Offsetting the cost of community-supported agriculture (CSA) for low-income families: perceptions and experiences of CSA farmers and members

Community-supported agriculture (CSA) is an alternative food marketing model in which community members subscribe to receive regular shares of a farm's harvest. Although CSA has the potential to improve access to fresh produce, certain features of CSA membership may prohibit low-income families from participating. A ‘cost-offset’ CSA (CO-CSA) model provides low-income families with purchasing support with the goal of making CSA more affordable. As a first step toward understanding the potential of CO-CSA to improve access to healthy foods among low-income households, we interviewed 24 CSA farmers and 20 full-pay CSA members about their experiences and perceptions of the cost-offset model and specific mechanisms for offsetting the cost of CSA. Audio recordings were transcribed verbatim and coded using a thematic approach. Ensuring that healthy food was accessible to everyone, regardless of income level, was a major theme expressed by both farmers and members. In general, CSA farmers and CSA members favored member donations over other mechanisms for funding the CO-CSA. The potential time burden that could affect CSA farmers when administering a cost-offset was a commonly-mentioned barrier. Future research should investigate various CO-CSA operational models in order to determine which models are most economically viable and sustainable.

Mixed Method Evaluation of a Graduate Student Teaching and Learning Internship Program

In recognition of the need to better prepare doctoral candidates with teaching and learning competencies, we devised an innovative internship program in the form of a structured apprenticeship and trialed it in public health higher education. The paid internship was comprised of: (i) Mentoring from an experienced educator, (ii) Structured program of education in pedagogy and curriculum design, and (iii) Opportunities for applied experience. Eleven interns completed the apprenticeship in its first 2 years. The mixed method evaluation assessed the impact of the internship on knowledge, skills, and confidence of interns throughout the internship, and included a cost-consequence analysis. Data collection included surveys and face-to-face interviews with interns and mentors. Changes in intern knowledge and skills were analyzed by intern self-ratings pre- and post-internship on 11 performance descriptors. All interns indicated improvement in at least one area of teaching. Interviews indicated general satisfaction, however raised incompatibilities between the unstructured nature of mentoring and intern expectations and preferences. The economic analysis calculated a cost-offset associated with intern-delivered teaching activities of $58,820 (AUD, 2019). The total cost of the program was calculated to be $70,561 (comprising mentor investment AUD$20,436, intern investment AUD$15,126, scholarship “top-up” payment of $5,000 paid to each of the 7 interns AUD $35,000). This Internship is associated with positive impacts for interns across a range of domains at a net total investment of $11,741.

Community supported agriculture plus nutrition education improves skills, self-efficacy, and eating behaviors among low-income caregivers but not their children: a randomized controlled trial

Background Adults and children in the U.S. consume inadequate quantities of fruit and vegetables (FV), in part, due to poor access among households with lower socioeconomic status. One approach to improving access to FV is community supported agriculture (CSA) in which households purchase a ‘share’ of local farm produce throughout the growing season. This study examined the effects of cost-offset (half-price) CSA plus tailored nutrition education for low-income households with children. Methods The Farm Fresh Foods for Healthy Kids (F3HK) randomized controlled trial in New York, North Carolina, Vermont, and Washington (2016–2018) assigned caregiver-child dyads (n = 305) into cost-offset CSA plus education intervention or control (delayed intervention) groups. Following one growing season of CSA participation, changes in children’s diet quality, body mass index (BMI), and physical activity; caregivers’ nutrition knowledge, attitudes, behaviors, and diet quality; and household food access and security were examined using multiple linear or logistic regression, with adjustment for baseline value within an intent-to-treat (ITT) framework in which missing data were multiply imputed. Results No significant net effects on children’s dietary intake, BMI, or physical activity were observed. Statistically significant net improvements were observed after one growing season for caregivers’ cooking attitudes, skills, and self-efficacy; FV intake and skin carotenoid levels; and household food security. Changes in attitudes and self-efficacy remained one-year after baseline, but improvements in caregiver diet and household food security did not. The number of weeks that participants picked up a CSA share (but not number of education sessions attended) was associated with improvements in caregiver FV intake and household food security. Conclusions Cost-offset CSA plus tailored nutrition education for low-income households improved important caregiver and household outcomes within just one season of participation; most notably, both self-reported and objectively measured caregiver FV intake and household food security improved. Households that picked up more shares also reported larger improvements. However, these changes were not maintained after the CSA season ended. These results suggest that cost-offset CSA is a viable approach to improving adult, but not child, FV intake and household food security for low-income families, but the seasonality of most CSAs may limit their potential to improve year-round dietary behavior and food security. Trial registration ClinicalTrials.gov. NCT02770196. Registered 5 April 2016. Retrospectively registered.

