Abstract
Despite growing attention to other social needs like food and housing insecurity, financial strain, defined as having difficulty making ends meet or lacking money for basic needs, is under-recognized. Inconsistent labels and measures have made the literature difficult to unify. We used many synonyms for financial strain to systematically identify 199 U.S. studies (316 papers) that used financial strain measures that were operationally consistent with our definition as predictors of health among adults. We thematically coded financial strain measures for content and synthesized evidence based on measure and methods. Financial strain was measured by self-reported lacking money for basic needs (119 studies) and/or difficulty making ends meet (n=132), and less commonly additionally based on coping strategies (n=23), satisfaction with finances (n=14), worry about finances (n=22), the anticipation of strain (n=14), and/or lacking money for leisure (n=29). Regardless of measure, financial strain was associated with poorer mental, physical, biological, and functional health, worse health behaviors and more social needs. Associations were found across diverse and population-based samples and when accounting for other socioeconomic factors and even intermediating health factors. Results demonstrate predictive validity for two different one-item screening tools. Furthermore, the vast evidence linking financial strain to health highlights an urgent need for policy action addressing financial strain to advance health equity.
Trial Registration: The review protocol was registered on Prospero (CRD42020210511).
Keywords: Socioeconomic factors, financial strain, health equity, social needs
Introduction
Despite recent calls to screen for and address social determinants of health as part of routine healthcare for adults in the United States (U.S.), there has been little attention paid to financial strain and its effects on health-relevant outcomes and health disparities. This is an important gap because financial strain – defined as difficulty making ends meet or lacking basic needs (Pearlin et al., 1981) – typically co-occurs with other economic constraints, such as housing and food insecurity, but is conceptually distinct and likely operates independently of them. (DeLuca & Rosen, 2022; Gundersen & Ziliak, 2015) Underscoring the importance of examining financial strain as a determinant of health, both the Centers of Medicare and Medicaid (CMS) and the National Academy of Medicine (NAM) have recommended screening for the presence of financial strain during health care encounters by simply asking people, “How hard is it for you to pay for the very basics like food, housing, medical care, and heating?”. (Billioux et al., 2017) Financial strain is believed to be a fundamental cause of multiple health outcomes, contributing to health disparities through multiple intervening mechanisms (Phelan et al., 2010). Recently, a conceptual framework for understanding financial strain (Tucker-Seeley & Thorpe, 2019) and a multi-level framework for addressing financial strain have both been developed (Nykiforuk et al., 2023), providing tools for addressing financial strain. However, there are two limitations to the financial strain science. Firstly, there are inconsistent ways to measure and label financial strain across health domains and settings (Tucker-Seeley & Thorpe, 2019). Secondly and relatedly, there has been no systematic attempt to evaluate the associations between financial strain and health-relevant outcomes. This presents an opportunity to compare findings across measures, ascertaining predictive validity and clinical relevance of measures of financial strain. This study sought to (1) systematically survey financial strain measures that have been used in research; and (2) synthesize the evidence linking financial strain to health-relevant outcomes among U.S. adults.
Methods
Data Sources and Searches
A systematic literature review (e.g. using systematic methods to select, critically appraise and synthesize research findings) was undertaken to describe financial strain measures and summarize their associations with health-relevant outcomes among adults. A systematic literature search was initially conducted in 2019 using PubMed, Web of Science, and PsychINFO to identify manuscripts published in English and was updated in 2022. Because the term “financial strain” is not used consistently in the literature, search terms included many synonyms for financial strain (e.g. ‘economic hardship’, ‘financial stress’, ‘income inadequacy’, and ‘income insufficiency’) and health-relevant terms (see Supplement 1).
Study Selection
Screening and data extraction were conducted by the study team using Covidence. (Veritas Health Innovation, 2019) Because the term “financial strain” is not used consistently, inclusion criteria focused on the operationalization of financial strain, encompassing indicator(s) that were consistent with our theoretical definition of financial strain (e.g. experiencing difficulty making ends meet and/or meeting basic needs (Pearlin et al., 1981)). Additional inclusion criteria were measuring financial strain (a) of individuals/households (i.e. not of a health system or government), (b) self-reported (i.e. not objective like income, debt, job loss), (c) modeling financial strain as an independent variable in relation to a health-relevant outcome, (d) including a sample of U.S. adults (due to differences in economic conditions, the social safety net and health care access based on country) and (e) being published in 2009 or later (Supplemental Table 1). Two reviewers screened each manuscript. Screening was first conducted based on title and abstract (inter-rater agreement was 71%) and then based on the full text (inter-rater agreement was 81%).
Data Extraction and Quality Assessment
Two blinded and trained abstractors extracted data for each paper (extraction form shown in Supplement 2). Conflicts for screening or data extraction were adjudicated by study team leaders based on discussion in regular team meetings. The National Institutes of Health Study Quality Assessment Tools were used to assess the quality of extracted studies. No studies were excluded due to poor quality. Since socioeconomic factors may be both strong predictors of financial strain and separately influence health, we noted whether the analyses presented in each paper adjusted for at least one of the following well-established socioeconomic predictors of health and well-being: employment status, educational achievement, household income, poverty level, and/or income-to-needs ratio. Because financial strain was not necessarily part of study research questions, some researchers statistically adjusted for health factors that likely lie on the causal pathway rather than confound the relationships between financial strain and outcomes. To account for this, we noted whether presented results adjusted for the following health factor(s): body mass index (BMI) or obesity/overweight, self-rated health (e.g., overall health, subjective mental health and/or subjective physical health), functional limitations, and/or presence of chronic condition(s) (e.g. diabetes, HIV, hypertension, cardiovascular disease, obesity, and/or mental illness diagnosis or symptoms), as well as baseline values for study outcomes in longitudinal analyses. Prior to synthesizing findings, papers arising from the same study were grouped together to avoid overstating the research findings. When study names were not available for grouping, publications were grouped if the following study characteristics matched: selection criteria, recruitment practices, location, setting and/or data collection years.
Data Synthesis and Analysis
Synthesis and analysis had two phases: 1) qualitative analysis of financial strain measures and 2) synthesis of findings by study design, category of financial strain measure, and statistical adjustment methods. First, we described the types of questions by performing content analysis on each financial strain measure. Coding was conducted independently by two reviewers. We resolved discrepancies by discussion until consensus was achieved. Measurement description information was compared across publications using the same data to validate coding. We then categorized codes. Two categories were defined a priori based on the study selection criteria, including “lacking money for basic needs” and “having difficulty making ends meet.” Five more related categories were generated based on inductive coding of financial strain measures, including relying on coping strategies, satisfaction with their financial situation, experiencing stress or worry about finances, anticipating future financial strain and lacking money for leisure (Table 1).
Table 1.
Categories of financial strain questions that were used in reviewed studies and exemplars of items used
| Category | Exemplars |
|---|---|
| Lacking basic needs 119 studies / 206 papers | For multiple-item measures: ‘In the past 12 months, how frequently were you unable to: 1. Buy the amount of food your family should have? 2. Buy the clothes you feel your family should have? 3. Pay your rent or mortgage? 4. Pay your monthly bills? (Bazargan et al., 2023) For single-item measures (Billioux et al., 2017): “How hard is it for you to pay for the very basics like food, housing, medical care, and heating?” |
| Difficulty making ends meet 132 studies / 176 papers |
For multiple item measures: “In general, how do your (family’s) finances usually work out at the end of the month - do you find that you usually end up with some money left over, just enough money to make ends meet or not enough money to make ends meet?” (Brown & Barrett, 2011) For single-item measures: “How difficult is it for you to pay your monthly bills?” (Slopen et al., 2012) |
| Coping strategies 23 studies / 41 papers | In the past 12 months, 1. did you receive free food or meals? 2. did you borrow money from friends or family to help pay bills? 3. did you move in with other people even for a little while because of financial problems? 4. did you stay at a shelter, in an abandoned building, an automobile or any other place not meant for regular housing even for one night? (Daundasekara et al., 2021) |
| Satisfaction 14 studies / 18 papers | “How satisfied you are with your present financial situation” (Rogers, 2019) |
| Stress/worry 22 studies / 30 papers | “How often do you worry about being able to meet normal monthly living expenses?” (Bassett et al., 2021) |
| Anticipatory financial strain 14 studies / 14 papers | “It would be hard for you to find the money to cover an unexpected expense, such as a medical bill or repair that was $500 or more.” (Banyard et al., 2017) |
| Lacking wants 29 studies / 30 papers | “Do you have enough money for the leisure activities you/your family want?” (Rios & Zautra, 2011) |
In the second phase, study findings were synthesized in three ways. First, data were synthesized based on study design, to compare cross-sectional to longitudinal associations, which better address reverse causality. Secondly, we synthesized findings by category of financial strain measure identified in the qualitative phase. Finally, we synthesized based on whether the presented results adjusted for other socioeconomic factors and/or potentially mediating health factors.
Results
A total of 316 papers from 199 studies were included in this review (Figure 1). Most studies were cross-sectional (n=150), and most papers reported cross-sectional findings (n=198), but 63 studies (118 papers) presented at least some longitudinal findings. Longitudinal analyses included cohort studies, trials and program evaluations. Interventions typically addressed psychosocial or behavioral factors; none of the interventions described in the included papers directly addressed financial strain. Most papers (n=207) presented results that statistically adjusted for socioeconomic factors other than financial strain and 129 papers presented results that adjusted for health factors.
Figure 1.
Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flowchart summarizing the identification and selection of studies included in this systematic literature review of papers examining financial strain and health relevant outcomes among adults.
Financial Strain Measures
Based on selection criteria, all studies measured financial strain based on lacking money for basic needs (n=119) and/or experiencing difficulty making ends meet (n=132) (Table 1). Fewer studies included questions about relying on coping strategies (n=23), satisfaction with financial situation (n=14), experiencing stress and/or worry about finances (n=22), anticipating future financial strain (n=14) and lacking money for leisure or recreation (n=29) (see Table 1 for exemplars). Because the majority of financial strain measures using more than one indicator relied heavily on questions about lacking money for basic needs and/or experiencing difficulty making ends meet (Table 1), we compared these two key categories of financial strain measures and found that they largely have similar reliability (Table 2).
Table 2.
Summary of measures of financial strain used in reviewed studies
| Category of financial strain measure | Number of studies (Number of papers) | Number of items | Cronbach α range |
|---|---|---|---|
| Single item | |||
| Lacking basic needs | 36 (54) | 1 | N/A |
| Difficulty making ends meet | 50 (75) | 1 | N/A |
| Multiple items | |||
| Lacking basic needs | 75 (136) | 2–26 | 0.71 – 0.96 |
| Difficulty making ends meet | 80 (108) | 2–22 | 0.63 – 0.94 |
| Both lacking basic needs and difficulty making ends meet | 52 (74) | 2–37 | 0.61 – 0.95 |
Although most studies used more than one indicator to measure financial strain, 85 studies (117 papers) used a single indicator (Table 2). Among those using a single indicator, 36 (Table 2) asked about lacking basic needs and typically (n=13 studies) used the question recommended by the NAM and CMS, providing evidence of predictive validity for this one-item screening tool. Notably, 50 studies (75 papers) asked about difficulty making ends meet with a single indicator (Table 2), thus providing evidence of predictive validity to support the use of an alternative social needs screening question, such as “How difficult is it for you to pay your monthly bills?”. Importantly, associations between financial strain and health outcomes did not tend to differ based on the type of financial strain measure (Tables 3 & 4).
Table 3.
