Latent Class Typologies for Emotional Support Among Midlifeand Aging Americans: Evidence from the National Healthand Human Nutrition Examination Survey

Timothy S. Killian • M. Jean Turner

� Springer Science+Business Media New York 2014

Abstract Using data from 40-year-old and older respon-

dents in the 2007–2008 National Health and Nutrition

Examination Study, this study sought to identify variations in

emotional support networks among midlife and older adults

and examine how those variations were related to depressive

symptoms and to perceptions of inadequate support. Latent

class analyses were used to identify six typologies of emo-

tional support networks. Typologies were labeled, and

multinomial logistic regression was used to examine how

membership in typologies was related to variations in

depressive symptoms and perceived adequacy of emotional

support. The findings indicate that when the focus is emo-

tional support, social support from spouses is related to fewer

depressive symptoms and less perceived need for increased

emotional support. The results of this study suggest that

access to family members, especially spouses, for emotional

support is related to fewer depressive symptoms and a

decreased probability of reporting inadequate social support.

Overall, this study suggests that emotional support networks

that include family members, especially spouses, are sup-

portive of older persons’ quality of life.

Keywords Emotional support � Depressive symptoms �Family relationships

Introduction

Mounting empirical evidence has contributed to the wide-

spread consensus that depressive symptoms are a public

health concern, especially in an era of healthcare reform.

Depressive symptoms are related to utilization of both

formal healthcare services (Callahan et al. 1997; Katon

et al. 2003) and informal caregiving (Langa et al. 2004),

often resulting in increased healthcare costs. Given that

social engagement seems protective against depressive

symptoms (Glass et al. 2006), there is increased interest in

adults’ social networks and how variations in those net-

works may be related to physical and psychological well-

being and healthcare costs (Jorm 2005). Based on these

findings, this study identified latent emotional support

network structures among midlife and older adults and

examined how variations in those structures were related to

depressive symptoms and perceptions of the adequacy of

their emotional support networks to meet their needs.

While social support has been approached from a variety of

perspectives, one vigorous dimension to understanding social

support has been the identification of social network typolo-

gies and how those typologies are related to older persons’

well-being. One of the first to articulate a social network

typology, Wenger (1991) identified five distinct network types

using extensive qualitative data: (1) Local Family Dependent,

(2) Locally Integrated Support, (3) Local Self-Contained, (4)

Wider Community Focused, and (5) Private Restricted Net-

work. Based on both qualitative data and theory, Wenger

suggested that Locally Integrated Support and Wider Com-

munity Focused networks supported well-being better than

other networks, including family-dependent networks,

because they were larger and characterized by more diversity.

This work was extended by Litwin (2001) in his analyses of

Israeli census data collected from individuals 60? years of

age. Using cluster analyses, he also identified five network

typologies and labeled them (1) Diverse, (2) Friends, (3)

Neighbors, (4) Family, and (5) Restricted. These five types

of networks were similar to those identified by Wenger.

T. S. Killian (&) � M. J. Turner

School of Human Environmental Sciences, University of

Arkansas, Fayetteville, AR 72701, USA

e-mail: tkillian@uark.edu

123

J Adult Dev

DOI 10.1007/s10804-014-9183-0

Similarly, he found that network type was related to physical

and psychological well-being. Specifically, Scheffe’s mean

comparisons showed that those with membership in the net-

works labeled Diverse and Friends had significantly lower

rates of disability and higher morale scores than respondents

in networks labeled Family and Restricted.

More recently, Fiori et al. (2006) examined data from

respondents 60? years of age in the Americans’ Changing

Lives study (House 1996). They also identified five

typologies: Non-family/Restricted, Nonfriends, Family,

Diverse, and Friends. These networks were similar to those

earlier observed by both Wenger (1991) and Litwin (2001).

They also found that Diverse and Friends networks

reported the lowest scores of depressive symptomatology,

but did not statistically differ from Family networks, a

finding contrasting earlier research. Fiori et al. (2006)

conducted a series of mediation analyses to demonstrate

that the association between network type and depressive

symptomatology was partially mediated by perceived

support and relationship quality.

