Access to Social Network Support and Material Hardship

Abstract

Does access to social network support help protect households from material hardship? In this study, we analyze data from the Survey of Income and Program Participation (N = 28,805) and find that access to assistance from family and friends is associated with a decrease in the likelihood that a household experiences bill-paying hardship, food hardship, or health care hardship. In addition, we examine the interaction between household income and level of available assistance from family and friends. Respondents with higher incomes are able to self-insure against material hardship, and consequently, the protection against material hardship offered by access to assistance is greatest for those respondents with the lowest incomes. Overall, these findings contribute to sociological understandings of how social networks and social isolation shape the well-being of households and suggest an important mechanism for how low-income households are able to avoid material hardship despite inadequate financial resources.

Keywords

inequality poverty and mobility social support material hardship

Introduction

Since at least Du Bois ([1899] 1996), sociologists have pointed to routine exchanges of assistance among families and friends as a common strategy for addressing household budget deficits. In this vein, a number of influential qualitative studies have documented how poor and low-income households often turn to family and friends when faced with a hardship (Dominguez and Watkins 2003; Edin 1991; Edin and Lein 1997; Stack 1974). This body of research shows that exchanges of assistance among members of social networks are important for maintaining relationships and that exchanges of assistance have cultural and symbolic value beyond their utilitarian uses (Edin and Lein 1997; Mazelis 2015; Nelson 2000; Stack 1974).

The overall effects of having access to assistance from family and friends on material well-being are less well known. While past studies have documented in detail the processes by which low-income households incorporate cash and in-kind assistance from friends and family members into their household economic survival strategy (Edin and Lein 1997; Jarrett 1994; Seefeldt and Sandstrom 2015; Stack 1974), few studies have considered the overall association between having access to social network support and household economic well-being. To elaborate on this relationship, we examine the association between access to assistance from family and friends and material hardship. By material hardship, we mean whether a household experiences food shortages or an inability to pay essential bills, or has unmet medical needs.

Past studies of the relationship between access to social network support and material hardship have emphasized low-income households in select cities, leaving understandings of the effects of access to assistance on material well-being in nonpoor households particularly underdeveloped. While income and the risk of material hardship are related, material hardship is not uncommon among middle-income and even affluent households (Iceland and Bauman 2007; Sullivan, Turner, and Danziger 2008). For example, Mayer and Jencks (1989) found that income only explained about 14 percent of the variance in material hardship. More recently, in a sample of New York City residents, Kathryn Neckerman and colleagues (2016) found that about one in three nonpoor households had experienced at least one form of material hardship in the past year.

Previous studies also show that experiencing material hardships has notable consequences. In children, material hardships have been linked with cognitive development, academic achievement, psychosocial outcomes, socioemotional behaviors, and physical health (Alaimo, Olson, and Frongillo 2001; Gershoff et al. 2007; Yoo, Slack, and Holl 2009; Zilanawala and Pilkauskas 2012). In adults, material hardships have been linked with depression, stress, and relationship quality (Heflin and Iceland 2009; Warren and Font 2015; Williams, Cheadle, and Goosby 2015). In short, material hardships are associated with an increased risk of experiencing a range of negative outcomes independent of income.

Only one previous quantitative study directly examines the effects of access to assistance on material hardship. Henly, Danziger, and Offer (2005), drawing on a sample of 652 single mother welfare recipients from an urban county in Michigan in the mid to late 1990s, found that perceived social assistance decreased the likelihood of experiencing material hardship. We build on Henly et al. (2005) and past qualitative studies in important ways. First, by drawing on nationally representative data from the Survey of Income and Program Participation (SIPP), we are able to examine whether the association between access to assistance and material hardship is generalizable beyond small samples drawn from select cities. Second, the research presented in this article includes all levels of income and considers whether the effects of access to assistance are conditional on household income. Third, by separately examining the effects of access to assistance on different material hardship domains, the analysis considers the possibility that access to assistance may not uniformly protect against all types of material hardship. In building on past studies, this research contributes to sociological understandings of how social network support and social isolation shape the well-being of households and the social processes that lead to material hardship.

Background

Access to Assistance and Material Hardship

Past studies have documented the widespread use of assistance from family and friends as a private safety net. In effect, during times of need, family and friends are called on to provide cash, food, housing, child care, and other in-kind support (Edin and Lein 1997; Hansen 2004; Hill and Kauff 2001; Howard 2006; Jarrett 1994; Pilkauskas, Garfinkel, and McLanahan 2014; Polit, London, and Martinez 2000; Radey and Padilla 2009; Seefeldt and Sandstrom 2015; Stack 1974; Teitler, Reichman, and Nepomnyaschy 2004). Having access to assistance from social network members has positive effects on physical and mental health (Hill et al. 2016; House, Umberson, and Landis 1988; Lin, Ye, and Ensel 1999; Umberson, Crosnoe, and Reczek 2010), leads to decreases in the emotional stress associated with economic hardship (Thoits 1995), leads to improved optimism among low-income mothers (Henly 2002; House et al. 1988; Howard 2006), and has a positive association with both parent-child relationships and child health (Hashima and Amato 1994; Leininger, Ryan, and Kalil 2013; Ryan, Kalil, and Leininger 2009; Turney 2013). Yet, while drawing on assistance from kin is common and having access to assistance is generally understood to improve well-being, few studies consider how access to assistance influences the risk of material hardship.

There are obvious direct mechanisms through which having access to assistance from family and friends can lead to a decrease in the risk of material hardship. For example, in the event that a household is unable to pay a utilities bill or is in danger of running out of food, a household with access to assistance from family and friends can call on its social network to provide cash assistance or provide food assistance so that the household can pay overdue bills or avoid hunger. Conversely, a household that lacks a support network and is unable to call on family or friends for assistance must look elsewhere for sources of support like government assistance programs or charitable organizations, which can be difficult and time-consuming to navigate.

