ORANGE COUNTY ANNUAL SURVEY

INTRODUCTION

This year, the Orange County Annual Survey highlights growth and its effects on the quality of local 
life. This topic moved to the forefront in 1987, and may play a very prominent role in next year's 
voting. It has joined traffic congestion among the most discussed issues in the county.

Is growth and development leading to a decline in the quality of life in orange County? Will local growth 
controls endanger the quality of life? We cannot fully answer these questions with public opinion data. 
But this year's survey offers new insights into how people perceive growth and the quality of life in 
Orange County, and the extent to which these issues are linked in residents' minds.

"Quality of life" is a rather ambiguous phrase that means something different to scholars than it does to 
the general public. Our study defines quality of life as a general evaluation of personal happiness and 
community satisfaction. But realizing that others define it differently, we go a step further and ask 
everyone in our survey what they think the term means.

We began with several questions in exploring what accounts for the "quality of life" ratings. Does 
personal happiness lead to community satisfaction? Are residents with higher incomes happier with their 
lives and with Orange County? How do housing ideals, community preferences and perceptions of current 
county problems affect evaluations of county life?

We are also interested in the extent to which concerns about quality of life are affecting the 
public-policy arena in Orange County. In particular, we explore whether quality of-life perceptions fuel 
interests in growth initiatives and result in pessimism about the county's future.

Of course, we continue our close watch this year on the topic of transportation and traffic congestion. 
This is the daily issue most on people's minds, a problem in desperate need of a publicly acceptable 
solution. The links with both quality of life and growth issues are obvious. We measure satisfaction 
about the county's freeways and attitudes about improving the system. We see if commuting behavior has 
charged since 1982. And we test to see if current conditions are leading to hopelessness and pessimism 
about ever improving the current traffic congestion in Orange County.

We also review the housing trends in Orange County. These include new figures on mortgage costs, rents, 
and the types of dwellings people live in as well as the affordability and choice of housing now 
available in the county. These issues have significant impact on residents' quality of life.

This year, we introduce a new issue that we plan to track on an annual basis. While much has been said 
about local charitable preferences and giving patterns, we find that very little actually is known on 
this important topic. Charity is a significant community issue, not only in its own right, but also as a 
barometer of local involvement, social concern and community attachment. Therefore, we begin this year a 
long-term commitment to tracking actual charitable giving and exploring attitudes towards charitable 
causes.

We also examine economic well-being and political attitudes in Orange County. In October, we provided 
subscribers with two pre-releases on these topics, and now, we review these findings in greater depth. We 
offer November survey data from a Register Poll to update consumer - confidence since the October stock 
market crash. And in light of our findings on attitudes about growth, we examine the likelihood of local 
political realignment.

Growth and the quality of life are complex issues. Therefore, we have used several methods to analyze the 
results of this year's survey. We examine time-series trends for the many "tracking" questions that have 
been asked repeatedly in the Orange County Annual Survey. Whenever possible, we compare the results of 
our survey to national figures. We contrast residents' responses in the North, West, Central, and South 
regions of the county. 

Age, income, sex, and other demographic differences in attitudes are examined. And finally, we employ 
multivariate statistical models to determine the strongest causes of certain opinions and to link the key 
findings in different attitude domains.