Utilization of Healthcare Services Among Elderly with Cognitive

Impairment No Dementia and Influence of Depression and Anxiety: a

Longitudinal Study

Alexandre St-Hilairea, Carol Hudona,b, Michel Previllec,d and Olivier Potvinb

aEcole de psychologie, Universite Laval, Quebec, QC, Canada;

bCentre de recherche de l’Institut universitaire en sante mentale de Quebec, Quebec, QC,

Canada;

cDepartement des sciences de la sante communautaire, Universite de Sherbrooke,

Sherbrooke, QC, Canada;

dCentre de recherche Hopital Charles LeMoyne, Longueuil, QC, Canada

Abstract

Objectives: Little objective and nationally-representative data are available concerning the

influence of cognitive impairment no dementia (CIND) on utilization of healthcare

services. The main objective was to compare the use of healthcare services over three years

between elders with current or incident CIND and those without CIND. A second objective

was to evaluate the effect of depression and anxiety. Methods: Cross-sectional and

longitudinal data from a population-based survey of 2265 older adults living in Quebec

(Canada) was used. CIND was identified using normative data for the MMSE and was

linked with medical records from public health insurance plan. Multinomial logistic

regressions adjusted for relevant socio-demographic, social network, and health-related

confounders were conducted for each service. Interaction between CIND and

depression/anxiety was also examined. Main results: Current CIND was a predictor of

longer anxiolytic/sedative/hypnotic medication use. Incident CIND led to longer hospital

stay. Depression raised the likelihood of frequenting geriatricians, psychiatrists or

neurologists and emergency department, but lessened the likelihood of visiting general

practitioners. The addition of the psychiatric conditions to the incident CIND did not

increase the likelihood of consuming antidepressants, while the incident CIND cases

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without psychiatric conditions increased this likelihood. Discussion: Compare to older

adults without CIND, older adults with CIND have a distinct utilization of healthcare

services. Multiple evaluations over many years may help to better understand the utilization

of healthcare services in individuals with CIND. In the meantime, evaluations of these

conditions at key moments could allow a more efficient use of health resources.

Key words: mild cognitive impairment; primary care; emergency service; hospitalization;

psychotropic drugs

Word count: 6899 (including in the text authors' names)

Abbreviations

AChEI: Acetylcholinesterase inhibitorsASH: Anxiolytic/sedative/hypnoticCI: Confidence intervalCIND: Cognitive impairment no dementiaDEIS: Depressive episode with insufficient symptomsDSM: Diagnostic and Statistical ManualESA: Study on elders’ healthLASA: Longitudinal Amsterdam Study of AgingMCI: Mild cognitive impairmentMDE: Major depressive episodeMMSE: Mini-Mental State ExaminationMoCA: Montreal Cognitive AssessmentOR: Odds ratioRAMQ: Régie de l’assurance maladie du QuébecT1: Initial evaluationT2: Follow-up evaluationTAG: Generalized anxiety disorderUAD: Unspecified anxiety disorder

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Introduction

By 2036, the proportion of Canadians aged 65 and older will be 25% (Sheets & Gallagher,

2013), thus increasing the number of health problems such as cognitive impairment no

dementia (CIND) and mild cognitive impairment (MCI), two potentially prodromal

conditions of dementia (Petersen et al., 2001; Tuokko et al., 2003). The diagnosis of MCI

as defined by Petersen et al. (2001) and Albert et al. (2011) refers to older adults having

subjective and objective cognitive deficits but relatively preserved general cognitive

functioning and activities of daily living. This condition is intended to identify the early

presence of an irreversible neurodegenerative process. This study focuses on the concept of

CIND, which refers to elders who do not meet all criteria for dementia but show cognitive

performance below what would be expected for age and education level (Tuokko et al.,

2003; Ward et al., 2012). The concept of CIND is more inclusive than MCI, especially

because CIND is based on a deficit on a test of general cognitive functioning. Thus, CIND

is an advantageous concept in the context of epidemiological studies in order to draw

representative conclusions on the population seen in medical practice rather than about a

small number of these individuals. Indeed, in medical practice, the assessment of cognitive

functions is usually limited to a screening of the general cognitive functioning (e.g., MMSE

or MoCA) rather than a neuropsychological assessment.

Depressive and anxiety symptoms are among the most current neuropsychiatric

symptoms in community-dwelling aged people with MCI (van der Linde et al., 2012).

Three recent meta-analyses indicated that symptoms of depression and anxiety increased

the risk of progression from no cognitive impairment to MCI or dementia (Diniz et al.,

2013; Gao et al., 2013; Yates et al., 2013). Despite the pieces of evidence about the role of

neuropsychiatric symptoms on cognition, many studies exclude subjects with such

comorbidity because they are excluded from the criteria of MCI, as defined by Petersen et

al. (2001). This has an impact on the prevalence of MCI. For example, clinical prevalence

of amnestic-type MCI was slightly greater than 50% in two different studies of depressed

patients (Adler, Chwalek, & Jajcevic, 2004; Lee, Potter, Wagner, Welsh-Bohmer, &

Steffens, 2007) which is considerably higher than the 3 to 6% prevalence of amnestic MCI

among nondepressed individuals (Ganguli, Dodge, Shen, & DeKosky, 2004; Lopez et al.,

2003). In order to preserve the representativeness of seniors with cognitive deficits that may

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progress to dementia, it seems more appropriate to include elders with depressive and

anxiety symptoms in the definition of MCI/CIND (Panza et al., 2010).

It is well documented that dementia leads to great costs and use of healthcare

services (Oremus & Aguilar, 2011), but few studies documented this use in MCI or CIND.

Some studies evaluated the use of healthcare services simultaneously in both cognitively

impaired and depressed older adults, although the effect of cognition and depression was

each measured as independent variables. Prospective studies found mixed results regarding

the effect of current CIND on visits to a medical professional (Beekman et al., 2002;

Fowler et al., 2012). Apart from participants (age, sex) or study (length of follow-up)

characteristics, in general the presence of incident CIND and depression predicted the

number of emergency department visits (Lee et al., 2008; Rottenberg et al., 2013; Stephens

et al., 2012; Wolinsky et al., 2008), as well as the number or length of hospitalizations

(Huang et al., 2000; Sandberg et al., 2012). To our knowledge, only three studies tested the

interaction (moderating effect) between depression and cognition on some services. After a

follow-up of 10 years, Sonnenberg et al. (2008) showed that both depression and the

presence of cognitive decline were associated with an increase of antidepressants use, but

the effect of cognition was only significant in participants without major depression.

Soudry et al. (2008) reported same results. Feng et al. (2009) studied the effect of the

interaction (CIND and depression) on visits to a general practitioner and hospitalizations.

The interaction was not significant.