Summary of cross-sectional associations between financial strain with health outcomes among U.S. adults
| Study, sample, & setting | Financial strain measurement | Associations between financial strain with outcomes | Socioeconomic adjustment | Health adjustment | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| # of items | Lacking basic needs | Difficulty making ends | Coping Strategies | Financial satisfaction | Financial stress/worry | Anticipating strain | Lack of money for wants | ||||
| Acute myocardial infarction registry (n = 3410) | 1 | X | Higher C-reactive protein at 30 days after a myocardial infarction (Qintar et al., 2017) | X | |||||||
| Aged 12+ in rural Appalachia (n=2565) | 5 | X | X | X | X | Poorer health-related quality of life, (Banyard et al., 2017) lower life satisfaction, higher posttraumatic growth and more trauma symptoms (Hamby et al., 2018) | |||||
| Hospice patients with cancer in Utah, Massachusetts, & Florida 2010 (n=102) | 1 | X | More anxiety and depressive symptoms but not associated with positive affect/well-being (Tay et al., 2022) | ||||||||
| Korean women who immigrated to the US in an East Coast city (n=130) | 8 | X | X | More emotional and somatic symptoms of well-being (Lee et al., 2016) | X | ||||||
| Aged 100+ Iowans (n=152) | 6 | X | X | X | More limitations in activities of daily living, cognitive impairment and depressive symptoms among those in institutional settings, but not community-dwelling (Garasky et al., 2012) | ||||||
| Aged 18+ near Dallas (n=238) | 8 | X | Higher odds of food insecurity (Hernandez et al., 2017) | X | |||||||
| 9 | X | X | X | Higher risk of smoking and more cigarette use among smokers (Waters et al., 2019) | X | ||||||
| Aged 50+ with arthritis and comorbidities in Austin (n=117) | 1 | X | Less self-efficacy and self-reported health care utilization but not associated with quality of life (Zhang et al., 2020) | X | |||||||
| Aged 65+ with chronic condition(s) in Maryland retirement communities (n=146) | 3 | X | X | Not associated with odds of frailty (Hladek et al., 2020) | |||||||
| Aged 40–65 in Phoenix, Arizona (n=680) | 6 | X | X | Higher IL-6 but not associated with CRP (Sturgeon et al., 2016) | X | X | |||||
| Adults at two Midwest dialysis units (n=109) | 7 | X | X | X | Higher levels of illness intrusiveness (Boehmer et al., 2016) | X | |||||
| Heart disease patients hospitalized at Vanderbilt (n=1527) | 1 | X | Less adherence to home medication regimens and poorer overall health (Osborn et al., 2017) | X | X | ||||||
| Adults in Livingston or Selma, Alabama (n=179) | 2 | X | Not associated with awareness of hospice (Noh et al., 2022) | ||||||||
| Recruited from Southwestern unemployment centers (n= 174) | 3 | X | X | Less psychological well-being (Huffman et al., 2015) | |||||||
| Adults with a significant limb loss (n=46) | 1 | X | Poorer role function and emotional health, but not associated with physical function, pain, general health, social functioning, vitality or mental health (Lee et al., 2020) | ||||||||
| Adults 35–80 with chronic condition(s) in St. Louis, Missouri (n=270) | 2 | X | X | More likely to spend less on basic needs to pay for medication (Rohatgi et al., 2021) | X | X | |||||
| Adults with tobacco use recruited online (n=234) | 6 | X | X | X | X | More depressive symptoms (Rogers, 2019) | |||||
| African American fathers in a parenting program in Midwestern cities (n=347) | 1 | X | More depressive symptoms (Tsuchiya et al., 2018) | X | |||||||
| African American females with breast cancer in a psychoeducational trial in urban Pennsylvania and Ohio (n=101) | 1 | X | Lower levels of knowledge about chemotherapy but not associated with belief in the necessity of chemotherapy (Jiang et al., 2016) | X | X | ||||||
| African American men 18+ recruited from a community health fair in Ohio (n=243) | 1 | X | Lower health self-efficacy (Tucker-Seeley, Mitchell, et al., 2015) | X | |||||||
| African American men 30–50 near San Francisco (n=92) | 1 | X | Not associated with shorter telomere length (Schrock et al., 2018) | X | |||||||
| African American mothers living with at least one child (n=305) | 1 3 |
X | X | X | X | X | Lower life satisfaction, poorer emotional well-being, more depressive symptoms and anxiety symptoms (Williams et al., 2021) | X | |||
| African American parents 18+ in public housing in Connecticut with depression (n=135) | 6 | X | X | More post-traumatic stress symptoms (Holmes et al., 2021) | |||||||
| African Americans 18+ in public prenatal clinics in Northern California (n=117) | 1 | X | More depressive symptoms and everyday discrimination, but not associated with lifetime trauma or social conflict (Dailey & Humphreys, 2011) | ||||||||
| African-American mothers of adolescents in economically disadvantaged neighborhoods in the Northeast (n=200) | 7 | X | X | More depressive symptoms and less optimism (Taylor et al., 2014) | X | ||||||
| Amazon Mechanical Turk adult respondents (n=131) | 5 | X | X | X | Lower meaning in life scores (Abeyta et al., 2017) | X | |||||
| Amazon Mechanical Turk adult respondents (n=231) | 7 | X | No association with medication adherence or rates of skipping medications (Strickland et al., 2019) | ||||||||
| Amazon Mechanical Turk respondents (n= 498) | 4 | X | X | Higher likelihood of workplace accidents and a higher likelihood of under-reporting workplace accidents (Petitta et al., 2020) | |||||||
| Amazon Mechanical Turk community-dwelling respondents (n=538) | 5 | X | X | X | More anxiety symptoms, more depressive symptoms and higher positive affect but not associated with life satisfaction (Hou et al., 2021) | ||||||
| Amazon Mechanical Turk adult respondents (n=1070) | 8 | X | X | X | X | Higher odds of using any nicotine product and combustible tobacco product(s) but not electronic nicotine product(s) (Rogers et al., 2018) | X | ||||
| Black/Latino adults 18–65 with HIV care near New York City (n=512) | 1 | X | Not associated with polysubstance use risk scores(Cleland et al., 2021) | ||||||||
| Bengali immigrant New York City parents (n=73) | 1 | X | More parent tension and depressive symptoms but not associated with sleep problems (Barajas-Gonzalez et al., 2021) | X | |||||||
| Black Baltimore senior housing adults 50+(n=450) | 1 | X | Not associated with sleep quality (Gamaldo et al., 2014) | X | X | ||||||
| Black adults 25– 65 in Tallahassee (n=128) | 1 | X | More depressive symptoms (Fuller et al., 2021) | ||||||||
| Black and White men who have sex with men 18+ with HIV in San Francisco, California and Syracuse, New York (n=77) | 1 | X | Less adherence to anti-retroviral treatment (Simmons et al., 2021) | ||||||||
| Black cis-gender men who have sex with men 18–29 in Dallas & Houston, Texas (n=1732) | 1 | X | Higher risk of sexual violence victimization, and among those who experienced sexual violence associated with a higher risk of experiencing it when they were <16 years of age (Siconolfi et al., 2021) | X | X | ||||||
| Black or White female breast cancer patients 18+in Pennsylvania & Ohio (n=119) | 1 7 |
X | X | X | X | More symptom distress (Mazanec et al., 2021) | |||||
| Black, Hispanic, or White sexual and gender minorities assigned female at birth 16–20 (n=308) | 3 | X | X | Higher risk of experiencing or perpetrating psychological IPV, physical IPV and sexual IPV (Whitton et al., 2021) | |||||||
| Boston nursing home employees (n=416) | 1 | X | Higher odds of high depressive symptoms (Okechukwu et al., 2012) | X | |||||||
| Cancer survivors 18+ treated at St. Jude Children’s Research Hospital (n=3906) | 1 | X | Not associated with suicidal ideation (Lubas et al., 2020) | X | X | ||||||
| Cancer survivors within 1–3 years of diagnosis and their partners 21–58 years (n= 98) | 1 | X | Poorer physical & mental quality of life and more pain & fatigue among survivors but not associated with quality of life or caregiver strain among partners (Lyons et al., 2022) | X | |||||||
| Carolina African American Twin Study of Aging; African American twins born between 1913 and 1975 (n=699) | 1 | X | Higher odds of having a limitation in activities of daily living and more depressive symptoms but not associated with lung function or cognitive status (Szanton et al., 2010) | X | X | ||||||
| Caregivers of a child with cancer at a large Southern medical center (n=163) | 2 | X | X | Higher risk of lacking social support, and more child problems, sibling problems, family problems, and parent stress reactions, and a lack of family coping ability at baseline (Karlson et al., 2013) | |||||||
| Chicago Community Adult Health Study; 18+(n=2093) | 9 | X | X | X | X | Higher odds of being both overweight and obese (Cuevas et al., 2019) | X | ||||
| Child Community Health Network study, fathers during the post-partum period in Baltimore & Washington D.C. (n=203) | 5 | X | X | X | Not associated with being married or being in a relationship with their baby’s mother (Kerr et al., 2018) | X | |||||
| Chinese adults 60+ in Chicago (n=2988) | 1 | X | Fewer cognitive activities and social activities (Lai et al., 2019) | X | |||||||
| Chinese immigrants 18+in Maryland (n=247) | 1 | X | More psychological distress (Lee et al., 2015) | X | |||||||
| Chronic heart failure patients in Pennsylvania & Delaware (n=265) | 1 | X | Poorer self-rated health (Carlson et al., 2013) | X | |||||||
| University counseling center clients 18+ (n=96) | 1 | X | Not associated with a composite score capturing symptom distress, interpersonal relationships and social role (Hawley, 2020) | X | |||||||
| Cohabiting couples < 200% poverty co-parenting a child near Denver (n=588) | 1 1 |
X | X | X | Differences in coping strategies based on financial strain, with the highest scores among those with high coping and negative cognition coping (Perzow et al., 2018) | ||||||
| Low-income, Baltimore adults 65+ with functional limitations in home-based trial | 3, 1a | X | X | Less patient activation (n=277) (Gleason et al., 2016) | |||||||
| 1 | X | Not associated with limitations in Activities of Daily Living or Instrumental Activities of Daily Living (n=300) (Liu et al., 2022) | |||||||||
| Community dwelling older adults 65+ with chronic illness(es) (n=159) | 3 | X | X | Higher IL-6 levels in sweat (Hladek et al., 2022) | X | ||||||
| Community-dwelling Northern Indiana adults (n=282) | 4 | X | X | X | X | Higher perceived stress scores (Scott et al., 2011) | |||||
| Community-dwelling African American adults 55+in a disadvantaged part of Los Angeles | 3 | X | Higher odds of insomnia and more severe insomnia symptoms (n=398), (Bazargan et al., 2019) more depressive symptoms (n=740), (M. C. Evans et al., 2019) more pain (n=740), (M.C. Evans et al., 2019) and lower odds of untreated depression but not associated with odds of treated depression (n=740). (Cobb et al., 2020) Among those aged ≥65 years, lower memory scores (n=399) (Assari et al., 2020) but not associated with odds of current smoking among subset with cardiometabolic condition(s) (n=576) (Shervin Assari, James L. Smith, Marc A. Zimmerman, et al., 2019) or drinking among those with diabetes (n=231) (Shervin Assari, James L. Smith, Mohammed Saqib, et al., 2019) | X | X | ||||||
| 5 | X | X | Poorer adherence to blood pressure medications but better adherence to recommended lifestyle modifications (n=338) (Adinkrah et al., 2020), better mental and physical quality of life scores (n=905) (Bazargan et al., 2023) and, among those aged ≥65 years higher odds of currently smoking and higher odds of drinking (n=619) (S. Assari et al., 2019) but not associated with use of opioid-based medication or psychotropic medication among those aged ≥65 years with cardiometabolic disease (n=74) (Bazargan et al., 2020) | X | X | ||||||