Access to assistance may also have an indirect effect on material well-being. In particular, access to assistance from family and friends is important for job searches, maintaining employment, and completing routine errands. Access to social network support may help households avoid hardship not only through direct assistance from network ties but also through indirect mechanisms like providing child care during job searches or providing a ride to work during an emergency.

Therefore, we expect that access to assistance from family and friends is negatively associated with the risk of material hardship. A small body of existing literature supports this. In particular, Henly et al. (2005), drawing on a sample of 652 single mother welfare recipients from an urban county in Michigan, found that perceived access to assistance from friends and family decreased the likelihood of living in poverty, experiencing material hardships like housing and utility upkeep, and engaging in financial coping strategies like visiting a food pantry or pawning possessions. Harknett (2006), drawing on a sample of nearly three thousand single mother welfare recipients from three U.S. counties, found that single mothers with strong social support networks were less likely to rely on public assistance. However, this study did not directly examine the effects of access to assistance on material hardship.

Household Income, Access to Assistance, and Material Hardship

In examining the relationships between income, assistance, and material hardship, it is important to note that if assistance is needed, higher income households are generally embedded in resource-rich networks and are likely to have social ties capable of providing the needed assistance. In other words, income level and the likelihood of receiving assistance in times of need are not independent. A second question is whether income moderates the effect of access to assistance on the risk of material hardship. At higher incomes, access to assistance may become less important because households can self-insure against material hardship, resulting in less need for assistance from others.

At lower incomes, while the need for assistance is greater, the available assistance may be less comprehensive. Specifically, research on the types and levels of assistance received by poor and low-income families shows that when cash transfers do take place, they are often for relatively small amounts (Edin and Lein 1997; Gottlieb, Pilkauskas, and Garfinkel 2014). As a result, poor and low-income families are likely unable to count on financial transfers to cover large expenses like the cost of a mortgage payment. However, low-income families may be able to draw on their family and friends for support that requires available time (such as a ride to a low-cost health clinic) or for types of assistance that do not require the purchase of items (such as sharing meals).

Aside from the potential lack of resources, research on social exchanges among poor and low-income families finds a strong expectation of reciprocity, which could limit the utility of assistance (Dominguez and Watkins 2003; Nelson 2000). For example, in Carol Stack’s (1974) famous account of exchanges in a low-income community, she noted that assistance is “given on the condition that something will be returned” (pp. 34). Edin and Lein (1997) observed a similar relationship, noting that financial and in-kind contributions “were not generally free” (pp. 153). Others have described these exchanges as a form of insurance whereby individuals offer assistance to others when they have the means so that they can draw on assistance from others when they need help in the future (McAdoo 1978; Uehara 1990).

Other research challenges the extent to which reciprocity is expected or the impetus for providing assistance to social network ties. For example, some studies have documented how altruism and kinscripts can lead people to give to others because of intrinsic values related to helping others or putting family well-being above individual well-being (Becker 1974; Stack and Burton 1993). A similar line of research has examined intergenerational financial transfers between parents and children and has found mixed evidence for both altruism and reciprocal exchanges (Altonji, Hayashi, and Kotlikoff 1997; Cox and Rank 1992; Hao 1996; Light and McGarry 2004; McGarry and Schoeni 1995).

Regardless of the motivations of the person providing assistance, past research finds that recipients of assistance often want to reciprocate even if reciprocity is not expected (Mazelis 2015; Nelson 2000) and that exchange-relationships can create stress (Durden, Hill, and Angel 2007; Thoits 1995). Consequently, having access to social support via friends and family can also be a drain on resources. Specifically, as a result of the expectation of reciprocity or beliefs related to shared well-being, the assistance available to poor and low-income families may help with unexpected short-term emergencies but may also lead to hardship because of the felt obligation to return the assistance or to provide assistance to others. In fact, both Stack (1974) and Edin and Lein (1997) were clear about how the need to rely on social exchanges can impede economic well-being, and Pilkauskas, Campbell, and Wimer (2017) show that giving financial transfers to family and friends is associated with an increased risk of material hardship. For low-income households, having access to assistance often comes with the expectation to provide assistance. This burden to provide to other households can increase the risk of material hardship and potentially decrease the value of social network support.

To summarize, theory and empirical findings suggest two alternate ways in which the relationship between assistance and hardship may differ depending on household income. First, the benefit of assistance in preventing hardship may be stronger for low-income households because these households do not have other financial resources to insure against hardship. Conversely, the utility of assistance in preventing hardship may be weaker among low-income families because the burden of reciprocity or expected provision of assistance to social network ties may result in additional experiences of material hardship for these families.

Access to Assistance and Material Hardship Domains

Studies commonly treat indicators of material hardship as if they represent a single construct. In such studies, the processes that produce different types of hardship are assumed to be similar. Heflin, Sandberg, and Rafail (2009) caution against this approach, arguing that different domains of material hardship are related but result from different processes—the processes that lead to, for example, food hardship may not be the same processes that lead to bill-paying hardship. Therefore, it is important to examine the effects of access to assistance on hardship domains separately.

Access to assistance from family and friends may help protect against particular hardships but not all hardships. For instance, the demands placed on network ties to remedy food hardship, while not trivial, are relatively modest compared with the demands needed to remedy other hardships—it is easier for a network tie to share a meal or buy groceries than to cover a missed mortgage payment. In fact, in research on the strategies used by low-income mothers to mitigate material hardship, Colleen Heflin, London, and Scott (2011) found that relying on social network support was more common for some hardships (e.g., food insecurity and clothing hardship) than others (e.g., utility payment). Consequently, access to assistance may only be useful for relatively “inexpensive” hardships.

