for the 

cultural forms that the researchers termed “elite,” but 

those respondents had higher rates of appreciation 

for “middle-“ and “lowbrow” forms as well.

These findings led Peterson to articulate the theory 

of the cultural omnivore:

In effect, elite taste is no longer defined simply 

as the expressed appreciation of the high art 

forms and a corresponding moral disdain of, or 

patronizing tolerance for, all other aesthetic 

expressions. Insofar as this view is correct, 

the aesthetics of elite status are being redefined 

as the appreciation of all distinctive leisure 

activities and creative forms along with the 

appreciation of the classic fine arts. Because 

status is gained by knowing about, and 

participating in (that is to say, by consuming) 

many if not all forms, the term ‘omnivore’ seems 

appropriate for those at the top of the emerging 

status hierarchy (Peterson 1992: 252).

One consequence of the omnivore thesis is to suggest 

that in making sense of arts participation, we should 

examine both rates of participation and patterns 

of participation as well. The variety of activities in 

which individuals choose to engage may be as 

important as the number of performances or exhibits 

they attend. As we shall see, these patterns of 

participation are associated with distinctive age and 

cohort influences. 
Age and arts participation: A case against demographic destiny 31

NOTES

9 Throughout this report, the terms cohort and birth cohort are 

used interchangeably.

10 Zukin and his collaborators differentiate four types of 

engagement. Civic engagement focuses on an involvement in 

community affairs, including: working on community problems; 

volunteering; group membership; and fundraising for charities. 

Political engagement refers to traditional political activities 

such as voting; persuading others; displaying buttons, signs, and 

stickers; making campaign contributions; and volunteering on a 

political campaign. Public voice — taking public stands on issues 

— includes: contacting officials; contacting the print or broadcast 

media; and participating in political demonstrations, petition 

drives, and boycotts, or canvassing for a social group. Finally, 

cognitive engagement refers to an intellectual involvement 

with issues, including: tracking public policy issues in the news; 

talking with friends and family members about political issues; 

knowledge of politics; and attention to the news media. A New 

Engagement? Zukin et al., 57–58. 

11 The source of Putnam’s measure of civic engagement is a 

series of data on organizational memberships that has been 

collected by the General Social Survey (GSS) since the 1970s. 

“Strange Disappearance” Putnam, 34-48. The GSS asked 

whether respondents were members of 16 different categories of 

organizations ranging from professional associations and unions 

to hobby clubs to veterans’ groups. Putnam used a summary 

measure that counts the number of types of memberships as his 

core indicator of participation.

Of the 16 different types of organizations, only five actually 

recorded declines between the 1970s and the first decade 

of this century: labor unions, fraternal organizations, church 

membership, veterans’ groups, and farm organizations. Over 

the same period, several types of memberships, including 

professional associations, literary groups, hobby groups, 

and school and youth organizations, recorded relatively 

healthy increases. 

Of the groups recording declines, four account for the bulk of the 

decline in participation. The decline in membership in religious 

organizations alone accounted for more than 40 percent of the 

decline in overall membership. Because church membership 

was so common (more than half of respondents), the modest 

drop in participation — from 54 percent in the 1970s to 51 percent 

in the 2000s — had a large impact on the overall indicator. The 

drop in two other forms of participation — farm organizations 

(from 6 to 4 percent) and labor unions (23 to 19 percent) —

represent large structural changes in the economy, rather 

than the disappearance of civic America. Along similar lines, 

the decline in veterans’ organizations is primarily a result 

of the impact of a declining number of World War II veterans. 

These four types of participation — church, farm, labor 

unions, and veterans — represent nearly 100 percent of the 

decline in the summary measure. So the overall decline in 

civic participation comes down to drops in religious affiliation, 

shifts in the economy, and the shrinking number of active 

World War II veterans. 

12 See the Technical Appendix for an explanation of the summary 

statistics. Another way of estimating the explanatory power of a 

variable in a multivariate analysis is to remove the factor and 

calculate how much power the model loses as a result. This is 

typically measured by the drop in R-square — the total variance 

in the dependent variable explained by the model. Surprisingly, 

when cohort is removed from the GLM, the adjusted R-square 

remains unchanged at .131. By this measure, cohort had no 

unique explanatory value in the model.

13 Using a four-category profile-of-engagement variable, 

the chi-square showed a statistically significant relationship 

between respondents’ type of engagement and generation. 

However, the lambda with one’s civic engagement type as 

dependent was .000, indicating that age/cohort did not 

improve one’s ability to identify a person’s participation profile.

14 Certainly, age/cohort has a modest influence on civic 

engagement. It is striking, however, given educational 

attainment’s far stronger statistical association with 

the indicator, that Zukin et al. use generation as their major 

lens for analyzing the data and give little attention the role 

of educational attainment. A NEA Research Note on civic 

engagement and the arts does note that education is a 

particularly strong predictor of volunteering. Art-Goers in 

Their Communities: Patterns of Civic and Social 

Engagement, NEA Research Note #98 (Washington, D.C.: 

National Endowment for the Arts, 2009), 13.

15 Peterson et al. conducted a study of age and arts participation 

using the 1997 survey. Their study reported summary statistics 

from a multivariate analysis: Age and Arts Participation: 

1982–1997, Richard A. Peterson, Pamela C. Hull, and Roger M. 

Kern, NEA Research Report #42 (Santa Ana, CA: Seven Locks 

Press, 2000). However, because the 1997 survey used a different 

method from previous and later surveys, and arguably led to 

inflated participation rates, we have followed previous scholars 

in not incorporating the 1997 results into this report. 

INTRODUCTION
32 National Endowment for the Arts

Overall, audience shares in 

2008 more closely tracked the 

distribution of the entire 

U.S. population than it had 

in previous years.
Age and arts participation: A case against demographic destiny 33

CHAPTER 1

BENCHMARK ARTS PARTICIPATION 

BY AGE AND COHORT 

INTRODUCTION

Age consciousness has led many scholars to 

assume that age and cohort strongly influence arts 

participation. Yet, as with civic engagement 

generally, we need to distinguish three aspects of the 

relationship of age, cohort, and arts participation. 

From the standpoint of description, we may find a 

pattern of relationships. Average participation 

may go up or down for older age groups or cohorts 

born earlier or later. In addition, because the 

Baby-Boom cohorts are larger than those born before 

or later, age has a compositional effect on the 

make-up of the arts audience. Finally, we need to 

distinguish the predictive value of age and cohort. 

From this perspective, the question is: to what extent 

does knowing people’s age or year of birth allow 

one to estimate their level of arts participation?

As we have seen, in the civic engagement literature, 

interest in the descriptive value of age and cohort 

effects has often obscured their limited predictive 

value. And yet, if we are to attribute some causal 

importance to age and cohort — that is, if we are to 

argue that age or cohort influences people’s behavior, 

we need to demonstrate their power to predict 

participation and how such power compares with 

that of other variables. When we control for other 

influences — especially the role of educational 

attainment — the predictive value of age and cohort 

turns out to be quite minor. Although they are 

statistically significant, the relationships of age and 

cohort to levels of arts participation are weak.

SUMMARY MEASURES

To provide an overview of general trends, this 

report uses three measures of overall participation: 

a dichotomous measure of any involvement in 

the benchmark activities; the number of activities in 

which a respondent was involved; and the number 

of individual events attended.

The SPPA’s “benchmark” questions focus on eight 

specific forms of arts participation: attendance 

at jazz, classical music, opera, musical plays, 

non-musical plays, ballet, other dance; and visits 

to art museums or galleries. For each of these 

activities, the survey asks whether the respondent 

had participated in the previous 12 months.16

Any benchmark participation

The simplest measure of participation is a yes/no 

variable based on any reported benchmark 

activity. This measure showed no particular trend 

between 1982 and 2002, but then fell sharply 

from 40 percent in 2002 to 36 percent in 2008. 

See Technical Appendix for additional details. 

(See Table 1, page 34.) 

Number of activities

Another measure of overall arts engagement is 

the number of different activities in which one 

participated during the survey year. This score was 

computed by assigning one point to each case for 

each different type of arts activity in which the 

respondent reported participating. We analyzed data 
34 National Endowment for the Arts

for nine activities (attendance at jazz, salsa music, 

classical music, opera, musical plays, non-musical 

plays, ballet, other dance; and visits to art museums) 

although “other dance” was not included in the 

survey until 1992 and “salsa and Latin music” were 

not included until 2008. See Technical Appendix 

for additional details. 

Events attended

The final summary measure included the total 

number of times the respondent reported attending 

events. This measure used total events attended 

for the nine benchmark activities. The data for 

this measure, however, were first collected in 1992. 

The average number of events attended fell 

from 2.6 in 1992 to 2.5 in 2002 and then plunged 

to 2.0 in 2008. More information is available in the 

Technical Appendix. 

Analysis

Age

These three summary measures for age exhibit the 

same curvilinear relationship. Very young and very 

old respondents have lower scores than those in the 

middle of the age distribution. (See Figure 2, below.)

The strength of the relationships between age and 

these summary measures declined over time, with 

the most profound decline between 2002 and 2008.17

Although this measure remained statistically 

significant, the predictive value of age went through 

a steady decline since the 1980s, and its explanatory 

power continued to decline between 2002 and 2008.

Birth cohorts

For this analysis, we classify respondents into six 

cohorts based on their year of birth — before 1935, 

1935–44, 1945–1954, 1955–1964, 1965–1974, and 

1975 and beyond. We identify the four middle cohorts 

as World War II, early Baby Boom, late Baby Boom, 

and Generation X.18

TABLE 1

Percent of respondents who reported attending at least 

one event of a given type by year

1982 1985 1992 2002 2008

Jazz 10.0% 10.0% 11.0% 11.0% 8.0%

Classical 13.0% 13.0% 12.0% 12.0% 9.0%

Opera 3.0% 3.0% 3.0% 3.0% 2.0%

Musicals 19.0% 17.0% 17.0% 17.0% 17.0%

Plays 12.0% 12.0% 13.0% 12.0% 9.0%

Ballet 4.0% 4.0% 5.0% 4.0% 3.0%

Other dance 7.0% 6.0% 5.0%

Visit art museum 22.0% 22.0% 27.0% 26.0% 23.0%

Types of activities 

(mean) 0.8 0.8 1.0 0.9 0.8

Average number 

of events 2.6 2.5 2.0

Any benchmark 

participation 39.2% 37.6% 42.4% 40.3% 36.2%

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file.

FIGURE 2

Indices of arts participation by age, U.S. adults, 

1982–2008

Age

Proportion/average

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

Percent who attended any benchmark arts event

Average number of types of activities attended

Average number of events attended

70 and over

25–29

30–34

35–39

40–44

45–49

50–54

55–59

60–64

65–69

Less than 25

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file.
Age and arts participation: A case against demographic destiny 35

As expected, the early and late Baby-Boom cohorts 

are larger than the World War II and Generation X 

cohorts. The two Baby-Boom cohorts together 

represent 41 percent of all respondents to the five 

SPPAs, while the World War II and Generation X 

cohorts include only 25 percent of all respondents. 

(See Table 2, below.)

The raw data on the relationship of cohort to arts 

participation indicates that the early Baby-Boom 

cohort had the highest rate of cultural participation 

overall. Forty-four percent of early Boomers reported 

attending at least one benchmark activity during 

the previous year. Nevertheless, the difference 

between different cohorts was relatively small. 

(See Figure 3, page 36.)

The predictive powers of age and cohort were never 

particularly strong and declined over time. Age 

and cohort predicted between 1 and 2 percent of any 

benchmark participation in the 1980s, and the 

variance in the number of those activities; but, by 

2008, their predictive power had fallen to less 

than 1 percent. The predictive power of number of 

events never exceeded one-half of 1 percent.

These summary measures underline the key 

findings of this report. Certainly, age mattered as a 

descriptive feature of arts participation. Age groups 

and cohorts had different levels of participation 

and some of these differences persisted over time. 

Yet from a statistical viewpoint the relationship of 

age and cohort to arts participation was always 

quite weak and, beginning at a low level, appears to 

have declined even further by the first decade of 

the twenty-first century.

CHAPTER 1

TABLE 2

Distribution of respondents by birth cohort, 1982–2008

1982 1985 1992 2002 2008 Total

Before 1934 38.4% 33.8% 24.2% 13.1% 8.3% 22.9%

World War II 15.1 14.7 13.5 11.0 9.2 12.5

Early Baby Boom 21.5 20.4 19.6 17.2 15.4 18.7

Late Baby Boom 25.0 24.8 23.6 21.7 19.9 22.8

Generation X 0.0 6.3 19.1 18.9 18.3 12.5

After 1975 0.0 0.0 0.0 18.1 28.8 10.6

Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Source: Author’s calculations from Survey of Public Participation in the Arts, 1982–2008 combined file.
36 National Endowment for the Arts

INDIVIDUAL ACTIVITIES

Overall, the SPPA has tracked a precipitous decline 

in attendance at benchmark arts events since 1992. 

