Health Services Utilization Among Chinese American Older Adults: Moderation of Social Support With Functional Limitation

Abstract

In this study, we aimed to examine the relationship of social support with hospitalizations and emergency department (ED) visits among older Chinese adults in the United States and its possible mechanism. This was a secondary analysis of data from the Population Study of Chinese Elderly (July 2011-June 2013; N = 3,157). After adjusting for demographic, clinical, and functional covariates in logistic regression analyses, significant interaction between social support from spouse and the number of functional limitations in (instrumental) activities of daily living was related to lower odds of hospitalization (odds ratio [OR] = 0.97 [0.95-0.99]) and ED visits (OR = 0.98 [0.96-0.99]). This finding suggests that among older Chinese American adults with functional limitations, more spousal support was related to lower odds of hospitalizations and ED visits. Future studies should comprehensively measure social support (e.g., content, amount) from other sources and investigate how unnecessary acute health service utilization in this population may be reduced by social support interventions.

Keywords

social support minority hospitalization emergency department visits

Introduction

Social Support in Chinese American Older Adults

Social support is the information obtained from one’s social relationships that leads the person to believe that he or she is cared for, loved, esteemed and valued, and that he or she belongs to a network of communication and mutual obligations (Cobb, 1976). Social support moderates stress and is related to health conditions caused by mental and social stressors, such as depression, alcoholism, and tuberculosis (Cobb, 1976; Thoits, 2011). Social support also modifies health promotion and psychological distress that are related to the development of physical diseases (Berkman, Glass, Brissette, & Seeman, 2000; Seeman, 2000 Uchino, 2006).

Chinese Americans represent a minority group with distinct social support from the mainstream U.S. population that is heavily influenced by traditional Chinese culture (Chi & Chou, 2001; Kim, Sherman, & Taylor, 2008). Due to collectivism and filial piety in traditional Chinese culture, Chinese American older adults perceive higher levels of support from spouse and family than that from friends (Chen, Simon, Chang, Zhen, & Dong, 2014). Yet to protect one’s close social contacts from potential emotional strain, Chinese Americans are also more likely to seek support that does not involve direct disclosure of personal stressful events or feelings of distress, when compared with European Americans (Kim et al., 2008). Other issues unique to this population such as acculturation difficulties (Shinagawa & Kim, 2008), inaccessibility to services, and culturally related misconception of illnesses (Chung, 2010) also shape social support among Chinese Americans. These factors comprise a unique social support profile of Chinese American older adults that is possibly linked to their health service use, such as hospitalization and emergency department (ED) visits.

Relationship Between Social Support and Health Service Use

Hospitalizations and ED visits are often caused by stressors, such as acute deterioration of diseases (Agency for Healthcare Research and Quality, 2016). Because social support protects individuals from adverse outcomes due to stressors, it is likely that enhanced social support, through ameliorating these stressors, can reduce the risk for hospitalizations and ED visits (Thoits, 2011). Research has shown that more peer support reduces the risk for hospitalization among Medicaid psychiatric patients (Landers & Zhou, 2011) and recently widowed women (Laditka & Laditka, 2003). Among patients recovering from hospitalization, more support from spouse, friends, and/or family is related to smaller doses of medication needed, accelerated recovery, and better compliance with prescribed medical regimen as well as lower mortality rates (Cobb, 1976; Mookadam & Arthur, 2004). Moreover, prior studies indicate that the type of relationships (i.e., sources) affects the stress-buffering effect of social support on health service use. For example, support from significant others (e.g., spouse, children) tends to exert through mechanisms such as active “coping assistance” and “emotionally-sustaining behaviors” on health outcomes and health service use, whereas support from secondary contacts (e.g., friends, neighbors) is more likely to affect health practice and health service use through social comparison (i.e., learning from similar others; Thoits, 2011). In addition, significant others tend to provide instrumental support, whereas secondary contacts inclined to provide information and advice. Taken together, existing evidence suggests that sources of social support may play an important role in health service utilization.

Hospitalizations and ED Visits in Chinese American Older Adults

Asian minority groups in the United States, such as Chinese Americans, have distinct patterns of health service utilization from the general U.S. population. For example, among older patients hospitalized for congestive heart failure in the United States, Asians have significantly longer length of hospital stay and more in-hospital procedures than Caucasians (Wheeler et al., 2004). Asian Americans are also more likely to receive less prioritized Emergency Severity Index scores at ED admission triage than their Caucasian counterparts, after controlling for patient demographic, medical, and triage nurse characteristics (Vigil et al., 2015). Substantial variation exists in health status and health care service utilization among specific racial/ethnic subgroups within the Asian American population (Sentell et al., 2013; Sentell et al., 2014), thus calling for research on specific subgroups (Esperat, Inouye, Gonzalez, Owen, & Feng, 2004; Klatsky & Tekawa, 2005). Chinese Americans represent the largest and fastest growing Asian subgroup in the United States (U.S. Census Bureau, 2016). As reported in a limited number of studies, Chinese Americans are more likely to report poor general health (39.1%; Ritenour, Rodriguez, Wilson-Frederick, Giordano, & Gualtieri, 2017) and to experience in-hospital adverse outcomes (e.g., death during diabetes-related hospitalizations) than other Asian subgroups (Guo, Ahn, Juarez, Miyamura, & Sentell, 2015; Sentell et al., 2014).