These studies suggest that types of social networks matter

for physical and mental well-being of older persons. Some of

the variation in findings across studies may be due to

inconsistencies in the conceptualization and measurement of

social support. One consistent conceptualization of social

support focuses on differentiating instrumental support from

emotional support (Antonucci 1990). Instrumental social

support involves providing direct and tangible assistance,

such as transportation to the doctor, financial assistance, and

other kinds of concrete assistance (House 1981). Emotional

support refers to providing support by showing empathy,

concern, and understanding for another person, usually

based on family histories of social interaction and exchange

(Antonucci 1990). Emotional support may be more impor-

tant than instrumental support for promoting successful

aging and health (Liebler and Sandefur 1998). While rides to

the doctor, and other kinds of instrumental assistance, are

clearly supportive of health and well-being, having loving,

caring, and supportive relationships may be even more

important when negotiating transitions related to midlife and

aging (Fiori et al. 2006; Merz et al. 2009). Unfortunately,

many previous studies of network structures rely on struc-

tural functional dimensions of social support, such as net-

work size, marital status, geographic distance to family

members, and other structural indicators as the underlying

variables used to construct typologies. For example, Fiori

et al. (2006) did not use emotional support variables in their

construction of typologies, but used relationship quality

variables in post hoc mediation analyses.

Fiori et al. (2007) provided one of the few studies that

included emotional support and satisfaction with family and

friends. In their cluster analyses of the Berlin Aging Study

data, they identified six network types labeled Diverse/

Supported, Family Focused, Friend Focused/Supported,

Friend Focused/Unsupported, Restricted-NonFriends-

Dissatisfied, and Restricted-Non-family-Unsupported. They

found that respondents in Family-Focused networks had the

lowest levels of depressive symptomatology, although not

statistically different from Diverse/Supported and Friend-

Focused/Unsupported networks. Although the key innova-

tion in their study was the inclusion of emotional support and

subjective well-being as underlying the typologies, they

were only two of the ten variables in the analyses.

In their study of differences in spousal support across

life stages aged 52 years to 85?, Lima et al. (2008) found

that spousal support was more critical for later midlife

adults than for older participants. The support networks of

those 52–65 years of age for problems with at least one

ADL were limited to one’s spouse. Spousal caregivers of

late midlife adults provided about half of the care provided

by spouses of older adults, partially because many were

still working full time. Although this study did not focus on

emotional support alone, it is one of the few studies that

included midlife adults in a study of spousal caregivers.

Studies that base the construction of social networks on

structural–functional variables seem to find that well-being

is better supported by social networks wider than family

members, but social networks that include relationship

quality or emotional support variables find support from

family members are on par or better than wider social net-

works relative to supporting well-being (Litwin and Shio-

vitz-Ezra 2011). Fiori et al. (2006) suggested their findings

were congruent with research, suggesting that relationships

with friends are more supportive than family relationships

because family relationships are more likely to be obligatory

than friend-focused relationships (Adams and Blieszner

1995; Antonucci and Akiyama 1995). When emotional

support and relationship satisfaction were included in the

construction of support typologies (Fiori et al. 2007), family

networks were equal to, if not better than, other networks in

supporting well-being. Although this finding is consistent

with a large body of research suggesting that relationship

quality and emotional support matter in terms of well-being

(e.g., Merz et al. 2009), few studies have examined empirical

typologies of emotional support.

Using data from the National Health and Nutrition

Examination Survey (NHANES), White et al. (2009) found

that emotional support received from family members was

positively associated with self-reported health status. How-

ever, they collapsed sources of emotional support into the-

oretical dimensions that included Family Only, Family and

Others, Others Only, and None. Because their social net-

works were not empirically derived, their categories may

have missed the richness and complexity with which indi-

viduals cobble together sources of emotional support as they

age.

T. S. Killian, M. J. Turner

123

The current study emphasized sources of emotional

support in constructing an empirically derived typology of

emotional support networks. It also examined how proba-

bility of membership in those networks was related to

emotional well-being. The study had two aims. The first

aim was to identify and label latent networks of emotional

support in midlife and older persons. The second aim was

to examine the association between probability of mem-

bership in emotional networks and emotional well-being.