In addition, past studies find that households are often reluctant to seek assistance from family and friends because of embarrassment or worries about the stigma that comes with seeking help (Desmond 2012; Offer 2012). If stigma makes households hesitant to ask for assistance, then households may only seek out assistance for severe hardship. For example, the consequences of missing a utilities bill payment are typically not as severe as foregoing needed medical assistance. Households may be willing to seek help to avoid severe hardships like food hardship or health care hardship but not less severe hardships like a missed bill payment. Consistent with this argument, past research finds that utility nonpayment is a common strategy to save money so that those resources can be used to avoid other hardships (Heflin et al. 2011). Households with a strong personal safety net may only be willing to rely on that safety net for particular hardships.

Data

The data for this study came from the 2008 panel of the SIPP, a nationally representative household survey of the civilian noninstitutionalized population in the United States. The SIPP is conducted by the U.S. Census Bureau. In the 2008 panel, interviews were conducted every four months, and each panel of the SIPP consisted of both a core interview and a topical module interview. The core interviews contained a standard set of questions on demographics, labor force participation, family income and composition, and program participation. The topical module interviews contained questions on particular subjects that changed from one wave to the next. The sixth wave, fielded during the summer of 2010, and the ninth wave, fielded during the summer of 2011, included a topical module on “adult well-being.” The adult well-being topical module contained a number of questions related to both material hardship and the ability to get assistance from family and friends when needed. While the adult well-being topical module has been a regular component of the SIPP since 1991, the 2008 panel was the first and only panel to include the adult well-being topical module in more than one wave. Due to the time frame applicable to each question, which we discuss in further detail in the “Measures” and “Analytic Approach” sections, we used the measures of material hardship from the Wave 9 interview, while measures of assistance available to households, as well as other individual and household characteristics, came from the Wave 6 interview.

The SIPP collects data for every member of a sample household at least 15 years old at the time of the interview. However, some items are measured at the household level. For these items, the response provided by the household reference person is assigned to all members of the household. The household reference person is the person listed on the lease or mortgage of the home; if more than one person is listed on the lease or mortgage, the SIPP interviewer selects a person from the lease or mortgage to serve as the household reference person. Items related to material hardship and access to assistance were measured at the household level. Therefore, we limit the sample to household reference persons.

In addition, for many items like monthly household income, respondents provide information about the four months since the last interview. This reporting structure leads to a well-documented “seam bias,” where respondents report changes as occurring between two interviews, not during the four-month retrospective reporting period (Moore 2008). While seam bias is not a concern with our analysis, we draw our measures from the most recent reporting month.

We lose some observations to missing data and to attrition. We excluded respondents who were not present in both Wave 6 and Wave 9 (17 percent), resulting in an analytic sample of 28,805 respondents. As a sensitivity test, to determine how individuals lost to attrition compared with those who remained in the sample, we estimated a logistic regression model of the likelihood of attrition. We found that neither our focal independent variable, perceived access to social network support, nor the Wave 6 measure of experiencing any material hardship were significantly associated with attrition. We did find that those lost to attrition were more disadvantaged in other ways. In particular, we found that the unemployed, those who did not own their home, those with worse health, and those without health insurance were significantly more likely to be lost to attrition. Variations in the risk of attrition were modest. For example, we found that the predicted probability an unemployed respondent would be lost to attrition was .02 greater than the predicted probability an employed respondent would be lost to attrition; the predicted probability a respondent who rented would be lost to attrition was .05 greater than the predicted probability a respondent who owned their home would be lost to attrition. We discuss how attrition may influence our findings in the conclusion.

Measures

Access to Routine Assistance

Following others (Harknett 2006; Henly et al. 2005), we operationalized access to assistance as the ability to draw on assistance from family and friends during times of need (measured at Time 1; Wave 6 of the 2008 SIPP). As part of the adult well-being topical module, respondents were asked, “If you had a problem with which you needed help (e.g., sickness or moving), how much help would you expect to get from family living nearby?” Respondents were offered four response categories: all of the help needed, most of the help needed, very little of the help needed, or no help. In a separate question, respondents were asked, “If you had a problem with which you needed help, how much help would you expect to get from friends?”

In terms of preventing hardship, we theorize that the relevant level of perceived available assistance is the highest level of perceived available assistance reported, regardless of whether the assistance comes from friends or from family. We, therefore, combined these measures into a single item, where 1 = the respondent had access to very little or no assistance from either friends or family, 2 = the respondent had access to most of the assistance needed from either friends or family, or 3 = the respondent had access to all of the assistance needed from either friends or family.

Table 1 shows summary statistics for our focal independent variable. Overall, a little over half (53 percent) of respondents reported access to all of the assistance needed, while 15 percent of respondents had access to very little or no assistance.

Table 1.

Weighted Distribution of Access to Assistance.

Access to assistance from friends or family	Sample proportion
No or very little assistance	0.15
Most assistance	0.33
All assistance	0.52

Note. Data are from the 2008 Survey of Income and Program Participation; N = 28,805.

As a sensitivity test, we explored other measures of perceived access to assistance and conducted all the analyses with these alternative measures. First, we examined a measure based on the average of available friend assistance and available family assistance. Second, we ran the analyses with separate measures of family assistance and friend assistance. Finally, we also ran the analyses with the full assistance variables (in effect, without combining little or no assistance). Across all specifications, we obtained substantively similar results.

Material Hardship

We used four measures to assess whether a respondent experienced material hardship. The first three measures were based on individual hardship domains: food hardship, bill-paying hardship, and health care hardship. The fourth measure was a reference variable for whether the respondent experienced any of these hardship domains. By separately considering different domains of hardship, the analysis allowed for the possibility that the effects of access to assistance may vary by the type of hardship—for example, access to assistance may not affect health care hardship in the same way that access to assistance affects bill-paying hardship. All of the dependent variables were measured at time 2 (Wave 9 of the 2008 SIPP).

