Feasibility of Delivering an on-Campus Food Distribution Program in a Community College Setting: A Mixed Methods Sequential Explanatory Investigation
Abstract
:1. Introduction
2. Materials and Methods
2.1. Setting
2.2. Study Design and Eligibility
2.3. Randomization
2.4. Recruitment for the Intervention
2.5. Survey
2.6. Intervention: Food Distribution Program
2.7. Focus Groups and Photo Elicitation Interviews
2.8. Measures
2.8.1. Recruitment Capability and Resulting Intervention Sample Characteristics
2.8.2. Data Collection Procedures and Outcome Measures
2.8.3. Participants’ Acceptability and Responses to the Intervention
2.9. Data Analysis
Trustworthiness and Credibility
3. Results
3.1. Recruitment Feasibility and Resulting Intervention Sample Characteristics
3.2. Evaluation of Data Collection Procedures and Sample Characteristics of the Students That Enrolled
3.3. Evaluation of Outcome Measures
3.3.1. Poundage of Food
3.3.2. Dietary Intake
3.3.3. Food Insecurity
3.4. Evaluation of Participants’ Acceptability and Responses to the Intervention
3.5. Barriers Limiting FDP Utilization
3.5.1. The Program’s Design and Organization
3.5.2. Personal Schedule and Transportation
3.5.3. Program Abuse by Other Attendees
3.6. Facilitators for FDP Utilization
3.6.1. Type of Food Distributed and Welcoming Environment
3.6.2. Allowing a Substitute Shopper to Collect Food
4. Discussion
4.1. Recruitment Feasibility
4.2. Utilization
4.3. Dietary Intake
4.4. Food Insecurity
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Acknowledgments
Conflicts of Interest
References
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Characteristic | Total Program Sample (n = 1000) | Program Sample (n = 1000) | Enrolled into the Program (n = 495) | ||
---|---|---|---|---|---|
Never Enrolled into the Program (n = 505) | Enrolled into the Program (n = 495) | No/Low Attendees (n = 363) | High Attendees (n = 132) | ||
Age | 29.65(10.35) | 27.71 (9.10) | 31.63 (11.15) a | 30.16 (10.40) | 35.66 (12.16) b |
Gender | |||||
Male | 331 (33.1%) | 209 (41.4%) | 122 (24.7%) a | 91 (25.1%) | 31 (23.5%) |
Female | 669 (66.9%) | 296 (58.6%) | 373 (75.4%) | 272 (74.9%) | 101 (76.5%) |
Race/ethnicity | |||||
Non-Hispanic white | 79 (7.9%) | 37 (7.3%) | 42 (8.5%) | 34 (9.4%) | 8 (6.1%) |
Non-Hispanic black | 544 (54.4%) | 263 (52.1%) | 281 (56.8%) | 200 (55.1%) | 81 (61.4%) |
Hispanic | 289 (28.9%) | 156 (30.9%) | 133 (26.9%) | 94 (25.9%) | 39 (29.6%) |
Other | 88 (8.8%) | 49 (9.7%) | 39 (7.9%) | 35 (9.6%) | 4 (3.1%) b |
Marital status | |||||
Married | 78 (7.8%) | 31 (6.2%) | 47 (9.5%) a | 35 (9.6%) | 12 (9.1%) |
Divorced/separated | 77 (7.7%) | 31 (6.2%) | 46 (9.3%) | 32 (8.8%) | 14 (10.6%) |
Single | 844 (84.4%) | 442 (87.7%) | 402 (81.2%) a | 296 (81.5%) | 106 (80.3%) |
Academic level | |||||
Freshman | 724 (72.4%) | 378 (74.9%) | 346 (69.9%) | 262 (72.2%) | 84 (63.6%) |
Sophomore | 59 (5.9%) | 30 (5.9%) | 29 (5.9%) | 18 (5.0%) | 11 (8.3%) |
Associate degree | 76 (7.6%) | 35 (6.9%) | 41 (8.3%) | 28 (7.7%) | 13 (9.9%) |
Bachelor’s degree | 29 (2.9%) | 13 (2.6%) | 16 (3.2%) | 14 (3.9%) | 2 (1.5%) |
Master’s degree | 5 (0.5%) | 3 (0.6%) | 2 (0.4%) | 1 (0.3%) | 1 (0.8%) |
Unclassified/not available | 107 (10.7%) | 46 (9.1%) | 61 (12.3%) | 40 (11.0%) | 21 (15.9%) |
Employment status | |||||
Full-time employee | 114 (11.4%) | 59 (11.7%) | 55 (11.1%) | 39 (10.7%) | 16 (12.1%) |
Part-time employee | 153 (15.3%) | 85 (16.8%) | 68 (13.7%) | 49 (13.5%) | 19 (14.4%) |
Not employed | 733 (73.3%) | 361 (71.5%) | 372 (75.2%) | 275 (75.8%) | 97 (73.5%) |
Female (n = 285) | |||||||
Dietary Intake Variables | No/Low Attendees (n = 139) | High Attendees (n = 60) | Never Enrolled (n = 86) | Recommended Intakes a | |||
S1 | S3 | S1 | S3 | S1 | S3 | ||
Fruit/vegetable score | 11.44 (6.08) | 10.40 (6.03) | 9.95 (6.21) | 9.58 (7.08) | 11.93 (7.09) | 10.97 (6.29) | NA |
Fruit/vegetable/bean score | 15.17 (8.43) | 13.80 (8.28) | 13.05 (7.54) f | 12.78 (8.55) | 16.16 (9.79) | 15.04 (8.73) | NA |
