{"title":"以社区为基础的印度农村人群的多病模式","authors":"Balaji Gummidi, Vaishali Gautam, Oommen John, Arpita Ghosh, Vivekanand Jha","doi":"10.1177/26335565221149623","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Multimorbidity estimates are expected to increase in India primarily due to the population aging. However, there is a lack of research estimating the burden of multimorbidity in the Indian context using a validated tool. We estimated the prevalence and determinants of multimorbidity amongst the adult population of the rural Uddanam region, Andhra Pradesh.</p><p><strong>Methods: </strong>This community-based cross-sectional study was conducted as a part of an ongoing research program. Multistage cluster sampling technique was used to select 2419 adult participants from 40 clusters. Multimorbidity was assessed using Multimorbidity Assessment Questionnaire for Primary Care (MAQ-PC) tool, collecting information on 13 chronic diseases. Patient Health Questionnaire (PHQ-12) was used to screen for depression. Multiple logistic regression was conducted to identify the strongest determinants of multimorbidity.</p><p><strong>Results: </strong>Of the 2419 participants, 2289 completed the MAQ-PC tool. Mean age (standard deviation) of participants was 48.1 (13.1) years. The overall prevalence of multimorbidity was 58.5% (95% CI 56.5-60.6); with 30.7%, 15.6%, and 12.2% reporting two, three, and four chronic conditions, respectively. Acid peptic disease-musculoskeletal disease (44%) and acid peptic disease-musculoskeletal disease-hypertension (14.9%) were the most common dyad and triad. Among metabolic diseases, diabetes-hypertension (28.3%) and diabetes-hypertension-chronic kidney disease (7.6%) were the most common dyad and triad, respectively. Advancing age, female gender, and being obese were the strongest determinates of the presence of multimorbidity. Depression was highly prevalent among the study population, and participants with higher PHQ-12 score had 3.7 (2.5-5.4) greater odds of having multimorbidity.</p><p><strong>Conclusions: </strong>Our findings suggest that six of 10 adults in rural India are affected with multimorbidity. We report a higher prevalence of multimorbidity as compared with other studies conducted in India. We also identified vulnerable groups which would guide policy makers in developing holistic care packages for individuals with multimorbidity.</p>","PeriodicalId":73843,"journal":{"name":"Journal of multimorbidity and comorbidity","volume":"13 ","pages":"26335565221149623"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/c0/d6/10.1177_26335565221149623.PMC9832245.pdf","citationCount":"2","resultStr":"{\"title\":\"Patterns of multimorbidity among a community-based cohort in rural India.\",\"authors\":\"Balaji Gummidi, Vaishali Gautam, Oommen John, Arpita Ghosh, Vivekanand Jha\",\"doi\":\"10.1177/26335565221149623\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Multimorbidity estimates are expected to increase in India primarily due to the population aging. However, there is a lack of research estimating the burden of multimorbidity in the Indian context using a validated tool. We estimated the prevalence and determinants of multimorbidity amongst the adult population of the rural Uddanam region, Andhra Pradesh.</p><p><strong>Methods: </strong>This community-based cross-sectional study was conducted as a part of an ongoing research program. Multistage cluster sampling technique was used to select 2419 adult participants from 40 clusters. Multimorbidity was assessed using Multimorbidity Assessment Questionnaire for Primary Care (MAQ-PC) tool, collecting information on 13 chronic diseases. Patient Health Questionnaire (PHQ-12) was used to screen for depression. Multiple logistic regression was conducted to identify the strongest determinants of multimorbidity.