Although anxiety disorders in older adults increase the likelihood of visiting a

general practitioner (de Beurs et al., 1999; Gurmankin Levy, Maselko, Bauer, Richman, &

Kubzansky, 2007), a medical specialist (Diefenbach et al., 2004; Gurmankin Levy et al.,

2007), emergency department (Diefenbach et al., 2004; Gurmankin Levy et al., 2007;

Naughton et al., 2010) and increased consumption of benzodiazepines (de Beurs et al.,

1999), researchers examining cases of generalized anxiety disorder have often found a lack

of effect on those services (Calleo et al., 2009; Porensky et al., 2009; Stanley et al., 2003).

All the studies listed above reported anxiety as an independent variable and not in

interaction with cognition.

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Critics and limits can be identified regarding the previous studies in this field. First,

previous researches were conducted in several countries with different health systems,

which make comparisons difficult.. Second, most studies documented use of services from

self-report and did not take into account the divergence of services according to geographic

regions (e.g., urban vs. rural). The validity and generalizability of the data can therefore be

questioned (Hunger et al., 2013). Third, few authors (Beekman et al., 2002; Comijs et al.,

2005) examined the effect of both current and incident CIND on the use of healthcare

services. Yet, the care trajectories of these two groups are possibly different as current

CIND refers to any cognitive impairment at a given time while incident CIND represents

new case at potentially early time in the continuum of cognitive decline. Fourth, many

studies used the term “cognitive decline”, which is confusing because the severity and

evolution of cognitive decline often remain unknown.

The first objective of the current study was to compare the use of healthcare

services on a period of three years between elders with current or incident CIND and those

without CIND. The interest in addressing both conditions in the same article was to

differentiate the influence of cognitive decline (i.e. incident CIND) of the influence of

cognitive deficits that may have been present for a long time (i.e. current CIND, which can

originate from various causes) on the use of healthcare services. The second objective was

to examine the independent or moderating effect of depression and anxiety disorders on the

use of these services. It was expected that the presence of CIND, depression and anxiety

would increase the use of healthcare services when compared to the absence of these

conditions.

Methods

Study Design and Setting

Data come from the ESA study (Enquête sur la santé des aînés; Study on elders’ health),

which is a population-based survey on the psychological distress of elders living in the

province of Quebec (Canada) (Préville et al., 2008). In 2005-2006, a random sample of

community-dwelling French-speaking older adults aged 65 years or older was recruited. A

little more than 94% of the Quebec population speaks French (Statistics Canada, 2011).

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The sampling frame of the study used a random dialing method with a stratification of

proportional sample of households according to three geographical areas: metropolitan,

urban and rural. In each geographical area, a proportional sample of households was

constituted according to the administrative regions of Quebec. Institutionalized elders were

not included (i.e. living in public nursing home). In this survey, subjects living in distant

regions (Côte-Nord, Gaspésie et Îles-de-la-Madeleine, Saguenay-Lac-Saint-Jean, and

Abitibi-Témiscamingue) from the main research center were excluded from the sampling

frame because of high travel costs. In 2005, 10% of the older adult population resided in

these regions. A random sampling method was also used to select only one elder within the

household. Data were collected through two in-home structured interviews. The follow-up

interview (T2) occurred approximately 12 months after the baseline assessment (T1; mean

= 12.5, SD = 1.4). They were conducted by trained research nurses who received two days

of training by the principal investigator of the ESA study (MP) in the administration of a

computer-assisted questionnaire (ESA questionnaire). Data from the ESA study were

linked with medical records from the RAMQ (Régie de l’assurance maladie du Québec),

which includes information about the use of healthcare services (see Figure 1). In Quebec,

all residents contribute financially to this public health insurance plan and 96% of people

aged 65 and older are covered exclusively by the RAMQ (Barnard et al., 2001).

Respondents were offered $15 for their participation at each interview. At the first

interview, a written consent to participate in the study and to use the medical records was

signed by the volunteers. The research procedures were authorized by the Ethics Research

Board of the Institut universitaire de gériatrie de Sherbrooke.

_________________________________________________________________________Insert Figure 1 here

_________________________________________________________________________

Participants

Figure 2 shows the flow chart of the study enrolment and exclusion criteria. There were

3675 people contacted. The response rate was 76.5% at baseline (n = 2811). Near 12

percent refused to take part in the study and another 12 percent were not eligible because

they did not speak French, were confused, had significant hearing loss, or were dead. There

6

was no difference between respondents and non-respondents according to available data

(i.e. age, sex and geographical area). To ensure the validity of the data in the ESA study,

the complete interview was done only with participants who scored 22 or higher on the

Mini-Mental State Examination (MMSE). This cut-off was based on Crum, Anthony,

Bassett, and Folstein (1993) in order to avoid the categorization of cognitively intact

elderly people with little education as demented. Medical records from the RAMQ were

available for 2494 individuals and only these participants were included in this study. The

missing data from the RAMQ records were due to refusal of consent to provide medical

records, moving outside Quebec, or having additional drug insurance. Participants excluded

because of missing RAMQ data did not differ statistically from those included in the study

in terms of mean MMSE score and prevalence of psychiatric diagnoses. In addition to the

exclusion of participants with an MMSE score below 22 (n = 26), potential dementia cases

were excluded using the RAMQ public medical records. Participants who received a

diagnosis of dementia from a medical doctor and/or were taking an approved

pharmacological treatment for dementia (memantine, donepezil, galantamine, or

rivastigmine) during the year before or the year following the first interview were excluded

from the sample (n = 47). In the Quebec public health insurance plan, these

pharmacological treatments are only covered for individuals who received a diagnosis of

dementia. In order to exclude diseases which are well-known for their high association with

elevated use of health services, seniors with neurological/brain disease (Parkinson's disease,

multiple sclerosis, epilepsy, acquired brain injury, cerebrovascular disease), psychotic

disorder (schizophrenia, affective psychosis, substance-induced psychosis, transient organic

psychosis, other psychosis), delirium and substance use disorder at baseline were excluded

(n = 174). Eight participants for whom education level was unknown were excluded since

this information was necessary to identify the presence of CIND according to normative

data.

The final sample used in this study comprised cross-sectional and longitudinal data from

2265 individuals at T1 aged between 65 and 96 years old. Four hundred and seventeen

participants dropped the study and 46 died before T2. The dropouts had relatively lower

MMSE scores compared to those who died and those who remained (p = .002; 28.3, 28.6

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and 29, respectively). Groups were equivalent on all other independent variables and

covariates (see Variables section).

_________________________________________________________________________Insert Figure 2 here

_________________________________________________________________________

Variables

Healthcare Services (dependent variables).

