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Research ArticleOriginal Research

Family Medicine Clinician Screening and Barriers to Communication on Food Insecurity: A CERA General Membership Survey

Stephanie K. Bunt, Matthew Traxler, Bridget Zimmerman, Marcy Rosenbaum, Sally Heaberlin, Peter F. Cronholm, Eliza W. Kinsey and Kelly Skelly
The Journal of the American Board of Family Medicine March 2024, 37 (2) 196-205; DOI: https://doi.org/10.3122/jabfm.2023.230319R1
Stephanie K. Bunt
From the Department of Family Medicine, University of Iowa, Iowa City, IA (SKB, MR, KS); Department of Family Medicine, University of Minnesota, Minneapolis, MN (MT); Department of Biostatistics, University of Iowa, Iowa City, IA (BZ); University of Iowa Carver College of Medicine, Iowa City, IA (SH); Department of Family Medicine and Community Health, Center for Public Health, Leonard Davis Institute, University of Pennsylvania, Philadelphia, PA (PFC, EWK).
PhD
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Matthew Traxler
From the Department of Family Medicine, University of Iowa, Iowa City, IA (SKB, MR, KS); Department of Family Medicine, University of Minnesota, Minneapolis, MN (MT); Department of Biostatistics, University of Iowa, Iowa City, IA (BZ); University of Iowa Carver College of Medicine, Iowa City, IA (SH); Department of Family Medicine and Community Health, Center for Public Health, Leonard Davis Institute, University of Pennsylvania, Philadelphia, PA (PFC, EWK).
MD
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Bridget Zimmerman
From the Department of Family Medicine, University of Iowa, Iowa City, IA (SKB, MR, KS); Department of Family Medicine, University of Minnesota, Minneapolis, MN (MT); Department of Biostatistics, University of Iowa, Iowa City, IA (BZ); University of Iowa Carver College of Medicine, Iowa City, IA (SH); Department of Family Medicine and Community Health, Center for Public Health, Leonard Davis Institute, University of Pennsylvania, Philadelphia, PA (PFC, EWK).
PhD
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Marcy Rosenbaum
From the Department of Family Medicine, University of Iowa, Iowa City, IA (SKB, MR, KS); Department of Family Medicine, University of Minnesota, Minneapolis, MN (MT); Department of Biostatistics, University of Iowa, Iowa City, IA (BZ); University of Iowa Carver College of Medicine, Iowa City, IA (SH); Department of Family Medicine and Community Health, Center for Public Health, Leonard Davis Institute, University of Pennsylvania, Philadelphia, PA (PFC, EWK).
PhD
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Sally Heaberlin
From the Department of Family Medicine, University of Iowa, Iowa City, IA (SKB, MR, KS); Department of Family Medicine, University of Minnesota, Minneapolis, MN (MT); Department of Biostatistics, University of Iowa, Iowa City, IA (BZ); University of Iowa Carver College of Medicine, Iowa City, IA (SH); Department of Family Medicine and Community Health, Center for Public Health, Leonard Davis Institute, University of Pennsylvania, Philadelphia, PA (PFC, EWK).
MD
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Peter F. Cronholm
From the Department of Family Medicine, University of Iowa, Iowa City, IA (SKB, MR, KS); Department of Family Medicine, University of Minnesota, Minneapolis, MN (MT); Department of Biostatistics, University of Iowa, Iowa City, IA (BZ); University of Iowa Carver College of Medicine, Iowa City, IA (SH); Department of Family Medicine and Community Health, Center for Public Health, Leonard Davis Institute, University of Pennsylvania, Philadelphia, PA (PFC, EWK).
MD, MSCE
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Eliza W. Kinsey
From the Department of Family Medicine, University of Iowa, Iowa City, IA (SKB, MR, KS); Department of Family Medicine, University of Minnesota, Minneapolis, MN (MT); Department of Biostatistics, University of Iowa, Iowa City, IA (BZ); University of Iowa Carver College of Medicine, Iowa City, IA (SH); Department of Family Medicine and Community Health, Center for Public Health, Leonard Davis Institute, University of Pennsylvania, Philadelphia, PA (PFC, EWK).
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Kelly Skelly
From the Department of Family Medicine, University of Iowa, Iowa City, IA (SKB, MR, KS); Department of Family Medicine, University of Minnesota, Minneapolis, MN (MT); Department of Biostatistics, University of Iowa, Iowa City, IA (BZ); University of Iowa Carver College of Medicine, Iowa City, IA (SH); Department of Family Medicine and Community Health, Center for Public Health, Leonard Davis Institute, University of Pennsylvania, Philadelphia, PA (PFC, EWK).
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    Figure 1.