With the exception of musical play attendance —

which held steady — the percent of respondents who 

reported attending at least one event in the previous 

year dropped for all of the benchmark indicators. 

One can describe these data from two perspectives:

■ Participation rates: what proportion of a 

particular group participated in arts activities 

during the previous year?

■ Audience share: among those who participated 

in arts activities, what proportion were members 

of a particular group?

Participation rates by age

There are a variety of patterns relating arts 

participation rates to age. Jazz has historically been 

more youth-oriented. Respondents in their twenties 

have generally reported participation rates in 

the mid-teens, much higher than the rates for older 

adults. For other activities, the participation-age 

profile has tended to be curvilinear, with some 

activities — like art museum attendance — peaking 

among those in their forties, and others — like 

classical music and opera — peaking a bit later. 

All forms of participation declined sharply for 

Americans after the age of 70. (See Figure 4, below.)

All of these relationships are statistically 

significant, meaning that the variation we see 

is unlikely to be a result of chance variation 

or sampling error. Still, the strength of these 

uncorrected associations between age and various 

measures of cultural participation are relatively 

weak. For none of the benchmark measures did age 

explain more than 1 percent of the variance.

FIGURE 3

Number of activities attended and percent attending 

any benchmark events, U.S. adults, by birth cohort, 

1982–2008

Birth cohort

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Percent who attended any benchmark art events

Average number of activities attended

After 1975

Generation X

Early Baby Boom

Late Baby Boom

Before 1934

World War II

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file.

Notes: Number of activities measures average number of activities reported. 

Benchmark participation reports proportion of respondents who reported any 

benchmark participation.

FIGURE 4

Percent of U.S. adults who attended different types of 

events, by age, 1982–2008

Age

Percent of U.S. adults 0%

5%

10%

15%

20%

25%

30%

Art museums

Other dance

Ballet

Plays

Musicals

Opera

Classical

Salsa

Jazz

70 and over

25–29

30–34

35–39

40–44

45–49

50–54

55–59

60–64

65–69

Less than 25

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file.
Age and arts participation: A case against demographic destiny 37

Participation rates by cohort

Overall, cultural participation declined steadily 

across the four central cohorts. Jazz attendance 

peaked at 14 percent among late Baby Boomers and 

then fell to 10 percent. For other activities, either 

the World War II or early Baby-Boom cohort had 

the highest rate. For five of the seven activities for 

which we have data since the 1980s, the overall trend 

was downward. The classical music attendance rate 

fell by 0.2 percent per year while musical and 

non-musical play attendance rates fell by 0.1 percent 

per year for the four cohorts. The jazz attendance 

rate rose among the first three cohorts, but then 

fell for Generation X respondents. Only art museum 

attendance held its own across the four cohorts, 

varying from 25 to 28 percent of respondents. 

(See Figure 5, below.)

Age and cohort

Because the SPPA provides data over a 26-year 

period, we are unable to calculate participation 

across any cohort’s entire life cycle. For the 

older cohorts, we lack data on their behavior as 

young adults. Younger cohorts are still in their 

young-adult years. Therefore, it is useful to examine 

cohort differences within particular age groups.

Here we examine just one measure — whether a 

respondent reported any benchmark participation in 

the previous year. These data confirm our previous 

assessment that the World War II cohort and the early 

Baby-Boom cohort exhibited the highest rates of 

cultural participation. The late Baby-Boom cohort’s 

rates were generally quite close to those of the two 

preceding cohorts. Of the four central cohorts, only 

Generation X had rates that were distinctly lower. 

This general appraisal is confirmed by summary 

statistics suggesting that within no age group did 

cohort differences account for even one-half of 

1 percent of the variance. (See Figure 6, below.)

FIGURE 5

Percent of U.S. adults who attended different types of 

events, by cohort, 1982–2008

Birth Cohort

Percent of U.S. adults 0%

5%

10%

15%

20%

25%

30%

Art museums

Other dance

Ballet

Plays

Musicals

Opera

Classical

Jazz

After 1975

Generation X

Early Baby Boom

Late Baby Boom

Before 1934

World War II

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file.

FIGURE 6

Percent of U.S. adults who attended any benchmark 

event, by age and birth cohort, 1982–2008

Age

Percent of U.S. adults

0%

10%

20%

30%

40%

50%

60%

After 1975

Generation X

Late Baby Boom

Early Baby Boom

World War II

Before 1935

70 and over

25–29

30–34

35–39

40–44

45–49

50–54

55–59

60–64

65–69

Less than 25

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file.

CHAPTER 1
38 National Endowment for the Arts

Audience share 

Another way to look at the impact of age and cohort 

on arts participation is to track the composition of 

the audience for benchmark activities over time. As 

an earlier report noted, the arts audience, like the 

population as a whole, has grown older over the past 

decade (NEA 2009a).

Certainly, the overall trend has been toward the 

aging of audiences for virtually all arts activities. 

Jazz is the most dramatic example. In 1982, 

two-thirds of its audience was under the age of 35; 

by 2008, the fraction had slipped to three-tenths. 

Ballet, too, experienced a sharp aging of its 

audience; young adults fell from 43 to 25 percent 

of ballet audience members between the 1982 

and 2008 SPPAs. (See Table 3, below.)

In order to use data from all five surveys — instead 

of just the start and end points — we calculated 

the trend line for each activity and the annual 

decline in audience share. Among younger adults, 

the jazz audience fell by 1.5 percent per year, while 

those for classical music, plays, and ballet fell 

by 0.6, 0.5 and 0.8 percent, respectively. Over the 

26 years of the SPPA, these figures translate 

into a 39 percentage-point decline for jazz and a 

21 percentage-point decline for ballet. 

TABLE 3

Distribution of participants by age and year, benchmark arts activities

Activity Age 1982 1985 1992 2002 2008

Jazz Under 35 67.0% 59.9% 42.8% 30.7% 29.2%

35-59 27.5 33.1 45.3 56.4 53.2

60 and over 5.5 7.1 11.9 12.9 17.5

Total 100.0% 100.0% 100.0% 100.0% 100.0%

Classical Under 35 38.2% 35.8% 29.2% 22.9% 22.8%

35-59 43.9 43.0 48.8 55.0 49.5

60 and over 17.9 21.2 22.0 22.1 27.7

Total 100.0% 100.0% 100.0% 100.0% 100.0%

Opera Under 35 31.7% 30.0% 29.7% 25.3% 21.2%

35-59 46.8 49.3 47.8 52.3 50.8

60 and over 21.6 20.7 22.5 22.4 28.1

Total 100.0% 100.0% 100.0% 100.0% 100.0%

Musicals Under 35 40.5% 37.7% 32.8% 27.4% 28.0%

35-59 43.6 44.6 47.9 54.2 50.4

60 and over 15.9 17.7 19.3 18.4 21.6

Total 100.0% 100.0% 100.0% 100.0% 100.0%

Plays Under 35 39.6% 39.0% 33.3% 27.6% 28.4%

35-59 44.2 42.9 47.8 54.8 46.8

60 and over 16.2 18.1 18.9 17.6 24.7

Total 100.0% 100.0% 100.0% 100.0% 100.0%

Ballet Under 35 43.4% 42.7% 38.4% 25.0% 24.9%

35-59 42.0 41.0 44.5 58.6 50.3

60 and over 14.6 16.4 17.1 16.4 24.9

Total 100.0% 100.0% 100.0% 100.0% 100.0%

Other dance Under 35 37.2% 29.5% 29.9%

35-59 43.7 55.1 46.1

60 and over 19.1 15.4 24.0

Total 100.0% 100.0% 100.0%

Art museum Under 35 46.1% 43.6% 39.1% 29.8% 31.7%

35-59 40.4 41.2 45.3 53.9 50.0

60 and over 13.5 15.2 15.5 16.4 18.3

Total 100.0% 100.0% 100.0% 100.0% 100.0%

Source: Author’s calculations from Survey of Public Participation in the Arts, 1982–2008 combined file.
Age and arts participation: A case against demographic destiny 39

Much of the shift of audience toward older age 

groups resulted from the aging of the population. For 

example, the entire SPPA population below the age of 

30 fell from 30 to 21 percent between 1982 and 2008, 

while the share of 45–59-year-olds increased from 

21 to 28 percent. 

In order to correct for the aging of the entire 

population, we calculated standardized audience 

share by applying a set of correction factors that 

divided the percent of the population in a given age 

group in each year by its share of the population 

across the five surveys. This procedure produces a 

set of data that estimate what audience shares 

would have been if the overall age structure of the 

population had not changed. As expected, 

the corrected audience-share figures show a less 

dramatic aging of the U.S. arts audience. The 

composition of the entire benchmark-arts audience 

population illustrates this point. Between 1982 and 

2008, the audience share that was under 30 years 

of age dropped from 33 to 21 percent while audience 

members in their late 40s and early 50s increased 

from 21 to 29 percent and those over the age of 

60 increased from 15 to 19 percent. 

Yet a large share of this aging of the audience 

resulted from changes in the overall composition of 

the population. The corrected scores show much 

smaller changes. For example, the decline in young 

adults’ audience share was only from 28 to 25 

percent, using corrected figures, while the increase 

in the older middle-age audience was less than 

one percent (23.6 to 24.3 percent). The increase in 

the older-adult audience remained a substantial 

5 percentage points. (See Table 4, below.)

Another way of gauging changes in the composition 

of the arts audience is to calculate an index 

of representativeness that measures the over- or 

underrepresentation of a particular age group 

in the arts audience, compared with its share of the 

total population. If the index is equal to zero, then 

the composition of the arts audience exactly reflects 

its share of the total population. If it is positive, 

that group is overrepresented; if negative, it is 

underrepresented. For example, if 33.1 percent of the 

audience is under the age of 30, but 29.7 percent of 

the entire population is in this age group, then the 

index of representativeness for those under the age of 

30 would be ((33.1/29.7*100) -100), or 11. For those over 

the age of 60 in 1992 — an underrepresented group 

— their audience share of 14.8 percent is divided by 

their share of the population (21.8 percent) and the 

result multiplied by 100. Subtracting 100 from this 

result gives the index of representativeness of -32, 

indicating a high level of underrepresentation.

For the entire benchmark arts population, the 

indices of representativeness tended to converge 

over time. In 1982, young adults’ audience share 

was 11 percentage points above their population 

share, while older adults were underrepresented 

by 32 percent. By 2008, the overrepresentation of 

younger groups and the underrepresentation of 

older groups had both been reduced. Young adults’ 

audience share exactly reflected their share of 

the population, whereas the underrepresentation 

of older adults had fallen from 32 percent in 1982 

to only 13 percent in 2008.

Turning to individual activities, the corrected 

audience share and index of representativeness 

both suggest that two activities — attending jazz 

and attending ballet — experienced the most 

extreme shifts in audience composition. For jazz, 

the corrected audience share of young adults fell 

TABLE 4

Audience share by age, benchmark participants

Under 

30 30-44 45-59 60+ Total

Corrected

1982 27.7% 33.8 23.6 14.9 100.0%

1985 25.3% 34.5 23.5 16.7 100.0%

1992 25.4% 32.1 24.6 17.8 100.0%

2002 23.4% 31.9 27.0 17.7 100.0%

2008 24.6% 31.9 24.3 19.2 100.0%

Uncorrected

1982 33.1% 31.5 20.6 14.8% 100.0%

1985 29.0% 34.5 19.7 16.8 100.0%

1992 24.2% 36.1 21.9 17.7 99.9%

2002 20.2% 32.9 29.8 17.0 99.9%

2008 21.1% 30.0 29.2 19.8 100.1%

Under 

30 30-44 45-59 60+

Index of representativeness

1982 11 13 0 -32

1985 2 16 -1 -24

1992 3 7 6 -20

2002 -6 6 15 -21

2008 0 7 4 -13

CHAPTER 1

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file.

Note: Corrected audience share adjusts figures for changes in composition of 

entire population. Index of representativeness equals zero if percent of audience is 

equal to percent of entire SPPA population. See technical appendix.
40 National Endowment for the Arts

from 46 to 24 percent, considerably less than the 

uncorrected decline from 52 to 20 percent. Jazz had 

become an art form dominated by persons over 

the age of 30. (See Table 5, below.)

