Social predictors of food insecurity during the stay-at-home order due to the COVID-19 pandemic in Peru. Results from a cross-sectional web-based survey

Abstract

Background

Stay-at-home orders and social distancing have been implemented as the primary tools to reduce the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, this approach has indirectly lead to the unemployment of 2·3 million Peruvians, in Lima, Perú alone. As a result, the risk of food insecurity may have increased, especially in low-income families who rely on a daily wage. This study estimates the prevalence of moderate or severe food insecurity (MSFI) and identifies the associated factors that explain this outcome during the stay-at-home order.

Methods

A cross-sectional web-based survey, with non-probabilistic sampling, was conducted between May 18 and June 30, 2020, during the stay-at-home order in Peru. We used social media advertisements on Facebook to reach 18-59-year-olds living in Peru. MSFI was assessed using the Food Insecurity Experience Scale (FIES). Rasch model methodology requirements were considered, and factors associated with MSFI were selected using stepwise forward selection. A Poisson generalized linear model (Poisson GLM), with log link function, was employed to estimate adjusted prevalence ratios (aPR).

Findings

This analysis is based on 1846 replies. The prevalence of MSFI was 23·2%, and FIES proved to be an acceptable instrument with reliability 0·72 and infit 0·8-1·3. People more likely to experience MSFI were those with low income (less than 255 US$/month) in the pre-pandemic period (aPR 3·77; 95%CI, 1·98-7·16), those whose income was significantly reduced during the pandemic period (aPR 2·27; 95%CI, 1·55-3·31), and those whose savings ran out in less than 21 days (aPR 1·86; 95%CI, 1·43-2·42). Likewise, heads of households (aPR 1·20; 95%CI, 1·00-1·44) and those with probable SARS-CoV2 cases as relatives (aPR 1·29; 95%CI, 1·05-1·58) were at an increased risk of MSFI. Additionally, those who perceived losing weight during the pandemic (aPR 1·21; 95%CI, 1·01-1·45), and increases in processed foods prices (aPR 1·31; 95%CI, 1·08-1·59), and eating less minimally processed food (aPR 1·82; 95%CI, 1·48-2·24) were more likely to experience MSFI.

Interpretation

People most at risk of MSFI were those in a critical economic situation before and during the pandemic. Social protection policies should be reinforced to prevent or mitigate these adverse effects.

Funding

None.

SciScore for 10.1101/2021.02.06.21251221: (What is this?)

Please note, not all rigor criteria are appropriate for all manuscripts.

Table 1: Rigor

Institutional Review Board Statement	Consent: Procedures: Participants who clicked on the link were redirected to a Qualtrics survey platform to read more about the study and give informed consent before starting the survey. IRB: Ethical Issues: The study was approved by the human ethics committee of “Instituto de Investigación Nutricional” (CIEI-IIN), Lima – Peru, N° 394-2020/CIEI-IIN.
Randomization	not detected.
Blinding	not detected.
Power Analysis	not detected.
Sex as a biological variable	not detected.

Table 2: Resources

No key resources detected.

Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:

The study has some limitations because it is a cross-sectional study; it cannot establish causal relationships. There might be bias due to the lack of randomization in selecting participants, which might mean that the results shown are only generalizable to our study population. It is important to discuss how the sample was obtained. This study is a web-based survey study where participants were not randomly selected. Ideally, we expected to have a sample with similar sociodemographic characteristics to the Peruvian national population (21·2% and 20·8% whit poorest quintile and poor quintile, respectively; with 28·8% of the Peruvian population residing in the province of Metropolitan Lima and 71·2% residing in other provinces or departments of Peru; with 60% of women between 15-49 years old having at least secondary level education and around 40% having higher education) (43, 44). However, our sample was constituted mainly by women (74·9%) and people who residing in the province of Lima Metropolitana (67·7%); with only 12·9% of those women have at least secondary level education, 87·1% have higher education (data do not show in the table) and with 12·4% of people with households with an average monthly income of less than 255 US$/month in pre-pandemic period (similar to the group of the poorest quintile). Considering these characteristics of the general Peruvian population and our study sample, we can mention that this study’s sample has a similar distribution to Peruvian pop...

Results from TrialIdentifier: No clinical trial numbers were referenced.

Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

Results from JetFighter: We did not find any issues relating to colormaps.

Results from rtransparent:

Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
No protocol registration statement was detected.

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