| 3 | X | Higher likelihood of smoking and binge drinking, more depressive symptoms and chronic conditions, more pain, poorer self-rated health and more sick days (n=740) (Evans et al., 2020) | |||||||||
| 5 | X | X | Lower odds of having a primary care or emergency department visit in the past year but not associated with inpatient hospitalization (n=905) (Cobb et al., 2022) | X | |||||||
| Middle aged adult women with osteoarthritis and/or fibromyalgia (n=250) | 7 | X | X | Higher pain levels (Rios & Zautra, 2011) | X | ||||||
| Smoking adults 18–65 interested in smoking cessation in Vermont and Texas (n=58) | 7 | X | X | X | Not associated with smoking abstinence (Reitzel et al., 2015) | X | |||||
| Coronary Artery Risk Development in Young Adults study, randomly sampled adults 18–30 in Chicago and Oakland (n=1336) | 1 | X | Not associated with salivary cortisol levels or positive affect, but associated with more negative affect over the day (Puterman et al., 2013) | X | |||||||
| Depression intervention for African Americans 55+ in Philadelphia (n=182) | 1 | X | More depressive symptoms at baseline (Szanton et al., 2014) | X | |||||||
| Sleep treatment trial for adults with sleep apnea and diabetes (n=209) | 1 | X | Poorer sleep quality (Morris et al., 2021) | X | X | ||||||
| Low-income employed adults 40–64 in a chronic disease self-management trial in North Carolina (n=323) | 5 | X | X | X | More likely to prefer a financial self-management program than a health self-management program (Kneipp et al., 2019) | X | X | ||||
| Family and Community Health Study, African American families with 5th grader in Iowa or Georgia (n =693) | 4, 2a | X | X | Poorer physical health functioning (Black et al., 2009) | X | ||||||
| Family caregivers for brain injury patients at a rehabilitation hospital (n=136) | 1 2 |
X | Lower life satisfaction scores (Sabella & Suchan, 2019) | ||||||||
| Family member of veteran with brain injury in Philadelphia (n=83) | 1 | X | More depressive symptoms (Moriarty et al., 2018) | ||||||||
| San Francisco Female Condom Intervention Trial participants 18–39 (n=735) | 7 | X | X | X | More race-based and gender-based discrimination (Ro & Choi, 2009) | X | |||||
| Female, first-year Latina college students 18+ (n=104) | 3 | X | X | Not associated with depressive and anxiety symptoms or post-traumatic stress disorder symptoms (Sims et al., 2020) | |||||||
| Los Angeles first-generation Korean immigrants 65+ (n=205) | 1 | X | Less subjective well-being (Kim et al., 2015) | X | |||||||
| East Coast urban first-generation Korean immigrants (n=242) | 8 | X | X | More emotional and somatic symptoms of well-being (Lee, 2019) | X | ||||||
| Fragile Families and Child Wellbeing Study, mothers of children in 20 large US cities living with a partner (n=1886) | 8 | X | X | Higher odds of experiencing intimate partner violence emotional abuse and coercion, but not associated with odds of experiencing physical assault by partner (Golden et al., 2013) | X | ||||||
| Graduate seminary students (n=189) | 8 | X | X | X | X | X | More depressive symptoms, more anxiety and less spiritual well-being (Blea et al., 2021) | ||||
| 1 | X | Higher odds of having depressive symptoms and anxiety symptoms (n= 6776) (Marshall et al., 2021) and higher cardiometabolic risk count (C-reactive protein, blood pressure, heart rate, glycosylated hemoglobin, cholesterol, and waist circumference) (n=8231) (Mawhorter et al., 2023) but not associated with episodic memory (n=871) (Byrd et al., 2020) | X | ||||||||
| 4 | X | X | Higher odds of poor self-reported oral health (n=1359) (Chi & Tucker-Seeley, 2013) | X | |||||||
| Health and Retirement Study, randomly sampled 50+ | 3 | X | X | Higher odds of obesity, but not associated with smoking status or drinking level (n= 8,212) (Marshall et al., 2019) | X | X | |||||
| 4 | X | X | X | Less partner support and more partner undermining (n=4935) (Park & Kim, 2018) | X | X | |||||
| 4 | X | X | Higher odds of reporting poor health (n=7619) (Marshall & Tucker-Seeley, 2018) | X | |||||||
| 4 | X | X | X | Higher odds of experiencing pain among communitydwelling adults (n=2883) (Song et al., 2021) | X | ||||||
| 1 | X | X | Higher likelihood of pain and severe pain levels among men (n=3174) (Marshall et al., 2018) | X | |||||||
| 2 | X | More depressive symptoms among community-dwelling adults (n=8366) (Asebedo & Wilmarth, 2017) | X | ||||||||
| 4 | X | X | Higher hemoglobin A1c among those with diabetes (n= 2682) (Walker et al., 2021) | X | X | ||||||
| Health in Common study; adults in low-income housing in Boston area | 1 | X | Higher likelihood of poor self-rated health (n=828) (Tucker-Seeley et al., 2013), less healthy eating, and a higher likelihood of tobacco use but a lower odds of having high sedentary behavior (n=828) (Harley et al., 2014) | X | |||||||
| 1 | X | Not associated with the likelihood of trying to quit tobacco or the confidence in ability to quit (n=170) (Tucker-Seeley, Selk, et al., 2015) | X | X | |||||||
| Health, Aging and Body Composition Study, randomly selected healthy adults 70–79 in Memphis & Pittsburgh (n=2,155) | 3 | X | X | Higher IL-6 and CRP, but not TNF-alpha (Samuel, Szanton, Fedarko, et al., 2020) | |||||||
| Healthy Miami Hispanic immigrants 70+ (n=237) | 1 | X | Higher odds of high depressive symptoms (Perrino et al., 2009) | X | X | ||||||
| Heterosexual women 18+ who were not trying to get pregnant recruited online (n=932) | 5 | X | Lower rates of using short-acting hormonal contraception but not associated with use of long-acting reversible contraception or coital-specific contraception (Lyons et al., 2019) | X | |||||||
| Homeless Veterans Administration primary care patients (n=5,406) | 1 | X | Higher odds of being unsheltered (Kertesz et al., 2021) | X | X | ||||||
| Unemployed hospitality workers during COVID-19 (n=607) | 3 | X | X | Less overall well-being (Chen & Chen, 2021) | X | ||||||
| Household Pulse Survey; randomly selected 18–64 with COVID-19 job loss (n=264,522) | 1 | X | Higher likelihood of anxiety symptoms, depressive symptoms, food insufficiency and housing insecurity (Kim, 2021) | X | X | ||||||
| Job seekers recruited online (n=384) | 3 | X | X | X | Not associated with coping by unemployment by drinking (Blau et al., 2013) | X | |||||
| Kentucky Substance Abuse Treatment Outcome Study randomly sampled from programs (n=734) | 8 | X | Higher perceived stress (Cole et al., 2011) | X | X | ||||||
| Korean immigrants 18+in Los Angeles and Orange counties in California | 1 | X | Lower levels of positive well-being, general well-being and vitality but not associated with anxiety or depressive symptoms or self-rated health (n=147) (Lee & Woo, 2013); more anxiety symptoms and less vitality among young adults; less well-being among older adults (n=346) (Woo et al., 2014) | X | |||||||
| Landmark Spirituality and Health Survey, randomly sampled18+, excluding atheists | 3 | X | Poorer self-rated health, more chronic health problems and more functional limitations (n=3010) (Krause et al., 2018) but not associated with a summary score for poly-drug use and meaning in life (n=2622) (Krause et al., 2017) | X | |||||||
| Latino and Black man who have sex with men in Los Angeles, New York, and Philadelphia (n=2235) | 1 | X | Higher risk of unprotected anal intercourse with sero-discordant or unknown-status partners (Ayala et al., 2012) | ||||||||
| Men 30–75 receiving urology care in Tennessee (n=90) | 1 | X | Lower health literacy but not associated with prostate-related knowledge or prostate cancer treatment regret (Joyce et al., 2020) | ||||||||
| Miami-Dade Health Survey; randomly sampled 18+ | 3 | X | X | More depressive symptoms (n=444) (Hill et al., 2017) and higher likelihood of religious attendance, but not associated with social support (n=444) (Bradley et al., 2020) | X | ||||||
| Michigan randomly sampled White and Black 18–64 (n=594) | 4, 1a | X | X | X | More conflict with spouse/partner (MacInnes & Broman, 2012) | X | |||||
| Middle-aged and older adults without dementia or depression in Tampa (n=93) | 1 | X | Less satisfaction with financial situation and income but not associated with satisfaction with home, city/town, daily life/leisure, family life, health or life as a whole (Gamaldo et al., 2021) | X | X | ||||||
| Midlife in the United States; randomly sampled Black adults 20–74 in Milwaukee, Wisconsin (n=592) | 2 | X | Higher odds of being a current smoker, but not associated with odds of past smoking (Slopen et al., 2012) | X | |||||||
| Midwestern Head Start Program staff (n=295) | 1 | X | Higher odds of reporting poor self-reported physical and mental health (Snyder et al., 2020) | ||||||||
| Mothers of children aged 4–17 receiving treatment from a community mental health clinic (n=336) | 1 8 |
X | More depressive symptoms (Gjesfjeld et al., 2010) | ||||||||
| Utah and Idaho National Guard Personnel (n=889) | 1 | X | Not associated with suicidal ideation or suicide attempts (Bryan & Bryan, 2019) | X | |||||||
| National Latino and Asian American Study | 2 | X | X | Poorer self-rated health (n=2095) (de Castro et al., 2010) | X | X | |||||
| 2 | X | X | Higher risk of heavy episodic drinking and an alcohol use disorder among Asian Americans but not Latinos (n=4649) (Cook et al., 2020) | X | |||||||
| National Longitudinal Study of Adolescent to Adult Health; randomly selected teenagers in the 7th-12th grade followed for <13 years | 3 | X | X | Higher likelihood of using prescription opioid medication(s) among parents (n= 6,872) (Austin & Shanahan, 2017) | |||||||
| 6 | X | Among young adults in relationships, more intimate partner violence among married couples but not cohabitating couples and not associated with relational affection (n= 1702) (Hardie & Lucas, 2010) | X | ||||||||
| 6 | X | X | More depressive symptoms and a higher likelihood of suicidal ideation (n=10058) (Eitle, 2022). Among Asian American young adults, more alcohol abuse symptoms but not associated with frequent drunkenness, or alcohol-dependence symptoms (n=719) (Cook et al., 2013) | X | |||||||
| 7 | X | Higher odds of both being overweight and obese (n=6515 for women, 5985 for men) (Averett & Smith, 2014) | X | X | |||||||
| 7 | X | Higher likelihood of experiencing or perpetrating intimate partner violence among adults in relationships (n=10665) (Spencer et al., 2016) | |||||||||
| 5 | X | X | Higher risk of obesity among women, but not men (n=10091) (Kim et al., 2020) | X | X | ||||||
| 5 | X | No association with metabolic syndrome(n=11575) (Goldberg et al., 2019) | X | ||||||||
| 6 | X | X | Higher likelihood of engaging in instrumental& violent crime and illegal drug use (n=13288) (Dennison, 2019) | X | X | ||||||
| 6 | X | X | Higher likelihood of perpetrating intimate partner violence among young adults recently in a relationship (n=11499) (Schwab-Reese et al., 2016) | X | |||||||
| National Survey of American Life; randomly sampled | 8 | X | X | More depressive symptoms (Hughes et al., 2014) | X | ||||||
| African Americans 18+ (n=3,570) | |||||||||||
| National Survey of Fertility Barriers National, randomly selected women 25–45 | 3 | X | X | Lower life satisfaction and more depressive symptoms among those partnered and with a child (n=2675) (Pritchard & Falci, 2020) | X | X | |||||
| 3 | X | X | More treatment concerns and depressive symptoms but not associated with infertility services use or fertility-specific distress (n=1218) (Greil et al., 2020) | X | |||||||
| National survey of Whites and African Americans 66+ | 2 | X | Poorer self-rated health, more depressive symptoms and less life satisfaction among atheists (n=1535) (Krause & Hayward, 2015) | X | |||||||
| 3 | X | X | More depressive symptoms but not associated with suffering in silence at seven years among Christians (n= 596) (Krause, 2010) | X | |||||||
