Racial, ethnic, and socioeconomic survival disparities have been well-demonstrated across population-based and clinical trial datasets in pediatric hematologic malignancies. To date, these analyses have relied on trial-collected data such as race, ethnicity, insurance, and zip code. These exposures serve as proxies for factors such as structural racism, genetic ancestry, and adverse social determinants of health (SDOH). Systematic measurement of SDOH and social needs—and interventions targeting these needs—are feasible in pediatric oncology. We use these data to present a roadmap for the next decade of health equity research to identify actionable mechanisms and develop a portfolio of interventions to advance equitable outcomes across pediatric hematologic malignancies.

Learning Objectives

  • Describe a framework for advancing health equity in pediatric oncology

  • Describe examples of interventions targeted to social determinants of health with a focus on targeting poverty and unmet social needs

You are seeing a 3-year-old child with B-cell acute lymphoblastic leukemia (ALL) who was recently discharged after completion of induction chemotherapy. Meeting her family, you learn that she is 1 of 3 children. Her parents emigrated from Mexico, and her mother had to quit her job as a cashier to be at her daughter's bedside during hospitalizations and to bring her to upcoming frequent appointments. The child is currently enrolled on Medicaid; her family is struggling to buy food for their family and is behind on rent for their 1-bedroom apartment.

As you look ahead to the next 2 years of therapy, you wonder how these factors will affect this child's care. Is she at risk of worse outcomes? If so, which factors drive that risk? And most importantly, what—if anything—can we as clinicians do about them?

In the era of contemporary therapy, the vast majority of children with pediatric hematologic malignancies will survive their cancer due to significant medical advances refined in cooperative group trials. Despite these advances, not all children have equitable opportunities for cure. Children who are Black, Hispanic, or living in poverty experience inequitable survival outcomes across pediatric hematologic malignancies.

Despite enrollment on clinical trials, Black and Hispanic children with B-cell acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) treated in Children's Oncology Group (COG) clinical trials experienced inferior survival outcomes compared to non-Hispanic White children.1,2 In ALL, insurance partially mediates the relationship between Hispanic ethnicity and survival, while in AML, higher disease burden and acuity at presentation requiring intensive care unit (ICU)-level care may contribute to early mortality.3,4 Similar survival disparities have been observed among children with ALL treated in Dana-Farber Consortium trials living in high-poverty zip codes.5 While frontline trial enrollment has mitigated survival disparities for Black and Hispanic children and adolescents/young adults with Hodgkin lymphoma, they experience higher rates of postrelapse mortality, suggesting disparities in postrelapse care.6 

These data demonstrate survival disparities by race, ethnicity, and proxied socioeconomic factors across diseases with variable prognoses; by inpatient vs outpatient care; and despite standardized care on clinical trials. Yet, limited by available collected data, analyses have focused on description (Figure 1). There is a pressing need to shift research away from description and toward mechanisms and interventions. We present a roadmap for the next decade of health equity research focused on identifying the mechanisms driving inequitable outcomes and opportunities to address them. We specifically delve into the evidence base for poverty-targeted interventions addressing unmet social needs in pediatric oncology.

Figure 1.

Proposed framework to measure drivers of disparities. CAR-T, chimeric antigen receptor T-cell therapy; MIBG, iodine meta- iodobenzylguanidine therapy; SNP, single nucleotide polymorphism.

Figure 1.

Proposed framework to measure drivers of disparities. CAR-T, chimeric antigen receptor T-cell therapy; MIBG, iodine meta- iodobenzylguanidine therapy; SNP, single nucleotide polymorphism.

Close modal

While race, ethnicity, and proxied socioeconomic status measures such as zip code and insurance can identify disparities, they do not adequately identify underlying mechanisms that can be targeted in the clinical setting. Race and ethnicity are constructs that proxy exposures to structural racism and racial discrimination; they may separately proxy genetic ancestry. While insurance and zip code can be indicators of health care access, as proxies for individual-level exposures such as low income or education, they are prone to misclassification.7-9 Identification of actionable targets for intervention requires measurement of self-reported individual- and family-level SDOH and social needs.

