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Trends in Hospitalization and Sociodemographic Factors in Diabetic and Nondiabetic Populations in Germany: National Health Survey, 1990–1992 and 1998 | Andrea Icks, MD, DrPH, Burkhard Haastert, PhD, Wolfgang Rathmann, MD, MSPH, Joachim Rosenbauer, MD, and Guido Giani, PhD
Reduction of hospitalization in chronically ill people is a main goal in health care, since hospitalization is associated with a high individual burden and social costs. Interventions to avoid hospital admissions in chronic disease patients include structured treatment, education programs, and specialized ambulatory care offers.1–5 Diabetes mellitus is the prototype of such chronic diseases, and several disease management approaches have been developed. Inpatient as well as outpatient structured education programs may improve disease outcomes and reduce hospitalization.4–8 In studies in Germany, metabolic control improved and hospitalization decreased from 7–11 to 4–5 days per personyear as a result of structured education programs conducted during these studies.4,5 Structured education programs are now routine care in Germany. In addition to the ambition to improve health care for chronically ill people, there was a general effort to reduce hospitalization in several countries during the 1990s, mainly because of rising health care costs.1,2,9 Between 1980 and 1992, health care costs in the hospital sector in western Germany increased by more than 150%, to about 90 million deutsche marks, in 1992 (this amount is equal to US $48 million in 2006 dollars). This sum accounted for 45% of total health care costs. Several political interventions have been introduced, including outpatient surgery, predischarge assessment and domiciliary aftercare, and specialized outpatient services. Between 1991 and 1998, the mean length of hospital stay declined from 14 to 10 days.10–12 Social inequalities in health have been described often13–17 and are likely to widen.18,19 In the diabetic population, metabolic control and the occurrence of late complications as well as health care seeking have been shown to be associated with socioeconomic status.3,20–27
Objectives. We examined time trends of hospitalization, a main outcome measure in health care, in the diabetic and nondiabetic populations in Germany and their associations with sociodemographic variables. Methods. Using data from 2 national health surveys, we estimated hospital days per person-year in the diabetic and nondiabetic populations in 1998 (n=5422) and 1990–1992 (n = 7363) in Germany. We used Poisson regression to estimate relative risks and interaction of secular time with age, gender, and educational level, considering the cluster sample design of the study. Results. Hospital days per person-year decreased between 1990–1992 and 1998—from 3.59 (95% confidence interval [CI] = 2.59, 4.97) to 3.14 (95% CI = 2.16, 4.56) for the diabetic population and from 1.38 (95% CI = 1.23, 1.55) to 1.33 (95% CI = 1.17, 1.51) for the nondiabetic population—but the decrease was not statistically significant. In the diabetic population, the decrease tended to be more pronounced (interaction year × time not significant; P = .756). Also, there was a notable decrease in men and in the group aged 25 to 39 years, and a decrease in both high- and low-educational-level subjects. Conclusions. There seems to have been a larger decrease in hospitalization in the diabetic population than in the nondiabetic population in Germany. An increase in social disparity in this health outcome measure in the diabetic population could not be confirmed. (Am J Public Health. 2006;96:1656–1661. doi:10. 2105/AJPH.2005.063339) To the best of our knowledge, no studies on hospitalization trends in the diabetic versus the nondiabetic population have been published. Furthermore, associations between hospitalization trends and sociodemographic variables such as age, gender, and socioeconomic status have not been systematically analyzed at the population level. Thus, our aims were to evaluate trends in hospitalization in the diabetic and nondiabetic populations between 1990–1992 and 1998 in Germany and to evaluate associations of hospitalization trends with age, gender, and educational level (as an indicator of social status). We used data from the 1990–1992 and 1998 National Health Survey.28,29
METHODS Study Design and Population In Germany, national health surveys were conducted in 1990–1992 and 1998 on the
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population aged 25 to 69 years (1990–1992) and 18 to 79 years (1998). Sampling, survey design, and data assessment have been described in detail elsewhere.28–32 Briefly, both surveys used 2-stage cluster sampling. Participation levels were 69.0% (n = 7466) and 61.4% (n = 7124) in 1990– 1992 and 1998, respectively. Trained staff interviewed subjects and administered a standardized questionnaire, which included questions about socioeconomic status, former and current illness, and health care seeking in the past 12 months. Furthermore, a standardized clinical investigation was performed, including assessment of anthropometric data and taking of blood samples. We analyzed data for subjects aged 25 to 69 years because both surveys included this age group. Only participants of German nationality were selected because no nonGermans were included in the 1990–1992 survey. Missing values for diabetics and
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hospitalization (103 in 1990–1992, 161 in 1998) excluded 264 subjects. Thus, the present analysis included 7363 subjects from the 1990–1992 survey and 5422 subjects from the 1998 survey.