These findings suggest that social support in Chinese Americans, as influenced by both traditional Eastern culture and modern Western system and shaped by their immigrant experiences, might be related to their increased risk for hospitalizations and ED visits. Specifically, research with older Asian adults suggests that social support moderates self-care ability (e.g., exercise, diet adjustment, symptom monitoring) among people with need factors such as chronic medical conditions (Gao et al., 2013), mental disorders (Kwag, Martin, Russell, Franke, & Kohut, 2011), and functional limitation (Jang, Mortimer, Haley, & Graves, 2004), thus affecting the outcomes of their medical and mental conditions and health services use. To date, no studies have systematically examined the association between social support and health service utilization among older Chinese American adults and the possible mechanism of such association. Therefore, the objective of this study was to examine the effect of social support from spouse, family, and friends on hospitalizations and ED visits among older Chinese adults in the United States, with a focus on potential moderation between social support and need factors of health service use. We hypothesized the following:

Hypothesis 1: More social support from spouse, family, and friends would be associated with lower rates of hospitalizations and ED visits in this population.

Hypothesis 2: The impact of social support from family and spouse would be stronger than that from friends, and that such impact was related to moderation between social support and need factors.

Conceptual Framework

We used the Andersen Behavioral Model (ABM) of health services use (Andersen, 1995) to guide the design and analysis of this study. ABM is a model that has been used extensively in health services research (Babitsch, Gohl, & von Lengerke, 2012). Because this study was focused on individual determinants, we removed the “system and environment” section in the original ABM model. The individual determinants were categorized into (a) predisposing factors—age, sex, marital status, years of education, and years living in the United States; (b) enabling factors—income, number of people in the household, health insurance coverage, and social support variables (spouse, family, friends); and (c) need factors—number of medical conditions, self-perceived health status, global cognitive function, depressive symptoms, and physical function (Andersen, 1995). “Years living in the United States” was included as a predisposing factor, as it is a characteristic unique to the immigrant population.

Method

Study Design

This was a secondary analysis of data collected in the Population Study of Chinese Elderly (PINE) study between July 2011 and June 2013. The PINE study is the largest population-based, community-engaged study of Chinese older adults in the Western countries aimed at examining psychological and social well-being of Chinese older adults (Dong, Wong, & Simon, 2014). Sample in the PINE study is representative of the Chinese aging population in the Greater Chicago area regarding key demographic attributes (i.e., age, sex, income, education, number of children, country of origin) (Simon, Chang, Rajan, Welch, & Dong, 2014).

Population and Settings

Eligible participants were (a) of Chinese ancestry, (b) 60 years or older, and (c) living in the Greater Chicago area at the time of enrollment. Participants were recruited through frequent promotions in the local Chinese quarterly newspapers, flyers, and posters in public spaces, and community-based culturally sensitive health promotion activities. Out of 3,542 eligible Chinese older adults who were approached, 3,159 participated in the study (response rate: 91.9%; Dong, Wong, & Simon, 2014).

Variables and Measurements

Dependent variables

Dependent variables in this study included hospitalizations and ED visits in the past 2 years as reported by the participant. Hospitalization was assessed by asking the participant, “How many times have you been hospitalized in the past 2 years?” ED visits was assessed by asking the participant, “How many times have you visited an emergency room in the past 2 years?” Hospitalization and ED visits were coded as dichotomous variables (yes/no) in regression analysis to minimize measurement errors in self-reported health service use (Bhandari & Wagner, 2006).

Independent variables

Independent variables in this study included social support from spouse, social support from family, and social support from friends, measured using the National Social Life, Health, and Aging Project (NSHAP) network support scale (Cronbach’s α = 0.63-0.73; Cornwell & Waite, 2009). For each source (spouse, family, and friends), the participant was asked (a) “how often can you open up to them if you need to talk about your worries?” (b) “how often can you rely on them for help if you have a problem?” (c) “how often do they make too many demands on you?” and (d) “how often do they criticize you?” (Chen et al., 2014). Each question was rated on a 3-point scale. For the first two questions, ratings included 1 = hardly ever, 2 = some of the time, and 3 = often. For the last two questions, ratings were reversed. Social support score from each source was generated by summing scores of the four questions.

Covariates

Predisposing factors included age (years), sex (female/male), marital status (married/not married), education (years), and years living in the United States. Enabling factors included income, health insurance coverage (yes/no), and number of people in the household. Income was annual personal income from all sources reported by the participant categorized into 10 levels, ranging from 1 (US$0- US$4,999) to 10 (⩾US$75,000). Number of people in household was the number of people in the household besides the participant. Need factors included number of medical conditions, self-perceived health status, global cognitive function, depressive symptoms, and physical function (number of activities of daily living [ADL]/instrumental activities of daily living [IADL] limitations). Number of medical conditions was the total number of chronic conditions reported by the participant from nine categories, including (a) heart disease, (b) stroke/brain hemorrhage, (c) cancer, (d) high cholesterol, (e) diabetes, (f) hypertension, (g) hip fracture, (h) thyroid disease, and (i) osteoarthritis. Self-perceived health status was measured by asking “in general, how would you rate your health?” on a 4-point scale ranging from 1 = poor to 4 = very good. Global cognitive function was assessed by the following tests: the Chinese Mini-Mental Status Exam (C-MMSE, range 0-30), East Boston Memory Test (EBMT, range 0-24), 11-item Symbol Digit Modalities Test (SDMT, range 0-80), and the Digit Span Backwards test. A composite score of global cognitive function was generated by first transforming the score on each cognitive test to a z score and then averaging these individual z scores. A higher composite z score indicates better cognitive function. This approach (a) generated a nearly normally distributed composite score and (b) increased statistical power (Chang & Dong, 2014). Depressive symptoms were measured using the 9-item Patient Health Questionnaire (PHQ-9; range 0-27), where a higher PHQ-9 score indicates a higher level of depressive symptomology (Kroenke, Spitzer, & Williams, 2001). The PHQ-9 has excellent validity (sensitivity = 81%, specificity = 98%) and reliability (Cronbach’s α > 0.90) when used in the Chinese American population (Yeung et al., 2008). Number of ADL/IADL limitations was the total number of limitations reported by the participant in the eight ADL domains (eating, dressing, bathing, walking, transferring, grooming, incontinence, and toileting) and eight IADL domains (managing money, telephone use, meal preparation, laundry, medications self-administration, housework, routine and special health care activities, shopping, commuting, ambulation, and being alone).