    Clinician gender, age and graduate degree year influence Food insecurity (FI) screening based on patient-identified factors. (A) Female clinicians are more likely to screen for FI if a “patient reports a chance in living status compared with male clinicians (OR 1.82; 95% CI 1.26-2.62, P < .0001). (B and C) Clinicians older than 60 yrs. (OR 2.22, 1.09-4.56, P < .02) or who received their degree before 2000 (OR 0.55; 95% CI 0.34-0.89; P = .004) were more likely to screen for FI based on a patient’s history of homelessness or poverty. (D and E) Clinicians younger than 40 yrs. (OR = 0.39; 95% CI = 0.20-0.74; p < 0.0001) or who received their degree after 2010 were more likely to screen for FI based if the subject came up in conversation (OR = 1.81; 95% CI = 1.14-2.87; p =0.003).

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    Figure 2.

    Clinician demographics influence ranking of top 3 barriers to discussing Food insecurity (FI) during patient encounters. (A) Clinicians working in underserved areas were less likely to rank “inadequate time during appointments” as a top barrier (OR 0.58; 95% CI 0.36-0.91; P = .01). (B) Clinicians under 40 yrs. of age were more likely than clinicians over 60 yrs. of age to rank “lack of knowledge about available resources for FI” in the top barriers (OR 0.52; 95% CI 0.27-0.99; P < .05). (C) Clinicians practicing in rural locations were more likely to rank “lack of resources in the community to address FI” as a top barrier compared with urban locations (OR 0.53; 95% CI 0.30- 0.91; P = .01). (D) Lack of community resources was ranked as the number 1 barrier by rural clinicians compared with suburban clinicians (P = .001) and compared with urban clinicians (P = .001).

Tables

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    Table 1.

    Demographic Characteristics of Survey Respondents

    Food Insecurity Survey (n = 913)
    Age, years(n = 838)
     Mean (SD)46.6 (11.2)
     Range27 to 88
    Gender(n = 903)
     Women574 (63.6%)
     Men324 (35.9%)
     Other5 (0.5%)
    Race(n = 891)
     White, non-Hispanic666 (74.7%)
     Black, non-Hispanic41 (4.6%)
     Hispanic58 (6.5%)
     Asian95 (10.7%)
     Multi-racial/Other31 (3.5%)
    (n = 910)
    Identify as under-represented in  medicine162 (17.8%)
    Education, highest degree(n = 912)
     MD/DO with PhD47 (5.2%)
     MD681 (74.7%)
     DO100 (11.0%)
     PhD/Other Doctoral68 (7.5%)
     Master's16 (1.8%)
    Degree earned, year(n = 910)
     Before 2000 (1964 to 1999)315 (34.6%)
     2000 to 2010273 (30.0%)
     After 2010 (2011 to 2022)322 (35.4%)
    Practice region(n = 905)
     New England/Middle Atlantic160 (17.7%)
     South Atlantic159 (17.6%)
     East North Central169 (18.7%)
     West North Central96 (10.6%)
     South Central96 (10.6%)
     Mountain81 (8.9%)
     Pacific144 (15.9%)
    Institute type(n = 910)
     Medical school (Allopathic/ Osteopathic)515 (56.6%)
     Not medical school395 (43.4%)
    Institute residency program(n = 909)
     Multiple residencies including  Family medicine633 (69.6%)
     Only family medicine residency240 (26.4%)
     Multiple w/o family medicine/No  residency36 (4.0%)
    Location class area of work(n = 911)
     Urban469 (51.5%)
     Suburban295 (32.4%)
     Rural147 (16.1%)
    (n = 907)
    Work in underserved area248 (27.3%)
    Role in institution(n = 912)
     Faculty463 (50.8%)
     Administrator/Chair/Director279 (30.6%)
     Practice Physician80 (8.8%)
     Behavior specialist49 (5.4%)
     Other41 (4.5%)
    • Abbreviation: SD, standard deviation.