Two indicators of emotional well-being were assessed:

depressive symptomatology and respondents’ perceptions

of receiving inadequate emotional support.

Methods

Data and Sample

Data from this study came from the 2007–2008 NHANES

(Centers for Disease Control 2009). Respondents in the

NHANES were identified using a complex multistage

stratified cluster design and are representative of the non-

institutionalized population of the USA. Data in the

2007–2008 release were collected from 9,762 respondents

representing a response rate of approximately 75 %. We

only used data from respondents over the age of 40 years

because the focus of this research was on social support in

mid- and late life and emotional support data were not

collected from respondents younger than 40 years. In

addition, respondents who indicated that they had no need

for emotional support were excluded (n = 826) and only

those respondents chosen to provide data during the medical

examination component (MEC) of the study were included

in this analyses, resulting in data from 3,199 adults.

Measures

Emotional Well-Being

The predicted variables in this study were depressive

symptomatology and perceptions of inadequate emotional

support. Data on depressive symptoms were derived from

the Patient Health Questionnaire (PHQ-9) (Kroenke et al.

2001) and collected during the MEC of the interview.

Interviewers recorded responses using computer-assisted

personal interviewing (CAPI). Respondents indicated, on a

four-point scale, the degree to which they had experienced

nine symptoms of depression, such as ‘‘little interest in

doing things,’’ ‘‘feeling bad about yourself,’’ and seven

other symptoms. Responses on each item ranged from 0

indicating ‘‘not at all’’ to 3 indicating ‘‘nearly every day.’’

Responses on each item were summed for a single indi-

cator of depressive symptomatology, with higher numbers

indicative of more symptoms. Only a single item was

available in the secondary data to identify participants’

perception that their emotional support was inadequate.

Therefore, insufficient emotional support was assessed

during the household interview by a single item asking, ‘‘In

the past 12 months, could you have used more emotional

support than you received?’’ Affirmative responses were

coded as 1 and negative responses coded as 0.

Sources of Emotional Support

Respondents were asked questions about emotional support

during the CAPI. The questions were derived from the Yale

Health and Aging Study (Berkman et al. 1993). First, they

were asked if they could, ‘‘count on anyone to provide you

with emotional support such as talking over problems or

helping you make a difficult decision.’’ A negative response

to this item indicated that respondents had no particular

source of emotional support to identify. Respondents who

affirmatively responded were asked, ‘‘in the last 12 months,

who was most helpful in providing you with emotional

support?’’ Interviewers were instructed to ‘‘code all that

apply’’ of 14 possible responses, such as spouse, daughter,

son, friends, coworkers, and nine other possible sources.

Responses were dichotomized so that two indicated an

affirmative response and one indicated no response. Of the

14 possible sources of emotional support, two were excluded

because of low numbers of affirmative responses: club

members (n = 4) and no one (n = 13).

Socio-Demographic Covariates

Variables describing respondents’ ages, sex, minority

identification, and socioeconomic status were included as

socio-demographic covariates. Data about age in NHANES

are right censored so that the maximum recorded age is

80 years. Sex was recoded to create a variable ‘‘female’’ so

that women were coded 1 and men 0. Respondents who

self-identified as a minority were coded as 1 for minority

and other respondents were coded as 0. Married respon-

dents coded 1 and unmarried respondents coded 0.

NHANES provides a ratio of family income to poverty. We

dichotomized this variable so that we could identify fam-

ilies below the poverty threshold (i.e., ratio of family

income to poverty \1). This variable was coded so that 1

indicated a ratio of below the poverty threshold and 0

indicated a ratio above the poverty threshold.

Analyses

All data analyses were done using SAS 9.2 (SAS Institute

(version 9.2) [Software] 2008). Descriptive statistics were

obtained using the SURVEYMEANS and SURVEYFREQ

Evidence from the National Health and Human Nutrition Examination Survey

123

procedures because these procedures accommodate the use

of interview weights and primary sampling units. Using the

‘‘least common denominator’’ principle described in the

NHANES analytical notes (Centers for Disease Control

2006), the sample weights used in these analyses were the

weights associated with MEC questionnaire as the depres-

sion screener was administered during the MEC interview.