Communities impacted by structural racism disproportionately experience adverse SDOH—the conditions in which individuals live, learn, play, grow, and work. Social needs are individual-level modifiable factors arising from adverse SDOH that can provide targets for intervention. As 1 example, household material hardship (HMH) is a social need measure well-studied in pediatric oncology and defined as lack of consistent access to adequate food, housing, transportation, or utilities.10 

The feasibility of systematic SDOH screening, including social needs such as HMH, across the care continuum, from cancer diagnosis to relapse/progression and survivorship,11 has now been demonstrated across multiple contexts including among historically marginalized populations and in clinical trials. SDOH data have been successfully collected as embedded aims of national multicenter clinical trials including within the Dana-Farber Cancer Institute ALL Consortium (NCT03020030) and Children's Oncology Group (NCT03126916, NCT03914625, NCT06172296) trials with >85% participation and minimal data missingness (<2% for HMH, the primary SDOH exposure of interest in each investigation).11,12 From these data, we have learned that approximately 1 in 3 children enrolled in national multicenter trials for de novo cancer experiences HMH,11,12 and 1 in 2 children with advanced cancer treated at a single, large volume center experiences HMH.13 Black and Hispanic families disproportionately experience HMH, with nearly 3 of 4 families reporting unmet social needs during their child's cancer care.14 These data provide proof of principle that SDOH data collection is highly feasible and that social needs are highly prevalent in pediatric oncology despite care at well-resourced centers with access to social workers, financial specialists, and resource specialists.

Critical next steps in advancing health equity research include identifying associations between modifiable SDOH and child and family outcomes. In a recent study, HMH was independently associated with severe psychological distress among parents of children enrolled on a multicenter therapeutic phase 3 trial for de novo ALL.15 Compared to unexposed parents, HMH-exposed parents were twice as likely to experience severe psychological distress at trial enrollment and 5 times as likely 6 months into therapy. As data mature from this trial and others in which SDOH have been prospectively collected, future analyses will examine associations between adverse SDOH and child health outcomes including health care utilization, survival, and quality-of-life. Systematic SDOH data collection in future therapeutic clinical trials leverages existing trial data collection infrastructure, ensures nationally representative populations, and maximizes homogeneity of disease and treatment to facilitate the identification of SDOH exposures independently associated with outcomes. As such, trial-collected data can both elucidate mechanisms by which SDOH contribute to outcome inequities and identify SDOH targets for intervention.

As health equity investigation enters the next decade, a focus on biology in addition to SDOH is key to understanding mechanisms driving inequities. Duffy null–associated neutrophil count is 1 example of a genetic ancestry–associated biological difference that may lead to clinical trial ineligibility and consequent disparities in trial diversity.16 Identifying mechanisms driving disparate outcomes for marginalized groups will require investigating potential contributory roles of both genetic ancestry and toxic stress. First, investigators should leverage trial-collected biology specimens to investigate the role of genetic ancestry in driving differential tumor biology and treatment toxicities. Examples include the higher frequency of risk-conferring IKZF1 alterations among pediatric patients of Hispanic ethnicity17 and the association of genetic ancestry with ALL subtypes and survival.18,19 Second, investigations should focus on the role of toxic stress, the mechanism by which severe and prolonged exposure to adverse SDOH lead to physiologic changes. Recent studies have identified DNA methylation changes associated with adverse SDOH among both childhood cancer survivors and healthy young adults.20,21 Further investigations of toxic stress in the context of pediatric oncology treatment resistance and toxicity may identify additional drivers of inequities.