TABLE 1—Characteristics of the Study Population: National Health Survey, Germany, 1990–1992 and 1998
Data Assessment
N Men, % Age, y, mean (SD) Age, y, % 25–39 40–60 61–69 Low educational level, %a
Study subjects were asked if they had ever been told by a doctor that they had diabetes. Diabetes self-reports have been shown to have reasonable validity compared with statements of primary care physicians.33,34 Subjects were asked if they had been hospitalized during the past 12 months and, if so, how many days they were hospitalized. As an indicator of social status, educational level was assessed in the National Health Survey by means of a standardized index that is well established in Germany and has been used in international comparisons of social inequalities in health.17,35,36 The index classifies educational level into categories on the basis of type and duration of school and vocational education, ranging from low (no or primary school qualification without vocational education) to high (university degree) educational level.
Analysis Descriptive statistics were performed for all continuous and categorical variables of the study participants. Differences between 1990–1992 and 1998 were analyzed by t test, Wilcoxon test, or Fisher exact test. Subjects with more than 100 hospital days per year were excluded (n = 8 in 1990–1992, n = 7 in 1998) to avoid outlier bias. Age was classified into 3 categories: 25 to 39, 40 to 60, and 61 to 69 years. Following the convention used in several studies,14,36,37 the educational level categories of the index were dichotomized into 2 classes (low and lower middle vs higher middle and high). The 2-stage cluster sampling of the survey requires specific analyses, considering the sample design.38 All following analyses were performed with sample weights for each proband according to the strata weights of the study design28,29 and with Huber–White standard errors, as suggested by the Stata user manual.39 Numbers of hospital days per person-year were estimated in the different strata, along with 95% confidence intervals, assuming Poisson distribution. Differences between 1990–1992 and 1998 were estimated
Diabetic Population
Nondiabetic Population
1990–1992
1998
1990–1992
1998
337 51.9 56.6 (9.3)
252 55.2 57.0 (10.1)
7018 48.9 44.5 (12.4)*
5163 48.0 45.7 (12.2)*
5.9 53.7 40.4 62.9
8.3 45.6 46.0 58.5
40.0 46.9 13.1 47.5*
37.4 48.5 14.1 36.3*
Note. Survey respondents with missing values (n = 264) and those with more than 100 hospital days during the past 12 months (n = 15) were excluded from our study. Also excluded were 5411 respondents to the 1998 survey who were 18 to 24 years of age, 70 to 79 years of age, or not German. a Low educational level was defined as no or primary school qualification without vocational education. *P < .05.
as relative hospital days per person-year with their 95% confidence intervals. A multivariate Poisson regression model was fitted to evaluate the association between hospital days and calendar year, diabetes, and an interaction term (year × diabetes), adjusted for age, gender, and educational level, to evaluate possible interaction between diabetes and the trend in hospitalization between 1990–1992 and 1998. Further Poisson regression models were fitted to evaluate associations between hospital days, calendar year, age, gender, and educational level as well as interaction between the time trend and these sociodemographic variables (year × gender, year × age, year × educational level). We did these analyses separately for the diabetic and the nondiabetic population to avoid 3-way interaction terms. Relative risks (relative hospital days per personyears) were estimated with their 95% confidence intervals. All analyses were performed with SAS 8.2 (SAS Institute Inc, Cary, NC) and Stata 7.0 (StataCorp LP, College Station, Tex).
