Advertisement

Uncontrolled Pain and Risk for Depression and Behavioral Symptoms in Residents With Dementia

      Abstract

      Objectives

      Limited cohort studies have assessed the association between uncontrolled pain and risk for behavioral and psychological symptoms of dementia (BPSDs). We conducted a longitudinal cohort study to examine whether associations exist between uncontrolled pain and risk for 2 common BPSDs—depression and behavioral symptoms—among long-term care (LTC) residents with Alzheimer disease and related dementia (ADRD).

      Design

      This retrospective cohort study analyzed quarterly data from the 5% Medicare sample linked to Minimum Data Set (MDS) 3.0 between January 1, 2011, and December 31, 2015.

      Setting and Participants

      LTC residents aged 50 years or older with ADRD who had chronic pain and at least 2 quarterly MDS 3.0 assessments.

      Methods

      LTC residents were followed up quarterly from first observed quarterly MDS 3.0 until first outcome event or last observed quarterly MDS 3.0. Uncontrolled pain was defined as numerical rating scale >4, verbal descriptor scale of moderate or severe pain, or ≥1 pain indicators on the Checklist of Nonverbal Pain Indicators. Depression was defined as ≥10 on the Patient Health Questionnaire 9; behavioral symptoms were defined as the presence of psychotic (delusions or hallucinations) or disruptive behaviors (rejection of care, or physical, verbal, or other aggressive behaviors). Generalized linear models (GLMs) with marginal structural modeling (MSM) stabilized weights were used to examine uncontrolled pain and outcome risk.

      Results

      The incidence rate of depression and behavioral symptoms during follow-up was 9.4 and 23.1 per 100 resident-years, respectively. Results from the MSM-GLMs showed that LTC residents with uncontrolled pain had a higher risk than those with controlled pain for developing depression [hazard ratio 1.67, 95% confidence interval (CI) 1.54–1.81] and behavioral symptoms (hazard ratio 1.28, 95% CI 1.19–1.37).

      Conclusions and Implications

      Uncontrolled pain was associated with elevated risk for depressive and behavioral symptoms in dementia, underscoring the importance of pain assessment and control among LTC residents with ADRD.

      Keywords

      Behavioral and psychological symptoms of dementia (BPSDs) affect 97% of people with Alzheimer disease and related dementia (ADRD)
      • Malara A.
      • De Biase G.A.
      • Bettarini F.
      • et al.
      Pain assessment in elderly with behavioral and psychological symptoms of dementia.
      at some point in time during the disease course and is one of the main reasons for nursing home admission.
      • Gaugler J.E.
      • Yu F.
      • Krichbaum K.
      • et al.
      Predictors of nursing home admission for persons with dementia.
      Common behavioral symptoms of dementia include agitation and aggression, and psychological symptoms include depression and anxiety.
      • Lyketsos C.G.
      • Lopez O.
      • Jones B.
      • et al.
      Prevalence of neuropsychiatric symptoms in dementia and mild cognitive impairment: results from the cardiovascular health study.
      ,
      • Kales H.C.
      • Gitlin L.N.
      • Lyketsos C.G.
      Assessment and management of behavioral and psychological symptoms of dementia.
      BPSD adversely affects individuals’ quality of life and physical and cognitive functioning and increases caregiver distress.
      • Kales H.C.
      • Gitlin L.N.
      • Lyketsos C.G.
      Assessment and management of behavioral and psychological symptoms of dementia.
      Treatment of BPSD remains challenging, largely owing to the lack of effective targeted therapies and concerns about the safety of psychopharmacological medications.
      • Kales H.C.
      • Gitlin L.N.
      • Lyketsos C.G.
      Assessment and management of behavioral and psychological symptoms of dementia.
      Current clinical guidelines highly recommend identifying risk factors that precipitate BPSD before initiation of any suggested pharmacological treatment.
      • Kales H.C.
      • Gitlin L.N.
      • Lyketsos C.G.
      • et al.
      Management of neuropsychiatric symptoms of dementia in clinical settings: recommendations from a multidisciplinary expert panel.
      ,
      • Livingston G.
      • Sommerlad A.
      • Orgeta V.
      • et al.
      Dementia prevention, intervention, and care.
      Although pain has been implicated as an important risk factor for BPSD,
      • Kales H.C.
      • Gitlin L.N.
      • Lyketsos C.G.
      • et al.
      Management of neuropsychiatric symptoms of dementia in clinical settings: recommendations from a multidisciplinary expert panel.
      ,
      • Livingston G.
      • Sommerlad A.
      • Orgeta V.
      • et al.
      Dementia prevention, intervention, and care.
      the magnitude of risk conferred by uncontrolled pain remains unclear. Available effect estimates have been inferred from cross-sectional studies that show a higher prevalence of depression, agitated and aggressive behaviors, and rejection of care among individuals with ADRD with versus without pain.
      • Hodgson N.
      • Gitlin L.N.
      • Winter L.
      • et al.
      Caregiver's perceptions of the relationship of pain to behavioral and psychiatric symptoms in older community-residing adults with dementia.
      • Tosato M.
      • Lukas A.
      • van der Roest H.G.
      • et al.
      Association of pain with behavioral and psychiatric symptoms among nursing home residents with cognitive impairment: results from the SHELTER study.
      • Ishii S.
      • Streim J.E.
      • Saliba D.
      A conceptual framework for rejection of care behaviors: review of literature and analysis of role of dementia severity.
      • Ahn H.
      • Horgas A.
      The relationship between pain and disruptive behaviors in nursing home residents with dementia.
      To date, limited cohort studies have assessed the association between uncontrolled pain and risk for BPSD,
      • Kunik M.E.
      • Snow A.L.
      • Davila J.A.
      • et al.
      Causes of aggressive behavior in patients with dementia.
      • Sampson E.L.
      • White N.
      • Lord K.
      • et al.
      Pain, agitation, and behavioural problems in people with dementia admitted to general hospital wards: a longitudinal cohort study.
      • Volicer L.
      • Frijters D.H.
      • Van der Steen J.T.
      Relationship between symptoms of depression and agitation in nursing home residents with dementia.
      • Erdal A.
      • Flo E.
      • Selbaek G.
      • et al.
      Associations between pain and depression in nursing home patients at different stages of dementia.
      and findings regarding pain control and risk for aggression and agitation are inconsistent.
      • Kunik M.E.
      • Snow A.L.
      • Davila J.A.
      • et al.
      Causes of aggressive behavior in patients with dementia.
      • Sampson E.L.
      • White N.
      • Lord K.
      • et al.
      Pain, agitation, and behavioural problems in people with dementia admitted to general hospital wards: a longitudinal cohort study.
      • Volicer L.
      • Frijters D.H.
      • Van der Steen J.T.
      Relationship between symptoms of depression and agitation in nursing home residents with dementia.
      These inconsistencies may be due to small sample sizes, outdated data, and most importantly, failure to account for the time-varying feature of pain and confounders (eg, use of pain medications), which can result in biased estimations of pain control on BPSD outcomes.
      • Mansournia M.A.
      • Etminan M.
      • Danaei G.
      • et al.
      Handling time varying confounding in observational research.
      Owing to serious adverse consequences of BPSD in persons with ADRD,
      • Kales H.C.
      • Gitlin L.N.
      • Lyketsos C.G.
      Assessment and management of behavioral and psychological symptoms of dementia.
      the association between pain and BPSD deserves further investigation through a longitudinal cohort study design that addresses the aforementioned study limitations. Using a marginal structural modeling (MSM) approach
      • Mansournia M.A.
      • Etminan M.
      • Danaei G.
      • et al.
      Handling time varying confounding in observational research.
      to account for time-varying pain control exposure and time-varying confounders, the present study examined the associations between uncontrolled pain and risk of 2 common BPSDs, depression and behavioral symptoms, among long-term care (LTC) residents with ADRD. We hypothesized that residents with (versus without) uncontrolled pain had a higher risk of developing depressive and behavioral symptoms in dementia.

