need and unmet need of mental health among community dwelling seniors in new york city shijian li,...

Need and Unmet Need of Mental Health among Community Dwelling Seniors In New

York City

Shijian Li, Ph.D.SUNY at Old Westbury

William Gallo, Ph.D.CUNY School of Public Health and Graduate Center

APHA, 2014

Aging and Prevalence of Mental Illness

Greater percentage of lifespan spent in old age Older Population by Age: 1900-2050

Source: U.S. Bureau of the Census

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

100,000

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050

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mb

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65-74 75-84 85+

Study Design (1): Research Questions

1. How prevalent were mental disorders (i.e. depression) among community dwelling older adults in NYC?

2. How often did older adults with mental disorder seek professional mental health service?

3. What were the predictors for using the professional mental health service among older adults?

Study Design (2): Data:

1. Health Indicators Project (HIP): Survey conducted in 2008 by the Brookdale Center for Healthy Aging & Longevity of Hunter College/City University of New York (CUNY)

2. Funded: NYC Mayor’s Office (through NYC Department for the Aging)

3. Sampling Stratified based on: 1) borough; 2) senior center size; 3) race/ethnicity.

4. Subject recruitment: systematic selection procedure.

Study Design (3): Final Sample

Sample drawn from 56 senior centers 10 in the Bronx 16 in Brooklyn 13 in Manhattan 14 in Queens 3 in Staten Island.

Final sample contains 1,870 older adults.

Theoretical Framework

Health Behavior Model (Anderson, 1995) Predisposing: predict the propensity of an individual to use

healthcare (e.g. demographics, etc.)

Enabling: factors enable or impede health service use (e.g. SES, health insurance, healthcare services availability)

Need variables: perceived or evaluated need, representing the most immediate cause of health service use.

Measurement (1)

Patient Health Questionnaire (PHQ-9): PHQ-9 scores of 5, 10, 15, and 20 represent valid thresholds demarcating the lower limits of mild, moderate, moderately severe, and severe depression.

Mental healthcare utilization: whether having been to or used mental health professional (e.g. a psychiatrist, psychologist or social worker) in the last 12 months. (Yes/No).

Unmet need: defined as in need of care (being mild to severe depression, 5<PHQ-9<27), but reporting no use of professional mental health services in the previous 12 months.

Measurement (2)

Predisposing: Age, Gender, Marital Status, Religion attendance, Race/Ethnicity, Education attainment

Enabling: Personal (i.e. Income, Difficulty to meet Expenses, English ability,

Accessibility, Social Support, Discrimination), Community (i.e. Neighborhood cohesion, Neighborhood safety,

Availability of medical clinic/health service in neighborhood)

Need: Health Assessment (Physical Disability, ranging 0-7)

Descriptive Highlights

Study Sample: 525 (28.1%) older adults mildly to severely depressed (PHQ9 score >=5)

Among them:

PHQ-9 Proportion % (SD)

Mildly/Moderately Depressed (PHQ9 score: 5-14)

88.8(1.4)

Moderately Severe/Severely Depressed(PHQ9 score: 15-27)

11.2(1.4)

Mental Health Service Use in 12 months  

Yes 20.1(1.8)

No 79.9(1.8)

Descriptive—Enabling & Need Factors

Enabling Proportion % (SD)Expenses

Extremely/somewhat Difficulty 45.6(2.2)Not all difficulty 54.4(2.2)

Language at HomeEnglish 53.4(2.2)

Other 46.6(2.2) Discrimination Experiences

Yes 40.2(2.1)No 59.8(2.1)

Medical service in neighborhoodYes 79.1(1.8)No 20.9(1.8)

Need Factors Proportion % (SDPhysical Disability

No/mildly disabled (<4) 47.7(2.2)Disabled (4-7) 52.3(2.2)

Multivariate Logistic Regression

Analytic Strategy: Multiple imputations: variables with missing values

were accomplished by imputing 10 values for missing items with the user-written ICE command in Stata.

Hierarchical logistical regression: to examine the relative contribution of predisposing, enabling and need factors for mental health service use within the past 12 months.

Regression Results

Model 1a Model 2b Model 3c

Characteristics (N=525) OR 95% CI OR 95% CI OR 95% CI

Predisposing Factors (ref.)

Age (60-65)

66-74 0.64 0.35-1.20 0.69 0.36-1.30 0.66 0.35-1.27

75-84 0.22 0.11-0.44 0.23 0.11-0.48 0.22 0.10-0.46

85+ 0.11 0.04-0.30 0.13 0.05-0.34 0.11 0.04-0.30

Marital Status (Married/Partnered) 0.42 0.22-0.80 0.41 0.21-0.81 0.43 0.21-0.86

Religious Attendance (never)

Monthly 1.03 0.56-1.9 0.96 0.51-1.83 1.01 0.53-1.92

Weekly 0.52 0.27-1.0 0.49 0.24-0.97 0.52 0.26-1.00

Education (<high School)

High School 0.53 0.28-1.00 0.51 0.26-0.97 0.55 0.28-1.07

>High School 0.89 0.48-1.64 0.86 0.45-1.62 0.89 0.47-1.68

Need-for-care Factors

Physical Disability (4-7 Disabilities)*

2.05 1.21-3.47

Notes: a. Model 1: predisposing factorsb. Model 2: Predisposing factors + Enabling Factorsc. Model 3: Predisposing factors + Enabling Factors + Need Factors

d. NONE of any enabling factors were significant (expenses, language at home, social support, discrimination, neighborhood cohesion, neighborhood safety, availability of health service in neighborhood)

Summary

Only about 20% of those in need of mental health service actually received it in the past 12 months

The older of Old Americans, the married, the better educated, and those attend religious service regularly are less likely to seek mental health service

Individuals with worse physical health condition are more likely to utilize mental health service

Interesting, none of the enabling factors, including financial resources, language, and social support, were significant predictors of service utilization.

Discussion

Underserved Mental health for the older of the old Americans

Age-appropriate mental services needed

Primary Care as a potential location for mental health

Connecting seniors to mental health resources may improve their lives.