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 tool to reduce the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, this approach has indirectly caused, only in Lima- Peru, more than 2.3 million Peruvians to lose their jobs. As a result, the risk of food insecurity may have increased in affected low-income families, especially those that depend on daily income. 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 the non-probability sample, 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 a stepwise forward selection. A Poisson generalized linear model (Poisson GLMs), 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 relatives with probable SARS-CoV2 cases (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 reported 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 also more likely to experience MSFI. Interpretation People most at risk of MSFI were those in a critical economic situation before and during the pandemic period. It is necessary to reinforce social protection policies to prevent or mitigate these adverse effects. Funding None.

Role of Government Financial Support and Vulnerability Characteristics Associated with Food Insecurity during the COVID-19 Pandemic among Young Peruvians

“…A limitation of this study is a possible misclassification associated with attrition biases in the phone-survey, potentially resulting in an underestimation of the prevalence of FI. Nonetheless, our results were consistent with the prevalence reported in a previous study that analysed FI during the lockdown period in Peru [33]. We also recognise some limitations that may affect our results concerning the association between government support and FI.…”

“…According to the Peruvian bureau of statistics 14% of families from Metropolitan Lima and Callao were unable to buy sources of protein (meat, fish, and eggs) during the pandemic. Furthermore, changes in dietary patterns such as the lower consumption of minimally processed food, along with sedentary lifestyles, could contribute to an increase in the prevalence of excess weight [33].…”

Effects of the COVID-19 Pandemic on Mental Health in Peru: Psychological Distress

“…It has been proposed to implement sex-sensitive preventive strategies [17,50,51], also related to age [17,18], socioeconomic level [14], culture, and ethnicity [52]. In Colombia, Ecuador, and Spain, it was seen that woman and the elderly were most involved with self-care activities and healthy routines, while in Chile, it was men and those under 60 years of age who had higher levels of healthy routines and compliance with published guidelines for prevention [17].…”

“…A limitation of this study, similar to others implemented in the country [14], is that only people with internet access could participate, leaving out groups of lower income and educational level, with a presumably higher risk of contagion and with a risk perception different from the analyzed sample. This possible bias is visible in that 85.9% of those who participated had university or a higher educational level, far from the average in the country and explained by the dissemination method conducted by researchers in universities.…”

“…Although economic measures were put in place in Peru for lower-income people, making it easier for them to be confined at home, fewer than 15.7% received them. This situation is explained by not having information about vulnerable people and because 59.8% of the adult population did not have a bank account to receive their welfare assistance money [14]. Peru, being one of the first countries in Latin America where its government took steps to control the pandemic and whose inhabitants were quite willing to comply, could not avoid generating the highest mortality rates from COVID-19, something that can be understood by Peru having the lowest per capita income, higher poverty rates, and a worse health system, as compared to other Latin American countries [15].…”