OCR Text |
Show were provided a map of their locality showing the proposed small area boundaries and asked to consider whether the combined ZIP code areas were similar in terms of lifestyle and demographic characteristics. Several changes were made based on their recommendations. Data on population size, median age, and median income were purchased for current Utah ZIP codes from a commercial vendor, CACI Marketing Systems. CACI constructed population estimates at the ZIP code level by using the most recent decennial census data and additional information, such as sub-county estimates of change from the U.S. Census Bureau, special censuses, local sources of information about change, and changes in residential delivery statistics from the U.S. Postal Service. Estimates included 1997 population totals and population by sex and age group for each ZIP code, allowing for age standardization. The CACI file also included estimates for the average annual rate of population change for each ZIP code area, which allowed for the derivation of 1994 through 1996 population estimates required for the analyses. The 61 small areas were used to examine several health measures. Four health measures were selected because they represented variables from a variety of health data sources that yielded geographic differences: motor vehicle death rates, percentages of mothers giving birth who had no prenatal care in the first trimester, percentages of persons who were without health insurance, and percentages of persons who smoked cigarettes. When comparing across geographic areas, some method of age-adjusting is typically used to control for area-to-area differences in health events that can be explained by differing ages of the area populations. For example, an area that has an older population will have higher crude (not age-adjusted) rates for cancer, even though its exposure levels and cancer rates for specific age groups are the same as those of other areas. One might incorrectly attribute the high cancer rates to some characteristic of the area other than age. Age-adjusted rates control for age effects, allowing better comparability of rates across areas. Direct standardization adjusts the age-specific rates observed in the small area to the age distribution of a standard population (Lilienfeld & Stolley, 1994). This method can present problems when age-group-specific rates for small areas are unstable. In such cases, indirect standardization of rates may be used. Indirect standardization adjusts the overall standard population rate to the age distribution of the small area (Lilienfeld & Stolley, 1994). It is technically appropriate to compare indirectly standardized rates only with the rate in the standard population, not with each other. In some cases, the investigator will not want to age-adjust. For instance, he or she may be interested in the actual cancer rates in an area for the purposes of targeting a screening program. Age-adjusting is not necessary when only age-specific rates are used, or when the population of study has a narrow age range. For purposes of comparing overall rates of disease across areas, age-adjusting was performed for three of the four variables in this study. Age-adjusting procedures are indicated below for each of the four variables. Motor vehicle crash deaths information was derived from a computer file of all deaths in Utah from 1980 to 1996, obtained from the Utah Department of Health Bureau of Vital Records, which excluded information that would identify individuals. Cases consisted of deaths of Utah residents occurring in the five year period from 1992 through 1996 in which motor vehicle crash was recorded on the death certificate as the underlying cause of death (International Classification of Diseases, Version 9, codes E810 to E825), and were assigned to an area according to the residence of the decedent. The motor vehicle death data were age-adjusted because factors other than age were of primary interest. The indirect method of age-adjustment was used because there were small numbers of deaths in individual age strata. Confidence intervals were calculated using a method recommended for indirectly standardized rates (Kahn & Sempos, 1989). For the motor vehicle data, 90% confidence intervals were used. The information on prenatal care was derived from a computer file of all births in Utah from 1980 to 1996 obtained from the Utah Department of Health Bureau of Vital Records, which excluded information that would identify individuals. Information regarding the month of pregnancy that prenatal care began originated from either a medical record or a parent's self-report, and is recorded on the birth certificate at the time of the infant's birth. Cases consisted of mothers giving live birth during the three year period from 1994 through 1996, and were assigned to the area of residence of the mother. Prenatal care data were not age-adjusted because the population has a relatively narrow age range and because information on prenatal care is traditionally used to target interventions, rather than to explain between-area differences. The 95% confidence intervals for these data were calculated using a method suggested by Fleiss 20 |