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    Table 2.

    Demographic Characteristics of Survey Respondents Based on How Often Clinician Personally Asked about Food Insecurity

    Always/Freq (n = 61)Sometimes (n = 487)Rarely/Never (n = 365)p-Value
    Age, years(n = 54)(n = 446)(n = 338)
     Mean (SD)46.0 (10.5)46.6 (11.1)46.8 (11.3)0.88
     Range30 to 7527 to 7529 to 88
    (n = 60)(n = 480)(n = 358)
    Gender (Female/Woman)45 (75.0%)317 (66.0%)212 (59.2%)0.023
     Race(n = 60)(n = 474)(n = 357)
     White, non-Hispanic42 (70.0%)349 (73.6%)275 (77.0%)0.36
    (n = 486)(n = 363)
    Identify as under-represented in medicine17 (27.9%)89 (18.3%)56 (15.4%)0.058
    Education, highest degree(n = 364)
     MD/DO with PhD1 (1.6%)22 (4.5%)24 (6.6%)0.041
     MD39 (63.9%)370 (76.0%)272 (74.7%)
     DO9 (14.8%)54 (11.1%)37 (10.2%)
     PhD/Other Doctoral/Master's12 (19.7%)41 (8.4%)31 (8.5%)
    Degree earned, year(n = 485)(n = 364)
     Before 2000 (1964 to 1999)19 (31.2%)169 (34.8%)127 (34.9%)0.84
     2000 to 201021 (34.4%)139 (28.7%)113 (31.0%)
     After 2010 (2011 to 2022)21 (34.4%)177 (36.5%)124 (34.1%)
    Practice region(n = 483)(n = 361)
     New England/Middle Atlantic12 (19.7%)91 (18.8%)57 (15.8%)0.92
     South Atlantic11 (18.0%)86 (17.8%)62 (17.2%)
     East North Central8 (13.1%)86 (17.8%)75 (20.8%)
     West North Central8 (13.1%)51 (10.6%)37 (10.3%)
     South Central6 (9.8%)46 (9.5%)44 (12.2%)
     Mountain7 (11.5%)44 (9.1%)30 (8.3%)
     Pacific9 (14.8%)79(16.4%)56 (15.5%)
    Institute type(n = 362)
     Medical school (Allopathic/Osteopathic)37 (60.6%)271 (55.6%)207 (57.2%)0.73
     Not medical school24 (39.3%)216 (44.4%)155 (42.8%)
     Institute residency program(n = 485)(n = 363)
     Multiple residencies including Family medicine43 (70.5%)330 (68.0%)260 (71.6%)0.71
     Only family medicine residency15 (24.6%)133 (27.4%)92 (25.3%)
     Multiple w/o family medicine/No residency3 (4.9%)22 (4.5%)11 (3.0%)
    Location class area of work(n = 363)
     Urban35 (57.4%)264 (54.2%)170 (46.8%)0.21
     Suburban19 (31.2%)147 (30.2%)129 (35.5%)
     Rural7 (11.5%)76 (15.6%)64 (17.6%)
    (n = 60)(n = 484)(n = 363)
    Work in underserved area13 (21.7%)110 (22.7%)125 (34.4%)0.0005
    • Abbreviation: SD, standard deviation.

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    Appendix Table 1.