| Non-Hispanic Black or Hispanic older adults at a Southwestern senior center (n=102) | 1 | X | More likely to feel older than their age (Choi et al., 2021) | X | |||||||
| Latinx 50+ (n=214) | 1 | X | More depressive symptoms (Aranda & Lincoln, 2011) | X | |||||||
| Non-binary gender, nonwhite and non-Latinx patients 18+ in Rio Grande Valley (n=546) | 5 | X | X | Higher odds of foregoing medical care and a higher odds of poor health (Tabler & Mykyta, 2021) | X | ||||||
| Online survey respondents 21+ (n=821) | 3 | X | Not associated with emotional exhaustion (Choi & Heo, 2021) | X | X | ||||||
| Online survey of first- and second-generation African immigrants 18+ (n=173) | 4 | X | X | More mental health symptoms (Saasa & Miller, 2021) | X | ||||||
| Parents/guardians of children admitted to hospitals in California, Wisconsin, Ohio, Utah, Washington, & Texas (n=526) | 8 | X | X | X | X | X | Not associated with parent’s preferences for health care cost- transparency practices (Bassett et al., 2021) | X | X | ||
| Cancer prevention and physical activity trial participants 21+in Appalachia (n=1,992) | 1 | X | Poorer self-rated health and more chronic conditions (Tarasenko & Schoenberg, 2017) | ||||||||
| Physical activity intervention participants in Dallas, Texas (n=238) | 8 | X | X | X | Poorer self-rated health and lower quality of life scores; association with quality of life was attenuated among those with greater social support (Garey et al., 2017) | X | |||||
| Midwest diabetes patients 18–74(n=117) | 3 | X | X | Lower diabetes self-efficacy scores and spouses less confidence in patienťs ability to manage diabetes (Novak et al., 2017) | X | ||||||
| Patients with urinary prolapse symptoms in | 1 | X | Higher odds of overactive bladder syndrome (Tellechea et al., 2021) | X | |||||||
| New York and Baltimore (n=256) | |||||||||||
| Randomly sampled Indiana White and Black adults 18–75 (n=970) | 1 | X | Not associated with likelihood of mammograms, colorectal cancer screening or cervical cancer screening (Kasting et al., 2021) | X | X | ||||||
| Randomly sampled Texans 18+ (n=1504) | 1 | X | More psychological distress (Acevedo et al., 2014) | X | |||||||
| Employed bone marrow transplant recipients | 2 | X | Lower self-rated health and less quality of life and higher perceived stress (n=171) (Albelda et al., 2019) | X | X | ||||||
| 3 | X | X | Poorer quality of life and self-rated health and more perceived stress 150 days after transplant (n=325) (Abel et al., 2016) | X | |||||||
| Pregnancy Risk Assessment Monitoring System; randomly sampled women after a live birth (n= 69,023) | 1 | X | Higher likelihood of food insecurity (Testa & Jackson, 2020) | X | |||||||
| Pregnant Californians18–45 | 1 | X | Higher likelihood of reporting that providers have reduced perinatal visit options during COVID-19 and worries about lacking birth support, provider availability for the birth, and lacking resources, and a higher likelihood of considering an out-of-hospital birth but not associated with seeking care or having remote visits (n=820) (Whipps et al., 2021) | ||||||||
| Pregnant women in Ohio (n=138) | 3 | X | X | More depressive symptoms, pregnancy-specific distress, perceived stress and anxiety (Mitchell & Christian, 2017) | X | ||||||
| Previously deployed female military veterans (n=128) | 1 | X | More depressive symptoms (Sairsingh et al., 2018) | X | X | ||||||
| Primary caregivers of Early Head Start children in northeastern cities (n=978) | 4, 2b | X | X | More depressive symptoms, but not anxiety symptoms. Difficulty making ends meet was associated with less dysfunction in parent-child relationship (Hurwich-Reiss et al., 2019) | X | ||||||
| Houston African Americans 18+ at Black churches (n=1341) | 7 | X | X | X | Lower composite scores that captured both physical activity levels and fruit and vegetable consumption (n=1009) (Heredia et al., 2020) | X | |||||
| 7 | X | X | X | Poorer self-rated health (Savoy et al., 2014) | X | X | |||||
| Puerto Rican Elderly Health Conditions, randomly sampled>60 (n=978) | 1 | X | Not associated with the age at the onset of natural menopause (Novak & Lozano-Keymolen, 2018) | X | |||||||
| Random national sample (n=1801) | 7 | X | X | X | Lower odds of good mental health (Marshall et al., 2017) | X | |||||
| Random sample of Black adults in New York City; Boston; Nassau-Suffolk, New York; and Florida (n = 962) | 2 | X | X | More psychological distress (Lincoln & Chae, 2010) | X | ||||||
| Randomly sampled homeless Veterans Administration primary care patients(n=4777) | 1 | X | Poorer care coordination, more hassles and long wait times when referred for services but not associated with satisfaction with community care (Jones et al., 2021) | X | X | ||||||
| Randomly sampled adults 18+(n=5083) | 1 | X | Higher odds of experiencing both migraines and post-traumatic stress disorder, but not associated with experiencing just one condition (Rao et al., 2015) | X | |||||||
| Randomly sampled Detroit adults 18–64 of Gujarati decent (n=373) | 1 | X | More attitudes supporting intimate partner violence (Yoshihama et al., 2014) | X | |||||||
| Randomly sampled healthy adults 18+not in prison/police custody (n=2312) | 1 | X | Higher odds of using any drug but not associated with binge drinking (Gerber et al., 2020) | X | X | ||||||
| Randomly sampled female community college students in a relationship in Midwestern city (n=435) | 1 3 |
X | More depressive symptoms and more PTSD symptoms (Schrag et al., 2019) | ||||||||
| Randomly sampled post-partum women in New York City (n=3566) | 1 | X | Not associated with being diagnosed with post-partum depression (Liu & Tronick, 2013) | X | |||||||
| Rectal cancer survivors in Minnesota, Colorado, Northern California, and the Northwest (n=527) | 1 | X | Less participation in life activities (Bulkley et al., 2021) | X | |||||||
| Living kidney donors (n=2455) | 1 | X | Less life satisfaction (Messersmith et al., 2014) | X | |||||||
| Resources for Enhancing Alzheimer’s Caregiver Health, co-residing caregivers 21+ | 1 | X | More depressive and anxiety symptoms(n=2133) (Sun et al., 2009) | X | X | ||||||
| 1 | X | More depressive symptoms among those with distress (n=642) (Miller et al., 2020) | |||||||||
| Retired community-dwelling Mexican Americans 66+ in Texas, Colorado, New Mexico, Arizona, & California (n=1005) | 3 | X | X | More cognitive and somatic symptoms of depression (Krause, 2012) | X | ||||||
| Young adults who had attended Minneapolis-St. Paul secondary schools(n=675) | 1 | X | More unhealthy weight control behaviors and more eating to cope behavior, but not associated with binge eating (Simone et al., 2021) | X | |||||||
| Staff of Pennsylvania Head Start program(n=2105) | 5 | X | X | More depressive symptoms and higher likelihood of having depression (Whitaker et al., 2021) | X | ||||||
| Stem cell transplantation survivors 18+ in remission and with distress in New York City and New Jersey (n=181) | 9 | X | X | X | Poorer physical, emotional and functional well-being and more transplant-specific concerns but not associated with social/family well-being (Hamilton et al., 2013) | X | X | ||||
| Minnesota public university students (n=1117) | 1 | X | Less physical activity and more unhealthy weight-control behaviors or binge drinking, but not associated with overweight/obesity or diet (VanKim & Laska, 2012) | X | |||||||
| Midwestern public university students (n=222) | 5, 17 | X | X | X | Lacking basic needs was associated with less life satisfaction. (Stein et al., 2013) | X | |||||
| Study of Women’s Health Across the Nation, non-Hispanic pre-menopausal White women 42–52 in Oakland, Los Angeles, Newark, Pittsburgh, Chicago, Boston and Detroit | 1 | X | Not associated with levels of per- and poly-fluoroalkyl synthetic compound substances (n=1302) (Park et al., 2019) | ||||||||
| 1 | X | Greater carotid intima media thickness and more plaque (n=1402), (Thurston et al., 2014) shorter sleep duration and more waking (n=1203) (Matthews et al., 2019) | X | ||||||||
| 1 | X | Poorer sleep quality but not associated with time sleeping (n=368) (Hall et al., 2009) | X | X | |||||||
| 1 | X | Higher odds of having a disability (n=376) (Karvonen-Gutierrez & Ylitalo, 2013) | X | ||||||||
| Sub-Saharan African immigrants 35+ with chronic illness in Washington, DC, New York, New Jersey, and Pennsylvania (n=88) | 1 | X | Poorer chronic illness self-care (Osokpo et al.) | ||||||||
| Survey of Income and Program Participation, randomly samples adults 55+(n=20852) | 3 | X | Higher odds of poor health (Li & Mutchler, 2019) | X | |||||||
| Survey of Older Floridians, White, Black, Cuban, Latino adults65+ | 1 | X | Poorer self-rated health among Cuban Americans (n=1471) (Jang et al., 2009) and non-Cuban Latino Americans, but not among those who were White or Black (n = 1,382) (Ko et al., 2014) | X | X | ||||||
| National Guard personnel (n=330) | 1 | X | More posttraumatic stress disorder symptoms, depressive symptoms, anger and insomnia symptoms (Russell et al., 2017) | ||||||||
| Midwestern university students (n=157) | 3 | X | X | X | Less academic and social integration and more psychological distress symptoms (Adams et al., 2016) | ||||||
| Midwestern university students (n=177) | 22 | X | Less physical functioning, more role limitations, more fatigue, poorer social functioning and more pain, but not associated with emotional role limitations or emotional well-being (Northern et al., 2010) | ||||||||
| Undocumented University of California students (n=508) | 4 | X | X | X | X | Poorer self-rated health (Enriquez et al., 2018) | |||||
| Community-dwelling African American Medicare beneficiaries 65+ in Alabama (n=247) | 1 | X | Poorer physical health-related and mental health-related quality of life (Clay et al., 2018) | X | X | ||||||
| Women with gynecologic cancers (n =334) | 11 | X | X | Higher risk of delaying/avoiding medical visits, prescriptions refills and buying over the counter medications or medical supplies (Esselen et al., 2021) | X | ||||||
| Workers 25–64 (n=10,748) | 1 | X | Higher odds of considering how much money was needed to retire, but not associated with having retirement account(s) (Fan et al., 2022) | X | |||||||
| Utah pregnant women 18+at prenatal clinics (n=85) | 1 | X | Higher levels of corticotropin releasing hormone at 20 weeks gestation (Latendresse & Ruiz, 2010) | ||||||||
| Washington State home care workers (n=421) | 3 | X | X | Higher pain levels (Greenspan et al., 2021) | |||||||
| Post-partum women 18+ with live births (n=304) | 10 | X | X | Higher odds of poor self-rated health (McCloskey, 2022) | |||||||
| Women who delivered a live infant during COVID-19 pandemic in New York City (n=1179) | 1 | X | X | Not associated with the odds of changing fertility intention during the COVID-19 pandemic or pregnancy intention (Kahn et al., 2021) | X | ||||||
| Mothers in low-income neighborhoods in Boston, Chicago, and San Antonio (n=2402) | 5 | X | X | X | Larger body mass index (Ross & Hill, 2013) | X | |||||
| Women with HIV-related risk behaviors (n=592) | 1 | X | Not associated with sexual risk scores (Batchelder et al., 2016) | X | |||||||
| Women’s Health and Aging Study, community-dwelling women 65–79 in Baltimore | 2 | X | Higher risk of being at risk for malnutrition (n=679) (Samuel et al., 2012) | X | X | ||||||
| 1 | X | Higher levels of oxidative stress (n=728) (Palta et al., 2015) | X | X | |||||||
| Women’s Health Study; health professionals 45+ (n=24,809) | 3 | X | X | Not associated with odds of reporting a diagnosis of atrial fibrillation (Westcott et al., 2018) | X | ||||||
Two financial strain measures were used. If not specified, both were associated with study outcome.