Multivariate analyses used the PROC LCA procedure

developed by the Methodology Center and Pennsylvania

State University (Lanza et al. 2011). Multivariate analyses

proceeded in two steps. First, baseline model identification

consisted of estimating models with two classes and adding

classes until the subsequent class did not substantially

improve model estimation. After the baseline model was

identified, covariates were added and estimated. Probabil-

ities of membership in classes, estimated percentages of

each class, and odds ratios estimating the effect of each

covariate on class membership probability were observed.

As with the descriptive statistics, all multivariate analyses

were weighted using the MEC weights.

Results

Descriptive Results

Descriptive sample statistics and variables used in the

analyses are given in Table 1. About 53 % of the sample

was female. About 63 % of were aged 40–59, about 31 %

were between 60 and 79 years old, and 5 % were 80 years

old and older. Slightly more than 64 % were married,

slightly more than 25 % self-identified as minority, and

nearly 11 % lived below the poverty level. The mean score

on depressive symptomatology was 3.14 (SE = .039).

Nearly 17 % indicated that they had needed more emo-

tional support during the 12 months prior to the survey.

Of all the potential sources, emotional support was most

likely received from spouses. Fifty-three percent reported

spousal support. Respondents also reported receiving emo-

tional support from friends (26.44 %), daughters (19.01 %),

siblings (15.56 %), sons (12.49 %), and parents (10.9 %).

(See Table 1).

Latent Class Analysis

The first step in model estimation was to determine the

number of latent classes that should be included in the

model. Relative model fit was assessed by examining four

fit statistics: the G-squared deviance statistic, Akaike

information criterion (AIC), Schwarz Bayesian Criterion

(BIC), and the consistent Akaike information criterion

(CAIC). Smaller numbers on each index represent a better

model fit. While it is expected that model fit will increase

with a greater number of latent classes, the indices also

vary in regard to how much they penalize for complexity.

As shown in Table 2, model fit improves on each index

with each additional latent class up to six. The deviance

statistic and AIC indicate a relatively small level of fit

improvement of a model with seven classes, compared to a

model of six. However, BIC and CAIC indicate a wors-

ening of model fit with an additional seventh class (see

Fig. 1). BIC and CAIC have larger penalties, relative to the

other two indices, for model complexity accounting for

worsening model fit. Therefore, a model with six latent

classes was identified as providing the best relative fit.

Identification and Characterization of Latent Classes

The second step of model estimation included covariates in

the six-class model, identified estimated probabilities of

Table 1 Descriptive statistics on study variables: weighted results

(n = 3,199)

Variables Unweighted (n) Weighted (%)

Socio-demographics

Female 1,622 53.03

Age (years)

40–59 1,522 62.88

60–79 1,390 30.85

80 plus 287 6.27

Married 1,863 64.30

Racial minority 1,541 24.32

Below poverty 576 10.78

Sources of emotional support

Spouse 1,493 52.70

Friends 771 26.44

Daughter 797 19.01

Sibling 571 15.56

Son 540 12.49

Parent 263 10.04

Other relative 238 5.42

Church member 147 3.49

Other 56 1.97

Neighbor 57 1.43

Coworker 29 1.03

Professional 30 .99

Covariates

Depression

None 2,393 76.12

Mild 508 15.73

Major 180 5.26

Severe 35 .94

Inadequate emotional support 585 16.90

T. S. Killian, M. J. Turner

123

membership in each latent class, and assigned a descriptive

label that characterized each class based on the probabilities

of receiving emotional support by source. Labels described

relatively high probabilities of participants receiving emo-

tional support from particular sources and imply low prob-

abilities of receiving support from other sources. The latent

class with highest percentage of estimated membership was

labeled Spouse Restricted (32 %), indicating a high proba-

bility of receiving emotional support from spouses but rel-

atively low probabilities receiving emotional support from

any other source. Other latent classes were labeled Spouses/

Adult Children Focused (24 %), Friends Focused (17 %),

Restricted/Isolated (14 %), Sibling Focused (9 %), and

Diverse (3 %). Estimated probabilities of participants who

indicated receiving emotional support by latent class and by

source of support are provided in Table 3.