Data Analysis

Descriptive statistics were used to summarize sample characteristics. Bivariate analyses (Spearman correlation) were conducted to examine the association between each social support variable (spouse, family, and friends) and each dependent variable (hospitalization and ED visits). To examine the association between each social support variable and each dependent variable, a set of logistic regression analyses were conducted while controlling for the covariates. For each source of social support, main effect was examined first, then interaction terms between this social support variable and need factors were added. To avoid collinearity, we did not combine social support variables from different sources into one model. In total, we built six regression models. Missing data were addressed by listwise deletion in all models. All statistical analyses were conducted using SAS 9.3 (SAS Institute Inc., Cary, NC).

Results

Sample Characteristics

The sample for this analysis included 3,157 Chinese older adults. As shown in Table 1, they had a mean age of 72.8 years and 58% were female, 71% were married, had an average of high school–level education (mean years of education: 8.7), and had an average annual personal income of US$5,000 to US$9,999. Participants had been living in the United States for 20 years with an average of two other people in the household. Four thirds (76%) of the participants reported having health insurance. Participants reported having two medical conditions and two ADL/IADL limitations on average, and 61% of them perceived their health status as “fair” or “poor.” The mean score of depressive symptoms (PHQ-9) was 2.65, indicating minimal depression. The mean of global cognitive function z score was −0.04.

Table 1.

Sample Characteristics.

ABM category	Variable	Descriptive summaries
Health service use	Having ⩾ 1 hospitalization, % (n)	17.7% (559)
Health service use	Having ⩾ 1 emergency department visit, % (n)	17.9% (566)
Social support	Social support from spouse, M (SD)	9.9 (1.79)
	Social support from family, M (SD)	10.6 (1.39)
	Social support from friends, M (SD)	9.5 (1.50)
Predisposing factors	Age, M (SD)	72.8 (8.3)
	Female, % (n)	58% (1,830)
	Married, % (n)	71% (2,236)
	Years of education, M (SD)	8.7 (5.05)
	Years of living in the United States, M (SD)	20.0 (13.12)
Enabling factors	Income (categories; dollars/year)	2 (1, 2): 1: US$0-US$4,999; 2: US$5,000-US$9,999
	Number of people in household, M (SD)	2 (1.89)
	Health Insurance coverage, % (n)	76.0% (2,383)
Need factors	Number of medical conditions, M (SD)	2.0 (1.46)
	Self-perceived health, % (n)	Very good: 4.4% (139) Good: 34.7% (1,096) Fair: 41.8% (1,319) Poor: 19.1% (601)
	Global cognitive function (z), M (SD)	−0.04 (0.85)
	Depressive symptoms, M (SD)	2.65 (4.13)
	Physical function: Number of ADL/IADL limitations, M (SD)	1.97 (3.22)

Note. ABM = Andersen Behavioral Model of health services use; ADL = activities of daily living; IADL = instrumental activities of daily living.

Association Between Social Support and Hospitalizations and ED Visits

Participants reported having received the most social support from family (M = 10.6) and spouse (M = 9.9) than that from friends (M = 9.5). Nearly one fifth of the sample reported having at least one hospitalization (17.7%, n = 559) and/or one ED visit (17.9%, n = 566) in the past 2 years. Spearman correlation analyses showed that social support from spouse, family, and friends were all negatively associated with hospitalization, and social support from family and friends were negatively associated with ED visits.

In the fully adjusted logistic regression models (Table 2), significant need factors associated with both hospitalizations and ED visits included the following: medical conditions (odds ratio [OR] = 1.27-1.29 for ED visits, 1.29-1.32 for hospitalization); ADL/IADL limitations (OR = 1.11-1.12 for ED visits, 1.13-1.15 for hospitalization); depressive symptoms (OR = 1.04-1.07 for ED visits, 1.04-1.06 for hospitalization); and self-perceive health status (OR = 0.63-0.65 for ED visits, 0.67-0.94 for hospitalization). Below we summarized the results of main effect (Table 2) and interaction effect (Table 3) for each source of social support.

Table 2.

Association Between Main Effects of Social Support and Outcomes (Hospitalization, Emergency Department Visits).