Racially, ethnically, and socioeconomically marginalized families have been historically underrepresented in pediatric oncology research due to structural participation barriers. Extrapolating from data in the adult oncology context, underrepresentation has historically been blamed on distrust.22 A recent mixed-methods study of Black and Hispanic parents of children with cancer challenges this concept and found that Black and Hispanic parents express high trust in their oncology teams and are willing to enroll their children in pediatric oncology research and clinical trials if offered.23 Ninety-four percent of families from historically marginalized communities approached for this study consented to participate, highlighting their willingness to engage in research. Qualitatively, parents named representation of their experiences and voices in research as a key motivator to research participation. These data provide proof-of-concept that historically marginalized families can and should be engaged in pediatric oncology research. Distrust cannot not be used as an excuse for underrepresentation, and underrepresentation should prompt critical examination into participation and retention.

Investigators should prioritize the perspectives of historically marginalized parents and communities across the research continuum, including in the selection of relevant research questions, study and intervention design, data interpretation, and framing/dissemination of the results (Figure 2). These perspectives should be incorporated across the continuum from clinical trial inception to the real-world implementation of efficacious therapies to ensure that advances do not widen inequities for historically marginalized groups and that potential barriers to equitable uptake are proactively addressed. Finally, engaging voices from historically marginalized groups requires consideration of barriers to research partnerships, such as timing, mode and frequency of meetings (virtual vs in person; work hours vs evenings), transportation, and childcare; thus, providing adequate support and compensation to facilitate participation is required.

Figure 2.

Community and parent engagement over the life course of a study.

Figure 2.

Community and parent engagement over the life course of a study.

Close modal

Interventions addressing poverty, SDOH, and social needs improve child outcomes in general pediatrics. Specifically, systematic screening and resource navigation decrease unmet needs, improve child health, increase on-time vaccination and preventative health visits, and decrease emergency department visits.24-26 Building on these foundational approaches to develop a portfolio of supportive care health equity interventions for the subspecialty setting has the potential to improve cancer outcomes. Reductions in toxicity and improvements in survival for pediatric hematologic malignancy have been successfully realized over the past decades with risk-stratified treatment and risk-stratified supportive care (eg, antimicrobial prophylaxis, leucovorin rescue). A similar framework for developing supportive care health equity interventions that target high-risk SDOH and social needs modeled on drug trial development has now been established and includes health equity intervention: 1) pilot and refinement in a single-center trial, 2) pilot feasibility and signal-finding in a 2-center trial, and 3) randomized efficacy evaluation in a multicenter clinical trial with the ultimate goal of real-world implementation of efficacious interventions.

The Pediatric CARE (Cancer Resource Equity) intervention targets food and transportation insecurities with provision of centrally delivered grocery and transportation resources to families with HMH for 6 months after a new cancer diagnosis. This intervention builds on systematic social needs screening and referral to community-based resources in general pediatrics24-26 by directly providing resources to address the acute and life-threatening nature of childhood cancer. In a single-center pilot study, PediCARE was refined based on parent feedback to optimize intervention duration (from 3 to 6 months), dose (broadened scope of transportation support), and intervention delivery logistics.27 Feasibility of multicenter, randomized administration of the refined PediCARE was subsequently demonstrated in a 2-center pilot of with 100% consent to enrollment and randomization and 0% attrition over 6 months; all families randomized to PediCARE successfully received resources.28 PediCARE is currently being evaluated for efficacy in a randomized phase 3 trial as an embedded aim of Dana-Farber Cancer Institute 23-001, a phase 3 multicenter trial for de novo ALL.

The Pediatric RISE (Resource Intervention to Support Equity) intervention targets income poverty by providing an unrestricted cash transfer to families of children with cancer with annual household income <200% of the federal poverty threshold. RISE builds on population-level and general pediatric data demonstrating that direct financial support—termed cash transfer—is feasible and associated with improved child and family outcomes.29-35 RISE was refined in a single-center pilot among families of children with newly diagnosed or advanced cancer with high acceptability (95% participation and 0% attrition). Intervention refinement included an increase in the standardized dollar amount provided to account for treatment-related financial toxicity. The feasibility of the refined RISE intervention is currently being evaluated in a 2-center randomized pilot of children with newly diagnosed cancer.