RESULTS Study Participants The characteristics of the diabetic and nondiabetic survey participants are described in Table 1. In the large nondiabetic sample, age and educational level differed statistically
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between 1990–1992 and 1998. However, age, gender, and the level of education among diabetic and nondiabetic subjects were rather similar in both surveys, as was diabetes prevalence (4.58% and 4.65% in 1990–1992 and 1998, respectively; data not shown). The general characteristics of the diabetic compared with the nondiabetic study populations remained the same between 1990–1992 and 1998. In both surveys, diabetic subjects were older and less educated than nondiabetic subjects.
Trends in Hospital Days per Person-Year Table 2 presents sample design–based hospital days per person-year in the diabetic and nondiabetic populations in 1990–1992 and 1998. In both the diabetic and nondiabetic populations, there was a decrease in hospitalization, but it was not statistically significant. The decrease tended to be larger in the diabetic than in the nondiabetic population. However, an interaction between year and diabetes was not significant (Table 3). Table 2 also presents hospital days per person-year for 1990–1992 and 1998 in the different age, gender, and education-level strata. In the nondiabetic population, the differences between the 2 surveys were moderate. Hospital days per person-year decreased among men, whereas there was a slight increase for women. In contrast to the age groups 25 to 39 and 61 to 69 years, hospital
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TABLE 2—Mean Hospital Days and 95% Confidence Intervals per Person-Year: National Health Survey, Germany, 1990–1992 and 1998 Diabetic Population
All Gender Male Female Age group, y 25–39 40–60 61–69 Educational levela Low High
Nondiabetic Population
1990–1992
1998
Relative Hospital Days
1990–1992
1998
Relative Hospital Days
3.59 (2.59, 4.97)
3.14 (2.16, 4.56)
0.88 (0.53, 1.44)
1.38 (1.23, 1.55)
1.33 (1.17, 1.51)
0.96 (0.81, 1.14)
3.83 (2.52, 5.83) 3.33 (2.00, 5.54)
2.02 (1.22, 3.35) 4.36 (2.66, 7.15)
0.53 (0.27, 1.02) 1.31 (0.64, 2.66)
1.25 (1.05, 1.49) 1.51 (1.29, 1.76)
1.06 (0.55, 1.31) 1.59 (1.37, 1.86)
0.84 (0.64, 1.11) 1.06 (0.85, 1.32)
5.28 (1.60, 17.47) 3.34 (2.17, 5.15) 3.64 (2.15, 6.17)
1.68 (0.58, 4.88) 2.02 (1.20, 3.40) 4.63 (2.79, 7.67)
0.32 (0.06, 1.58) 0.61 (0.31, 1.19) 1.27 (0.61, 2.64)
0.98 (0.83, 1.17) 1.53 (1.29, 1.82) 2.02 (1.55, 2.65)
1.04 (0.83, 1.31) 1.34 (1.12, 1.61) 2.10 (1.60, 2.75)
1.06 (0.80, 1.40) 0.88 (0.68, 1.13) 1.04 (0.71, 1.52)
3.79 (2.49, 5.76) 3.24 (1.96, 5.36)
3.40 (2.04, 5.67) 2.55 (1.53, 4.24)
0.90 (0.46, 1.74) 0.79 (0.38, 1.61)
1.47 (1.26, 1.73) 1.30 (1.10, 1.54)
1.58 (1.30, 1.91) 1.17 (0.99, 1.39)
1.07 (0.83, 1.38) 0.90 (0.71, 1.14)
Note. Survey respondents with missing values (n = 264) and with more than 100 hospital days during the past 12 months (n = 15) were excluded from our study. Also excluded were 5411 respondents to the 1998 survey who were 18 to 24 years of age, 70 to 79 years of age, or not German. Estimates took into account the 2-stage cluster sampling design of the study (estimators and 95% confidence intervals adjusted for the sample design). Relative hospital days are the ratio of 1998 to 1990–1992 hospital days. a Low educational level was defined as no or primary school qualification without vocational education. High educational level is defined as having a university degree.