Outcomes		Hospitalization			Emergency department visits
Source of social support		Spouse	Family	Friends	Spouse	Family	Friends
Predisposing factors	Age	1.01 [1.00, 1.03]	1.01 [0.99, 1.03]	1.01 [0.99, 1.03]	1.02 [1.00, 1.04]*	1.02 [1.00, 1.04]*	1.02 [1.00, 1.03]*
	Female	0.63 [0.51, 0.79]***	0.62 [0.49, 0.79]***	0.64 [0.50, 0.81]***	0.74 [0.59, 0.92]**	0.73 [0.58, 0.92]**	0.75 [0.59, 0.94]*
	Married	(not included due to collinearity)	0.95 [0.73, 1.23]	0.97 [0.74, 1.26]	(not included due to collinearity)	1.08 [0.83, 1.41]	1.11 [0.85, 1.44]
	Years of education	1.01 [0.98, 1.04]	1.01 [0.98, 1.04]	1.01 [0.98, 1.04]	1.04 [1.01, 1.06]**	1.04 [1.01,1.06]**	1.04 [1.01, 1.06]**
	Years of living in the United States	0.99 [0.98, 1.00]	1.00 [0.99, 1.01]	1.00 [0.99, 1.01]	0.99 [0.98, 1.00]	0.99 [0.98, 1.00]	0.99 [0.98, 1.00]
Enabling factors	Income	0.89 [0.78, 1.00]	0.88 [0.78, 0.99]*	0.88 [0.78, 0.99]*	0.92 [0.82, 1.03]	0.91 [0.85, 0.97]	0.91 [0.81, 1.02]
	Number of people in the household	0.91 [0.86, 0.98]**	0.92 [0.86, 0.98]*	0.92 [0.86, 0.98]*	0.92 [0.86, 0.98]**	0.91 [0.85,0.97]**	0.91 [0.86, 0.97]**
	Having health insurance	1.57 [1.12, 2.19]**	1.59 [1.14, 2.22]**	1.58 [1.13, 2.20]**	1.29 [0.94, 1.77]	1.29 [0.95, 1.77]	1.26 [0.94, 1.76]
Need factors	Number of medical conditions	1.29 [1.20, 1.39]***	1.30 [1.20, 1.40]***	1.30 [1.21, 1.40]***	1.29 [1.20, 1.39]***	1.29 [1.20, 1.39]***	1.30 [1.20, 1.40]***
	Self-perceived health	0.67 [0.57, 0.78]***	0.66 [0.57, 0.77]***	0.67 [0.58, 0.79]***	0.67 [0.58, 0.78]***	0.67 [0.58, 0.78]***	0.68 [0.58, 0.79]***
	Global cognitive score	1.15 [0.97, 1.36]	1.16 [0.57, 0.77]	1.16 [0.98, 1.38]	1.22 [1.03, 1.45]*	1.22 [1.03, 1.44]	1.22 [1.03, 1.44]*
	Depressive symptoms	1.05 [1.02, 1.08]***	1.05 [1.02, 1.08]***	1.05 [1.02, 1.07]***	1.06 [1.03, 1.08]***	1.05 [1.03, 1.08]***	1.05 [1.02, 1.08]***
	Number of ADL/IADL limitations	1.14 [1.10, 1.19]***	1.14 [1.10, 1.18]***	1.14 [1.10, 1.19]***	1.12 [1.08, 1.17]***	1.12[1.08, 1.17]***	1.12 [1.08, 1.17]***
Social support	Main effect	1.01 [0.95, 1.08]	1.00 [0.92, 1.08]	0.97 [0.90, 1.04]	1.03 [0.96, 1.09]	1.00 [0.93, 1.08]	0.99 [0.92, 1.07]

Note. Presented values are odds ratios (95% confidence intervals). ADL = activities of daily living; IADL = instrumental activities of daily living.

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

Table 3.

Moderation of Social Support With Need Factors Associated With Outcomes (Hospitalization, Emergency Department Visits).

Outcomes		Hospitalization			Emergency department visits
Source of social support		Spouse	Family	Friends	Spouse	Family	Friends
Predisposing factors	Age	1.01 [0.99, 1.03]***	1.01 [0.99, 1.03]	1.01 [0.99, 1.03]	1.02 [1.00, 1.04]*	1.02 [1.00, 1.03]	1.02 [1.00, 1.04]
	Female	0.61 [0.48, 0.77]	0.62 [0.48, 0.79]***	0.69 [0.53, 0.89]**	0.72 [0.58, 0.90]	0.74 [0.58, 0.95]*	0.74 [0.58, 0.95]*
	Married	(not included due to collinearity)	0.91 [0.69, 1.21]	1.05 [0.79, 1.40]	(not included due to collinearity)	1.02 [0.78, 1.35]	1.14 [0.86, 1.51]
	Years of education	1.01 [0.98, 1.03]	1.01 [0.98, 1.04]	1.01 [0.98, 1.04]	1.03 [1.01,1.06]*	1.03[1.01, 1.06]*	1.04 [1.01, 1.07]**
	Years of living in the United States	1.00 [0.99, 1.01]	1.00 [0.99, 1.01]	1.00 [0.99, 1.01]	0.99 [0.98, 1.00]**	0.99 [0.98, 1.00]	0.99 [0.99, 1.00]
Enabling factors	Income	0.89 [0.78, 1.01]	0.88 [0.77, 1.00]	0.89 [0.78, 1.01]	0.92 [0.81, 1.03]	0.91 [0.81, 1.03]	0.91 [0.81, 1.02]
	Number of people in the household	0.92 [0.86, 0.99]*	0.93 [0.87, 0.99]*	0.93 [0.86, 1.00]	0.92 [0.86, 0.98]**	0.91 [0.85, 0.97]**	0.89 [0.83, 0.96]**
	Having health insurance	1.63 [1.16, 2.29]**	1.60 [1.13, 2.25]**	1.75 [1.21, 2.51]**	1.31 [0.95, 1.80]	1.32 [0.95, 1.83]	1.33 [0.95, 1.85]
Need factors	Number of medical conditions	1.30 [1.21, 1.41]	1.30 [1.20, 1.41]***	1.32 [1.22, 1.44]***	1.29 [1.20,1.39]***	1.29 [1.19, 1.39]***	1.27 [1.18, 1.38]***
	Self-perceived health status	0.64 [0.55, 0.75]***	0.64 [0.54, 0.75]***	0.67 [0.57, 0.79]***	0.65 [0.56, 0.76]***	0.63 [0.53, 0.73]***	0.64 [0.54, 0.75]***
	Global cognitive score	1.12 [0.94, 1.33]***	1.11 [0.93, 1.33]	1.15 [0.95, 1.38]	1.21 [1.02, 1.43]	1.23 [1.03, 1.47]*	1.20 [1.00, 1.45]
	Depressive symptoms	1.06 [1.03, 1.09]	1.05 [1.02, 1.08]**	1.04 [1.01, 1.07]*	1.07 [1.04, 1.10]***	1.05 [1.02, 1.08]***	1.04 [1.01, 1.07]**
	Number of ADL/IADL limitations	1.13 [1.09, 1.18]***	1.14 [1.10, 1.19]***	1.15 [1.10, 1.20]***	1.11 [1.07, 1.15]***	1.12 [1.08, 1.16]***	1.11 [1.06, 1.16]***
Social support	Main effect	1.13 [0.88, 1.45]	1.33 [0.95, 1.86]	0.75 [0.54, 1.06]	1.12 [0.88, 1.43]	1.43 [1.03, 1.98]*	1.21 [0.87, 1.68]
Social support	Moderation with need factors: Social support × Physical function	0.98 [0.96, 0.99]*	1.00 [0.98, 1.03]	1.01 [0.98, 1.03]	0.97 [0.95, 0.99]**	1.00 [0.97, 1.02]	0.99 [0.96, 1.01]