The CHEF (Cardiovascular Health Equity through Food) intervention targets food insecurity among families in the first year following completion of cancer-directed therapy with provision of meal kits (fresh ingredients paired with recipes) and assisted nutrition benefits enrollment. This intervention model is based on general pediatric and internal medicine data that “food is medicine” interventions, which provide food directly to patients to address food insecurity and prevent or treat diet-sensitive chronic illness, improve food security status, diet quality, and cardiometabolic risk.36-38 CHEF was refined in a single-center pilot with high acceptability (100% participation, 0% attrition). Refinements in response to parent feedback included extended intervention duration (3 to 6 months) and need for a step-down period of less-intensive food support (grocery gift cards for months 3-6). CHEF will undergo proof-of-concept testing to evaluate its signal of impact on cardiovascular-relevant outcomes (dietary quality, food security status, and cardiometabolic risk condition control) in an upcoming single-site study.

The ASSIST (Assisted Benefits Navigation Support) intervention targets HMH by providing real-time, centralized, means-tested benefits navigation and enrollment assistance for families of children with cancer. This intervention model is based on population-level data that benefits such as the Supplemental Nutritional Assistance Program; Women, Infants, and Children Program; and the Earned Income Tax Credit improve maternal and child health.39,40 ASSIST was developed with the input of a racially, ethnically, and socioeconomically diverse cohort of parents who identified the need for systematic social needs evaluation and hands-on support accessing resources due to limited bandwidth and time during their child's cancer care. ASSIST will undergo pilot and refinement testing in an upcoming single center study.

Developing and evaluating health equity interventions that target multiple SDOH across the pediatric oncology care continuum is feasible (Figure 3). Just like drugs, efficacy evaluation of novel health equity interventions requires sample sizes achievable only in the pediatric cooperative group setting given the rarity of childhood cancer. Development of an evidence-based portfolio of supportive care health equity interventions will require the equivalent of an early-phase drug pipeline infrastructure to refine interventions and subsequent active support from the National Cancer Institute (NCI) and pediatric cooperative groups to evaluate equity intervention efficacy in the existing clinical trials research infrastructure, given that no similar federally supported infrastructure dedicated to SDOH-targeted interventions exists.41 

Figure 3.

Intervention models targeting social needs in pediatric oncology that demonstrate feasibility and provide a framework for future interventions.

Figure 3.

Intervention models targeting social needs in pediatric oncology that demonstrate feasibility and provide a framework for future interventions.

Close modal

While the prognosis for a 3-year-old with standard risk leukemia is excellent, data suggest that this child is at risk for inferior outcomes based on her public insurance.1 The family-reported HMH (food and transportation insecurity) increases her parents' risk for severe psychological distress during therapy with downstream implications for the child. The identification and reassessment of these needs over the course of therapy and the subsequent connection to available resources are important first steps. Evidence-based intervention to mitigate her risks will rely on future translational and clinical investigation.

Pediatric oncologists are facile at molecular prognostication and risk-stratified therapy in hematologic malignancies; analogous consideration of SDOH as independent prognostic factors and targets for risk-stratified supportive care delivery is a next step to improve outcomes. Systematic evaluation of SDOH and development and evaluation of health equity interventions is feasible in pediatric hematologic malignancies. By embedding health equity investigation into all aspects of pediatric oncology research (Figure 4), investigators can identify mechanistic drivers of inequities and build a portfolio of interventions to eliminate outcome inequities across the cancer care continuum. True scalability and impact of such efforts will require explicit support, funding, and infrastructure from pediatric oncology cooperative groups, trial consortia, and the NCI. In the next decade, systematic integration of SDOH into risk stratification for pediatric hematologic malignancies combined with risk-stratified health equity intervention is necessary to complement disease-directed therapies and improve pediatric hematologic malignancy outcomes.