      Methods

       Study Design and Data Source

      We conducted a retrospective cohort study of a 5% Medicare sample linked to the Minimum Data Set, version 3.0 (MDS 3.0), from 2011 to 2015. The Medicare data contain enrollees’ medical billing records for Parts A (inpatient), B (outpatient), and D (prescription drugs), as well as beneficiary-level sociodemographic characteristics and enrollment status. The MDS 3.0 is the latest version of a federal clinical assessment required for all residents of nursing homes certified by the Centers For Medicare and Medicaid Services (CMS).
      • Rahman A.N.
      • Applebaum R.A.
      The nursing home Minimum Data Set assessment instrument: manifest functions and unintended consequences--past, present, and future.
      We leveraged the MDS 3.0 data to measure a key exposure (pain intensity) and 2 BPSD outcomes while accounting for important medication-related confounders, including the use of prescription pain medications, the use of psychotropic medications, and polypharmacy, all of which were ascertained from the Medicare Part D data. An institutional review board approved the study and waived informed patient consent.

       Study Sample

      The study sample included LTC residents aged 50 years or older who (1) entered a cohort on the date of their first observed quarterly MDS 3.0 pain assessment (ie, index date), with at least 6 months of continuous Medicare enrollment before that date; and (2) were diagnosed with ADRD and not comatose
      The Centers for Medicare & Medicaid Services (CMS)
      Chronic Conditions Data Warehouse 2020.
      before the index date between January 1, 2011, and December 31, 2015. To study a homogeneous population regarding pain conditions, we further restricted the sample to those with a diagnosis of chronic pain but without cancer, or palliative or hospice care during the 6-month pre-index period (baseline). Supplementary Table 1 lists the diagnoses of diseases and service care considered in sample selection.
      We created 2 independent cohorts to detect the risk of depression and behavioral symptoms outcomes. For each cohort, we included only residents who had no clinically diagnosed or MDS-assessed outcome of interest during the 6-month baseline or on the index date. Residents were followed up from the index date until the first outcome event or the last observed quarterly MDS 3.0 before death, nursing home discharge, Medicare Part D disenrollment, or study end, whichever came first. We excluded residents who had no quarterly MDS 3.0 assessment during follow-up for outcome ascertainment. Figure 1 shows the procedures of sample selection for each cohort.
      Figure thumbnail gr1
      Fig. 1Flow chart of the retrospective cohort study samples for depression and for behavioral symptom outcomes.

       Outcome Measures

      Outcomes included the presence of depression and the presence of behavioral symptoms (including psychotic and disruptive behaviors) extracted from the MDS 3.0 data. In the MDS 3.0, depression was measured by residents’ self-assessment of mood status in the previous 2 weeks using the Patient Health Questionnaire (PHQ)-9, a validated tool to detect major depressive disorder with high sensitivity and specificity (both >85%).
      • Levis B.
      • Benedetti A.
      • Thombs B.D.
      • et al.
      Accuracy of Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression: individual participant data meta-analysis.
      ,
      • Kroenke K.
      • Spitzer R.L.
      • Williams J.B.
      The PHQ-9: validity of a brief depression severity measure.
      The depression status of residents who were nonverbal was measured by a staff-assessed PHQ-9. Each of the PHQ-9 items scored symptoms from 0 (not at all) to 3 (nearly every day), resulting in a total score ranging from 0 to 27. Residents whose PHQ-9 score was ≥10 were classified as having moderate-to-severe depression; otherwise, they were classified as having no or mild depression.
      • Levis B.
      • Benedetti A.
      • Thombs B.D.
      • et al.
      Accuracy of Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression: individual participant data meta-analysis.
      ,
      • Kroenke K.
      • Spitzer R.L.
      • Williams J.B.
      The PHQ-9: validity of a brief depression severity measure.
      In the MDS 3.0, nursing staff assessed the presence of 2 common behavioral symptoms during the previous 7 days, including (1) psychotic behaviors (ie, delusions and hallucinations) and (2) disruptive behaviors, including physical or behavioral symptoms directed toward others, verbal behavioral symptoms directed toward others, other behavioral symptoms not directed toward others, and rejection of care.
      • Gruber-Baldini A.L.
      • Boustani M.
      • Sloane P.D.
      • et al.
      Behavioral symptoms in residential care/assisted living facilities: prevalence, risk factors, and medication management.
      ,
      • Galik E.
      • Resnick B.
      • Vigne E.
      • et al.
      Reliability and validity of the resistiveness to care scale among cognitively impaired older adults.
      Wandering was not included because this behavior is not commonly displayed among residents with pain.
      • Ahn H.
      • Horgas A.
      The relationship between pain and disruptive behaviors in nursing home residents with dementia.
      Residents were only considered to have a behavioral symptom if they exhibited any of the 5 behaviors.
      Both the MDS 3.0–assessed depression and behavioral items have been psychometrically tested in residents who are verbal and nonverbal and have shown excellent nurse-to-nurse interrater reliability (kappa >0.90).
      • Saliba D.
      • Buchanan J.
      Rand Corporation Health: Development & validation of a revised nursing home assessment tool: MDS 3.0 health.
      We relied on MDS 3.0 assessments rather than on diagnostic codes for the ascertainment of depression and behavioral symptoms during follow-up because these symptoms are often delayed or underdiagnosed in older adults.
      • Allan C.E.
      • Valkanova V.
      • Ebmeier K.P.
      Depression in older people is underdiagnosed.

       Pain Control

      Pain intensity was extracted from quarterly MDS 3.0 assessments.
      • Saliba D.
      • Buchanan J.
      Making the investment count: Revision of the Minimum Data Set for nursing homes, MDS 3.0.
      At each assessment, residents were asked to rate their worst pain intensity in the previous 5 days using a numeric rating scale (NRS; from 0 to 10) or verbal descriptor scale (VDS; no, mild, moderate, or severe) for residents who were verbal. For nonverbal residents, nurses evaluated their pain intensity using the Checklist of Nonverbal Pain Indicators (CNPI) to assess the presence (1) or absence (0) of 4 pain behaviors (ie, nonverbal sounds, vocal complaints of pain, facial expressions, and body postures) in the previous 5 days. Residents were classified as having uncontrolled pain if they had an NRS of >4, a VDS indicating moderate or severe pain, or ≥1 pain indicators in the CNPI; otherwise, they were considered to have controlled pain. Missing pain value data during baseline or cohort entry were low (<1%; n = 652 residents), and these residents were excluded.