This pattern is confirmed by the index of 

representativeness. The young-adult figure declined 

from 76 to -6 percent, while the older adult figure 

increased from -75 to -23 percent. The young 

middle-aged adult figure fell from 1 percent to -6 

percent — indicating that it shifted from slightly 

overrepresented to slightly underrepresented —

while the older middle-aged adult figure increased 

from -32 percent in 1982 to 17 percent in 2002 and 

29 percent in 2008.

Ballet experienced a similar shift. Both the young 

adult and young middle-aged shares of the ballet 

audience declined — even when correcting for 

population composition. By 2008, young adults were 

the only age group underrepresented among ballet 

participants. (See Table 6, below.)

Symphony orchestras have expressed concerns 

about the rapid aging of their audiences, a pattern 

confirmed by a recent study by the League of 

American Orchestras (League of American 

Orchestras 2010). The uncorrected audience-share 

decline of young adults (under 30) from 26 to 16 was 

dramatic. Yet, if corrected for overall population 

TABLE 5 

Jazz participation: audience share by age and year 

of survey

Jazz Under 

30 30-44 45-59 60+ Total

Corrected

1982 46.1% 31.0 17.1 5.8 100.0%

1985 36.1% 38.7 18.1 7.1 100.0%

1992 29.2% 36.6 22.2 12.1 100.0%

2002 25.7% 33.2 27.5 13.6 100.0%

2008 23.7% 28.5 30.4 17.3 100.0%

Uncorrected

1982 52.4% 28.1 14.1 5.5 100.1%

1985 40.1% 38.2 14.6 7.1 100.0%

1992 27.7% 40.8 19.7 11.9 100.1%

2002 22.0% 34.5 30.5 12.9 99.9%

2008 20.0% 26.4 36.0 17.6 100.0%

UNDER 

30

30-44 45-59 60+

Index of representativeness

1982 76 1 -32 -75

1985 41 28 -26 -68

1992 17 21 -5 -46

2002 2 12 17 -40

2008 -6 -6 29 -23

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file.

Note: Corrected audience share adjusts figures for changes in composition of 

entire population. Index of representativeness equals zero if percent of audience is 

equal to percent of entire SPPA population. See technical appendix.

TABLE 6

Ballet participation: audience share by age and year 

of survey

Ballet Under 

30 30-44 45-59 60+ Total

Corrected

1982 24.5% 40.1 20.7 14.7 100.0%

1985 24.5% 39.4 19.6 16.4 100.0%

1992 26.0% 32.2 24.7 17.1 100.0%

2002 17.9% 36.3 28.4 17.3 100.0%

2008 20.5% 31.0 24.2 24.3 100.0%

Uncorrected

1982 29.4% 37.5 18.3 14.7 99.9%

1985 27.9% 39.1 16.6 16.4 100.0%

1992 24.7% 36.4 22.0 17.0 100.1%

2002 15.2% 37.1 31.4 16.4 100.1%

2008 17.5% 29.1 28.7 24.8 100.1%

Under 

30 30-44 45-59 60+ Total

Total population

1982 29.7% 27.9 20.6 21.8 100.0%

1985 28.4% 29.8 19.8 22.1 100.1%

1992 23.6% 33.6 20.7 22.1 100.0%

2002 21.5% 30.9 26.0 21.6 100.0%

2008 21.2% 28.0 28.0 22.8 100.0%

Under 

30 30-44 45-59 60+

Index of representativeness

1982 -1 34 -11 -33

1985 -2 31 -16 -26

1992 5 8 6 -23

2002 -29 20 21 -24

2008 -17 4 2 9

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file.

Note: Corrected audience share adjusts figures for changes in composition of 

entire population. Index of representativeness equals zero if percent of audience is 

equal to percent of entire SPPA population. See technical appendix.
Age and arts participation: A case against demographic destiny 41

aging, the decline was from 22 to 19 percent. At the 

same time, the 8-point decline among young 

middle-aged adults (from 33 to 25 percent) did not 

change appreciably when corrected for population 

declines (from 35 to 27 percent). 

Younger adults were always underrepresented 

in the classical music audience and their index of 

representativeness fell slightly for young adults 

between 1985 and 2008 from -20 to -26. Between 

2002 and 2008, however, the representation of older 

middle-aged adults (35 to 14 percent) and older 

adults (2 to 22 percent) changed dramatically as 

more respondents over the age of 60 and fewer 

respondents between 45 and 59 years of age reported 

attending classical music events. (See Table 7, below.)

The interpretation of these data depends on one’s 

perspective. For a symphony or opera company, the 

rapid shrinking of a demographic group can have 

an impact on how many tickets it sells. So, while our 

analysis concludes that a large share of the change 

in the composition of the arts audience is attributable 

to the composition of the general population —

and not to changes in who participates in the arts —

we must keep in mind that these broader population 

trends, too, have an impact on arts organizations.

School attendance provides a useful analogy. 

During the 1950s, the Baby-Boom generation put 

enormous strain on public school systems as 

the number of school-age children increased rapidly. 

If one were a school administrator, this increase 

was a challenging and worrisome situation, although 

it told us nothing about the likelihood that children 

would attend school. Similarly, classical music 

organizations have reason to be concerned about 

attendance rates, even if the trends do not indicate 

radical shifts in people’s behavior.

The same trends can be seen in changes in the 

average and median age of participants. Again, one 

needs to compare shifts in these figures with 

changes in figures for the entire population. For 

example, while the average age of a benchmark 

arts participant increased from 40 to 45 between 

1982 and 2008, the average age of the entire SPPA 

population increased from 43 to 46. We can 

gauge shifts in age by dividing the average age for 

participants by that for the entire population and 

multiplying the resulting figure by 100. A score 

TABLE 7 

Classical music participation: audience share by age 

and year of survey

Classical music Under 

30 30-44 45-59 60+ Total

Corrected

1982 21.6% 35.0 25.6 17.7 100.0%

1985 19.6% 35.8 23.9 20.8 100.0%

1992 19.6% 27.9 30.7 21.8 100.0%

2002 18.4% 26.0 32.4 23.2 100.0%

2008 18.6% 26.9 27.1 27.5 100.0%

Uncorrected

1982 26.4% 33.0 22.9 17.9 100.2%

1985 22.6% 36.0 20.2 21.2 100.0%

1992 18.8% 31.6 27.6 21.9 99.9%

2002 15.7% 26.9 35.2 22.1 99.9%

2008 15.6% 24.9 31.8 27.8 100.1%

Under 

30 30-44 45-59 60+ Total

Total population

1982 29.7% 27.9 20.6 21.8 100.0%

1985 28.4% 29.8 19.8 22.1 100.1%

1992 23.6% 33.6 20.7 22.1 100.0%

2002 21.5% 30.9 26.0 21.6 100.0%

2008 21.2% 28.0 28.0 22.8 100.0%

Under 

30 30-44 45-59 60+

Index of representativeness

1982 -11 18 11 -18

1985 -20 21 2 -4

1992 -20 -6 33 -1

2002 -27 -13 35 2

2008 -26 -11 14 22

CHAPTER 1

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file.

Note: Corrected audience share adjusts figures for changes in composition of 

entire population. Index of representativeness equals zero if percent of audience is 

equal to percent of entire SPPA population. See technical appendix.
42 National Endowment for the Arts

below 100 indicates that the audience age is younger 

than the general population; a figure over 100 

indicates that it is above the population figure. In 

the case of all benchmark participants, this 

calculation results in an increase in the index from 

93 in 1982 to 98 in 2008. Again, these indicators 

suggest that the arts audience in 2008 more closely 

mirrored the entire population than they had in 

the 1980s. (See Table 8, below.)

These general conclusions hold for individual 

activities as well. There was a general drift up in 

terms of average age, but, with the exception of jazz 

and ballet, the changes were not dramatic. Jazz’s 

index increased from 74 to 102, while ballet rose from 

95 to 102. Classical music and opera had the highest 

index scores in 1982 and retained this distinction 

in 2008, although opera’s index actually fell from 

1982 to 2008 from 110 to 107.

Overall, then, audience shares in 2008 more closely 

tracked the distribution of the entire population 

than it had earlier. Whereas in 1982, young adults 

and the middle-aged were strongly overrepresented 

among arts participants, the 2008 audience share 

looked more like the population as a whole. Although 

the aging of the arts audience was real, its cause 

was less the result of changes in people’s tastes and 

behavior than the overall aging of the population. 

With a couple of exceptions — especially jazz 

and ballet — changes in audience share by age 

groups for arts activities tracked changes in the 

composition of the population.

EDUCATIONAL ATTAINMENT AND AGE: 

A CONFOUNDING RELATIONSHIP

Age has a statistically significant, but weak 

relationship to our summary measures of arts 

participation. Moreover, we can judge the 

importance of this relationship only in comparison 

to other variables that might influence participation.

As virtually all research on arts participation 

has demonstrated, educational attainment is the 

strongest predictor of cultural engagement 

(DiMaggio and Ostrower 1992; Peterson et al. 2000; 

Rabkin and Hedberg 2011). This is certainly the 

case with our three summary measures, all of which 

show a clear relationship between educational 

attainment and arts participation. While the 

strength of this relationship has declined somewhat 

since the 1980s — and especially between 2002 

and 2008 — it continues to explain 16–17 percent of 

the variance in our measures of participation.

Not only is education strongly correlated with 

cultural participation, but before 2008, it had 

a strong relationship with age as well. During the 

1980s, individuals with less than a high-school 

diploma and those with a graduate degree were 

considerably older than those with either a 

high-school degree or some college experience. 

Over time, this relationship faded. In 2008, 

educational attainment had only a fraction of 

the explanatory power than it did in 1982.19

The weakening relationship between age and 

education has implications for our interpretation 

of the link between age and arts participation. 

At least a share of the apparent correlation of age 

and participation was accounted for by the 

correlation of age and educational attainment. 

In the 1980s, the correlation between age and 

education made the correlation between age and 

participation appear stronger than it really was. 

As the correlation between age and education 

declines, the correlations between age and 

participation should decline as well, even though 

age’s actual influence might remain unchanged. 

To disentangle these confounding effects, we must 

turn to multivariate analysis.

TABLE 8 

Average age of benchmark arts participants, by activity 

and year

1982 1985 1992 2002 2008

Any benchmark 

activity

40.1 41.0 42.4 44.2 44.8

Jazz 33.1 35.2 39.6 42.6 45.2

Classical 42.5 43.3 45.5 47.5 48.9

Opera 45.0 44.3 45.2 47.0 48.4

Musicals 41.5 42.2 43.8 45.0 45.9

Plays 41.7 42.0 43.6 44.7 46.8

Ballet 40.3 40.7 41.9 44.7 46.5

Other dance 42.6 43.7 45.6

Art museum 39.7 40.4 41.3 44.1 44.1

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file.
Age and arts participation: A case against demographic destiny 43

MULTIVARIATE ANALYSIS

Multivariate analysis allows us to answer two 

questions. First, does adjusting for age or cohort 

change our conclusions about the rapid decline 

in benchmark participation over time? Second, if 

we adjust for other factors, how strongly do age 

and cohort influence benchmark participation? 

(See Table 9, below.)

The answer to the first question is clear. The 

year-to-year declines in the participation indices 

were unaffected by adjusting for cohort or age. 

For example, controlling for other variables, the 

decline in the attendance rate at any benchmark arts 

activity between 1992 and 2008 actually increased 

from 6 percent to 9 percent. Also, changes in the 

number of activities attended were slight. The 

decline in benchmark attendance was not the result 

of changes in the influence of age or cohort.

TABLE 9

Benchmark participation index, by year. General linear analysis

Number of activities by age

To assess the relative strength of age and cohort, 

we conducted a set of multivariate analyses. The 

variables included in the analysis are gender, marital 

status, educational attainment, ethnicity, year of 

birth, and the interaction effect between year and 

educational attainment. (See Table 10, below.)

As we have noted, educational attainment 

overwhelms all other variables in the analysis.20

The entire model explains 20 percent of the variance 

in number of activities, but educational attainment 

alone explains 18 percent of the variance. Although 

the impact of other variables is statistically 

significant, none explains more than 0.7 percent 

of the variance in number of activities attended. 

(See Table 11, page 44.)

Uncorrected Corrected for other variables

Year Number of activities Any benchmark activity Number of activities Any benchmark activity

1982 0.8 39.2% 1.1 45.5%

1985 0.8 37.6% 1.0 43.2%

1992 1.0 42.4% 1.1 45.5%

2002 0.9 40.3% 1.0 41.1%

2008 0.8 36.2% 0.8 36.4%

Source: Author’s calculations from Survey of Public Participation in the Arts, 1982–2008 combined file.