Healthcare services were derived from RAMQ data and covered separately the year before

and after T1, as well as the year after T2. Healthcare services were the number of: 1) visits

to a general practitioner (excluding in-home visits); 2) visits to a geriatrician, a psychiatrist

or a neurologist; 3) emergency department visits; 4) days of hospitalizations; 5) dosing days

of anxiolytic/sedative/hypnotic (ASH) medication; and 6) dosing days of antidepressant

medication. Psychotropic drugs were classified according to the American Hospital

Formulary Service (American Society of Health System Pharmacist, 2001). A level of

emergency was evaluated by medical doctors for each hospitalization at admission: 1)

urgent (admission which cannot be delayed because of the risk of threatening the life or

seriously worsen the disease); 2) semi-urgent (admission which cannot be delayed more

than the number of days specified by the physician, without the risk of threatening the life

or seriously worsen the disease); and 3) non-urgent (admission for which a delay will not

aggravate the disease). The visits to doctors in the three medical specialties under study

were combined to avoid an absence of visit for one specialty.

Since healthcare services variables were not normally distributed, three categories

(none, < median, ≥ median) were derived for each service based on the median number of

visits or days of medication consumption (median derived among users of services).

Median number for psychotropic drugs were calculated separately for men and women

since women are larger consumers (Sewitch et al., 2006). Medians were chosen because

they are not influenced by outliers. Emergency department visits were divided in two

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categories (none, ≥ one visit) because the range of this variable was lower than the other

variables. For all services variables, the reference category was the absence of utilization.

Current and Incident CIND (independent variables)

Current CIND refers to any cognitive deficits of different sources at T1 according to a

MMSE score (French version, score ranging from 0 to 30) (Hébert, Bravo, & Girouard,

1992) at least below the 15th percentile (one standard deviation below the mean on a normal

distribution) according to age (three categories), education (three categories), and sex

normative data (Hudon et al., 2009). More precisely, MMSE scores increase with education

level and decrease with age while women have higher scores than men.

Incident CIND was meant to identify cognitive decline between T1 and T2. It was

defined as participants without current CIND at T1 but who fell under the 15th percentile at

T2. In addition to this criterion, a loss of at least two MMSE points between baseline and

follow-up interviews was required to meet incident CIND criteria since it was previously

established that a reliable change in MMSE score for short intervals corresponds to a loss

of at least two points (Hensel, Angermeyer, & Riedel-Heller, 2007). On average, 3.5 points

(SD = 1.5) were loss on MMSE between T1 and T2 for participant with incident CIND.

People with current CIND who declined between T1 and T2 were not considered as

incident CIND.

Depression and Anxiety (independent variables)

The presence of depression and anxiety was initially identified according to an adapted-to-

elders version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR)

mood and anxiety disorders sections of the Diagnostic Interview Schedule and Composite

International Diagnostic Interview, a semi-structured interview assessing DSM criteria

which have demonstrated satisfactory reliability and validity to establish psychiatric

diagnoses (Erdman et al., 1992; Robins et al., 2000; Wittchen et al., 1991). The criteria

were later adapted for the fifth edition (APA, 2013). Major modifications were the removal

of the bereavement exclusion in major depressive episode and the exclusion of obsessive-

compulsive disorder from the anxiety disorders. Depression was categorized into major

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depressive episode (MDE) and depressive episode with insufficient symptoms (DEIS).

DEIS refers to the presence of a depressed affect, at least one other symptom of a MDE,

and clinically significant distress or functional impairment that persist for at least two

weeks. Unlike other diagnoses from DSM-5 Other Specified Depressive Disorder category,

the criteria for DEIS allowed us to include subjects with the same minimal symptoms

period as those with a MDE (two weeks). Anxiety disorders included specific phobia,

social anxiety disorder, agoraphobia, panic disorder and generalized anxiety disorder.

Symptoms characteristic of an anxiety disorder that cause clinically significant distress or

functional impairment not meeting the full criteria for any of the anxiety disorders were

categorized as unspecified anxiety disorder (UAD).

Covariates

Data on covariates were collected through the administration of the ESA questionnaire.

Covariates were chosen because they have been documented to modify the utilization of

healthcare services (Andersen, 2008). Sociodemographic covariates included age, sex, level

of education (primary, secondary, postsecondary) and annual household income, which

was dichotomized (< CAD $25,000; ≥ CAD $25,000) according to the 2005 Canadian

poverty threshold (CAD $24,412) for a two-person household with no dependent children

(Government of Quebec, 2013). Geographical accessibility of healthcare services included

two variables: geographical area (metropolitan, urban, rural) and the median distance in

kilometers to access the nearest medical facility or hospital (documented through RAMQ

data). Health covariates included subjective health (poor/medium, good/very

good/excellent) and the number of chronic diseases. An inventory of 16 chronic health

problems was developed in reference to the International Classification of Diseases (ICD-

10). The number of chronic diseases was measured by asking participants if they had any of

the following chronic health problems: anemia, arthritis or rheumatism, asthma or

emphysema or chronic bronchial diseases, backache or spinal problems, blood pressure,

diabetes, digestive problems, eye diseases, hearth diseases, hypercholesterolemia, kidney or

urinary problems, liver diseases, migraine or frequent headaches, skin diseases, thyroid

disorders, and other metabolic disorders.

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The influence of the social network was taken into account using six variables:

marital status (living alone, living in a couple), having at least one child, sibling or friend

still alive, social support, and social integration. The social support and social integration

scales were each composed of three statements (see Mechakra-Tahiri et al., 2011 for

questions). For each endorsed question, one point was given leading to scales ranging from

0 (no support/integration) to 3 (high support/integration).

Statistical Methods

Data were weighted to ensure that the actual proportion of older adults in each region and

in each geographical area was reflected in the analyses. Weights were determined based on:

(1) the probability of selection of the administrative region in the geographical area [π (a)];

(2) the conditional probability of selection of the household in the administrative region [π

(b/a)], and (3) the conditional probability of selection of the subject in the household [π

(c/ab)]. The weight attributed to each subject represented the inverse of its probability of

selection (1/[π (abc)]). All results in this article refer to weighted data and frequencies are

rounded to the nearest integer number.

First, multinomial logistic regressions (or binary logistic regression for emergency

department visits) were conducted for each dependent variable for the period of one year

before T1 and for the two subsequent years. This strategy allowed documenting the use of

healthcare services preceding and following current CIND, as the utilization preceding and

during a cognitive decline (incident CIND). The reference group was always the absence of

the condition under interest (e.g., incident CIND vs. no incident CIND, MDE vs. no MDE,

etc.). For the selection of covariates, a manual backward selection approach was used with

a P-value for removal of .10, to build a model that included only the covariates that were

significant or nearly significant in predicting the use of healthcare services. Thus, all

covariates were included in the first regression and were removed from the initial model

when not significant. However, the predictors of interest (CIND, depression and anxiety)

were retained into the final models even when they were not significant. All results are

derived from adjusted analyses. Second, in order to verify a potentialmoderating effect of

psychiatric conditions (i.e. depression and/or anxiety) on the relationship between CIND

and service utilization, further analyses tested an interaction term (current or incident

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CIND*depression and/or anxiety vs. absence of all these conditions) in each final model,

which only includes significant covariates. Depression and anxiety were merged because

the number of participants was not sufficient to evaluate separately effects of each

condition taken individually.

