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Aging Research Center (ARC), Karolinska Institutet and Stockholm University, Stockholm, SwedenInstitute of Gerontology, School of Health Welfare, Aging Research Network–Jönköping (ARN-J), Jönköping University, Jönköping, Sweden
Division of Family Medicine and Primary Care, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, SwedenNeuro Theme, Karolinska University Hospital, Stockholm, Sweden
Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, SwedenAging Theme, Karolinska University Hospital, Stockholm, Sweden
Aging Research Center (ARC), Karolinska Institutet and Stockholm University, Stockholm, SwedenFaculty of Medicine and Health, School of Pharmacy, The University of Sydney, New South Wales, Australia
Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, SwedenAging Theme, Karolinska University Hospital, Stockholm, Sweden
To explore the dementia diagnostic process and drug prescription for persons with dementia (PWD) with different socioeconomic status (SES).
Design
Register-based cohort study.
Setting and Participants
This study included 74,414 PWD aged ≥65 years from the Swedish Dementia Register (2007–2018). Their data were linked with the Swedish Longitudinal Integrated Database for Health Insurance and Labor Market Studies (2006–2017) to acquire the SES information 1 year before dementia diagnosis.
Methods
Education and income—2 traditional SES indicators—were divided into 5 levels. Outcomes comprised the dementia diagnostic examinations, types of dementia diagnosis, diagnostic unit, and prescription of antidementia drugs. Binary logistic regression was performed to evaluate socioeconomic inequalities.
Results
Compared to PWD with the lowest educational level, PWD with the highest educational level had a higher probability of receiving the basic diagnostic workup [odds ratio (OR) 1.19, 95% confidence interval (CI) 1.10-1.29], clock test (OR 1.12, 95% CI 1.02-1.24) and neuroimaging (OR 1.23, 95% CI 1.09-1.39). Compared with PWD in the lowest income quintile, PWD in the highest income quintile presented a higher chance of receiving the basic diagnostic workup (OR 1.35, 95% CI 1.26-1.46), clock test (OR 1.40, 95% CI 1.28-1.52), blood analysis (OR 1.21, 95% CI 1.06-1.39), Mini-Mental State Examination (OR 1.47, 95% CI 1.26-1.70), and neuroimaging (OR 1.30, 95% CI 1.18-1.44). PWD with higher education or income had a higher likelihood of obtaining a specified dementia diagnosis or being diagnosed at a memory clinic. SES presented no association with prescription of antidementia medication, except for the association between education and the use of memantine.
Conclusions and Implications
Higher education or income was significantly associated with higher chance of receiving dementia diagnostic examinations, a specified dementia diagnosis, being diagnosed at a memory clinic, and using memantine. Socioeconomic inequalities in dementia diagnostic process and prescription of memantine occurred among PWD with different education or income levels.
Ensuring equitable access to preventive, diagnostic and care services for this vulnerable population is considered as an important goal in the World Health Organization global action plan for dementia.
The influence of SES on the dementia diagnostic process and prescription of antidementia medication is underinvestigated. People with lower SES reported significantly higher levels of unmet health care needs than people in higher positions.
Assessing the dementia diagnostic process and medication prescription among different SES levels is important to dementia care. It would both ensure the equal access to health care for PWD and help health care providers and policy makers evaluate the quality of care. Our study aimed to investigate the socioeconomic indicators influencing dementia diagnostic process and prescription of antidementia drugs for PWD. We hypothesized that PWD with higher education and income had better access to dementia diagnosis and treatment.
Methods
Study Design and Setting
This study had a retrospective cohort design and included PWD registered in the Swedish Dementia Register (SveDem) between 2007 and 2018. Established in 2007, SveDem is a nationwide register, and has previously been described.
Individuals are registered at the time of dementia diagnosis, according to the International Classification of Diseases, Tenth Revision, codes, and specific diagnostic criteria are used for certain dementia types.
SveDem includes information at baseline registration and annual follow-ups, regarding demographics, cognition, diagnosis, living situation, and medication, as previously described.
