Limitation in activities of daily living (ADL) is one of the core features of dementia. Clinical differentiation among dementia, mild cognitive impairment (MCI) and normal cognitive aging is largely dependent on ADL assessment. For example, ADL should be intact for a diagnosis of MCI according to the original diagnostic criteria for MCI proposed by Petersen.1 However, as impairments in complex instrumental function were repeatedly reported in patients with MCI,2,3 minimal impairment in complex ADL, which is not severe enough to satisfy the threshold of dementia, is allowed in the revised MCI diagnostic criteria proposed by the International Working Group on MCI.4 Because cognitive function and processing speed are normally decreased to some extent in normal elders, complex ADL also can be minimally impaired in the elderly subjects without objective cognitive impairments on formal neuropsychological tests.5 The importance of evaluating ADL is not limited to differentiation of MCI from dementia or normal cognitive aging. Patients with MCI who exhibit minimal ADL impairments are more likely to progress to dementia6,7 and to have smaller hippocampal volumes than those without minimal ADL impairments.8 In addition, any degree of cognitive decline assessed by neuropsychological tests may have a measurable impact on a person's ability to function in daily life, provided instruments exist that are sensitive enough to document activity restriction.9,10,11 Moreover, impairments in executive function, which are often not detected by formal neuropsychological tests, are detected from the informant-based complex ADL test.5

As the assessment of ADL impairment has become important in diagnosing MCI and dementia, the requirements for developing sensitive and reliable instruments for evaluating ADL have increased. However, in both clinical and research settings, there is no agreement on the standard instruments of ADL assessment or the norms and cut-off values for determining minimal and/or significant impairments in ADL for diagnosing MCI and dementia.4 Various scales such as the ADL scale,12 the IADL scale,13 the Bayer ADL scale14 and related dimensions of the Clinical Dementia Rating (CDR)2,4,9,10,15,16 as well as clinicians' judgments17 have been used to assess ADL in diagnosing MCI or dementia. However, there are no agreed upon normative data or cut-off values for defining minimal impairment.1 Complex instrumental ADL, in particular, may be influenced by demographic factors such as gender, education and age. These operational ambiguities in evaluating ADL might result in increased diagnostic heterogeneity and reduced predictive validity for outcomes.7

The Disability Assessment for Dementia (DAD)18 is an informant-based interview that has several strengths over other complex ADL scales in diagnosing and evaluating patients with MCI or dementia. First, it includes both instrumental and basic ADL items. Second, it evaluates which activities are problematic as well as which aspects of performance are impaired.18 Third, it is available in many languages including Korean,19,20,21,22 which facilitates multi-center and international studies.18 Therefore, in the present study, we hypothesized the Korean version of DAD (DAD-K)22 would be helpful in differentiating the NC or MCI from dementia and based on that hypothesis we examined the validity of DAD-K and established gender-, education-, and age-specific norms that may contribute to the development of a standard for evaluating ADL and studying MCI and dementia.

Subjects' demographic and clinical characteristics are shown in Table 1. Age, education, gender as well as MMSE, GDS-KR and SMCQ scores were significantly different among the six groups (p<0.001). Therefore, we performed MANCOVA using age, education, gender and GDS-KR score as covariates to compare DAD-K scores among the three groups (Table 2). All DAD-K subscale scores were significantly different among the groups (p<0.001). The post hoc analysis results are summarized in Table 2. The IADL scores began to decline significantly as the CDR increased starting from the very mild stage of AD, whereas the BADL scores declined from the mild stage of AD. Initiation, planning and organization, and performance scores also began to decline significantly as the CDR increased from the very mild stage of AD.

We summarized the area under ROC curve (AUC) and optimal cut-off scores for AD and MCI in Table 3. The AUC of the DAD-K total score differentiating MCI or AD from NC was 0.737 (95% CI=0.710-0.763) and sensitivity and specificity at its optimal cut-off were 0.964 and 0.497, respectively. The AUC of the DAD-K total score for differentiating AD from MCI or NC was 0.911 (95% CI=0.885-0.937) and sensitivity and specificity at its optimal cut-off were 0.936 and 0.824, respectively. The AUC of the DAD-K total score for differentiating MCI from NC was too low (AUC=0.549, 95%CI=0.512-0.586).

