- Research article
- Open Access
Self-rated health in multimorbid older general practice patients: a cross-sectional study in Germany
BMC Family Practice volume 15, Article number: 1 (2014)
With increasing life expectancy the number of people affected by multimorbidity rises. Knowledge of factors associated with health-related quality of life in multimorbid people is scarce. We aimed to identify the factors that are associated with self-rated health (SRH) in aged multimorbid primary care patients.
Cross-sectional study with 3,189 multimorbid primary care patients aged from 65 to 85 years recruited in 158 general practices in 8 study centers in Germany. Information about morbidity, risk factors, resources, functional status and socio-economic data were collected in face-to-face interviews. Factors associated with SRH were identified by multivariable regression analyses.
Depression, somatization, pain, limitations of instrumental activities (iADL), age, distress and Body Mass Index (BMI) were inversely related with SRH. Higher levels of physical activity, income and self-efficacy expectation had a positive association with SRH. The only chronic diseases remaining in the final model were Parkinson’s disease and neuropathies. The final model accounted for 35% variance of SRH. Separate analyses for men and women detected some similarities; however, gender specific variation existed for several factors.
In multimorbid patients symptoms and consequences of diseases such as pain and activity limitations, as well as depression, seem to be far stronger associated with SRH than the diseases themselves. High income and self-efficacy expectation are independently associated with better SRH and high BMI and age with low SRH.
MultiCare Cohort study registration: ISRCTN89818205.
Multimorbidity is an issue of increasing importance to the health care system. The prevalence of multimorbidity rises from 10 percent in the 0 to 19 year-olds up to 78 percent in people aged 80 years and older . As a consequence of an increasing life expectancy, the number of people affected by multimorbidity will probably steadily grow. However, little is known about the impact of multimorbidity on health-related quality of life of elderly primary care patients.
Factors associated with health-related quality of life have been studied in the general population as well as in patient-populations suffering from different chronic diseases. Several studies indicated a positive association between higher education and income with better self-rated health (SRH) [4–6]. The relationship between age, gender and SRH, however, is less clear [5–7]. Modifiable lifestyle factors, such as obesity, smoking, risky alcohol consumption and low levels of physical activity were found to have a negative correlation with health-related quality of life [8–10]. Furthermore, several studies concurrently report a negative association between depressive symptoms and chronic pain and SRH [11, 12], respectively. In recent years, research has particularly focused on the relationship between different chronic diseases and health-related quality of life. Neurological diseases, cancer and rheumatoid arthritis have been reported as conditions associated with low SRH among the elderly . With increasing age the prevalence of chronic diseases, disability and limitations of activities of daily living rises, with limitations of daily activities being associated with lower levels of SRH .
Although a lot is known about factors correlated with SRH in the general population, knowledge of corresponding factors in aged multimorbid patients is scarce. Important questions remain: Is SRH in multimorbid patients more strongly affected by the presence of single disease states or by the sequelae of illnesses (i.e. pain, limitations of daily living)? What are demographic (i.e. age, education and income), lifestyle (i.e. BMI, smoking, alcohol consumption, level of physical activity) and psychological factors (i.e. depression, social support and self-efficacy expectation) associated with SRH in this patient group? Is SRH determined by the same factors in men and women or are there gender-specific differences? Therefore, the aim of this study was twofold: First, to identify the factors that are independently related to SRH in a multimorbid primary care sample of elderly people; and second, to identify possible gender-related differences in these factors.
Multimorbidity is usually defined as the presence of two or more illnesses at the same time. In the inspection of the diagnosis distribution it however became clear that two or more chronic illnesses were present in practically all our elderly patients. We thereupon defined multimorbidity as the presence of at least three chronic illnesses. In addition, in order to ensure a large number of patterns of multimorbidity, the very frequent illnesses with a prevalence of over 25% (e.g. hypertension, hyperlipidemia) were not considered for the inclusion in the sample. Nevertheless, these highly prevalent diagnoses are frequently combined with the relatively lower prevalent ones and are therefore still part of the sample. A detailed list of the 29 diseases used for inclusion of multimorbid patients can be found elsewhere . This list was newly compiled at the beginning of the MultiCare-Study and represents the most frequent chronic conditions in the population based on prevalence data.
Data analyzed in this study came from the baseline investigation of the German MultiCare-Study , conducted from July 2008 to October 2009.
Patients were recruited in 8 study centers across Germany (Bonn, Düsseldorf, Frankfurt/Main, Hamburg, Jena, Leipzig, Mannheim and Munich). In each city about 20 general practitiosners (GPs) were recruited and asked to provide the study group with a list containing all of their patients between 65 and 85 years (date of birth 1.7.1923 to 30.6.1943), who had at least one consultation in the most recent quarter.