       Statistical Analysis

      We measured pain control, outcomes of depression and behavioral symptoms, and confounders (Supplementary Method 1) at baseline and updated at each quarterly MDS 3.0 assessment during follow-up. Thus, resident assessment was the unit of analysis. Because we censored dichotomized depression and behavioral symptoms at quarterly intervals, to model interval-censored outcomes, we used a generalized linear model (GLM) with a complementary log-log link function to examine the association of prior uncontrolled pain (exposure) with the subsequent risk of the outcome of interest.
      • Farrington C.P.
      Interval censored survival data: A generalized linear modelling approach.
      To account for time-varying pain control and confounders, we used an MSM approach.
      • Robins J.M.
      • Hernan M.A.
      • Brumback B.
      Marginal structural models and causal inference in epidemiology.
      Unlike conventional covariate adjustments, MSMs adjust for time-varying confounders by assigning weights to individuals, and thus create a pseudo sample in which all observed potential confounders are equally distributed between the pain-controlled and pain-uncontrolled groups, yielding results that approximate causal relationships.
      • Robins J.M.
      • Hernan M.A.
      • Brumback B.
      Marginal structural models and causal inference in epidemiology.
      ,
      • Williamson T.
      • Ravani P.
      Marginal structural models in clinical research: When and how to use them?.
      The use of an MSM involves 2 steps: (1) calculating a stabilized weight by multiplying the inverse probability of treatment (or exposure) weights (IPTWs) and inverse probability of censoring weights (IPCWs) of each resident assessment; and (2) incorporating the calculated stabilized weights into the GLMs to estimate the weighted associations between uncontrolled pain with outcomes of interests.
      • Cole S.R.
      • Hernan M.A.
      Constructing inverse probability weights for marginal structural models.
      To estimate IPTWs and IPCWs, we fit 2 separate pooled multivariable logistic regression models, with uncontrolled pain and censoring (due to death or Medicare Part D disenrollment) as the dependent variable, respectively, and the time-fixed and time-varying variables as the independent variables. Weights were truncated at the 1st and 99th percentiles to reduce the influence of outliers on estimates. In the second step, we reported hazard ratios (HRs) and 95% confidence intervals (CIs) derived from the MSM-weighted GLM for each outcome. Generalized estimating equations were included in the final weighted models to account for within-resident correlations from quarterly repeated measures of pain control.
      • Zeger S.L.
      • Liang K.Y.
      Longitudinal data analysis for discrete and continuous outcomes.
      To evaluate the robustness of our findings, we conducted several subgroup and sensitivity analyses. For sensitivity analyses, we compared estimates from MSM-GLMs with those from conventional unweighted models that adjusted for baseline covariates as well as with estimates from GLMs with IPTW. We also truncated weights at the 0.5th and 99.5th percentiles and at the 2nd and 98th percentiles as a sensitivity analysis.
      • Cole S.R.
      • Hernan M.A.
      Constructing inverse probability weights for marginal structural models.
      To test the positivity assumption (ie, any individual has a positive, nonzero probability of experiencing exposure at any given combination of covariates), we examined the distribution of propensity scores by baseline pain control. In subgroup analysis, we stratified the MSM-GLM analysis by dementia severity, use of prescription pain medications, and use of pain management, including pharmacological and nonpharmacological approaches at baseline to explore their potential effect modification. Nonpharmacological pain management approaches documented in MDS 3.0 included but were not limited to comfort therapy (eg, heat/cold application), physical therapy (eg, exercises), neurostimulation (eg, electrical nerve stimulation), and alternative therapy (massage, acupuncture, and chiropractic).
      The Centers for Medicare & Medicaid Services (CMS)
      Long-Term Care Facility Resident Assessment Instrument 3.0 User’s Manual, Version 1.17.1 2019.
      We chose these 3 effect modifiers because prior studies have reported that the association between pain and BPSD differed according to use of pain interventions
      • Husebo B.S.
      • Ballard C.
      • Sandvik R.
      • et al.
      Efficacy of treating pain to reduce behavioural disturbances in residents of nursing homes with dementia: Cluster randomised clinical trial.
      ,
      • Husebo B.S.
      • Ballard C.
      • Fritze F.
      • et al.
      Efficacy of pain treatment on mood syndrome in patients with dementia: A randomized clinical trial.
      and severity of cognitive impairment.
      • Hodgson N.
      • Gitlin L.N.
      • Winter L.
      • et al.
      Caregiver's perceptions of the relationship of pain to behavioral and psychiatric symptoms in older community-residing adults with dementia.
      ,
      • Erdal A.
      • Flo E.
      • Selbaek G.
      • et al.
      Associations between pain and depression in nursing home patients at different stages of dementia.
      All analyses were performed using SAS, version 9.4 (SAS Institute Inc, Cary, NC). Statistical significance was set at P < .05, and all tests were 2-sided.

      Results

      We identified a cohort of 27,131 eligible LTC residents with ADRD who had no depression outcome (contributing 221,237 resident MDS assessments) and a cohort of 15,657 LTC residents with ADRD who had no behavioral symptoms outcome (contributing 113,534 resident MDS assessments), 6 months before or at cohort entry (Figure 1). Baseline summary statistics for the cohort of depression and behavioral sample are presented in Supplementary Table 2. The mean (SD) length of follow-up was 1.6 (1.3) years [median, 1.2 years; interquartile range (IQR), 0.5–2.4 years] for the depression cohort and 1.4 (1.2) years (median, 1.2 years; IQR, 0.5–2.1 years) for the behavioral cohort. During the follow-up period, 8.9% of residents in the depression cohort and 6.5% in the behavioral cohort died and were censored at the time of death.
      Table 1 gives the characteristics of LTC residents with or without pain control before or at cohort entry in the depression and behavioral cohorts. At baseline, 15.1% (4087 of 27,131) of residents with ADRD in the depression cohort and 20.4% (3192 of 15,657) of residents in the behavioral cohort experienced uncontrolled pain. In both cohorts, residents whose pain was uncontrolled (vs controlled) were more likely to be younger (50–64 years old), female, white, and have 5 or more comorbidities, but were less likely to have moderate or severe dementia. The residents with uncontrolled pain were also more likely to receive prescription pain medications, use pharmacological or nonpharmacological pain interventions, and experience any hospitalization and emergency department visit at baseline.
      Table 1Baseline
      Baseline was defined as 6 months before the index MDS 3.0 assessment.
      Demographic and Clinical Characteristics of Long-term Care Residents With or Without Pain Control
      Uncontrolled pain was defined based on pain assessment of the index MDS 3.0.
      in the Depression and Behavioral Symptoms Cohorts
      Baseline Characteristic
      Baseline was defined as 6 months before the index MDS 3.0 assessment.
      Depression Cohort (n = 27,131)Behavioral Symptoms Cohort (n = 15,657)
      Residents With Uncontrolled Pain, %
      Baseline was defined as 6 months before the index MDS 3.0 assessment.
      Residents With Controlled Pain, %
      Baseline was defined as 6 months before the index MDS 3.0 assessment.
      Adjusted OR

      (95% CI)
      P ValueResidents With Uncontrolled Pain, %
      Baseline was defined as 6 months before the index MDS 3.0 assessment.
      Residents With Controlled Pain, %
      Baseline was defined as 6 months before the index MDS 3.0 assessment.
      Adjusted OR

