Perceived Stress and Cognitive Functions Among Chinese Older Adults: The Moderating Role of Health Status

Abstract

Objective: The primary purposes of the present study are (a) to investigate the stress–cognition relationship among U.S. Chinese older adults and (b) to examine the moderating role of health status on the stress–cognition relationship. Method: Data were drawn from the Population Study of Chinese Elderly in Chicago (PINE), which investigated 3,157 Chinese adults over 60 years old living in Chicago. Participants reported health status and completed the Chinese Perceived Stress Scale. Cognitive functions were measured by the East Boston Memory Test, the Digit Span Backward, the Symbol Digit Modalities Test, and Chinese Mini-Mental State Examination. Results: Controlling for age, sex, education, and income, perceived stress was negatively associated with cognitive functions, whereas health status was positively associated with cognitive functions. In addition, older adults’ health status interacted with stress such that the negative relationships between perceived stress and cognitive functions were more pronounced for those who had poor health than for those who had good health. Conclusion: Findings suggest that physical health is a critical factor moderating the relationship between perceived stress and cognitive functions among U.S. Chinese older adults. Longitudinal research is needed to examine the complex relationships among stress, health, and cognitive functions of U.S. Chinese older adults.

Keywords

perceived stress cognitive functions health status U.S. Chinese older adults

Introduction

Cognitive impairment and dementia are among major causes of morbidity and mortality among older adults and contribute substantially to health care expenditures around the world (P. M. Krueger, Saint Onge, & Chang, 2011; Wimo, Jönsson, Bond, Prince, & Winblad, 2013). Recent research suggests that stress can affect brain and cognitive functions profoundly (Lupien, McEwen, Gunnar, & Heim, 2009). The relationship between stress and cognition is, however, paradoxical because stress can either facilitate or impair cognitive functions (Joëls, Pu, Wiegert, Oitzl, & Krugers, 2006; Sandi, 2013). Reviewing hundreds of experiments with animals and humans, Sandi (2013) concluded that stress intensity is a major defining factor of the effects of stress on cognition. While mild stress tends to facilitate cognitive functions, high or sustained stress typically impairs explicit memory (but improves implicit memory). In addition, the context where stress occurs matters. Stress promotes cognitive functioning if it is triggered by the cognitive task itself. In contrast, stress impairs cognitive functioning if it is triggered by the external environment (Sandi, 2013). Nevertheless, much evidence on the stress–cognition relationship is derived from experimental research. Very few population-based research has examined the stress–cognition relationship (Aggarwal et al., 2014). Cognitive functions decline with increasing age (Salthouse, 1996). Thus, it is especially important to study the stress–cognition relationship among the older adult population. Using data from the Chicago Health and Aging Project, Aggarwal and colleagues (2014) found that increasing levels of perceived stress were related to lower cognitive functions among 6,207 Black and White older adults.

No research so far has examined the stress–cognition relationship among U.S. Chinese older adults, despite the fact that Chinese older adults are the fastest growing segment of the aging population in the United States (U.S. Census Bureau, 2010). The Population Study of Chinese Elderly in Chicago (PINE) is the first population-based research that measured both perceived stress and cognitive functions of 3,157 U.S. Chinese older adults (Chang & Dong, 2014; Zhang, Simon, & Dong, 2014). Thus, the first primary goal of the present study is to investigate the stress–cognition relationship among Chinese older adults, using the PINE data.