Our measures of hardship domains are similar to those used in past research with data from the SIPP (Heflin et al. 2009). We used four items to construct a single reference measure of a respondent’s ability to pay bills. Respondents were asked whether there was a time in the past 12 months when they did not pay the full amount of the rent or mortgage, and did not pay the full gas, oil, or electricity bills, and whether the telephone company disconnected service because payments were not made. In addition, respondents were asked whether there was a time in the past 12 months when they did not meet all of their essential expenses. We defined respondents who experienced any of these hardships—not making a full rent or mortgage payment, not paying the full utilities bill, having their telephone service disconnected, or not meeting essential expenses—as experiencing bill-paying hardship.

We used three items to construct a single reference measure of food hardship. The first measure asked respondents whether there was a time in the last four months when the food they bought did not last and they could not afford to buy more. The second measure asked respondents whether there was a time in the last four months when they could not afford balanced meals. The third measure asked, “Which of the following statements best describes the food eaten in your household in the last 12 months: enough to eat, sometimes not enough to eat, or often not enough to eat?” We defined respondents as experiencing food hardship if they reported that they sometimes or often did not have enough to eat in the past 12 months or had either run out of food or had not been able to afford balanced meals in the past four months.

We used two items to measure health care hardship. Respondents were asked whether there was a time during the past 12 months when they or someone in their household needed to see a doctor or go to the hospital but did not go. Similarly, respondents were asked whether they or someone in their household needed to see a dentist but did not go. If respondents reported either of these hardships, we counted that respondent as experiencing health care hardship.

A description and sample proportion for the outcomes measures are presented in Table 2. The probability of experiencing at least one of the forms of hardship in the past year was 28 percent. The probability of experiencing one of the specific forms of hardship ranged from a low of 12 percent for health care hardship to 19 percent for bill-paying hardship.

Table 2.

Description and Weighted Sample Proportions of Outcome Variables.

Variable	Description	Sample proportion
Bill-paying hardship		.19
Utility	Did not pay full gas, oil, or electricity bill
Telephone	Telephone company disconnected service
Essential expenses	Not able to meet all essential expenses
Rent/mortgage	Did not pay full rent or mortgage
Food hardship		.16
Balanced meals	Could not afford balanced meals
Food lasts	Ran out of food and could not afford more
Not enough to eat	Sometimes or often not enough food to eat
Health hardship		.12
Doctor/hospital	Needed to go to doctor or hospital but did not
Dentist	Needed to go to a dentist but did not
Any hardship		.28

Note. Data are from the 2008 Survey of Income and Program Participation; N = 28,805. Material hardship is measured at Time 2 (Wave 9).

Other Covariates

In our regression analyses, we included controls for household income (total household income from all sources in the reference month, divided by 1,000), marital status (married or not married), presence of children under the age of 18 in the home, race/ethnicity (non-Hispanic white, non-Hispanic black, Hispanic of any race, or other race/ethnicity), gender, whether the respondent was born in the United States, educational attainment (did not complete high school, high school graduate, some college, or college graduate), region of residence (Northeast, South, West, or Midwest), whether the respondent had health insurance, whether the respondent was employed, whether the respondent reported owning or renting their home, the respondent’s self-reported health (poor, fair, good, very good, or excellent), and whether the respondent reported frequently feeling anxious or depressed. All control variables were measured at Time 1. Descriptive statistics for these controls are presented in Table 3.

Table 3.

Weighted Descriptive Statistics for Control Variables.

Variable	Mean/proportion	SD
Monthly household income (in 1,000s)	4.65	3.78
Age	49.54	18.06
Educational attainment
Less than high school	0.11
High school graduate	0.24
Some college	0.35
College graduate	0.31
Married	0.5
Child in home	0.33
Race/ethnicity
Non-Hispanic white	0.71
Non-Hispanic black	0.12
Hispanic	0.12
Other race/ethnicity	0.06
Born in the United States	0.86
Female	0.53
Region of residence
South	0.38
Northeast	0.18
Midwest	0.22
West	0.22
No health insurance	0.15
Employed	0.62
Owns house	0.68
Self-rated health	3.6	1.16
Depressed or anxious	0.07

Note. Data are from the 2008 Survey of Income and Program Participation; N = 28,805. Control variables are measured at Time 1 (Wave 6).

Analytic Approach

To explore the relationship between perceived social network assistance from friends and family on the likelihood of experiencing material hardships, we estimated four models, one for each of our four outcomes: experienced food hardship, experienced health care hardship, experienced bill-paying hardship, experienced any hardship. These four models are shown in Table 4. As the outcomes are dichotomous, we used logistic regression to estimate these models. We used survey weights in all multivariate analyses.

Table 4.

Weighted Logistic Regression Models of the Effects of Access to Assistance on Material Hardship.