All covariates used were those collected during the initial interview, except for

psychiatric (MDE, DEIS, anxiety disorder and UAD) and chronic diseases which also

included the year following T1for the follow-up analyses (T2). Nagelkerke R Square value

was computed for each model. Assumptions for the multinomial logistic regressions were

verified including linearity in the logit, multicollinearity and outliers using common criteria

(Tabachnick & Fidell, 2012).

In order to minimize the effect of outliers on the analyses, values greater or less than

three standard deviations were replaced with the value corresponding to three standard

deviations (Osborne & Overbay, 2004). This procedure applied only for one continuous

variable, namely the distance in kilometers to access the nearest medical facility or hospital.

Since missing data in covariates lead to the exclusion of participants in logistic regression,

a strategy of multiple imputations (Rubin & Schenker, 1991) was used in order to verify the

impact of missing data. Ten datasets using all covariates were generated. Given the number

of dependent variables, the alpha level was conservatively set at .01 (two-tailed). Analyses

were performed using SPSS 21.0 software.

Results

Descriptive Data

After comparing analyses using with and without imputed data, missing data for covariates

had little effect on the results. Therefore, results without imputation were reported in this

study. A total of 190 (8.4%) participants met the criteria for current CIND while 91 (5.5%)

met those of incident CIND. Table 1 shows the characteristics of the sample at baseline

(T1). Participants with current CIND were compared to those without CIND at T1.

Likewise, participants with incident CIND were compared to those without CIND neither at

T1 nor T2. Compared to those without CIND, participants with current CIND were more

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likely to have lower MMSE scores. Participants with incident CIND had lower MMSE

scores at T1 than those without CIND (see Table 1) as well as at T2 (24.7 versus 29.0,

respectively), t(1648) = -35.08, P < .001. Tables 2 to 5 present effects of independent

variables on each service under study. Significant interaction analyses are only presented in

the corpus of the article.

_________________________________________________________________________Insert Table 1 here

_________________________________________________________________________

Visits to a General Practitioner and to a Geriatrician, a Psychiatrist or a Neurologist

Having a MDE or DEIS was significantly associated with fewer visits to a general

practitioner before T1 (Table 2). In contrast, having a MDE or DEIS at least doubled the

likelihood of consulting a geriatrician, a psychiatrist or a neurologist during the two years

after T1. Because one could argue that visits to a psychiatrist contributed mainly to the

significant results, this was verified and MDE and DEIS were still significant in predicting

one visit to a geriatrician or a neurologist during the two years after T1 (MDE: adjusted OR

= 2.53, 99% CI = 1.06-6.09, P = .006; DEIS: adjusted OR = 3.13, 99% CI = 1.30-7.55, P

= .001).

_________________________________________________________________________Insert Table 2 here

_________________________________________________________________________

Emergency Department Visits and Hospital Stays

Only DEIS increased the likelihood of having at least one emergency department visit the

year before T1 (Table 3). UAD reduced the likelihood of a hospital stay before T1 (Table

4). Incident CIND led to over twofold likelihood increment of having a hospital stay over

the median during the two years after T1. During this period, among elderly with at least

one day of hospitalization, people with incident CIND were in average hospitalized 20.6

days by opposition to 8.7 for those without CIND.

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A non-negligible proportion of hospitalizations was categorized as non-urgent

(admission for which a delay will not aggravate the disease) by medical doctors. With

regard to the first hospitalization at each year of the study, this concerned 32% and 20%

(before T1), 28% and 10% (first year after T1) and 43% and 43% (second year after T1) of

people with current and incident CIND, respectively.

_________________________________________________________________________Insert Table 3 here

__________________________________________________________________________________________________________________________________________________

Insert Table 4 here_________________________________________________________________________

Dosing Days of an Anxiolytic, Sedative or Hypnotic (ASH)

Current CIND was a significant predictor of ASH taking during the year before T1 (Table

5). During this period, among elders with at least one dosing day of ASH, those with

current CIND took ASH in average during 224 days by opposition to 181 for those without

CIND. MDE increased at least by two-fold the likelihood of taking ASH before and after

T1. UAD also influenced upward ASH taking during the year before T1. Anxiety disorder

led to a significant increase of ASH consumption after T1.

Dosing Days of Antidepressants

There was a significant increasing effect of incident CIND on antidepressant taking during

the cognitive decline (Table 5). Indeed, after T1, 27.5% of participants with incident CIND

took antidepressants against 14.9% for those without CIND. Unsurprisingly, MDE and

DEIS increased significantly the likelihood of taking antidepressants before and after T1.

MDE raised also the likelihood of taking antidepressants after T1 over the median while

UAD had a rising effect after T1.

_________________________________________________________________________Insert Table 5 here

_________________________________________________________________________

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Interaction Between CIND and Anxiety/Depression

Interaction analyses between incident CIND and psychiatric conditions revealed a

significant interaction for dosing days of antidepressants after T1 (P < .001). Stratification

of this interaction revealed that the addition of the psychiatric conditions to the incident

CIND did not increase the likelihood of consuming antidepressants (adjusted OR = 0.38,

99% CI = 0.09-1.63, P = .088), while the incident CIND cases without psychiatric

conditions increased the likelihood of consuming antidepressants (adjusted OR = 3.72, 99%

CI = 1.70-8.13, P < .001). Among participants with both incident CIND and psychiatric

condition, only 13.8% took antidepressants whereas 32.8% of participants with incident

CIND without psychiatric condition took antidepressants. No other significant interaction

between CIND and anxiety/depression was observed for other healthcare services.

Discussion

The first objective of this study was to compare the use of professional and

pharmacological healthcare services on a period of three years between Quebec-French

older adults with current or incident CIND and those without CIND. Healthcare services

included the number of visits to a general practitioner, visits to a geriatrician, a psychiatrist

or a neurologist, emergency department visits, days of hospitalization, and dosing days of

ASH and antidepressants. The second objective was to examine the effect of depression and

anxiety on the use of healthcare services. The clinical utility of this study allows us to make

recommendations to promote the detection and management of these patients in different

service points and improve coordination between different levels of care.

Visits to General Practitioners and to Medical Specialists

Current and Incident CIND

Despite the lack of effect of CIND on visits to general practitioner in our study, the vast

majority of seniors visited this professional at least once a year, whether or not they had a

CIND. Thus, many elders with CIND possibly met their general practitioner for the same

reasons than non-CIND participants. Besides, Helmer et al. (2008) found that one third of

patients with dementia did not explicitly report their cognitive problems to their general

15

practitioner. It may be hypothesized that the same scenario applies for CIND patients and

that they may be more numerous to do so since their cognitive deficits are less likely to

have an impact on their daily activities and may be less apparent if a caregiver

compensates.

