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Randomized unconditional cash transfers improved diet quantity and quality in a low-income community in Massachusetts, USA

Nature Food (2026)Cite this article

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Abstract

During COVID-19, Chelsea, a city in Massachusetts, USA, implemented an unconditional cash transfer (UCT) programme (‘Chelsea Eats’) that provided a nine-month benefit of up to US$400 per month to low-income households, allocated via lottery. UCTs are increasingly common, but their dietary impacts in high-income countries are unclear. In a randomized experiment, 905 individuals assigned to receive UCTs and 555 controls completed a 24-h diet recall after 4–6 months. At baseline, 90% identified as Latino/a, and 86% experienced food insecurity. At follow-up, average caloric intake was 1,351 kcal among those in control—far less than the approximately 2,060 kcal recommended by the Dietary Guidelines for Americans. The intervention led to increased kilocalories (+146 kcal), and increased fruit (+0.17 cup equiv.), vegetable (+0.14 cup equiv.) and unprocessed meat (+0.54 oz.) consumption. These findings suggest that a recurring UCT reduced caloric deficits and improved intake of nutrient-dense foods among this food-insecure population in the United States.

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Fig. 1: Participant flow diagram and study timeline.
Fig. 2: Estimated regression-adjusted differences in total energy intake (kilocalories), and intake of primary, secondary and addendum foods in terms of servings comparing Chelsea Eats benefit versus no benefit at follow-up.

Data availability

Researchers interested in accessing the data that support the findings of this study should contact the principle investigator, J. Liebman (jeffrey_liebman@hks.harvard.edu). Source data are provided with this paper.

Code availability

Source code to clean, analyse and process data for this study is available from Zenodo via https://doi.org/10.5281/zenodo.17834150 (ref. 52). The repository also includes documentation and data for publicly available data sources such as the NHANES, the Food Patterns Equivalents Database and the What We Eat in America Database, and preanalysis plans and protocol for the Chelsea Eats study.

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Acknowledgements

We thank A. Finkelstein, L. Shaefer, J. Shapiro, and seminar participants at the Harvard Kennedy School, the Abdul Latif Jameel Poverty Action Lab at the Massachusetts Institute of Technology, and the University of Michigan Poverty Solutions Center for helpful suggestions and comments. The authors are grateful to the City of Chelsea and the participants of the Chelsea Eats study for making this research possible. M.M.L. was supported by a training grant (5T32HL098048) from the National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (NIH). B.J.K.S. is also supported by a grant (5K01HL166442-03) from the NHLBI of the NIH. E.L.K. is supported by a grant (5K01DK125278-04) from the National Institute of Diabetes and Digestive and Kidney Diseases of the NIH. This study was funded by the Shah Family Foundation and the Rappaport Institute for Greater Boston. One of the authors (E.N.), who was involved in study design and data collection, is an employee of the Shah Family Foundation, which funded a portion of the intervention and data collection. No other funders of the study contributed to any component of study design, writing or analysis.

Author information

Authors and Affiliations

  1. Harvard T.H. Chan School of Public Health, Department of Nutrition, Boston, MA, USA

    Matthew M. Lee, Erica L. Kenney & Eric B. Rimm

  2. Harvard T.H. Chan School of Public Health, Department of Social & Behavioral Sciences, Boston, MA, USA

    Erica L. Kenney, Jarvis T. Chen & Steven L. Gortmaker

  3. Harvard University John F. Kennedy School of Government, Cambridge, MA, USA

    Kathryn Carlson, Pamela Portocarrero & Jeffrey Liebman

  4. Shah Family Foundation, Boston, MA, USA

    Eliza Novick

  5. Harvard T.H. Chan School of Public Health, Department of Epidemiology, Boston, MA, USA

    Eric B. Rimm

  6. Harvard T.H. Chan School of Public Health, Department of Biostatistics, Boston, MA, USA

    Briana Joy K. Stephenson

  7. National Bureau of Economic Research, Cambridge, MA, USA

    Jeffrey Liebman

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Contributions

M.M.L. helped conceptualize the study and methodology, conducted data curation and formal analysis, visualization, and wrote the manuscript (original draft, review and editing). J.L. and M.M.L. directly accessed and verified the underlying data reported in the manuscript. J.L. conceptualized the study and methodology, curated the data, acquired funding, administered the project, provided supervision, and wrote the manuscript (original draft, review and editing). E.L.K. helped conceptualize the methodology, supervised, and reviewed and edited the manuscript. K.C. helped conceptualize the study and reviewed and edited the manuscript. E.N. helped conceptualize the study and reviewed and edited the manuscript. P.P. helped conceptualize the study, administered the project, and reviewed and edited the manuscript. E.B.R. helped conceptualize the study and reviewed and edited the manuscript. J.T.C., S.L.G. and B.J.K.S. supervised and reviewed and edited the manuscript. All authors had full access to the data in the study and accept responsibility to submit for publication.

Corresponding author

Correspondence to Matthew M. Lee.

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Nature Food thanks Greg Duncan, Natasha Pilkauskas and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Text, Tables 1–13 and Figs. 1–3.

Reporting Summary

Supplementary Data 1

Source Data for Supplementary Fig. 1: Underlying percentile data for Quantile-Quantile plots.

Supplementary Data 2

Source Data for Supplementary Fig. 2: Underlying overall consumption data for top 25 sources of unprocessed meat consumed in study sample.

Supplementary Data 3

Estimates, confidence intervals, and P-values for the data underlying Supplementary Figure 3.

Source data

Source Data Fig. 2

Estimates, confidence intervals, and P-values for the data underlying Fig. 2 in the main text.

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Lee, M.M., Kenney, E.L., Carlson, K. et al. Randomized unconditional cash transfers improved diet quantity and quality in a low-income community in Massachusetts, USA. Nat Food (2026). https://doi.org/10.1038/s43016-026-01301-8

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