人口特征的变化及其对公共卫生研究的启示。

Ping Du, F Bruce Coles, Patricia O'Campo, Louise-Anne McNutt
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引用次数: 9

摘要

人口估计通常从一个时间点得出,以研究一段时间内的疾病趋势;人群特征随时间的变化通常不被评估,也不包括在研究设计中。我们评估了种群特征是否保持不变,并评估了种群随时间变化的程度。该分析基于纽约州1990年和2000年的人口普查数据,并根据地理边界的变化进行了调整。通过计算每个人口特征的平均值、中位数、标准差和变化百分比来量化普查区信息的差异。1990年至2000年期间,人口规模的正负波动造成了人口变化的u型双峰模式,这增加了许多人口普查区在人口和社会经济地位方面的差距。268个(10%)人口普查区收缩了10%,而两倍多的人口普查区(21%,N = 557)增长了至少10%。值得注意的是,152个地区的非西班牙裔美国人人口增长了10%或更多。虽然工人阶级和受教育程度低的人口总体减少,收入增加,但大多数人口普查区的收入不平等现象日益严重,贫困率上升。这些变化在城市人口普查区最为明显。十年来人口特征的差异表明人口和社会经济地位的差距越来越大。本研究阐明了在进行纵向研究时应考虑重要的人口变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Changes in population characteristics and their implication on public health research.

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.

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