Unlike Beekman et al. (2002), neither current nor incident CIND increased the

likelihood of consulting a medical specialist. In Quebec, access to a medical specialist is

usually possible only after a referral from a general practitioner. The involvement of the

neurologist and psychiatrist is thus usually preceded by a cognitive screening completed by

the general practitioner. However, it was demonstrated that cognitive deficits are under-

diagnosed in the elderly attending primary care services (Mitchell, Meader, & Pentzek,

2011) and only 24.4% of general practitioner reported screening their patients aged 75

years and older each year (Gaboreau et al., 2014). Furthermore, it can be assumed that

when general practitioners detect CIND, they consider they can handle cognitive deficits by

themselves. In sum, geriatricians, psychiatrists and neurologists are probably consulted

primarily for reasons of differential diagnosis rather than for the continuous delivery of

services. Yet, these specialists can often better inform patients about their cognition and

provide recommendations to prevent a possible cognitive decline.

Depression and anxiety

Similar to Beekman et al. (2002), MDE and DEIS increased the likelihood of consulting a

geriatrician, a psychiatrist or a neurologist after T1, whether or not psychiatrist visits were

included. All these professionals must be aware that they are thus likely to encounter

depressive seniors in their practice. On the contrary, MDE and DEIS decreased the

likelihood to consult a general practitioner before T1. Yet, the systematic review of Luppa

et al. (2012) showed higher proportion of depressed older adults consulting a general

practitioner. However, many studies included in this review used scales of severity with

different cut-off scores for the same tool, which may alter the likelihood of being targeted

as depressed. These diagnostic differences could explain the discrepancy between studies.

Some reasons may also explain the under-utilization of general practitioners in

depressed elders of our study. First, maybe participants are already monitored by a medical

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specialist. Another explanation is that those elders with depression or anxiety disorder are

more likely to have symptomatology associated with these conditions (e.g., lethargy,

isolation) that prevent them from seeking general services, whether for their physical or

mental health. Furthermore, in regards of mental health, older adults have often negative

attitudes toward seeking professional help (Mackenzie, Scott, Mather, & Sareen, 2008).

Barriers for seeking help in medical practice are the common desire in elderly to handle

problems by themselves (Mackenzie, Pagura, & Sareen, 2010), the fear of being

stigmatized (Goncalves, Coelho, & Byrne, 2014), the hopelessness about the prospect of

recovering (Corcoran et al., 2013), the older people’s preference for psychotherapeutic

treatments rather than medication (which is most of the time offered by scarce non-medical

professionals specialized in geriatrics) (Laidlaw, 2013) and the belief from general

practitioners that depression is relatively expected in old age (Burroughs et al., 2006),

which in turn may result in the minimization by elders of the importance of their

psychological symptoms or their attribution to normal aging (Corcoran et al., 2013).

With respect to anxiety disorder or UAD, they neither led to a greater number of

visits to general practitioners nor medical specialists. In addition to barriers listed above, as

avoidance is a characteristic in anxiety, this may result in low levels of older people seeking

help (Laidlaw, 2013). Moreover, it is possible that anxiety is less well detected by general

practitioners than depressive symptoms (Mohlman et al., 2012) and therefore, they are less

referred to medical specialists.

In sum, depressed or anxious seniors probably seek for help mainly when they

suffer from persisting somatic symptoms related to their psychiatric condition (Corcoran et

al., 2013). Thus, clinicians should be aware about typical manifestation of depression and

anxiety in older adults (e.g., irritability, somatization, social isolation) which may differ of

younger adults in order to target those who could benefit from further evaluation and

treatments. Routine screening for depression in adults is subject of debate (Joffres et al.,

2013). However, considering the barriers stated above as well as evidence that older people

are less able to identify symptoms of depression and anxiety (Wetherell et al., 2009), it may

be difficult to identify these symptoms without questioning the elder. Indeed, questioning

depressed mood or mental distress (Bland & Streiner, 2013) has a good predictive value for

17

frequent unnecessary visits to the emergency department (McCusker et al., 2000) and is

recommended by the National Institute for Health and Clinical Excellence (National

Collaborating Centre for Mental Health, 2010). Finally, as depression and anxiety raise the

likelihood of progressing from no cognitive impairment to MCI and dementia (Yates et al.,

2013), we may hypothesize that harm could be greater if these mental conditions were not

investigated by a clinician who would doubt about the mental health integrity of his/her

elder patients. General screening questions for anxiety were proposed in recent Canadian

guidelines (Katzman et al., 2014).

Hospitalizations and Emergency Department Visits

Current and Incident CIND

A significant effect was found in favor of incident CIND regarding the length of

hospitalization after T1 (about 12 days longer in hospital than those without CIND) and

this result echoed those of many previous studies (Chodosh et al., 2004; Ehlenbach et al.,

2010; Wilson et al., 2012). Incident CIND could be due to an Alzheimer-type

neurodegenerative process or vascular risk factors, even in absence of dementia (Stephan,

Matthews, Khaw, Dufouil, & Brayne, 2009). In addition of being accentuated after

hospitalization, it has been shown that cognitive decline post-hospitalization among the

elderly is significantly correlated with cognitive decline pre-hospitalization (Wilson et al.,

2012). It thus may be advantageous to promote a close monitoring of vascular risk factors

in order to lessen some preventable causes of hospitalizations, which cost more than $4

billion per year in the USA (Ouslander & Berenson, 2011). Assessment of cognitive

functions could also be led before the decision to hospitalize is taken (Shah et al., 2011) as

well as setting a monitoring follow-up few weeks after a hospital discharge (Bradshaw et

al., 2013). Moreover, some authors argued that convalescence could be improved if the

length of stay of hospitalization was shortened (Krumholz, 2013). Indeed, longer hospital

stays were associated with greater cognitive decline (Wilson et al., 2012) and delirium

(Vasilevskis, Han, Hughes, & Ely, 2012), which arise in five to 35% of cases during

hospitalization (Chong, Chan, Tay, & Ding, 2014). In our sample, 43% of participants with

current or incident CIND were admitted to the hospital although their admission could have

been delayed without a deterioration of their medical condition. Therefore, it is possible to

18

ask whether it was necessary to hospitalize these patients and particularly those with CIND.

If necessary, it might have been possible to plan their medical examinations on a more

limited time period to avoid long hospitalizations, cognitive decline and to reduce costs

related to room occupancy.

Depression and anxiety

It may seem counterintuitive that MDE did not increase the likelihood of going to the

emergency department while it was the case for DEIS. As stated earlier, McCusker et al.

(2000) found in their Quebec study from an elderly sample that feeling depressed assessed

by solely one question had a good predictive value for frequent visits to the emergency

department. One could argue that MDE participants had mainly a loss of interest without

feeling depressed. However, in our study, 93.3% of MDE participants reported feeling

depressed. In order to meet clinical criteria for MDE, the symptoms are so significant that

they impact functioning (e.g., lethargy, isolation), which could include seeking health

services. Because DEIS would probably not result in as much functional impact, they may

be more aware of their medical and mental problem and inclined to seek services. Another

explanation could be that participants with DEIS had MDE in the past and that they are

looking for help to avoid falling again in a worst depressive mood. While visits to

emergency department by depressed elders can be explained by a physical health problem,

it is also possible that the emergency is the only service to which they have a quick access

to report their distress.