Demographic characteristics of NCs who were enrolled in establishing normative data are shown in Table 4. Age was comparable between men and women (69.23 years vs. 69.58 years, t=-1.342, p=0.180). Men were more educated than women (11.16 years vs. 7.13 years, t=20.202, p<0.001).

In the Pearson's correlation analysis, age was highly correlated with the IADL score and planning and organization (r=-0.046, p=0.024 and r=-0.060, p=0.003, respectively). Age was not significantly correlated with the BADL score, initiation, performance or DAD-K total score (r=-0.013, p=0.512; r=-0.002, p=0.928; r=-0.030, p=0.140; and r=-0.018, p=0.383, respectively). Education was highly correlated with the IADL score, DAD-K total score, initiation, planning and organization and performance (r=0.078, p<0.001; r=0.053, p=0.010; r=0.048, p=0.019; r=0.068, p=0.001; and r=0.055, p=0.008, respectively). Education was not significantly correlated with the BADL score (r=-0.026, p=0.200). In the t-test analysis, the BADL score, IADL score, DAD-K total score, initiation, planning and organization and performance were comparable between both genders [t(2357)=1.247, p=0.213; t(2358)=782, p=0.434; t(2358)=0.440, p=0.660; t(2358)=507, p=0.613; t (2357)=302, p=0.762; and t(2358)=1.034, p=0.301, respectively].

Gender factor among demographics was excluded in multiple regression analyses because gender was not significantly related with DAD-K performance. The BADL score was not significantly influenced by age and education. However, the IADL score, DAD-K total score, initiation and performance were significantly influenced by education (R²=0.6, p<0.001; R²=0.3, p=0.010; R²=0.2, p=0.019; and R²=0.3, p=0.008, respectively). The planning and organization score was significantly accounted for by age and education (R²=0.2, p=0.026 and R²=0.5, p=0.006, respectively).

The results of the 3×6 ANOVA are as follows: No main or interaction effects were found between the BADL scores and demographics variables (F=0.866, p=0.421; F=1.466, p=0.198; and F=0.624, p=0.794, respectively). The main effects of age and education, and the interaction effects between age and education were significant on the IADL score (F=6.338, p=0.002; F=12.846, p<0.001; and F=4.504, p<001, respectively). The main effect of education and the interaction effects between age and education were significant on the DAD-K total scores (F=5.215, p<0.001 and F=1.968, p=0.033, respectively). The main effect of education was significant on the initiation score (F=2.245, p=0.047). The main effects of age and education and the interaction between age and education were significant on the planning and organization score (F=3.924, p=0.020; F=5.584, p<0.001; and F=2.883, p=0.001, respectively). The main effect of education and the interaction effects between age and education were significant on the performance scores (F=4.855, p<0.001 and F=1.999, p=0.030, respectively).

In summary, the BADL score was not influenced by age and education; however, the IADL score was significantly influenced by age and education, and the DAD-K total score was significantly influenced by education. In terms of executive functioning (i.e., initiation, planning and organization, and performance) the initiation and performance scores were significantly influenced by education, and the planning and organization score was significantly influenced by age and education. Therefore, we provided mean, standard deviation, median and the 5th percentile of the BADL score as unitary scores that were not classified by demographic factors (Table 5). Mean, standard deviation, median and the 5th percentile score of the IADL score and the planning and organization score classified by age and education were provided (Table 5). Even though initiation score was influenced by education, it was not significant in the post hoc analysis. Thus, mean, standard deviation, median and the 5th percentile score of the initiation score were provided as unitary scores (Table 5). Mean, standard deviation, median and the 5th percentile score of the DAD-K total and performance scores were stratified by education (Table 5). To develop normative data for IADL, the total group was divided into four overlapping age tables and two strata of educational levels (0-3, ≥4 years). The educational strata were determined by first considering the results from the post hoc contrasts between the educational groups, which indicated significant differences between the lowest groups (i.e., 0 vs. 4-6, 0 vs. 10-12, or 0 vs. ≥13 years) and no significant differences between the lower educational groups (i.e., 0 vs. 1-3). The number of subjects within each cell required for stable estimation of normative value was also taken into account. Overlapping cell tables with midpoint ages occurring at 5-year intervals from 67 to 82 years (i.e., 67, 72, 77, and 82) were developed. The age range from which each normative value was estimated was 14 years (i.e., ±7 years around the midpoint age) for each table and the ranges for the adjacent tables are overlapped (i.e., 60-74, 65-79, 70-84, and ≥75). To interpret the test scores, the user should select the table with the closest midpoint from the subject's age.