	Bill-paying	Food	Health	Any hardship
	b (SE)	b (SE)	b (SE)	b (SE)
Available support (Ref = most)
Little or no help	0.447***	0.376***	0.491***	0.463***
	(0.05)	(0.05)	(0.06)	(0.05)
All help	−0.307***	−0.336***	−0.363***	−0.318***
	(0.04)	(0.04)	(0.05)	(0.04)
Monthly household income	−0.112***	−0.120***	−0.096***	−0.108***
	(0.01)	(0.01)	(0.01)	(0.01)
Age	−0.021***	−0.016***	−0.013***	−0.019***
	(0.00)	(0.00)	(0.00)	(0.00)
Educational attainment (ref = < high school)
HS grad	−0.005	−0.093	−0.006	−0.062
	(0.06)	(0.06)	(0.07)	(0.06)
Some college	0.070	−0.154*	0.139*	−0.084
	(0.06)	(0.06)	(0.07)	(0.05)
College	−0.500***	−0.618***	−0.352***	−0.561***
	(0.07)	(0.07)	(0.08)	(0.06)
Married	−0.114*	−0.081^†	−0.025	−0.121**
	(0.04)	(0.05)	(0.05)	(0.04)
Child in home	0.513***	0.311***	0.071	0.407***
	(0.05)	(0.05)	(0.05)	(0.04)
Race/ethnicity (ref = non-Hispanic white)
Non-Hispanic black	0.549***	0.440***	−0.219**	0.469***
	(0.06)	(0.06)	(0.07)	(0.05)
Hispanic	0.100	0.338***	−0.107	0.159**
	(0.07)	(0.07)	(0.08)	(0.06)
Other race/ethnicity	0.170*	0.135^†	0.066	0.114^†
	(0.08)	(0.08)	(0.09)	(0.07)
Born in the United States	0.209***	−0.015	0.107	0.038
	(0.06)	(0.06)	(0.07)	(0.05)
Female	0.169***	0.160***	0.172***	0.155***
	(0.04)	(0.04)	(0.04)	(0.03)
Region (ref = South)
Northeast	0.273***	0.191***	−0.238***	0.280***
	(0.06)	(0.06)	(0.07)	(0.05)
Midwest	0.109*	0.058	−0.110*	0.098*
	(0.05)	(0.05)	(0.06)	(0.04)
West	0.259***	0.196***	0.126*	0.323***
	(0.05)	(0.05)	(0.06)	(0.05)
No health insurance	0.657***	0.409***	0.998***	0.683***
	(0.05)	(0.05)	(0.05)	(0.05)
Owns home	−0.177***	−0.383***	−0.205***	−0.278***
	(0.04)	(0.04)	(0.05)	(0.04)
Employed	0.156***	−0.017	0.231***	0.107**
	(0.05)	(0.05)	(0.05)	(0.04)
Self-rated health	−0.304***	−0.290***	−0.303***	−0.302***
	(0.02)	(0.02)	(0.02)	(0.02)
Depression or anxiety	0.646***	0.701***	0.735***	0.741***
	(0.06)	(0.06)	(0.06)	(0.06)
Intercept	0.380*	0.577***	−0.259	1.232***
	(0.15)	(0.16)	(0.17)	(0.13)

†

p < .1. *p < .05. **p < .01. ***p < .001.

Note. Data are from the 2008 Survey of Income and Program Participation. N = 28,805. Independent variables are measured at Time 1 (Wave 6). Dependent variables are measured at Time 2 (Wave 9).

To examine how income level moderates the relationship between assistance from friends and family and material hardship, we estimated additional logistic regression models that added an interaction term between level of assistance from friends and family and total household income. As the variable for assistance from friends and family is categorical, this is in fact a series of interaction terms, one for each parameter estimating the impact of friend and family assistance. To assess possible threshold effects, we explored treating income as a categorical variable as well. However, the analysis suggested that the moderating effect of income operated in a linear fashion. The models with interaction terms are shown in Table 5.

Table 5.

Weighted Logistic Regression Models of the Effects of Access to Assistance on Material Hardship with Interaction between Income and Access to Assistance.

	Bill-paying	Food	Health	Any hardship
	b	b	b	b
	(SE)	(SE)	(SE)	(SE)
Available support (Ref = most)
No/very little assistance	0.470***	0.586***	0.480***	0.668***
	(0.08)	(0.08)	(0.09)	(0.08)
All assistance	−0.391***	−0.307***	−0.325***	−0.365***
	(0.07)	(0.07)	(0.08)	(0.06)
Household income	−0.121***	−0.104***	−0.092***	−0.104***
	(0.01)	(0.01)	(0.01)	(0.01)
No/very little assistance × Income	−0.007	−0.065**	0.004	−0.053***
	(0.02)	(0.02)	(0.02)	(0.02)
All assistance × Income	0.024^†	−0.008	−0.011	0.013
	(0.01)	(0.02)	(0.02)	(0.01)
Age	−0.021***	−0.016***	−0.013***	−0.019***
	(0.00)	(0.00)	(0.00)	(0.00)
Educational attainment (ref = < high school)
HS grad	−0.007	−0.095	−0.005	−0.066
	(0.06)	(0.06)	(0.07)	(0.06)
Some college	0.067	−0.157*	0.140*	−0.090
	(0.06)	(0.06)	(0.07)	(0.05)
College	−0.501***	−0.622***	−0.351***	−0.564***
	(0.07)	(0.07)	(0.08)	(0.06)
Married	−0.113*	−0.079^†	−0.025	−0.120**
	(0.04)	(0.05)	(0.05)	(0.04)
Child in home	0.513***	0.311***	0.071	0.407***
	(0.05)	(0.05)	(0.05)	(0.04)
Race/ethnicity (ref = non-Hispanic white)
Non-Hispanic black	0.549***	0.441***	−0.218**	0.470***
	(0.06)	(0.06)	(0.07)	(0.05)
Hispanic	0.099	0.338***	−0.106	0.158*
	(0.07)	(0.07)	(0.08)	(0.06)
Other race/ethnicity	0.171*	0.140^†	0.066	0.119^†
	(0.08)	(0.08)	(0.09)	(0.07)
Born in the United States	0.208***	−0.017	0.108	0.036
	(0.06)	(0.06)	(0.07)	(0.05)
Female	0.171***	0.162***	0.172***	0.158***
	(0.04)	(0.04)	(0.04)	(0.03)
Region (ref = South)
Northeast	0.272***	0.188**	−0.237***	0.278***
	(0.06)	(0.06)	(0.07)	(0.05)
Midwest	0.109*	0.058	−0.110*	0.099*
	(0.05)	(0.05)	(0.06)	(0.04)
West	0.260***	0.195***	0.126*	0.324***
	(0.05)	(0.05)	(0.06)	(0.05)
No health insurance	0.656***	0.408***	0.998***	0.682***
	(0.05)	(0.05)	(0.05)	(0.05)
Owns home	−0.178***	−0.385***	−0.205***	−0.280***
	(0.04)	(0.04)	(0.05)	(0.04)
Employed	0.156***	−0.019	0.231***	0.105**
	(0.05)	(0.05)	(0.05)	(0.04)
Self-rated health	−0.303***	−0.289***	−0.303***	−0.301***
	(0.02)	(0.02)	(0.02)	(0.02)
Depression or anxiety	0.645***	0.700***	0.735***	0.739***
	(0.06)	(0.06)	(0.06)	(0.06)
Intercept	0.411**	0.525**	−0.271	1.219***
	(0.16)	(0.16)	(0.18)	(0.14)