The relationship between stress and cognitive functions depends on a combination of factors related to both stress and cognitive functions (Sandi, 2013), such as the stress intensity and the context where stress occurs. Perceived stress, the psychological perception of whether environmental demands exceed an individual’s coping resources, is important to study in relation to physical health (Cohen, Kessler, & Gordon, 1995; Lazarus & Folkman, 1987). Physical health declines with aging and is positively associated with cognitive functions and negatively associated with perceived stress among U.S. Chinese older adults (Chang & Dong, 2014; Chen, Peng, Ma, & Dong, 2017; Zhang et al., 2014). U.S. Chinese older adults are susceptible to the double jeopardy of physical aging and acculturation stress (Chen et al., 2017). It is estimated that more than 80% of the U.S. Chinese older adults were born in foreign countries and 30% of them immigrated to the United States after the age of 60 (Dong, Wong, & Simon, 2014). Immigration is a highly stressful process, let alone immigration in late adulthood. Compared with their White counterparts, U.S. Chinese older adults suffer from greater psychological distress and health disparity (Chen et al., 2017).

However, there is a great paucity of data on cognitive functions of U.S. Chinese older adults. This is likely due to the absence of culturally and linguistically sensitive instruments (Chang & Dong, 2014). The PINE study used culturally and linguistically appropriate instruments and measured multiple cognitive functions, including episodic memory, working memory, and perceptual speed, among Chinese older adults (Chang & Dong, 2014). Based on the literature review on the stress–cognition relationship (Sandi, 2013), negative relationships between perceived stress and cognitive functions were hypothesized among U.S. Chinese adults for the following two reasons. First, the stress Chinese older adults encountered in the United States typically occurred during the acculturation process and originated from the context (Dong et al., 2014). Second, the PINE study is a population-based study. In the Chicago Health and Aging Project (Aggarwal et al., 2014), negative relationships between stress and cognitive functions were found for both White and Black older adults. Thus, we made the first hypothesis of the present study.

Hypothesis 1: The relationships between perceived stress and cognitive functions (i.e., episodic memory, working memory, and perceptual speed) would be negative among U.S. Chinese older adults.

Physical health decline is a major source of stress among older adults (Chen, Peng, Xu, & O’Brien, 2018). According to the Socioemotional Selectivity Theory (SST; Carstensen, Isaacowitz, & Charles, 1999), older adults may conserve their cognitive resources and are more likely than younger adults to focus on health and well-being because of their limited future time perspective. The Strength and Vulnerability Integration (SAVI) model (Charles, 2010; Charles, Leger, & Urban, 2016) further emphasizes the important role of physiological vulnerability on older adults’ cognitive and emotional functioning. Similar to the SST (Carstensen et al., 1999), the SAVI model (Charles et al., 2016) suggests that older adults actively avoid exposure to situations that may elicit high levels of emotional distress to maintain their health and well-being. However, when older adults could not avoid stress exposure, they suffer from worse health consequences than younger adults due to their increased physiological vulnerabilities. Chinese older adults living in the United States typically experience high levels of acculturation stress that cannot be avoided, such as language barrier and racial discrimination (Chen et al., 2017; Dong et al., 2014). Thus, based on both the SST (Carstensen et al., 1999) and the SAVI model (Charles, 2010), we expected that physical health status would moderate the negative relationship between perceived stress and cognitive functions among U.S. Chinese older adults. Specifically, for Chinese older adults who had good health status, the stress associated with aging and acculturation may not be perceived as demanding and, therefore, may have little impact on their cognitive functions. In contrast, perceived stress may be more pronounced for those older adults who had poor health and impair their cognitive functions. Thus, the second goal of the present study was to examine the moderating role of health status on the stress–cognition relationship among U.S. Chinese older adults.

Hypothesis 2: The negative stress–cognition relationships would be more pronounced for those who had poor health status than for those who had good health status.

Method

Population and Settings

The PINE is a community-engaged, population-based epidemiological study of U.S. Chinese older adults aged 60 and above living in the Greater Chicago area. The PINE study implemented culturally and linguistically appropriate community recruitment strategies guided by a community-based participatory research (CBPR) approach (Dong et al., 2014). More than 20 social service agencies, community centers, health advocacy agencies, faith-based organizations, senior apartments, and social clubs served as study recruitment sites. Of 3,542 eligible older adults who were approached, 3,157 agreed to participate in the study, a response rate of 91.9%. All participants were consented and interviewed by trained bicultural research assistants in English or in a Chinese dialect, including Mandarin, Cantonese, Toishanese, and Teochow, according to participants’ preference. Demographic characteristics of the PINE sample were comparable with those available from the 2010 U.S. Census and a random street-block census of the Chinese community in Chicago (Simon, Chang, Rajan, Welch, & Dong, 2014). The PINE study was approved by the Institutional Review Board of the Rush University Medical Center.

