Measuring mental health of the Dutch population: a comparison of the GHQ-12 and the MHI-5

BACKGROUD: The objective is to compare the performance of the MHI-5 and GHQ-12, both measures of general mental health. Therefore, we studied the relationship of the GHQ-12 and MHI-5 with sociodemographic characteristics, self-reported visits to general practice and mental health care, and with diagnoses made by the general practitioner. METHODS: Data were used from the Second Dutch National Survey of General Practice, which was carried out in 104 practices. This study combines data from a representative sample of the Dutch population with data from general practice. RESULTS: The agreement between the GHQ-12 and MHI-5 is only moderate. Both instruments are however similarly associated with demographic characteristics (except age), self-reported health care use, and psychological and social diagnoses in general practice. CONCLUSIONS: The performance of the MHI-5 and GHQ-12 in terms of predicting mental health problems and related help seeking behaviour is similar. An advantage of the MHI-5 is that it has been widely used, not only in surveys of mental health, but also in surveys of general health and quality of life, and it is shorter. A disadvantage of the MHI-5 is that there is no cut-off point. We recommend a study to establish a valid, internationally comparable cut-off point

Do conceptualisations of health differ across social strata? A concept mapping study among lay people.

The legitimacy of policies that aim at tackling socioeconomic inequalities in health can be challenged if they do not reflect the conceptualisations of health that are valued in all strata. Therefore, this study analyses how different socioeconomic groups formulate their own answers regarding: what does health mean to you

Disability weights for comorbidity and their influence on Health-adjusted Life Expectancy

BACKGROUND: Comorbidity complicates estimations of health-adjusted life expectancy (HALE) using disease prevalences and disability weights from Burden of Disease studies. Usually, the exact amount of comorbidity is unknown and no disability weights are defined for comorbidity. METHODS: Using data of the Dutch national burden of disease study, the effects of different methods to adjust for comorbidity on HALE calculations are estimated. The default multiplicative adjustment method to define disability weights for comorbidity is compared to HALE estimates without adjustment for comorbidity and to HALE estimates in which the amount of disability in patients with multiple diseases is solely determined by the disease that leads to most disability (the maximum adjustment method). To estimate the amount of comorbidity, independence between diseases is assumed. RESULTS: Compared to the multiplicative adjustment method, the maximum adjustment method lowers HALE estimates by 1.2 years for males and 1.9 years for females. Compared to no adjustment, a multiplicative adjustment lowers HALE estimates by 1.0 years for males and 1.4 years for females. CONCLUSION: The differences in HALE caused by the different adjustment methods demonstrate that adjusting for comorbidity in HALE calculations is an important topic that needs more attention. More empirical research is needed to develop a more general theory as to how comorbidity influences disability

Multimorbidity and comorbidity in the Dutch population - data from general practices

<p>Abstract</p> <p>Background</p> <p>Multimorbidity is increasingly recognized as a major public health challenge of modern societies. However, knowledge about the size of the population suffering from multimorbidity and the type of multimorbidity is scarce. The objective of this study was to present an overview of the prevalence of multimorbidity and comorbidity of chronic diseases in the Dutch population and to explore disease clustering and common comorbidities.</p> <p>Methods</p> <p>We used 7 years data (2002–2008) of a large Dutch representative network of general practices (212,902 patients). Multimorbidity was defined as having two or more out of 29 chronic diseases. The prevalence of multimorbidity was calculated for the total population and by sex and age group. For 10 prevalent diseases among patients of 55 years and older (N = 52,014) logistic regressions analyses were used to study disease clustering and descriptive analyses to explore common comorbid diseases.</p> <p>Results</p> <p>Multimorbidity of chronic diseases was found among 13% of the Dutch population and in 37% of those older than 55 years. Among patients over 55 years with a specific chronic disease more than two-thirds also had one or more other chronic diseases. Most disease pairs occurred more frequently than would be expected if diseases had been independent. Comorbidity was not limited to specific combinations of diseases; about 70% of those with a disease had one or more extra chronic diseases recorded which were not included in the top five of most common diseases.</p> <p>Conclusion</p> <p>Multimorbidity is common at all ages though increasing with age, with over two-thirds of those with chronic diseases and aged 55 years and older being recorded with multimorbidity. Comorbidity encompassed many different combinations of chronic diseases. Given the ageing population, multimorbidity and its consequences should be taken into account in the organization of care in order to avoid fragmented care, in medical research and healthcare policy.</p