†

p < .1. *p < .05. **p < .01. ***p < .001.

Note. Data are from the 2008 Survey of Income and Program Participation. N = 28,805. Independent variables are measured at Time 1 (Wave 6). Dependent variables are measured at Time 2 (Wave 9).

As previously discussed, the time frame for capturing experiences of material hardship is the 12 months prior to Wave 9 of the 2008 SIPP. To establish appropriate temporal ordering with independent variables occurring before or concurrently with the outcome variables, we measure material hardship at Time 2 (Wave 9) and measure all of the independent variables, including perceived access to social network assistance, at Time 1 (Wave 6). As Wave 6 is 12 months prior to Wave 9, the independent variables are measured at the start of the time period for which material hardship is captured, and thus our analytic approach offers a clear account of the relationship between access to assistance and the risk of material hardship in the following year.

To facilitate interpretation of the relationship between access to assistance from friends and families and material hardship, we calculated a series of simulated predicted probabilities for the four outcomes, varying the values of assistance from friends and family. For our final models, which included interactions between income level and family/friend assistance, we also calculated simulated probabilities at varying income levels for each level of assistance from family and friends. The simulated probabilities are shown in Figures 1 and 2.¹

Figure 1.

Predicted probability of material hardship by level of access to assistance.

Figure 2.

Predicted probability of material hardship by level of assistance and household income.

We also conducted supplemental analyses using a lagged measured of material hardship. In principle, the lagged dependent variable models can help address the issue that respondents who have experienced material hardship in the past may also be less likely to have access to assistance. Unfortunately, due to the correlation between the lagged dependent variable and the time-invariant portion of the error term, coefficient estimates from models using lagged dependent variables are biased toward 0 (Hsiao 2003; Keele and Kelly 2006). Hence, the lagged dependent variable model resolves one potential issue of endogeneity (i.e., the impact of past hardship on assistance) while creating a new issue of endogeneity. Therefore, we focus on the results that do not include a lagged measure of material hardship but present the lagged dependent variable models as supplemental analyses.

An alternative and more robust approach to the lagged dependent variable model would be to use within-person fixed effects. Unfortunately, at both waves, respondents were asked about current access to social network support and past hardship (hardships that had taken place in the previous 12 months). As a result, it is not possible to determine the temporal ordering of access to social network support and material hardship when using measures from the same wave of data. For this reason, we used measurements of access to social network assistance from family and friends from the wave of data that is one year prior to when experiences of material hardship were measured. As a result, we only have outcome measurements for each respondent at one wave of data, which precludes estimation of a fixed-effects model.

Findings

Regression Results

Table 4 presents results from weighted logistic regression models. Compared with respondents who expected to receive most of the assistance they may need from family or friends, respondents who expected to receive all the assistance they need were significantly less likely to experience any hardship or any of the specific material hardship domains. Correspondingly, respondents who expected to receive very little or no assistance from friends or family were most likely to experience at least one form of hardship or any of the specific material hardship domains.

Figure 1 illustrates the relationship between level of available assistance from family and friends and the risk experiencing the various forms of material hardship using predicted probabilities. Respondents who expected to receive very little or no assistance from friends or family were almost twice as likely (38 percent) to have experienced at least one of the forms of material hardship (any hardship) in the past year compared with respondents who expected to receive all of the assistance they might need (22 percent). The same general trends hold for each of the specific forms of material hardship: respondents who expected to receive very little or no assistance were much more likely than respondents who expected to receive all the assistance they need to experience any of the specific forms of material hardship. However, as Table 2 shows, the likelihood of experiencing each of the specific forms of hardship varies. In particular, bill-paying hardship is the most common, and health care hardship is the least common.

The other covariates presented in Table 4 were generally as expected. Age and income were both negatively associated with the likelihood of experiencing each material hardship domain. College-educated respondents were less likely to experience material hardships than respondents who did not complete high school; however, differences between those who did not complete high school and high school graduates were not statistically significant, and those with some college were less likely to experience food hardship but not other hardships. Black respondents were more likely to experience most forms of material hardship than white respondents, although black respondents were less likely than white respondents to experience health care hardship. In addition, those who did not own their home and respondents without access to health insurance were more likely to experience most material hardships than their respective reference groups. Similarly, overall health was negatively associated with the risk of material hardship, while reporting depression or anxiety was positively associated with the risk of material hardship. In general, married respondents were less likely to experience hardship, while respondents with a child under the age of 18 in the home were more likely to experience material hardship.

Table 5 shows the results from the models that included interactions between household income and available assistance from family and friends. The findings show that income level moderates the difference in the likelihood of experiencing any hardship between respondents who expected to receive most of the assistance they needed and respondents who expected to receive very little or no assistance. We also found that income significantly moderates the difference between respondents who expected to receive very little or no assistance and respondents who expected to receive all the assistance they needed (analysis not shown). However, income does not significantly moderate the difference between respondents who expected to receive all of the assistance they needed and respondents who expected to receive most of the assistance they needed.