Note. Moderation between social support and other need factors were not significant; presented values are odds ratios (95% confidence intervals). ADL = activities of daily living; IADL = instrumental activities of daily living.

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

Social support from spouse

Social support from spouse was not significantly associated with hospitalization or ED visits in the main effect models (Table 2). Significant interaction was noted between social support from spouse and the number of ADL/IADL limitations, which was significantly associated with lower odds of hospitalization (OR = 0.98 [0.96-0.99], p < .05) and ED visits (OR = .97 [0.95-0.99], p < .01; Table 3).

Social support from family

Social support from family was not significantly associated with hospitalization or ED visits in the main effect models (Table 2). After interaction terms between social support from family and need factors were added (Table 3), social support from family was associated with higher odds of ED visits (OR = 1.43 [1.03, 1.98]).

Social support from friends

No significant relationships were noted between social support from friends (both main effects and moderation) with hospitalization and ED visits.

Discussion

To the knowledge of the authors, this is the first study that systematically examined the association between social support from multiple sources and acute health care services use among older Chinese adults in the United States. The principal findings of this study included that (a) among older Chinese American adults, hospitalization and ED visits were mainly related to need factors, such as the number of medical conditions and the number of ADL/IADL limitations; and (b) significant interaction existed between spousal support and the number of ADL/IADL limitations. In particular, the sources of social support mattered: among patients with ADL/IADL limitations, more support from spouse was related to lower odds of hospitalizations and ED visits. Our hypotheses were supported, as (a) more social support from spouse was related to lower odds of hospitalization and ED visits in patients with ADL/IADL limitations; and (b) the impact of social support from spouse on hospitalization and ED visits was through the significant moderation between social support and ADL/IADL limitations.

Findings in this study were consistent with prior evidence on the importance of need factors to hospitalization and ED visits, especially depressive symptoms (Kong, Wang, Davitt, & Dong, 2018), medical conditions, and functional limitations. National data have showed that up to 84.8% of hospitalizations in older Americans are caused by medical conditions (Weiss & Elixhauser, 2014), and 70.4% of rehospitalizations in the Medicare population are attributed to acute medical conditions and/or acute deterioration of chronic conditions (Jencks, Williams, & Coleman, 2009). In addition, older adults with more functional limitations had significantly higher risk for hospitalizations (Ehlenbach, Larson, Randall Curtis, & Hough, 2015) and prolonged functional decline after hospital discharge (Covinsky, Pierluissi, & Johnston, 2011), thus forming a vicious cycle between need factors and adverse outcomes.

One way to break this vicious cycle is through enhanced and diversified social support. In this study, among older Chinese Americans with ADL/IADL limitations—a high-risk group for health deterioration and adverse outcomes—having more spousal support decreased the odds of both hospitalization and ED visits. One explanation for this finding is that better support from spouse among older adults with ADL/IADL limitations suggests better caregiver assistance and safety in daily life, which is critical to preventing adverse events such as incident falls and hip fracture that can lead to hospitalization and ED visits. Older Chinese adults with more spousal support are also more likely to adopt health behaviors and self-care routines, such as regular use of preventive care services (Dong & Liu, 2017). Better self-care will then facilitate effective disease management of chronic conditions, lessen the likelihood of acute deterioration of these conditions, thus reducing the odds of hospitalization and ED services. Given that over half of the older Chinese American adults have ADL/IADL limitations (Dong, Chang, & Simon, 2014) with at least two medical conditions, it is important to examine, in interventional studies, how enhancing older Chinese American adults’ social support from spouse improves their health status and if enhanced social support can prevent unnecessary hospitalizations and ED visits. Of note, the sex of spouse was not assessed in this study, and it is possible that support from a female spouse is different in both content and amount from the support from a male spouse.

In addition, it is important to diversify social support in the older Chinese American population. Research should examine (a) the content/amount of support from family, friends, and other sources that are available to older Chinese American adults and (b) whether enhanced support from different sources exert different impacts on health service use.

In accordance with previous research (Chen et al., 2014), older Chinese Americans reported having received more social support from family and spouse than that from friends in this study. However, family support did not significantly moderate the relationship between functional limitations and acute health care services use, as did spousal support.