TABLE 3—Hospitalization by Diabetes Status and Calendar Year, Including Interaction: National Health Survey, Germany, 1990–1992 and 1998 Relative Hospital Days per Person-Year (95% CI)
Model Without further adjustment Year 1998 (1990–1992 = baseline) Diabetes (nondiabetes = baseline) Interaction term: Year 1998 × Diabetes Adjusted for age and gender Year 1998 (1990–1992 = baseline) Diabetes (nondiabetes = baseline) Interaction term: Year 1998 × Diabetes Adjusted for age, gender, and educational level Year 1998 (1990–1992 = baseline) Diabetes (nondiabetes = baseline) Interaction term: Year 1998 × Diabetes
0.96 (0.81, 1.14) 2.60 (1.84, 3.67) 0.91 (0.54, 1.53) 0.96 (0.81, 1.14) 2.13 (1.49, 3.05) 0.92 (0.55, 1.55) 0.96 (0.81, 1.15) 2.13 (1.49, 3.05) 0.90 (0.53, 1.52)
Note. CI = confidence interval. Estimates took into account the 2-stage cluster sampling design of the study (estimators and 95% confidence intervals adjusted for the sample design). Relative hospital days are the ratio of 1998 to 1990–1992 hospital days.
days per person-year tended to decrease in the middle-aged. In subjects with high educational level, hospital days per person-year decreased between 1990–1992 and 1998, whereas there was a slight increase in hospital days for subjects with low education. Differences between the 2 surveys were not significant in any stratum (all Ps > .05). In the diabetic population, differences in hospital days per person-year between 1990
and 1998 appeared larger and showed a different pattern than in the nondiabetic population. Among men, the number of hospital days per person-year was high in 1990– 1992 but was considerably lower in 1998. The same pattern was observed in the age group 25 to 39 years and, though less pronounced, in the age group 40 to 60 years. Among women and among all subjects aged 61 to 69 years, hospital days per person-year
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increased between the 2 surveys. In diabetic subjects of both educational levels, hospital days per person-year were lower in 1998 than in 1990–1992. The decrease tended to be more prominent in high-educational-level subjects (Table 2). However, the differences between the 2 surveys again failed to reach statistical significance (all Ps > .05). In both diabetic and nondiabetic populations, there were no significant interactions between the trend in hospital days between 1990–1992 and 1998 and the sociodemographic variables (regression models including interaction terms, all Ps > .05; data not shown). The non–sample-design-based analyses yielded comparable point estimates (data not shown) but some significant differences. The decrease in hospital days per person-year between the 2 surveys was significant, and it was significantly higher in the diabetic than in the nondiabetic population (both Ps < .001). Interaction between calendar year and age, gender, and educational level were all significant in the nondiabetic population (P < .001 and P = .03, P < .001, and P < .001, respectively), as was interaction between calendar year and age and gender (all Ps < .001), but the interaction between calendar year and education (P = .04) in the diabetic population was not significant. When subjects with more than 100 hospital days per person-year were included
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in the analyses, the main results remained unchanged.
DISCUSSION Principal Findings To the best of our knowledge, this is the first report comparing trends in hospitalization between diabetic and nondiabetic populations and examining the association between these trends and age, gender, and educational level (as an indicator of social status). As expected, hospitalization was significantly higher in the diabetic compared with the nondiabetic population in both 1990–1992 and 1998. We found an overall but not significant reduction in hospital days from 1990–1992 to 1998, and, unexpectedly, the reduction appeared to be more pronounced in the diabetic population. In the diabetic population in 1990–1992, hospitalization seemed to be especially high in younger and middle-aged subjects and in men, and the reduction in hospital days appeared considerable in these groups. In the nondiabetic population, there seemed to be a reduction in hospitalization among subjects with high educational levels but a trend toward an increase among subjects with low educational levels. In the diabetic population, a reduction in hospitalization was present at both educational levels. The estimates that considered the sample design failed to reach statistical significance. This may be in part because of low statistical power. The sample design–based analyses, which use robust estimators, may overestimate dispersion and thus, be too conservative. The non–sample-design-based analyses yielded point estimates comparable to those of the sample design–based analyses with some significant results. In particular, the interaction between year and diabetes was significant, which means that the reduction in hospitalization was greater in the diabetic than in the nondiabetic population. However, in light of the complex sample design of the study, the results of the sample design–based analyses have to be considered in the interpretation of the data.