    Top Factors Influencing Providers Decisions to Discuss Food Insecurity (FI) with Patients, by Respondent's Demographic Characteristics

    Patient reports change in living statusPatient/Family has history of homelessness/Comes up in conversationFood Insecurity screen identifies an issue
    n%95%CI%95%CI%95%CI%95%CIInteraction Effect p-Value
    Gender
     Female57172.068.275.565.261.269.055.951.859.955.951.859.9
     Male32158.653.163.864.859.469.859.554.064.750.845.356.2
    Odds ratio (95% CI); p-valueGender*Reason
     Female versus Male1.82 (1.26, 2.62); <0.00011.02 (0.70, 1.46); >0.990.86 (0.60, 1.23); >0.991.23 (0.86, 1.74); 0.570.005
    Age
     <4028363.357.568.759.453.564.967.161.572.453.447.559.1
     40 to 4924168.962.874.460.253.966.257.350.963.461.455.167.4
     50 to 5917368.260.974.766.559.173.156.148.663.352.044.659.4
     ≥6013669.961.677.076.568.682.944.136.052.646.338.154.7
    Odds ratio (95% CI); p-valueAge (P > .99)Age (P = .015)Age (P = .0004)Age (P = .129)Age*Reason<0.0001
     ≥60 versus <402.22 (1.09, 4.56); 0.0150.39 (0.20, 0.74); <0.0001
     >60 versus 40 to 492.15 (1.03, 4.48); 0.032
    Race
     White (non-hispanic)66166.362.669.865.762.069.257.553.761.254.851.058.5
     Non-White/Multi-racial22568.462.174.262.255.768.357.350.863.651.645.058.0
    Odds ratio (95% CI); p-valueRace*Reason
     White versus Non-white0.91 (0.60, 1.37); >0.991.16 (0.78, 1.73); >0.991.01 (0.68, 1.49); >0.991.14 (0.77, 1.67); >0.990.71
    Under-represented in medicine
     Yes16167.760.174.558.450.665.856.548.864.054.046.361.6
     No74267.063.570.365.662.169.057.654.061.154.050.457.6
    Odds ratio (95% CI); p-valueUnderRep*Reason
     Yes versus No1.03 (0.65, 1.64); >0.990.74 (0.47, 1.14); 0.330.96 (0.62, 1.49); >0.991.00 (0.65, 1.55); >0.990.58
    Year earned degree
     Before 200031268.362.973.270.565.275.350.044.555.551.946.457.4
     2000 to 201027167.261.472.566.460.671.857.651.663.357.952.063.7
     After 201032065.660.370.656.951.462.264.459.069.452.547.057.9
    Odds ratio (95% CI); p-valueDegreeYr (P > .99)DegreeYr (P = .005)DegreeYr (P = .005)DegreeYr (P > .99)DegreeYr*Reason
     After 2010 versus Before 20000.55 (0.34, 0.89); 0.0041.81 (1.14, 2.87); 0.0030.002
    Year earned degree
     MD/DO with PhD4667.452.779.358.744.171.967.452.779.356.542.170.0
     MD67864.961.268.465.862.169.356.252.459.954.350.558.0
     DO10073.063.580.858.048.167.357.047.266.353.043.262.6
     Masters/PhD/Other Doctoral8177.867.585.564.253.273.960.549.570.551.941.162.5Degree*Reason
    Among DegreesDegree (P = .27)Degree (P > .99)Degree (P > .99)Degree (P > .99)0.31
    Institute type
     Medical school (Allopath/Osteopath)51168.964.772.864.860.568.858.354.062.551.547.155.8
     Not medical school39264.859.969.464.359.468.955.650.760.557.752.762.5
    Odds ratio (95% CI); p-valueInstType*Reason
     Med school versus not1.20 (0.84, 1.72); 0.781.02 (0.72, 1.45); >0.991.12 (0.80, 1.57); >0.990.78 (0.56, 1.09); 0.260.18
    Institute residency programResidency*Reason
     Family medicine + other62965.561.769.164.460.668.059.355.463.154.250.358.1
     Family medicine only23770.964.876.365.058.770.852.746.459.054.448.160.7
     No Family medicine/No residency3672.255.684.466.750.080.052.836.868.344.429.360.7
    Among institute residency progResidency (P > .99)Residency (P > .99)Residency (P = .76)Residency (P > .99)0.46
    Location class area of workLocClass*Reason
     Urban46666.562.170.762.958.467.259.054.563.455.651.060.0
     Suburban29265.159.470.365.159.470.357.952.163.453.848.059.4
     Rural14772.865.079.468.060.175.150.342.358.349.741.757.7
    Among location class areaLocClass (P > .99)LocClass (P > .99)LocClass (P = .70)LocClass (P > .99)0.32
    Work in underserved area
     Yes24468.061.973.667.261.172.855.349.061.556.249.962.3
     No/unsure65666.863.170.363.459.767.058.254.462.053.249.457.0
    Odds ratio (95% CI); p-valueUnderserved*Reason
    Yes versus no/unsure1.06 (0.71, 1.58); >0.991.18 (0.80, 1.76); >0.990.89 (0.61, 1.30); >0.991.13 (0.77, 1.64); >0.990.65
    • *Note: For each demographic variable the p-values for the test of effect of demographic variable and pairwise comparisons have been adjusted for multiplicity (i.e. number of reasons and number of pairwise comparisons).