Measurements

Perceived stress

The Chinese Perceived Stress Scale (PSS-10) was used to assess the degree to which life situations were perceived as stressful (Zhang et al., 2014). Participants were asked how often in the last month they had felt (a) upset because of something that happened unexpectedly, (b) unable to control important things in life, (c) nervous and “stressed,” (d) confident about the ability to handle personal problems, (e) that things were going your way, (f) unable to cope with all the things had to do, (g) able to control irritations in life, (h) on top of things, (i) angered because of things that happened out of control, and (j) unable to overcome piled up difficulties. Respondents indicated answers to each question on a 5-point scale ranging from 0 = never to 4 = very often. Of the 10 items, four items (Items 4, 5, 7, and 8) were worded in a positive direction, so they were reversely coded as 0 = very often to 4 = never. The scores of all items were then summed. Total scores ranged from 0 to 40, with higher scores indicating greater psychological stress. The PSS-10 demonstrated good internal consistency reliability in the present study (α = .86).

Cognitive functions

A battery of five cognitive tests was administered during the face-to-face interviews (Chang & Dong, 2014). Four of the five tests assessed three cognitive domains: episodic memory, working memory, and perceptual speed. Episodic memory was a composite of the East Boston Memory Test–Immediate Recall (EBMT) and the East Boston Memory Test–Delayed Recall (EBDR) (Albert et al., 1991). Working memory was assessed by the Digit Span Backward which was drawn from the Wechsler Memory Scale–Revised (Wechsler, 1987). Perceptual speed was measured by the Symbol Digit Modalities Test (SDMT), an 11-item test that required rapid perceptual comparisons of numbers and symbols in 90 s (Smith, 1982). Finally, the C-MMSE was adapted from the MMSE (Mini-Mental State Examination), a widely used tool in epidemiological studies to assess overall cognitive status (Folstein, Folstein, & McHugh, 1975). The C-MMSE was validated in Chinese older adults in Hong Kong (Chiu, Lee, Chung, & Kwong, 1994). Higher scores represented better cognitive performance in all tests. Raw scores of all five tests were converted to z scores, using means and standard deviations of the distribution of the scores of all participants on the tests, to construct cognitive factors (three cognitive functions and C-MMSE). A composite score of global cognition was calculated by averaging the z scores of all five cognitive tests (K. R. Krueger, Wilson, Bennett, & Aggarwal, 2009). The composite score has the advantage of increasing power by reducing random variability present within tests and is approximately normally distributed (Chang & Dong, 2014).

Health status

Participants’ general health status was assessed by asking them to rate their health in general on a 4-point scale (1 = poor, 2 = fair, 3 = good, 4 = very good). Due to the skewed distribution, we dichotomized participants into two groups: 0 = poor or fair health and 1 = good or very good health.

Sociodemographic covariates

Age, sex, education, and income were correlated to perceived stress and cognitive functions in previous PINE studies (Chang & Dong, 2014; Zhang et al., 2014). Thus, they were controlled to examine the joint influence of perceived stress and health status on cognitive functions. Gender was coded as 1 = male, 0 = female. Participants’ education was assessed by the years of formal education completed, ranging from 0 to 26 years. Participants’ annual income was categorized into two groups: 0 = less than US$10,000, and 1 = more than US$10,000.