Data on SES (2006-2017) from the Swedish Longitudinal Integrated Database for Health Insurance and Labor Market Studies (LISA) and comorbidities from the Swedish National Patient Register were linked to SveDem through PWD's identity numbers. LISA's goal is to provide a tool for statistical research on health and labor market.
Data of 80,004 PWD registered in SveDem (2007-2018) were linked with LISA (2006-2017) to retrieve socioeconomic information 1 year before dementia diagnosis. We excluded 1552 persons diagnosed before 2007, when SveDem was founded. PWD younger than 65 years were excluded in our study (n = 3739). We assumed that PWD had less fluctuations in income after this age because it is the most common retirement age. PWD who had individual disposable income less than 57,200 Swedish krona per year (about 6046 US dollars, with the Swedish Central Bank exchange rate in 2019
) were excluded. The older care allowance is a support for persons who have no or low pensions in Sweden. In 2019, the amount that a person with no income and no housing cost can receive from the older care allowance is up to 57,200 Swedish krona per year.
It means that the lowest reasonable individual income is 57,200 Swedish krona per year. After inflating the individual disposable income of each person to the 2019 value, we excluded persons with income less than 57,200 Swedish krona. These people had income lower than this threshold or had negative income. These people are likely to live off capital and their income does not represent their SES. A total of 709 out of 80,004 persons (0.89%) were excluded based on this criterion. Finally, this left 74,414 PWD for analysis.
Exposures
SES indicators, including education and individual disposable income, were the 2 main exposures of this study. The highest attained education level was extracted from LISA.
Educational levels included compulsory education <9 years, compulsory education 9 years, upper secondary, university <3 years, and university ≥3 years. Education of immigrants is explored by annual questionnaires.
If immigrants participate in any educational activity in Sweden, the new level of education will be recorded and overwrite the older one, via their personal identity number.
The inflated income was then classified into quintiles.
Dementia types, types of diagnostic unit, age at dementia diagnosis, and sex were retrieved from SveDem. Other confounding factors included living alone and Mini-Mental State Examination (MMSE) scores at dementia diagnosis. Comorbidities before dementia were condensed into the Charlson Comorbidity Index, which was calculated based on information from the Swedish National Patient Register.
Outcomes, obtained from SveDem, encompassed variables related to the dementia diagnostic process and medication. A basic diagnostic workup was recommended in the 2010 (revised 2017) guidelines by the Swedish National Board of Health and Welfare
and is followed up as a quality indicator in SveDem. It includes the completion of a structured patient history and evaluation of the patients' functional ability, physical and psychological status, an interview with a reliable relative or caregiver, and 4 tests that are followed as quality indicators in SveDem: the clock test, a blood analysis (including calcium, TSH, and either homocysteine or B12 and folate), MMSE, and neuroimaging [computed tomography (CT) or magnetic resonance imaging (MRI) of the brain].
Additional dementia diagnostic tests registered in SveDem are neuropsychological assessment, occupational therapy assessment, and physiotherapy assessment. Diagnostic units were classified as primary care or memory clinic. Dementia types were categorized as specified dementia diagnoses (Alzheimer's disease, vascular dementia, mixed dementia, dementia with Lewy bodies, frontotemporal dementia, Parkinson's disease, and other dementia) vs unspecified dementia diagnoses. Prescription of cholinesterase inhibitors (donepezil, galantamine, and rivastigmine) and memantine were examined in persons with Alzheimer's disease or mixed dementia.
Statistical Analyses
Categorical variables were presented as number of cases and percentages. Pearson chi-square or Fisher exact test was employed to compare attributes among different educational levels or income quintiles. Age was described with mean and standard deviation, using ANOVA to acquire a P value. Median, interquartile range, and P values from Kruskal-Wallis test were used to present MMSE scores.