Psychotropic Drugs

Current CIND was associated with more dosing days of ASH before T1. This result is not

surprising considering that long-term intake of benzodiazepines, the main ASH, can be

associated with cognitive deficits (Weston et al., 2010). Préville et al. (2012) reported from

the current sample that nearly half of seniors had at least one potentially inappropriate

prescription of benzodiazepines the year preceding the survey. Alternative pharmacological

and psychological treatments should be chosen whenever possible for psychiatric

conditions such as anxiety (Gould, Coulson, & Howard, 2012) and trouble sleeping (Irwin,

Cole, & Nicassio, 2006) in elderly, especially since no long-term benefit on trouble

19

sleeping was found with benzodiazepines contrarily to cognitive behavioural therapy

(Morin, Colecchi, Stone, Sood, & Brink, 1999).

In agreement with the results of Sonnenberg et al. (2008) and Soudry et al. (2008), it

was also found that incident CIND was associated with more dosing days of

antidepressants in the absence of a comorbid psychiatric condition. Perhaps people with

incident CIND consume more antidepressants because of sleep disorders. Indeed, these

disorders can precede cognitive decline (Potvin et al., 2012) and antidepressants count

among the possible treatments. It is also possible that early cognitive decline potentially

caused by neurodegenerative or vascular processes have been attributed to a depressive

condition considering some shared cognitive deficits of these disorders (e.g., retrieval in

memory and attention fluctuation). If these cognitive deficits occur together with some

depressive symptoms not meeting however MDE or DEIS diagnosis, prescription of an

antidepressant may be tempting.

Strengths and Limits of the Study

This study has benefited from several methodological strengths. First,

the study was conducted on a community-dwelling random sample, minimizing sample

selection bias. Furthermore, because of the large sample size, the weighting applied to each

participant, the absence of missing data related to the use of healthcare services and through

the use of objective data from medical records, our results are representative and

generalizable to the Quebec population of older people living in the community. These are

important advantages compared to previous studies which give our study a high external

validity. Internal validity is also interesting with respect to psychiatric diagnoses. These

were established on the basis of structured interviews adapted to older adults. Moreover, a

large range of potential confounders was taken into account including some that are not

always subject to investigation like anxiety, geographical accessibility of healthcare

services and the influence of the social network in many ways.

However, one should not that results can vary from one country to another. For

example, in Quebec, nearly all of those aged 65 and over are covered by the RAMQ (free

access to public services) (Government of Quebec, 2012), which could facilitate access for

20

poorer seniors compared to other health systems. Moreover, unlike the Quebec system,

some jurisdictions require that all residents are registered with a general practitioner (e.g.,

Denmark, France, Italy, Netherlands, United Kingdom) (Thomson, Osborn, Squires, & Jun,

2013). In other cases, direct access to medical specialists of his choice is possible without a

referral from a general practitioner (e.g., Germany, Greece, Spain, Switzerland) (van

Doorslaer, Masseria & Koolman, 2006). Finally, in some cultures, nontraditional care

services (e.g., oriental medicine) are most common, potentially reducing the influx to other

more traditional health services (Kim et al., 2011).

Despite its strengths, this study has some limitations. First, the MMSE was used to

measure cognitive functioning and cognitive decline. While the MMSE is widely used for

screening for cognitive impairment, it is not sensitive to subtle cognitive decline, especially

in highly educated and younger subjects (Nasreddine et al., 2005). This could have led to

an underestimation of the number of persons with cognitive decline in our sample. An

elaborate neuropsychological assessment would have been more precise to characterize

cognitive performance. At the same time, however, it is likely that participants identified as

CIND based on the MMSE had genuine cognitive deficits. We have also defined CIND

according to normative data from Quebec aged 65 and older stratified for age, education,

and sex, which is more precise than the traditional cut-off of 24. Second, the number of

participants was not sufficient to evaluate separately anxiety and depression effects which

can diverge from one another. Third, although longitudinal, the study design comprised

only two fixed assessment points in time. It was thus impossible to know whether

participants still in a state of cognitive decline on the last year of medical records data.

However, although individuals with CIND may improve their general cognition over time

(Petersen et al., 2001), the risk of transitioning to MCI or dementia again over the next

three to five years was five to six times higher compared to individuals with no history of

MCI in two studies (Koepsell & Monsell, 2012; Roberts et al., 2014). Fourth, participants

who dropped out had relatively lower MMSE scores compared to those who died and those

who remained in the sample (28.3, 28.6 and 29.0, respectively). However, since the raw

score difference between groups was very little, the impact on results may be modest. Fifth,

in the current study, we had access to 90% of the population of Quebec (subjects living far

from the main research center were excluded) and each administrative regions was well

21

represented in our sample. Nevertheless, we cannot rule out the hypothesis that people

living in excluded regions (10%) possibly use less certain healthcare services due to the

distance to reach the medical offices and hospitals. Sixth, one should note that these data

were collected in 2005. However, we think that the results are still up to date. For example,

general practitioners and emergency remain the gateway to access other health services and

benzodiazepines in Quebec are still too often prescribed over long periods of time for

seniors, even today (Lader, 2011; Trudel & Roy-Desruisseaux, 2014). Finally, although

many healthcare services have been studied, some relevant services were not documented

(e.g., memory clinics, private mental health services, and unprescribed drugs).

In summary, this study showed differential effects of current and incident CIND,

depression and anxiety on the healthcare utilization among elderly. Evaluations of cognitive

and psychological conditions at key moments in the trajectory of cares, preventable

hospitalizations and a greater role for non-pharmacological interventions are among the

challenges that the majority of health systems face in order to ensure better care for seniors.

Future studies using more elaborate neuropsychological assessment, longer follow-up with

objective data and that take into account the influence of services and caregivers support as

covariates are needed. An analytical study of the costs associated with the use of healthcare

services by people with CIND could also be useful to identify interventions on the health

system to achieve first.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research,

authorship, and/or publication of this article. This article is part of the first author’s

master’s thesis.

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Figures and Tables

Figure 1. Research design.

Abbreviations. RAMQ, Régie de l’assurance maladie du Québec (medical records); CIND, cognitive impairment no dementia.

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Abbreviations. MMSE, Mini-Mental State Examination; AChEI, acetylcholinesterase inhibitors;CIND, cognitive impairment no dementia.Note. Gray and white shapes represent exclusion and inclusion criteria, respectively

Figure 2. Flow chart of the study enrolment.

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Table 1. Characteristics of participants with and without cognitive impairment no dementia at baseline.