Figure 2 illustrates the relationships between income and level of expected assistance from friends and families in predicting the probability of experiencing at least one form of material hardship (any hardship) and separate hardship domains. The bottom right panel reports estimates of experiencing any hardship. For respondents with no income, the probability of experiencing any material hardship is almost twice as high (52 percent) for those who expected to receive very little or no assistance from friends or family compared with respondents who expected to receive all the assistance they needed (27 percent).² However, as income levels rise, the probability of experiencing any hardship falls for all respondents, regardless of level of assistance, and also differs less and less between respondents with varying levels of perceived assistance from friends and family. In effect, the protection against material hardship provided by assistance from friends and family is greatest for those with low to moderate income.

The other panels in Figure 2 show differences among the specific hardship domains. The overall patterns are similar. Difference in the risk of hardship by access to assistance are substantial at low incomes but decrease as income rises.

Supplemental Analyses

Table 6 reports estimates from models that include a lagged measure of whether the respondent experienced any material hardships at Time 1 (Wave 6). Overall, the sign and statistical significance of the relationship between assistance and hardship is consistent with the results that do not include a lagged measure of hardship (Table 4). However, the magnitude of the relationships between assistance and each type of hardship were somewhat attenuated when a lagged measure of hardship was included in the model. Specifically, the predicted probability of experiencing bill-paying hardship, food hardship, health hardship, or any hardship for those with access to no or very little available assistance was 0.22, 0.19, 0.16, and 0.33, respectively. For those with access to all needed assistance, the predicted probabilities for bill-paying hardship, food hardship, health hardship, or any hardship were 0.17, 0.14, 0.11, and 0.26, respectively.

Table 6.

Weighted Logistic Regression Models of the Effects of Access to Assistance on Material Hardship with a Lagged Measure of Material Hardship.

	Bill-paying	Food	Health	Any hardship
	b	b	b	b
	(SE)	(SE)	(SE)	(SE)
Available support (Ref = most)
Little or no help	0.269***	0.217***	0.332***	0.294***
	(0.05)	(0.05)	(0.06)	(0.05)
All help	−0.136**	−0.190***	−0.209***	−0.167***
	(0.04)	(0.05)	(0.05)	(0.04)
Lagged any material hardship	1.502***	1.287***	1.392***	1.513***
	(0.04)	(0.04)	(0.05)	(0.04)
Monthly household income	−0.087***	−0.098***	−0.070***	−0.086***
	(0.01)	(0.01)	(0.01)	(0.01)
Age	−0.017***	−0.011***	−0.008***	−0.014***
	(0.00)	(0.00)	(0.00)	(0.00)
Educational attainment (ref = < high school)
HS grad	−0.006	−0.103	−0.002	−0.070
	(0.07)	(0.06)	(0.07)	(0.06)
Some college	0.099	−0.145*	0.171*	−0.069
	(0.06)	(0.06)	(0.07)	(0.06)
College	−0.400***	−0.536***	−0.239**	−0.483***
	(0.08)	(0.08)	(0.09)	(0.07)
Married	−0.112*	−0.078	−0.024	−0.119**
	(0.05)	(0.05)	(0.05)	(0.04)
Child in home	0.422***	0.216***	−0.040	0.313***
	(0.05)	(0.05)	(0.06)	(0.04)
Race/ethnicity (ref = non-Hispanic white)
Non-Hispanic black	0.473***	0.360***	−0.340***	0.380***
	(0.06)	(0.06)	(0.07)	(0.05)
Hispanic	0.042	0.303***	−0.163*	0.104
	(0.07)	(0.07)	(0.08)	(0.07)
Other race/ethnicity	0.144^†	0.107	0.029	0.088
	(0.08)	(0.08)	(0.09)	(0.07)
Born in the United States	0.162*	−0.066	0.056	−0.019
	(0.07)	(0.07)	(0.07)	(0.06)
Female	0.110**	0.109**	0.114*	0.100**
	(0.04)	(0.04)	(0.05)	(0.04)
Region (ref = South)
Northeast	0.258***	0.178**	−0.284***	0.263***
	(0.06)	(0.06)	(0.07)	(0.05)
Midwest	0.075	0.031	−0.149**	0.068
	(0.05)	(0.05)	(0.06)	(0.04)
West	0.176**	0.124*	0.042	0.250***
	(0.05)	(0.06)	(0.06)	(0.05)
No health insurance	0.437***	0.208***	0.801***	0.462***
	(0.05)	(0.05)	(0.06)	(0.05)
Owns home	−0.121**	−0.344***	−0.152**	−0.233***
	(0.05)	(0.05)	(0.05)	(0.04)
Employed	0.130**	−0.045	0.203***	0.082^†
	(0.05)	(0.05)	(0.05)	(0.04)
Self-rated health	−0.218***	−0.214***	−0.220***	−0.222***
	(0.02)	(0.02)	(0.02)	(0.02)
Depression or anxiety	0.395***	0.489***	0.508***	0.499***
	(0.06)	(0.06)	(0.07)	(0.06)
Intercept	−0.714***	−0.377*	−1.340***	0.256^†
	(0.16)	(0.17)	(0.18)	(0.14)

†

p < .1. *p < .05. **p < .01. ***p < .001.

Note. Data are from the 2008 Survey of Income and Program Participation. N = 28,805. Independent variables are measured at Time 1 (Wave 6). Dependent variables are measured at Time 2 (Wave 9).

As previously discussed, due to the correlation between the lagged measure and the time-invariant portion of the error term, coefficient estimates from lagged dependent variable models are biased toward 0 (Hsiao 2003; Keele and Kelly 2006). Consequently, the models with a lagged measure of material hardship offer a more conservative estimate of the relationship between access to social network support and material hardship.