Note: Other variables entered in equation: educational attainment, marital status, ethnicity, gender, and age.

TABLE 10 

Average number of activities. General linear model, summary statistics

Tests of Between-Subjects Effects

Source Type III Sum of 

Squares df Mean Square F Significance Partial Eta Squared

Corrected model 31422 31 1014 668 0.000 0.206

Intercept 11360 1 11360 7490 0.000 0.086

Gender 904 1 904 596 0.000 0.007

Marital status 420 2 210 138 0.000 0.003

Educational attainment 27266 4 6816 4494 0.000 0.183

Ethnicity 685 4 171 113 0.000 0.006

Year 457 4 114 75 0.000 0.004

Interaction: education and year 306 16 19 13 0.000 0.003

Error 121441 80063 2

Total 210690 80095

Corrected total 152863 80094

CHAPTER 1

df = degrees of freedom

F = F-ratio
44 National Endowment for the Arts

Adding age to the analysis makes a few changes 

to the overall explanatory pattern. With the 

addition of age as a main effect and two interaction 

terms (age/year and education/age), educational 

attainment’s partial eta declines from 18 to 15 

percent. Yet the three additional terms only add 0.4, 

0.1, and 0.3 percent to the model’s explanatory power. 

Another notable feature of this model, compared 

with that in the previous table, is the addition to 

adjusted R square. Without age present, the model 

explained 20.5 percent of the variance in total 

activities. Adding age and its interaction terms, this 

figure increases by 0.6 percent to 21.1 percent. 

Again, although age is statistically significant — that 

is, its effect is not zero — its impact is minor.

The analysis allows us to examine the age profile 

of participation, correcting for other influences, 

by comparing the uncorrected age profile for 

“number of activities attended” with the estimated 

marginal means of the regression analysis. As we 

have noted, the strong correlation of age with 

education (older respondents having lower 

educational attainment) had a large impact on the 

age profile. Specifically, the uncorrected data 

tended to overestimate the decline in participation 

as respondents aged. If all age groups had the same 

educational attainment, participation would remain 

steady among the middle aged and the “young old.” 

Only respondents over the age of 70 showed a 

marked decline in participation when corrected for 

other influences. (See Figure 7, page 45.)

TABLE 11 

Average number of activities. General linear model (age included), summary statistics

Tests of Between-Subjects Effects

Source Type III Sum of 

Squares df Mean Square F Significance Partial Eta Squared

Corrected model 32375 121 268 178 0.000 0.212

Intercept 11111 1 11111 7375 0.000 0.084

Gender 911 1 911 605 0.000 0.008

Marital status 498 2 249 165 0.000 0.004

Educational attainment 22002 4 5501 3651 0.000 0.154

Ethnicity 637 4 159 106 0.000 0.005

Year 502 4 125 83 0.000 0.004

Interaction: education and year 267 16 17 11 0.000 0.002

Age 540 10 54 36 0.000 0.004

Interaction: age and year 107 40 3 2 0.002 0.001

Interaction: age and education 341 40 9 6 0.000 0.003

Error 120488 79973 2

Total 210690 80095

Corrected total 152863 80094

R Squared = .212 (Adjusted R Squared = .211)

df = degrees of freedom

F = F-ratio

Source: Author’s calculations from Survey of Public Participation in the Arts, 1982–2008 combined file.
Age and arts participation: A case against demographic destiny 45

This pattern did not change much from survey 

to survey. The summary data for the interaction of 

age and year remained statistically significant —

although it had the lowest level of significance of 

any term in the analysis — but explained less than 

0.1 percent of the variance in number of activities 

attended. What is more, much of the change in 

the age profile from year to year is accounted for by 

the large decline in participation in 2008. If we 

leave aside 2008, it is hard to discern any important 

change in the age profile over time.

Finally, the regression analysis suggests that 

while age’s explanatory power declined over time, 

the decline was not as precipitous as the 

uncorrected data suggest. The correlation of age 

and education in the early surveys made age’s 

influence on participation appear stronger than 

it was. (See Figure 8, below.)

If we use age’s impact on the R-square of the 

model, then the decline in age’s influence is even 

smaller. In 1982, age added 0.8 percent to the 

model’s explanatory value. This amount rose as high 

as 1.1 percent in 1985. In the last three surveys 

(1992, 2002, and 2008), however, the contribution 

to R-square remained at 0.6 or 0.5 percent. Again, 

while age never had the degree of influence apparent 

in the uncorrected data, its modest influence has 

not declined as much as those data suggest.

FIGURE 7

Average number of activities attended by U.S. adults, 

by age, uncontrolled and controlling for other variables, 

1982–2008

Age

Average number of activities

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Uncorrected

Estimated marginal mean

70 and over

65–69

60–64

55–59

50–54

45–49

35–3

40–44

9

30–34

25–29

Less than 25

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file. See Table 11 for detailed results.

Note: General linear model analysis results, controlled for gender, marital 

status, educational attainment, ethnicity, and year of survey. 

FIGURE 8

Strength of relationship between age and average 

activities attended by U.S. adults, uncontrolled and 

controlling for other variables, 1982–2008

Year

Strength of relationship 0.000

0.005

0.010

0.015

0.020

eta squared

partial eta squared

1982 1985 1992 2002 2008

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file. See Table 11 for detailed results.

Note: General linear model analysis results, controlled for gender, marital 

status, educational attainment, ethnicity, and year of survey.

CHAPTER 1
46 National Endowment for the Arts

Number of activities and cohort

An analysis of cohort and number of activities 

attended, controlling for other demographic 

variables, yields a similar result. The explanatory 

value of cohort is statistically significant, but 

it explains only two-tenths of one percent (or one 

five-hundredth) of the variance in number of 

benchmark activities. Again, cohort’s influence 

is dwarfed by educational attainment and 

overshadowed by gender, marital status, and 

ethnicity as well. (See Table 12, below.)

As with age, correcting for other influences reduces 

the differences between cohorts. For example, 

the relatively low average number of activities for 

the two earliest cohorts rises when educational 

attainment and other influences are controlled for. 

The one substantive change of this adjustment 

relates to the World War II cohort. Using raw scores, 

it appears that the World War II cohort’s average 

number of benchmark activities was somewhat 

lower than that for the early Baby-Boom cohort. Yet, 

when correcting for other influences — especially 

the World War II cohort’s average educational 

attainment, which was lower than for subsequent 

generational cohorts — its average number 

of activities is actually higher than that of early 

Baby-Boom generations. (See Figure 9, page 47.)

TABLE 12 

Average number of activities. General linear model (cohort included), summary statistics

Tests of Between-Subjects Effects

Source Type III Sum of 

Squares df Mean Square F Significance Partial Eta Squared

Corrected model 32001 72 444 294 0.000 0.209

Intercept 10769 1 10769 7130 0.000 0.082

Gender 920 1 920 609 0.000 0.008

Marital status 539 2 270 178 0.000 0.004

Educational attainment 20087 4 5022 3325 0.000 0.143

Ethnicity 642 4 161 106 0.000 0.005

Year 298 4 75 49 0.000 0.002

Interaction: year and education 215 16 13 9 0.000 0.002

Cohort 257 5 51 34 0.000 0.002

Interaction: cohort and year 176 16 11 7 0.000 0.001

Interaction: cohort and education 170 20 8 6 0.000 0.001

Error 120863 80022 2

Total 210690 80095

Corrected total 152863 80094

R Squared = .209 (Adjusted R Squared = .209)

df = degrees of freedom

F = F-ratio

Source: Author’s calculations from Survey of Public Participation in the Arts, 1982–2008 combined file.
Age and arts participation: A case against demographic destiny 47

CONCLUSION

We habitually view the world through the lens of 

age and cohort. But this habit may cloud our ability 

to assess their actual importance in explaining 

arts attendance. While age has some influence of arts 

participation, it is at best a modest one. This is not 

to say that age and cohort don’t matter. As we shall 

see in the next section, age has had an important 

influence on patterns of participation.

NOTES

16 “Other dance” was added to the survey in 1992 and salsa 

and Latin music in 2008. See Technical Appendix for an exact 

calculation of summary statistics.

17 The summary measure used here is the eta-square that can be 

interpreted as indicating the proportion of all variance in the 

dependent variable that can be explained by the independent 

variable.

18 For a more extensive discussion of twentieth-century American 

cohorts, see Michael B. Katz and Mark J. Stern, One Nation 

Divisible: What America Was and What It Is Becoming (New 

York: Russell Sage Foundation Press, 2006), chapter 3.

19 As a result, the eta square for the relationship between age and 

educational attainment fell from 0.118 in 1982 to 0.012 in 2008.

20 Using all three of our summary measures, we conducted 

multivariate analyses that produced generally similar results. In 

the remainder of this section, we restrict our attention to number 

of activities.

FIGURE 9

Average number of events attended by U.S. adults, 

by birth cohort, uncontrolled and controlling for other 

variables, 1982–2008

Cohort

Average number of events attended

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Corrected

Uncorrected

Before 1935 1935–1944 1945–54 1955–64 1965–74 After 1975

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file. See Table 12 for detailed results.

Note: General linear model analysis results, controlled for gender, marital 

status, educational attainment, ethnicity, and year of survey.

CHAPTER 1
48 National Endowment for the Arts

The “cultural omnivore” 

pattern is more associated 

with the World War II 

and early Baby-Boom cohorts 

than with later generations.
Age and arts participation: A case against demographic destiny 49

CHAPTER 2

PATTERNS OF PARTICIPATION

INTRODUCTION

The previous section examined the impact of 

age and cohort on aggregate measures of cultural 

participation. It found their influence to be 

statistically significant, but having relatively little 

explanatory value, especially when other variables 

have been controlled for.

Still, these variables can influence participation in 

other ways. In this section we examine how age and 

cohort influence patterns of arts participation —

that is, how individuals mix and match different 

types of participation. In particular, we examine two 

patterns that have been of interest to other researchers. One is “highbrow,” the tendency 

of people who are active in one “high-status” cultural 

form (as determined by the researcher) to be active 

in one or more other high-status forms. The other 

pattern is that of the cultural “omnivore.” Following 

Peterson, we define omnivores as individuals 

who are active in both “highbrow” and so-called 

middle- or lowbrow arts activities. 

This chapter undertakes two tasks. First, it uses 

cluster analysis as a means of identifying 

individuals by how they combine one or more 

cultural forms into a particular palette of activities. 

Second, it uses the resulting clusters to assess 

change over time in the size of different clusters 

and their relationship to age and year of birth. 

The analysis is complicated by the sudden and 

dramatic downturn in cultural participation 

reported in the 2008 SPPA. One question posed by 

these data is whether the 2008 data represent a 

one-time shock to the cultural system — perhaps 

caused by the economic recession that began in 

late 2007 — or represent a longer trend. After all, 

although the drop in participation in 2008 was 

dramatic, the benchmark arts attendance rates have 

not increased since 1992.

This paper finds evidence of both a one-time shock 

— what statisticians would call a period effect — and 

a longer-term trend — or cohort effect. In particular, 

the number of omnivores dropped at the same time 

that they attended fewer events on average. 

CLUSTER ANALYSIS

Cluster analysis is a statistical technique for 

identifying regularities among different variables. 

Here we use it to identify SPPA respondents who 

share particular patterns of participation. Using 

Peterson’s typology, we identified omnivore and 

“highbrow” patterns of participation. We also 

report data on an “other” category of participants 

that did not fit into either of Peterson’s constructs. 

(See Technical Appendix, page 73, for an explanation 

of how these clusters were determined.)

Approximately twice as many respondents 

were classified as omnivores as highbrows. Together, 

these two groups represent 19 percent of all 

respondents and more than half of all respondents 

that reported any type of arts attendance. The 

distribution of respondents varied markedly by 

year. The number of respondents with little or 

no participation peaked in 2008 at 67 percent after 

remaining relatively stable in earlier years. 
50 National Endowment for the Arts

Omnivore representation declined from 15 percent 

in 1982 to 10 percent in 2008. Highbrows represented 

just over 7 percent of all respondents in 1985 and 

1992 and then declined to 5 percent in 2008. Finally, 

the “other” category showed no clear trend across 

the five surveys. (See Table 13, below.)