Figure 4.

A roadmap for health equity research in pediatric oncology. NIH, National Institutes of Health.

Figure 4.

A roadmap for health equity research in pediatric oncology. NIH, National Institutes of Health.

Close modal

Figures created with biorender.com.

Puja J. Umaretiya: no competing financial interests to declare.

Rahela Aziz-Bose: no competing financial interests to declare.

Colleen Kelly: no competing financial interests to declare.

Kira Bona: no competing financial interests to declare.

Puja J. Umaretiya: Nothing to disclose.

Rahela Aziz-Bose: Nothing to disclose.

Colleen Kelly: Nothing to disclose.

Kira Bona: Nothing to disclose.

1.
Gupta
S
,
Dai
Y
,
Chen
Z
, et al.
Racial and ethnic disparities in childhood and young adult acute lymphocytic leukaemia: secondary analyses of eight Children's Oncology Group cohort trials
.
Lancet Haematol
.
2023
;
10
(
2
):
e129
-
e141
.
2.
Aplenc
R
,
Alonzo
TA
,
Gerbing
RB
, et al.
Ethnicity and survival in childhood acute myeloid leukemia: a report from the Children's Oncology Group
.
Blood
.
2006
;
108
(
1
):
74
-
80
.
3.
Winestone
LE
,
Getz
KD
,
Miller
TP
, et al.
The role of acuity of illness at presentation in early mortality in Black children with acute myeloid leukemia
.
Am J Hematol
.
2017
;
92
(
2
):
141
-
148
.
4.
Winestone
LE
,
Getz
KD
,
Li
Y
, et al.
Racial and ethnic disparities in acuity of presentation among children with newly diagnosed acute leukemia
.
Pediatr Blood Cancer
.
2024
;
71
(
1
):
e30726
.
5.
Bona
K
,
Blonquist
TM
,
Neuberg
DS
,
Silverman
LB
,
Wolfe
J.
Impact of socioeconomic status on timing of relapse and overall survival for children treated on Dana-Farber Cancer Institute ALL Consortium protocols (2000-2010)
.
Pediatr Blood Cancer
.
2016
;
63
(
6
):
1012
-
1018
.
6.
Kahn
JM
,
Kelly
KM
,
Pei
Q
, et al.
Survival by race and ethnicity in pediatric and adolescent patients with Hodgkin lymphoma: a Children's Oncology Group Study
.
J Clin Oncol
.
2019
;
37
(
32
):
3009
-
3017
.
7.
Casey
JA
,
Pollak
J
,
Glymour
MM
,
Mayeda
ER
,
Hirsch
AG
,
Schwartz
BS
.
Measures of SES for electronic health record-based research
.
Am J Prev Med
.
2018
;
54
(
3
):
430
-
439
.
8.
Link-Gelles
R
,
Westreich
D
,
Aiello
AE
, et al.
Bias with respect to socioeconomic status: a closer look at zip code matching in a pneumococcal vaccine effectiveness study
.
SSM Popul Health
.
2016
;
2
:
587
-
594
.
9.
Brignone
E
,
LeJeune
K
,
Mihalko
AE
,
Shannon
AL
,
Sinoway
LI
.
Self-reported social determinants of health and area-level social vulnerability
.
JAMA Netw Open
.
2024
;
7
(
5
):
e2412109
.
10.
Bona
K
,
London
WB
,
Guo
D
,
Frank
DA
,
Wolfe
J.
Trajectory of material hardship and income poverty in families of children undergoing chemotherapy: a prospective cohort study
.
Pediatr Blood Cancer
.
2016
;
63
(
1
):
105
-
11
.
11.
Aziz-Bose
R
,
Zheng
DJ
,
Umaretiya
PJ
, et al.
Feasibility of oncology clinical trial-embedded evaluation of social determinants of health
.
Pediatr Blood Cancer