Two binary logistic regression models were performed to examine the association between each outcome and independent variables (education or disposable individual income), as well as the robustness of the results. The first model was controlled for age at dementia diagnosis, sex, region of birth, living alone, dementia types (except for diagnosis as outcome), Charlson Comorbidity Index, types of diagnostic unit (except for diagnostic unit as outcome), and MMSE scores [except for the basic diagnostic workup and MMSE (yes/no) as dependent variables]. The second model was fully adjusted with the above covariates and additionally controlled for education (if income was the independent variable) or disposable individual income (if education was the independent variable). Spearman correlation was conducted for education and disposable individual income (r = 0.36, P < .001). Wald test was applied after the regression models to evaluate whether the association between outcomes, and SES indicators was statistically significant. Odds ratio (OR) and 95% confidence interval (95% CI) were reported.
All statistical tests were 2-tailed, with a P value less than 0.05 considered statistically significant. Stata, version 15.1 (StataCorp LLC, College Station, TX), was employed to perform the statistical analyses in this study. Missing data were addressed by excluding cases listwise.
Ethical Considerations
Ethical approval was granted by the Swedish Ethical Review Authority. All patients were informed about the registration in SveDem and their data might be used for quality improvement or research purposes. Patients could refuse to participate or withdraw consent at any time. Patient identity was pseudonymized and blinded to the researchers.
Results
Description of the Research Population
Characteristics of PWD were presented according to different educational levels (Table 1) or income quintiles (Table 2). Mean age at dementia diagnosis was around 80 years, lower in PWD with university education ≥3 years (78.9 ± 6.7) and in the highest income quintile (78.9 ± 7.2). The percentage of female PWD differed significantly in educational levels or income quintiles: decreasing from 82.2% to 38.3% (corresponding to lowest-to highest-income quintiles). In all education or income groups, more than 90% of PWD were born in Sweden or the other Nordic countries.
Table 1Demographics Among Different Educational Levels (n = 74,414)
Specified dementia includes Alzheimer's disease, vascular dementia, mixed dementia, dementia with Lewy bodies, frontotemporal dementia, Parkinson's disease, and other dementia.
Specified dementia includes Alzheimer's disease, vascular dementia, mixed dementia, dementia with Lewy bodies, frontotemporal dementia, Parkinson's disease, and other dementia.
Regarding diagnostic process, there was a significant difference in receiving the basic diagnostic workup among educational levels or income quintiles: increasing from 67.5% to 81.6% (from lowest to highest educational levels) and from 67.8% to 80.5% (from lowest to highest income quintiles). The proportions of PWD receiving individual tests separately also increased with education or income. PWD with higher SES were more often diagnosed at memory clinics: 72.6% in PWD with university education ≥3 years vs 42.3% in PWD with only compulsory education <9 years; 69.8% in PWD with highest income quintile vs 45.9% PWD with lowest income quintiles. Unspecified dementia diagnoses were more common among PWD with lower SES.
As for antidementia medications, the proportion of patients with Alzheimer's disease and mixed dementia receiving cholinesterase inhibitors among educational levels or income quintiles differed significantly: 63.2% of PWD with university ≥3 years vs 55.9% in PWD with compulsory education <9 years; 62.8% in PWD with higher income quintile vs 60.1% in PWD with lowest income quintile. A higher proportion of memantine users was also observed among individuals with higher SES.
Dementia Diagnosis and Medication in Association With Education
As shown in Figure 1, PWD with higher education presented significantly higher odds of receiving diagnostic examinations, even when adjusting for level of income: university ≥3 years vs compulsory education <9 years regarding the basic diagnostic workup (OR 1.19, 95% CI 1.10-1.29) or computed tomography and magnetic resonance imaging (OR 1.23, 95% CI 1.09-1.39). Meanwhile, no significant association between receiving blood analysis or MMSE and education was seen when controlling for income. The odds of obtaining a diagnosis in memory clinic for PWD with the highest educational level was more than 2 times higher (OR 2.16, 95% CI 2.02-2.31) than that for PWD with the lowest educational level. Significantly higher odds of receiving specified dementia diagnosis were found in PWD with higher educational levels; however, this was not significant when adjusting for their income. There was no significant association between education and prescription of cholinesterase inhibitors. Compared with PWD with compulsory education <9 years, PWD with university ≥3 years presented higher odds of receiving memantine (OR 1.16, 95% CI 1.04-1.29).