We investigated the influences of age, education, and gender on DAD-K performance and developed normative data for the DAD-K from a large, nationally representative, community-dwelling elderly Korean population. In addition, we examined the usefulness of DAD-K in differentiating patients with MCI and/or AD from NCs.

Patients with MCI or very mild AD (CDR=0.5) and NCs had comparable BADL total scores; however, patients with mild or severer AD (CDR≥1) had significantly lower BADL total scores than that of the NCs. Moreover, patients with MCI and NCs had comparable IADL total scores; however, patients with very mild or severer AD (CDR≥0.5) had significantly lower IADL total scores than that of the NCs. This indicated that the decrease in the IADL performance preceded the decrease in the function of BADL performance, which is consistent with the results of a previous study.18 Community-dwelling patients with MCI had a significantly lower annual conversion rate to AD and a low degree of functional impairment at baseline than that of the clinic-based patients with MCI.32

The number of IADL items that the patients could perform in the DAD-K effectively differentiated the patients with MCI from those with AD (AUC=0.909). The optimal cut-off was 18/19, where sensitivity and specificity were 85.8% and 82.2%, respectively. In a previous work, the DAD-6 scale, which consisted of 6 IADL items of the DAD, also differentiated patients with AD from individuals with MCI (AUC=0.900, optimal cut-off=14).33

Consistent with a previous study,18 the total DAD-K score was not significantly correlated with age, gender and education. Deeper analysis revealed that the total IADL score was correlated with age and education. However, the influence of demographic factors on DAD-K scores was not obvious as compared with other neuropsychological tests developed for elderly Koreans.31,34

Comparing the raw score of detailed DAD-K items between the NC and MCI groups, there were no significant differences. To modify negatively skewed data, we performed log transformation with these raw scores. This revealed significant differences in the IADL total scores of DAD-K between the NC and MCI groups, but the differentiating power was low (AUC=0.546). Although log transformation revealed significant differences in some DAD-K subscales, low differentiation power and highly skewed scores toward ceiling in NCs suggested some difficulties in the practical application of our norm in differentiating NC from MCI. The 5th percentile of the IADL and planning and organization scores in some stratified groups, like less educated (0-3 years) and >69 years old, can be applied to differentiate NC from MCI. In BADL, initiation, performance and total DAD-K scores and in IADL and planning and organization scores of other demographic populations, bad performance on only one item can be interpreted as abnormal. Although the discrimination power could be low, unitary or minimally stratified our DAD-K norm is advantageous because of its easy application and interpretation.

The logistic regression analysis showed that there were significant differences between the NC and MCI groups on the IADLs, such as the ability to use the telephone and perform leisure activities/hobbies. It seems that patients with MCI have limitations in performing everyday tasks that involve memory and frontal/executive functioning. This results are partially consistent with a previous study that demonstrated that IADLs, such as the ability to use the telephone (OR=10.55) and to perform leisure activities/hobbies (OR=3.01), were decreased in patients with MCI than in the NCs.5 However in this previous study, the ability of preparing meals, taking medication, managing belongings, keeping appointments and talking about recent events were also decreased in patients with MCI than in NCs, although both this study and our current study targeted Korean elders. These differences might be partially because the characteristics of MCI group were different between the two studies. In the Seoul-IADL study,5 patients with MCI were recruited from the visitors to the geropsychiatry clinic at the department of psychiatry at the Sam-sung Medical Center in Seoul and these participants might have had more functional impairments than the participants with MCI in the present study.

Our study has several limitations. The participants are unlikely to be representative of the entire MCI population and selection of International working group MCI criteria rather than National Institute on Aging-Alzheimer's Association workgroups MCI criteria,35 in which some degree of functional impairment is allowed might contribute to our results. The cross-sectional design is another limitation. An extended longitudinal study is needed to confirm the results.

In conclusion, our findings suggest that the DAD-K scale, which evaluates complex ADL based on an informant interview, can effectively differentiate between patients with MCI and AD. Moreover, DAD-K can be used to evaluate functional impairment in MCI by using established log rank IADL norms.