      (95% CI)
      P Value
      Total, no.408723,044319212,465
      Age group, y
       50–646.05.2Reference8.26.2Reference
       65–7412.410.20.91 (0.75–1.11).3414.911.50.92 (0.74–1.13).42
       75–8428.024.80.86 (0.72–1.03).1028.424.30.84 (0.70–1.03).09
       ≥8553.759.70.72 (0.60–0.86)<.00148.458.00.71 (0.59–0.86)<.001
      Sex
       Male20.626.5Reference19.124.2Reference
       Female79.473.51.23 (1.12–1.37)<.00180.975.81.24 (1.10–1.40)<.001
      Race/ethnicity
       White82.275.4Reference84.577.8Reference
       Black12.016.00.75 (0.66–0.84)<.0019.613.40.74 (0.64–0.87)<.001
       Other
      Included Hispanic, Asian, Pacific Islander, and Native American individuals.
      5.88.60.77 (0.65–0.90).0025.98.80.76 (0.63–0.93).006
      Region of United States
       Northeast17.624.0Reference17.022.8Reference
       Northcentral30.725.61.27 (1.13–1.42)<.00130.826.01.30 (1.13–1.50)<.001
       West11.611.01.41 (1.22–1.63)<.00111.611.21.41 (1.18–1.67)<.001
       South40.139.41.28 (1.14–1.42)<.00140.640.01.26 (1.10–1.43)<.001
      Receipt of low-income subsidy
       No18.516.8Reference16.516.2Reference
       Yes81.583.20.88 (0.79–0.97).0183.583.80.94 (0.83–1.07).37
      Body mass index
       Normal34.741.0Reference31.337.1Reference
       Underweight8.48.61.02 (0.88–1.18).776.07.60.86 (0.71–1.04).13
       Overweight27.728.81.05 (0.96–1.16).2626.428.81.06 (0.94–1.19).34
       Obese29.221.721.09 (0.99–1.21).0936.426.51.13 (1.00–1.27).04
      Pain reporting
       Staff-observed8.516.1Reference3.511.8Reference
       Self-reported91.583.91.01 (0.87–1.18).8996.588.21.44 (1.12–1.85).005
      ADL dependence
       No28.425.6Reference33.228.8Reference
       Mild32.632.50.92 (0.83–1.01).0933.532.90.87 (0.78–0.98).02
       Moderate26.626.70.98 (0.88–1.10).7524.425.80.86 (0.76–0.98).02
       Severe12.415.21.00 (0.87–1.15).999.012.50.90 (0.75–1.08).27
      Comorbidity
       0–221.629.6Reference17.224.9Reference
       3–434.436.51.10 (0.99–1.21).0933.036.91.01 (0.89–1.15).88
       5–625.221.71.18 (1.05–1.31).00628.823.91.13 (0.99–1.31).07
       ≥718.912.21.30 (1.15–1.48)<.00121.012.31.14 (0.98–1.34).09
      Dementia severity
       Mild67.741.0Reference82.757.1Reference
       Moderate26.344.80.50 (0.45–0.54)<.00114.932.80.55 (0.49–0.62)<.001
       Severe6.014.30.43 (0.36–0.52)<.0012.410.10.47 (0.35–0.64)<.001
      Pain management (yes vs no as reference)
       Receipt of prescription pain medication78.846.41.94 (1.76–2.13)<.00183.852.51.87 (1.65–2.11)<.001
       Use of PRN pain medication76.423.44.98 (4.52–5.49)<.00178.026.64.70 (4.19–5.26)<.001
       Use of scheduled pain medication61.435.61.47 (1.34–1.62)<.00167.639.81.69 (1.51–1.89)<.001
       Use of pain management94.951.53.55 (2.97–4.24)<.00196.456.33.73 (2.96–4.70)<.001
      Use of psychotropic medication62.058.20.93 (0.86–1.02).1171.261.30.96 (0.86–1.07).42
      Polypharmacy91.784.30.97 (0.84–1.12).7093.686.20.97 (0.80–1.17).75
      Healthcare utilization
       Any hospitalization43.334.41.19 (1.06–1.33).00339.324.51.43 (1.24–1.65)<.001
       Any ED visit55.744.81.34 (1.20–1.50)<.00149.633.01.36 (1.19–1.65)<.001
      Depression (PHQ-9 ≥10)N/AN/AN/AN/A9.45.51.56 (1.31–1.84)<.001
      Behavioral symptoms23.827.40.98 (0.90–1.08).74N/AN/AN/AN/A
      ADL, activities of daily living; ED, emergency department; N/A, not available; PRN, pro re nata.
      Baseline was defined as 6 months before the index MDS 3.0 assessment.
      Uncontrolled pain was defined based on pain assessment of the index MDS 3.0.
      Included Hispanic, Asian, Pacific Islander, and Native American individuals.
      Table 2 gives the unadjusted incidence estimate of depression and behavioral symptoms among eligible LTC residents with ADRD. The overall incidence rate of depression symptoms and of behavioral symptoms during follow-up was 9.4 and 23.1 per 100 resident-years, respectively. The rates were higher among residents with rather than without uncontrolled pain (12.2 vs 8.9 per 100 resident-years for risk of depression; 25.9 vs. 22.4 per 100 resident-years for risk of behavioral symptoms).
      Table 2Unadjusted Absolute Rate of Depression and Behavioral Symptoms Among Long-term Care Residents With ADRD, Overall, and by Status of Pain Control at Baseline
      VariableDepression CohortBehavioral Symptoms Cohort
      No. of ResidentsNo. of EventsResident-yearsIncidence Rate per 100 Resident-yearsFollow-up, Mean ± SD; Median (IQR), yearsNo. of ResidentsNo. of EventsResident-yearsIncidence Rate per 100 Resident-yearsFollow-up, Mean ± SD; Median (IQR), years
      Overall27,131418744,4549.41.64 ± 1.28; 1.25 (0.54–2.45)15,657522022,56523.11.24 ± 1.20; 1.10 (0.49–2.06)
      Pain status
       Uncontrolled4087793650212.21.59 ± 1.28; 1.23 (0.50–2.42)31921204464325.91.45 ± 1.22; 1.10 (0.48–2.14)
       Controlled23,0443394379528.91.64 ± 1.28; 1.25 (0.57–2.46)12,465401617,92222.41.44 ± 1.20; 1.11 (0.49–2.04)
      Table 3 gives the associations between uncontrolled pain and risk for depression and behavioral symptoms. The crude estimate without confounding adjustment (conventional model) indicated that uncontrolled pain was associated with 35% increased risk for depression (95% CI 1.25–1.46) and 22% increased risk for behavioral symptoms (95% CI 1.14–1.30). Compared with the crude estimates, both conventional baseline adjustment and IPTW models yielded lower effect estimates for depression (HR 1.30; 95% CI 1.18–1.42 and HR 1.25; 95% CI 1.17–1.43) and for behavioral symptoms (HR 1.17; 95% CI 1.09–1.27 and HR 1.20; 95% CI 1.14–1.27). The weighted MSM that accounted for time-varying confounders yielded the largest estimate, with a 67% increased risk for depression (95% CI 1.54–1.81) and 28% for behavioral symptoms (95% CI 1.19–1.37).
      Table 3Adjusted Associations Between Uncontrolled Pain and Risk of Depression and Behavioral Symptoms Among Long-term Care Residents With ADRD
      AnalysisRisk for DepressionRisk for Behavioral Symptoms
      HR (95% CI)P ValueHR (95% CI)P Value
      Main analysis
       Conventional models
      Without adjustment1.35 (1.25–1.46)<.0011.22 (1.14–1.30)<.001
      Adjusted for baseline variables1.30 (1.18–1.42)<.0011.17 (1.09–1.27)<.001
       Weighted models
      IPTW1.25 (1.17–1.43)<.0011.20 (1.14–1.27)<.001
      MSM estimates1.67 (1.54–1.81)<.0011.28 (1.19–1.37)<.001
      Subgroup analysisP value for interactionP value for interaction
      Dementia severity
       Mild1.71 (1.53–1.90).401.31 (1.21–143).21
       Moderate1.91 (1.67–2.21)1.36 (1.16–1.60)
       Severe1.42 (1.03–1.95)1.53 (0.97–2.40)
      Use of prescription pain medication
       Yes1.56 (1.41–1.72).031.26 (1.16–1.37).30
       No1.90 (1.64–2.12)1.38 (1.18–1.62)
      Use of pain management
       Yes1.54 (1.40–1.69).021.20 (1.11–1.30)<.001
       No1.98 (1.65–2.37)1.76 (1.48–2.10)

