宽带互联网采用与美国各县自我报告的糖尿病患病率之间的关系
Matthew S Farmer1, Kimberly R Powell, Anne Sales
1Author Affiliation: Sinclair School of Nursing, University of Missouri, Columbia.
Computers, informatics, nursing : CIN
|July 10, 2025
概括
家庭互联网使用率的增加与美国各县糖尿病患病率的降低有关. 这项研究强调互联网接入是健康的关键社会决定因素,影响公共卫生结果.
科学领域:
- 公共卫生 公共卫生
- 医疗信息学 医疗信息学
- 社会流行病学 社会流行病学
背景情况:
- 互联网提供了重要的健康资源,但家庭有限的互联网接入对健康结果的影响仍然不清楚.
- 了解数字沟在健康差异中的作用对于公共卫生干预至关重要.
研究的目的:
- 调查家庭使用互联网与美国各县的自我报告糖尿病患病率之间的关联.
- 分析采用互联网作为健康的潜在社会决定因素,控制其他社会经济因素.
主要方法:
- 采用2021年美国社区调查和行为风险因素监测系统的县级数据进行的横截面,回顾性研究.
- 采用描述性统计,两阶段线性回归和机器学习技术进行分析.
- 分析了来自美国3076个县的数据.
主要成果:
- 在县级观察到互联网采用和糖尿病患病率 (β = -.20,P < .001) 之间存在统计学意义上的反向关系.
- 较高的家庭互联网使用率与较低的糖尿病患病率相关,即使考虑到健康的社会决定因素.
- 调查结果表明,随着互联网普及的增加,糖尿病患病率在县级下降.
结论:
- 家庭使用互联网成为健康的重要社会决定因素,影响糖尿病患病率.
- 这项研究提供了证据,支持数字访问在减轻糖尿病等负面健康结果中的作用.
- 建议进行进一步的研究,以探索个人层面的数据和与糖尿病风险相关的特定健康行为.
相关概念视频
Diabetes Mellitus: Overview and Type I Subtype
3.2K
Diabetes mellitus is a chronic metabolic disorder characterized by high blood glucose levels due to inadequate insulin production, insulin resistance, or both. The condition affects millions worldwide and can significantly impact their health and quality of life.
Type 1 diabetes is an autoimmune disease in which the immune system mistakenly attacks and destroys the insulin-producing beta cells in the pancreas. As a result, the body is unable to produce sufficient insulin, and individuals with...
Type 1 diabetes is an autoimmune disease in which the immune system mistakenly attacks and destroys the insulin-producing beta cells in the pancreas. As a result, the body is unable to produce sufficient insulin, and individuals with...
3.2K
Diabetes Mellitus: Type 2 and Gestational
2.9K
Type 2 diabetes, characterized by insulin resistance, arises when the insulin receptors on cells lose responsiveness to insulin, diminishing the cell's capacity to take up glucose, resulting in elevated blood glucose levels. To receive a diagnosis of Type 2 diabetes, a series of blood glucose tests are necessary to assess whether the blood glucose falls within normal parameters. If the result is out of the normal range, a patient may be diagnosed as prediabetic or diabetic, depending on the...
2.9K
Diabetes: Symptoms, Diagnosis, and Complications
684
For most patients, experiencing several weeks of polyuria, polydipsia, fatigue, and significant weight loss may indicate the presence of diabetes. Furthermore, adults displaying the phenotypic appearance of type 2 diabetes (particularly those who are obese and not initially insulin-requiring), may have islet cell autoantibodies, suggesting autoimmune-mediated β cell destruction and a diagnosis of latent autoimmune diabetes of adults (LADA). The categorization of glucose homeostasis is...
684
Diabetes: Management and Pharmacotherapy
354
The therapy for diabetes aims to alleviate hyperglycemia-related symptoms, prevent acute metabolic decompensation, and reduce chronic end-organ complications. Glycemic control is evaluated through short-term (self-monitoring, continuous glucose monitoring) and long-term (A1c, fructosamine) metrics, enabling near real-time tracking of blood glucose levels and reflecting glycemic control over specific time frames.
Insulin remains the cornerstone of treatment for most patients with type 1 and many...
Insulin remains the cornerstone of treatment for most patients with type 1 and many...
354
Pathophysiology of Diabetes
1.2K
Diabetes mellitus is a chronic metabolic disorder characterized by hyperglycemia. The four categories of diabetes are type 1 diabetes, type 2 diabetes, other specific types of diabetes, and gestational diabetes.
Type 1 diabetes is characterized by autoimmune-mediated destruction of pancreatic β cells, with environmental factors potentially triggering this process in genetically susceptible individuals. Despite many not having a family history, certain genes increase susceptibility,...
Type 1 diabetes is characterized by autoimmune-mediated destruction of pancreatic β cells, with environmental factors potentially triggering this process in genetically susceptible individuals. Despite many not having a family history, certain genes increase susceptibility,...
1.2K
Bias in Epidemiological Studies
666
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
666