Values differed based on sub-sample included.
Values differed across sub-domains.
Table 4.
Summary of longitudinal associations between financial strain and health-relevant outcomes among U.S. adults
| Study, sample & setting | Financial strain measure | Associations between financial strain with health-relevant outcomes | Socioeconomic adjustment | Health adjustment | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| # of items | Lacking basic needs | Difficulty making ends meet | Coping Strategies | Financial satisfaction | Financial stress/worry | Anticipating strain | Lack of money for wants | ||||
| A myocardial infarction registry (n=2693) | 1 | X | Not associated with angina-specific quality of life (Arnold et al., 2014) | X | X | ||||||
| Adults 21–82 near Deepwater Horizon Oil Spill in Florida & Alabama (n=175) | 2 6 |
X | X | More drug abuse, mood disturbance and depressive symptoms at a two years but not associated with problematic alcohol use (Buckingham-Howes et al., 2019) | |||||||
| Heart disease patients hospitalized at Vanderbilt (n=2042) | 1 | X | Not associated with incomplete follow-up at 2–3 days, 30 days or 90 days after hospital discharge, or incomplete follow up calls (Leak et al., 2015) | X | |||||||
| Adults with serious mental illness admitted to two outpatient mental health centers (n=271) | 3 | X | Higher odds of using cocaine or illicit sedatives and more internal stigma, depressive symptoms, interpersonal problems and emotional lability, but not associated with use of alcohol, cannabis or heroin or risk of self-harm, psychosis or other schizophrenia symptoms (Spivak et al., 2019) | X | X | ||||||
| African American female physical activity trial participants 40–65 with diabetes in Chicago (n=288) | 9 | X | Not associated with study retention (Buchholz et al., 2016) | ||||||||
| African-American and Puerto Rican adults who had attended East Harlem schools 21 years earlier (n=674) | 8 | X | X | X | More mental health services utilization (Brook et al., 2014) | X | X | ||||
| Adults 75+ in Texas, New Mexico, Colorado, Arizona, and California (n=1964) | 4 | X | X | Faster 12-year cognitive decline (Sachs-Ericsson et al., 2009) | X | X | |||||
| Americans Changing Lives Study, 60+ | 3 | X | X | Not associated with physical health by year 8 (n=1653) (Oates, 2016) but increased three-year financial strain predicted worsening depressive symptoms life satisfaction (n=1221) (Brown & Barrett, 2011) | X | X | |||||
| Black males 16–29 who have sex with men in South Chicago (n=545) | 2 | X | X | Higher odds of criminal justice involvement over 18 months (Hotton et al., 2020) | X | ||||||
| Black, Hispanic or multi-racial men who have sex with men 16–24 near Los Angeles (n=448) | 1 | X | Not associated with risk of sexually transmitted infection(s) (Kipke et al., 2020) | ||||||||
| Caregivers co-residing with persons with dementia (n=184) | 2 | X | More caregiving role overload (Liu et al., 2019) | X | |||||||
| Caregivers of a child with cancer at a large Southern medical center (n=163) | 2 | X | X | Less social support, more child problems, sibling problems, family problems, and parent stress reactions, and a lack of family coping ability over two years (Karlson et al., 2013) | |||||||
| Caregivers of children ≤6 years Philadelphia (n=373) | 4 | X | X | Not associated with self-rated health or depressive symptoms, accounting for food-, energy-, and housing-insecurity (Weida et al., 2020) | X | ||||||
| Chicago Earned Income Tax Credit Periodic Payment Pilot (n=507) | 8 | X | X | X | X | X | More depressive symptoms (Andrade et al., 2017) | X | |||
| Adults 18–65 interested in smoking cessation in Vermont and Texas (n=102) | 8 | X | X | X | More motivated to smoke because of affect and likely to expect negative moods after quitting but not associated with barriers to quitting (Robles et al., 2017) | X | X | ||||
| Coronary Artery Risk Development in Young Adults study, randomly sampled adults 18–30 in Birmingham, Chicago, Minneapolis, & Oakland | 1 | X | Less verbal memory, slower processing speed and poorer executive function over time (n=3383) (Zeki Al Hazzouri et al., 2017) and higher fasting glucose at the 13-year follow up(n=2591) (Puterman et al., 2012) | X | X | ||||||
| Diabetes patients 30–75 in Northern California (n=7,773) | 1 | X | Not associated with filling a new prescription or refilling the prescription but associated with delays in refilling (Lyles et al., 2016) | X | X | ||||||
| Employees of a manufacturing company (n=80) and Amazon Mechanical Turk respondents (n=331) | 3 | X | More musculoskeletal symptom s (Odle-Dusseau et al., 2018) | ||||||||
| Family and Community Health Study, African American families with 5th grade child in Iowa or Georgia in 1997–1998 | 4 | X | Not associated with allostatic load scores through 2008 (n=327) (Berg et al., 2017) | X | |||||||
| 12 | X | X | Higher hemoglobin A1C levels after 11-years(n=312) (Cutrona et al., 2015) | X | |||||||
| 4 | X | Not associated with epigenetic scores for biologic aging over four years (n=386) (Simons et al., 2019) | |||||||||
| 4 | X | More epigenetic methylation over eight years (n=100) (Simons et al., 2016) | X | X | |||||||
| Fragile Families and Child Wellbeing Study, mothers of children born in 20 large US cities in 1998–2000 with an oversampling of unmarried mothers | 1 2 |
X | X | Higher likelihood of parents breaking up before the child was 5 among Latina mothers (n= 1314) (Cabrera et al., 2019) | |||||||
| 7 | X | X | Higher odds of depression within five years (n=3675) (Manuel et al., 2012) | X | X | ||||||
| 8 | X | X | More substance use/intimate partner violence/HIV risk at year five (n = 4,898) (Caiola et al., 2021) and, among parents living together at year one, more parental relationship distress at year 5 (n=1492) (Williams & Cheadle, 2016). High and increasing financial strain was associated with more depressive symptoms by year 15 but not anxiety (n=1645) (Daundasekara et al., 2021) | X | X | ||||||
| 9 | X | X | More intimate partner violence over 9 years and more physical violence, emotional violence, controlling violence among mothers living with a partner at baseline (n=4234) (O’Connor & Nepomnyaschy, 2020) | X | |||||||
| 7 | X | X | Higher odds of prevalent and incident depression and prevalent and incident general anxiety over 3 years (n=2104) (Suglia et al., 2011) | X | |||||||
| 10 | X | X | More intimate partner violence among those in a stable relationship for nine years (n=947) (Lucero et al., 2016) | X | X | ||||||
| 5 | X | X | More parental relationship distress among those living together in 2006 (Mothers= 1304/Fathers= 1230) (Williams et al., 2015) | X | X | ||||||
| Health and Retirement Study, randomly sampled adults 50+ | 4 | X | X | Higher risk of mortality over 8 years, 1996–2004 (n=8377) (Tucker-Seeley et al., 2009) | X | ||||||
| 2 | X | X | Higher C reactive protein but not associated with metabolic dysregulation, 2004–2012 (n=7280) (Boen, 2019) | X | |||||||
| 1 | X | Higher risk of diabetes-related kidney disease, 2006–2012 (n=2735) (Corwin et al., 2021) | X | X | |||||||
| 1 | X | Poorer glycemic control (hemoglobin A1c levels), 2006–2014 (n= 2662) (Walker et al., 2020) | X | X | |||||||
| 4 | X | X | X | Not associated with body mass index BMI 4–8 years later (n= 3956) (Cuevas et al., 2021) | X | ||||||
| 2 | X | X | More anxiety symptoms and depressive symptoms, 2006–2014 (n=5,229) (Wilkinson, 2016) | ||||||||
| Health, Aging and Body Composition Study, randomly selected healthy adults 70–79 in Memphis & Pittsburgh (n=2457) | 1 | X | X | Higher risk of 11-year incident dementia (Yaffe et al., 2013) | X | X | |||||
| Hispanic Established Population for the Epidemiologic Study of the Elderly; randomly sampled adults 75+ years in Texas, New Mexico, Colorado, Arizona, and California | 1 | X | More frailty by 2008 (n=2438) (Peek et al., 2012) and greater 13-year mortality risk (n=768) (Ottenbacher et al., 2012) but, among those married at baseline, not associated with odds of having a limitation in activities of daily living (n=385) (Monserud, 2019) | X | X | ||||||
| Hispanic/Latinos 18–74 in Chicago, Miami, Bronx, New York, & San Diego (n=4981) | 1 | X | Larger body mass index (BMI) (Isasi et al., 2016) | X | |||||||
| Indiana 6th-12th graders with 31 year follow up (n=3984) | 3 | X | X | Less likely to check ingredient labels and less vigorous exercise but also less smoking and no association with seat belt use (Macy et al., 2013) | X | ||||||
| Iowa Youth and Families Project; recruited as cohabitating parents of 7th grade children in rural Iowa in 1989 | 2 2 |
X | X | X | Decreasing/increasing or persistently high strain were associated with physical impairment, depressive symptoms and physical illness at year 15 (n=360) (Wickrama et al., 2010) | X | |||||
| 2 7 |
X | X | X | Greater depressive symptoms at a 12-years (n=370) (Wickrama, O’Neal, & Lorenz, 2018); poorer marital quality among consistently married for 10 years (n=370) (Wickrama & O’Neal, 2019) | |||||||
| 2 7 |
X | X | X | More depressive symptoms by 2001 (n=370) (Wickrama et al., 2012) and among husbands, more cardiometabolic disease at 14 years (n=257) (Wickrama, O’Neal, & Neppl, 2018). Ten-year financial strain predicted more psychological distress, poorer physical health and more loneliness among husbands at 26 years, and poorer physical health among wives (n=254) (Wickrama & O’Neal, 2021b). Baseline financial strain and 14-year increased strain predicted more memory impairment at 26 years (n=224) (Wickrama & O’Neal, 2021a). | X | ||||||
| 3 7 |
X | X | X | More physical impairments by 26 years (n=243) (Neppl et al., 2021) | X | ||||||