In each surgery, approximately 50 patients of those who suffered from at least three different chronic diseases out of a reference list of 29 chronic conditions  and did not meet the exclusion criteria (see below), were drawn at random. Multimorbidity was determined by chart review. These patients were contacted and asked to participate.
Exclusion criteria were:
● Residence in a nursing home
● Severe illness probably lethal within three months according to the GP
● Insufficient ability to speak and read German language
● Insufficient ability to consent (e.g. due to dementia)
● Insufficient ability to participate in interviews (e.g. due to blindness, deafness)
● Patients with no regular consultations and therefore poorly known to the GP
● Participation in other studies
Patients who met the inclusion criteria and were willing to participate were visited at home or in the GP practice and interviewed by a trained investigator. A set of standardized questionnaires was used to collect variables belonging to the area of socio-demography, lifestyle, psychological and illness-related factors. Table 1 provides an overview of the standardized instruments. The GPs measured height and weight at the patients’ next routine consultation in the surgery.
SRH was measured with the visual analogous scale (VAS) of the EuroQoL-5D (EQ-5D) . With one single question (“In general, how would you rate your health status today?”) patients were asked to rate their subjective health status on a scale from “0” representing the worst to “100” representing the best possible health status.
Socio-demographic variables included age, gender, marital status and living conditions. Educational level was categorized as low, intermediate or high according to the CASMIN (Comparative Analysis of Social Mobility in Industrial Nations) classification , a certificate-orientated classification scheme developed by an international research group. Equivalent income was calculated from the total household income by using the per capita demand weighting scale  of the Organization for Economic Cooperation and Development (OECD). It was calculated as household total net income per month divided by the equivalised household size, which gives 1.0 to the householder, 0.5 to other household members aged 15 or over and 0.3 to each child aged less than 15 years old.
Lifestyle variables included physical activity (IPAQ-7) , alcohol consumption (AUDIT-C) , smoking behavior and Body Mass Index (BMI). Smoking behavior was assessed by asking the patient the following question: “Are you a regular smoker, occasional smoker, former smoker or non-smoker?”
Psychological variables ascertained in the patient-interview included perceived social support (F-SOZU K-14) , patients’ self-efficacy expectation (SWE) , depression (GDS)  and symptoms belonging to the four dimensions somatization, depression, anxiety and distress (4 DBL) .
Illness related factors
Patients were asked for the presence of chronic diseases. The interviewer read 32 chronic diseases (Table 2) to the patients who respectively responded with either “yes” or “no” to indicate whether they did or did not suffer from a particular chronic disease. Further, pain intensity and pain associated disability (GCPS)  were assessed. Additionally, grade of independence in performing basic (Barthel-Index)  and instrumental activities of daily living (iADL)  were illness-related factors that were rated by the interviewer.
Missing values were substituted by the hot-deck method. This technique identifies the most similar case in the sample (nearest neighbor distance) and uses this value for imputation . If more than one case were possible for the imputation one case was selected by chance. Imputation was done with the R - 2.13.0 package StatMatch . A detailed description of the substitution process can be found elsewhere . For all variables the missing value rate was less than 2 percent except the variable total household income which had a missing value rate of 12.2 percent.
The data were analyzed using the Statistical Package for the Social Sciences (SPSS, Version 19.0). Means (M) and standard deviations (SD) were calculated for continuous variables and frequencies, as well as percentages, for categorical variables. Group differences were tested for statistical significance either by χ2-test or t-test as appropriate. Linearity of the relationship between independent variables and SRH was controlled by visual inspection. Bivariate associations between risk factors and SRH were analyzed by Pearson’s correlation and differences by t-test.
Variables that showed a significance level of p ≤ 0.01 in the bivariate analyses were entered into multivariable linear regression analyses in a stepwise forward manner, with SRH as the dependent variable. Multivariable linear regression analyses were performed for the whole sample as well as for men and women separately.
The study protocol was approved by the Ethics Committee of the Medical Association of Hamburg (Approval Nr. 2881) and by the Ethics Committees of the participating study centers. Written consent was obtained from every participant after being completely informed about the study.
A total of 50,786 patients in the database of the participating GPs fulfilled the age criterion and had at least one GP contact in the last quarter. Out of those 24,862 were randomly selected and checked for the presence of at least three chronic diseases and exclusion criteria. After exclusion of the patients without multimorbidity and those who met the exclusion criteria, 7,172 patients remained and were contacted. Out of those 3,317 agreed to participate (response rate 46.2%). In total, data of 3,189 patients were included in the final analyses. The difference of 128 cases between the 3,317 patients who agreed to participate and the 3,189 whose data it was possible to include in the statistical analysis is due to the fact that patients died before they could be interviewed or that exclusion criteria became obvious only after sample selection. A more detailed description of sampling and response rate, as well as a non-responder analysis can be found elsewhere .
