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At least 91 records · Page 5Linked to original sources
PubMed1981

Prevalence of Pediculus humanus capitis among school girls of Chuang-Wei and Nan-Ao Districts in I-Lan County and Man-Chow District in Ping-Tung County, Taiwan.

By using the naked eye examination and comb method, a field survey and combing collection of head louse (Pediculus humanus capitis) among school girls in three different area (Man-Chow, Nan-Ao and Chuang-Wei) of Taiwan were performed from July 1979 to February, 1980. The general infestation rate of head louse was 39.8% (or 998/2,509). In the primary schools, comparatively, the rate at Man-Chow (66.7%) was highest, the next at Nan-Ao (55.4%) and the lowest at Chuang-Wei (39.4%). While in the junior high schools, the rate was apparently higher at Nan-Ao (38.4%) than that at Man-Chow (15.6%) and Chang-Wei (12.0%). The highest rate in the primary schools was found in 3rd graders except at Chuang-Wei in 5th graders. The corresponding figure in the junior high schools was found in 1st graders except at Nan-Ao in 2nd graders. Of 774 infested girls studied, according to the number of lice per infested girl, the percentages of infestation in the 5 groups were: the very light (nits only) 54.5, light (1-10) 38.5, moderate (11-50) 6.5, heavy (51-100) 0.4 and very heavy (over 100) 0.1 respectively. Of 2,178 head lice examined, 53.0% was nymphs; 28.7% females; 18.2% males. The average number of head louse in each infested girl 6.2.

Age Factors↗
PubMed2006

Place-of-residence errors on death certificates for two contiguous U. S. counties.

BACKGROUND: Based on death certificate data, the Texas Department of Health Bureau of Vital Statistics calculates age adjusted all-cause mortality rates for each Texas county yearly. In 1998 the calculated rates for two adjacent Texas counties was disparate. These counties contain one city (Amarillo) and are identical in size. This study examined the accuracy of recorded county of residence for deaths in the two counties in 1998. In our jurisdiction, the county of residence is assigned by funeral homes. METHODS: A random sample of 20% of death certificates was selected. The accuracy of the county of residence was verified by using a large area map, Tax Appraisal District records, and U.S. Census Bureau databases. Inaccuracies in recording the county or zip code of residence was recorded. RESULTS: Eighteen of 354 (5.4%) death certificates recorded the incorrect county and 21 of 354 (5.9%) of death certificates recorded the zip code improperly. There was a 14.4% county recording error rate for one county compared to a 0.82% for the other county. The zip code error rate was similar for the two counties (5.9% vs. 5.8%). Of the county errors, 83% occurred for addresses within a zip code that contained addresses in both counties. CONCLUSION: This study demonstrated a large error rate (14%) in recording county of residence for deaths in one county. A similar rate was not seen in an adjacent county. This led to significant miscalculation of mortality rates for two counties. We believe that errors may have arisen in part from use of internet programs by funeral homes to assign the county of residence. With some of these programs, the county is determined by zip code, and when a zip code straddles two counties, the program automatically assigns the county whose name appears first in the alphabet. This type of error could be avoided if funeral homes determined the county of residence from Tax Appraisal District or Census Bureau records, both of which are available on the internet. This type of error could also be avoided if vital statistics offices verified the county and zip code of residence using official sources.

Journal Article↗
PubMed2003

Consideration of driver home county prohibition and alcohol-related vehicle crashes.

This study examines the characteristics of alcohol-related crashes in wet versus dry counties in the state of Kentucky, USA and incorporates the location of driver residences through use of geographic information system (GIS) analysis. Between 1991 and 1997, 39344 alcohol-related crashes by Kentucky residents on Kentucky State roads were reported. The location of the crash and the home ZIP code from the driver's address were used to consider distance from home in the GIS. Analysis of the crash data revealed that a similar proportion of crashes in wet and dry counties are alcohol-related but that a higher proportion of dry counties residents are involved in an alcohol-related crash. However, when the distance from home variable is considered, several results suggest that dry county residents may be driving further when consuming alcohol. In part due to the rural nature of dry counties, drivers from dry counties have both alcohol-related and non-alcohol related crashes farther from their homes than residents from wet counties. Alcohol-related crashes by dry county residents in wet counties are the greatest average distance from home while crashes by wet county residents in wet counties are the smallest average distance. Drivers from dry counties over 21 years of age have alcohol-related crashes significantly farther from home than those under 21 who would not legally be admitted to drinking establishments in the wet counties. Furthermore, residents from dry counties that do not border wet counties have alcohol-related crashes on average farther from home than the border county residents. These last three results provide circumstantial evidence that some dry county drivers may be driving to wet counties to consume alcohol thus increasing impaired driving exposure. In conclusion, by considering crash location and driver residence, these findings indicate that county-level prohibition is not necessarily effective in improving highway safety.