Fig. 1Dementia diagnosis and treatment in association with education. For all graphs, data were presented as odds ratios (95% confidence interval). Model 1: Binary logistic regression, controlled for age, sex, regions of birth, living alone, dementia types (except for diagnosis types as dependent variable), Charlson Comorbidity Index, types of diagnostic unit (except for types of diagnostic unit as outcome), and MMSE scores (except for basic tests and MMSE as dependent variables). Model 2: Binary logistic regression, controlled for other variables like Model 1 and additionally adjusted for disposable individual income. ∗ The basic diagnostic workup meant whether patients received all basic tests (clock test, blood analysis, MMSE, CT-MRI) or not. † Only patients with Alzheimer's disease or mixed dementia were analyzed (E1 = 13080, E2 = 2687, E3 = 13574, E4 = 2919, E5 = 4335). CT, computed tomography; MRI, magnetic resonance imaging.
Dementia Diagnosis and Medication in Association With Disposable Individual Income
Disposable individual income was significantly associated with receiving all dementia diagnostic examinations when both adjusting for and not adjusting for education, as shown in Figure 2. Compared with PWD in the lowest income quintile, PWD in the highest quintile presented higher odds of receiving the basic diagnostic workup (OR 1.35, 95% CI 1.26-1.46) and most individual tests. The odds of receiving a diagnosis at a memory clinic for PWD in the highest income quintile was double that of PWD in the lowest quintile: (OR 2.03, 95% CI 1.91-2.16). Income was associated significantly with obtaining a specified dementia diagnosis: highest vs lowest quintile (OR 1.33, 95% CI 1.24-1.43). Income was not significantly associated with the prescription of cholinesterase inhibitors or memantine.
Fig. 2Dementia diagnosis and treatment in association with disposable individual income. For all graphs, data were presented as odds ratios (95% confidence interval). Model 1: Binary logistic regression, controlled for age, sex, regions of birth, controlled for age, sex, regions of birth, living alone, dementia types (except for diagnosis types as dependent variable), Charlson Comorbidity Index, types of diagnostic unit (except for types of diagnostic unit as outcome) and MMSE scores (except for Basic Tests and MMSE as dependent variables). Model 2: Binary logistic regression, controlled for other variables like Model 1 and additionally adjusted for education. ∗ The basic diagnostic workup meant whether patients received all basic tests (clock test, blood analysis, MMSE, CT-MRI) or not. † Only patients with Alzheimer's disease or mixed dementia were analyzed (I1 = 7138, I2 = 6882, I3 = 7059, I4 = 7696, I5 = 8357). CT, computed tomography; MRI, magnetic resonance imaging.
This study aimed to assess the difference in dementia diagnostic process and antidementia medications in relation to SES. To our knowledge, this is the first study that explored dementia diagnostic process among different SES. We found that PWD with higher income had a higher probability of receiving the basic diagnostic workup, clock test, blood analysis, MMSE, computed tomography and magnetic resonance imaging, neuropsychological assessment, and occupational therapy assessment. Higher educational level was significantly associated with higher likelihood of receiving these dementia examinations, except for blood analysis and MMSE. PWD with higher education or income had higher chances of being diagnosed at a memory clinic. Receiving a specified dementia diagnosis was significantly associated with income (both when adjusting and not adjusting for education), but not with education (when controlling for income). We interpret this to mean that income was more decisive than education, in relation to dementia diagnostic process.
Our study showed that there was no significant association between SES and the use of antidementia drugs, apart from the association between education and prescription of memantine. The result regarding memantine was in concordance with a previous study in Sweden, where PWD with higher educational levels had higher chances of receiving memantine.
Differences in age range, time frame, and study population might explain these differences. PWD with higher income were less likely to receive antipsychotics. This finding is particularly important because previous studies have shown that the use of antipsychotics increases the mortality risk in PWD.
Our study is in line with prior publications on the effects of SEP on health care; the difficulty is in identifying why these differences occur and how they can be addressed. From a clinical perspective, our findings may be a signal of unfulfilled care demands and unequal provision of care. This argument is plausible to some extent because unmet health care needs among PWD with low SES in Sweden were reported in previous studies.