Predicting Probabilities of Class Membership

Multinomial logistic regression was used to examine how

socio-demographic variables and covariates were related to

the estimated probabilities of membership in each latent class.

The latent class with the highest percentage of estimated

membership (i.e., Spouse Restricted) was used as the refer-

ence category so that estimates of odds ratios are interpreted in

comparison with the probability of membership in that class.

Spouses/Adult Children Focused

Age and marital status were negatively related to proba-

bilities of membership in the Spouses/Adult Children

Focused class, as compared to the Spouse Restricted class.

Being female and poverty status were positively related to

membership in the Spouses/Adult Children Focused class.

Perceptions of needing more emotional support and

depressive symptomatology were positively related to

membership in Spouses/Adult Children Focused.

Friends Focused

Age, marriage, female, poverty status, and minority status

were all negatively related to the probability of membership in

the Friends Focused class. Perception of needing more social

support was positively related to membership in the Friends

Focused class, while depressive symptoms were negatively

related to membership in the Friends Focused class.

Restricted/Isolated

Probability of membership in Restricted/Isolated was

negatively related to age, being married, and being a

minority. Female respondents had a higher probability of

membership, but poverty was not significantly related to

the probability of membership. Members in this class had a

significantly higher probability of reporting needing more

emotional support, but depressive symptomatology was not

related to membership in this class (Table 4).

Sibling Focused

Age and poverty status were both negatively related to the

probability of membership in the Sibling Focused class. No

other socio-demographic variable was related to probability

Table 2 Latent class analysis goodness of fit indices (GFI) identifying number of classes (n = 3,199)

GFI Number of latent classes

2 3 4 5 6 7

G-squared 1,662.13 1,183.24 1,063.70 946.91 645.00 595.35

AIC 1,712.13 1,259.24 1,165.70 1,074.91 799.00 775.35

BIC 1,863.90 1,489.92 1,475.30 1,463.42 1,266.44 1,321.71

CAIC 1,888.90 1,527.92 1,526.30 1,527.42 1,343.44 1,411.71

df 4,070 4,057 4,044 4,031 4,018 4,005

AIC Akaike information criterion, BIC Schwarz Bayesian Criterion, CAIC consistent Akaike information criterion, df degrees of freedom

Fig. 1 Goodness of fit indices by number of latent classes

Evidence from the National Health and Human Nutrition Examination Survey

123

of membership. Respondents in the Sibling Focused class

had a higher probability of perceived need for more emo-

tional support. Depressive symptomatology was negatively

related to membership in the Sibling Focused class.

Diverse

Age, marital status, poverty status, and minority status were all

negatively related to probabilities of membership in the

Diverse class. Females had higher probabilities of belonging to

the Diverse class compared to the Spouse Restricted class.

Depressive symptoms and perceptions of needing more emo-

tional support were both positively related to the Diverse class.

Discussion

This study’s approach is broadly consistent with previous

research (e.g., Fiori et al. 2006, 2007; Litwin 2001). It

empirically derived latent classes of sources of emotional

support. The key innovation of this study was that the

manifest variables used to construct latent categories of

support were derived from questionnaire items that focused

solely on sources of emotional support. This study was also

distinctive in that midlife individuals over the age of

39 years were included in the sample. Most other research

has focused exclusively on adults in later life. The results

provide an opportunity to draw similarities and contrasts

with previous research describing how people construct

networks of support and how variations in those networks

are related to age, marital status, and well-being.

One key similarity is that latent classes seemed to coa-

lesce around networks consisting of family members, of

non-family members, and a diverse social network. Also,

similar to previous studies, some fit into a category best

described as isolated or restricted. Six latent networks were

identified and labeled Spouse/Restricted, Spouses/Adult

Children Focused, Friends Focused, Isolated/Restricted,

Table 3 Estimation of probabilities of latent class membership by source of emotional support

Sources of

emotional support

Spouse restricted

(31.73 %)

Spouses and adult children

focused (24.55 %)

Friends focused

(17.36 %)

Restricted and

isolated (13.86 %)

Sibling focused

(9.04 %)

Diverse

(3.47 %)