Data Analysis

We first used descriptive statistics to describe the sample characteristics. Second, Spearman correlations were used to describe the relationships between perceived stress, health status, and sociodemographic variables with the global cognition, three specific cognitive functions, and C-MMSE. Finally, four linear regression models were performed on the global cognition as well as three specific cognitive functions (i.e., episodic memory, working memory, and perceptual speed) to test our hypotheses. First, Model 1 investigated the influence of the sociodemographic variables on cognitive functions. To test Hypothesis 1, Model 2 examined the influence of perceived stress and health status on cognitive functions, controlling for sociodemographic variables. Model 3 tested Hypothesis 2 by entering the interaction term between perceived stress and health status, controlling for sociodemographic variables. Listwise deletion was used to address missing data. All statistical analyses were undertaken using SAS, Version 9.2.

Results

Table 1 provided descriptive statistics of all variables under study. Specifically, it included age, sex, education, income, general health status, perceived stress, and z scores of cognitive functions (i.e., global cognition, episodic memory, working memory, perceptual speed, and C-MMSE).

Table 1.

Descriptive Statistics for the Sociodemographic and Testing Variables.

Variable	Total number	M/n(%)	SD	Range
Age		72.31	8.30	59 to 105
Sex
Male		1,334 (42.3)	—	—
Female		1,822 (57.7)	—	—
Education (years)		8.72	5.06	0 to 26
Income
Less than US$10,000		2,656 (84.1)	—	—
More than US$10,000		465 (14.7)	—	—
Perceived stress		10.07	6.54	0 to 39
General health
Poor/fair		1,921 (60.8)	—	—
Good/very good		1,236 (39.2)	—	—
Global cognitive functions	3,148	−.02	.79	−4.45 to 1.68
C-MMSE	3,142	0	1	−5.08 to 1.03
Episodic memory	3,097	0	1	−2.53 to 1.45
Working memory	2,971	0	1	−2.31 to 2.76
Perceptual speed	2,878	0	1	−1.46 to 2.83

Note. C-MMSE, episodic memory, working memory, and perceptual speed were standardized prior to testing. C-MMSE = Chinese Mini-Mental State Exam.

Table 2 showed Spearman correlations between cognitive functions and perceived stress, health status, and sociodemographic variables. Cognitive functions were positively related to education, income, and health status, but negatively related to age, sex (female), and perceived stress.

Table 2.

Spearman Correlations Between Cognitive Functions and Perceived Stress, Health Status, and Sociodemographic Variables.

Variables	Age	Sex	Education	Income	Perceived stress	General health
1. Global cognitive function	−.32**	−.14**	.58**	.17**	−.16**	.10**
2. C-MMSE	−.30**	−.16**	.53**	.18**	−.20**	.08**
3. Episodic memory	−.30**	−.08**	.46**	.15**	−.09**	.09**
4. Working memory	−.22**	−.20**	.51**	.12**	−.14**	.07**
5. Perceptual speed	−.23**	−.08**	.41**	.11**	−.17**	.09**

Note. C-MMSE = Chinese Mini-Mental Status Exam.

p < .05. **p < .01.

Regression Model 2 tested Hypothesis 1, the relationship between perceived stress and cognitive functions among U.S. Chinese older adults. Perceived stress had negative impact on the cognitive functions, after controlling for age, sex, education, and income (see Table 3). For every unit increase of perceived stress, global cognition decreased by .02 standard score units, p < .001; episodic memory decreased by .01 standard score units, p < .001; working memory decreased by .01 standard score units, p < .001; and perceptual speed decreased by .02 standard score units, p < .001.

Table 3.

Linear Regression Models on Cognitive Functions.