Study Limitations Several limitations of the present study must be considered. Because of low statistical
power, we were unable to conduct a more detailed analysis of differences between the diabetic and nondiabetic populations. The number of variables available for analysis was limited by the questions asked in the survey from which we drew our data. Thus, potentially explaining factors (e.g., reasons for hospitalization) that were not assessed by survey questions could not be evaluated. In addition, because the 1990–1992 survey was limited to German citizens aged 25 to 69 years, no non-German subjects or adults older than 69 years could be included in our study. Hospital days were self-reported and may be underestimated. Only hospitalizations during the 12 months before the survey were assessed, and hospital stays are profound events that should be easily recalled; however, a recall bias cannot be excluded. Furthermore, recall may be associated with educational level. We expect that less educated subjects are more likely to underreport hospitalization. Thus, our estimate is conservative, since differences in hospitalization would tend toward the null. Rathmann et al.40 have shown that undiagnosed diabetes is common in Germany, as it is in many other countries. Subjects classified as nondiabetic might actually have had diabetes, so differences might be underestimated. There is no evidence that the prevalence of unknown diabetes changed between 1990–1992 and 1998, so the hospitalization trend should not be influenced by undiagnosed diabetic subjects. However, a bias cannot be excluded. The strength of the present study is that it is based on 2 comparable, carefully designed nationwide population-based surveys using standardized questionnaires. The validity of self-reported presence of diabetes has been shown to be high.33,34 Thus, misclassification of known diabetes should be low. Though the questionnaires of the 2 surveys differed slightly, the predictor and outcome variables used in the present study were assessed in both surveys in a comparable manner.
Comparison With Other Studies We found only 1 similar study (in the United States) in which trends in hospitalization because of chronic diseases including diabetes were compared between African
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Americans and other ethnic groups.41 Davis et al. found that African Americans experienced 10 times as many hospital days per person-year because of diabetes as members of other ethnic groups. They observed a significant widening in the social gradient, as the ratio between African Americans’ hospitalizations and those of other ethnic groups became larger. They found no reduction in diabetes-related hospitalization over time. However, their results are difficult to compare with ours because of the different study design. Our use of educational level as an indicator of socioeconomic status may be criticized.14–16 In contrast to other common indicators, such as occupational class or household income, educational level has the disadvantage that individuals usually achieve their final level of education early in life. Thus, educational level may not accurately indicate a person’s current socioeconomic status. But there are several advantages to the use of educational level. Unlike occupational class, it allows classification of individuals who do not work. The fact that educational level is attained early in life makes it a more accurate indicator of socioeconomic position than occupation or income, which may be adversely affected by illness in later life. A further advantage is that educational level categories do not change over time as income level categories do (because of inflation). In several studies, educational level has been used as an indicator of socioeconomic status and has been shown to fit well with health behavior and to be strongly associated with the occurrence of chronic diseases and health outcomes.14–16,36,37
Implications An overall reduction in hospital days between 1990–1992 and 1998 in Germany might be explained in part by the health care policies of the past decade. During the 1990s, outpatient care (e.g., ambulant surgery, predischarge assessment, and domiciliary aftercare) became more prevalent in Germany.10–12 In the nondiabetic population, the decrease in hospital days per personyear between 1990–1992 and 1998 appears to be present in high-educational-level but not in low-educational-level subjects.