One possible reason is related to the changes in family structure and caregiving responsibilities of family members among Chinese Americans. Due to adaptation to the mainstream filial value in the United States, generational gap, and disadvantaged socioeconomic status associated with immigration faced by the adult children (Dong, Chang, Wong, & Simon, 2012; Lai, 2005; Wong, Yoo, & Stewart, 2006), older Chinese adults in the United States are less likely to rely on their adult children for support as they would traditionally have been. Different from the traditional filial value where adult children are expected to care for their aging parents in multigenerational households, with the shift in familial values, older Chinese adults nowadays live more independently (Wong et al., 2006), usually not in close proximity with their adult children (Pang, Jordan-Marsh, Silverstein, & Cody, 2003; Wong et al., 2006). In the new familial structure, older Chinese Americans avoid soliciting support from their adult children for health care needs unless important medical decisions need to be made (Pang et al., 2003).

Another possible reason is that the nature of family support among older Chinese American adults—often from adult children living separately from them—differs from that of spousal support. In the modified family structure, older Chinese adults tend to receive emotional support in forms of monthly visits and phone contacts from their adult children, compared with tangible support in the traditional Chinese family dynamic (Dong et al., 2012; Wong et al., 2006). Therefore, Chinese American older adults with chronic medical conditions and functional limitations may be relying more on their spouse, than family or friends, with daily caregiving assistance with self-care (ADL/IADL limitations) and management of the chronic diseases.

This is especially relevant to today’s world, considering that future generations of Chinese in the United States tend to be more Westernized than their ancestors and that their family structure and ways to seek social support might be going through substantial shifts. With these changes, more caregiving responsibilities will be assumed by older adults’ spouse, who are also in their elderly years and may have a number of medical conditions of their own. As a result, elderly spouses of older Chinese adults with chronic diseases and functional limitations (e.g., those of Alzheimer’s disease) may experience caregiver burden. If left unaddressed, excessive caregiver burden can lead to adverse health effects, such as depression, stress, poor self-rated health, and even early mortality (Pinquart & Sörensen, 2003; Schulz & Beach, 1999). Elderly spouses of medically ill older patients may also experience transportation and language barriers, which represent the two most common forms of help needed by United States older Chinese adults in the health seeking process (Pang et al., 2003). These barriers further preclude elderly spouses of older Chinese Americans to seek help from their extended social network and become less able to support their sick partners. Therefore, future research needs to explore (a) how caregivers of older adults in minority groups (usually their spouses) can be reached and supported in linguistically and culturally sensitive approaches, utilizing resources in the broader social network, and (b) how social support in the older Chinese American population be enhanced through resources beyond their spouses and immediate family.

Some unexpected findings were noted. In moderation models, more family support was related to higher odds of ED visits (OR = 1.43). A possible reason is that older Chinese adults with more support from the family, when developing acute medical conditions, were more likely to be recognized by their family members and sent to the ED, compared with those with less support from the family. However, it is also possible that more family support helps Chinese American older adults better maintain self-care routines to avoid acute illness that leads to ED visit in the first place. Future research is needed to examine how the nature, content, and amount of social support from spouse and family differ as the nature and severity of medical illnesses change.

Study Limitations

First, participants in this study were representative of the Greater Chicago area (Simon et al., 2014); however, it is not clear whether the findings could be generalizable to older Chinese adults in other geographic areas in the United States or other counties. Second, our study focused on emotional social support and did not examine other types of social support, such as informational, tangible, and financial support and companionship. Given that tangible social support, for example, transportation and language assistances, is important to health services use among Chinese American older adults, lack of attention to this specific type of social support in this study represents another limitation (Dong et al., 2012; Pang et al., 2003). Third, participants reported hospitalization and ED visits in the past 2 years, which may differ from current or future acute care health service use. Last, the cross-sectional design of this study limits our ability to determine causal relationships between social support and health service utilization.

Implications and Future Directions

This study reveals that more spousal support was related to lower odds of acute health care service use among older Chinese American adults who have functional limitations. Future studies should employ a more comprehensive measurement of social support, where the nature, content, and amount of social support that Chinese American older adults receive from spouse, family, friend, and other possible sources are examined in greater detail. Caregiver burden among spouses of medically ill older Chinese Americans should also be examined. Health care providers, researchers, and policy makers should consider the influence of social support from spouse and family on health service use when designing behavioral interventions (e.g., self-monitoring programs conducted in dyads with the spouse or a family member), providing care and assistance (e.g., education focused on preventing unncessary health service use through enhancing support support network for older adults with multimorbidity), and allocating resources (e.g., community-based senior centers for elderly married couples with chronic conditions) in this vulnerable population. Support from broader social contacts should also be promoted in the older Chinese American population. Finally, special considerations are needed to meet the needs of Chinese American older adults in different areas (rural/urban), as the sample was from a metropolitan area with ethnic enclave that may create a unique and protective environment for immigrants (e.g., Chinatown) that may alter their experience of acculturation, social support, and attitudes toward health care service use.

In conclusion, more social support from spouse and partially from family was related to lower odds of hospitalizations and ED visits among older Chinese American adults with functional limitations. Future studies should comprehensively measure social support (e.g., content, amount) and investigate how unnecessary acute health service utilization in this population may be reduced by enhancing social support from diverse sources.

Footnotes

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) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Jinjiao Wang

References

Agency for Healthcare Research and Quality. (2016, December). HCUP fast stats. Healthcare Cost and Utilization Project (HCUP). Rockville, MD. Retrieved from www.hcup-us.ahrq.gov/faststats/national/inpatientcommondiagnoses.jsp?year1=2014&characteristic1=0&included1=0&year2=&characteristic2=0&included2=0&expansionInfoState=hide&dataTablesState=hide&definitionsState=hide&exportState=hide

Andersen

R. M.

(1995). Revisiting the behavioral model and access to medical care: Does it matter? Journal of Health and Social Behavior, 36, 1-10.

