Background

The Assessment Process

In this report, we have done our best to obtain the opinions of a broad range of county residents. We believe it provides a fair picture of the quality of our community life – our assets, resources, and needs. We hope that this report solicits even greater participation in determining Cortland County’s priorities in the future.

Our Purpose

To provide baseline data and the foundation of a system that will periodically and accurately assess the quality of life in our county.
To put forth a set of indicators that will provide a widely accepted index for monitoring the well-being of the county.
To inform funding and policy decisions.
To qualify the county for funding from various public and private granting agencies.
To engage citizens in a priority-setting and monitoring process.
To complement the goals and progress of other entities in Cortland County working for our betterment.

Our Beliefs

A community pulling together -- citizens and experts, public and private sectors, town and gown, and many different disciplines -- can accomplish much. Working toward widely accepted priorities, informed citizens are the most effective agents for change.
A long-term, comparative view of our well being is useful in evaluating where we have been and establishing community priorities for the future.
Resources are more properly allocated and all members of the county benefit when there is a comprehensive plan in place.
Prevention and early intervention to address the community’s problems are more effective and less costly than remediation.

Data Sources

Public opinion has been obtained from numerous focus groups and surveys conducted in 2004 and 2005. In May 2005, the Seven Valleys Health Coalition conducted two non-random sample surveys, one of business leaders and the other of the general public, at the Business Showcase. Two hundred and fifty-seven neighbors were surveyed in the east end of the City of Cortland. Human service providers and key informants from the various fields of business, religion and government were surveyed for this study. The opinions put forth in the surveys and focus groups are reflected in the narrative areas of this report; summaries of the focus groups appear in the appendix. The sources of all objective data (U.S. Census, state and federal agencies, etc.) are referenced in the footnotes.

How to Read the Indicators

A number, by itself, usually means relatively little. This report seeks to compare Cortland indicators over time to the 57 New York counties that exclude NYC and to state and national data. Data from New York City sometimes skews the data for the entire state due to the city’s large high- and low-income populations. Therefore, it is usually better to compare Cortland to the 57-county composite, known as “the rest of the state,” or upstate New York.

1. Rates and Age-Specific Rates

The indicator numbers herein are usually expressed as rates -- the number of events per 1,000 or per 100,000 individuals per year. When the rate applies to a specific age group, the rate is called an age-specific rate. For example, the age-specific teen pregnancy rate would be the number of teen pregnancies per 1,000 females in the 15 to 19-year-old age group in a given year. Even though there are fewer teens in Cortland compared to a larger county, the rate allows us to compare similar units to one another. The 1999 teen pregnancy rate in Cortland County is 42.6 per 1,000 15-19 year old females. In Columbia County, that rate is 72.8 per 1,000. Despite the fact the Columbia County has fewer 15-19 year old females than Cortland County, its rate of teen pregnancy is higher. Absolute numbers would not show this. By comparing the rates, we can tell which county has the lower frequency of teen pregnancy relative to its population.

2. Confidence Interval

Some data are expressed as confidence intervals at specified levels. A confidence interval is a margin of error related to chance. For example, we might say that the percent of people who smoke cigarettes in Cortland County is 40.1% with a “confidence interval” of 22.7% to 57.6% at a 95% level. Expressed this way, we mean that there are 95 chances out of a 100 that the actual percentage of smokers in the population is somewhere between 22.7% and 57.6%. In general, the larger the sample drawn from a population, the smaller the confidence interval tends to be and thus the more likely the true rate corresponds to that from our sample.

3. Rolled Averages

Small numbers of events can be much more erratic over time than larger numbers of events. For example, if the measles cases in Cortland doubled in a year by going from 2 to 4 that would not be as statistically important as would be the doubling of cases of measles in the entire United States. Similarly, even small changes in the number of events occurring to Cortland’s small Native American population could cause the rate to vary substantially from year to year. For this reason, data from multi-year intervals are sometimes combined to give “rolled” averages. Rolled averages stabilize the rates and allow us to look at trends over time. For example, to report on hospitalizations of children due to asthma, the rates from each of three years are averaged and reported for the periods of 1996-1999, 1998-2000 and 2000-2002.

4. Age-Adjusted Rates

Age adjusted rates allow a comparison of rates between communities with different age structures. The incidence of cancer is one example of age-adjusted rates in this study.