Connecting Residential

Dissatisfaction and

Cognitive Decline in Older Adults:

A Longitudinal Analysis

Russell N. James III and Anne L. Sweaney

University of Georgia

Linking housing quality with health outcomes is quite common in accessibility and safety.

(Golant, 1993; Hutchings, Olsen, & Moulton, 2008; Trickey, Maltais, Gosselin, & Robitaille, 1993).

But, home is also a place of personal, social, emotional and psychological importance(Tanner, Tilse, & Jong, 2008; Rowles & Chaundhury, 2005).

Housing quality has been positively associated with psychological well-being and positive affect. (Evans, Kantrowitz, and Eshelman, 2002)

Is housing directly related to cognitive function?

Both poor housing quality (Obasanjo, 1998)

and a lack of contact with nature (Wells, 2000)

were found to be predictive of poor cognitive outcomes for minor children.

Is housing directly related to cognitive function?

Caplan et al., (2006) found that among a population with serious mental illness, socially isolated housing was associated with weakened executive functioning.

Is housing directly related to cognitive function?

In mice with Alzheimer’s Disease symptoms, long-term housing in an enriched physical environment (with, e.g., platforms, passageways, and lofts) resulted in improved rates of cognitive decline (Arendash, et al., 2004; Jankowsky, et al., 2005; Costa, 2007)

Living in neighborhoods of relatively high deprivation (income, employment, health and disability, education, living environments, and crime) was independently associated with lower cognitive ability, even after controlling for individual socioeconomic circumstances. (Lang, et al., 2008)

Wight et al. (2006), in a cross-sectional study of Americans over 70, found evidence of a neighborhood effect on cognitive scores based upon the average educational attainment within the census tract.

In a regional cross-sectional study, neighborhood type, measured by income and ethnic composition, was a predictor of cognitive impairment even after controlling for individual respondent characteristics Espino, Lichtenstein, Palmer, and Hazuda (2001)

Individual living space matters

- Institutionalized

- Mentally ill

- Children

Neighborhoods matter

- Community-dwelling elderly

Question: Does a perceived deficit in the physical conditions of one’s individual residence predict subsequent cognitive decline in community-dwelling older adults?

If only neighborhoods matter, then improving outcomes requires improving the entire neighborhood

If individual housing quality matters, then improving outcomes may be possible with a more targeted approach.

Morris and Winter’s (1978) model suggests

1. A gap between the physical condition of housing and housing norms or expectations can lead to psychological stress resulting in negative mental health outcomes.

2. Subjective housing deficits can also lead to social stress and biological stress, each of which can result in additional psychological stress resulting in negative mental health outcomes.

DATA: Over 15,000 respondents, age 50 and above, completed HRS cognitive tests in the 1998 survey and also in the 2002 survey and/or the 2006 survey.

Question: Does a perceived deficit in the physical conditions of one’s individual residence predict subsequent cognitive decline in community-dwelling older adults?

Perceived Deficit

Cognitive Decline

Perceived deficit

“How about the physical condition of your (house or apartment/house/apartment), would you say it is in excellent, very good, good, fair, or poor condition?”

Cognitive decline

Interviewer reads a list of 10 words. Respondent asked to recall words immediately. After 5 minutes of other questions, then asked to name as many words from the list as possible.

Outcome: change in combined score (delayed and immediate) between the baseline year (in 1998) and the subsequent year.

Cognitive decline

Similar tests of memory have been successful in identifying conditions such as the very early onset of mild Alzheimer’s disease (Coen et al., 1997).

Controls

Neighborhood“Would you say the safety of your neighborhood is excellent, very good, good, fair or poor?”

DepressionA 9-question version of the Center for Epidemiologic Studies Depression Scale

Socio-economicAssets, income, education, married, gender, race, employed, volunteer, charitable giving

HealthSelf-rated health, cancer, stroke, heart problems

House condition = “poor” 1.7% 15898House condition = “fair” 8.7% 15898House condition = “good” 25.7% 15898House condition = “very good” 35.7% 15898House condition = “excellent” 28.3% 15898Age 64.35 (10.01) 16040Black 13.2% 16042Hispanic 7.6% 16042Male 39.7% 16042Household assets ($10k) 31.67 (68.02) 16042Household income ($10k) 5.32 (8.49) 16042Married 71.1% 16042Baseline (1998) recall score 10.78 (3.56) 153312002 recall score 9.86 (3.71) 151732006 recall score 9.5 (3.55) 13100

Sample Descriptive Statistics

Baseline variables Recall score Δ (4 years)

Recall score Δ (8 years)

Recall score Δ (4 years)

Recall score Δ (8 years)

House condition score 0.0782** 0.0137 HC fair v. poor 0.2872 0.5666* HC good v. poor 0.4520* 0.603** HC very good v. poor 0.4483* 0.5787** HC excellent v. poor 0.5445** 0.5514* Neighborhood safety 0.0274 0.0629* 0.0305 0.0678* CES-D (depression) -0.0482** -0.0533*** -0.0471** -0.0508** Volunteer 0.3113*** 0.2216*** 0.3113*** 0.2214*** Working 0.0400 0.2655*** 0.0383 0.2622*** Male -0.7101*** -0.6634*** -0.7089*** -0.6611*** Black -0.457*** -0.8631*** -0.455*** -0.8586*** Hispanic -0.065 -0.1988 -0.0674 -0.2053 Education (years) 0.1277*** 0.1645*** 0.1279*** 0.1644*** Age -0.0864*** -0.1177*** -0.0865*** -0.1178*** Household assets ($10k) 0.0003 0.0005 0.0004 0.0005 Household income ($10k) 0.0088** 0.0068 0.0088** 0.0069 Married -0.0188 0.0846 -0.0207 0.0805 Number of children 0.003 0.0236 0.0034 0.0236 Health (self-rated) 0.1439*** 0.1617*** 0.1438*** 0.1619*** Cancer 0.0611 0.1527 0.0631 0.1564 Stroke -0.445*** -0.2875* -0.4476*** -0.293* Heart problems 0.0216 -0.0056 0.0237 -0.0031 Baseline (1998) recall score -0.577*** -0.6627*** -0.5771*** -0.6627*** Intercept 8.7759*** 10.5183*** 8.6052 9.9882 (0.39)*** R-square 0.2801 0.3659 0.2802 0.3663n 13829 11687 13829 11687

But dramatic differences in

subsequent cognitive scores associated with

being in housing in “poor”

physical condition.

There is little difference in subsequent cognitive scores associated with “good,” “very good,” or “excellent” housing.

This suggests that potential gains to be made in subsequent cognitive decline may come, almost exclusively, from targeting the small percentage of housing in the poorest physical condition.

Given that only 1.7% of housing was rated as “poor,” this segment generating the most notable differences was relatively small.

• The magnitude of the impact on subsequent cognitive decline associated with housing in “poor” physical condition is significant.

• The difference in subsequent cognitive decline associated with being in housing in “poor” physical condition instead of “good” physical condition is roughly equivalent to an additional six years of age.

• In 1978, Morris and Winter proposed a model suggesting that housing-deficit induced stress could lead to negative mental health outcomes.

• The effect of housing satisfaction was seen primarily at the very lowest end of the rating spectrum, i.e., only where a clear deficit is being indicated.

• Housing researchers have long understood the potential cost savings and health benefits from improving the accessibility and safety of housing for older adults.

• These arguments now appear to have a parallel argument related to cognitive decline, another driver of institutionalization (St. John

et al., 2002).

Questions?

Comments?

Dirty looks?