Meat/snack score | 24.29 (11.72) | 24.12 (12.39) | 22.45 (11.28) | 20.63 (10.84) f | 25.73 (11.10) | 26.17 (11.50) | NA |
Fruit and vegetable intake | |||||||
Fruit and Vegetable servings (per day) | 3.47 (2.23) | 3.08 (2.22) | 2.92 (2.27) | 2.82 (2.55) | 3.64 (2.62) | 3.30 (2.29) | |
Micronutrient intake | |||||||
Vitamin C (mg) | 115.97 (55.86) | 106.67 (54.91) | 100.92 (49.15) f | 98.96 (56.89) | 124.05 (64.57) | 116.32 (57.99) | 75.0 |
Magnesium (mg) | 302.94 (99.55) e | 286.10 (97.97) | 274.39 (86.29) f | 270.53 (101.93) f | 320.26 (113.92) | 306.07 (103.25) | 320.0 |
Potassium (mg) | 2902.53 (979.63) | 2737.43 (963.67) | 2626.91 (852.92) f | 2590.09 (1001.16) | 3063.54 (1125.36) | 2925.07 (1016.76) | 2600.0 |
Dietary fiber (g) | 14.20 (6.72) e | 13.06 (6.62) | 12.19 (5.78) f | 11.93 (6.89) f | 15.51(7.61) | 14.54 (6.95) | 25.0 |
Fat intake | |||||||
Total fat (f) | 102.19 (28.12) | 101.79 (29.74) | 97.78 (27.07) | 93.42 (26.03) f | 105.66 (26.64) | 106.72 (27.59) | NA b |
Fat % | 36.67 (7.03) | 36.57 (7.44) | 35.57 (6.77) | 34.48 (6.51) f | 37.54 (6.66) | 37.81 (6.90) | 20–35% |
Saturated fat (g) | 27.27 (10.31) | 27.13 (10.91) | 25.66 (9.93) | 24.06 (9.54) f | 28.54 (9.77) | 28.93 (10.12) | NA c |
Dietary cholesterol (g) | 284.55 (92.58) | 283.26 (98.51) | 269.13 (90.20) | 254.96 (86.40) f | 295.86 (90.94) | 299.30 (93.71) | NA d |
Male (n = 100) | |||||||
Dietary Intake Variables | No/Low Attendees (n = 33) | High Attendees (n = 19) | Never Enrolled (n = 48) | Recommended Intakes a | |||
S1 | S3 | S1 | S3 | S1 | S3 | ||
Fruit/vegetable score | 9.64 (7.52) | 10.18 (7.24) | 10.21 (6.52) | 8.90 (4.74) | 10.65 (5.51) | 12.19 (6.93) | NA |
Fruit/vegetable/bean score | 13.52 (10.36) | 15.18 (10.05) | 14.53 (8.15) | 13.37 (6.73) | 15.27 (7.54) | 17.46 (10.02) | NA |
Meat/snack score | 24.76 (13.64) | 24.61 (9.91) | 22.79 (12.56) | 20.79 (11.33) | 24.40 (8.81) | 25.60 (9.52) | NA |
Fruit and vegetable intake | |||||||
Fruit and Vegetable servings (per day) | 3.34 (2.77) | 3.54 (2.68) | 3.56 (2.39) | 3.06 (1.75) | 3.71 (2.04) | 4.29 (2.55) | |
Micronutrient intake | |||||||
Vitamin C (mg) | 132.68 (68.43) | 143.45 (67.26) | 137.12 (54.96) | 129.36 (44.88) | 145.18 (49.85) | 159.36 (66.62) | 90.0 |
Magnesium (mg) | 379.58 (121.17) | 398.04 (120.78) | 382.88 (100.26) | 369.01 (81.40) | 403.38 (88.55) | 427.80 (118.70) | 420.0 |
Potassium (mg) | 3500.18 (1195.21) | 3684.40 (1185.90) | 3547.87 (978.58) | 3411.32 (795.34) | 3729.64 (872.31) | 3973.00 (1168.72) | 3400.0 |
Dietary fiber (g) | 18.38 (8.13) | 19.58 (8.19) | 18.36 (6.90) | 17.43 (5.61) f | 20.05 (5.96) | 21.65 (7.99) | 38.0 |
Fat intake | |||||||
Total fat (g) | 92.12 (32.73) | 91.76 (23.77) | 87.40 (30.14) | 82.60 (27.18) | 91.25 (21.14) | 94.15 (22.85) | NA b |
Fat % | 34.66 (8.18) | 34.56 (5.94) | 33.47 (7.54) | 32.27 (6.80) | 34.44 (5.29) | 35.16 (5.71) | 20–35% |
Saturated fat (g) | 31.19 (12.00) | 31.05 (8.72) | 29.45 (11.05) | 27.69 (9.97) | 30.87 (7.75) | 31.93 (8.38) | NA c |
Dietary cholesterol (g) | 336.40 (114.44) | 335.22 (84.35) | 332.43 (97.15) | 316.83 (87.26) | 332.40 (74.27) | 341.83 (82.07) | NA d |
Characteristic | Analytic Sample (n = 385 a) | Analytic Sample (n = 385) | Enrolled into the Program (n = 251) | ||||
---|---|---|---|---|---|---|---|
Never Enrolled in the Program (n = 134) | Enrolled into the Program (n = 251) | Comparison Never Enrolled vs. Enrolled b | No/Low Attendees (n = 172) | High Attendees (n = 79) | Comparison No/Low vs. High Attendees b | ||
Food insecurity at S1 (baseline) | |||||||
Food secure | 150 (39.0%) | 60 (44.8%) | 90 (35.9%) | 63(36.6%) | 27 (34.2%) | ||
Food insecure | 235 (61.0%) | 74 (55.2%) | 161 (64.1%) | z = −1.710 | 109 (63.4%) | 52 (65.8%) | z = −0.376 |
Low food security | 117 (30.4%) | 41 (30.6%) | 76 (30.3%) | z = −0.065 | 54 (31.4%) | 22 (27.9%) | z = 0.568 |
Very low food security | 118 (30.7%) | 33 (24.6%) | 85 (33.9%) | z = −1.873 | 55 (32.0%) | 30 (38.0%) | z = −0.933 |
Food insecurity at S3 (final time point) | |||||||
Food secure | 159 (41.3%) | 74 (55.2%) | 85 (33.9%) | 60 (34.9%) | 25 (31.7%) | ||