Model	Global cognitive functions		Episodic memory		Working memory		Perceptual speed
Model	B	SE	B	SE	B	SE	B	SE
Model 1
Age	−.03***	.00	−.03***	.00	−.02***	.00	−.01***	.00
Sex	−.07**	.02	.00	.03	−.21***	.03	.02	.04
Education	.08***	.00	.08***	.00	.09***	.00	.04***	.00
Income	.10**	.03	.04**	.04	.04	.04	.04	.05
Adjusted R²	.39		.28		.29		.40
Model 2
Age	−.03***	.00	−.03***	.00	−.02***	.00	−.01**	.00
Sex	−.06**	.02	.02	.03	−.19***	.03	.03	.04
Education	.08***	.00	.08***	.00	.09***	.00	.04***	.00
Income	.08**	.03	.11*	.04	.02	.04	.02	.05
Perceived Stress	−.02***	.00	−.01***	.00	−.01***	.00	−.02***	.00
General Health	.06*	.02	.11**	.03	.03	.03	.02	.04
Adjusted R²	.41		.29		.30		.41
Model 3
Age	−.03***	.00	−.03***	.00	−.02***	.00	−.01**	.00
Sex	−.06**	.02	.02	.03	−.19***	.03	.03	.04
Education	.08***	.00	.08***	.00	.09***	.00	.04***	.00
Income	.08*	.03	.11*	.04	.02	.04	.02	.05
Perceived Stress	−.02***	.00	−.01***	.00	−.02***	.00	−.02***	.00
General Health	−.04	.04	.00	.06	−.07	.06	−.01	.07
Stress × Health	.01**	.00	.01*	.00	.01*	.00	.00	.01
Adjusted R²	.41		.29		.30		.41

p < .05. **p < .01. ***p < .001.

Regression Model 3 tested Hypothesis 2, the moderating role of health status on the stress–cognition relationship. Significant interactions between perceived stress and general health were found for global cognition, β = .07, t(3017) = 2.97, p < .01; episodic memory, β = .07, t(2985) = 2.47, p < .05; and working memory, β = .06, t(2875) = 2.17, p < .05; but not for perceptual speed, t(2780) = 0.525, p = .60. Multicollinearity was tested by examining tolerance and the variance inflation factor (VIF) for the variables. Overall, results indicated that multicollinearity was not a problem (VIFs < 3.2, Tolerance > 0.32).

To better understand the significant interaction effects, separate linear regressions of perceived stress on cognitive functions were performed for Chinese older adults who reported poor health status and those who reported good health status. After controlling for sociodemographic variables, the estimated slope of perceived stress on global cognitive function was −.15, t(1825) = −8.41, p < .001, for Chinese older adults who reported poor health status, and −.06, t(1188) = −2.58, p < .05, for those who reported good health status. For episodic memory, the estimated slope of perceived stress was −.08, t(1799) = −4.13, p < .001, for Chinese older adults who reported poor health status. In contrast, the effect of perceived stress on cognitive functions was not significant for those who reported good health, t(1182) = 0.07, p = .95. Similar results were found for working memory. Perceived stress had an estimated slope of −.12, t(1731) = −6.06, p < .001, for those who reported poor health status. In contrast, perceived stress did not significantly predict working memory for those who reported good health status, t(1140) = −1.31, p = .19. Figure 1 illustrated the interaction effect of perceived stress and health status on global cognition. Supporting Hypothesis 2, the figure shows that the negative stress–cognition slopes were steeper for those who had poor health status than for those who had good health status.

Figure 1.

Interaction of perceived stress and health status on global cognition.

Discussion

The present study is the first population-based study that investigated the stress–cognition relationships among U.S. Chinese older adults. Perceived stress was found negatively related to multiple cognitive functions (i.e., episodic memory, working memory, and perceptual speed) among Chinese older adults. More importantly, Chinese older adults’ health status moderated the negative relationships between perceived stress and cognitive functions. Perceived stress had more pronounced negative impacts on cognitive functions for Chinese older adults with poor health status than those with good health status. These findings add to our understanding of the complex relationships among stress, health, and cognitive functions among older adults.