Characterization of the study population
Table 3 summarizes the mean values in demographic, lifestyle and psychological variables separately for men and women. Women represented 59.3% of the study participants. Mean EQ-VAS value of the whole sample was 62.5 (SD = 18.2); men had a significant higher mean SRH of 63.6 (SD 18.4) compared to 61.6 (SD 18.0) in women (p = 0.003, see Table 4). The prevalence of self-reported diseases is presented in Table 2. Hypertension (present in 72.3%), joint arthrosis (present in 55.4% of the men and 73.9% of the women) and chronic low back pain (present in 54.1% of the men and 67.5% of the women) were the most frequently reported diseases in the study population.
The bivariate analyses suggested that all continuous variables showed weak but highly significant (p < 0.001) correlations with the dependent variable SRH (Table 5). Similarly, for all demographic and lifestyle variables and for most individual chronic diseases significant differences in SRH values were found. Table 4 presents differences between groups. Age and female gender was associated with lower SRH values and income, education, being married and living together with others are socio-demographic factors that were positively associated with SRH. A negative association was found between depression, anxiety, somatization and mental distress and SRH. Self-efficacy expectation and social support were psychological factors positively associated with SRH. Among the variables which showed no significant differences in mean SRH values were smoking and the presence or absence of lipid metabolism disorders, thyroid dysfunction, prostate hyperplasia, non-inflammatory gynecological problems, cardiac valve disorders, kidney stones, psoriasis and malignant tumors.
Multiple regression analyses
Table 6 shows the factors remaining in the final regression model when the whole sample was analyzed. These factors explained 35% of the variance in SRH. The intensity of chronic pain, pain associated disability, depressive symptoms, somatization, high BMI levels (all p < 0.001), age (p = 0.001), psychological distress (p = 0.01), a self-reported diagnosis of Parkinson’s disease (p = 0.003) and neuropathies (p = 0.008) had a significant negative effect on SRH. Significantly positive relationships were found between SRH and physical activity, independency in instrumental activities, higher monthly income (all p < 0.001) and self-efficacy expectation (p = 0.002).
Factors associated with SRH when multiple regression analyses were conducted for men and women separately are presented in Table 7. Separate analyses were able to explain equal amounts of variance in SRH in both genders. In men, seven variables explained 34% of the variance of SRH, whereas, in women eleven variables were found to explain 35% of the variance of SRH. In both genders depression, somatization and pain associated disability had a negative effect on SRH (all p < 0.001). Physical activity (p < 0.001) had a positive effect on SRH. Low or intermediate education (p < 0.001) and a self-reported diagnosis of cardiac arrhythmia (p = 0.004) were associated with reduced SRH in men. In women pain intensity, high BMI, distress (all p < 0.001), age (p = 0.001) and chronic low back pain (p = 0.004) were significantly negatively associated with SRH. SRH was better among women with higher monthly income (p = 0.009).
In both genders a negative association between SRH and restrictions in activities of daily living was found. Whereas in men lower SRH scores were associated with restrictions in basic activities of daily living (p < 0.001), in women restrictions in instrumental activities (p < 0.001) resulted in significantly lower SRH values.
The present study aimed to identify socio-demographic, lifestyle, psychological and disease-related factors associated with SRH in a large sample of elderly multimorbid general practice patients. To the best of our knowledge there are no studies that investigated SRH in multimorbid samples of comparable size and age.
Whereas in the bivariate analyses nearly all variables showed significant correlations with SRH, the final regression model for the whole sample included 13 of the initially more than 50 variables. Lifestyle variables like current smoking and alcohol consumption [36, 37] that were often found to influence SRH were not independently associated with SRH in our sample. But BMI and physical activity were lifestyle factors independently associated with SRH in our study. We found that increasing BMI reduced and physical activity increased SRH, respectively. The finding of high BMI as a correlate of low SRH was confirmed by other studies [38, 39], but not by all . Several studies support the strong relationship between high levels of physical activity and better SRH [36, 41–43].
In our multimorbid sample the association between socioeconomic factors and SRH seems to be weaker than in other samples . Age and income were the only socioeconomic variables independently correlated with SRH in the whole sample.Among the psychological factors depression, somatization and distress significantly reduced SRH whereas self-efficacy expectation increased SRH. It might be that in a sample of multimorbid elderly patients somatization probably reflects true physical symptoms representing diseases rather than unspecific somatic complaints. The association between mental distress [44–46] and depression [42, 47–49] and SRH was shown in many studies. We suspect that psychological factors exist that mediate the subjective rating of health in patients suffering from multiple chronic diseases. Those with high expectations of self-efficacy and low levels of stress and depression probably cope better with multimorbidity.