Spouse .9992 .4250 .3848 .0037 .2432 .4729

Friends .0019 .2132 .9944 .0561 .0055 .8788

Daughter .0003 .6594 .0056 .0057 .0227 .7028

Sibling .0034 .0582 .1294 .0412 .9902 .6495

Son .0033 .3989 .0020 .0272 .0173 .5828

Parent .0346 .0371 .0885 .3136 .1129 .3268

Other relative .0087 .0377 .0434 .1004 .0386 .4959

Church member .0234 .0196 .0141 .0343 .0124 .4134

Other .0049 .0101 .0073 .1037 .0001 .0001

Neighbor 0 .0076 .0176 .0105 .0037 .2178

Coworker .0086 .0034 .0159 .0069 0 .0877

Professional .0097 .0057 .0062 .0141 .0001 .0706

Table 4 Multinomial logistic regression of covariates on probabilities of latent class membership: odds ratios (OR) and 95 % confidence

intervals (CI)

Covariates Spouses and adult

children focused

Friends focused Isolated and

restricted

Siblings focused Diverse

OR 95 % CI OR 95 % CI OR 95 % CI OR 95 % CI OR 95 % CI

Age .953 .949–.956 .949 .949–.950 .983 .981–.984 .947 .941–.952 .927 .924–.930

Married .163 .156–.170 .546 .527–.566 .092 .088–.096 .097 .091–.104 .077 .073–.080

Female 1.083 1.043–1.124 .781 .780–.781 1.269 1.262–1.276 .995 .938–1.056 1.094 1.002–1.194

Below poverty 1.126 1.065–1.190 .808 .743–.878 1.052 .993–1.114 .848 .812–.885 .763 .703–.828

Racial minority 1.125 .948–1.335 .603 .552–.658 .803 .793–.813 .988 .875–1.116 .689 .683–.695

Depression score 1.007 1.004–1.010 .991 .984–.998 1.006 .999–1.012 .993 .989–.997 1.011 1.010–1.012

Inadequate emotional support 1.431 1.328–1.541 1.148 1.045–1.261 1.327 1.191–1.478 1.789 1.611–1.987 1.417 1.290–1.556

The class Spouse Restricted was the reference class

T. S. Killian, M. J. Turner

123

Siblings Focused, and Diverse. These latent classes clearly

echo those of previous studies (Fiori et al. 2006, 2007;

Litwin 2001). We focus first on comparisons of member-

ship in latent classes consisting primarily of family mem-

bers and classes not focused on family members. The

diverse social network will be discussed separately because

these class members were likely to receive emotional

assistance from family and non-family.

Families and Emotional Support

There is a strong consensus among researchers that social

support contributes to positive health outcomes (Uchino

et al. 1996; Umberson and Montez 2010), but the specific

role that family members play is less clear. Fiori et al. (2006)

found that membership in family-focused social networks

was not related to depressive symptoms, whereas member-

ship in diverse and friend-focused networks was negatively

related to depressive symptoms. They suggested the findings

may be partially explained by Antonucci and Akiyama’s

(1995) conclusion that family relationships, unlike friend-

ships, are obligatory. They also suggested that family-

focused networks may leave some members isolated from

broader community and friend-focused networks.

Our study found members of the Spouse/Adult Children

Focused class and the Diverse class had more depressive

symptoms compared to those in the Spouse Restricted

class. Further, respondents in the Spouse Restricted class

seemed largely satisfied with the emotional support they

received. Those in the Spouse Restricted class were sig-

nificantly less likely to indicate that their emotional support

was inadequate than members of any other class. More

research is needed, but these findings indicate that spousal

social support is more supportive of well-being than any

other support source when the focus is emotional support

(Fiori et al. 2007).

This study also suggests that when emotional support is

the focus, family members are turned to more than anyone

else. More than 70 % of respondents were estimated to be

members of a family-focused latent class. In contrast, only

15 % of Litwin and Shiovitz-Ezra’s (2011) and 12 % of

Fiori et al’s. (2006) samples were clustered in family ty-

pologies. One explanation for the relatively high number of

respondents in a family-focused class compared to other

research is that social support measures in this study

focused exclusively on emotional support rather than a

more broadly socio-structural-based support measure

including emotional and instrumental support (Fiori et al.