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Subjects with a high educational level are more likely to participate in preventive services42 and may have used outpatient care more extensively. A greater decrease in hospitalization in the diabetic population could be explained by structured diabetes education programs, which have been shown to reduce hospitalization,4,5 and successful implementation of outpatient specialized diabetes care. During the 1990s, inpatient and outpatient education programs were implemented in routine health care in Germany. At the end of the 1990s, more than 300 hospitals and an even higher number of practices offered specialized diabetes care and education programs, and more than 3000 physicians were qualified as diabetologists.43 Younger subjects may have used diabetic outpatient care more than older subjects. However, the finding of high hospitalization in men and in younger diabetic subjects in 1990–1992 and the considerable decrease between 1990 and 1998 should be interpreted with caution, since estimates are uncertain because of low numbers of diabetic cases in the group aged 25 to 39 years. Although diabetic subjects of high social status have been found to be more likely to participate in structured education programs than subjects of low social status,26,27 widespread specialized diabetes treatment may have reached a large number of diabetic subjects at all social levels in Germany. This might explain a decrease in hospital days in both high- and low-educational-level diabetic subjects.
Conclusions We found a decrease in hospital days per person-year in both the nondiabetic and diabetic populations. No remarkable social gradient and no widening in social disparity could be confirmed in the diabetic population. Although this finding may have resulted in part from low statistical power and an overestimation of dispersion, the result is surprising, because a widening of social inequality in health is often observed. It would be a great success if improvement in diabetes care reached subjects regardless of their social status. Further studies are warranted to confirm our results and to identify possible explanations for our results.
About the Authors The authors are with the German Diabetes Research Center, Institute of Biometrics and Epidemiology, Düsseldorf, Germany. Request for reprints should be sent to Andrea Icks, MD, DrPH, German Diabetes Research Center, Institute of Biometrics and Epidemiology, Auf’m Hennekamp 65, 40225 Düsseldorf, Germany (e-mail:
[email protected]). This article was accepted November 14, 2005.
10. Federal Statistic Office. Health Report for Germany [in German]. Stuttgart, Germany: MetzlerPoeschel; 1998. 11. Klauber J, Robra B-P, Schellschmidt H. Hospital Report 2004 [in German]. Stuttgart, Germany: Schattauer; 2004.
Contributors A. Icks conceptualized the study and its design, interpreted the findings, and wrote the article. B. Haastert conducted the statistical analysis and provided assistance in the study design and interpretation. W. Rathmann assisted in the conceptualization of the study design, provided assistance in interpreting the clinical relevance of the research findings, and reviewed the article. J. Rosenbauer provided assistance in the conceptualization of the statistical analysis. G. Giani provided assistance in the conceptualization of the statistical analysis and interpretation of the findings and reviewed the article.
Acknowledgments This study was supported by institutional funding to the German Diabetes Research Institute from the German Ministry of Health and by the Ministry of Science of North-Rhine Westfalia. We would like to thank the Robert Koch Institute, Berlin, Germany, for providing the survey data, and in particular Elisabeth Gaber and Heribert Stolzenberg, Department of Epidemiology, for their support.
Human Participant Protection No protocol approval was needed for this analysis.
References 1. Bodenheimer T, Fernandez A. High and rising health care costs. Part 4: can costs be controlled while preserving quality? Arch Intern Med. 2005;143:26–31. 2. Benbassat J, Taragin M. Hospital readmissions as a measure of quality of health care: advantages and limitations. Arch Intern Med. 2000;160:1074–1081. 3. Booth GL, Hux JE. Relationship between avoidable hospitalizations for diabetes mellitus and income level. Arch Intern Med. 2003;163:101–106. 4. Jörgens V, Grüsser M, Bott U, Mühlhauser I, Berger M. Effective and safe translation of intensified insulin therapy to general internal medicine departments. Diabetologia. 1993;36:99–105. 5. Kronsbein P, Jörgens V, Mühlhauser I, Scholz V, Venhaus A, Berger M. Evaluation of a structured treatment and teaching programme on non-insulin-dependent diabetes. Lancet. 1988;2:1407–1411. 6. Delamater AM, Bubb J, Davis SG, et al. Randomized prospective study of self-management training with newly diagnosed diabetic children. Diabetes Care. 1990;13:492–498. 7. Deakin T, McShane CE, Cade JE, Williams RD. Group based training for self-management strategies in people with type 2 diabetes mellitus. Cochrane Database Syst Rev. 2005;Apr 18(2):CD003417. 8. Miller LV, Goldstein J. More efficient care of diabetic patients in a county-hospital setting. N Engl J Med. 1972;286:1388–1391.
