87% rural households in Salone forced to miss meals due to COVID-19

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A study published in February in the journal Science Advances aims to provide some answers on how COVID-19 pandemic has had a chilling impact on people’s daily lives.

The researchers are worried about the long-term effects of the economic crisis spurred by the pandemic, which can play out in a number of ways. The study found that many households were unable to meet basic nutritional needs.

According to the surveys, the researchers said that by April, many households were already unable to meet basic nutritional needs. For example, 48% of rural Kenyan households, 69% of landless agricultural households in Bangladesh, and 87% of rural households in Sierra Leone were forced to miss meals or reduce portion sizes to cope with the crisis.

From April to July 2020, researchers collected data on the socioeconomic impact of COVID-19 from over 30,000 households in nine lower- and middle-income countries: Bangladesh, Burkina Faso, Colombia, Ghana, Kenya, Nepal, Philippines, Rwanda and Sierra Leone.

In phone surveys using random numbers, researchers asked families in a range of income brackets how the pandemic has affected their jobs and income, their health, their ability to put food on the table and their children’s education.

The study further revealed that a full 50 to 80% of sample populations in Bangladesh, Burkina Faso, Colombia, Ghana, Kenya, Rwanda, and Sierra Leone report income losses during the COVID-19 period. “If these effects persist, then they risk pushing tens of millions of already vulnerable households into poverty.”

“This economic shock caused by the global pandemic spans socioeconomic strata within each country, and similar proportions of households at different rungs of the socioeconomic ladder report employment and income decreases. While the data shed light on the proportion of population suffering an income decline during the period, it should be noted that we are only able to characterize the magnitude of the decline for specific households in some of the samples.”

They sampled the more agriculture-dependent nations, the baseline pre–COVID-19 period falls during a postharvest season in Bangladesh, Burkina Faso, Ghana, Nepal, and Sierra Leone, when food stocks in the rural population tend to be relatively high, and food prices are typically low.

While this timing is fortunate for households’ ability to cope, postharvest is also a low point for agricultural labor demand in these countries, making subsequent declines in income and employment particularly notable. “In Burkina Faso, Philippines, Rwanda, and Sierra Leone the RDD samples are less poor, and in Burkina Faso, Ghana, and Sierra Leone they are more urban than the national population. Household sizes are larger in the RDD samples than in the national population in Ghana, Kenya, Philippines, Rwanda, and Sierra Leone. In the Philippines, RDD respondents are disproportionately female, while in Ghana they are more likely male.”

During the same period, food expenditures in Kenya and Sierra Leone actually rose slightly, by 11% (B1) and 6% (B2), respectively, although in Sierra Leone, this appears to have been driven by higher food prices facing these households (19%, P < 0.05 relative to the pre-period; (C2) rather than greater quantities consumed. Examining food insecurity in greater detail, the researchers observe rising rates of missed meals and reduced portions during the crisis in both Kenya (D1) and Sierra Leone (D2), respectively.

In Kenya, they record a 38% proportional increase in the rate of adults missing meals (0.5 meals per week) and 69% for children (0.5 meals per week). The proportional increase in the share of adults reducing portions in Sierra Leone is 86% (30 percentage points) and for children is 68% (17 percentage points, P < 0.05 for all of these effects).

The Sierra Leone sample is representative of households in 195 rural towns across all 12 districts of Sierra Leone. Surveys in Sierra Leone were conducted across 2,439 households. The pre–COVID-19 levels are from questions that recall data from February (A1) and March (A2 to C2) or from a previous survey conducted in November 2019 (D2).

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