美国泌尿科医生密度与前列腺癌死亡率的地理分析

数据集获取（Figshare）

• 源站标题：Geographic Analysis of Urologist Density and Prostate Cancer Mortality in the United States
• DOI：10.1371/journal.pone.0131578
• 发布日期：2015-06-25
• 文件数：7 个
• 文件总体积：1.96 MB
• 源站页面：https://plos.figshare.com/articles/dataset/_Geographic_Analysis_of_Urologist_Density_and_Prostate_Cancer_Mortality_in_the_United_States_/1464725

命令行下载

curl -L -o "S1_Fig.pdf" "https://ndownloader.figshare.com/files/2150265"
curl -L -o "S2_Fig.pdf" "https://ndownloader.figshare.com/files/2150266"
curl -L -o "S3_Fig.pdf" "https://ndownloader.figshare.com/files/2150267"
curl -L -o "S4_Fig.pdf" "https://ndownloader.figshare.com/files/2150268"
curl -L -o "S5_Fig.pdf" "https://ndownloader.figshare.com/files/2150269"
curl -L -o "S1_File.pdf" "https://ndownloader.figshare.com/files/2150270"
curl -L -o "S1_Table.pdf" "https://ndownloader.figshare.com/files/2150271"

文件清单

• S1_Fig.pdf（271.93 KB）
• S2_Fig.pdf（428.47 KB）
• S3_Fig.pdf（199.32 KB）
• S4_Fig.pdf（248.75 KB）
• S5_Fig.pdf（220.29 KB）
• S1_File.pdf（529.20 KB）
• S1_Table.pdf（65.63 KB）

文件总体积 1.96 MB（源站 API 实测）。

数据加载示例（表格/文本类）

import pandas as pd, glob, os

files = (glob.glob(os.path.join(path, "**", "*.csv"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tsv"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.xlsx"), recursive=True))
print("数据文件:", files)
df = pd.read_csv(files[0])
print(df.shape); print(df.columns.tolist()); print(df.head(3))

数据说明

Context
Financial and demographic pressures in US require an understanding of the most efficient distribution of physicians to maximize population-level health benefits. Prior work has assumed a constant negative relationship between physician supply and mortality outcomes throughout the US and has not addressed regional variation.
Methods
In this ecological analysis, geographically weighted regression was used to identify spatially varying relationships between local urologist density and prostate cancer mortality at the county level. Data from 1,492 counties in 30 eastern and southern states from 2006–2010 were analyzed.
Findings
The ordinary least squares (OLS) regression found that, on average, increasing urologist density by 1 urologist per 100,000 people resulted in an expected decrease in prostate cancer mortality of -0.499 deaths per 100,000 men (95% CI -0.709 to -0.289, p-value Conclusions
The strength of association between urologist density and prostate cancer mortality varied regionally. Those areas with the highest potential for effects could be targeted for increasing the supply of urologists, as it associated with the largest predicted improvement in prostate cancer mortality.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0131578（source: https://plos.figshare.com/articles/dataset/_Geographic_Analysis_of_Urologist_Density_and_Prostate_Cancer_Mortality_in_the_United_States_/1464725）。