Babitsch

Gohl

von Lengerke

(2012). Re-revisiting Andersen’s Behavioral Model of health services use: A systematic review of studies from 1998–2011. GMS Psycho-Social-Medicine, 9, Doc11. doi:10.3205/psm000089

Berkman

L. F.

Glass

Brissette

Seeman

T. E.

(2000). From social integration to health: Durkheim in the new millennium. Social Science & Medicine, 51, 843-857.

Bhandari

Wagner

(2006). Self-reported utilization of health care services: Improving measurement and accuracy. Medical Care Research and Review, 63, 217-235. doi:10.1177/1077558705285298

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: Biological Sciences & Medical Sciences, 69(Suppl. 2), S23-S30. doi:10.1093/gerona/glu195

Chen

Simon

M. A.

Chang

E. S.

Zhen

Dong

(2014). The perception of social support among U.S. Chinese older adults: Findings from the PINE study. Journal of Aging and Health, 26, 1137-1154. doi:10.1177/0898264314529332

Chi

Chou

K. L.

(2001). Social support and depression among elderly Chinese people in Hong Kong. The International Journal of Aging & Human Development, 52, 231-252. doi:10.2190/v5k8-cnmg-g2up-37qv

Chung

(2010). Changes in the sociocultural reality of Chinese immigrants: Challenges and opportunities in help-seeking behaviour. International Journal of Social Psychiatry, 56, 436-447. doi:10.1177/0020764009105647

10.

Cobb

(1976). Social support as a moderator of life stress. Psychosomatic Medicine, 38, 300-314.

11.

Cornwell

E. Y.

Waite

L. J.

(2009). Measuring social isolation among older adults using multiple indicators from the NSHAP study. The Journals of Gerontology, Series B: Psychological Sciences & Social Sciences, 64B(Suppl. 1), i38-i46. doi:10.1093/geronb/gbp037

12.

Covinsky

K. E.

Pierluissi

Johnston

C. B.

(2011). Hospitalization-associated disability: “She was probably able to ambulate, but I’m not sure”. Journal of the American Medical Association, 306, 1782-1793. doi:10.1001/jama.2011.1556

13.

Dong

Chang

E.-S.

Simon

M. A.

(2014). Physical function assessment in a community-dwelling population of U.S. Chinese older adults. The Journals of Gerontology, Series A: Biological Sciences & Medical Sciences, 69(Suppl. 2), S31-S38. doi:10.1093/gerona/glu205

14.

Dong

Chang

E.-S.

Wong

Simon

(2012). A qualitative study of filial piety among community dwelling, Chinese, older adults: Changing meaning and impact on health and well-being. Journal of Intergenerational Relationships, 10, 131-146. doi:10.1080/15350770.2012.673393

15.

Dong

Liu

(2017). Variations between sources of social support and cancer screen behaviors in US Chinese older adults. The Journals of Gerontology, Series A: Biological Sciences & Medical Sciences, 72(suppl. 1), S26-S31.

16.

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

17.

Ehlenbach

W. J.

Larson

E. B.

Randall Curtis

Hough

C. L.

(2015). Physical function and disability after acute care and critical illness hospitalizations in a prospective cohort of older adults. Journal of the American Geriatrics Society, 63, 2061-2069.

18.

Esperat

M. C.

Inouye

Gonzalez

E. W.

Owen

D. C.

Feng

(2004). Health disparities among Asian Americans and Pacific Islanders. Annual Review of Nursing Research, 22, 135-159.

19.

Gao

Wang

Zheng

Haardörfer

Kegler

M. C.

Zhu

(2013). Effects of self-care, self-efficacy, social support on glycemic control in adults with type 2 diabetes. BMC Family Practice, 14, Article 66.

20.

Guo

M. W.

Ahn

H. J.

Juarez

D. T.

Miyamura

Sentell

T. L.

(2015). Length of stay and deaths in diabetes-related preventable hospitalizations among Asian American, Pacific Islander, and White older adults on Medicare, Hawai’i, December 2006-December 2010. Preventing Chronic Disease, 12, E124. doi:10.5888/pcd12.150092

21.

Jang

Mortimer

J. A.

Haley

W. E.

Graves

A. R. B.

(2004). The role of social engagement in life satisfaction: Its significance among older individuals with disease and disability. Journal of Applied Gerontology, 23, 266-278.

22.

Jencks

S. F.

Williams

M. V.

Coleman

E. A.

(2009). Rehospitalizations among patients in the Medicare fee-for-service program. New England Journal of Medicine, 360, 1418-1428. doi:10.1056/NEJMsa0803563

23.

Kim

H. S.

Sherman

D. K.

Taylor

S. E.

(2008). Culture and social support. American Psychologist, 63, 518-526. doi:10.1037/0003-066X

24.

Klatsky

A. L.

Tekawa

(2005). Health problems and hospitalizations among Asian-American ethnic groups. Ethnicity & Disease, 15, 753-760.

25.

Kong

Wang

Davitt

Dong

X. Q.

(2018). Association between depressive symptoms and health services utilization in U.S. Chinese Older Adults. The Gerontologist. Advance online publication. Available at: https://www.ncbi.nlm.nih.gov/pubmed/29546324

26.

Kroenke

Spitzer

R. L.

Williams

J. B.

(2001). The PhQ-9. Journal of General Internal Medicine, 16, 606-613.

27.

Kwag

K. H.

Martin

Russell

Franke

Kohut

(2011). The impact of perceived stress, social support, and home-based physical activity on mental health among older adults. The International Journal of Aging & Human Development, 72, 137-154.