The ethnic and educational backgrounds of the four 

clusters are consistent with Peterson’s theory. More 

than 34 percent of adults holding a graduate degree 

were omnivores and 14 percent were highbrows. At 

the other extreme, only 7 percent of adults with a 

high-school diploma were omnivores, and 4 percent 

were highbrows. Whites were overrepresented 

among omnivores and highbrows. Asians and Pacific 

Islanders were overrepresented among highbrows, 

while the multi-racial/Native American category 

was overrepresented among omnivores.21

PATTERNS OF PARTICIPATION BY AGE 

AND COHORT

The omnivore pattern of cultural participation is 

associated with distinctive age and cohort features. 

First, the proportion of cultural omnivores tends 

to decline with age. Younger adults are more likely to 

be omnivores than older adults. Second, omnivores 

are more likely to have been born before 1955 than 

after. The omnivore pattern is more associated with 

the World War II and early Baby-Boom cohorts than 

with later groups.

These two features of the omnivore pattern can 

obscure each other. At the time of the first survey 

in 1982, members of the World War II cohort 

were already in their late thirties and early forties, 

beyond their prime omnivore years. We capture 

late Baby Boomers and Generation Xers during early 

adulthood, a factor that tends to overestimate 

their propensity to be omnivores. 

TABLE 13 

Distribution of U.S. adults by arts participation patterns, by survey year

1982 1985 1992 2002 2008 Total

Nonparticipants Count 10,517 8,557 7,804 10,825 12,391 50,094

Percent 61.0% 62.6% 61.3% 63.2% 67.2% 63.2%

Omnivores Count 2,612 1,897 1,740 2,173 1,866 10,288

Percent 15.1% 13.9% 13.7% 12.7% 10.1% 13.0%

High brow Count 1,156 982 907 1,008 977 5,030

Percent 6.7% 7.2% 7.1% 5.9% 5.3% 6.3%

Other Count 2,969 2,238 2,285 3,129 3,210 13,831

Percent 17.2% 16.4% 17.9% 18.3% 17.4% 17.5%

Total Count 17,254 13,674 12,736 17,135 18,444 79,243

Percent 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Source: Author’s calculations from Survey of Public Participation in the Arts, 1982–2008 combined file.

Note: See text for explanation. 
Age and arts participation: A case against demographic destiny 51

During their thirties and forties, members of the 

World War II and early Baby-Boom cohorts had 

omnivore rates in the 16 to 18 percent range. By 

contrast, the late Baby Boomers’ omnivore rate, when 

they reached this age range, fell as low as 12 percent. 

Generation X’s omnivore rate fell to 9 percent. 

Although all cohorts tended to see this percentage 

drop as they aged, the differences between cohorts 

remained strong. (See Figure 10, below.)

This pattern is captured to some extent by summary 

statistics. The interaction of age and cohort 

explains 1.1 percent of the variance in the omnivore 

rate. Although hardly an overwhelming level of 

association, compared with previous analyses this 

link suggests that age and cohort had a stronger 

influence on the omnivore pattern of participation 

than on the overall rate of arts participation.

Highbrow participation was not as strongly 

associated with age. With the exception of an 

increase in highbrow participation among older 

members of the World War II cohort, the highbrow 

rate remained relatively flat within each cohort. 

Cohort effects, too, were muted. Only Americans 

born after 1975 showed a distinctly lower rate of 

highbrow participation. (See Figure 11, below.)

CHAPTER 2

FIGURE 10

Percent of U.S. adults classified as omnivores, by age 

and birth cohort, 1982–2008

Age

Percent of U.S. adults

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

After 1975

Generation X

Late Baby Boom

Early Baby Boom

World War II

Before 1935

70 and over

65–69

60–64

55–59

50–54

45–49

35–3

40–44

9

30–34

25–29

Less than 25

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file.

Note: See text and appendix for explanation of classification procedure.

FIGURE 11

Percent of U.S. adults classified as highbrow 

participants, by age and birth cohort, 1982–2008

Age

Percent of U.S. adults

0%

2%

4%

6%

8%

10%

12%

After 1975

Generation X

Late Baby Boom

Early Baby Boom

World War II

Before 1935

70 and over

65–69

60–64

55–59

50–54

45–49

35–3

40–44

9

30–34

25–29

Less than 25

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file.

Note: See text and appendix for explanation of classification procedure.
52 National Endowment for the Arts

THE IMPACT OF DECLINING OMNIVORE 

BEHAVIOR ON TOTAL ATTENDANCE

Omnivores represent the most active segment of the 

entire arts audience. They go to more types of 

arts activities than other groups, and they go to more 

individual events than others. In 1982 and 1985, 

the SPPA asked about events attended at benchmark 

activities during the previous month. As the 

following figures show, omnivores accounted for 

a large share of respondents, with more than 

one event attended during the previous month. 

(See Figure 12, below.)

In 1992 and afterward, we received more precise 

information on the number of events attended during 

the previous year. With the exception of classical 

music, omnivores attended more events in all the 

benchmark cultural activities over the last three 

SPPAs, typically with average attendance rates 

at three or more times those of other groups. 

Although the omnivores represented only 13 percent 

of the population, they accounted for 58 percent 

of all events attended in those years. 

The average number of events attended by 

omnivores and highbrows dropped sharply between 

2002 and 2008. Omnivores’ average number of 

events attended fell from 12.1 to 11.0 events per year, 

a decline of 9 percent. Highbrow attendance fell 

by 11 percent — from 6.1 to 5.5 events per year —

while other participants’ attendance held steady. 

(See Figure 13, page 53.)

Between 2002 and 2008, a double blow hit 

cultural participation. First, the proportion of the 

population that we characterize as omnivores —

individuals who attend a variety of different 

cultural forms — dropped sharply. At the same 

time, as with the rest of the population, the number 

of events that omnivores attended also fell —

by more than one event per respondent. Taken 

together, the decline of omnivores’ share of 

the population and their drop in average number 

of events attended represented 82 percent of the 

entire decline in individual attendance at 

benchmark arts events between 2002 and 2008.22

FIGURE 12

Percent of U.S. adults by type of participant and number 

of events attended

Number of events Number of events

1982 1985

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Other

Highbrow

Omnivores

Nonparticipants

None 1 2–4 5+

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Other

Highbrow

Omnivores

Nonparticipants

None 1 2–4 5+

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file.

Note: See text and appendix for explanation of classification procedure.
Age and arts participation: A case against demographic destiny 53

CONCLUSION

This chapter has focused on the relationship 

between the omnivore pattern of cultural 

participation and age and birth cohort. We have 

discovered that the omnivore pattern was 

particularly common among respondents born 

between 1935 and 1954, and that this pattern 

has declined in popularity. The declines in the 

number of omnivores and in their participation 

rate explain most of the overall decline in 

participation between 2002 and 2008, at least 

by total number of events attended. 

The role of age and cohort in this decline was 

indirect. Omnivores — a small minority of the 

population — account for a disproportionate share 

of all arts participation. Because the omnivore 

pattern is associated with both age (omnivores are 

more likely to be young adults) and cohort 

(the World War II and early Baby-Boom cohorts), 

the aging of these birth cohorts has had a strong 

impact on overall arts participation.

NOTES

21 The U.S. Census began in 2000 to allow respondents to check 

more than one racial category. As a result, the multi-racial category 

was included in the 2002 and 2008 SPPAs. 

22 Correcting for differences in sample sizes, omnivores accounted 

for 82 percent of the total decline in events attended by survey 

respondents between 2002 and 2008. 

CHAPTER 2

FIGURE 13

Average number of events attended by U.S. adults, by 

type of participant, 1982–2008

Year

Average number of events

0

2

4

6

8

10

12

14

Other

Highbrow

Omnivores

1992 2002 2008

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file.

Note: See text and appendix for explanation of classification procedure.
54 National Endowment for the Arts

Gender and educational 

attainment seem the 

most important influences 

on literary reading.
Age and arts participation: A case against demographic destiny 55

CHAPTER 3

LITERARY READING

INTRODUCTION

In previous chapters, we found that age and cohort 

have statistically significant, but relatively weak, 

relationships to participation in live cultural events. 

However, they are relevant for various patterns of 

cultural participation, particularly for the rise 

and fall of the omnivorous pattern first identified 

by Richard A. Peterson.

In this chapter we examine the three SPPA 

variables on literary reading that have been included 

in the surveys since 1992. The yes/no questions 

ask whether the respondent had read any novels or 

short stories, poetry, or plays during the previous 

12 months. 

Since 1992, the literary reading rates of Americans 

have declined (NEA 2004, 2007). In 1992, 52 percent 

of SPPA respondents reported reading a novel, play, 

or short story in the previous year. Ten years later, 

this figure had fallen to 45 percent. Although it rose 

to 47 percent in 2008, this rate is still below the 1992 

figure (NEA 2009c). In contrast, poetry and play 

reading both fell from survey to survey. The 2008 

rates for these two activities were less than half what 

they had been in 1992. (See Figure 14, below.)

WHAT FACTORS ARE CORRELATED WITH 

LITERARY READING?

Education

As with other forms of arts or cultural engagement, 

education was consistently the most important 

determinant of reading. Respondents with a 

graduate degree were roughly three times more 

likely to do any literary reading in the previous year 

than those with less than a high-school diploma. 

Overall, this relationship remained fairly stable, 

although the gaps narrowed a bit. By 2008, the figure 

for those with a graduate degree was 70 percent 

compared to a figure of 29 percent for those with less 

than a high-school diploma. (See Table 14, page 56.)

FIGURE 14

Percent of U.S. adults who read any novels or short 

stories, poetry, or plays in the previous year, 1992–2008

Survey year

Percent of U.S. adults 0%

10%

20%

30%

40%

50%

60%

Plays

Poetry

Novels

1992 2002 2008

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file.
56 National Endowment for the Arts

Gender, race, and ethnicity

The gender gap in literary reading remained fairly 

consistent across the three surveys. In 1992, 60 

percent of women reported any reading while only 

47 percent of men reported doing so. Both figures 

fell in 2002 and then rebounded a bit in 2008, leaving 

the male figure 6 percentage points below the 

1992 figure and the female figure 3 points lower. 

Racial and ethnic differences in literary readers are 

comparable in strength to those associated with 

gender (each has an eta-square of 0.03). Differences 

remained fairly consistent over time, with whites 

and multi-racial or other respondents having the 

highest rates (between 50 and 60 percent), African 

Americans and Asian/Pacific Islanders having 

somewhat lower rates (between 35 and 45 percent), 

and Hispanics reporting the lowest reading rates 

(between 26 and 34 percent). 

Age and cohort

Overall, the relationships of age and cohort to 

literary reading were statistically significant, but 

weak. In 1992, middle-aged adults were more 

likely to report any literary reading than older adults. 

The highest rates were among those in their forties 

— at around 60 percent — while those in their 

twenties and sixties had rates closer to 50 percent. 

Rates dropped across the board in 2002, although 

the declines among Americans in their fifties were 

much smaller than for other age groups, suggesting 

perhaps a cohort effect. Rates recovered a bit by 

2008, with those in their sixties showing the 

largest increases, again suggesting a cohort effect. 

(See Figure 15, below.)

As the age data intimate, birth cohorts had a 

consistent set of differentials between 1992 and 2008. 

The World War II cohort (1935–44) had the lowest 

literary reading rate in all three years, and 

the early Baby Boomers had the highest. The late 

TABLE 14 

Percent of respondents reporting any reading, by 

gender, educational attainment, ethnicity, and year

1992 2002 2008

Gender

Male 47.2% 37.1% 41.0%

Female 60.1 54.8 56.9

Educational attainment

Less than high school grad 25.4% 19.7% 28.5%

High school graduate 48.8 37.4 38.1

Some college 64.7 52.5 55.1

College graduate 70.5 62.5 65.4

Graduate degree 79.1 73.6 69.7

Ethnicity

White 57.8% 51.0% 54.7%

Black 45.4 36.8 41.5

Hispanic 33.9 26.2 31.1

Asian Pacific Islanders 39.7 41.9 40.2

Multi-racial, American Indian 57.9 51.6 48.6

Total 54.0% 46.3% 49.2%

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file.

FIGURE 15

Percent of U.S. adults who read any novels or 

short stories, poetry, or plays in the previous year, 

by age of respondent, 1992–2008

Age of respondent

Percent reporting any literary reading 0%

10%

20%

30%

40%

50%

60%

70%

2008

2002

1992

70 and over

25–29

30–34

35–39

40–44

45–49

50–54

55–59

60–64

65–69

Less than 25

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file.
Age and arts participation: A case against demographic destiny 57

Baby Boomers rate, which fell from 56 percent in 

1992 to 49 percent in 2008, were closer to that of the 

World War II cohort in all three years. This trend is 

consistent with age data suggesting that as the 

early Baby Boomers aged, their reading rates tended 

to rise, while those of age groups behind them —

including the late Boomers — tended to fall. (See 

Figure 16, below.)