       Subgroup and Sensitivity Analyses

      Uncontrolled pain had statistically significant and large effects on depression or behavioral symptom outcomes for LTC residents with ADRD who had no baseline use of any prescription pain medications (vs use; P value for interaction = .03 for depression only) and who had no baseline use of any pain management (vs use; P = .02 for depression and P < .001 for behavioral symptoms) (Table 3). We did not observe a statistically significant modification effect of dementia severity on the association between pain control and risk for depression (P = .40) and behavioral symptoms (P = .21). Sensitivity analyses that truncated weights at different percentiles did not alter our findings (Supplementary Table 3). We did not find evidence of violation of the positivity assumption (Supplementary Figure 1).

      Discussion

      The present study using MDS 3.0 assessments linked to Medicare claims data is among the first to provide population-based data on pain control and risk for depression and behavioral symptoms among LTC residents with ADRD. Using an MSM approach to account for time-varying confounders, we found that uncontrolled pain increased the risk of developing depression by 1.67-fold and of developing behavioral symptoms by 1.28-fold. The direction of association was generally consistent across different models, with smaller magnitudes found in conventional adjusted and IPTW models compared with weighted MSMs. Findings were also consistent across sensitivity and subgroup analyses.
      Associations between pain and depression and behavioral symptoms are well documented among older adults with intact cognition,
      • IsHak W.W.
      • Wen R.Y.
      • Naghdechi L.
      • et al.
      Pain and depression: A systematic review.
      but less well documented among those with cognitive impairment. Limited longitudinal cohort studies have assessed the association between uncontrolled pain and risk for BPSD.
      • Kunik M.E.
      • Snow A.L.
      • Davila J.A.
      • et al.
      Causes of aggressive behavior in patients with dementia.
      • Sampson E.L.
      • White N.
      • Lord K.
      • et al.
      Pain, agitation, and behavioural problems in people with dementia admitted to general hospital wards: a longitudinal cohort study.
      • Volicer L.
      • Frijters D.H.
      • Van der Steen J.T.
      Relationship between symptoms of depression and agitation in nursing home residents with dementia.
      • Erdal A.
      • Flo E.
      • Selbaek G.
      • et al.
      Associations between pain and depression in nursing home patients at different stages of dementia.
      Prior findings have been consistent regarding pain and risk of depression,
      • Kunik M.E.
      • Snow A.L.
      • Davila J.A.
      • et al.
      Causes of aggressive behavior in patients with dementia.
      • Sampson E.L.
      • White N.
      • Lord K.
      • et al.
      Pain, agitation, and behavioural problems in people with dementia admitted to general hospital wards: a longitudinal cohort study.
      • Volicer L.
      • Frijters D.H.
      • Van der Steen J.T.
      Relationship between symptoms of depression and agitation in nursing home residents with dementia.
      but inconsistent regarding pain and risk of aggression and agitation, with 2 studies showing a positive association,
      • Kunik M.E.
      • Snow A.L.
      • Davila J.A.
      • et al.
      Causes of aggressive behavior in patients with dementia.
      ,
      • Sampson E.L.
      • White N.
      • Lord K.
      • et al.
      Pain, agitation, and behavioural problems in people with dementia admitted to general hospital wards: a longitudinal cohort study.
      whereas another study indicating no association.
      • Volicer L.
      • Frijters D.H.
      • Van der Steen J.T.
      Relationship between symptoms of depression and agitation in nursing home residents with dementia.
      Our study using the most recent version of MDS data in a large sample of LTC residents found positive associations between poor pain control and depression or behavioral symptoms for residents with ADRD after accounting for time-varying pain control and time-varying variables that could act as confounders and intermediate variables simultaneously.
      The present study also explored the effect modification of the association between uncontrolled pain and depression or behavioral symptoms by dementia severity and by use of pain treatment and management at baseline. We observed statistically significant and stronger associations for subgroups of LTC residents with ADRD who had no prescription pain treatment or no pain management at baseline, compared with their counterparts who had intervention(s). Our finding is analogous to results from published randomized clinical trials showing that pain treatment (vs no treatment) is associated with decreased pain and subsequent risk for agitation in patients with moderate-to-severe dementia.
      • Husebo B.S.
      • Ballard C.
      • Sandvik R.
      • et al.
      Efficacy of treating pain to reduce behavioural disturbances in residents of nursing homes with dementia: Cluster randomised clinical trial.
      ,
      • Husebo B.S.
      • Ballard C.
      • Fritze F.
      • et al.
      Efficacy of pain treatment on mood syndrome in patients with dementia: A randomized clinical trial.
      We did not find evidence of an effect modification by dementia severity. Our null finding is consistent with the result of a prior study of residents with dementia,
      • Erdal A.
      • Flo E.
      • Selbaek G.
      • et al.
      Associations between pain and depression in nursing home patients at different stages of dementia.
      but inconsistent with that of a study of community-dwelling persons with dementia whose pain was primarily assessed by their caregivers.
      • Hodgson N.
      • Gitlin L.N.
      • Winter L.
      • et al.
      Caregiver's perceptions of the relationship of pain to behavioral and psychiatric symptoms in older community-residing adults with dementia.
      Our findings reemphasized the importance of pain assessment in LTC residents with ADRD for early detection and intervention of BPSD given the lack of effective treatment and potential harms of psychotropic medications for BPSD. For individuals with ADRD who reside in LTC facilities, the MDS 3.0 could serve as a useful data source because it regularly assesses and documents the pain status of residents, most of whom are diagnosed as having ADRD. Our incidence estimate of depression ascertained from the MDS 3.0 is consistent with prior data.
      • Payne J.L.
      • Sheppard J.M.
      • Steinberg M.
      • et al.
      Incidence, prevalence, and outcomes of depression in residents of a long-term care facility with dementia.
      Overall, our findings may assist health care professionals in distinguishing LTC residents with ADRD who have a higher predisposition to depression or behavioral symptoms. It is particularly important to focus on residents with ADRD who are younger, female, white, and have multiple comorbidities, all of which are important risk factors associated with uncontrolled pain demonstrated in the present study.
      A strength of our study is that we adjusted for time-varying pain control and time-varying confounders using an MSM approach. Causality may be inferred when the MSM assumptions of positivity, consistency, exchangeability, and correctness of model specifications are fulfilled.
      • Cole S.R.
      • Hernan M.A.
      Constructing inverse probability weights for marginal structural models.
      ,
      • Platt R.W.
      • Delaney J.A.
      • Suissa S.
      The positivity assumption and marginal structural models: The example of warfarin use and risk of bleeding.
      In our study, the positivity assumption was satisfied, as the probability of any resident experiencing the exposure was positive within each stratum of covariate combination. The consistency assumption was also satisfied, as our results remain unchanged after truncation of weights at various percentiles. However, it is challenging to test the other MSM assumptions; thus, the interpretation of our study findings in light of causality remains limited.
      There are several additional limitations to this study. First, the validity of pain intensity, PHQ-9 depression, and behavioral symptom assessment in the MDS 3.0 is uncertain, particularly for residents with ADRD. Our previous pilot study found a moderate-to-high agreement for these 3 MDS 3.0 measures against medical records of local Medicare- and Medicaid-certified LTC facilities.
      • Wei Y.J.
      • Solberg L.
      • Chen C.
      • et al.
      Pain assessments in MDS 3.0: Agreement with vital sign pain records of nursing home residents.
      ,
      • Wei Y.J.
      • Solberg L.
      • Chen C.
      • et al.
      Agreement of Minimum Data Set 3.0 depression and behavioral symptoms with clinical diagnosis in a nursing home.
      Studies using a nationally representative sample of LTC residents are warranted to better understand the validity of MDS 3.0-based measures. Second, although studies of cognitively intact populations show sex and racial differences in pain perception and report,
      • Fillingim R.B.
      • King C.D.
      • Ribeiro-Dasilva M.C.
      • et al.
      Sex, gender, and pain: A review of recent clinical and experimental findings.
      limited evidence exists, with only 1 pilot examining sex differences in pain response among patients with ADRD.
      • Cowan R.L.
      • Beach P.A.
      • Atalla S.W.
      • et al.
      Sex differences in the psychophysical response to contact heat in moderate cognitive impairment Alzheimer's disease: A cross-sectional brief report.
      More studies that understand biopsychosocial mechanisms underlying sex and racial differences among ADRD may help explain our finding on being female and white as risk factors of uncontrolled pain. Third, although we accounted for many potential confounders measured from the MDS 3.0 data and Medicare claims, unmeasured confounders are possible and could influence our estimates. Finally, our results could only be generalized to Medicare older adults with ADRD who resided in LTC facilities.

