Ping Du, F Bruce Coles, Patricia O'Campo, Louise-Anne McNutt
{"title":"Changes in population characteristics and their implication on public health research.","authors":"Ping Du, F Bruce Coles, Patricia O'Campo, Louise-Anne McNutt","doi":"10.1186/1742-5573-4-6","DOIUrl":null,"url":null,"abstract":"<p><p>Population estimates are generally drawn from one point in time to study disease trends over time; changes in population characteristics over time are usually not assessed and included in the study design. We evaluated whether population characteristics remained static and assessed the degree of population shifts over time. The analysis was based on the New York State 1990 and 2000 census data with adjustments for changes in geographic boundaries. Differences in census tract information were quantified by calculating the mean, median, standard deviation, and the percent of change for each population characteristic. Between 1990 and 2000, positive and negative fluctuations in population size created a U-shaped bimodal pattern of population change which increased the disparities in demographics and socioeconomic status for many census tracts. While 268 (10%) census tracts contracted by 10%, twice as many census tracts (21%, N = 557) grew at least 10%. Notably, the non-Hispanic African-American population grew 10% or more in 152 tracts. Although there were overall reductions in working class and undereducated populations and gains in incomes, most census tracts experienced growing income inequalities and an increased poverty rate. These changes were most pronounced in urban census tracts. Differences in population characteristics in a decade showed growing disparities in demographics and socioeconomic status. This study elucidates that important population shifts should be taken into account when conducting longitudinal research.</p>","PeriodicalId":87082,"journal":{"name":"Epidemiologic perspectives & innovations : EP+I","volume":"4 ","pages":"6"},"PeriodicalIF":0.0000,"publicationDate":"2007-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/1742-5573-4-6","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Epidemiologic perspectives & innovations : EP+I","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/1742-5573-4-6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Population estimates are generally drawn from one point in time to study disease trends over time; changes in population characteristics over time are usually not assessed and included in the study design. We evaluated whether population characteristics remained static and assessed the degree of population shifts over time. The analysis was based on the New York State 1990 and 2000 census data with adjustments for changes in geographic boundaries. Differences in census tract information were quantified by calculating the mean, median, standard deviation, and the percent of change for each population characteristic. Between 1990 and 2000, positive and negative fluctuations in population size created a U-shaped bimodal pattern of population change which increased the disparities in demographics and socioeconomic status for many census tracts. While 268 (10%) census tracts contracted by 10%, twice as many census tracts (21%, N = 557) grew at least 10%. Notably, the non-Hispanic African-American population grew 10% or more in 152 tracts. Although there were overall reductions in working class and undereducated populations and gains in incomes, most census tracts experienced growing income inequalities and an increased poverty rate. These changes were most pronounced in urban census tracts. Differences in population characteristics in a decade showed growing disparities in demographics and socioeconomic status. This study elucidates that important population shifts should be taken into account when conducting longitudinal research.