Characteristic at T1Cognitive status at T1 Cognitive status at T2

No CIND (T1) (n=2075)

Current CIND(n=190)

P-valuea

No CIND (T1-T2)(n=1559)

Incident CIND(n=91)

P-valuea

Age, mean (SD) 73.7 (6.0) 74.4 (6.7) .156 73.6 (6.0) 75.2 (5.9) .016 Female, n (%) 1177 (56.7) 127 (66.8) .007 894 (57.4) 47 (51.2) .286 Education, n (%) ≤ Primary 457 (22.0) 51 (27.0)

.155334 (21.4) 28 (30.8)

.108 Secondary 856 (41.2) 81 (42.5) 659 (42.3) 35 (38.0) Postsecondary 762 (36.7) 58 (30.5) 566 (36.3) 28 (31.2) Income < CAD $ 25 000, n (%) 789 (38.0) 102 (53.7) <.001 568 (36.4) 53 (58.7) <.001 Geographical area, n (%) Rural 803 (38.7) 89 (47.2)

<.001583 (37.4) 49 (54.3)

<.001 Urban 333 (16.0) 51 (26.7) 245 (15.7) 20 (22.0) Metropolitan 940 (45.3) 50 (26.1) 731 (46.9) 22 (23.7) MMSE, mean (SD) 28.8 (1.1) 25.0 (1.4) <.001 28.9 (1.1) 28.3 (1.2) <.001 Anxiety disorder, n (%) 53 (2.6) 12 (6.4)

.004b 39 (2.5) 5 (5.5).013b

UAD, n (%) 121 (5.8) 16 (8.2) 82 (5.3) 10 (11.1) MDE, n (%) 79 (3.8) 10 (5.2)

.092b50 (3.2) 6 (6.4)

.215b

DEIS, n (%) 133 (6.4) 19 (10.1) 100 (6.4) 5 (5.2) Chronic diseases, mean (SD) 3.2 (2.1) 3.1 (2.1) .305 3.2 (2.0) 3.7 (2.2) .014 Subjective health (poor or medium), n (%) 300 (14.4) 34 (17.7) .201 200 (12.8) 19 (21.2) .028

Living in a couple, n (%) 970 (46.7) 89 (46.8) .987 757 (48.6) 27 (29.5) <.001

Abbreviations. MMSE, Mini-Mental State Examination; UAD, unspecified anxiety disorder; MDE, major depressive episode; DEIS, depressive episode with insufficient symptoms; CIND, cognitive impairment no dementia; T1, initial evaluation; T2, follow-up evaluation.a P-value from t-tests or chi-square tests, bilateral. Weighted data. Bold corresponds to a significant result (corrected P-value < .010). b Anxiety and depression are two-level variables.Note. The left half represents the final sample at T1. The right half represents the final sample who took part in the baseline and follow-up evaluations (T1 and T2). To allow comparisons, each column shows characteristics of participants at baseline (T1).

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Table 2. Predictors of the number of visits to a general practitioner and to a geriatrician, a psychiatrist or a neurologist.One year before T1 Two years after T1

General practitioner d

< median (1-4) a ≥ median (5-25) a < median (1-9) a ≥ median (10-45) a

Independent variable Adjusted OR(99% CI)

P-value

Adjusted OR (99% CI)

P-value

Adjusted OR (99% CI)

P-value

Adjusted OR (99% CI)

P-value

Current CIND b 0.68 (0.37-1.25) .110 0.69 (0.36-1.30) .128 1.54 (0.47-5.05) .348 1.50 (0.45-5.02) .387Incident CIND c 0.84 (0.31-2.25) .642 1.15 (0.44-3.03) .710 1.13 (0.29-4.42) .822 1.14 (0.29-4.50) .810

Anxiety disorder b 0.90 (0.33-2.49) .797 0.67 (0.23-1.96) .333 0.81 (0.20-3.18) .684 1.03 (0.26-4.07) .957UAD b 1.01 (0.42-2.44) .969 1.12 (0.51-2.91) .565 0.66 (0.27-1.63) .235 0.84 (0.34-2.07) .617MDE b 0.40 (0.16-0.99) .009 0.51 (0.21-1.25) .052 0.67 (0.24-1.87) .318 0.98 (0.37-2.71) .965DEIS b 0.48 (0.23-0.97) .007 0.75 (0.37-1.50) .285 1.18 (0.35-3.94) .728 1.09 (0.32-3.70) .858

Geriatrician, psychiatrist, neurologist e

< median (1) a ≥ median (2-28) a < median (1) a ≥ median (2-31) a

Current CIND b 0.79 (0.22-2.92) .647 0.40 (0.06-2.64) .213 0.78 (0.23-2.66) .596 0.98 (0.25-3.80) .970Incident CIND c 1.17 (0.23-5.97) .803 0.51 (0.04-5.91) .475 2.02 (0.68-5.97) .096 1.96 (0.55-6.97) .170

Anxiety disorder b 0.76 (0.09-6.61) .744 0.22 (0.01-8.19) .277 2.22 (0.83-5.98) .038 1.58 (0.40-6.18) .391UAD b 1.51 (0.48-4.79) .359 1.53 (0.51-4.63) .321 0.71 (0.25-1.99) .389 1.38 (0.53-3.61) .391MDE b 0.90 (0.17-4.81) .866 2.41 (0.67-8.66) .078 2.39 (1.01-5.66) .009 1.47 (0.52-4.14) .334DEIS b 1.29 (0.39-4.31) .589 2.20 (0.72-6.77) .070 2.79 (1.17-6.64) .002 1.36 (0.40-4.61) .520

Abbreviations. CIND, cognitive impairment no dementia; UAD, unspecified anxiety disorder; MDE, major depressive episode; DEIS, depressive episode with insufficient symptoms; OR, odds ratio; CI, confidence interval.a Range based on the median number of visits. Category of reference: no use.b Estimated using multinomial logistic regressions with current CIND, anxiety and depression as predictors, adjusted for significant covariates (see Supplemental table online for all significant covariates; P-value < .10).c Estimated using multinomial logistic regressions with incident CIND, anxiety and depression as predictors, adjusted for significant covariates.d R2 (analyses with current CIND): before T1 = 0.18 and after T1 = 0.14 e R2 (analyses with current CIND): before T1 = 0.06 and after T1 = 0.05 R2 (analyses with incident CIND): before T1 = 0.19 and after T1 = 0.14 R2 (analyses with incident CIND): before T1 = 0.11 and after T1 = 0.06Note. Bold corresponds to a significant result (corrected P-value < .010).

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Table 3. Predictors of the number of emergency department visits.

Abbreviations. CIND, cognitive impairment no dementia; UAD, unspecified anxiety disorder; MDE, major depressive episode; DEIS, depressive episode with insufficient symptoms; OR, odds ratio; CI, confidence interval.a Category of reference: no use. b Estimated using multinomial logistic regressions with current CIND, anxiety and depression as predictors, adjusted for significant covariates (see Supplemental table online for all significant covariates; P-value < .10).c Estimated using multinomial logistic regressions with incident CIND, anxiety and depression as predictors, adjusted for significant covariates.Note. R2 (analyses with current CIND): before T1 = 0.11 and after T1 = 0.13 R2 (analyses with incident CIND): before T1 = 0.09 and after T1 = 0.13Note. Bold corresponds to a significant result (corrected P-value < .010).