      Conclusions and Implications

      In this study of Medicare LTC residents with ADRD, uncontrolled pain is associated with increased risk for 2 common BPSDs: depressive and behavioral symptoms. Our findings reemphasized the importance of pain assessment in LTC residents with ADRD, particularly those with identified risk factors associated with uncontrolled pain. Given that there is no cure for ADRD and the potential harms of psychotropic medication administered for treatment of BPSD, it is important to regularly assess, prevent, and manage pain in LTC residents with ADRD to prevent BPSD.

      Acknowledgments

      The National Institute on Aging had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or the decision to submit the manuscript for publication.

      Supplementary Method 1. Confounders

      We measured both time-fixed and time-varying confounders. Time-fixed confounders measured at baseline included demographic characteristics (age group: ≤64, 65–74, 75–84, and ≥85 years; sex; race/ethnicity: White, Black, and other), region of the United States (Northeast, Midwest, West, and South), low-income subsidy receipt (yes vs no), source of pain reporting (self-reported vs staff-observed from MDS 3.0 data), body mass index (BMI), and dementia severity. BMI was calculated as the weight in kilograms divided by the height in meters squared based on MDS 3.0–documented weight and height and categorized as underweight (BMI <18.5), normal (18.5–24.9), obese (25.0–29.9), and overweight (≥30).
      Obesity: preventing and managing the global epidemic. Report of a WHO consultation.
      Dementia severity was measured by a validated algorithm using 2 MDS 3.0 scales: the Cognitive Performance Scale (CPS; range 0–6, with a lower score indicating worse cognition) and the Brief Interview for Mental Status (BIMS; range 0–15, with a higher score indicating worse mental function).
      • Downer B.
      • Thomas K.S.
      • Mor V.
      • et al.
      Cognitive status of older adults on admission to a skilled nursing facility according to a hospital discharge diagnosis of dementia.
      Consistent with prior literature, we classified residents as having no (BIMS: 13–15), mild (BIMS: 8–12 or CPS: 0–2), moderate (BIMS: 0–7 or CPS: 3–4), or severe (CPS: 5–6) dementia.
      • Downer B.
      • Thomas K.S.
      • Mor V.
      • et al.
      Cognitive status of older adults on admission to a skilled nursing facility according to a hospital discharge diagnosis of dementia.
      ,
      • Mehta H.B.
      • Kuo Y.F.
      • Raji M.
      • et al.
      Time trends in opioid use by dementia severity in long-term care nursing home residents.
      In addition, we included baseline depression as a covariate in the analysis for the behavioral symptoms outcome, and baseline behavioral symptoms for the depression outcome.
      We assessed time-varying confounders at baseline and at each quarterly MDS assessment (approximately every 3 months) during follow-up. Variables measured from MDS 3.0 data included activities of daily living (classified by number of activities of daily living into groups of no [0–7], mild [8–14], moderate [15–21], and severe [≥21] dependence), disease burden (total number of 54 active diagnoses, excluding ADRD, recorded in MDS 3.0), use of scheduled pain medications (yes vs no), use of any pain medications on an as-needed basis (yes vs no), and use of any pain management including drug and nondrug interventions (yes vs no). Fewer than 0.1% of resident MDS-3.0 assessments had one of the time-varying covariates missing, and the last observation carried forward approach was used to minimize missing data.
      • Shao J.
      • Zhong B.
      Last observation carry-forward and last observation analysis.
      We also used Medicare Part D prescription data to capture time-varying utilization of prescription medications over the 3 months before each quarterly MDS 3.0 assessment. These variables included (1) use of prescription pain medications (nonopioids, opioids, and adjuvants), (2) use of prescription psychotropic medications (antipsychotics, antidepressants, anxiolytics, and sedative-hypnotics), and (3) polypharmacy, defined as concurrent use of 5 or more distinct generic drugs dispensed.
      • Masnoon N.
      • Shakib S.
      • Kalisch-Ellett L.
      • et al.
      What is polypharmacy? A systematic review of definitions.
      Figure thumbnail fx1
      Supplementary Fig. 1Distribution of propensity score by baseline pain control for the depression cohort (A) and the behavioral symptoms cohort (B).
      Supplementary Table 1ICD-9-CM Codes and Procedures for Disease Conditions and Service Care Considered in the Study Sample Selection
      Disease, Condition, or Service CareICD-9-CM Codes or ProceduresAlgorithm