The Stress–Cognition Relationship

The paradoxical relationships between stress and cognition have been frequently studied in experiments with animals, but rarely with humans (Sandi, 2013). Stress intensity and the context where stress occurred were two important factors influencing the stress–cognition relationships (Sandi, 2013). Our findings of the negative relationship between perceived stress and cognitive functions among U.S. Chinese older adults support the important role of context on the stress–cognition relationship. Individuals perceive stress when environmental demands exceed their coping resources (Cohen et al., 1995). Although the present study only assessed the degree to which life situations were perceived stressful in the last month, it likely reflected an overall evaluation of stressful life situations of U.S. Chinese older adults. The double jeopardy of physical aging and acculturation stress may make Chinese older adults in the United States especially vulnerable to cognitive impairment (Chen et al., 2017).

Few population-based studies examined the stress–cognition relationships due to the difficulty of measuring cognitive functions in large populations (Aggarwal et al., 2014). One strength of the PINE data is the inclusion of multiple measures of cognitive functions, such as episodic memory, working memory, and perceptual speed. The present study is the first to discover the negative stress–cognition relationship in a population-based study of U.S. Chinese older adults (i.e., PINE). The stress–cognition relationship among Chinese older adults was similar to the relationships among White and Black older adults in another population-based research (i.e., Chicago Health and Aging Project; Aggarwal et al., 2014).

The Moderating Role of Health Status

Under stressful situations, it is vital to have adequate coping resources (Carver, 2007; Cohen et al., 1995). Physical health is an important coping resource. Our results suggested that when Chinese older adults had good health status, the negative impact of stress on global cognition was not as pronounced as those older adults who had poor health status. Furthermore, the negative stress–cognition relationships were not significant for episodic memory and working memory when Chinese older adults reported good health, but were significantly more negative when they reported poor health. These findings support the SAVI model (Charles, 2010), which suggests that older adults may be more vulnerable to stressful situations and suffer worse cognitive and emotional consequences than younger adults due to their increased physiological vulnerabilities. Chinese older adults who reported poor health status were likely to have increased physiological vulnerabilities to stressful situations, and thus had impaired cognitive functions than those who reported good health status. Recent cognitive aging research calls for studies that advance our understanding of cognitive aging processes (Kremen, Lachman, Pruessner, Sliwinski, & Wilson, 2012). The recommendations include testing multiple mediators, examining moderation effects, and targeting interventions (Kremen et al., 2012). Following these recommendations, we found that health status was a significant moderator of the stress–cognition relationship. Our findings extend current understanding of the mechanisms underlying the stress–cognition relationships.

Limitations and Future Direction

The findings of the present study should be interpreted with limitations in mind. First, although the PINE study was representative of Chinese older adults living in the Greater Chicago area, our findings may not be generalizable to other Chinese populations because of geographical variations, which may influence the regional variations on demography, immigration, acculturation, and social support network. More population-based research is needed to investigate Chinese older adults’ stress and cognitive functions in different regions across the United States. Second, the interaction effects of stress and health status were found on episodic memory and working memory, but not on perceptual speed. As the PINE only had these three cognitive measures, it was difficult to speculate why. Future research may include more comprehensive cognitive assessments to test the interaction effects. Finally, the cross-sectional design cannot determine the causal directions of perceived stress and cognitive functions. Perceived stress may increase in response to cognitive impairments rather than cause it. Future studies with longitudinal designs are needed to better understand the complex relationships of stress, health, and cognitive functions among Chinese older adults.

Implications

This present study has important implications for researchers, health professionals, social workers, and policy makers. First, this study provided a basis for population-based research investigating the relationships between perceived stress and cognitive functions among U.S. Chinese older adults. Standardized cognitive scores in this sample can be compared with those in other older adult populations in the United States and China. For example, the cognitive functions of U.S. Chinese older adults can be compared with their White counterparts in the United States and Chinese older adults in China to estimate the normative age-related declines in cognitive functions due to physical aging versus acculturation stress unique to Chinese older adults living in the United States. Second, our findings can help health professionals, social workers, and policy makers identify the high-risk older adults for intervention purposes. The present study suggests that Chinese elderly who perceived high levels of stress and had poor health status is the most vulnerable group of cognitive impairments. It is essential to prioritize this high-risk group in clinical evaluations and interventions.