Nevertheless, a raw comparison of cohorts is 

always a problematic because one is catching them 

at different points in their life cycles. To correct 

for this factor, we need to examine age and birth 

cohorts together. (See Figure 17, below.)

Disaggregating the results by age and cohort lead to 

a number of surprising results. First, these data 

suggest a fairly consistent decline in literary reading 

within each cohort as it ages. The World War II 

cohort, which we can chart only from the time these 

adults were in their late 40s, saw their reading rate 

decline from 58 to 47 percent as it aged. The early 

Baby Boomer began with a 57 percent rate when they 

were in their late 30s and then declined to as low 

as 51 percent for those in their fifties. (Americans 

who were over 60 in 2008 had a 54 percent reading 

rate.) Finally, the late Baby Boomers began their late 

twenties with a literary reading rate at 55 percent, 

which fell to 50 percent when they were in their early 

fifties. Americans born after 1975 — often referred 

to as Millennials — reported low reading rates when 

they were under 25, but by the time they were 

in their late 20s, their rate was higher than that of 

respondents in Generation X.

At the same time, disaggregating the results by age 

changes our view of cohort behavior. The World War 

II cohort, instead of having the lowest literary 

reading rate, actually had the highest rate for every 

age group except those in their early sixties. 

CHAPTER 3

FIGURE 16

Percent of U.S. adults who read any novels or 

short stories, poetry, or plays in the previous year, 

by birth cohort, 1992–2008

Year

Percen t of respondents

0%

10%

20%

30%

40%

50%

60%

70%

1965–74

1955–64

1945–54

1935–1944

Before 1935

1992 2002 2008

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file.

FIGURE 17

Percent of U.S. adults who read any novels or 

short stories, poetry, or plays in the previous year, 

by age and birth cohort, 1982–2008

Age

Percent of respondents 0%

10%

20%

30%

40%

50%

60%

70%

After 1975

After 1975

Generation X

Late Baby Boom

Early Baby Boom

World War II

70 and over

65–69

60–64

55–59

50–54

45–49

35–3

40–44

9

30–34

25–29

Less than 25

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008 combined file.
58 National Endowment for the Arts

MULTIVARIATE ANALYSIS

In order to disentangle the various influences 

on literary reading, we conducted a regression 

analysis with the following independent 

variables: cohort and age, educational attainment, 

gender, ethnicity, and marital status. Only two 

factors explain a noteworthy amount of variance: 

educational attainment and gender.23 As with earlier 

analyses, the impact of age and cohort remains 

statistically significant, but relatively minor, 

explaining only one-half of one percent of the 

variance. (See Table 15, below.)

The results for age and cohort reinforce our earlier 

conclusions. First, there is a fairly strong decline 

in reading within each birth cohort over the life 

span. For example, the World War II cohort saw its 

rate decline from 53 percent among those in their 

early forties to 46–47 percent among those in 

their sixties. Each cohort’s reading rate, however, 

was lower than that of the previous cohort at 

comparable ages. For example, in their late forties, 

the World War II cohort had a rate of 53 percent, 

the early Baby Boomers had a rate of 52 percent, and 

the late Baby Boomers a rate of 47 percent. 

Taken together, these results suggest that all three 

possible time issues — period, age, and birth cohort 

— have a role in explaining the observed data. 

There seems to be a general tendency of reading to 

decline with age. Reading rates in successive cohorts 

appear to decline. Finally, although the reading 

rate rebounded somewhat between 2002 and 2008, 

it still remained lower than it had been in 1992.

The key to all of this, perhaps, is to remember 

that all of these effects are relatively small. While 

we have focused on differences across age and 

cohort, we could just as easily have focused on their 

similarities, a perspective reinforced by the meager 

explanatory value of age and cohort. This is to say, 

we should keep these results in perspective. Gender 

and educational attainment seem the most important 

influences on reading. The age-related variables, at 

best, slightly modify the picture.

TABLE 15 

Percent of respondents who read any novels or short stories, poetry, or plays in the previous year. General linear model 

analysis, summary statistics

Tests of Between-Subjects Effects

Source Type III Sum of 

Squares df Mean Square F Significance Partial Eta Squared

Corrected model 1155 33 35 164 0.000 0.144

Intercept 1117 1 1117 5217 0.000 0.140

Ethnicity 97 4 24 114 0.000 0.014

Educational attainment 629 4 157 735 0.000 0.084

Marital status 1 2 <1 2 0.138 0.000

Gender 241 1 241 1126 0.000 0.034

Interaction: age and cohort 37 22 2 8 0.000 0.005

Error 6862 32053 <1

Total 16414 32087

Corrected total 8017 32086

R Squared = .144 (Adjusted R Squared = .143)

Source: Author’s calculations from Survey of Public Participation in the Arts, 1982–2008 combined file.

Note: See text for explanation.
Age and arts participation: A case against demographic destiny 59

NOTES

23 Educational attainment remains the most important, with a 

partial eta-square of .08. Gender’s partial eta square was .03, about 

the same as its raw eta-square. When controlled for educational 

attainment, a large share of ethnicity’s explanatory power 

disappears. Its partial eta-square of .01 is about half of its raw 

eta-square.

CHAPTER 3
60 National Endowment for the Arts

The analysis of media 

and personal arts involvement 

fills in our view of overall 

arts participation, but 

does not alter the basic outline 

of the story.
Age and arts participation: A case against demographic destiny 61

CHAPTER 4

MEDIA-BASED AND PERSONAL 

ARTS PARTICIPATION

INTRODUCTION

In earlier chapters, we have examined different 

dimensions of arts participation from the 

perspective of age and cohort. We discovered, in 

most cases, that age and cohort have had a 

modest, but statistically significant, influence 

on live attendance at arts events and on literary 

reading behavior. 

In this chapter, we turn to two topics to fill in our 

portrait of participation: consuming cultural 

content through the media, and personal or creative 

involvement in the arts. The core conclusions of 

our analysis are similar to those we have reached in 

other aspects of this study. The most important 

determinants of participation are educational 

attainment and gender. Although age and cohort in 

most cases have a statistically significant effect 

on participation, the magnitude of the effect is quite 

modest. Furthermore, when we control for other 

variables, even this apparent effect is reduced. 

OVERALL PATTERNS IN MEDIA-BASED 

AND PERSONAL ARTS PARTICIPATION

Overall, media-based participation in the arts 

and personal participation have experienced 

the same declines as live attendance since 1992. 

By 1992, 58 percent of respondents reported some 

media-based participation and 55 percent some 

form of personal participation. The proportion 

of respondents reporting media-based arts 

participation fell sharply after 1992, from 63 to 41 

percent in 2008. Personal participation in the arts 

(activities such as art-making, the performance 

of art, and the acquisition of artwork) fell from 56 in 

1992 to 44 percent in 2002 and 42 percent in 2008.24

MEDIA-BASED AND PERSONAL ARTS 

PARTICIPATION BY AGE AND COHORT

Between 1992 and 2008, neither media-based nor 

personal arts participation exhibited a distinctive 

relationship to age. Media participation was lower 

among those under the age of 25 and over the age 

of 70, but for other age groups, it hovered between 

58 and 54 percent across the three years. Personal 

participation exhibited a somewhat stronger 

relationship. It was lower among respondents in 

their twenties, rose to about 48 percent among age 

groups between 40 and 64, and then fell off slightly. 

Age differences explained less than one-half of 

one percent of the variation for both media-based 

and personal arts participation rates.

There was little change in these patterns from 

year to year. Rather, the overall declines in 

participation tended to shift the age curves down, 

without appreciable changes to their shapes. The 

relationships of age to these indicators — although 

weak to begin with — declined in explanatory 

power over time. In 2008, age explained less than 0.2 

percent of the variance in media participation and 

0.4 percent of the variance in personal participation. 

(See Table 16, page 62.)

Cohort, too, had little influence on either media or 

personal participation. The youngest and oldest 

cohorts had the lowest rates, while the World War II 

and the two Baby-Boom cohorts had the highest rates. 

Generation X’s media and personal participation 

rates were about five percentage points below those 

of the Baby-Boom generations. (See Table 17, page 62.)

The relationship of media participation to cohort 

declined over time. All cohorts experienced 

significant declines in participation across survey 

years. For example, the early Baby-Boom cohort 

saw its media-based arts participation rate decline 
62 National Endowment for the Arts

from 67 percent in 1992 to 56 percent in 2002 

to 45 percent in 2008. Differences between cohorts 

remained small but consistent. The explanatory 

power of cohort remained low for each year.

A similar pattern influenced our personal arts 

participation index. The Baby-Boom cohorts had the 

highest rates of personal participation in all three 

years, but like other cohorts, their rates fell 

across years, suggesting that the general decline in 

participation overwhelmed any age or cohort effect.25

The most interesting results of this analysis relate 

to the late Baby-Boom cohort. Through most of 

the analyses in this report, this birth cohort lagged 

behind the World War II and early Baby-Boom 

cohorts in participation level. In 2008, however, its 

rate of personal participation was not statistically 

different from that of the early Baby-Boom cohort. 

CONCLUSION

The analysis of media and personal participation 

fills in our view of overall arts participation, 

but does not alter the basic outline of the story. In 

aggregate, like other forms of cultural engagement, 

both media-based arts participation and personal 

participation appear to have declined over time.26

Education and (in the case of personal participation) 

gender have important influences on arts 

participation. Age- and cohort-specific influences 

are relatively small. 

TABLE 16 

Media-based and personal arts participation rates 

by age and year

1992 2002 2008 1992-2008

Any media participation

Less than 25 58% 43% 42% 48%

25-29 62 52 41 54

30-34 65 51 39 55

35-39 65 53 40 56

40-44 67 55 41 57

45-49 68 57 41 58

50-54 63 56 42 56

55-59 62 59 45 57

60-64 66 54 46 57

65-69 65 53 42 56

70 and over 58 51 39 51

Total 63% 53% 41% 55%

Any personal participation

Less than 25 53% 40% 39% 42%

25-29 53 41 38 43

30-34 57 42 42 45

35-39 60 44 43 47

40-44 57 47 43 48

45-49 60 48 44 49

50-54 58 46 46 48

55-59 57 48 46 48

60-64 60 45 45 48

65-69 57 44 40 46

70 and over 45 38 38 40

Total 56% 44% 42% 45%

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008.

TABLE 17

Media-based and personal arts participation rates 

by birth cohort and year

1992 2002 2008 1992-2008

Any media participation

Before 1935 61.7% 50.6% 36.5% 55.2%

World War II 63.8 55.9 43.4 57.7

Early Baby Boom 66.9 56.3 44.6 59.1

Late Baby Boom 64.9 55.4 42.2 57.3

Generation X 59.2 51.9 39.4 52.7

After 1975 45.7 41.2 44.0

Total 63.3% 52.6% 41.3% 54.6%

Any personal participation

Before 1935 52.1% 39.1% 36.4% 42.9%

World War II 57.7 44.9 42.5 47.4

Early Baby Boom 58.7 46.9 45.7 49.1

Late Baby Boom 57.1 46.7 45.9 48.7

Generation X 53.1 43.1 41.9 44.7

After 1975 39.8 39.4 39.6

Total 55.6% 43.6% 42.1% 45.4%

Source: Author’s calculations from Survey of Public Participation in the Arts, 

1982–2008.
Age and arts participation: A case against demographic destiny 63

NOTES

24 See the Technical Appendix for discussion of these variables. 

The SPPA questions on personal and media participation have 

changed considerably from survey to survey, making accurate 

measurement of trends difficult. Sometimes general questions 

(played jazz) were replaced with more specific questions 

(performed jazz in public). In other cases, new categories were 

added, as composing music was in 1992, or dropped, as that same 

category was in 2008. Media participation went through some 

predictable changes; for example, television-watching in 1992 and 

earlier was replaced by TV-, VCR-, and DVD-watching in 2002. In 

addition, the 2008 survey reduced the number of media questions 

by combining questions on watching and listening to art 

programming. 

25 The eta-square for the cohort was .003 in 1992 and .004 in 2002 

and 2008. 

26 However, see Footnote 25 (above) for a cautionary note about 

interpreting trend data for media-based and personal arts 

participation.

