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理解残疾与多病共存之间的关联,以及印度老年人口的医疗保健利用情况:来自 SAGE-2 的横断面证据的见解。

Understanding the association of disability with multimorbidity, and healthcare utilization in India's older adult population: insights from cross-sectional evidence of SAGE-2.

机构信息

ICMR-Regional Medical Research Centre, Bhubaneswar, India.

South Asian Institute of Health Promotion, Bhubaneswar, India.

出版信息

Front Public Health. 2024 Oct 23;12:1435315. doi: 10.3389/fpubh.2024.1435315. eCollection 2024.

DOI:10.3389/fpubh.2024.1435315
PMID:39507660
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11537888/
Abstract

BACKGROUND

Like other low-and middle-income countries, India is undergoing a demographic and epidemiologic shift that has led to a significant rise in the burden of non-communicable diseases (NCDs). Evidence suggests that chronic illnesses and disability are linked but limited studies have explored the association between disability and multimorbidity (simultaneous presence of two or more chronic conditions). Since the magnitude of multimorbidity is becoming a norm, it is prudent to understand the association between these two. We aimed to estimate the association between disability and multimorbidity and assess their healthcare utilization among older adults in India using a nationally representative data.

METHODS

We employed data from the second round of World Health Organization's Study on Global AGEing and adult health (SAGE) conducted in 2015. SAGE is a nation-wide survey conducted among a representative sample of older adults aged ≥50 years, a total of 7,118 participants aged ≥50 years were included in the analysis. The main outcome of interest was disability for which we used WHODAS 2.0 scoring scale which ranges from 0 to 100. Descriptive statistics such as frequency and proportion were used to report the characteristics of study population, and prevalence. We performed the univariable followed by multiple ordinal logistic regression to assess the association between disability and multimorbidity, reported as adjusted odds ratio (AOR) with 95% confidence interval (CI) and -value. Healthcare utilization was presented as frequency and proportion.

RESULTS

The overall prevalence of disability was found to be 89.0% (95% CI: 88.3-89.8) while that of multimorbidity was 39.7% (95% CI: 35.6-37.8). Most of the participants had moderate followed by mild disability. Hypertension (32.7%) was found to be the most prevalent chronic condition followed by cataract (21.3%). The chances of having disability among multimorbid individuals was AOR: 1.40 (95% CI: 1.13-1.75). Participants having disability and multimorbidity mostly visited private sector followed by public healthcare facilities.

CONCLUSION

We observed that nine out of every 10 individuals had some kind of disability in India. We observed multimorbidity to be associated with disability that signifies the need for including disabilities as a part of NCD program as these factors could be bi-directional. Longitudinal studies for disability will be helpful to better understand and address the growing needs of these individuals.

摘要

背景

与其他中低收入国家一样,印度正在经历人口和流行病学的转变,这导致非传染性疾病(NCDs)的负担显著增加。有证据表明,慢性病和残疾是相关的,但有限的研究探索了残疾和多种疾病(同时存在两种或多种慢性疾病)之间的关联。由于多种疾病的程度正在成为一种常态,因此了解这两者之间的关联是明智的。我们的目的是使用全国代表性数据估计印度老年人残疾和多种疾病之间的关联,并评估他们的医疗保健利用情况。

方法

我们使用了 2015 年世界卫生组织全球老龄化和成人健康研究(SAGE)第二轮的数据。SAGE 是一项在代表性的 50 岁以上老年人样本中进行的全国性调查,共有 7118 名 50 岁以上的参与者纳入了分析。主要的研究结果是残疾,我们使用了 WHODAS 2.0 评分量表,范围从 0 到 100。描述性统计,如频率和比例,用于报告研究人群的特征和患病率。我们进行了单变量和多元有序逻辑回归,以评估残疾和多种疾病之间的关联,报告为调整后的优势比(AOR)及其 95%置信区间(CI)和 - 值。医疗保健利用情况以频率和比例表示。

结果

我们发现,残疾的总体患病率为 89.0%(95%CI:88.3-89.8),而多种疾病的患病率为 39.7%(95%CI:35.6-37.8)。大多数参与者患有中度残疾,其次是轻度残疾。高血压(32.7%)是最常见的慢性疾病,其次是白内障(21.3%)。在多种疾病患者中,残疾的可能性为 AOR:1.40(95%CI:1.13-1.75)。患有残疾和多种疾病的参与者大多去私人部门,其次是公共医疗保健设施。

结论

我们发现,印度每 10 人中就有 9 人患有某种残疾。我们观察到多种疾病与残疾有关,这表明需要将残疾作为非传染性疾病计划的一部分,因为这些因素可能是双向的。关于残疾的纵向研究将有助于更好地理解和满足这些人的需求。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/209d/11537888/26baec391669/fpubh-12-1435315-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/209d/11537888/708805622d2c/fpubh-12-1435315-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/209d/11537888/26baec391669/fpubh-12-1435315-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/209d/11537888/708805622d2c/fpubh-12-1435315-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/209d/11537888/26baec391669/fpubh-12-1435315-g002.jpg

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