Not surprisingly, among the disease-related factors single diseases were less influential for SRH in our sample than sequelae of diseases like pain intensity, disability caused by pain and restrictions in instrumental activities. It appears as if general factors like pain, disability, depression, somatic complaints, restrictions in physical activity and independent living, which accumulate in multimorbid patients due to the presence of multiple chronic diseases, affect SRH more than single self-reported diseases. Based on the fact that every patient in our sample having at least three diagnoses, it is not surprising that most diseases do not contribute independently to the explained variance of SRH. It might be, that in a general population sample with a lower prevalence of diagnoses the result would be different.
Gender-specific analyses indicated that there are no differences in the relationship between somatization, depression, pain associated disability, and low physical activity and SRH in men and women. It seems that in both genders consequences of and complaints due to multimorbidity explain most of the variance of SRH. Besides these most important factors, we found different variables to be associated with SRH specifically in men and women. As found in a previous study , education was associated with SRH only in men. A possible explanation might be that in most families the total household income is more dependent on men’s than on women’s educational level. BMI values revealed a negative association with SRH exclusively in women, in line with a study from the US which showed a stronger association between high BMI values and low SRH scores in aged women compared to aged men . Chronic low back pain and characteristic pain intensity were negatively related to SRH exclusively in women. Therefore, it appears that in women SRH is more affected by pain than in men.
Most importantly, we found SRH to be predominantly associated with modifiable factors. This suggests that SRH could be improved through specific interventions at the level of primary care. Main focus should be on modifiable aspects and consequences of multimorbidity: appropriate interventions of pain treatment and reduction; thorough exploration of somatic symptoms, since they could reflect sequelae of multimorbidity as well as potential side and interaction effects of polypharmacy. In order to improve SRH, physical complaints should be relieved, be it by improving patients compliance to or by adjusting the medication. Besides the reduction of pain and somatic complaints, depression provides another important starting point for improvement of SRH. The high burden of physical complaints and symptoms could make it difficult to reliably detect and diagnose depression in elderly multimorbid patients. Screening for and when indicated, treatment of depression should be standard in multimorbid patients. In addition, patients’ health-related behavior should be the target of interventions in order to improve SRH. Possible interventions are: participation on special training programs for elderly that focus on weight reduction and simultaneously increase physical activity; rehabilitation interventions for those patients who have restrictions in functional abilities.
Strengths and weaknesses
A major strength of our study was the large number of multimorbid general practice patients assessed that were spread over eight study centers distributed throughout Germany. In contrast to other studies of comparable size, which are generally based on postal or telephone surveys, our study data was collected by face-to-face interviews. In our study a larger set of variables was collected and tested for associations than in comparable studies. To enhance accuracy of the diagnoses used for inclusion of multimorbid patients, GPs’ diagnoses were used for selection of participants. Nevertheless, GPs’ diagnoses are also not entirely valid . Despite the fact that participants were of advanced age and suffering from multimorbidity we obtained a satisfactory response rate.
We decided to measure the health related life quality by means of a global visual analog scale. To this it could be objected that such a simple scale were not capable of representing all facets of the complex construct: life quality. According to Idler and Benyamini , however, it was possible to show that global self-ratings of health reflect “the respondents’ views of global health in a way that nothing else can” (p. 34). We used an analog scale in order to allow the patients to include their own dimensions into their concept of health-related quality-of-life.
However, the present study also had some limitations. Most of the information was obtained through self-report, which may reduce the validity of the information. For example, questions about alcohol consumption, smoking behavior and physical activity may have been answered in a socially acceptable manner. Conversely, it can be seen as an advantage of our study that information regarding BMI was directly measured by the physician and the ability to perform instrumental and basic activities was rated by the interviewer based on the patients’ narration. Although electronic health records are more reliable in detecting multimorbidity in younger patients, the prevalence of multimorbidity in elderly patients appears to be the same for electronic health records as for self-reports . Patients living in a nursing home and those suffering from dementia or severe illness of terminal stage were excluded from the sample. Therefore, it is possible that certain aspects of multimorbidity are not represented in our sample. Due to the cross-sectional character of our data, the direction of the relationship between SRH and independent factors remains unclear.
SRH is a pivotal indicator of quality of life. The identification of factors influencing health-related quality of life in elderly multimorbid patients gains in importance in our aging society.
We found the strongest correlation between SRH and disease sequelae, but only few diseases and only those with a high burden of symptoms or limitations were independently associated with low SRH. In women SRH seemed to be more strongly associated with pain, whereas, in men threats of limitations of activity seemed to play a larger role.
In conclusion, perception of health and health-related quality of life at an older age might be improved by treatment of disease sequelae such as pain and discomfort. To enhance quality of life in the elderly, particular attention might be paid to the diagnosis and treatment of depression.