CHAPTER 4
64 National Endowment for the Arts

Factors that explain a few 

thousandths of the variation 

in participation will hardly 

define the future of art 

in America for good or ill.
Age and arts participation: A case against demographic destiny 65

CHAPTER 5

CONCLUSION AND IMPLICATIONS

This paper has examined the role that age and cohort 

play in various forms of arts participation. It has 

examined four different dimensions of participation:

■ Live attendance at “benchmark” arts events

■ Literary reading

■ Personal participation in the arts

■ Media-based participation in the arts

Given the diversity of these various dimensions of 

cultural engagement, it is striking how consistent 

the findings are. Over the four dimensions, we 

discovered that age and cohort have statistically 

significant, but extremely modest impacts on 

levels of participation. Indeed, when educational 

attainment and gender are taken into consideration, 

the role of age and cohort fades even more. 

This is not to say there are no patterns related 

to age and cohort. Overall, it appears that Americans 

born between 1935 and 1954 are more likely to 

participate in arts-related activities than those born 

after 1955. The strongest relationship noted in this 

report tied these cohorts to the omnivore cultural 

pattern. The decline of omnivores is a major 

cause of the decline in overall arts attendance 

since 1992. Generally, participation is higher 

among middle-aged persons than among very young 

adults and older Americans.

These broad findings appear to fly in the face of 

current understanding of civic participation, 

of which cultural participation is one element. As 

previously noted, Robert Putnam and the authors 

of A New Engagement? have suggested that birth 

cohorts provide the best framework for making sense 

of current patterns of civic engagement. Yet, as our 

re-analysis of their data reveals, age and cohort have 

a weak relationship to civic engagement and provide 

little power in explaining trends in participation.

The interest with age and cohort has as much to do 

with the future as the past. If age and cohort are 

strong predictors of arts participation, it is reasoned, 

then we may be able to better predict the future of 

the cultural audience by looking at younger cohorts 

and examining their preferences. The life-cycle 

literature’s concept of life trajectory supports this 

line of reasoning. If younger adults get into the habit 

of attending events, it is hoped, they will keep this 

habit as they age. Viewed another way, the decline of 

youth interest in a number of activities — not only 

classical music, but also jazz — may indicate that the 

future of these activities is in jeopardy.

A recent report by the League of American 

Orchestras (LAO 2010) epitomizes this approach. It 

suggests that the fate of classical music is tied to 

the behavior of cohorts. Graphing the same data used 

in this report — but with different cohort categories 

and a shortened vertical axis — the LAO report 

identifies a blip in classical music attendance as most 

cohorts age.
66 National Endowment for the Arts

In his New Yorker Blog, Unquiet Thoughts: Notes 

on Music, Alex Ross commented on the LAO study 

by underlining the strength of the “age-as-destiny” 

narrative:

You can see clearly how various generations 

experienced a bump in participation as they got 

older. The so-called Generation X, however, 

has yet to exhibit an upward spike as it moves into 

middle age. Every classical organization in 

America should print out this graph, pin it on the 

bulletin board, and ponder what is to be done. 

If the light-gray line doesn’t reverse direction in 

the next 10 years, those organizations may 

begin to fold (Ross 2010).

The present study’s findings challenge this 

perspective on two counts. First, age and cohort have 

little statistical power in explaining changes in arts 

participation. Factors that explain a few thousandths 

of the variation in participation will hardly define 

the future of art in America for either good or ill.

More importantly, this perspective underestimates 

how broader changes in personal life are influencing 

civic and arts participation. As we noted earlier, 

the middle of the 20th century represented 

the high-point of processes that standardized the 

life-course. A combination of the opportunity 

structure and coercive social norms created an 

environment in which a variety of personal decisions 

— when one married, entered the labor force, gave 

birth, or retired — occurred in lock-step fashion for a 

large share of the population. After 1970, this 

uniformity gave way to a new diversity of personal 

decision-making. The transition to adulthood 

became more protracted and characterized by 

diversity and autonomy. The timing of life-events 

for older Americans — retirement and household 

configurations — also became more varied; 

retirement ages have become less standardized and 

the “empty nest” life-cycle stage went from an 

exceptional to a typical household form for older 

adults. The growth of the population over the age of 

85 led to a rethinking of old age (Stanger-Ross, 

Collins, and Stern 2005; Katz and Stern 2006). 

This same pursuit of flexibility and informality has 

influenced the art world as well. If we are correct 

that the cultural omnivore is in decline, it may be 

because the omnivore represented a transitional 

stage in our cultural development. After all, Peterson 

and his collaborators discovered the omnivore 

pattern because of the unexpected loosening of the 

straitjacket of “cultural capital” associated with 

musical preference. Cultural participants were 

no longer willing to let their social status define 

what cultural tastes were acceptable for them. 

Although the omnivore — as measured by the SPPA 

— may be foundering, this quest for a more 

personal, flexible, and protean approach to cultural 

engagement appears very much alive.

A recent study by Alan Brown (2009) of 

WolfBrown Associates that measures the “cultural 

engagement index” for metropolitan Philadelphia 

illustrates the implications of this new perspective. 

Instead of beginning with a traditional view 

of arts participation as exemplified by the NEA’s 

“benchmark” arts activities, Brown began his 

surveys by engaging his respondents in their own 

definitions of creativity. Creativity turned up 

in some surprising places. Who anticipated that 

the “most common forms of dance participation 

are ‘watching TV shows about dance or dance 

competitions’ (32% ‘very important’), followed 

by ‘social dancing at clubs or parties’ (21% ‘very 

important’)”? Who would have expected that 

“‘writing for business purposes’ and ‘writing in a 

journal, diary or blog’ are the most common 

forms of creative expression through writing”? 

By inviting his respondents to define cultural 

engagement rather than respond to a predetermined 

list of activities, Brown generated a surprising 

“top 10” list of cultural activities:

1. Listen to music on a local radio station. 

2. Read books, magazines or newspapers. 

3. Watch programs about science or history on TV. 

4. Sing.

5. Watch TV shows about dance. 

6. Hear music as part of a worship service. 

7. Do gardening or landscaping for fun.

8. Prepare ethnic or traditional foods of your 

heritage.

9. Buy music for your own collection.

10. Download music or listen to Internet radio/

streaming audio.
Age and arts participation: A case against demographic destiny 67

Admittedly, Brown’s approach was not limited 

to “arts” activities, but it extended rather to 

a consideration of broader types of cultural 

participation. Still, for many activities that parallel 

the SPPA — such as reading — the method appears to 

generate much higher rates of cultural engagement 

than the SPPA. It does raise the possibility, 

moreover, that the SPPA’s methods — rather than 

Americans’ actual behavior — have influenced the 

trends in arts participation identified by the SPPA.

Notwithstanding the ultimate reason for changes 

in the SPPA trend line, the present study suggests 

that age and cohort are not destiny. Although age 

and cohort may shape the contours of the potential 

U.S. audience for the arts, the success of arts 

organizations will be guided by their ability to 

connect to the creative aspirations of current and 

future participants. 

CHAPTER 5
68 National Endowment for the Arts
Age and arts participation: A case against demographic destiny 69

REFERENCES

Attanasio, Orazio P. and Martin Browning. 

“Consumption over the Life Cycle and over the 

Business Cycle.” American Economic Review 85, 

no. 5 (December 1995): 1118–37.

Brown, Alan. Philadelphia Cultural Engagement 

Index. San Francisco: WolfBrown, 2009.

DiMaggio, Paul and Francie Ostrower. Race, 

Ethnicity, and Participation in the Arts. National 

Endowment for the Arts, Research Report #25. 

Washington, D.C.: Seven Locks Press, 1992.

Easterlin, Richard A. “What Will 1984 Be Like? 

Socioeconomic Implications of Recent Twists in Age 

Structure.” Demography 15, no. 4 (November 1978): 

397–432.

Elder, Glen H. Children of the Great Depression: 

Social Change in Life Experience. Chicago: 

University of Chicago Press, 1974.

Fernandez-Villaverde, Jesus and Dirk Krueger. 

“Consumption over the Life Cycle: Facts from 

Consumer Expenditure Survey Data.” Review of 

Economic and Statistics 89, no. 3 (2007): 552–65.

Katz, Michael B. and Mark J. Stern. One Nation 

Divisible: What America Was and What It Is 

Becoming. New York: Russell Sage Foundation, 2006.

League of American Orchestras (LAO). Audience 

Demographic Research Review. New York and 

Washington, D.C.: League of American Orchestras, 

2010.

National Endowment for the Arts. (2009b) Art-Goers 

in Their Communities: Patterns of Civic and Social 

Engagement. NEA Research Note #98. Washington, 

D.C.: National Endowment for the Arts, 2009.

————. Reading at Risk: A Survey of Literary 

Reading in America. Research Division Report #46. 

Washington, D.C.: National Endowment for the Arts, 

2004.

————. (2009c) Reading on the Rise: A New Chapter 

in American Literacy. Washington, D.C.: National 

Endowment for the Arts, 2009.

————. To Read or Not To Read: A Question of 

National Consequence. Research Report #47. 

Washington, D.C.: National Endowment for the Arts, 

2007.

————. (2009a) 2008 Survey of Public Participation 

in the Arts. Research Report #49. Washington, D.C.: 

National Endowment for the Arts, 2009.

Peterson, Richard A. “Understanding audience 

segmentation: From elite and mass to omnivore and 

univore.” Poetics 21, no. 4 (1992): 243–58.

Peterson, Richard A., Pamela C. Hull, and Roger M. 

Kern. Age and Arts Participation: 1982–1997. 

National Endowment for the Arts, Research Division 

Report #42. Santa Ana, CA: Seven Locks Press, 2000.

Peterson, Richard A., Darren E. Sherkat, Judith 

Huggins Balfe, and Rolf Meyersohn. Age and Arts 

Participation with a Focus on the Baby Boom 

Cohort. National Endowment for the Arts, Research 

Division Report #34. Santa Ana, CA: Seven Locks 

Press, 1996.
70 National Endowment for the Arts

Peterson, Richard A. and Albert Simkus. “How 

Musical Taste Groups Mark Occupational Status 

Groups.” In Cultivating Differences: Symbolic 

Boundaries and the Making of Inequality, edited 

by Michele Lamont and Marcel Fournier, 152–68. 

Chicago, IL: University of Chicago Press, 1992.

Putnam, Robert D. Making Democracy Work: 

Civic Traditions in Modern Italy. Princeton: 

Princeton University Press, 1993.

————. “Tuning In, Tuning Out: The Strange 

Disappearance of Social Capital in America.” 

PS: Political Science and Politics 28, no. 4 

(December 1995): 664–83.

————. “The Strange Disappearance of Civic 

America.” The American Prospect 24 (Winter 1996): 

34–48.

————. Bowling Alone: The Collapse and Revival 

of American Community. New York: Simon and 

Shuster, 2000.

Ross, Alex. Unquiet Thoughts: Notes on Music, The 

New Yorker Blog; “The Fatal X,” blog entry posted 

February 3, 2010. www.newyorker.com/online/

blogs/alexross/2010/02/more-on-audiences.html. 

Stanger-Ross, Jordan, Christina Collins, and 

Mark J. Stern. “Falling Far from the Tree: 

Transitions to Adulthood and the Social History of 

Twentieth-Century America.” Social Science 

History 29, no. 4 (Winter 2005): 625–48.

Wegner, D. M. White Bears and Other Unwanted 

Thoughts: Suppression, Obsession, and the 

Psychology of Mental Control. New York: Viking, 

1989.

Zukin, Cliff, Scott Keeter, Molly Andolina, Krista 

Jenkins, and Michael X. Delli Carpini. A New 

Engagement? Political Participation, Civic Life, 

and the Changing American Citizen. Oxford and 

New York: Oxford University Press, 2006.
Age and arts participation: A case against demographic destiny 71

REFERENCES
72 National Endowment for the Arts
Age and arts participation: A case against demographic destiny 73

TECHNICAL APPENDIX

DATA SETS

The bulk of this analysis was conducted using the 

combined 1982–2008 Survey of Public Participation 

in the Arts file produced by the National Endowment 

for the Arts in November 2009. For most analyses, the 

file was weighted using the “normalized weights.” 

The analysis of media and personal participation 

used the individual SPPA files available on the 

Cultural Policy and the Arts National Data Archive 

(CPANDA) website. The constructed variables from 

this file were then merged into the 1982–2008 files.

The secondary analysis of civic participation 

in Chapter 1 used two datasets: the General 

Social Survey (GSS) conducted by the National 

Opinion Research Corporation (NORC) and the 

National Civic Engagement Survey I commissioned 

by the Center for Information and Research 

on Civic Learning and Engagement (CIRCLE) of 

the University of Maryland. The GSS dataset 

was downloaded from the Survey Documentation 

and Analysis website of the University of 

California-Berkeley. The NCES dataset was 

downloaded from CIRCLE’s website.

