Community Health Profile

The Community Health Profile (CHP) has been a valuable resource to track trends in the health of local communities and to inform programming and policy-making decisions. From 1998 through 2012, the Yale-Griffin PRC received funding from the CDC to prepare 5 editions of the CHP, starting first with data from Ansonia, Beacon Falls, Derby, Oxford, Seymour and Shelton, and periodically revised over the years to include more data from a broader geographic area. In 2014, the Valley Community Foundation enlisted DataHaven to produce The Valley Community Index, which replaced the CHP in response to the local desire for even more comprehensive data collection.

Below is the final edition (2009-2010) of the CHP prepared by the PRC, with data from communities served by the Naugatuck Valley Health District (Ansonia, Beacon Falls, Derby, Naugatuck, Seymour, Shelton), and the Pomperaug Health District (Oxford, Southbury, Woodbury), along with data from Bridgeport, Hartford, New Haven, and the state of Connecticut. It includes a searchable database with the ability to generate custom reports to track trends at the local, regional, or state level. 

View Profiles

Use the links below to view or download the Community Health Profile (PDF files) .

CHP Methods and Sources of Data

Data were collected on the six towns of the Lower Naugatuck Valley (Ansonia, Beacon Falls, Derby, Oxford, Seymour and Shelton), Bridgeport, Hartford and New Haven from publicly available data sources (e.g. the Department of Public Health). Specific demographics of these towns are available in subsequent sections of this document (see Population Statistics).

The 1998, 2000, and 2003 Valley Health Profiles were reviewed to assess sections of the document that needed updating.

The collection of data to update the Community Health Profile was conducted mainly via publicly available datasets. Data sources used in the previous report were contacted and electronic data were accessed through the Internet or hard copies were sent to the center for manual data re-entry.
Data storage: Phone interviews, data collection, manipulation and presentation took place at the Yale-Griffin Prevention Research Center in Griffin Hospital, Derby, CT under the supervision of David Katz, MD, MPH, and Veronika Northrup, MPH.

Incidence and mortality data are presented in frequency tables, rates (per 100,000 people), and graphs. For trend analysis, rates of individual towns in the Valley, as well as total Valley rates were compared to rates of Bridgeport, Hartford, New Haven, and Connecticut, by examining confidence intervals around the rates (see Definitions of Rates and Terms). An overlap in confidence intervals indicated no statistically significant difference between rates. The purpose of this statistical testing is to establish whether two rates are truly different, or that there is a statistical chance that the rates are not different. That statistical chance is based on the existence of a random error in the calculation of the true rate. (Such error can come from a reporting error or a mistake in entering data). For example, if a rate is 100 with 95 percent of the time falling within the bounds of 89 and 111 interval, is that rate statistically different from a rate of 115, which 95 percent of the time falls within the bounds of 105 and 125? In this case, there is a chance that the first rate (given that a random error in the calculation of the rate exists) can be equal to 105, which is the number that falls within the bounds of the second rate’s true value. Therefore, the two rates are not statistically different. Caution should be taken in translating a statistical finding, or a lack thereof, into a significant finding. If a rare event, such as a rare disease, takes place in a small population, the magnitude of an incidence rate can fluctuate from one time point to another time point. However, a seemingly large difference between two incidence rates of a rare event in a small population may not be statistically significant based on the examination of the confidence intervals around each rate. A decision to establish a significant trend of some event should take into consideration a statistical significance testing, the nature of the event and the size of the population.

Definition of Rates and Terms

TermSorted By Term In Ascending OrderDefinition
Age-adjusted death rate

To allow for valid comparisons of rates between populations, the age-specific death rate is multiplied by the number of persons in the corresponding age group in the standard population (in this case Connecticut). This method shows the number of deaths that would have occurred in the standard population if the age-specific death rates in the individual population had occurred.

Age-specific death rate
Number of deaths in a specific age group
---------------------------------------------------------- x 100,000
Total resident population in specific age group
Birth weight

The first weight of a fetus or infant at time of delivery. This weight is usually measured during the first hour of life, before postnatal weight loss occurs.

Cause of death

The underlying cause of death determined to be the primary condition leading to death, based on the international rules and sequential procedure set forth for manual classification of the underlying causes of death by the National Center for Health Statistics and the World Health Organization (International Classification of Disease, Ninth Revision).

Chronic Lower Respiratory Disease (CLRD)

Currently the fourth leading cause of death in the United States, CLRD compromises three major diseases, i.e. chronic bronchitis, emphysema, and asthma. The airway obstruction is irreversible in chronic bronchitis and emphysema, and reversible in asthma. Before 1999, CLRD was called Chronic Obstructive Pulmonary Disease (COPD). The International Classification of Diseases used by the World Health Organization (WHO) to code diseases and mortality was revised in 1999, with slight changes to the category between the 9th and 10th editions.

Confidence Limit of IR (Lower 95%)

IR - (1.96 X Standard Error)

Confidence Limit of IR (Upper 95%)IR + (1.96 X Standard Error)
Confidence Limit of SMR (Lower 95%)

SMR – [(1.96 X Standard Error) X 100]

Confidence Limit of SMR (Upper 95%)

SMR + [(1.96 X Standard Error) X 100]

Crude birth rateNumber of resident live births
-------------------------------------------------------- x 1,000
Total resident population
Crude death rate (CDR)Number of resident deaths
---------------------------------------------------- x 100,000
Total resident population

The number of deaths per 100,000 people. This rate should not be used for making comparisons between different populations when the age, race, and sex distributions of the populations are different. (See "Age-adjusted death rate" and "Age-specific death rate.")

