肥胖与商业人群医疗资源利用和成本的关联

数据集获取（Figshare）

• 源站标题：Association of obesity with healthcare resource utilization and costs in a commercial population
• DOI：10.6084/m9.figshare.6138845.v1
• 发布日期：2018-04-13
• 文件数：5 个
• 文件总体积：73.53 KB
• 源站页面：https://tandf.figshare.com/articles/dataset/Association_of_obesity_with_healthcare_resource_utilization_and_costs_in_a_commercial_population/6138845

命令行下载

curl -L -o "icmo_a_1464435_sm5764.docx" "https://ndownloader.figshare.com/files/11080193"
curl -L -o "icmo_a_1464435_sm5763.docx" "https://ndownloader.figshare.com/files/11080196"
curl -L -o "icmo_a_1464435_sm5762.docx" "https://ndownloader.figshare.com/files/11080199"
curl -L -o "icmo_a_1464435_sm5761.docx" "https://ndownloader.figshare.com/files/11080202"
curl -L -o "icmo_a_1464435_sm5760.docx" "https://ndownloader.figshare.com/files/11080205"

文件清单

• icmo_a_1464435_sm5764.docx（14.38 KB）
• icmo_a_1464435_sm5763.docx（14.14 KB）
• icmo_a_1464435_sm5762.docx（14.42 KB）
• icmo_a_1464435_sm5761.docx（16.14 KB）
• icmo_a_1464435_sm5760.docx（14.45 KB）

文件总体积 73.53 KB（源站 API 实测）。

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。

数据说明

Objective: To examine the association of obesity with healthcare resource utilization (HRU) and costs among commercially insured individuals.
Methods: This retrospective observational cohort study used administrative claims from 1 January 2007 to 1 December 2013. The ICD-9-CM status codes (V85 hierarchy) from 2008 to 2012 classified body mass index (BMI) into the World Health Organizations’ BMI categories. The date of first observed BMI code was defined as the index date and continuous eligibility for one year pre- and post- index date was ensured. Post-index claims determined individuals’ HRU and costs. Sampling weights developed using the entropy balance method and National Health and Nutrition Examination Survey data ensured representation of the US adult commercially insured population. Baseline characteristics were described across BMI classes and associations between BMI categories, and outcomes were examined using multivariable regression.
Results: The cohort included 9651 individuals with BMI V85 codes. After weighting, the BMI distribution was: normal (31.1%), overweight (33.4%), obese class I (22.0%), obese class II (8.1%) and obese class III (5.4%). Increasing BMI was associated with greater prevalence of cardiometabolic conditions, including hypertension, type 2 diabetes and metabolic syndrome. The use of antihypertensives, antihyperlipidemics, antidiabetics, analgesics and antidepressants rose with increasing BMI. Greater BMI level was associated with increased inpatient, emergency department and outpatient utilization, and higher total healthcare, medical and pharmacy costs.
Conclusions: Increasing BMI was associated with higher prevalence of cardiometabolic conditions and higher HRU and costs. There is an urgent need to address the epidemic of obesity and its clinical and economic impacts.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.6084/m9.figshare.6138845.v1（source: https://tandf.figshare.com/articles/dataset/Association_of_obesity_with_healthcare_resource_utilization_and_costs_in_a_commercial_population/6138845）。