It is possible that PWD with low SES sought or received help later in the disease process (as seen by their higher age and lower MMSE level), which could lead to less extensive testing, and increase the chances of primary care (vs memory clinic) diagnosis. It is less likely that this is the explanation since we controlled both for age and MMSE level. It is important to reconsider the dementia diagnostic process. Assessing PWD's satisfaction with dementia care is also an area of future research. As a group, PWD often receive different care for other somatic conditions than their nondementia counterparts.
It is interesting to note that SES further influences care, even within PWD as a group.
From a public health perspective, differences in dementia diagnosis among SES may mean that health care resources were being allocated unequally between PWD with different SES. These differences in the dementia diagnostic process among SES possibly reflected a gap in the quality of dementia care. Meanwhile, PWD with lower SES accounted for a large share of the dementia population and were also more cognitively impaired. Previous studies showed that lower SES was associated with a higher dementia-related mortality risk.
The Swedish health care system is mainly financed through the regional governments and is universal for residents. Co-pays differ among regions in Sweden, but they are low (maximum $125 per year for health care services). Despite this universal health coverage, income or education lead to differences in the provision of care. In countries without a universal health care system such as the United States, people with lower education or lower income are more likely to forgo medical care due to costs.
Another study showed that care disparities due to education and income were more extreme in the United States, compared to Canada, a country with a universal health care system.
It appears that universal health care is helpful, but not in itself sufficient, to eliminate SES differences in care. Other determinants of unequal dementia care in Sweden were also shown in previous studies from our group where the type of diagnostic unit (primary vs memory clinic), population density, and living alone affected dementia diagnostic workup.
Differences in diagnostic process, treatment and social Support for Alzheimer's dementia between primary and specialist care: Results from the Swedish Dementia Registry.
As demonstrated by our study, universal healthcare was not sufficient to eliminate socioeconomic differences in access to care. Socioeconomic inequalities in dementia care should be studied and their impact on patient outcomes should be quantified. In developing nations, an aging population represents a future demographic challenge: considering these issues of access and equality of care early on would help these countries to improve their preparedness for these future changes.
Limitations
There were several limitations in our study. First, we could not investigate ethnic disparities because ethnicity is not recorded in Swedish registers. We tried to overcome this hurdle by using the regions of birth. Second, information about occupation before retirement was not available in our study. Additionally, as in many observational studies, causality cannot be inferred, and we acknowledge the possibility of residual confounding. Typical weaknesses of a register-based study cannot be neglected, such as missing values or incomplete data. Providers of health care in Sweden may be private or public but funding is through the government. We did not consider whether providers of care were public or private because access to care would not differ. Despite drawbacks, the strength of our study is the inclusion of a large national cohort with high quality and coverage for socioeconomic data.
Conclusions and Implications
PWD with lower SES (education or disposable individual income) had significantly lower odds of receiving specific dementia diagnostic examinations, getting a specified dementia diagnosis, and being diagnosed at a memory clinic. There was no significant association between SES and prescription of antidementia medication, aside from the association between education and the use of memantine. Our study results revealed socioeconomic inequalities in the dementia diagnostic process in Sweden. Future studies on health equity and equality of dementia care should be conducted.
Acknowledgments
The authors sincerely thank all patients, caregivers, reporting units, coordinators, and steering committees in the Swedish Dementia Register and the Swedish National Patient Register for providing data for this study.
References
Institute for health Metrics and evaluation. Sweden.
Differences in diagnostic process, treatment and social Support for Alzheimer's dementia between primary and specialist care: Results from the Swedish Dementia Registry.
This study was supported by FORTE, the Swedish Council for Health, Working Life and Welfare (dnr 2017-01646); Johanniterorden I Sverige/Swedish Order of St. John; Stiftelsen för Sigurd och Elsa Goljes Minne; StratNeuro and Svenska Sällskapet för Medicinsk Forskning (Swedish Society for Medical Research).
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