    • Abbreviation: CI, confidence interval.

    • View popup
    Appendix Table 2.

    Most Challenging Obstacles in Addressing Food Insecurity (FI), by Respondent's Demographic Characteristics

    Inadequate time during appointmentsOther medical issues take priorityLack of knowledge about available resources for food insecurityLack of resources in community to address food insecurity
    n%95%CI%95%CI%95%CI%95%CIInteraction effect p-Value
    Gender
     Female56580.577.183.675.271.578.646.041.950.238.234.342.3
     Male31783.979.587.675.770.780.144.539.150.039.133.944.6
    Odds ratio (95% CI); p-valueGender*Obstacle
     Female versus Male0.79 (0.50, 1.26); 0.850.97 (0.65, 1.46); >0.991.06 (0.75, 1.51); >0.990.96 (0.67, 1.38); >0.990.66
    Age
     <4028183.678.887.573.367.878.254.548.660.235.229.941.0
     40 to 4923881.576.186.074.868.979.943.337.149.743.737.550.1
     50 to 5917281.474.986.582.676.287.544.837.552.331.424.938.7
     ≥6013677.269.483.573.565.580.338.230.546.742.734.651.1
    Odds ratio (95% CI); p-valueAge (P > .99)Age (P = .52)Age (P = .030)Age (P = .143)Age*Obstacle
     ≥60 versus <400.52 (0.27, 0.99); 0.0440.004
    Race
     White (non-hispanic)65483.580.486.176.673.279.744.540.748.337.634.041.4
     Non-White/Multi-racial22277.071.082.171.264.976.850.543.957.040.133.946.7
    Odds ratio (95% CI); p-valueRace*Obstacle
     White versus Non-white1.51 (0.94, 2.43); 0.1271.33 (0.86, 2.05); 0.420.79 (0.53, 1.16); 0.500.90 (0.61, 1.34); >0.990.099
    Under-represented in medicine
     Yes15876.068.782.069.662.076.351.944.159.642.434.950.2
     No73582.980.085.476.673.479.544.540.948.137.634.141.1
    Odds ratio (95% CI); p-valueUnderRep*Obstacle
     Yes versus No0.65 (0.39, 1.10); 0.170.70 (0.43, 1.14); 0.261.35 (0.87, 2.09); 0.361.22 (0.78, 1.91); >0.990.061
    Year earned degree
     Before 200030879.274.383.478.373.382.541.936.547.539.033.744.5
     2000 to 201026779.073.783.576.070.580.843.838.049.837.531.943.4
     After 201031886.281.989.572.066.876.751.345.856.738.132.943.5
    Among year earned degreeDegreeYr (P = .142)DegreeYr (P = .75)DegreeYr (P = .188)DegreeYr (P > .99)DegreeYr*Obstacle
    0.034
    Highest Degree
     MD/DO with PhD4691.379.096.763.048.475.656.542.170.050.035.964.1
     MD67681.778.684.477.173.880.145.341.649.037.333.741.0
     DO9883.775.089.878.669.485.644.935.454.833.725.043.6
     Masters/PhD/Other Doctoral7573.362.282.164.052.674.044.033.355.446.735.757.9
    Among DegreesDegree (P = .39)Degree (P = .064)Degree (P > .99)Degree (P = .45)Degree*Obstacle
    0.123
    Institute type
     Medical school Allopath/Osteopath)50880.176.483.473.469.477.147.142.751.439.235.043.5
     Not medical school38583.679.687.078.273.882.043.638.848.637.432.742.4
    Odds ratio (95% CI); p-valueInstType*Obstacle
     Med school versus not0.79 (0.51, 1.23); 0.720.77 (0.52, 1.15); 0.411.15 (0.82, 1.61); >0.991.08 (0.76, 1.53); >0.990.29
    Institute residency program
     Family medicine + other62382.078.884.873.569.976.849.045.152.938.434.642.3
     Family medicine only23381.676.086.078.572.883.338.632.645.037.331.443.7
     No Family medicine/No residency3677.861.588.588.973.995.838.924.655.438.924.655.4
    Among Institute residency progResidency (P > .99)Residency (P = .23)Residency (P = .074)Residency (P > .99)Residency*Obstacle
    0.049
    Location class area of work
     Urban46182.979.286.076.172.079.845.841.350.335.130.939.6
     Suburban28881.977.186.076.771.581.346.240.552.037.231.842.9
     Rural14677.469.983.570.662.777.444.536.752.750.742.658.7
    Odds ratio (95% CI); p-valueLocClass (P > .99)LocClass (P > .99)LocClass (P > .99)LocClass (P = .014)LocClass*Obstacle
     Urban versus Rural0.53 (0.30, 0.91); 0.0100.043
     Suburban versus Rural0.58 (0.32, 1.03); 0.078
    Work in underserved area
     Yes24375.369.580.371.265.276.549.042.755.234.628.940.8
     No/unsure64784.181.186.777.173.780.244.740.948.539.635.943.4
    Odds ratio (95% CI); p-valueUnderserved*Reason
     Yes versus no/unsure0.58 (0.36, 0.91); 0.0110.73 (0.48, 1.12); 0.271.19 (0.82, 1.73); >0.990.81 (0.54, 1.19); 0.690.051
    • *Note: For each demographic variable the p-values for the test of effect of demographic variable and pairwise comparisons have been adjusted for multiplicity (i.e. number of reasons and number of pairwise comparisons).