Crude vs. Specific Rate

A crude rate is a rate that applies to an entire population, for example, a crude incidence rate of a disease refers to the number of new cases of that disease divided by the total population, without reference to age or gender or any other population characteristic. A specific rate is a rate that applies to or is calculated within a particular sub-group of a population, for example, the age-specific death rate is the number of deaths due to a certain health risk occurring in a particular age group, divided by the number of people at risk in that age group.

Fetal death

Death prior to the complete expulsion or extraction from the mother of a product of conception, which has passed through at least the 20th week of gestation. The fetus shows no signs of life such as heartbeat, pulsation of the umbilical cord, or movement of voluntary muscles.

Fetal death rate*

Number of fetal deaths
-------------------------------------------------------- x 1,000
Number of live births

*This fraction is often referred to as a ratio, rather than a rate, because the denominator (live births) does not contain the numerator (fetal deaths).

Gestational age

The number of completed weeks elapsed between the first day of the last normal menstrual period (LMP) and the date of delivery.


The frequency (number) of new occurrences of disease, injury, or death in the study population during the time period being examined.

Incidence Rate (IR)

The number of new cases during a defined period of time, divided by the population at risk

Expected Number of Deaths

IR = ------------------------------------------

Population Size at midpoint of the study period
Income Estimates

All income estimates are expressed in current year dollars using the “money income” definition reported in the 2000 census. In contrast to the 1990 census, which reported income for the previous calendar year (1989), income estimates are for the calendar year relevant to each set of estimates and projections. As with the demographic estimates and projections, data are produced first at the national level, then for progressively smaller areas, with successive ratio adjustments ensuring consistency between levels. Per capita and aggregate income are estimated first. Aggregate income is the total of all income for all persons in an area, and per capita is the average income per person—or aggregate income divided by total estimated population. Income earned by persons in group quarters facilities is estimated separately, and subtracted from aggregate income to derive aggregate household income—or the total income earned by persons living in households. Aggregate household income divided by total estimated households is the estimate of average household income.

Infant death

Death occurring to an individual of less than one year (365 days) of age, comprising the sum of neonatal death and postneonatal death.

Infant death rate

Number of infant deaths
-------------------------------------------------------- x 1,000
Number of live births

Kessner Index (Modified)

The Kessner Index is a composite indicator of the adequacy of prenatal care a mother receives during her pregnancy. Prenatal care is categorized as adequate, intermediate, or inadequate based on three items from the birth certificate: timing of the first prenatal visit; total number of prenatal visits; and length of gestation. The term, non-adequate prenatal care, which is the sum of the intermediate and the inadequate levels of care, is used in Table 2-A, B, C of the present report. A more detailed definition of the Modified Kessner Index and reference documents can be obtained from the Connecticut Department of Public Health, Office of Policy, Planning and Evaluation.

Live birth

The complete expulsion or extraction from the mother of a product of conception, regardless of the duration of pregnancy; after such separation, shows signs of life (e.g., heartbeat, pulsation of the umbilical cord, or movement of voluntary muscles.)

Live birth order

The number of children born alive to the same mother, including the current birth (first born, second born, third born, etc.).

Low birth weight

A birth weight of less than 2,500 grams (approximately 5 lbs., 8 oz.).

Neonatal death

Death occurring to an infant less than 28 days of age.

Standard Error of the Incidence Rate (SEIR)SEIR = IR / √Incident Cases
Standard Error of the SMR multiplied by 1.96 (SESMR X 1.96)

Multiplying the Standard Error by 1.96 allows for the calculation of the 95% confidence interval for the Standardized Mortality Ratio. Thus, the 95% confidence interval would signify that the Standardized Mortality Ratio of a particular disease in a specific ‘population under study’ would range from the lower limit to the upper limit of the 95% confidence interval.

Standard Error of the Standardized Mortality Ratio (SESMR)

SESMR = Square root of the variance of the SMR

Note: Normally the square root of the variance equals the standard deviation and not the standard error. The standard error is derived by dividing the standard deviation by the square root of the sample size. However, (according to statistical proofs that are beyond the scope of this paper), in these calculations the standard error is simply the square root of the variance.

Standardized Mortality Ratio (SMR)

Observed Crude Death Rate
-------------------------------------- X 100
Expected Crude Death Rate

The Standardized Mortality Ratio is used to compare the cause-specific death rate in a standard population to the cause-specific death rate for the same disease in other populations. Comparisons are possible because the standard population (namely Connecticut) will have an SMR equal to 100 for each cause of death in question. the ‘population under study’ (e.g. Valley) has an SMR that is under 100 for a specific cause of death (e.g. heart disease), then the rate of death for heart disease will be lower the Valley than in Connecticut. On the other hand, if the Valley has an SMR for Heart Disease that is greater than 100, then the rate of death for heart disease would be higherin the Valley than in Connecticut.

Tuberculosis (TB) – Active

Exhibiting a positive PPD (purified protein derivative) and signs and symptoms of TB.