</p><p><strong>Results: </strong>Of the 2419 participants, 2289 completed the MAQ-PC tool. Mean age (standard deviation) of participants was 48.1 (13.1) years. The overall prevalence of multimorbidity was 58.5% (95% CI 56.5-60.6); with 30.7%, 15.6%, and 12.2% reporting two, three, and four chronic conditions, respectively. Acid peptic disease-musculoskeletal disease (44%) and acid peptic disease-musculoskeletal disease-hypertension (14.9%) were the most common dyad and triad. Among metabolic diseases, diabetes-hypertension (28.3%) and diabetes-hypertension-chronic kidney disease (7.6%) were the most common dyad and triad, respectively. Advancing age, female gender, and being obese were the strongest determinates of the presence of multimorbidity. Depression was highly prevalent among the study population, and participants with higher PHQ-12 score had 3.7 (2.5-5.4) greater odds of having multimorbidity.</p><p><strong>Conclusions: </strong>Our findings suggest that six of 10 adults in rural India are affected with multimorbidity. We report a higher prevalence of multimorbidity as compared with other studies conducted in India. 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引用次数: 2
摘要
背景:由于人口老龄化,预计印度的多重疾病估计将增加。然而,在印度缺乏使用有效工具评估多重发病负担的研究。我们估计了安得拉邦乌达纳姆地区农村成年人中多病的患病率和决定因素。方法:这项以社区为基础的横断面研究是一项正在进行的研究计划的一部分。采用多阶段整群抽样方法,从40个整群中抽取2419名成年参与者。采用初级保健多发病评估问卷(MAQ-PC)工具对13种慢性疾病进行多发病评估。患者健康问卷(PHQ-12)用于筛查抑郁症。进行了多重逻辑回归来确定多重发病的最强决定因素。结果:在2419名参与者中,2289人完成了MAQ-PC工具。参与者的平均年龄(标准差)为48.1(13.1)岁。多病总患病率为58.5% (95% CI 56.5-60.6);30.7%, 15.6%和12.2%分别报告了两种,三种和四种慢性疾病。酸性消化性疾病-肌肉骨骼疾病(44%)和酸性消化性疾病-肌肉骨骼疾病-高血压(14.9%)是最常见的二、三联征。在代谢性疾病中,糖尿病-高血压(28.3%)和糖尿病-高血压-慢性肾病(7.6%)分别是最常见的二联体和三联体。高龄、女性和肥胖是多重发病的最强决定因素。抑郁症在研究人群中非常普遍,PHQ-12得分较高的参与者有3.7(2.5-5.4)的多病几率。结论:我们的研究结果表明,印度农村10个成年人中有6个患有多重疾病。与在印度进行的其他研究相比,我们报告了更高的多病患病率。我们还确定了弱势群体,这将指导政策制定者为患有多种疾病的个人制定整体护理方案。
Patterns of multimorbidity among a community-based cohort in rural India.
Background: Multimorbidity estimates are expected to increase in India primarily due to the population aging. However, there is a lack of research estimating the burden of multimorbidity in the Indian context using a validated tool. We estimated the prevalence and determinants of multimorbidity amongst the adult population of the rural Uddanam region, Andhra Pradesh.
Methods: This community-based cross-sectional study was conducted as a part of an ongoing research program. Multistage cluster sampling technique was used to select 2419 adult participants from 40 clusters. Multimorbidity was assessed using Multimorbidity Assessment Questionnaire for Primary Care (MAQ-PC) tool, collecting information on 13 chronic diseases. Patient Health Questionnaire (PHQ-12) was used to screen for depression. Multiple logistic regression was conducted to identify the strongest determinants of multimorbidity.
Results: Of the 2419 participants, 2289 completed the MAQ-PC tool. Mean age (standard deviation) of participants was 48.1 (13.1) years. The overall prevalence of multimorbidity was 58.5% (95% CI 56.5-60.6); with 30.7%, 15.6%, and 12.2% reporting two, three, and four chronic conditions, respectively. Acid peptic disease-musculoskeletal disease (44%) and acid peptic disease-musculoskeletal disease-hypertension (14.9%) were the most common dyad and triad. Among metabolic diseases, diabetes-hypertension (28.3%) and diabetes-hypertension-chronic kidney disease (7.6%) were the most common dyad and triad, respectively. Advancing age, female gender, and being obese were the strongest determinates of the presence of multimorbidity. Depression was highly prevalent among the study population, and participants with higher PHQ-12 score had 3.7 (2.5-5.4) greater odds of having multimorbidity.
Conclusions: Our findings suggest that six of 10 adults in rural India are affected with multimorbidity. We report a higher prevalence of multimorbidity as compared with other studies conducted in India. We also identified vulnerable groups which would guide policy makers in developing holistic care packages for individuals with multimorbidity.