Evidence map›Paper›PMID 42224212›Full record

ArticlePLOS global public health2026

Food purchase patterns in Nairobi before, during, and after the COVID-19 pandemic lockdown measures.

Reinpeter Momanyi, Tatenda Duncan Kavu, Daniel Mtai Mwanga, Caroline H Karugu, Steve Cygu, Gershim Asiki, Agnes Kiragga

Abstract read
In one paragraph

Article in PLOS global public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

7 authors.

Reinpeter MomanyiAfrican Population and Health Research Center, Nairobi, Kenya.ORCID https://orcid.org/0009-0002-9059-393X
Tatenda Duncan KavuAfrican Population and Health Research Center, Nairobi, Kenya.ORCID https://orcid.org/0000-0002-9479-1143
Daniel Mtai MwangaAfrican Population and Health Research Center, Nairobi, Kenya.ORCID https://orcid.org/0000-0003-3907-1538
Caroline H KaruguAfrican Population and Health Research Center, Nairobi, Kenya.ORCID https://orcid.org/0000-0002-6914-9714
Steve CyguAfrican Population and Health Research Center, Nairobi, Kenya.ORCID https://orcid.org/0000-0002-9284-8863
Gershim AsikiAfrican Population and Health Research Center, Nairobi, Kenya.
Agnes KiraggaAfrican Population and Health Research Center, Nairobi, Kenya.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The nationwide lockdown measures implemented during the coronavirus disease 2019 (COVID-19) pandemic disrupted food supply systems, potentially altering consumer purchasing behaviour. There is limited evidence quantifying these changes in low- and middle-income settings. This study aimed to examine the impact of COVID-19 on grocery purchase patterns among consumers in Nairobi. Using generalized least squares (GLS), we conducted an interrupted time series (ITS) analysis of weekly food purchase data from 2018 to 2023. The analysis considered three periods: pre-COVID (12th January 2018-26th March 2020), COVID (27th March 2020-21st October 2021), and post-COVID (22nd October 2021-31st December 2023). A total of 11,105,974 transactions from two supermarkets in Nairobi were classified using the NOVA food classification and linked with nutrient composition data. Compared to the pre-COVID period, characterized by declining purchases of processed culinary, unprocessed/minimally processed foods, and increasing ultra-processed food (UPF) purchases, the COVID period was associated with a short-term change toward healthier purchasing patterns, including reduced UPF, with increased processed and unprocessed/minimally processed food purchases. Nutritionally, pre-COVID trends of rising energy and carbohydrate purchases and declining proteins, calcium, iron, magnesium, potassium, and sodium, were contrasted by short-term increases during COVID in fibre, iron, magnesium, phosphorus, potassium, and sodium, alongside a long-term decline in carbohydrates. Proteins showed consistent short- and long-term increases, while calcium rose sharply at COVID onset but declined over time. In comparison, the post-COVID period reflected a reversal of these changes. While processed food purchases increased briefly before declining, longer-term trends showed increases in calcium, sodium, and carbohydrate purchases and decreases in energy and fat. These findings shed light on how populations adapt their food purchasing behaviors during and after global crises, offering insights that can inform future policies aimed at curbing unhealthy food purchases and strengthening food security.

Identifiers

PMID42224212
PMCPMC13225382

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.