Accidents, Traffic↗
PubMed2003

Cancer mortality in a Texas county with prior uranium mining and milling activities, 1950-2001.

Uranium was discovered in Karnes County, Texas, in 1954 and the first uranium mill began operating in 1961 near Falls City. Uranium milling and surface and in situ mining continued in Karnes County until the early 1990s. Remediation of uranium tailings ponds was completed in the 1990s. There were three mills and over 40 mines operating in Karnes County over these years and potential exposure to the population was from possible environmental releases into the air and ground water. From time to time concerns have been raised in Karnes County about potential increased cancer risk from these uranium mining and milling activities. To evaluate the possibility of increased cancer deaths associated with these uranium operations, a mortality survey was conducted. The numbers and rates of cancer deaths were determined for Karnes County and for comparison for four 'control' counties in the same region with similar age, race, urbanisation and socioeconomic distributions reported in the 1990 US Census. Comparisons were also made with US and Texas general population rates. Following similar methods to those used by the National Cancer Institute, standardised mortality ratios (SMRs) were computed as the ratio of observed numbers of cancers in the study and control counties compared to the expected number derived from general population rates for the United States. Relative risks (RRs) were computed as the ratios of the SMRs for the study and the control counties. Overall, 1223 cancer deaths occurred in the population residing in Karnes County from 1950 to 2001 compared with 1392 expected based on general population rates for the US. There were 3857 cancer deaths in the four control counties during the same 52 year period compared with 4389 expected. There was no difference between the total cancer mortality rates in Karnes County and those in the control counties (RR = 1.0; 95% confidence interval 0.9-1.1). There were no significant increases in Karnes County for any cancer when comparisons were made with either the US population, the State of Texas or the control counties. In particular, deaths due to cancers of the lung, bone, liver and kidney were not more frequent in Karnes County than in the control counties. These are the cancers of a priori interest given that uranium might be expected to concentrate more in these tissues than in others. Further, any radium intake would deposit primarily in the bone and radon progeny primarily in the lung. Deaths from all cancers combined also were not increased in Karnes County and the RRs of cancer mortality in Karnes County before and in the early years of operations (1950-64), shortly after the uranium activities began (1965-79) and in two later time periods (1980-89, 1990-2001) were similar, 1.0, 0.9, 1.1 and 1.0, respectively. No unusual patterns of cancer mortality could be seen in Karnes County over a period of 50 years, suggesting that the uranium mining and milling operations had not increased cancer rates among residents.

Death Certificates↗
PubMedDate not supplied

Health care for children and youth in the United States: annual report on patterns of coverage, utilization, quality, and expenditures by a county level of urban influence.

OBJECTIVE: To examine child and hospital demographics and children's health care coverage, use, expenditures, and quality by a county-level measure of urban influence. METHODS: Two national health care databases serve as the sources of data for this report: the 2002 Medical Expenditure Panel Survey (MEPS) and the 2002 Nationwide Inpatient Sample (NIS) and State Inpatient Databases (SID) from the Healthcare Cost and Utilization Project (HCUP). In both data sets, county urbanicity is defined by use of a collapsed version of the 2003 Urban Influence Codes, to distinguish among children residing in and hospitals located in large metropolitan (metro) counties, small metro counties, micropolitan counties, and noncore counties. RESULTS: Demographics. In large metro counties, greater percentages of the child population are Hispanic or black non-Hispanic than in small metro, micropolitan, and noncore counties; in micropolitan and noncore counties, higher proportions of children are below 200% of the federal poverty level than in large metro and small metro counties. Noncore areas have a greater percentage of children in fair or poor health compared with those in small metro and micropolitan counties. Most hospitals are located in large and small metro areas, and large metro areas have a higher proportion of teaching hospitals compared with other areas. Health care. In general, there were no overall differences by place of residence in the proportion of children with and without insurance, although differences emerged in subpopulations within Urban Influence Code types. Hispanic children residing in large metro counties were more likely to be uninsured than those in small metro counties. Overall, the proportion of children with at least one dental visit was larger in small metro areas compared with both large metro and noncore areas. The proportion of children with medicines prescribed was generally lower in large metro areas compared with all other areas both overall and among subpopulations of children. Children in noncore areas were more likely to have a hospital inpatient stay and any emergency department use compared with children in large metro areas. Children in large metro counties had longer average inpatient stays and a higher hospital inpatient charge per day compared with children in all other counties. Although most hospitalizations for children from large metro areas occurred in large metro areas, over half of hospitalizations for noncore children occurred outside of noncore counties. Further, children from noncore counties appear to be hospitalized for ambulatory sensitive conditions more than children from all other areas. CONCLUSIONS: County-level data analyses performed using a collapsed version of the Urban Influence Codes with MEPS and HCUP data shed additional light on the health care patterns for children that were not previously evident when only the dichotomous metropolitan/nonmetropolitan geographic schema was used.

Adolescent↗