1660 | Research and Practice | Peer Reviewed | Icks et al.
9. Organisation for Economic Co-operation and Development. OECD Health Data 2002: A Software for the Comparative Analysis of 29 Health Systems [CD-ROM]. OECD Electronic Editions catalogue. Munich, Germany: Digento; 2002.
12. Sachverständigenrat für die Konzertierte Aktion im Gesundheitswesen: Gutachten des Sachverständigenrates für die Konzertierte Aktion im Gesundheitswesen (SVR KAG) Bedarfsgerechtigkeit und Wirtschaftlichkeit Kurzfassung Band III. 2000–2001. Baden-Baden, Germany: Nomos; 2002. 13. Pappas G, Hadden WC, Kozak LJ, Fisher GF. Potentially avoidable hospitalizations: inequalities in rates between US socioeconomic groups. Am J Public Health. 1997;87:811–816. 14. Huisman M, Kunst AE, Bopp M, et al. Educational inequalities in cause-specific mortality in middle-aged and older men and women in eight western European populations. Lancet. 2005;365:493–500. 15. Mackenbach JP, Kunst AE, Cavelaars AE, Groenhof F, Geurts JJ. Socioeconomic inequalities in morbidity and mortality in western Europe. The EU Working Group on Socioeconomic Inequalities in Health. Lancet. 1997;349:1655–1659. 16. Kunst AE, Mackenbach JP. The size of mortality differences associated with educational level in nine industrialized countries. Am J Public Health. 1994; 84:932–937. 17. Mackenbach JP, Kunst AE. Measuring the magnitude of socio-economic inequalities in health: an overview of available measures illustrated with two examples in Europe. Soc Sci Med. 1997;44:757–771. 18. Marmot M, Bobak M. International comparators and poverty and health in Europe. BMJ. 2000; 321:1124–1128. 19. Mackenbach JP, Bakker MJ, for the European Network on Interventions and Policy to Reduce Inequalities in Health. Tackling socioeconomic inequalities in health: analysis of European experiences. Lancet. 2003;362:1409–1414. 20. Chaturvedi N, Jarrett J, Shipley MJ, Fuller J. Socioeconomic gradients in morbidity and mortality in people with diabetes: cohort study findings from the Whitehall study and the WHO multinational study of vascular disease in diabetes. BMJ. 1998;316:100–105. 21. Gulliford MC, Ariyanayagam-Baksh SM, Bickram L, Picou D, Mahabir D. Social environment, morbidity and use of health care among people with diabetes mellitus in Trinidad. Int J Epidemiol. 1997;26:620–627. 22. Bachmann MO, Eachus J, Hopper CD, et al. Socioeconomic inequalities in diabetes complications, control, attitudes and health service use: a cross-sectional study. Diabet Med. 2003;20:921–929. 23. Icks A, Rosenbauer J, Haastert B, Giani G. Social inequality in childhood diabetes. Pediatrics. 2003; 111:222–224. 24. Icks A, Rosenbauer J, Haastert B, Giani G. Hospitalization among diabetic children and adolescents and
American Journal of Public Health | September 2006, Vol 96, No. 9
RESEARCH AND PRACTICE
in nondiabetic control subjects: a prospective populationbased study. Diabetologia. 2001;44:B87–92.
the 1990s: implications and benchmarks. Am J Public Health. 2003;93:447–455.
25. Mühlhauser I, Overmann H, Bender R, Bott U, Berger M. Risk factors of severe hypoglycaemia in adult patients with type 1 diabetes—a prospective populationbased study. Diabetologia. 1998;41:1274–1282.
