How to weight chronic diseases in multimorbidity indices? Development of a new method on the basis of individual data from five population-based studies

Diederichs, Claudia; Wellmann, Jürgen; Bartels, Dorothee B.; Ellert, Ute; Hoffmann, Wolfgang; Berger, Klaus

doi:10.1016/j.jclinepi.2011.11.006

Cited by 31 publications

(23 citation statements)

References 38 publications

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“…For example, an individual with multiple sclerosis alone would not be considered to have multimorbidity despite having severalfold worse HRQoL ( plus the associated burden of medication use and health-care utilization) than an individual with multiple conditions of lesser severity. Some multimorbidity indices weight diseases through nonstandard, semiquantitative measures, such as subjective ratings by patients or providers (3,28). However, these indices are less translatable, and findings obtained using them are less comparable with those of other studies.…”

Section: Comparison With Prior Studiesmentioning

confidence: 99%

Diverse Cumulative Impact of Chronic Diseases on Physical Health–Related Quality of Life: Implications for a Measure of Multimorbidity

Wei¹,

Kawachi²,

Okereke³

et al. 2016

Am. J. Epidemiol.

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Debate continues on how to measure and weight diseases in multimorbidity. We quantified the association of a broad range of chronic diseases with physical health-related qualify of life and used these weights to develop and validate a multimorbidity weighted index (MWI). Community-dwelling adults in 3 national, prospective studies-the Nurses' Health Study (n = 121,701), Nurses' Health Study II (n = 116,686), and Health Professionals Follow-up Study (n = 51,529)-reported physician-diagnosed diseases and completed the Short Form 36 physical functioning (PF) scale over multiple survey cycles between 1992 and 2008. Mixed models were used to obtain regression coefficients for the impact of 98 morbid conditions on PF. The MWI was formed by weighting conditions by these coefficients and was validated through bootstrapping. The final sample included 612,592 observations from 216,890 participants (PF mean score = 46.5 (standard deviation, 11)). The association between diseases and PF varied severalfold (median, −1.4; range, −10.6 to 0.8). End-stage organ diseases were associated with the greatest reduction in PF. The mean MWI score was 4.8 (median, 3.7; range, 0-53), and the mean number of comorbid conditions was 3.3 (median, 2.8; range, 0-34). This validated MWI weights diseases by severity using PF, a patient-centered outcome. These results suggest that simple disease count is unlikely to capture the full impact of multimorbidity on health-related quality of life, and that the MWI is feasible and readily implemented. comorbidity; health-related quality of life; multimorbidity; multiple chronic conditions; physical functioning; Short Form 36Abbreviations: HPFS, Health Professionals Follow-up Study; HRQoL, health-related qualify of life; MWI, multimorbidity weighted index; NHS, Nurses' Health Study; PF, physical functioning; SF-36, Short Form 36.

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Section: Comparison With Prior Studiesmentioning

confidence: 99%

Diverse Cumulative Impact of Chronic Diseases on Physical Health–Related Quality of Life: Implications for a Measure of Multimorbidity

Wei¹,

Kawachi²,

Okereke³

et al. 2016

Am. J. Epidemiol.

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“…UPDRS items for TD and PIGD designations were used to calculate mean TD and PIGD scores, as previously suggested [1], and the population was classified according to the motor subtype into TD, PIGD or indeterminate. Concomitant diseases and voluptuary habits associated with increased vascular risk (diabetes, hypertension, myocardial infarction, obesity, smoking) were recorded in order to calculate the comorbidity index, a measure of the disease burden, previously tested on general and neurological populations, including the present PD cohort [14,15].…”

Section: Clinical Evaluationmentioning

confidence: 99%

White matter changes and the development of motor phenotypes in de novo Parkinson's Disease

Moccia

Tedeschi

Ugga

et al. 2016

Journal of the Neurological Sciences

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“…[1][2][3] Multimorbidity is associated with a higher mortality risk and increased utilisation of healthcare services; therefore, it is a demanding situation for patients, their families and healthcare providers. [4][5][6][7][8] Despite the increase in life expectancy among lower and middle income countries over the last decades, the growing prevalence of multimorbidity has led to a decreased quality of life in patients with chronic diseases, especially in populations with limited resources. 9 10 Patients with multimorbidity require specific medical care; however, the current clinical practice lacks practical guidelines to manage and treat these patients.…”

Section: Introductionmentioning

confidence: 99%

Multimorbidity as an important issue among women: results of a gender difference investigation in a large population-based cross-sectional study in West Asia

et al. 2017

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ObjectivesTo investigate the impact of gender on multimorbidity in northern Iran.DesignA cross-sectional analysis of the Golestan cohort data.SettingGolestan Province, Iran.Study population49 946 residents (age 40–75 years) of Golestan Province, Iran.Main outcome measuresResearchers collected data related to multimorbidity, defined as co-existence of two or more chronic diseases in an individual, at the beginning of a representative cohort study which recruited its participants from 2004 to 2008. The researchers utilised simple and multiple Poisson regression models with robust variances to examine the simultaneous effects of multiple factors.ResultsWomen had a 25.0% prevalence of multimorbidity, whereas men had a 13.4% prevalence (p<0.001). Women of all age-groups had a higher prevalence of multimorbidity. Of note, multimorbidity began at a lower age (40–49 years) in women (17.3%) compared with men (8.6%) of the same age (p<0.001). This study identified significant interactions between gender as well as socioeconomic status, ethnicity, physical activity, marital status, education level and smoking (p<0.01).ConclusionPrevention and control of multimorbidity requires health promotion programmes to increase public awareness about the modifiable risk factors, particularly among women.

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How to weight chronic diseases in multimorbidity indices? Development of a new method on the basis of individual data from five population-based studies

Cited by 31 publications

References 38 publications

Diverse Cumulative Impact of Chronic Diseases on Physical Health–Related Quality of Life: Implications for a Measure of Multimorbidity

Diverse Cumulative Impact of Chronic Diseases on Physical Health–Related Quality of Life: Implications for a Measure of Multimorbidity

White matter changes and the development of motor phenotypes in de novo Parkinson's Disease

Multimorbidity as an important issue among women: results of a gender difference investigation in a large population-based cross-sectional study in West Asia

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