Food insecure | 226 (58.7%) | 60 (44.8%) | 166 (66.1%) | z = −4.055 *** | 112 (65.1%) | 54 (68.4%) | z = −0.503 |
Low food security | 89 (23.2%) | 25 (18.7%) c | 64 (25.5%) | z = −1.517 | 43 (25.0%) | 21 (26.6%) | z = −0.267 |
Very low food security | 137 (35.6%) | 35 (26.1%) | 102 (40.6%) | z = −2.834 *** | 69 (40.1%) | 33 (41.8%) | z = −0.248 |
Barriers | Facilitators |
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“Yeah, I had medical issues. I had a couple surgeries. And I had to get a co-worker of mine to go up there with me. Because the check-in process was really long and I wasn’t supposed to be up just period. So just standing there in line waiting.” “I think they had more options in the beginning. Then as time progressed, the options changed, too.” “I think that’s slow, not—I mean I get it like once you check-in it’s find. But I shouldn’t have to check out I believe. I think that kind of slowed things down a little bit because you’re checking in, you go through the line, you get the end, you got to go through the same process.” “And because it was such slim pickings they were sending you through the line three and four times trying to get you to meet that quota on that weight amount.” |
“But in most cases, we brought our own bags to carry, a cart, or whatever to carry it, but they also had carts that you could put _____ _____ in and take it to your car, and unload it in your car and bring the cart back. So, that was helpful, too, yeah.” “Really, it was really convenient, because when you would get there, they would give you the option of having a bag that they had already packed with each food group. Or you can go through and get what you wanted off the tables from, you know, each food group.’ “Yeah, because there weren’t too many sweets. Like I didn’t see that as far as giving us cakes. So if you don’t have it, you’re not going to consume it, right? So yeah, I didn’t see cakes and stuff. Unhealthy.” “The selections were, the specials were I think good and excellent because we had a choice of everything on the pyramid, of meat, vegetables, different things.” “They treated us equally, they made us feel like we were welcome there, and that’s the biggest thing of it, when somebody’s doing something like this, you know, you want them to feel, like, accepted.” |
“I sometimes—most of the time, either I had class, I couldn’t leave class and go. And so, this lady that was picking it up for me and taking it home for me, she couldn’t do it no more, so that really knocked me out of the box, ‘cause she couldn’t do it no more. And when I wasn’t in class, that wasn’t the day they’d get it. The day that they’d bring it over there to the Newton, it was my class, I had class.” “And then I found out that it was over here at Newton. Highland didn’t have it, Pin Oak didn’t have it, Saddle Brook didn’t have it. So I had no other option but—and like I said because I work in the Hacienda it was kind of convenient when I was at work. But coming from home, I’m passing up two other campuses to get there.” “My location for sure. Only because I live in Wilcox and at the time, I didn’t have a car, which is why online classes was really easy for me but that would have been my only obstacle, actually getting to the food bank.” “Well, first of all, I work part time and I go to school part time, so the timing affects me, because I also ride Metro. I’m a seizure patient, so I don’t try to drive. My seizures are basically controlled, but I do have problems with stress, and pressure, and have seizures occasionally, so I ride Metro. So basically, my biggest I guess you can say problem would be timing.” “Transportation, yeah, _____ _____ challenge, ‘cause it’s kind of difficult, by the time you get home, the meat is thawed out and, you know, so you got to cook it ‘cause it’s already thawed out. So now you got to _____ _____ _____ cook it, you can’t put it back in the fridge, and…” “Yeah, they missed it, because I live in Katy; if I didn’t have a car, there’s no bus that comes in, where I live in Kollen, to over here. So, yeah, there’s a lot of people that may have classes here, but they live over here and there’s no public transportation to get you from Point A to Point B. And everybody can’t afford Uber or Lyft or going to pay somebody to take them somewhere, you know? They only have maybe the resources to get them to that specific class at that location at that time, yeah, so.” |