Footnotes

Acknowledgements

The authors are grateful to Community Advisory Board members for their continued effort in this project. Particular thanks are extended to Bernie Wong, Vivian Xu, and Yicklun Mo with the Chinese American Service League (CASL); Dr. David Lee with the Illinois College of Optometry; David Wu with the Pui Tak Center; Dr. Hong Liu with the Midwest Asian Health Association; Dr. Margaret Dolan with John H. Stroger Jr. Hospital; Mary Jane Welch with the Rush University Medical Center; Florence Lei with the CASL Pine Tree Council; Julia Wong with CASL Senior Housing; Dr. Jing Zhang with Asian Human Services; Marta Pereya with the Coalition of Limited English Speaking Elderly; and Mona El-Shamaa with the Asian Health Coalition.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Dr. Dong was supported by National Institute on Aging grants (R01 AG042318, R01 MD006173, R01 CA163830, R34MH100443, R34MH100393 & RC4 AG039085), Paul B. Beeson Award in Aging, The Starr Foundation, American Federation for Aging Research, John A. Hartford Foundation and The Atlantic Philanthropies.

References

Aggarwal

N. T.

Wilson

R. S.

Beck

T. L.

Rajan

K. B.

de Leon

C. F. M.

Evans

D. A.

Everson-Rose

S. A.

(2014). Perceived stress and change in cognitive function among adults 65 years and older. Psychosomatic Medicine, 76, 80-85. doi:10.1097/PSY.0000000000000016

Albert

Smith

L. A.

Scherr

P. A.

Taylor

J. O.

Evans

D. A.

Funkenstein

H. H.

(1991). Use of brief cognitive tests to identify individuals in the community with clinically diagnosed Alzheimer’s disease. International Journal of Neuroscience, 57, 167-178. doi:10.3109/00207459109150691

Carstensen

L. L.

Isaacowitz

D. M.

Charles

S. T.

(1999). “Taking time seriously: A theory of socioemotional selectivity.” American Psychologist, 54, 165-181. doi:10.1037/0003-066X.54.3.165PMID10199217

Carver

C. S.

(2007). Stress, coping, and health. In Friedman

H. S.

Silver

R. C.

(Eds.), Foundations of health psychology (pp. 117-144). New York, NY: Oxford University Press.

Chang

E. S.

Dong

(2014). A battery of tests for assessing cognitive function in U.S. Chinese older adults—Findings from the PINE study. The Journals of Gerontology, Series A: Biomedical Sciences & Medical Sciences, 69(Suppl. 2), S23-S30. doi:10.1093/gerona/glu195

Charles

S. T.

(2010). Strength and vulnerability integration: A model of emotional well-being across adulthood. Psychological Bulletin, 136, 1068-1091. doi:10.1037/a0021232

Charles

S. T.

Leger

K. A.

Urban

E. J.

(2016). Emotional experience and health: What we know, and where to go from here. In Ong

A. D.

Löckenhoff

C. E.

(Eds.), Emotion, aging, and health (pp. 185-204). Washington, DC: American Psychological Association. doi:10.1037/14857-010

Chen

Peng

Dong

(2017). Conscientiousness moderates the relationship between perceived stress and depressive symptoms among U.S. Chinese older adults. The Journals of Gerontology, Series A: Biomedical Sciences & Medical Sciences, 72(Suppl. 1), S108-S112. doi:10.1093/gerona/glw172

Chen

Peng

O’Brien

W. H.

(2018). Age differences in stress and coping: Problem-focused strategies mediate the relationship between age and positive affect. International Journal of Aging and Human Development, 86, 347-363. doi:10.1177/0091415017720890

10.