28.

Laditka

J. N.

Laditka

S. B.

(2003). Increased hospitalization risk for recently widowed older women and protective effects of social contacts. Journal of Women & Aging, 15(2-3), 7-28; discussion 185-187. doi:10.1300/J074v15n02_02

29.

Lai

D. W.

(2005). Cultural factors and preferred living arrangement of aging Chinese Canadians. Journal of Housing for the Elderly, 19(2), 71-86. doi:10.1300/J081v19n02_05

30.

Landers

G. M.

Zhou

(2011). An analysis of relationships among peer support, psychiatric hospitalization, and crisis stabilization. Community Mental Health Journal, 47, 106-112.

31.

Mookadam

Arthur

H. M.

(2004). Social support and its relationship to morbidity and mortality after acute myocardial infarction: Systematic overview. Archives of Internal Medicine, 164, 1514-1518. doi:10.1001/archinte.164.14.1514

32.

Pang

E. C.

Jordan-Marsh

Silverstein

Cody

(2003). Health-seeking behaviors of elderly Chinese Americans: Shifts in expectations. The Gerontologist, 43, 864-874. doi:10.1093/geront/43.6.864

33.

Pinquart

Sörensen

(2003). Differences between caregivers and noncaregivers in psychological health and physical health: A meta-analysis. Psychology and Aging, 18, 250-267.

34.

Ritenour

Rodriguez

Wilson-Frederick

Giordano

Gualtieri

(2017). Understanding the health needs of diverse groups of Asian and native Hawaiian or other Pacific Islander Medicare beneficiaries (CMS OMH Data Highlight No. 10). Baltimore, MD: Centers for Medicare & Medicaid Services, Office of Minotiry Health.

35.

Schulz

Beach

S. R.

(1999). Caregiving as a risk factor for mortality: The Caregiver Health Effects Study. Journal of the American Medical Association, 282, 2215-2219.

36.

Seeman

T. E.

(2000). Health promoting effects of friends and family on health outcomes in older adults. American Journal of Health Promotion, 14, 362-370. doi:10.4278/0890-1171-14.6.362

37.

Sentell

T. L.

Ahn

H. J.

Juarez

D. T.

Tseng

C. W.

Chen

J. J.

Salvail

F. R.

. . . Mau

M. L.

(2013). Comparison of potentially preventable hospitalizations related to diabetes among native Hawaiian, Chinese, Filipino, and Japanese elderly compared with whites, Hawai’i, December 2006-December 2010. Preventing Chronic Disease, 10, E123. doi:10.5888/pcd10.120340

38.

Sentell

T. L.

Juarez

D. T.

Ahn

H. J.

Tseng

C. W.

Chen

J. J.

Salvail

F. R.

. . . Mau

M. K.

(2014). Disparities in diabetes-related preventable hospitalizations among working-age Native Hawaiians and Asians in Hawai’i. Hawai’i Journal of Medicine & Public Health, 73(12, Suppl. 3), 8-13.

39.

Shinagawa

L. H.

Kim

D. Y.

(2008). A portrait of Chinese American: A national demographic and social profile of Chinese Americans. College Park: Asian American Studies Program, University of Maryland.

40.

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. Journal of Aging and Health, 26, 1100-1115. doi:10.1177/0898264314543472

41.

Thoits

P. A.

(2011). Mechanisms linking social ties and support to physical and mental health. Journal of Health and Social Behavior, 52, 145-161.

42.

Uchino

B. N.

(2006). Social support and health: A review of physiological processes potentially underlying links to disease outcomes. Journal of Behavioral Medicine, 29, 377-387.

43.

U.S. Census Bureau. (2016). FFF: Asian/Pacific American heritage month: May 2016. Retrieved from http://www.census.gov/newsroom/facts-for-features/2016/cb16-ff07.html

44.

Vigil

J. M.

Alcock

Coulombe

McPherson

Parshall

Murata

Brislen

(2015). Ethnic disparities in Emergency Severity Index scores among U.S. Veteran’s Affairs emergency department patients. PLoS ONE, 10(5), e0126792. doi:10.1371/journal.pone.0126792

45.

Weiss

A. J.

(Truven Health Analytics), & Elixhauser

(AHRQ). (2014). Overview of hospital stays in the United States, 2012 (HCUP Statistical Brief #180). Rockville, MD: Agency for Healthcare Research and Quality. Retrieved from http://www.hcup-us.ahrq.gov/reports/statbriefs/sb180-Hospitalizations-United-States-2012.pdf

46.

Wheeler

E. C.

Klemm

Hardie

Plowfield

Birney

Polek

. . . Lynch

K. G.

(2004). Racial disparities in hospitalized elderly patients with chronic heart failure. Journal of Transcultural Nursing, 15, 291-297. doi:10.1177/1043659604268962

47.

Wong

S. T.

Yoo

G. J.

Stewart

A. L.

(2006). The changing meaning of family support among older Chinese and Korean immigrants. The Journals of Gerontology, Series B: Psychological Sciences & Social Sciences, 61(1), S4-S9. doi:10.1093/geronb/61.1.S4

48.

Wong

S. T.

Yoo

G. J.

Stewart

A. L.

(2007). An empirical evaluation of social support and psychological well-being in older Chinese and Korean immigrants. Ethnicity & Health, 12, 43-67. doi:10.1080/13557850600824104

49.

Yeung

Fung

S. C.

Vorono

Fava

(2008). Validation of the Patient Health Questionnaire-9 for depression screening among Chinese Americans. Comprehensive Psychiatry, 49, 211-217. doi:10.1016/j.comppsych.2006.06.002