“I lived so close to campus, and I also had, like, housemates that, you know, one of my housemates was willing to go and stand in and pick up for me.” “And it was me and my daughter and my daughter would go for me because during that time I had surgery. Yeah, and I wasn’t supposed to be out.” “And so if you weren’t able to go, you could send someone to go for you, and I think it was usually two different locations” “Usually the challenges that I had was regarding time and I would just send my son in my place to go and get it. So when they were having it either I was at work or I was in class, so I would just let him go. If I didn’t have him, then it probably would have been more of a challenge, but he was able to compensate for where I couldn’t go.” “And also one thing other, they had a part of it if you weren’t able to make it you could send someone. So that was really good” |
“Because people were being greedy, getting too much. Then that became a problem.” “I can’t really say. No, it was a good variety of everything that time that I went. At the beginning, I was kind of in the middle of the line, so I noticed that a lot of people were trying to—I think the limit was 50 pounds or something, so a lot of people were just trying to get meat and that was not leaving a good selection for the people that were behind them if you only grabbed meat and nothing else.” “It came at a time where I really needed it and I don’t have anything negative to say about the program. It’s just some of the people, I think, were discourteous and they went in with an attitude like, “Hey, I’m going in with me and my daughter. I’m going to bring my daughter with me and me and my daughter’s going to get this.” And I’ve seen some people get eight, nine, ten packs of meat, and I was, wait. This is crazy.” “People on your back, people reaching over your shoulder, or you’re trying to get your products, and they see something they want, so they just go around you and grab it. That was my only kickback about it, and I’m the type of person, I’m going to let you go ahead and get what you want.” |
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Hernandez, D.C.; Daundasekara, S.S.; Walton, Q.L.; Eigege, C.Y.; Marshall, A.N. Feasibility of Delivering an on-Campus Food Distribution Program in a Community College Setting: A Mixed Methods Sequential Explanatory Investigation. Int. J. Environ. Res. Public Health 2021, 18, 12106. https://doi.org/10.3390/ijerph182212106
Hernandez DC, Daundasekara SS, Walton QL, Eigege CY, Marshall AN. Feasibility of Delivering an on-Campus Food Distribution Program in a Community College Setting: A Mixed Methods Sequential Explanatory Investigation. International Journal of Environmental Research and Public Health. 2021; 18(22):12106. https://doi.org/10.3390/ijerph182212106
Chicago/Turabian StyleHernandez, Daphne C., Sajeevika S. Daundasekara, Quenette L. Walton, Chinyere Y. Eigege, and Allison N. Marshall. 2021. "Feasibility of Delivering an on-Campus Food Distribution Program in a Community College Setting: A Mixed Methods Sequential Explanatory Investigation" International Journal of Environmental Research and Public Health 18, no. 22: 12106. https://doi.org/10.3390/ijerph182212106
APA StyleHernandez, D. C., Daundasekara, S. S., Walton, Q. L., Eigege, C. Y., & Marshall, A. N. (2021). Feasibility of Delivering an on-Campus Food Distribution Program in a Community College Setting: A Mixed Methods Sequential Explanatory Investigation. International Journal of Environmental Research and Public Health, 18(22), 12106. https://doi.org/10.3390/ijerph182212106