DEPENDENT VARIABLES

Measures of arts participation

Chapter 2 focuses on the “benchmark” measures of 

arts participation. These measures consist of a set of 

questions asked about live attendance at arts events 

in the previous year. The art activities included: jazz, 

salsa (added in 2008), classical music, opera, musical 

plays, non-musical plays, ballet, other dance (added 

in 1992), and art museums. These are dichotomous 

variables that are answered yes or no.

The SPPA has also included questions about the 

frequency of attendance at each of these activities. 

For 1982 and 1985, these questions asked about 

number of times attended in the previous month; 

in subsequent surveys, the question asked about 

number of times attended in the previous year. 

No effort was made to reconcile the two sets 

of questions.

■ We use three summary measures of benchmark 

participation:

■ Attendance at any benchmark activity —

a dichotomous variable

■ Number of activities — how many types of

benchmark activities a respondent reported 

attending in the previous year.

■ Number of events (1992–2008) — the aggregate 

number of events reported for all benchmark 

activities.
74 National Endowment for the Arts

Because this study focuses on the relationship of arts 

participation to age and cohort, rather than trends 

in overall attendance over time, “other dance” and 

“salsa and Latin music” have been included in our 

calculation of summary measures, to provide wider 

measures of attendance. We conducted a sensitivity 

analysis that determined that excluding these 

two variables would not have influenced any of the 

substantive findings of the study. However, our 

method increases the attendance indices in 1992, 

2002, and 2008, and it understates the overall decline 

in attendance between 2002 and 2008. For example, 

if the two variables were excluded, the average 

number events attended would be 0.2 events lower 

in 1992, 0.1 events lower in 2002, and 0.2 events 

lower in 2008. Similarly, the average number of 

types of activities would have been 0.07, 0.06, and 

0.08 lower in 1992, 2002, and 2008, respectively. 

Finally, attendance at any benchmark event would 

have been 1.1 percent, 0.7 percent, and 1.5 percent 

lower in 1992, 2002, and 2008, respectively. 

Our decision to include “other dance” and salsa and 

Latin music in our calculations also tends to 

understate the decline in attendance that occurred 

between 2002 and 2008. Our method led to declines 

of 0.51 in average events, 0.13 in number of activities, 

and 4.1 percent in attendance at any benchmark 

event. Excluding “other dance” and salsa and Latin 

music would lead to estimated declines of 0.59 in 

number of events, 0.15 in number of activity types, 

and 4.9 percent in attendance in the three indices, 

respectively. 

Chapter 4 examines the benchmark activities from 

the standpoint of patterns of participation. This 

analysis used a k-means clustering technique that 

aimed at assigning every case in the combined SPPA 

file to one of 10 clusters based on the similarity in its 

pattern of cultural participation. Cluster analysis is 

not driven by a particular theory; it simply looks for 

regularities within a body of data and seeks to group 

cases based on those regularities. The program 

allows the researcher to set the number of clusters. 

Using fewer than 10 resulted in clusters in which 

several of the least popular activities (opera and 

ballet) were not represented. The final cluster centers 

show that each of the eight activities was represented 

in at least one cluster.

The 10 clusters were then regrouped using Peterson’s 

theoretical constructs. As these tables show, one 

cluster — number 4 — epitomizes an omnivorous 

pattern; respondents in this group generally had 

been involved in all eight activities. In addition, four 

other clusters — numbers 3, 5, 9, and 10 — were 

characterized by multiple and diverse activities. Two 

clusters — numbers 6 and 8 — are consistent with 

Peterson’s concept of “highbrow” in that they involve 

more than one discipline that fit a traditional idea 

of “high art.” Over half of the respondents were 

members of cluster 1, which represented those 

involved in few or no activities. Finally, we group the 

remaining three categories into an “other” category. 

Although this report provides data on all of these 

clusters, we pay particular attention to the omnivore 

category. (See tables, page 75.) 
Age and arts participation: A case against demographic destiny 75

Chapter 4 uses the SPPA questions about literary 

reading. For some analyses, separate counts for 

novels, plays, and poetry are reported. For other 

analyses, we used a dichotomous variable based on a 

respondent’s report of reading any of these forms of 

literature.

Chapter 5 uses constructed indices for media and 

personal participation. These topics pose two 

methodological challenges. First, the questions used 

to track these areas have not been consistent over 

time. When the first SPPA was conducted in 1982, 

CDs, DVDs, and videocassettes were not in common 

use; as media have changed, so have the questions. 

Second, in a number of years, these questions were 

asked to only some respondents. As a result, the 

statistical power of the analysis of these data is 

weaker than for other elements of the study. 

Because of these variations in the number, wording, 

and order of questions, it is difficult to conduct much 

analysis of trends in personal or media-based 

participation. For a study of age and cohort, this 

limitation is particularly constraining because it 

makes any attempt at tracking birth cohorts over 

time challenging.

Clearly, there is no way to overcome the limitation 

in the data. However, for exploratory purposes, 

we experimented with several summary measures 

to assess if they could tell us anything about how 

these dimensions of arts participation changed over 

time. (See tables, page 76.)

Cluster analysis. Benchmark arts activities

a. Final cluster centers

Cluster # Jazz Opera Musicals Plays Ballet Art 

museum Classical Other dance

1 0 0 0 0 0 0 0 0

2 0 0 1 0 0 0 0 0

3 1 0 1 1 0 1 0 0

4 1 1 1 1 1 1 1 1

5 1 0 0 0 0 0 0 1

6 0 0 0 0 1 1 0 0

7 0 0 0 0 0 1 0 0

8 0 0 0 0 0 1 1 0

9 0 0 1 0 0 1 1 0

10 0 0 1 0 0 0 1 0

Unweighted Weighted

Nonparticipants 49,536 50,094

Musicals 6,084 5,909

Jazz, musicals, plays, museums 3,861 3,768

Everything 1,556 1,499

Jazz, other dance 2,260 2,274

Ballet, museums 1,285 1,261

Museums 7,897 7,828

Museums, classical 3,866 3,770

Musicals, museums, classical 1,652 1,604

Musicals, classical 1,173 1,144

79,170 79,149

TECHNICAL APPENDIX

b. Number of cases in each cluster
76 National Endowment for the Arts

Questions used to construct media index

1992 2002 2008

Jazz on television Saw jazz on TV/VCR/DVD last 12 months Watched or listened to jazz during the last 

12 months Jazz on radio Listen to jazz radio last 12 months

Jazz records Listen to jazz records last 12 months

Watched or listened to Latin, Spanish or salsa 

music in last 12 months

Classical music on television Saw classical on TV/VCR/DVD last 12 months Watched or listened to classical music during 

the last 12 months Classical music on radio Listen to classical radio last 12 months

Classical music on records Listen to classical records last 12 months

Opera on television Saw opera on TV/VCR/DVD last 12 months Watched or listened to opera during the last 

12 months Opera on radio Listen to opera radio last 12 months

Opera records Listen to opera records last 12 months

Musical stage play or operetta on television Saw musical on TV/VCR/DVD last 12 months Watched or listened to musical stage play 

during last 12 months Musical stage play or operetta on radio Listen to musical on radio last 12 months

Musical stage play or operetta on records Listen to musical on record last 12 months

Non-musical stage play on television Saw play on TV/VCR/DVD last 12 months Watched or listened to non-musical stage play 

during last 12 months Non-musical stage play on radio Listen to play on radio last 12 months

Dance on television Saw dance on TV/VCR/DVD last 12 months Watched or listened to dance performances 

during last 12 months

Art program on television Saw artists on TV/VCR/DVD last 12 months Watched or listened to a program about 

artists/art in last 12 months

Questions used to construct personal participation index

Did pottery/ceramics/jewelry during the last 12 months

Did weave/needlework/sewing during the last 12 months

Made photo/movies/video during the last 12 months

Did paint/draw/sculpture during the last 12 months

Did creative writing during the last 12 months

Own original art pieces

Acquired art pieces during the last 12 months

Played a musical instrument during the last 12 months

Performed jazz music during the last 12 months

Performed classical music during the last 12 months

Sang music from an opera during the last 12 month

Sang or acted in a musical play during the last 12 months

Acted in a non-musical play during the last 12 months

Sang with a vocal group during the last 12 months

Danced during the last 12 months
Age and arts participation: A case against demographic destiny 77

STATISTICAL TESTS

For the most part, this report relies on simple 

computation of means and cross-tabulations. In a 

number of cases, the report used regression 

analysis to control for the correlations between 

independent variables. Specifically, we used SPSS’s 

general linear model (GLM) program because it 

provided several benefits. First, it allowed the use 

of categorical variables without the separate 

computation of dummy variables. This same feature 

allows the analyst to enter interaction terms in 

the regression equation without the computation 

of separate interaction variables. The program 

computes a partial eta-square statistic that expresses 

the strength of the association between each 

independent variable and the dependent variable. 

Finally, the program computes estimates of marginal 

means — that is, the means of each factor, controlling 

for the effects of other factors in the equation.

One of the drawbacks of using GLM with 

dichotomous variables is that they violate several 

assumptions about the variance of the dependent 

variable. We conducted a set of logistic regressions 

that produced results similar to the GLM findings we 

reported. We chose to use the GLM findings because 

they are easier to explain to a general audience.

Because this report is primarily interested in the 

impact of age and birth cohort on participation, we 

have not reported all results from the general linear 

model analysis. Instead, we have reported summary 

statistics that estimate the relative strength of 

different factors and the estimated marginal means 

for age and birth cohort.

TECHNICAL APPENDIX

CORRECTED AUDIENCE SHARE AND INDEX 

OF REPRESENTATIVENESS

In Chapter 2, we calculate audience shares corrected 

for changes in the composition of the entire SPPA 

population. The goal is to estimate how audience 

shares of different age groups would have changed if 

the overall composition of the population had not 

changed. In other words, we aimed to isolate changes 

in audience share that resulted from changes in 

respondents’ participation behavior from those that 

resulted simply from the growth or shrinkage of the 

size of a group.

These estimates require two steps. First, we 

calculated a set of correction factors that compare 

the population composition in each year to its 

composition across all five years. As these factors 

suggest in the 1980s, very young and very old age 

groups were overrepresented, compared with 

those between the ages of 40 and 59. By the end of 

the period, the Baby Boom had moved from 

young adulthood to older middle age. As a result, 

ages between 40 and 64 were overrepresented. 

(See Correction factor 1 table, page 78.)

The uncorrected audience share figures were 

divided by this correction factor to adjust for 

population change. However, because of differences 

in the composition of the participant population, this 

adjustment did not assure that the audience shares 

would add to 100 percent. Therefore, a second factor 

was applied to the preliminary corrected audience 

shares for each benchmark activity within each year 

so that they would add to 100 percent. This resulted 

in the final corrected audience share figures. 

(See Correction factor 2 table, page 78.)
78 National Endowment for the Arts

An alternative method for correcting audience share 

for population change is the calculation of an index 

of representativeness. The index was calculated 

by dividing each audience-share figure by that age 

group’s share of the entire population. This number 

was then multiplied by 100. Finally, we subtracted 

100 from the resulting figure, so that a positive 

number indicates overrepresentation and a negative 

number indicates underrepresentation

This index can be interpreted as the percent by 

which the audience share for a particular age group 

is larger or smaller than its share of the entire 

population. If the number is positive, then audience 

share exceeds share of population; if negative, 

then audience share is less than population share.

Correction factor 1

Age 1982 1985 1992 2002 2008

Less than 25 1.204 1.114 0.900 0.900 0.886

25–29 1.197 1.197 1.032 0.827 0.818

30–34 1.054 1.091 1.148 0.894 0.884

35–39 0.931 1.012 1.154 1.043 0.911

40–44 0.807 0.883 1.076 1.195 1.033

45–49 0.795 0.795 0.985 1.210 1.163

50–54 0.881 0.830 0.843 1.111 1.251

55–59 0.985 0.929 0.816 0.999 1.182

60–64 1.038 1.055 0.923 0.907 1.055

65–69 1.060 1.060 1.060 0.887 0.964

70 and over 0.921 0.940 1.013 1.059 1.050

Correction factor 2

1982 1985 1992 2002 2008

Jazz 0.946 0.968 0.988 0.986 0.985

Classical music 1.016 1.010 1.007 0.983 0.980

Opera 1.028 1.021 1.006 0.991 0.984

Musicals 1.009 1.006 1.002 0.990 0.995

Plays 1.008 1.006 1.005 0.990 0.995

Ballet 1.000 0.992 1.000 0.977 0.994

Other dance 1.000 0.988 0.997

Art museum 0.996 0.996 0.996 0.992 1.003

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