| 2 2 |
X | X | X | Poorer overall health by 2015 (n=370) (Lee et al., 2021) | |||||||
| 7 | X | Poorer physical function but not chronic illness cross-sectionally and financial strain trajectories over time did not predict outcomes in 2019 (n=505) (Klopack et al., 2021) | X | X | |||||||
| 4 | X | Poorer overall health, larger body mass index, more loneliness, and less life satisfaction among heterosexual married couples over 26 years, but not associated with sense of control (n= 254) (Wickrama et al., 2022). Baseline financial strain, but not 10-year change predicted more pain over 26 years (n= 508) (Wickrama et al., 2021b) | X | ||||||||
| 4 | X | More physical limitations, subjective memory impairment and loneliness over 16-years (n=244) (Wickrama et al., 2021a) | |||||||||
| African American adults 33–84 (n=2256) | 5 | X | X | X | X | Higher risk of incident heart disease (Moran et al., 2019) | X | ||||
| Kentucky Substance Abuse Treatment Outcome Study randomly sampled from programs | 8 | X | Greater drug addiction severity over 1–2 years, but not alcohol addiction severity (n=1,099) (Wahler, 2015) | X | |||||||
| 8 | X | Not associated with likelihood of successfully abstaining from alcohol and illicit drugs (n=1123) (Wahler & Otis, 2014) | X | X | |||||||
| Knowledge Networks panel online respondents (n=704) | 3 | X | X | More post-traumatic stress symptoms and more impaired work/social functioning 2- to 3-years post 9/11 if specific genotypes (Lucas-Thompson & Holman, 2013) | X | X | |||||
| Mexican/Mexican American, 18+, low-income, uninsured, and/or undocumented mothers of infants (n=205) | 2 0 |
X | X | X | X | More post-partum depressive symptoms at six weeks, but not cortisol levels at 12 weeks (Jewell et al., 2015) | |||||
| Midlife in the United States; randomly sampled adults 20–74 (n=3257) | 4 | X | X | X | Less volunteering (Son & Wilson, 2015) | X | X | ||||
| Mothers of North Carolina newborns 18+who plan to return to work (n=190) | 2 | X | Lower physical & mental health-related quality of life over time (Tucker et al., 2010) | X | |||||||
| National Health and Aging Trends Study, randomly sampled adults 65 + | 4 | X | Faster two-year declines in walking speed and reduced ability to walk (n=3234) (Samuel et al., 2019) | X | X | ||||||
| 4 | X | Higher odds of six-year incident dementia (n= 5,034) (Samuel, Szanton, Wolff, et al., 2020) | |||||||||
| 4 | X | Not associated with one-year odds of falls(n=5581) (Okoye et al., 2021) | X | ||||||||
| National Longitudinal Study of Adolescent to Adult Health, randomly selected teenagers in the 7th-12th grade in 1995 | 7 | X | Among adolescents with a maternal figure, baseline financial strain predicted higher Framingham Risk Score in 2008–2009 (n=11013) (Doom et al., 2016) | X | |||||||
| 3 | X | More alcohol use and heavy drinking cross sectionally, but not longitudinally and more problematic drinking both cross-sectionally and longitudinally, 2001–2009 (n=7159) (Serido et al., 2014) | X | ||||||||
| 7 | X | Higher Framingham Risk Score among healthy participants in 2016 (n=14493) (Doom et al., 2017) | X | ||||||||
| National Longitudinal Survey of Mature Women; women 30–44 in 1967 | 1 | X | More depressive symptoms and less life satisfaction by 2003 (n=3,296) (Shippee et al., 2019) | X | |||||||
| 1 | X | Poorer self-rated health by 2003 (n=3181) (Shippee et al., 2012) | X | X | |||||||
| National sample of retired adults 65–100 | 3 | X | X | More depressive symptoms 1992–2005 (n=818) (Krause, 2009) | X | ||||||
| 4 | X | Higher odds of ever smoking, but not heavy drinking 1992–2006 (n=2352) (Shaw et al., 2011) | X | ||||||||
| National Survey of Fertility Barriers, randomly selected women 25–45 (n=759) | 3 | X | X | 2–6 years change in financial strain not associated with life satisfaction change (Greil et al., 2019) | X | ||||||
| Non-pregnant White, Black or Latina mothers 18–40 in DC, Maryland, California, Illinois, North Carolina (n=1206) | 5 | X | X | Higher C-reactive protein at 6- and 12-months post-partum (Guardino et al., 2017) | X | ||||||
| Prospective Registry Evaluating Myocardial Infarction Event and Recovery study, 18+ (n=2344) | 1 | X | Poorer physical health, mental health, and quality of life, more angina symptoms, and a higher likelihood of one-year rehospitalization, but not associated with 4-year mortality risk (Shah et al., 2012) | X | X | ||||||
| Older workers eligible to retire (n=292) | 5 | X | X | X | Retirement financial strain predicted more alcohol misuse (Belogolovsky et al., 2012) | X | |||||
| Unpaid caregivers of patients 21+ with brain tumor near Pittsburgh (n=33) | 4 | X | X | X | X | Greater caregiver burden due to abandonment at diagnosis, but not associated with burden due to schedule, depressive symptoms or anxiety symptoms (Bradley et al., 2009) | |||||
| Systemic lupus erythematosus patients in San Francisco (n=682) | 2 | X | X | More depressive symptoms (McCormick et al., 2018) | X | X | |||||
| Population Assessment of Tobacco and Health study, randomly sampled adults | 1 | X | Among smokers, more quit attempts but not associated with 1–2 year abstinence (n=7213) (Kalkhoran et al., 2018) | X | X | ||||||
| 1 | X | Higher odds of using electronic nicotine delivery systems some days, but not every day among 18–24 year-olds (n=5740) (Han & Seo, 2021) | X | ||||||||
| Randomly sampled from Alameda County, California, (n=378) | 5 | X | More five-year self-reported cognitive impairment among those married (Strawbridge et al., 2011) | X | X | ||||||
| Houston African American church-going adults 18+ (n=1278) | 7 | X | X | X | More cancer risk factors and higher odds of smoking, insufficient physical activity, being overweight/obese, having <5 servings of fruit and vegetables each day, but not with at-risk alcohol use (Advani et al., 2014) | X | |||||
| Protecting Strong African American Families program in economically disadvantaged Georgia communities | 15 | X | X | More depressive symptoms, poorer overall health, more sleep problems, greater impact of and stress due to COVID-19 (n=320) (Adesogan et al., 2022) | |||||||
| 2 | X | Poorer two-year overall health (n=348) (Barton et al., 2018) | |||||||||
| 4 | X | Higher epigenetic aging scores (n=348) (Lei et al., 2021) | X | ||||||||
| Puerto Rican Elderly Health Conditions, randomly sampled 60+, 2002–2008 | 2 | X | Not associated with cognitive function (n=1632) (Vigoureux et al., 2021) or four-year cognitive decline (n=3,385) (Barba et al., 2021) | X | X | ||||||
| Random sample of a large national employer (n=1209) | 4 | X | X | Poorer self-rated physical & mental health and higher likelihood of depression & anxiety diagnoses, but not associated with the heart disease risk count or cardiovascular disease diagnosis (Bialowolski et al., 2021) | X | ||||||
| Randomly sampled adult residents of Atlanta low-income housing communities (n=232) | 1 | X | Not associated with satisfaction with housing relocation (Oakley et al., 2013) | X | |||||||
| Randomly sampled African American couples within first year of marriage (n=506) | 6 | X | X | More weight management behaviors at one-year follow up (O’Neal et al., 2015) | X | ||||||
| Resources for Enhancing Alzheimer’s Caregiver Health, family caregivers 1996–2000 (n=659) | 1 | X | More depressive symptoms (Nam, 2016) | X | |||||||
| Seattle Midlife Women’s Health Study, menopausal women 1990 to 2005 | 6 | X | X | More perceived stress over 9 years (n=418) (Woods, Mitchell, Percival, et al., 2009) but not associated with urine cortisol levels (n=132) (Woods, Mitchell, & Smith-Dijulio, 2009) | |||||||
| Smoking cessation program in Houston (n=320) | 7 | X | X | X | Lower odds of successful 26 week abstinence (Kendzor et al., 2010) | X | |||||
| Spanish-speaking Mexican American smoking adults in Houston (n=199) | 8 | X | X | X | Lower odds of being abstinent from smoking at 26 weeks (Vinci et al., 2017) | X | |||||
| Study of Women’s Health Across the Nation, non-Hispanic pre-menopausal White women 42–52 years Oakland, Los Angeles, Newark, Pittsburgh, Chicago, Boston and Detroit | 1 | X | More severe menopausal symptoms over 16 years (n=3289) (Harlow et al., 2017) | X | X | ||||||
| 1 | X | Higher perceived stress over 13 years (n=3044) (Hedgeman et al., 2018) and poorer verbal episodic memory but not working memory within 20 years (n =394) (Kolli et al., 2021); among those in Detroit and Chicago, slower mobility over 20 years (n=830) (Lange-Maia et al., 2019) | X | ||||||||
| 1 | X | Higher odds of having physical function limitations and a higher odds of 12-year declines (n=2497) (Ylitalo et al., 2013), less subjective well-being over 19 years (n=1693) (Avis et al., 2021) and higher 20-year incidence of peripheral neuropathy (n=1718) (Dusendang et al., 2019) | X | ||||||||
| 1 | X | More depressive symptoms within four years (n=2400) (Li, Liang, et al., 2020), higher five-year odds of depressive symptoms (n=2376) (Li, Zheng, et al., 2020) but not associated with 16-year incident diabetes among those in Detroit (n=424) (Karvonen-Gutierrez et al., 2018) | |||||||||
| 1 | X | Higher cumulative 15 year depressive symptom burden among participants in Boston, Chicago, Detroit and Pittsburgh (n=1109) (Bromberger et al., 2017) | X | X | |||||||
| Suicide prevention trial for adults 60+ (n=1226) | 1 | X | Higher odds of suicidal ideation but not associated with depressive symptoms at each study visit (Gilman et al., 2013) | X | X | ||||||
| Motivational interviewing trial for colorectal cancer screening in Kentucky, 50+ (n=134) | 1 | X | Not associated with use of colorectal cancer screening, perceived colorectal cancer susceptibility, perceived benefits of screening, or barriers to screening (Adegboyega et al., 2022) | ||||||||