Alcohol use disorders identification test
Body mass index
Comparative analysis of social mobility in industrial Nations
Chronic obstructive pulmonary disease
- F-SOZU K-14:
Fragebogen zur sozialen Unterstützung
Graded chronic pain scale
Geriatric depression scale
Instrumental activities of daily living
International physical activities questionnaire
Organization for economic cooperation
Peripheral arterial occlusive disease
Statistical package for the social sciences
Visual analogous scale
Four dimensional symptom questionnaire.
van den Akker M, Buntinx F, Metsemakers JF, Roos S, Knottnerus JA: Multimorbidity in general practice: prevalence, incidence, and determinants of co-occurring chronic and recurrent diseases. J Clin Epidemiol. 1998, 51: 367-375. 10.1016/S0895-4356(97)00306-5.
Idler EL, Benyamini Y: Self-rated health and mortality: a review of twenty-seven community studies. J Health Soc Behav. 1997, 38: 21-37. 10.2307/2955359.
Idler EL, Russell LB, Davis D: Survival, functional limitations, and self-rated health in the NHANES I epidemiologic follow-up study, 1992. First National health and nutrition examination survey. Am J Epidemiol. 1992, 2000 (152): 874-883.
Elwell-Sutton TM, Jiang CQ, Zhang WS, Cheng KK, Lam TH, Leung GM, et al: Socioeconomic influences at different life stages on health in Guangzhou, China. Soc Sci Med. 2011, 72: 1884-1892. 10.1016/j.socscimed.2011.03.041.
Barros MB, Zanchetta LM, Moura EC, Malta DC: Self-rated health and associated factors, Brazil, 2006. Rev Saude Publica. 2009, 43 (Suppl 2): 27-37.
Lubetkin EI, Jia H, Franks P, Gold MR: Relationship among sociodemographic factors, clinical conditions, and health-related quality of life: examining the EQ-5D in the U.S. general population. Qual Life Res. 2005, 14: 2187-2196. 10.1007/s11136-005-8028-5.
Wolinsky FD, Miller TR, Malmstrom TK, Miller JP, Schootman M, Andresen EM, et al: Self-rated health: changes, trajectories, and their antecedents among African Americans. J Aging Health. 2008, 20: 143-158.
Bäckmand H, Kujala U, Sarna S, Kaprio J: Former athletes’ health-related lifestyle behaviours and self-rated health in late adulthood. Int J Sports Med. 2010, 31: 751-758. 10.1055/s-0030-1255109.
Conry M, Morgan K, Curry P, McGee H, Harrington J, Ward M, et al: The clustering of health behaviours in Ireland and their relationship with mental health, self-rated health and quality of life. BMC Public Health. 2011, 11: 692-701. 10.1186/1471-2458-11-692.
Jia H, Lubetkin EI: The impact of obesity on health-related quality-of-life in the general adult US population. J Public Health (Oxf). 2005, 27: 156-164. 10.1093/pubmed/fdi025.
Motl RW, McAuley E: Symptom cluster and quality of life: preliminary evidence in multiple sclerosis. J Neurosci Nurs. 2010, 42: 212-216. 10.1097/JNN.0b013e3181e26c5f.
Rosso AL, Gallagher RM, Luborsky M, Mossey JM: Depression and self-rated health are proximal predictors of episodes of sustained change in pain in independently living, community dwelling elders. Pain Med. 2008, 9: 1035-1049. 10.1111/j.1526-4637.2008.00533.x.
Molarius A, Janson S: Self-rated health, chronic diseases, and symptoms among middle-aged and elderly men and women. J Clin Epidemiol. 2002, 55: 364-370. 10.1016/S0895-4356(01)00491-7.
Perruccio AV, Power JD, Badley EM: Arthritis onset and worsening self-rated health: a longitudinal evaluation of the role of pain and activity limitations. Arthritis Rheum. 2005, 53: 571-577. 10.1002/art.21317.
Schäfer I, Hansen H, Schön G, Maier W, Höfels S, Altiner A, et al: The German MultiCare-study: patterns of multimorbidity in primary health care - protocol of a prospective cohort study. BMC Health Serv Res. 2009, 9: 145-10.1186/1472-6963-9-145.
The EuroQol Group: EuroQol--a new facility for the measurement of health-related quality of life. Health Policy. 1990, 16: 199-208.
Brauns H, Steinmann S: Educational reform in France, West-Germany and the United Kingdom: Updating the CASMIN educational classification. ZUMA-Nachrichten. 1999, 44: 7-44.
Burniaux J-M: Income distribution and poverty in selected OECD countries. OECD Econ Dep Working Papers. 1998, 6: 1-21.
Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, et al: International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003, 35: 1381-1395. 10.1249/01.MSS.0000078924.61453.FB.
Bush K, Kivlahan DR, McDonell MB, Fihn SD, Bradley KA: The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Ambulatory care quality improvement project (ACQUIP). Alcohol use disorders identification test. Arch Intern Med. 1998, 158: 1789-1795. 10.1001/archinte.158.16.1789.