Chiu

H. F.

Lee

H. C.

Chung

W. S.

Kwong

P. K.

(1994). Reliability and validity of the Cantonese version of mini-mental state examination—A preliminary study. Hong Kong Journal of Psychiatry, 4(2), 25-28.

11.

Cohen

Kessler

R. C.

Gordon

L. U.

(1995). Strategies for measuring stress in studies of psychiatric and physical disorders. In Cohen

Kessler

R. C.

Gordon

L. U.

(Eds.), Measuring stress: A guide for health and social scientists (pp. 3-26). New York, NY: Oxford University Press.

12.

Dong

Wong

Simon

M. A.

(2014). Study design and implementation of the PINE study. Journal of Aging and Health, 26, 1085-1099. doi:10.1177/0898264314526620

13.

Folstein

M. F.

Folstein

S. E.

McHugh

P. R.

(1975). “Mini-mental state”: A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189-198.

14.

Joëls

Wiegert

Oitzl

M. S.

Krugers

H. J.

(2006). Learning under stress: How does it work? Trends in Cognitive Sciences, 10, 152-158. doi:10.1016/j.tics.2006.02.002

15.

Kremen

W. S.

Lachman

M. E.

Pruessner

J. C.

Sliwinski

Wilson

R. S.

(2012). Mechanisms of age-related cognitive change and targets for intervention: Social interactions and stress. The Journals of Gerontology, Series A: Biomedical Sciences & Medical Sciences, 67, 760-765. doi:10.1093/gerona/gls125

16.

Krueger

K. R.

Wilson

R. S.

Bennett

D. A.

Aggarwal

N. T.

(2009). A battery of tests for assessing cognitive function in older Latino persons. Alzheimer Disease and Associated Disorders, 23, 384-388. doi:10.1097/WAD.0b013e31819e0bfc

17.

Krueger

P. M.

Saint Onge

J. M.

Chang

V. W.

(2011). Race/ethnic differences in adult mortality: The role of perceived stress and health behaviors. Social Science & Medicine, 73, 1312-1322. doi:10.1016/j.socscimed.2011.08.007

18.

Lazarus

R. S.

Folkman

(1987). Transactional theory and research on emotions and coping. European Journal of Personality, 1, 141-169. doi:10.1002/per.2410010304

19.

Lupien

S. J.

McEwen

B. S.

Gunnar

M. R.

Heim

(2009). Effects of stress throughout the lifespan on the brain, behaviour and cognition. Nature Reviews Neuroscience, 10, 434-445. doi:10.1038/nrn2639

20.

Salthouse

T. A.

(1996). The processing-speed theory of adult age differences in cognition. Psychological Review, 103, 403-428.

21.

Sandi

(2013). Stress and cognition. Wiley Interdisciplinary Reviews: Cognitive Science, 4, 245-261. doi:10.1002/wcs.1222

22.

Simon

M. A.

Chang

E. S.

Rajan

K. B.

Welch

M. J.

Dong

(2014). Demographic characteristics of U.S. Chinese older adults in the greater Chicago area: Assessing the representativeness of the PINE study. Journal of Aging and Health, 26, 1100-1115. doi:10.1177/0898264314543472

23.

Smith

(1982). Symbol Digit Modalities Test (SDMT): Manual (revised). Los Angeles, CA: Western Psychological Services.

24.

U.S.Census Bureau. (2010). Census demographic profile 2011. Washington, DC: Author.

25.

Wechsler

(1987). Wechsler Memory Scale—Revised Manual. San Antonio, TX: Psychological Corporation.

26.

Wimo

Jönsson

Bond

Prince

Winblad

(2013). The worldwide economic impact of dementia 2010. Alzheimer’s & Dementia, 9, 1-11.e3. doi:10.1016/j.jalz.2012.11.006

27.

Zhang

Simon

M. A.

Dong

(2014). The prevalence of perceived stress among U.S. Chinese older adults. AIMS Medical Science, 1, 40-56. doi:10.3934/medsci.2014.1.40