Discussion

Sociologists have long been interested in the role social support networks play in helping families get by. This line of research has shown that exchanges of assistance are common, having access to assistance is valuable for the receiver, and providing assistance can produce economic burdens for the giver (Dominguez and Watkins 2003; Edin and Lein 1997; Pilkauskas et al. 2017; Stack 1974). We add to this literature by examining the relationship between perceived access to social network support and material hardship.

The descriptive statistics in this study show that respondents generally report having access to assistance from family and friends. Over one half of respondents reported having access to all of the assistance they would need if confronted with a problem. However, a sizable portion of respondents reported having access to very little or no assistance from family or friends. Nearly one in seven respondents have access to no or very little social network assistance. This absence of support is associated with an increased risk of experiencing material hardships.

We find that increasing levels of perceived access to assistance from friends and family are associated with sizable reductions in the likelihood of a variety of forms of material hardship including food hardship, health care hardship, bill-paying hardship, and the probability of experiencing at least one of the aforementioned forms of hardship. Overall, access to assistance is associated with reductions in the risk of material hardship across all of the observed hardship domains. In addition, the benefit of assistance from friends and family is inversely proportional to income. For respondents with very low income, support from family and friends serves to cut the probability of potential material hardships approximately in half. As incomes rise, assistance from family and friends plays much less of a role in terms of preventing material hardship. For poor and low-income households, having access to assistance from family and friends is particularly valuable.

Past research finds that poor and low-income households often provide assistance to social network ties as a form of social insurance—households give assistance to family and friends when they are able so they can draw assistance from family and friends when needed (McAdoo 1978; Stack 1974; Uehara 1990). Our findings underscore the potential for social network support to serve as a form of social insurance. Middle-income and more affluent households can self-insure against the risk of material, making access to social network support less consequential. For poor and low-income families, access to social network support is strongly related to the risk of material hardship.

Similarly, past studies find that material hardships are often the results of unalike processes, that strategies for addressing hardships vary across material hardship domains, and suggest that households may be less willing to seek help for less severe hardships. However, we find that access to social network support is positively associated with a decreased risk of experiencing material hardship across all hardship domains. We suspect this may be attributable to the indirect effects of social network support. In particular, in addition to direct assistance, indirect social network support such as a ride to work or emergency child care can help families avoid hardship by allowing families to maintain employment and be better positioned to access resources. Research that distinguishes between potential direct and indirect effects of social network support is needed.

While the data used in this study allow for greater generalizability than past studies, the findings are limited by our measures and the timing of data collection. First, we rely on the subjective perceptions of respondents vis-à-vis the level of support they expect to be able to receive. By using a measure based on perceived support rather than received support, we avoid conflating respondents that do not need support with respondents that do. Measures that rely on received support treat all respondents that do not receive support—both those that need support and those that do not—as one and the same. Nonetheless, past studies find variations along social and demographic lines in who is willing to activate social support networks during times of need (Mazelis and Mykyta 2011), and show that social support networks can be unreliable (Henly 2002). It is possible that perceptions of available assistance may either overestimate or underestimate the actual level of assistance available, and measures of perceived assistance are unable to speak to the willingness of individuals to activate assistance.

In addition, we were only able to capture hardship events over the course of a single year. As with any event that does not impact a large proportion of the population at any given time, repeated measurements over a longer time frame would allow for more precise measurement of specific respondents’ risk of experiencing hardship. In addition, this study focuses on short-term well-being, while access to assistance may have long-term effects that this study is unable to capture.

We also lost observations to attrition. While we found that neither perceived access to assistance nor experiencing any material hardship were associated with subsequent attrition, we found that those lost to attrition were less likely to own their home, more likely to be unemployed, and more likely to be disadvantaged in other ways. Our results also show that access to assistance is most strongly linked to material hardship for more disadvantaged respondents. Consequently, our findings may underestimate the association between access to social network support and material hardship.

Finally, the data were collected during a recession in 2010 and 2011. Households likely had greater need for assistance and were also in a worse position to provide assistance. To the extent that the recession depressed available assistance, then the descriptive statistics may underestimate typical levels of available assistance. If the recession negatively affected the ability of households to rely on social network members for expected assistance, then our findings may underestimate the relationship between access to assistance and material hardship.

Despite these limitations, the findings build on past studies and suggest needed areas for future research. This study shows that access to assistance from family and friends is associated with a decrease in the risk of material hardship. Past sociological research on exchanges of assistance is still relevant today, and researchers interested in the economic well-being of households should not dismiss familial and friendship ties. This study also draws attention to differences in the benefits associated with access to assistance by household income. For low-income households, access to assistance is valuable. However, Harknett and Hartnett (2011) find that economic hardship is negatively associated with perceived available assistance: the households that see the greatest benefit from access to assistance are also the households least likely to have access to assistance. This may create a self-reinforcing cycle where households most in need of assistance do not have access to assistance, which leads to an even greater need for assistance and even greater social isolation. Future research should explore whether the experience of material hardship is associated with a decrease in available assistance.

Finally, past research notes a modest correlation between household income and the risk of material hardship (Iceland and Bauman 2007; Sullivan, Turner, and Danziger 2008), but many poor and low-income households are able to escape material hardship, while more affluent households experience material hardships despite having seemingly adequate resources. Our findings suggest that variations in social network support is a contributor to these unexpected differences across income.

Footnotes

Acknowledgements

The authors benefitted from a workshop on the use of the Survey of Income and Program Participation (SIPP) at the University of Michigan as part of the NSF-Census Research Network (NCRN, NSF SES-1131500). Both authors contributed equally to the manuscript and are listed in alphabetical order.

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.

Notes

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