Fydrich T, Sommer G, Brähler E, F-Soz U: Fragebogen zur Sozialen Unterstützung. 2007, Göttingen: Hogrefe
Hinz A, Schumacher J, Albani C, Schmid G, Brähler E: Bevölkerungsrepräsentative Normierung der Skala zur allgemeinen Selbstwirksamkeitserwartung. Diagnostica. 2006, 52: 26-32. 10.1026/0012-1918.104.22.168.
Sheikh J, Yesavage J: Geriatric Depression Scale (GDS): recent evidence and development of a shorter version. Clin Gerontol. 1986, 5: 165-173. 10.1300/J018v05n01_09.
Terluin B, van Marwijk HW, Ader HJ, de Vet HC, Penninx BW, Hermens ML, et al: The Four-Dimensional Symptom Questionnaire (4DSQ): a validation study of a multidimensional self-report questionnaire to assess distress, depression, anxiety and somatization. BMC Psychiatry. 2006, 6: 34-10.1186/1471-244X-6-34.
Klasen BW, Hallner D, Schaub C, Willburger R, Hasenbring M: Validation and reliability of the German version of the Chronic Pain Grade questionnaire in primary care back pain patients. Psychosoc Med. 2004, 1: Doc07-
Collin C, Wade DT, Davies S, Horne V: The Barthel ADL Index: a reliability study. Int Disabil Stud. 1988, 10: 61-63. 10.3109/09638288809164103.
Lawton MP, Brody EM: Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist. 1969, 9: 179-186. 10.1093/geront/9.3_Part_1.179.
Gower JC: A general coefficient of similarity and some of its properties. Biometrics. 1971, 27: 857-871. 10.2307/2528823.
D’Orazio M: StatMatch: Statistical Matching. 2009, Ref Type: Computer Program
Schäfer I, Hansen H, Schön G, Höfels S, Altiner A, Dahlhaus A, et al: The influence of age, gender and socio-economic status on multimorbidity patterns in primary care. first results from the multicare cohort study. BMC Health Serv Res. 2012, 12: 89-10.1186/1472-6963-12-89.
König HH, Bernert S, Angermeyer MC: Health Status of the German population: results of a representative survey using the EuroQol questionnaire. Gesundheitswesen. 2005, 67: 173-182. 10.1055/s-2005-857991.
König HH, Bernert S, Angermeyer MC, Matschinger H, Martinez M, Vilagut G, et al: Comparison of population health status in six european countries: results of a representative survey using the EQ-5D questionnaire. Med Care. 2009, 47: 255-261. 10.1097/MLR.0b013e318184759e.
König HH, Heider D, Lehnert T, Riedel-Heller SG, Angermeyer MC, Matschinger H, et al: Health status of the advanced elderly in six European countries: results from a representative survey using EQ-5D and SF-12. Health Qual Life Outcomes. 2010, 8: 143-
Szende A, Williams A: Measuring self-reported population health: an international perspective based on EQ-5D. 2004, Budapest: SpringMed Publishing
Wang HM, Beyer M, Gensichen J, Gerlach FM: Health-related quality of life among general practice patients with differing chronic diseases in Germany: cross sectional survey. BMC Public Health. 2008, 8: 246-10.1186/1471-2458-8-246.
Darviri C, Artemiadis AK, Tigani X, Alexopoulos EC: Lifestyle and self-rated health: a cross-sectional study of 3,601 citizens of Athens, Greece. BMC Public Health. 2011, 11: 619-10.1186/1471-2458-11-619.
Haseli-Mashhadi N, Pan A, Ye X, Wang J, Qi Q, Liu Y, et al: Self-rated health in middle-aged and elderly Chinese: distribution, determinants and associations with cardio-metabolic risk factors. BMC Public Health. 2009, 9: 368-10.1186/1471-2458-9-368.
Grov EK, Fossa SD, Dahl AA: Short-term and long-term elderly cancer survivors: a population-based comparative and controlled study of morbidity, psychosocial situation, and lifestyle. Eur J Oncol Nurs. 2011, 15: 213-220. 10.1016/j.ejon.2010.06.011.
Kind P, Dolan P, Gudex C, Williams A: Variations in population health status: results from a United Kingdom national questionnaire survey. BMJ. 1998, 316: 736-741. 10.1136/bmj.316.7133.736.
Sach TH, Barton GR, Doherty M, Muir KR, Jenkinson C, Avery AJ: The relationship between body mass index and health-related quality of life: comparing the EQ-5D, EuroQol VAS and SF-6D. Int J Obes (Lond). 2007, 31: 189-196. 10.1038/sj.ijo.0803365.
Buman MP, Hekler EB, Haskell WL, Pruitt L, Conway TL, Cain KL, et al: Objective light-intensity physical activity associations with rated health in older adults. Am J Epidemiol. 2010, 172: 1155-1165. 10.1093/aje/kwq249.