2007). It may also be that the differences are partially a

result of a younger sample. These results are consistent

with studies that find spouses, if available, are the primary

providers of care when it is needed. Lima et al. (2008)

found that younger age was positively related to probability

of receiving care from spouses. They also found that, when

needed, over 80 % of available spouses provided care.

Adult children were only primary caregivers when spouses

were not available.

Another point of contrast in the findings of this study

compared to previous research was increased heterogene-

ity in family-focused latent classes. Specifically, three

different family-focused classes were identified: Spouse/

Restricted, Spouse/Adult Children Focused, and Siblings.

Almost 32 % of respondents in the study characterized

their emotional support as Spouse/Restricted. Nearly 25 %

were members of the Spouse/Adult Children Focused class,

and another 9 % were in the Sibling Focused class. Again,

these findings emphasize the importance of spouses in

providing emotional support. Spouses play a key role in

two of three latent classes. In the Spouse/Restricted class,

the percentage of respondents receiving emotional support

from a spouse was nearly 100 % with the next largest

percentage a parent (about 3.5 %). The second largest class

was clearly focused on adult children. Respondents esti-

mated to be members of this class had a nearly 66 %

probability of receiving emotional assistance from daugh-

ters, and nearly a 40 % probability of receiving assistance

from sons. Spouses were included because members had

42.5 % probability of receiving support from a spouse.

Therefore, spouses were retained in the label Spouses/Adult

Children Focused. Being younger, female, in poverty and

unmarried increased the probability of membership in the

Spouses/Adult Children latent class when compared to the

Spouse Restricted class. This class may represent some of

the more vulnerable sample members, as evidenced by

their reports of higher depressive symptoms and greater

perceptions of receiving inadequate emotional support. Our

models estimated that over 50 % of respondents were in

one of the two latent categories with high probabilities of

receiving emotional assistance from spouses, and an

additional 9 % were estimated to be members of the Sib-

ling Focused support network.

The importance of spouses in social networks is con-

trasted with respondents who indicated that they were not

married. Being married provides midlife and older adults

with advantages in social networks. Not only do many of

them have the close emotional relationship with a romantic

partner, they are also more likely to have access to larger

family networks from which they receive emotional sup-

port. This is clearly seen in the results of this study. In

particular, unmarried persons in this study were signifi-

cantly more likely to receive emotional support in Diverse

and Friends Focused networks, and they were more likely

to be in Isolated/Restricted networks as compared to

married respondents. At the same time, they were more

likely than married respondents to be in family networks

Evidence from the National Health and Human Nutrition Examination Survey

123

not focused on spouses. Research on the relationship

between marital status and well-being is less clear. Broadly,

being married provides advantages for well-being in late

life, but relationship quality is a significant mediator to those

broad effects (Choi and Marks 2011). Moreover, developing

physical limitations is related to increase marital strain and

depressive symptoms over time, especially for men (Caputo

and Simon 2013).

Non-family-Focused Networks

Two non-family latent classes emerged from our goodness

of fit model, but respondents had a much smaller likelihood

of membership than in the family classes. Friends Focused

represented a probability of membership for over 17 % of

the sample. Another 14 % were included in the Restricted/

Isolated class. When compared to Spouse Restricted, the

Restricted/Isolated class was younger, more likely single,

and receiving emotional support from parents. Previous

research has generally found depression to be related to

membership in Restricted Isolated support networks (e.g.,

Glass et al. 2006; Litwin and Shiovitz-Ezra 2011). There-

fore, it was unexpected to find that depressive symptoms

were not related to our respondents’ membership in the

Restricted/Isolated group. It may again be that our focus on

emotional support and the inclusion of midlife adults

contributed to this finding. Consistent with previous

research, our respondents in this class reported needing

more emotional support.

Other researchers identified a similar classification to

our Friends Focused latent class. Both Litwin (2001) and

Fiori et al. (2006) identified a cluster they labeled

‘‘friends’’ as a source of social support. Younger, unmar-

ried, males had a higher probability of being in the Friends

Focused class compared to the Spouse Focused class.