| Adults 21–30 and 50–70 near San Francisco (n=1159) | 1 | X | Not associated with reporting a cardiometabolic condition (Child et al., 2022) | X | |||||||
| Southwest wellness trials for women with multiple sclerosis (n=118) and fibromyalgia (n=197) | 8 | X | Poorer physical functioning, social functioning and role limitations within 1–2 years (Phillips & Stuifbergen, 2009, 2010) | X | X | ||||||
| Mothers in low-income neighborhoods in Boston, Chicago, and San Antonio (n=2014) | 1 3 |
X | X | Both baseline financial strain and two-year increases predicted greater 2-year increase in psychological distress (Hill et al., 2013) | X | X | |||||
| Working US adults 18+ (n=1,122) | 4 | X | X | More family-to-work conflict and more psychological distress (Young & Schieman, 2012) | X | ||||||
Values varied over time
Kuder-Richardson values, not Cronbach α
Values varied across sub-samples
Values varied across sub-domains
Financial Strain and Mental Health
Financial strain was consistently associated with worse mental health, including in many studies that statistically adjusted for other socioeconomic factors and even in studies that adjusted for health factors that likely lie on the causal pathway between financial strain and mental health (Tables 3 & 4). Although financial strain was generally associated with relatively worse mental health in both cross-sectional (Table 3) and longitudinal analyses (Table 4), some associations were found more consistently in longitudinal studies. As examples, financial strain was associated with more symptoms of depression and anxiety in most cross-sectional studies (Aranda & Lincoln, 2011; Barajas-Gonzalez et al., 2021; Blea et al., 2021; Dailey & Humphreys, 2011; Eitle, 2022; Evans et al., 2020; M. C. Evans et al., 2019; Fuller et al., 2021; Gjesfjeld et al., 2010; Greil et al., 2020; Hill et al., 2017; Hou et al., 2021; Hughes et al., 2014; Hurwich-Reiss et al., 2019; Kim, 2021; Krause, 2010, 2012; Krause & Hayward, 2015; Marshall et al., 2021; Marshall et al., 2017; Miller et al., 2020; Mitchell & Christian, 2017; Moriarty et al., 2018; Okechukwu et al., 2012; Perrino et al., 2009; Pritchard & Falci, 2020; Rogers, 2019; Russell et al., 2017; Saasa & Miller, 2021; Sairsingh et al., 2018; Schrag et al., 2019; Stein et al., 2013; Sun et al., 2009; Szanton et al., 2014; Szanton et al., 2010; Tay et al., 2022; Taylor et al., 2014; Tsuchiya et al., 2018; Whitaker et al., 2021; Williams et al., 2021; Woo et al., 2014) except for three (Hurwich-Reiss et al., 2019; Sims et al., 2020; Woo et al., 2014) and financially strained adults without depression did not have a higher risk of suicidal ideation than their non-strained peers. (Bryan & Bryan, 2019; Lubas et al., 2020) However, in longitudinal studies, financial strain always predicted more symptoms of depression and anxiety over time, (Adesogan et al., 2022; Andrade et al., 2017; Bialowolski et al., 2021; Bromberger et al., 2017; Buckingham-Howes et al., 2019; Daundasekara et al., 2021; Krause, 2009; Li, Liang, et al., 2020; Li, Zheng, et al., 2020; Manuel et al., 2012; McCormick et al., 2018; Nam, 2016; Shippee et al., 2019; Spivak et al., 2019; Suglia et al., 2011; Wickrama et al., 2010; Wickrama et al., 2012; Wickrama, O’Neal, & Lorenz, 2018; Wilkinson, 2016) except for one study that adjusted for housing and food insecurity, (Weida et al., 2020) and predicted increased suicidal ideation risk in a suicide prevention program. (Gilman et al., 2013) Similarly, financial strain predicted post-partum depression longitudinally (Jewell et al., 2015) despite not having a cross-sectional association. (Liu & Tronick, 2013) Likewise, financial strain was typically associated with more post-traumatic stress symptoms in cross-sectional (Hamby et al., 2018; Holmes et al., 2021; Russell et al., 2017; Schrag et al., 2019) and longitudinal analyses, (Lucas-Thompson & Holman, 2013) except for two cross-sectional studies. (Rao et al., 2015; Sims et al., 2020) Financial strain was also associated with poorer quality of life in both cross-sectional (Abel et al., 2016; Albelda et al., 2019; Banyard et al., 2017; Clay et al., 2018; Garey et al., 2017; Lyons et al., 2022) and longitudinal analyses (Shah et al., 2012; Tucker et al., 2010) except that one cross-sectional study of older adults found an association with better quality of life. (Bazargan et al., 2023) Financial strain was also typically (Hamby et al., 2018; Krause & Hayward, 2015; Messersmith et al., 2014; Pritchard & Falci, 2020; Sabella & Suchan, 2019; Stein et al., 2013; Williams et al., 2021) but not always (Gamaldo et al., 2021; Hou et al., 2021) associated with less life satisfaction in cross-sectional analyses, whereas it consistently predicted greater declines in life satisfaction longitudinally (Brown & Barrett, 2011; Shippee et al., 2019; Wickrama et al., 2022) except when adjusting for health status. (Greil et al., 2019) Financial strain was also associated both cross-sectionally and longitudinally with more psychological distress ((Acevedo et al., 2014; Adams et al., 2016; Lee et al., 2015; Lincoln & Chae, 2010; Mitchell & Christian, 2017) and (Hill et al., 2013; Wickrama & O’Neal, 2021b; Young & Schieman, 2012), respectively), more stress ((Albelda et al., 2019; Cole et al., 2011; Karlson et al., 2013; Scott et al., 2011) and (Adesogan et al., 2022; Hedgeman et al., 2018; Woods, Mitchell, Percival, et al., 2009), respectively), and less well-being ((Blea et al., 2021; Chen & Chen, 2021; Hamilton et al., 2013; Huffman et al., 2015; Kim et al., 2015; Lee, 2019; Lee et al., 2016; Lee & Woo, 2013; Northern et al., 2010; Williams et al., 2021) and (Avis et al., 2021), respectively).
Financial Strain and Physical Health
Financial strain was also consistently associated with relatively poorer physical health and greater chronic disease burden, including in many studies that statistically adjusted for other socioeconomic factors and even in some studies that adjusted for health factors, which should mediate relationships with health (Tables 3 & 4). Specifically, financial strain was consistently associated with poorer self-rated health in cross-sectional (Abel et al., 2016; Albelda et al., 2019; Black et al., 2009; Carlson et al., 2013; de Castro et al., 2010; Enriquez et al., 2018; Evans et al., 2020; Garey et al., 2017; Jang et al., 2009; Ko et al., 2014; Krause & Hayward, 2015; Krause et al., 2018; Li & Mutchler, 2019; Marshall & Tucker-Seeley, 2018; McCloskey, 2022; Savoy et al., 2014; Snyder et al., 2020; Tabler & Mykyta, 2021; Tarasenko & Schoenberg, 2017; Tucker-Seeley et al., 2013) (Table 3) and longitudinal studies (Adesogan et al., 2022; Barton et al., 2018; Bialowolski et al., 2021; Lee et al., 2021; Shippee et al., 2012; Wickrama et al., 2022; Wickrama & O’Neal, 2021b) (Table 4) except when adjusting for food and housing insecurity (Weida et al., 2020) or other health factors. (Oates, 2016) Financial strain also predicted physical health outcomes including higher mortality risk in population-based studies of older adults that accounted for other socioeconomic factors and baseline health, (Ottenbacher et al., 2012; Tucker-Seeley et al., 2009) and a higher risk for incident heart disease. (Moran et al., 2019) Financial strain was associated with larger body mass index both cross-sectionally (Averett & Smith, 2014; Cuevas et al., 2019; Kim et al., 2020; Marshall et al., 2019; Ross & Hill, 2013) and longitudinally. (Isasi et al., 2016; Wickrama et al., 2022; Wickrama et al., 2021b) Financial strain was also typically associated with greater cardiometabolic risk cross-sectionally (Krause et al., 2018; Mawhorter et al., 2023; Tarasenko & Schoenberg, 2017; Thurston et al., 2014) except among young adults, (Goldberg et al., 2019) and predicted greater cardiometabolic risk over 13–20 years of follow up among young and middle-aged adults (Doom et al., 2016; Doom et al., 2017; Wickrama, O’Neal, & Neppl, 2018) but not in studies that followed adults for 1–8 years (Bialowolski et al., 2021; Boen, 2019; Cuevas et al., 2021) nor in another study that adjusted for other health factors. (Child et al., 2022) Although financial strain did not predict incidence of diabetes (Karvonen-Gutierrez et al., 2018) in one cohort study, it predicted worse glycemic control in both cross-sectional (Walker et al., 2021) and longitudinal studies (Cutrona et al., 2015; Puterman et al., 2012; Walker et al., 2020) and increased likelihood of incident diabetic kidney disease. (Corwin et al., 2021) Financial strain was also associated cross-sectionally with disease management outcomes, including less self-efficacy,(Novak et al., 2017; Tucker-Seeley, Mitchell, et al., 2015; Zhang et al., 2020) patient activation, (Gleason et al., 2016) coping, (Karlson et al., 2013) and self-care. (Osokpo et al.) Although it was not associated with medication adherence among healthy adults, (Strickland et al., 2019) financial strain was associated in both cross-sectional and longitudinal analyses with less medication adherence among those with chronic conditions ((Adinkrah et al., 2020; Osborn et al., 2017; Simmons et al., 2021) and (Lyles et al., 2016), respectively) as well as more symptom burden and distress ((Boehmer et al., 2016; Lyons et al., 2022; Mazanec et al., 2021; Tellechea et al., 2021) and (Dusendang et al., 2019; Harlow et al., 2017; Odle-Dusseau et al., 2018; Shah et al., 2012), respectively), and more pain ((M.C. Evans et al., 2019; Greenspan et al., 2021; Lyons et al., 2022; Marshall et al., 2018; Rios & Zautra, 2011; Song et al., 2021) and (Wickrama et al., 2021b), respectively).
