{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T17:00:28Z","timestamp":1790614828550,"version":"4.1.0"},"reference-count":41,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T00:00:00Z","timestamp":1790553600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Nutr."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>The digital economy has reshaped how people work, shop, and manage health, yet uneven nutrition remains a pressing livelihood concern for low-income groups in China now that absolute poverty has ended. Most of what is known about improving nutrition in these households has to do with money, whether cash transfers or food subsidies, and much less is known about what changes when a household simply gets online. This study asks whether being connected goes together with a lower risk of nutritional imbalance among low-income adults, and what may lie behind that link.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Nutritional imbalance here covers both sides of the problem, being too thin and being too heavy, since low-income households in China face the two at once. It is built from body mass index and coded as six ordered categories, with a higher value standing for a more serious departure from a healthy weight. We draw on five waves of the China Family Panel Studies covering 2014 to 2022 and focus on adults aged 18 to 69 whose household per capita income falls in the bottom fifth within their province, which leaves 12,076 observations. The estimates compare the same person across waves, setting aside what is fixed about an individual and what moves for everyone at once. Three possible routes are then examined in turn, namely the weight of food in the household budget, labor income, and exercise frequency.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Low-income adults who are online carry a lower risk of nutritional imbalance, and the finding holds when the income line is drawn differently, when connectivity is counted differently, and when the model is changed. Being online goes together most clearly with more regular exercise, and it also goes together with a slightly larger share of the household budget spent on food and with higher earnings among those who work. The link is strongest for rural residents, for adults aged 50 and over, and for those who left school at or before the end of lower secondary education, while among urban, younger, and better educated adults no clear link shows up.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>Connectivity seems to supplement offline provision rather than replace it, since little shows up where offline services are already dense. Expanding rural digital infrastructure and pairing online with offline nutrition support may therefore help narrow the nutrition gap that runs alongside the digital divide. The findings are reported throughout as associations.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fnut.2026.1927357","type":"journal-article","created":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T16:06:28Z","timestamp":1790611588000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Does getting online help low-income adults eat better? 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