Fujikawa A, Suzue T, Jitsunari F, Hirao T: Evaluation of health-related quality of life using EQ-5D in Takamatsu, Japan. Environ Health Prev Med. 2011, 16: 25-35. 10.1007/s12199-010-0162-1.
Schweikert B, Hunger M, Meisinger C, König HH, Gapp O, Holle R: Quality of life several years after myocardial infarction: comparing the MONICA/KORA registry to the general population. Eur Heart J. 2009, 30: 436-443.
Arne M, Lundin F, Boman G, Janson C, Janson S, Emtner M: Factors associated with good self-rated health and quality of life in subjects with self-reported COPD. Int J Chron Obstruct Pulmon Dis. 2011, 6: 511-519.
Burström K, Johannesson M, Diderichsen F: Swedish population health-related quality of life results using the EQ-5D. Qual Life Res. 2001, 10: 621-635. 10.1023/A:1013171831202.
Herman KM, Hopman WM, Vandenkerkhof EG, Rosenberg MW: Physical activity, body mass index, and health-related quality of life in Canadian adults. Med Sci Sports Exerc. 2012, 44: 625-636. 10.1249/MSS.0b013e31823a90ae.
Cleland JA, Lee AJ, Hall S: Associations of depression and anxiety with gender, age, health-related quality of life and symptoms in primary care COPD patients. Fam Pract. 2007, 24: 217-223. 10.1093/fampra/cmm009.
Haacke C, Althaus A, Spottke A, Siebert U, Back T, Dodel R: Long-term outcome after stroke: evaluating health-related quality of life using utility measurements. Stroke. 2006, 37: 193-198. 10.1161/01.STR.0000196990.69412.fb.
Kerse N, Elley CR, Robinson E, Arroll B: Is physical activity counseling effective for older people? A cluster randomized, controlled trial in primary care. J Am Geriatr Soc. 2005, 53: 1951-1956. 10.1111/j.1532-5415.2005.00466.x.
Unden AL, Elofsson S: Do different factors explain self-rated health in men and women?. Gend Med. 2006, 3: 295-308. 10.1016/S1550-8579(06)80218-4.
Imai K, Gregg EW, Chen YJ, Zhang P, de Rekeneire N, Williamson DF: The association of BMI with functional status and self-rated health in US adults. Obesity (Silver Spring). 2008, 16: 402-408. 10.1038/oby.2007.70.
Erler A, Beyer M, Muth C, Gerlach FM, Brennecke R: Garbage in – Garbage out? Validität von Abrechnungsdiagnosen in hausärztlichen Praxen. Gesundheitswesen. 2009, 71: 823-831. 10.1055/s-0029-1214399.
Violán C, Fouguet-Boreu Q, Hermosilla-Pérez E, Valderas JM, Bolíbar B, Fábregas-Escurriola M, Brugulat-Guiteras P, Muñoz-Pérez MÁ: Comparison of the information provided by electronic health records data and a population health survey to estimate prevalence of selected health conditions and multimorbidity. BMC Public Health. 2013, 21: 251-10.1007/s10389-012-0536-5.
The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2296/15/1/prepub
The study is funded by the German Federal Ministry of Education and Research (grant numbers 01ET0725-31 and 01ET1006A-K).
This article is on behalf of the MultiCare Cohort Study Group, which consists of Attila Altiner, Horst Bickel, Wolfgang Blank, Monika Bullinger, Hendrik van den Bussche, Anne Dahlhaus, Lena Ehreke, Michael Freitag, Angela Fuchs, Jochen Gensichen, Ferdinand Gerlach, Heike Hansen, Sven Heinrich, Susanne Höfels, Olaf von dem Knesebeck, Hans-Helmut König, Norbert Krause, Hanna Leicht, Melanie Luppa, Wolfgang Maier, Manfred Mayer, Christine Mellert, Anna Nützel, Thomas Paschke, Juliana Petersen, Jana Prokein, Steffi Riedel-Heller, Heinz-Peter Romberg, Ingmar Schäfer, Martin Scherer, Gerhard Schön, Susanne Steinmann, Sven Schulz, Karl Wegscheider, Klaus Weckbecker, Jochen Werle, Siegfried Weyerer, Birgitt Wiese, and Margrit Zieger.