The FOCUS, AFFINITY and EFFECTS trials studying the effect(s) of fluoxetine in patients with a recent stroke:a study protocol for three multicentre randomised controlled trials

BACKGROUND: Several small trials have suggested that fluoxetine improves neurological recovery from stroke. FOCUS, AFFINITY and EFFECTS are a family of investigator-led, multicentre, parallel group, randomised, placebo-controlled trials that aim to determine whether routine administration of fluoxetine (20 mg daily) for 6 months after acute stroke improves patients' functional outcome. METHODS/DESIGN: The three trial investigator teams have collaboratively developed a core protocol. Minor variations have been tailored to the national setting in the UK (FOCUS), Australia and New Zealand (AFFINITY) and Sweden (EFFECTS). Each trial is run and funded independently and will report its own results. A prospectively planned individual patient data meta-analysis of all three trials will subsequently provide the most precise estimate of the overall effect of fluoxetine after stroke and establish whether any effects differ between trials and subgroups of patients. The trials include patients ≥18 years old with a clinical diagnosis of stroke, persisting focal neurological deficits at randomisation between 2 and 15 days after stroke onset. Patients are randomised centrally via web-based randomisation systems using a common minimisation algorithm. Patients are allocated fluoxetine 20 mg once daily or matching placebo capsules for 6 months. Our primary outcome measure is the modified Rankin scale (mRS) at 6 months. Secondary outcomes include the Stroke Impact Scale, EuroQol (EQ5D-5 L), the vitality subscale of the Short-Form 36, diagnosis of depression, adherence to medication, adverse events and resource use. Outcomes are collected at 6 and 12 months. The methods of collecting these data are tailored to the national setting. If FOCUS, AFFINITY and EFFECTS combined enrol 6000 participants as planned, they would have 90 % power (alpha 5 %) to detect a common odds ratio of 1.16, equivalent to a 3.7 % absolute difference in percentage with mRS 0-2 (44.0 % to 47.7 %). This is based on an ordinal analysis of mRS adjusted for baseline variables included in the minimisation algorithm. DISCUSSION: If fluoxetine is safe and effective in promoting functional recovery, it could be rapidly, widely and affordably implemented in routine clinical practice and reduce the burden of disability due to stroke. TRIAL REGISTRATION: FOCUS: ISRCTN83290762 (23/05/2012), AFFINITY: ACTRN12611000774921 (22/07/2011). EFFECTS: ISRCTN13020412 (19/12/2014)

The use of models in the estimation of disease epidemiology.

OBJECTIVE: To explore the usefulness of incidence-prevalence-mortality (IPM) models in improving estimates of disease epidemiology. METHODS: Two artificial and four empirical data sets (for breast, prostate, colorectal, and stomach cancer) were employed in IPM models. FINDINGS: The internally consistent artificial data sets could be reproduced virtually identically by the models. Our estimates often differed considerably from the empirical data sets, especially for breast and prostate cancer and for older ages. Only for stomach cancer did the estimates approximate to the data, except at older ages. CONCLUSION: There is evidence that the discrepancies between model estimates and observations are caused both by data inaccuracies and past trends in incidence or mortality. Because IPM models cannot distinguish these effects, their use in improving disease estimates becomes complicated. Expert opinion is indispensable in assessing whether the use of these models improves data quality or, inappropriately, removes the effect of trends

Has the burden of depression been overestimated?

OBJECTIVE: To investigate whether high estimates of the burden of depression could be attributed to an overestimation of disability weights (reflecting more severe disability). METHODS: We derived disability weights that were tailored to prevalence data. Empirical disability data from a Dutch community survey was used to describe three classes of severity of depression and their proportional prevalence. We obtained valuations from experts for each class and calculated the overall disability weight for depression. FINDINGS: Expert valuations were similar to those of previous studies. The overall disability weight for depression was similar to other studies except the 1994 Dutch Burden of Disease Calculation, which it exceeded by 73%. The lower Dutch 1994 disability weight resulted from an overestimation of the proportion of mild cases of depression by experts (60% versus 27% observed in the empirical data used in the present study). CONCLUSION: This study found no indication that disability associated with depression was overestimated. The Dutch example showed the importance of tailoring disability weights to epidemiological data on prevalence