Friends Focused class members reported a need for more

emotional support but indicated fewer depressive symp-

toms. The lower number of depressive symptoms is con-

sistent with both Litwin (2001) and Fiori et al. (2006) who

suggested membership in their friends clusters led to higher

levels of morale and fewer depressive symptoms. However,

neither study included an assessment of the perceived need

for further emotional support. Our findings agree that the

Friends Focused source reduced depression but that friends

alone may not be an adequate source of emotional support

for midlife single males.

Diverse Social Networks

Although membership in the Diverse social network class

included only a small portion of our respondents, it is

consistent with previous research and it bridges classes

focused on family members and classes focused on non-

family members. Members in this class had high proba-

bilities of receiving emotional support from a variety of

persons within and outside of their families. Compared to

Fiori et al. (2006), where 32 % of respondents were in the

diverse class, and Litwin and Shiovitz-Ezra’s (2011) study,

with almost 20 % in the diverse group, this study found

only about 3.5 % of respondents were estimated to be in

this class. Litwin and Shiovitz-Ezra (2011) concluded that

the diverse group represents ‘‘the greatest degree of

sociability’’ among all of their typologies. They determined

that those in the Diverse cluster interacted with a larger

family network as well as more actively socialized in the

neighborhood and community making these individuals

less isolated. One important difference between our find-

ings and theirs was that membership in this category was

negatively related to well-being. Compared to Spouse

Restricted, our respondents in the Diverse category had

more depressive symptoms and were more likely to per-

ceive that their emotional support was inadequate. This

finding is at odds with previous research findings that

Diverse networks were supportive of well-being. The dif-

ference is likely related to the operationalized definition of

social support. The questions from Berkman et al. (1993)

used in the NHANES to define emotional support were

behavior related, such as having someone available to

assist in making a difficult decision or to talk over prob-

lems. It is likely that when an adult seeks emotional sup-

port he or she is more likely to seek out a family member

because of longevity, trust, and confidentiality that char-

acterizes those relationships. It may be that while it is

comfortable to receive transportation to the doctor’s office

or assistance with grocery shopping from friends or

neighbors, family members’ assistance is sought when in

need of a confidant for emotional support.

Conclusions and Limitations

Because this study is based on cross-sectional data, it is not

possible to determine the causal relationships. Moreover, the

study focused exclusively on sources of emotional support.

Comparisons were drawn between the results of this study

and other research examining primarily instrumental sup-

port. Additional research is needed that incorporates mea-

sures of both kinds of support within the same study to more

specifically examine variability in classifications of social

support as well as determinants of membership in specific

classes and differences in the relationship with well-being.

Also, respondents in this study were 40 years old and older,

but comparisons were drawn with studies based on older

participants largely because there are few typological anal-

yses of social support during midlife. Finally, the measure of

perceived inadequate emotional support was based on a

T. S. Killian, M. J. Turner

123

single item. Although clearly a disadvantage, it was also

related to estimated memberships in social network types in

predicted patterns.

Despite these limitations, NHANES data are nationally

representative of the non-institutionalized population of the

USA. Sample weights were used to correct for unequal

probabilities of selection throughout the analyses, and

clusters were used to compute standard errors. Therefore,

the findings related to emotional support are representative

of midlife and older adults in the USA.

A key finding of this research is that it is possible to

identify patterns for how people construct networks of

emotional support. Variations in these patterns are associ-

ated with differences in care recipients’ well-being as

measured by the number of depressive symptoms and

perceptions of adequacy of emotional support. Contrary to

studies that focused primarily on structural support net-

works, our study found family members to be key members

in emotional support networks. Further, emotional support

networks that include family members, especially spouses,

are supportive of well-being.

As healthcare reform places increasing responsibility on

informal support networks, it is critical to increase our

understandings of the most efficient distribution of instru-

mental and emotional tasks required to maintain one’s

health and well-being. Further research is needed to reach

definitive conclusions of the best way to maintain inde-

pendent living while reducing healthcare costs. Informal

care networks are a major component to successfully

navigating increasing healthcare complexity. Increasing

our knowledge about these networks is essential in order to

strengthen them.

Acknowledgments This study is partially funded by the University

of Arkansas Division of Agriculture. The authors thank Mr. James

Duncan for his assistance on this manuscript.

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