Financial Strain and Biological Health
Financial strain was also associated with biologic measures of aging (Tables 3 & 4), including in studies that accounted for socioeconomic factors and health status. Although financial strain was not associated with telomere length, (Schrock et al., 2018) cortisol (Puterman et al., 2013; Woods, Mitchell, & Smith-Dijulio, 2009) or allostatic load scores(Berg et al., 2017) among young and middle-aged adults, financially strained adults typically had higher levels of C-reactive protein (Boen, 2019; Guardino et al., 2017; Qintar et al., 2017; Samuel, Szanton, Fedarko, et al., 2020) except when adjusting for health status among middle-aged adults,(Sturgeon et al., 2016) and higher levels of cytokine IL-6 (Hladek et al., 2022; Samuel, Szanton, Fedarko, et al., 2020; Sturgeon et al., 2016) and oxidative stress scores. (Palta et al., 2015) Although financial strain did not predict epigenetic markers for biologic aging within four years in one study, (Simons et al., 2019) it did predict change over eight years in the same study (Simons et al., 2016) and in another longitudinal study. (Lei et al., 2021)
Financial Strain and Functional Health
Financial strain was also associated with relatively poorer cognitive and functional health (Tables 3 & 4). Financial strain was associated with more functional limitations in three cross-sectional studies (Garasky et al., 2012; Karvonen-Gutierrez & Ylitalo, 2013; Szanton et al., 2010) and faster functional declines in four longitudinal studies, (Klopack et al., 2021; Lange-Maia et al., 2019; Neppl et al., 2021; Phillips & Stuifbergen, 2009, 2010; Samuel et al., 2019; Wickrama et al., 2010; Wickrama et al., 2021a; Ylitalo et al., 2013) although it was not associated with number of limitations among older adults with existing disability (Liu et al., 2022) and did not predict decline in one study that adjusted for other health factors, (Klopack et al., 2021; Monserud, 2019) Although financial strain was not associated with poorer cognitive function in one cross-sectional study, (Szanton et al., 2010) it was in two other studies (Assari et al., 2020; Garasky et al., 2012) and typically predicted faster cognitive decline over time (Kolli et al., 2021; Neppl et al., 2021; Sachs-Ericsson et al., 2009; Samuel, Szanton, Wolff, et al., 2020; Strawbridge et al., 2011; Wickrama et al., 2021a; Wickrama & O’Neal, 2021a; Yaffe et al., 2013; Zeki Al Hazzouri et al., 2017) except when adjusting for potentially mediating health factors. (Barba et al., 2021; Vigoureux et al., 2021) Financial strain also predicted a higher risk of subsequent frailty (Peek et al., 2012) despite not having a cross-sectional relationship. (Hladek et al., 2020) It was mostly but not always(Barajas-Gonzalez et al., 2021; Gamaldo et al., 2014) associated with poorer sleep in cross-sectional (Bazargan et al., 2019; Hall et al., 2009; Matthews et al., 2019; Morris et al., 2021; Russell et al., 2017) and longitudinal analyses. (Adesogan et al., 2022)
Financial strain and Health Behaviors
Financial strain was associated with some, but not all the health behaviors examined in reviewed studies (Tables 3 & 4). Financial strain was associated with more tobacco use in both cross-sectional (S. Assari et al., 2019; Evans et al., 2020; Harley et al., 2014; Rogers et al., 2018; Slopen et al., 2012; Waters et al., 2019) and longitudinal studies, (Advani et al., 2014; Han & Seo, 2021; Shaw et al., 2011) except in one study. (Macy et al., 2013) Although cross-sectional studies found no associations between financial strain with smoking abstinence (Reitzel et al., 2015; Tucker-Seeley, Selk, et al., 2015) longitudinal data shows that financially strained smoking adults are less likely to successfully quit smoking. (Kalkhoran et al., 2018; Kendzor et al., 2010; Vinci et al., 2017) Financial strain was also associated with poorer dietary quality, (Harley et al., 2014; Heredia et al., 2020) more unhealthy weight control behaviors, (Simone et al., 2021; VanKim & Laska, 2012) and lower physical activity levels. (Advani et al., 2014; Macy et al., 2013; VanKim & Laska, 2012) There was also some evidence linking financial strain to a higher risk of engaging in crime. (Dennison, 2019; Hotton et al., 2020) However, there was no clear association with alcohol use; four cross-sectional (S. Assari et al., 2019; Cook et al., 2013; Cook et al., 2020; Evans et al., 2020) and two cohort studies found more alcohol use among financially strained adults, (Belogolovsky et al., 2012; Serido et al., 2014) but most cross-sectional (Shervin Assari, James L. Smith, Mohammed Saqib, et al., 2019; Shervin Assari, James L. Smith, Marc A. Zimmerman, et al., 2019; Blau et al., 2013; Gerber et al., 2020; Marshall et al., 2019) and longitudinal studies found no association. (Buckingham-Howes et al., 2019; Shaw et al., 2011; Spivak et al., 2019; Wahler, 2015) There was also not strong evidence linking financial strain to the use of other substances; two studies found a higher risk of drug use, (Austin & Shanahan, 2017; Gerber et al., 2020) but most studies did not find associations with drug use (Bazargan et al., 2020; Cleland et al., 2021; Krause et al., 2017) or abstinence from drugs. (Kalkhoran et al., 2018; Wahler & Otis, 2014) Similarly, although one cross-sectional study found that financially strained adults were more likely to have unprotected anal intercourse (Ayala et al., 2012) there was no evidence of higher sexual risk scores (Batchelder et al., 2016) or incidence of sexually transmitted infection(s). (Kipke et al., 2020)
Financial Strain and Social Needs
Financial strain was also associated with more social needs among adults (Tables 3 & 4). Although financial strain was not associated with low social support (Bradley et al., 2020) except among caregivers, (Karlson et al., 2013) it was correlated with less engagement in activities (Bulkley et al., 2021; Lai et al., 2019) and predicted more loneliness in one cohort study (Wickrama et al., 2022; Wickrama et al., 2021a; Wickrama & O’Neal, 2021b) and greater caregiver burden in two cohort studies. (Bradley et al., 2009; Liu et al., 2019) Financial strain was also associated with a higher risk of experiencing relationship problems (Cabrera et al., 2019; Wickrama & O’Neal, 2019; Williams et al., 2015) and intimate partner violence (Golden et al., 2013; Hardie & Lucas, 2010; Lucero et al., 2016; O’Connor & Nepomnyaschy, 2020; Siconolfi et al., 2021; Spencer et al., 2016; Whitton et al., 2021) and perpetrating violence. (Schwab-Reese et al., 2016; Spencer et al., 2016)
Financial strain also co-occurred with reduced access to health care and other basic needs, even when adjusting for other socioeconomic factors (Cobb et al., 2022; Esselen et al., 2021; Hernandez et al., 2017; Jiang et al., 2016; Jones et al., 2021; Kertesz et al., 2021; Kim, 2021; Rohatgi et al., 2021; Tabler & Mykyta, 2021; Testa & Jackson, 2020) (Tables 3 & 4). Although financially strained adults did not differ with regard to using recommended health care services, (Adegboyega et al., 2022; Leak et al., 2015) they typically reported poorer access to outpatient health care services (Cobb et al., 2022; Jones et al., 2021; Whipps et al., 2021) and sometimes (Jiang et al., 2016; Noh et al., 2022) but not always (Joyce et al., 2020) had less knowledge about care options. Financially strained adults are also more likely to lack basic needs like food, housing, and health care. (Esselen et al., 2021; Hernandez et al., 2017; Kertesz et al., 2021; Kim, 2021; Rohatgi et al., 2021; Tabler & Mykyta, 2021; Testa & Jackson, 2020)
Discussion
This extensive study identified a deep and broad body of literature that establishes a clear connection between financial strain and a range of health outcomes across the adult lifespan. Financial strain was consistently associated with poorer outcomes for mental health, physical health, cognitive, and functional health as well as biologic factors, social factors, and other social needs. Importantly, associations were found in population-based samples and across samples diverse in race, age, disability status, health status, and pregnancy status, demonstrating broad generalizability of these findings. Associations were found in studies that adjusted for other socioeconomic conditions, suggesting that the relationships between financial strain and health outcomes operate independently of other socioeconomic conditions. Most notably, more than one-third of the papers summarized found associations with financial strain despite using statistical models that adjusted for mediating health conditions, suggesting that financial strain operates through multiple intervening mechanisms. These results demonstrate the key role of financial strain as a social determinant of health.
These findings support the idea that financial strain influences multiple health outcomes through many intervening pathways over the life course (Phelan et al., 2010). Importantly, financial strain has been theorized to operate through two key pathways, and this study provides empirical evidence supporting both mechanisms of action. First, financial strain is believed to influence health by constraining access to basic necessities (Phelan et al., 2010; Tucker-Seeley & Thorpe, 2019). This study found that financially strained adults were more likely than their peers to lack basic needs such as food and housing. We also found that statistical adjustment for these factors weakens the associations between financial strain with health outcomes, suggesting that they mediate the relationships with health. Second, financial strain is believed to influence health by activating stress-response mechanisms (Phelan et al., 2010; Tucker-Seeley & Thorpe, 2019) and this study found that financial strain is associated with stress-sensitive biologic measures including CRP and IL-6. Importantly, the finding of somewhat stronger associations between financial strain and health-relevant outcomes in longitudinal vs. cross-sectional studies suggests that the effects of financial strain on health may accumulate over time, which is consistent with the concept of cumulative disadvantage (Dannefer, 2003). This finding contributes to the literature by suggesting that the effects of the two financial strain pathways likely accumulate over time. Together, these results suggest that efforts to address financial strain at any point over the lifespan or across disease processes (i.e. primary, secondary, and tertiary prevention) may prevent subsequent decline, and ameliorate its effect over time.
Limitations & strengths
Studies reviewed here are observational and did not manipulate financial strain, which precludes causal inference. This study focused on the U.S. context and findings in other countries may differ. Only published research was used to draw conclusions and this approach has potential for publication bias. Since financial strain was not part of the research question for all studies, some studies may not have accounted for potentially confounding factors and some studies adjusted for potentially mediating factors; both approaches could contribute to bias. This systematic review is strengthened by an exhaustive search of the literature for terms synonymous with financial strain and a broad set of health outcomes. Importantly, the focus on the operational definition of financial strain produced a set of papers measuring the same concept despite the use of different terminology.
Implications
These findings have important policy implications. Because financial strain captures the sufficiency of income for basic needs, financial strain can be reduced by increasing household income, other household resources (such as food) and/or reducing household expenses. As highlighted in a recent summary (Nykiforuk et al., 2023), natural experimental studies have highlighted promising policy-based strategies. As examples, increased minimum wages (Sabia & Nielsen, 2015) and tax credits including the Earned Income Tax Credit and the Child Tax Credit (Hoynes, 2019) have been shown to reduce poverty and should have a similar effect on financial strain. Similarly, increasing benefits and expanding the scope of eligibility for safety net programs such as Medicaid, the Special Supplemental Nutrition Program for Women, Infants, and Children, and the Supplemental Nutrition Assistance Program for households vulnerable to experiencing financial strain can improve people’s ability to afford basic needs such as food, health care and transit (Baicker et al., 2013; Kim, 2016). These results demonstrate the money is fungible within households and that reducing the cost of one basic need (e.g. health care) can improve the household’s ability to meet other basic need (e.g. food, transit). However, economic policies and income support programs each target different subgroups of people and there is a need to better understand how to leverage policy solutions to universally address financial strain and related health disparities across all income groups. Therefore, the current findings underscore the need to prioritize studies evaluating the health impact of policies and programs among all income groups experiencing financial strain.
These findings also have important clinical implications in providing timely evidence to inform social needs screening for financial strain. Despite recommendations to implement financial strain screening, uptake has been slow (Fraze et al., 2019) due to several factors. First, financial strain has not typically been prioritized for social needs screening. For example, the CMS tool described above lists financial strain as a supplemental, not core, question. However, this study provides evidence to support the prioritization of financial strain as a social need that is important to health outcomes. Importantly, although findings from this study show that financial strain co-occurs with other social needs, like food insecurity and housing insecurity, evidence elsewhere suggests that screening for financial strain should be conducted alongside but not instead of other social needs screening to avoid missing important social needs (Hanmer et al., 2023). Secondly, the implementation of financial strain screening has multiple practical barriers, including time constraints, gaps in understanding which services best address financial strain , limited access to and resources for the social workers and case managers who have the expertise needed to integrate social care and health care, and limited capacity within community social service agencies to ethically respond to positive screenings (Kreuter et al., 2021). Therefore, there is a need for more implementation research to evaluate if and how to conduct financial strain screening in ways that improve patient care and health outcomes. There is also a need to build capacity within health care and social services sectors to increase access to care and better integrate care. The current study findings underscore the urgent need to address these barriers to social needs screening and improve access to services for people facing financial strain. Importantly, financial strain is stigmatizing suggesting that efforts to identify and address financial strain should be done in a sensitive and supportive manner.
Conclusion
This study is the largest and most comprehensive analysis to date of the vast literature that consistently links financial strain to poorer outcomes for mental health, physical health, cognitive and functional health as well as biologic factors, social factors, and other social determinants of health. This study provides evidence of predictive validity for two distinctly different but simple single-item financial strain questions, thus supporting their use as social needs screeners at points of care and service delivery. These results call for greater attention to addressing financial strain as a key social determinant of health and health disparities across the life-course.
Supplementary Material
Highlights.
Studies captured difficulty making ends meet and/or lacking money for basic needs
Financial strain was consistently associated with numerous outcomes
Two single-item financial strain screeners demonstrate predictive validity
Findings are consistent across settings, samples, measures and methods
Findings highlight that financial strain is a key and under-addressed social need
Acknowledgement and Funding Disclosure:
Dr. Samuel was supported by the National Institute on Aging (K01AG054751). Dr. Abshire Saylor was supported by the Building Interdisciplinary Careers in Women’s Health program of the National Institute of Child Health and Human Development (NICHD) (K12HD085845, PI: Ford). Drs Samuel and Szanton were supported by National Institute on Aging DP1AG069874. Dr Nkimbeng was supported by the National Institute on Aging (1K01AG076807, L60AG069218). The funders were not involved in conducting the study.
Footnotes
Disclosure:
The authors are grateful for the contributions of Jasmine Gil, Stacey Gonzalez, Tiara Askew, Naia Wiggens, Lavbirka Nkefon, Alexander Rike, Danielle Ramsey, Lydia Koh Krienke, Safiyyah Okoye, Hannah Mikus, Alice Gonzalez, Caroline Sacko, Rachel Austin, Melissa Lutz, and Rebecca Wright who participated in screening and/or data extraction.
Ethical approval was not required for this systematic literature review study because it was not human subjects research.
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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