We are grateful to the general practitioners in Bonn, Dusseldorf, Frankfurt/Main, Hamburg, Jena, Leipzig, Mannheim and Munich who supplied the clinical information on their patients, namely Theodor Alfen, Martina Amm, Katrin Ascher, Philipp Ascher, Heinz-Michael Assmann, Hubertus Axthelm, Leonhard Badmann, Horst Bauer, Veit-Harold Bauer, Sylvia Baumbach, Brigitte Behrend-Berdin, Rainer Bents, Werner Besier, Liv Betge, Arno Bewig, Hannes Blankenfeld, Harald Bohnau, Claudia Böhnke, Ulrike Börgerding, Gundula Bormann, Martin Braun, Inge Bürfent, Klaus Busch, Jürgen Claus, Peter Dick, Heide Dickenbrok, Wolfgang Dörr, Nadejda Dörrler-Naidenoff, Ralf Dumjahn, Norbert Eckhardt, Richard Ellersdorfer, Doris Fischer-Radizi, Martin Fleckenstein, Anna Frangoulis, Daniela Freise, Denise Fricke, Nicola Fritz, Sabine Füllgraf-Horst, Angelika Gabriel-Müller, Rainer Gareis, Benno Gelshorn, Maria Göbel-Schlatholt, Manuela Godorr, Jutta Goertz, Cornelia Gold, Stefanie Grabs, Hartmut Grella, Peter Gülle, Elisabeth Gummersbach, Heinz Gürster, Eva Hager, Wolfgang-Christoph Hager, Henning Harder, Matthias Harms, Dagmar Harnisch, Marie-Luise von der Heide, Katharina Hein, Ludger Helm, Silvia Helm, Udo Hilsmann, Claus W. Hinrichs, Bernhard Hoff, Karl-Friedrich Holtz, Wolf-Dietrich Honig, Christian Hottas, Helmut Ilstadt, Detmar Jobst, Gunter Kässner, Volker Kielstein, Gabriele Kirsch, Thomas Kochems, Martina Koch-Preißer, Andreas Koeppel, Almut Körner, Gabriele Krause, Jens Krautheim, Nicolas Kreff, Daniela Kreuzer, Franz Kreuzer, Judith Künstler, Christiane Kunz, Doris Kurzeja-Hüsch, Felizitas Leitner, Holger Liebermann, Ina Lipp, Thomas Lipp, Bernd Löbbert, Guido Marx, Stefan Maydl, Manfred Mayer, Stefan-Wolfgang Meier, Jürgen Meissner, Anne Meister, Ruth Möhrke, Christian Mörchen, Andrea Moritz, Ute Mühlmann, Gabi Müller, Sabine Müller, Karl-Christian Münter, Helga Nowak, Erwin Ottahal, Christina Panzer, Thomas Paschke, Helmut Perleberg, Eberhard Prechtel, Hubertus Protz, Sandra Quantz, Eva-Maria Rappen-Cremer, Thomas Reckers, Elke Reichert, Birgitt Richter-Polynice, Franz Roegele, Heinz-Peter Romberg, Anette Rommel, Michael Rothe, Uwe Rumbach, Michael Schilp, Franz Schlensog, Ina Schmalbruch, Angela Schmid, Holger Schmidt, Lothar Schmittdiel, Matthias Schneider, Ulrich Schott, Gerhard Schulze, Heribert Schützendorf, Harald Siegmund, Gerd Specht, Karsten Sperling, Meingard Staude, Hans-Günter Stieglitz, Martin Strickfaden, Hans-Christian Taut, Johann Thaller, Uwe Thürmer, Ljudmila Titova, Michael Traub, Martin Tschoke, Maya Tügel, Christian Uhle, Kristina Vogel, Florian Vorderwülbecke, Hella Voß, Christoph Weber, Klaus Weckbecker, Sebastian Weichert, Sabine Weidnitzer, Brigitte Weingärtner, Karl-Michael Werner, Hartmut Wetzel, Edgar Widmann, Alexander Winkler, Otto-Peter Witt, Martin Wolfrum, Rudolf Wolter, Armin Wunder, and Steffi Wünsch.
We also thank Corinna Contenius, Cornelia Eichhorn, Sarah Floehr, Vera Kleppel, Heidi Kubieziel, Rebekka Maier, Natascha Malukow, Karola Mergenthal, Christine Müller, Sandra Müller, Michaela Schwarzbach, Wibke Selbig, Astrid Steen, Miriam Steigerwald, and Meike Thiele for data collection as well as Ulrike Barth, Elena Hoffmann, Friederike Isensee, Leyla Kalaz, Heidi Kubieziel, Helga Mayer, Karine Mnatsakanyan, Michael Paulitsch, Merima Ramic, Sandra Rauck, Nico Schneider, Jakob Schroeber, Susann Schumann, and Daniel Steigerwald for data entry.
The authors declare that they have no competing interests.
AN and HB performed the statistical analyses and interpretation of the data, and drafted the manuscript. IS, BW, MS and HvB conceived and designed the study. GS and BW prepared the data for analysis. AD, AF, JG, HHK, SRH, WM and SW participated in study design and implementation. All authors read and approved the final manuscript.
About this article
Cite this article
Nützel, A., Dahlhaus, A., Fuchs, A. et al. Self-rated health in multimorbid older general practice patients: a cross-sectional study in Germany. BMC Fam Pract 15, 1 (2014). https://doi.org/10.1186/1471-2296-15-1
- Quality of life
- Chronic disease
- Functionally- impaired elderly
- General practice