42. Kahl H, Hülling H, Kamtsiuris P. Adherence to screening programs and to interventions of health promotion [in German]. Gesundheitswesen. 1999;61: S163–S168.
26. Mühlhauser I, Overmann H, Bender R, et al. Social status and the quality of care for adult people with type 1 diabetes—a population-based study. Diabetologia. 1998;41:1139–1150.
43. Icks A, Rathmann W, Rosenbauer J, Giani G, et al. Diabetes mellitus [in German]. Berlin, Germany: Robert Koch Institute; 2005.
27. Mielck A, Reitmeir P, Rathmann W. Social inequalities in type 2 diabetes education. Results of the KORA A study [in German]. Diabetes und Stoffwechsel. 2002;10(suppl 1):107–108. 28. Stolzenberg H. National Health Survey 1998. Public Use File BGS98. Documentation of the data set [in German]. Berlin, Germany: Robert Koch Institute; 2000.
Communicating Public Health Information Effectively:
29. Stolzenberg H. Health Survey East-West 1990– 1992. Public Use File OW91. Documentation of the data set [in German]. Berlin, Germany: Robert Koch Institute; 1995.
A Guide for Practitioners
30. Thefeld W, Stolzenberg H, Bellach BM. National Health Survey. Response, participants and nonresponders [in German]. Gesundheitswesen. 1999;61(S2): S57–S61.
Edited by David E. Nelson, MD, MPH; Ross C. Brownson, PhD; Patrick L. Remington, MD, MPH; and Claudia Parvanta, PhD
31. Helmert U, Herman B, Shea S. Moderate and vigorous leisure-time physical activity and cardiovascular disease risk factors in West Germany, 1984–1991 [published correction appears in Int J Epidemiol. 1994; 23:1330]. Int J Epidemiol. 1994;23:285–292.
A
32. Cavelaars AEJM, Kunst AE, Geurts JJM, et al. Educational differences in smoking: an international comparison. BMJ. 2000;320:1102–1107. 33. Bormann C, Hoeltz J, Hoffmeister H, et al. Subjective Morbidity. Prevalence, Reliability, and Validity of Self Reported Heart Diseases, Diabetes, and Risk Factors in the National Health Service 1984–1986 [in German]. Berlin, Germany: Bundesgesundheitsblatt; 1990.
ISBN 0-87553-027-3 2002 ❚ 240 pages ❚ softcover $23.75 APHA Members $33.95 Non-members Plus shipping and handling
34. Thefeld W. Prevalence of diabetes mellitus in the adult German population [in German]. Gesundheitswesen. 1999;61:S85–S89. 35. Winkler J, Stolzenberg H. The social status index in the National Health Survey [in German]. Gesundheitswesen. 1999;61(S2):S178–S183. 36. Giskes K, Kunst AE, Benach J, et al. Trends in smoking behaviour between 1985 and 2000 in nine European countries by education. J Epidemiol Community Health. 2005;59:395–401.
s the first of its kind, this book provides a comprehensive approach to help public health practitioners in both the public and private sector to improve their ability to communicate with different audiences. Covering all the various modes of communication, each chapter provides practical, real-world recommendations and examples of how to communicate public health information to nonscientific audiences more effectively. The knowledge and skills gleaned from this book will assist with planning and executing simple and complex communication activities commonly done by public health practitioners.
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37. Mackenbach JP, Kunst AE, Groenhof F, et al. Socioeconomic inequalities in mortality among women and among men: an international study. Am J Public Health. 1999;89:1800–1806. 38. Särndal CE, Swenson B, Wretman J. Model Assisted Survey Sampling. New York: Springer; 1992. 39. Stata 7.0 User’s Guide. College Station, Tex: StataCorp LP; 2001. 40. Rathmann W, Haastert B, Icks A, et al. High prevalence of undiagnosed diabetes mellitus in Southern Germany: target populations for efficient screening. The KORA Survey 2000. Diabetologia. 2003;46: 182–189. 41. Davis SK, Liu Y, Gibbons GH. Disparities in trends of hospitalization for potentially preventable chronic conditions among African Americans during
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