.
2022
;
69
(
11
):
e29933
.
12.
Jones
E
,
Naranjo
A
,
Winestone
LE
, et al.
Feasibility and acceptability of social determinants of health data collection in the context of a Children's Oncology Group trial
.
J Clin Oncol
.
2023
;
41
(
16_suppl
):
10010
.
13.
Umaretiya
P
,
Jones
E
,
Heneghan
C
, et al.
Feasibility of systematic social needs screening among families of children with advanced cancer
.
J Pain Symptom Manage
.
2024
;
67
(
5
):
e717
-
e718
.
14.
Valenzuela
A
,
Hawkins
A
,
Revette
A
, et al.
“It's a lot of things”: household material hardship among Black and Hispanic parents of children with cancer
.
Pediatr Blood Cancer
.
2023
:
e30485
.
15.
Umaretiya
PJ
,
Koch
VB
,
Flamand
Y
, et al.
Disparities in parental distress in a multicenter clinical trial for pediatric acute lymphoblastic leukemia
.
J Natl Cancer Inst
.
2023
;
115
(
10
):
1179
-
1187
.
16.
Ruiz
J
,
Kelly
RK
,
Aplenc
R
,
Laetsch
TW
,
Seif
AE
.
Absolute neutrophil count clinical trial eligibility criteria for pediatric oncology phase I and phase I/II trials by sponsorship
.
Pediatr Blood Cancer
.
2024
;
71
(
5
):
e30925
.
17.
de Smith
AJ
,
Wahlster
L
,
Jeon
S
, et al.
A noncoding regulatory variant in IKZF1 increases acute lymphoblastic leukemia risk in Hispanic/Latino children
.
Cell Genom
.
2024
;
4
(
4
):
100526
.
18.
Lee
SHR
,
Antillon-Klussmann
F
,
Pei
D
, et al.
Association of genetic ancestry with the molecular subtypes and prognosis of childhood acute lymphoblastic leukemia
.
JAMA Oncol
.
2022
;
8
(
3
):
354
-
363
.
19.
Newman
H
,
Lee
S
,
Pölönen
P
, et al.
The influence of genetic ancestry on disease biology in pediatric T-cell acute lymphoblastic leukemia
.
Blood
.
2022
;
140
(
suppl 1
):
3458
-
3460
.
20.
Song
N
,
Sim
J-A
,
Dong
Q
, et al.
Blood DNA methylation signatures are associated with social determinants of health among survivors of childhood cancer
.
Epigenetics
.
2022
;
17
(
11
):
1389
-
1403
.
21.
Reuben
A
,
Sugden
K
,
Arseneault
L
, et al.
Association of neighborhood disadvantage in childhood with DNA methylation in young adulthood
.
JAMA Netw Open
.
2020
;
3
(
6
):
e206095
.
22.
Ford
JG
,
Howerton
MW
,
Lai
GY
, et al.
Barriers to recruiting underrepresented populations to cancer clinical trials: a systematic review
.
Cancer
.
2008
;
112
(
2
):
228
-
242
.
23.
Umaretiya
P
,
Valenzuela
A
,
Hawkins
A
, et al.
Exploration of trust among Black and Hispanic parents of children with cancer
.
J Pain Symptom Manage
.
2023
;
65
(
3
):
e266
.
24.
Garg
A
,
Toy
S
,
Tripodis
Y
,
Silverstein
M
,
Freeman
E.
Addressing social determinants of health at well child care visits: a cluster RCT
.
Pediatrics
.
2015
;
135
(
2
):
e296
-
e304
.
25.
Gottlieb
LM
,
Hessler
D
,
Long
D
, et al.
Effects of social needs screening and in-person service navigation on child health: a randomized clinical trial
.
JAMA Pediatr
.
2016
;
170
(
11
):
e162521
.
26.
Sege
R
,
Preer
G
,
Morton
SJ
, et al.
Medical-legal strategies to improve infant health care: a randomized trial