      ADRD331.x, 331.2, 331.7, 290.0–290.4x, 294.x (exclude 294.9), 797At least one inpatient, SNF, HHA, HOP, or carrier claim with disease code
      Chronic pain
       Musculoskeletal274.x, 710.x-729.x (exclude 723.4, 724.3, 724.4, 729.1, 729.2)At least one inpatient, SNF, HHA, HOP, or carrier claim with disease code
       Neuropathic053.1x, 249.6, 250.6, 307.89, 336.x, 337.x, 338.0, 340, 350.x, 351.x, 352.1, 353.x-355.x, 357.1, 357.2–357.4, 357.8, 357.9, 723.4, 724.3, 724.4, 729.1, 729.2
       Idiopathic338.2, 338.4, 780.96
      Cancer diagnosisCCS11-CCS43HCUP CCS for ICD-9-CM or ICD-10-CM
      Hospice careAdmission date of hospice claimsAt least 1 hospice claim
      Palliative careDX: V 66.7 Provide specialty code: 17At least one inpatient, SNF, HHA, HOP, carrier, or DME claim with disease code; or at least one inpatient, SNF, HHA, HOP with provider specialty code
      Depression296.2x, 296.3x, 300.4, 309.1 and 311.xxAt least one inpatient, SNF, HHA, HOP, or carrier claim with disease code
      Behavioral symptoms due to dementia290.x (excluding 290.0, 290.10, and 290.40), 293.x, 294.x, (excluding 294.0 and 294.10), 297.x, 298.x, 312.9, 780.97
      CCS, Clinical Classification Software; DME, durable medical equipment; HCUP, Healthcare Cost and Utilization Project; HHA, home health agency; HOP, hospital outpatient; ICD-9-CM, International Statistical Classification of Diseases, Ninth Revision, Clinical Modification; ICD-10-CM, International Statistical Classification of Diseases, 10th Revision, Clinical Modification; SNF, skilled nursing facility.
      Supplementary Table 2Baseline
      Baseline was defined as 6 months before or at the index MDS 3.0 assessment.
      Characteristics of Eligible Long-term Care Residents With ADRD in the Cohort for Depression and Behavior Outcomes
      Baseline
      Baseline was defined as 6 months before or at the index MDS 3.0 assessment.
      Characteristic
      No. (%) of Eligible Residents
      Depression CohortBehavioral Symptoms Cohort
      Total sample size27,131 (100%)15,657 (100%)
      Age group, y
       Mean (±SD)84.5 (±10.6)83.8 (±11.2)
       50–6414415.310306.6
       65–74286610.6190412.2
       75–84686425.3394225.2
       ≥8515,96058.8878156.1
      Female20,17974.412,02876.8
      Race/ethnicity
       White20,74276.512,39779.2
       Black418315.4197612.6
       Other
      Included Hispanic, Asian, Pacific Islander, and Native American individuals.
      22068.112848.2
      Region of the United States
       Northeast625323.1338521.6
       Northcentral715626.4422627.0
       West301311.1176411.3
       South10,70939.5626840.1
      Receipt of low-income subsidy22,50082.913,11383.8
      Body mass index
       Underweight23208.611387.3
       Normal10,85540.0562735.9
       Overweight775828.6443028.3
       Obese619822.8446228.5
      Source of pain report
       Resident reported23,07485.014,07689.9
       Staff-observed405715.0158110.1
      ADL dependence
       No706926.1465029.7
       Mild881932.5517333.0
       Moderate722826.6399125.5
       Severe401514.8184311.8
      No. of chronic conditions
       0–2770628.4365423.3
       3–4981936.2565336.1
       5–6601822.2390224.9
       ≥7358813.2244815.6
      Dementia severity
       Mild12,20745.0975762.3
       Moderate11,39542.0456029.1
       Severe352913.013408.6
      Pain management
       Use of prescription pain medication13,90251.2921558.9
       Use of PRN pain medication851031.4712445.5
       Use of scheduled pain medication10,71339.5580837.1
       Use of pain management15,73958.0110,09364.5
      Use of psychotropic medication15,93958.8991263.3
      Polypharmacy (>5)23,16885.413,73387.7
      Health care utilization
       Any hospitalization968935.7430427.5
       Any ED visit12,58946.4569536.4
      Follow-up period
       Mean ± SD, y1.64 ± 1.281.44 ± 1.20
       Median (IQR), y1.25 (0.54–2.45)1.24 (0.49–2.06)
      Death24148.910106.5
      ADL, activities of daily living; ED, emergency department; PRN, pro re nata.
      Baseline was defined as 6 months before or at the index MDS 3.0 assessment.
      Included Hispanic, Asian, Pacific Islander, and Native American individuals.
      Supplementary Table 3Adjusted Association Between Uncontrolled Pain and Risk of Depression and Behavioral Symptoms among Residents with ADRD: Sensitivity Analyses of Truncation of Different Percentiles of Weights
      Percentiles of TruncationRisk for Depression OutcomeRisk for Behavioral Symptoms Outcome
      Mean (SD) of Stabilized WeightsAdjusted HR (95% CI)Mean (SD) of Stabilized WeightsAdjusted HR (95% CI)
      0.5, 99.51.03 (0.48)1.65 (1.52–1.79)1.03 (0.38)1.28 (1.19–1.38)
      1.0, 99.0

      (primary analyses)
      1.03 (.041)1.67 (1.54–1.81)1.02 (0.35)1.28 (1.19–1.37)
      2.0, 98.01.02 (0.37)1.70 (1.57–1.84)1.02 (.033)1.28 (1.20–1.37)