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One year before T1 Two years after T1≥ 1 visit a ≥ 1 visit a

Independent variable Adjusted OR (99% CI) P-value Adjusted OR (99% CI) P-value

Current CIND b 0.59 (0.20-1.73) .209 1.01 (0.47-2.19) .969Incident CIND c 1.61 (0.58-4.43) .230 1.46 (0.67-3.18) .206

Anxiety disorder b 0.49 (0.09-2.73) .281 0.53 (0.18-1.57) .130UAD b 0.45 (0.13-1.53) .091 0.84 (0.44-1.59) .476MDE b 1.28 (0.37-4.42) .606 1.36 (0.70-2.65) .232DEIS b 2.49 (1.12-5.58) .003 1.05 (0.50-2.39) .862

Table 4. Predictors of hospital stays.One year before T1 Two years after T1

< median (1-2) a ≥ median (3-110) a < median (1-2) a ≥ median (3-98) a

Independent variable Adjusted OR(99% CI)c

P-value

Adjusted OR(99% CI)c

P-value

Adjusted OR (99% CI)c

P-value

Adjusted OR (99% CI)c

P-value

Current CIND b 0.79 (0.38-1.66) .420 0.72 (0.30-1.70) .322 0.86 (0.39-1.88) .624 1.45 (0.77-2.75) .131Incident CIND c 0.82 (0.28-2.40) .627 1.01 (0.38-2.70) .976 0.86 (0.31-2.34) .693 2.20 (1.11-4.36) .003

Anxiety disorder b 0.39 (0.08-1.86) .121 0.63 (0.15-2.66) .404 0.58 (0.22-1.54) .153 0.64 (0.25-1.60) .204UAD b 0.30 (0.09-0.98) .009 0.58 (0.22-1.59) .167 0.62 (0.32-1.23) .072 0.84 (0.47-1.50) .434MDE b 0.74 (0.22-2.46) .513 0.62 (0.16-2.41) .365 1.23 (0.62-2.44) .433 1.56 (0.85-2.86) .060DEIS b 1.93 (0.98-3.82) .013 1.69 (0.78-3.68) .080 1.24 (0.62-2.49) .432 0.96 (0.47-1.97) .886

Abbreviations. CIND, cognitive impairment no dementia; UAD, unspecified anxiety disorder; MDE, major depressive episode; DEIS, depressive episode with insufficient symptoms; OR, odds ratio; CI, confidence interval.a Range based on the median number of days. Category of reference: no use.b Estimated using multinomial logistic regressions with current CIND, anxiety and depression as predictors, adjusted for significant covariates (see Supplemental table online for all significant covariates; P-value < .10).c Estimated using multinomial logistic regressions with incident CIND, anxiety and depression as predictors, adjusted for significant covariates.Note. R2 (analyses with current CIND): before T1 = 0.07 and after T1 = 0.10 R2 (analyses with incident CIND): before T1 = 0.10 and after T1 = 0.12Note. Bold corresponds to a significant result (corrected P-value < .010).

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Table 5. Predictors of the number of dosing days of an anxiolytic/sedative/hypnotic and an antidepressant.One year before T1 Two years after T1

Anxiolytic/sedative/hypnotic d

< median (2-189) a ≥ median (193-365) a < median (2-180) a ≥ median (189-730) a

Independent variable Adjusted OR (99% CI)

P-value

Adjusted OR(99% CI)

P-value

Adjusted OR (99% CI)

P-value

Adjusted OR (99% CI)

P-value

Current CIND b 0.89 (0.48-1.64) .609 1.72 (1.03-2.88) .007 1.06 (0.52-2.15) .839 1.46 (0.80-2.66) .107Incident CIND c 1.20 (0.53-2.74) .564 0.90 (0.37-2.16) .746 1.33 (0.59-2.98) .372 1.17 (0.54-2.50) .605

Anxiety disorder b 1.53 (0.64-3.70) .210 1.35 (0.55-3.28) .386 2.62 (1.25-5.48) .001 1.28 (0.57-2.89) .431UAD b 1.97 (1.11-3.48) .002 1.02 (0.52-2.02) .940 1.63 (0.93-2.87) .025 1.60 (0.96-2.67) .018MDE b 2.91 (1.43-5.93) <.001 2.67 (1.27-5.62) .001 2.04 (1.10-3.79) .003 2.02 (1.16-3.54) .001DEIS b 1.38 (0.75-2.53) .171 1.46 (0.80-2.66) .103 1.84 (0.99-3.41) .011 0.96 (0.49-1.90) .878

Antidepressant e

< median (7-304) a ≥ median (304-365) a < median (10-383) a ≥ median (390-730) a

Current CIND b 1.05 (0.46-2.37) .883 0.96 (0.41-2.28) .911 1.17 (0.47-2.87) .662 0.97 (0.41-2.29) .921Incident CIND c 0.15 (0.01-2.11) .065 1.37 (0.52-3.64) .405 2.43 (1.00-5.96) .010 1.27 (0.49-3.29) .517

Anxiety disorder b 0.77 (0.21-2.85) .608 1.08 (0.30-3.95) .881 1.40 (0.52-3.75) .381 1.98 (0.85-4.58) .036UAD b 1.04 (0.43-2.49) .913 1.16 (0.47-2.86) .671 2.05 (1.07-3.93) .005 1.38 (0.70-2.70) .219MDE b 2.92 (1.21-7.04) .002 1.56 (0.56-4.36) .269 4.78 (2.47-9.36) <.001 2.51 (1.30-4.84) <.001DEIS b 4.56 (2.41-8.63) <.001 1.60 (0.69-3.68) .148 3.28 (1.57-6.82) <.001 1.22 (0.53-2.82) .545

Abbreviations. CIND, cognitive impairment no dementia; UAD, unspecified anxiety disorder; MDE, major depressive episode; DEIS, depressive episode with insufficient symptoms; OR, odds ratio; CI, confidence interval.a Range based on the median number of dosing days. Category of reference: no use.b Estimated using multinomial logistic regressions with current CIND, anxiety and depression as predictors, adjusted for significant covariates (see Supplemental table online for all significant covariates; P-value < .10).c Estimated using multinomial logistic regressions with incident CIND, anxiety and depression as predictors, adjusted for significant covariates.d R2 (analyses with current CIND): before T1 = 0.12 and after T1 = 0.15 e R2 (analyses with current CIND): before T1 = 0.08 and after T1 = 0.11 R2 (analyses with incident CIND): before T1 = 0.14 and after T1 = 0.15 R2 (analyses with incident CIND): before T1 = 0.09 and after T1 = 0.12Note. Bold corresponds to a significant result (corrected P-value < .010).

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