Models for cost-offset community supported agriculture (CO-CSA) programs

Cost-offset community supported agriculture (CO-CSA) appears to be a promising way to increase low-income households’ access and intake of fresh produce, while also helping CSA farms expand their farm business. Yet single farms operating CO-CSAs may struggle to balance the demands of farming with CO-CSA program administration, funding, and recruitment. To address these chal­lenges, CO-CSA programs operated by nonprofits have emerged, equipped with dedicated infrastruc­ture, resources, and staffing. This study aims to describe organizational models and best practices of nonprofit CO-CSA programs, using a qualitative approach. We conducted interviews with five well-established nonprofit CO-CSA programs in the U.S. Administration of these five nonprofit CO-CSAs took several forms: (1) providing direct sub­sidies to individual CO-CSA member farms; (2) functioning themselves as an aggregator, packer, and distributor of regional produce; and (3) sourcing from an in-house farm incubator or food hub, then packing and coordinating delivery to pick-up sites. Nonprofit CO-CSA funding strategies included grants from federal and local government sources, private donations, fundrais­ing, and grants. Marketing efforts occurred via social media, community events, and word of mouth. Both fundraising and recruitment were greatly facilitated by relationships with community partners. Having dedicated staff, as well as a com­munity that values local agriculture and social jus­tice, were identified as success factors. This descriptive, qualitative study systematically com­pares the attributes of five nonprofit CO-CSA programs. Future research should focus on identifying the cost-effectiveness of nonprofit CO-CSAs, compare the relative merits of single-farm and nonprofit CO-CSAs, and quantify the eco­nomic benefit of CO-CSA programs for farmers and local communities.

Health care cost and benefits of artificial intelligence-assisted population-based glaucoma screening for the elderly in remote areas of China: a cost-offset analysis

Background Population-based screening was essential for glaucoma management. Although various studies have investigated the cost-effectiveness of glaucoma screening, policymakers facing with uncontrollably growing total health expenses were deeply concerned about the potential financial consequences of glaucoma screening. This present study was aimed to explore the impact of glaucoma screening with artificial intelligence (AI) automated diagnosis from a budgetary standpoint in Changjiang county, China. Methods A Markov model based on health care system’s perspective was adapted from previously published studies to predict disease progression and healthcare costs. A cohort of 19,395 individuals aged 65 and above were simulated over a 15-year timeframe. Fur illustrative purpose, we only considered primary angle-closure glaucoma (PACG) in this study. Prevalence, disease progression risks between stages, compliance rates were obtained from publish studies. We did a meta-analysis to estimate diagnostic performance of AI automated diagnosis system from fundus image. Screening costs were provided by the Changjiang screening programme, whereas treatment costs were derived from electronic medical records from two county hospitals. Main outcomes included the number of PACG patients and health care costs. Cost-offset analysis was employed to compare projected health outcomes and medical care costs under the screening with what they would have been without screening. One-way sensitivity analysis was conducted to quantify uncertainties around model results. Results Among people aged 65 and above in Changjiang county, it was predicted that there were 1940 PACG patients under the AI-assisted screening scenario, compared with 2104 patients without screening in 15 years’ time. Specifically, the screening would reduce patients with primary angle closure suspect by 7.7%, primary angle closure by 8.8%, PACG by 16.7%, and visual blindness by 33.3%. Due to early diagnosis and treatment under the screening, healthcare costs surged dramatically to $107,761.4 dollar in the first year and then were constantly declining over time, while without screening costs grew from $14,759.8 in the second year until peaking at $17,900.9 in the 9th year. However, cost-offset analysis revealed that additional healthcare costs resulted from the screening could not be offset by decreased disease progression. The 5-, 10-, and 15-year accumulated incremental costs of screening versus no screening were estimated to be $396,362.8, $424,907.9, and $434,903.2, respectively. As a result, the incremental cost per PACG of any stages prevented was $1464.3. Conclusions This study represented the first attempt to address decision-maker’s budgetary concerns when adopting glaucoma screening by developing a Markov prediction model to project health outcomes and costs. Population screening combined with AI automated diagnosis for PACG in China were able to reduce disease progression risks. However, the excess costs of screening could never be offset by reduction in disease progression. Further studies examining the cost-effectiveness or cost-utility of AI-assisted glaucoma screening were needed.

Making community-supported agriculture accessible to low-income families: findings from the Farm Fresh Foods for Healthy Kids process evaluation

A randomized trial of Farm Fresh Foods for Healthy Kids (F3HK) was initiated across 4 states and 12 farms to test whether cost-offset community-supported agriculture (CO-CSA) could improve diet quality among children in low-income families. Intervention households purchased a 50% subsidized share of local produce and were invited to nine complimentary nutrition classes. The purpose of this study was to assess F3HK reach, dose, and fidelity via a mixed methods process evaluation. Screening and enrollment records indicated reach; study records and postlesson educator surveys tracked dose delivered; CSA pickup logs, lesson sign-in sheets, postseason participant surveys, and postlesson caregiver surveys assessed dose received; and coordinator audits and educator surveys tracked fidelity. Educator interviews contextualized findings. The results of this study were as follows. Reach: enrolled caregivers (n = 305) were older (p = .005) than eligible nonenrollees (n = 243) and more likely to be female (p < .001). Dose: mean CSA season was 21 weeks (interquartile range [IQR]: 19–23). Median CSA pickup was 88% of the weeks (IQR: 40–100). All sites offered each class at least once. Most adults (77%) and children (54%) attended at least one class; few attended all. Eighty-two percent of caregivers indicated that their household consumed most or all produce. Median lesson activity ratings were 5/5 (“very useful”). Fidelity: CSA locations functioned with integrity to project standards. Educators taught 92% of activities but frequently modified lesson order. This study demonstrates the feasibility of pairing a CO-CSA intervention with nutrition education across geographically dispersed sites. Greater integration of intervention elements and clearer allowance for site-level modifications, particularly for educational elements, may improve intervention dose and, ultimately, impact.