.
Pediatrics
.
2015
;
136
(
1
):
97
-
106
.
27.
Umaretiya
PJ
,
Revette
A
,
Seo
A
, et al.
PediCARE: development of a poverty-targeted intervention for pediatric cancer
.
Pediatr Blood Cancer
.
2021
;
68
(
10
):
e29195
.
28.
Newman
H
,
Jones
E
,
Li
Y
, et al.
Providing groceries and transportation to poverty-exposed pediatric oncology families: the PediCARE pilot randomized clinical trial
.
JAMA Netw Open
.
2024
;
7
(
5
):
e2412890
.
29.
Guanais
FC
.
The combined effects of the expansion of primary health care and conditional cash transfers on infant mortality in Brazil, 1998-2010
.
Am J Public Health
.
2015
;
105
(
S4
):
S593
-
S599
.
30.
Shei
A
,
Costa
F
,
Reis
MG
,
Ko
AI
.
The impact of Brazil's Bolsa Família conditional cash transfer program on children's health care utilization and health outcomes
.
BMC Int Health Hum Rights
.
2014
;
14
:
10
.
31.
Angeles
G
,
de Hoop
J
,
Handa
S
,
Kilburn
K
,
Milazzo
A
,
Peterman
A.
Government of Malawi's unconditional cash transfer improves youth mental health
.
Soc Sci & Med
.
2019
;
225
(
2
):
108
-
119
.
32.
Troller-Renfree
SV
,
Costanzo
MA
,
Duncan
GJ
, et al.
The impact of a poverty reduction intervention on infant brain activity
.
Proc Natl Acad Sci U S A
.
2022
;
119
(
5
).
33.
Noble
KG
,
Magnuson
K
,
Gennetian
LA
, et al.
Baby's first years: design of a randomized controlled trial of poverty reduction in the United States
.
Pediatrics
.
2021
;
148
(
4
):
e2020049702
.
34.
Shafer
PR
,
Gutiérrez
KM
,
Ettinger de Cuba
S
,
Bovell-Ammon
A
,
Raifman
J.
Association of the implementation of child tax credit advance payments with food insufficiency in US Households
.
JAMA Netw Open
.
2022
;
5
(
1
):
e2143296
.
35.
Coughlin
CG
,
Bovell-Ammon
A
,
Sandel
M.
Extending the child tax credit to break the cycle of poverty
.
JAMA Pediatr
.
2022
;
176
(
3
):
225
-
227
.
36.
Hager
K
,
Du
M
,
Li
Z
, et al.
Impact of produce prescriptions on diet, food security, and cardiometabolic health outcomes: a multisite evaluation of 9 produce prescription programs in the United States
.
Circ Cardiovasc Qual Outcomes
.
2023
;
16
(
9
):
e009520
.
37.
Berkowitz
SA
,
Terranova
J
,
Randall
L
,
Cranston
K
,
Waters
DB
,
Hsu
J.
Association between receipt of a medically tailored meal program and health care use
.
JAMA Intern Med
.
2019
;
179
(
6
):
786
-
793
.
38.
Berkowitz
SA
,
Terranova
J.
Medically tailored meals to address the health consequences of food insecurity
.
N Engl J Med
.
2024
;
390
(
9
):
775
-
776
.
39.
Wicks-Lim
J
,
Arno
PS
.
Improving population health by reducing poverty: New York's earned income tax credit
.
SSM Popul Health
.
2017
;
3
:
373
-
381
.
40.
Ettinger de Cuba
SA
,
Bovell-Ammon
AR
,
Cook
JT
, et al.
SNAP, young children's health, and family food security and healthcare access
.
Am J Prev Med
.
2019
;
57
(
4
):
525
-
532
.
41.
Tucker-Seeley
R
,
Abu-Khalaf
M
,
Bona
K
, et al.
Social determinants of health and cancer care: an ASCO policy statement
.
JCO Oncol Pr
.
2024
;
20
(
5
):
621
-
630
.