    • Abbreviation: CI, confidence interval.

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The Journal of the American Board of Family     Medicine: 37 (2)
The Journal of the American Board of Family Medicine
Vol. 37, Issue 2
March-April 2024
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Family Medicine Clinician Screening and Barriers to Communication on Food Insecurity: A CERA General Membership Survey
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Family Medicine Clinician Screening and Barriers to Communication on Food Insecurity: A CERA General Membership Survey
Stephanie K. Bunt, Matthew Traxler, Bridget Zimmerman, Marcy Rosenbaum, Sally Heaberlin, Peter F. Cronholm, Eliza W. Kinsey, Kelly Skelly
The Journal of the American Board of Family Medicine Mar 2024, 37 (2) 196-205; DOI: 10.3122/jabfm.2023.230319R1

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Family Medicine Clinician Screening and Barriers to Communication on Food Insecurity: A CERA General Membership Survey
Stephanie K. Bunt, Matthew Traxler, Bridget Zimmerman, Marcy Rosenbaum, Sally Heaberlin, Peter F. Cronholm, Eliza W. Kinsey, Kelly Skelly
The Journal of the American Board of Family Medicine Mar 2024, 37 (2) 196-205; DOI: 10.3122/jabfm.2023.230319R1
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Keywords

  • CERA
  • Family Medicine
  • Food Insecurity
  • Health Communication
  • Nutrition Assessment
  • Screening
  • Social Determinants of Health
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