      References

        • Malara A.
        • De Biase G.A.
        • Bettarini F.
        • et al.
        Pain assessment in elderly with behavioral and psychological symptoms of dementia.
        J Alzheimers Dis. 2016; 50: 1217-1225
        • Gaugler J.E.
        • Yu F.
        • Krichbaum K.
        • et al.
        Predictors of nursing home admission for persons with dementia.
        Med Care. 2009; 47: 191-198
        • Lyketsos C.G.
        • Lopez O.
        • Jones B.
        • et al.
        Prevalence of neuropsychiatric symptoms in dementia and mild cognitive impairment: results from the cardiovascular health study.
        JAMA. 2002; 288: 1475-1483
        • Kales H.C.
        • Gitlin L.N.
        • Lyketsos C.G.
        Assessment and management of behavioral and psychological symptoms of dementia.
        BMJ. 2015; 350: h369
        • Kales H.C.
        • Gitlin L.N.
        • Lyketsos C.G.
        • et al.
        Management of neuropsychiatric symptoms of dementia in clinical settings: recommendations from a multidisciplinary expert panel.
        J Am Geriatr Soc. 2014; 62: 762-769
        • Livingston G.
        • Sommerlad A.
        • Orgeta V.
        • et al.
        Dementia prevention, intervention, and care.
        Lancet. 2017; 390: 2673-2734
        • Hodgson N.
        • Gitlin L.N.
        • Winter L.
        • et al.
        Caregiver's perceptions of the relationship of pain to behavioral and psychiatric symptoms in older community-residing adults with dementia.
        Clin J Pain. 2014; 30: 421-427
        • Tosato M.
        • Lukas A.
        • van der Roest H.G.
        • et al.
        Association of pain with behavioral and psychiatric symptoms among nursing home residents with cognitive impairment: results from the SHELTER study.
        Pain. 2012; 153: 305-310
        • Ishii S.
        • Streim J.E.
        • Saliba D.
        A conceptual framework for rejection of care behaviors: review of literature and analysis of role of dementia severity.
        J Am Med Dir Assoc. 2012; 13 (e11–e12): 11-23
        • Ahn H.
        • Horgas A.
        The relationship between pain and disruptive behaviors in nursing home residents with dementia.
        BMC Geriatr. 2013; 13: 14
        • Kunik M.E.
        • Snow A.L.
        • Davila J.A.
        • et al.
        Causes of aggressive behavior in patients with dementia.
        J Clin Psychiatry. 2010; 71: 1145-1152
        • Sampson E.L.
        • White N.
        • Lord K.
        • et al.
        Pain, agitation, and behavioural problems in people with dementia admitted to general hospital wards: a longitudinal cohort study.
        Pain. 2015; 156: 675-683
        • Volicer L.
        • Frijters D.H.
        • Van der Steen J.T.
        Relationship between symptoms of depression and agitation in nursing home residents with dementia.
        Int J Geriatr Psychiatry. 2012; 27: 749-754
        • Erdal A.
        • Flo E.
        • Selbaek G.
        • et al.
        Associations between pain and depression in nursing home patients at different stages of dementia.
        J Affect Disord. 2017; 218: 8-14
        • Mansournia M.A.
        • Etminan M.
        • Danaei G.
        • et al.
        Handling time varying confounding in observational research.
        BMJ. 2017; 359: j4587
        • Rahman A.N.
        • Applebaum R.A.
        The nursing home Minimum Data Set assessment instrument: manifest functions and unintended consequences--past, present, and future.
        Gerontologist. 2009; 49: 727-735
        • The Centers for Medicare & Medicaid Services (CMS)
        Chronic Conditions Data Warehouse 2020.
        (Available at:)
        • Levis B.
        • Benedetti A.
        • Thombs B.D.
        • et al.
        Accuracy of Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression: individual participant data meta-analysis.
        BMJ. 2019; 365: l1476
        • Kroenke K.
        • Spitzer R.L.
        • Williams J.B.
        The PHQ-9: validity of a brief depression severity measure.
        J Gen Intern Med. 2001; 16: 606-613
        • Gruber-Baldini A.L.
        • Boustani M.
        • Sloane P.D.
        • et al.
        Behavioral symptoms in residential care/assisted living facilities: prevalence, risk factors, and medication management.
        J Am Geriatr Soc. 2004; 52: 1610-1617
        • Galik E.
        • Resnick B.
        • Vigne E.
        • et al.
        Reliability and validity of the resistiveness to care scale among cognitively impaired older adults.
        J Am Med Dir Assoc. 2017; 18: 59-64
        • Saliba D.
        • Buchanan J.
        Rand Corporation Health: Development & validation of a revised nursing home assessment tool: MDS 3.0 health.
        (Available at:)
        • Allan C.E.
        • Valkanova V.
        • Ebmeier K.P.
        Depression in older people is underdiagnosed.
        Practitioner. 2014; 258 (19–22): 12-13
        • Saliba D.
        • Buchanan J.
        Making the investment count: Revision of the Minimum Data Set for nursing homes, MDS 3.0.
        J Am Med Dir Assoc. 2012; 13: 602-610
        • Farrington C.P.
        Interval censored survival data: A generalized linear modelling approach.
        Stat Med. 1996; 15: 283-292
        • Robins J.M.
        • Hernan M.A.
        • Brumback B.
        Marginal structural models and causal inference in epidemiology.
        Epidemiology. 2000; 11: 550-560
        • Williamson T.
        • Ravani P.
        Marginal structural models in clinical research: When and how to use them?.
        Nephrol Dial Transplant. 2017; 32: ii84-ii90
        • Cole S.R.
        • Hernan M.A.
        Constructing inverse probability weights for marginal structural models.
        Am J Epidemiol. 2008; 168: 656-664
        • Zeger S.L.
        • Liang K.Y.
        Longitudinal data analysis for discrete and continuous outcomes.
        Biometrics. 1986; 42: 121-130
        • The Centers for Medicare & Medicaid Services (CMS)
        Long-Term Care Facility Resident Assessment Instrument 3.0 User’s Manual, Version 1.17.1 2019.
        (Available at:)
        • Husebo B.S.
        • Ballard C.
        • Sandvik R.
        • et al.
        Efficacy of treating pain to reduce behavioural disturbances in residents of nursing homes with dementia: Cluster randomised clinical trial.
        BMJ. 2011; 343: d4065
        • Husebo B.S.
        • Ballard C.
        • Fritze F.
        • et al.
        Efficacy of pain treatment on mood syndrome in patients with dementia: A randomized clinical trial.
        Int J Geriatr Psychiatry. 2014; 29: 828-836
        • IsHak W.W.
        • Wen R.Y.
        • Naghdechi L.
        • et al.
        Pain and depression: A systematic review.
        Harv Rev Psychiatry. 2018; 26: 352-363
        • Payne J.L.
        • Sheppard J.M.
        • Steinberg M.
        • et al.
        Incidence, prevalence, and outcomes of depression in residents of a long-term care facility with dementia.
        Int J Geriatr Psychiatry. 2002; 17: 247-253
        • Platt R.W.
        • Delaney J.A.
        • Suissa S.
        The positivity assumption and marginal structural models: The example of warfarin use and risk of bleeding.
        Eur J Epidemiol. 2012; 27: 77-83
        • Wei Y.J.
        • Solberg L.
        • Chen C.
        • et al.
        Pain assessments in MDS 3.0: Agreement with vital sign pain records of nursing home residents.
        J Am Geriatr Soc. 2019; 67: 2421-2422
        • Wei Y.J.
        • Solberg L.
        • Chen C.
        • et al.
        Agreement of Minimum Data Set 3.0 depression and behavioral symptoms with clinical diagnosis in a nursing home.
        Aging Ment Health. 2020 May 25; ([E-pub ahead of print])
        • Fillingim R.B.
        • King C.D.
        • Ribeiro-Dasilva M.C.
        • et al.
        Sex, gender, and pain: A review of recent clinical and experimental findings.
        J Pain. 2009; 10: 447-485
        • Cowan R.L.
        • Beach P.A.
        • Atalla S.W.
        • et al.
        Sex differences in the psychophysical response to contact heat in moderate cognitive impairment Alzheimer's disease: A cross-sectional brief report.
        J Alzheimers Dis. 2017; 60: 1633-1640
      1. Obesity: preventing and managing the global epidemic. Report of a WHO consultation.
        World Health Organ Tech Rep Ser. 2000; 894: 1-253
        • Downer B.
        • Thomas K.S.
        • Mor V.
        • et al.
        Cognitive status of older adults on admission to a skilled nursing facility according to a hospital discharge diagnosis of dementia.
        J Am Med Dir Assoc. 2017; 18: 726-728
        • Mehta H.B.
        • Kuo Y.F.
        • Raji M.
        • et al.
        Time trends in opioid use by dementia severity in long-term care nursing home residents.
        J Am Med Dir Assoc. 2021; 22: 124-131.e121
        • Shao J.
        • Zhong B.
        Last observation carry-forward and last observation analysis.
        Stat Med. 2003; 22: 2429-2441
        • Masnoon N.
        • Shakib S.
        • Kalisch-Ellett L.
        • et al.
        What is polypharmacy? A systematic review of definitions.
        BMC Geriatr. 2017; 17: 230