The hidden inequality: the disparities in the quality of daily use masks associated with family economic status

Abstract

Wearing high-quality masks plays a critical role in reducing COVID-19 transmission. However, no study has investigated socioeconomic inequality in the quality of masks. Addressing this gap, this paper explored the relationships between mask's quality and family economic status. The cross-sectional survey was conducted in two Chinese universities by distributing structured questionnaires to assess participants' characteristics including family economic status, and meanwhile collecting their masks to evaluate the quality by measuring particle filtration efficiency. The valid responses were obtained from 912 students with mean age of 19.556 ± 1.453 years and were analyzed by using fractional or binary logistic regression. Three main findings were presented. First, inequality existed in the quality of masks. 36.07% of students were using unqualified masks with average filtration efficiency of 0.795 ± 0.119, which was much lower than China's national standard (0.9). Of those masks with identified production date, 11.43% were manufactured during COVID-19 outbreak when market was flooded with counterfeit production, and thus were of poor quality with average filtration efficiency of 0.819 ± 0.152. Second, better family economic status was associated with better masks' filtration efficiency and greater probability of using qualified masks. Third, students with better family economic status tend to use masks with individual packaging, and unique patterns and special designs, which may lead to inequality on a psychological level. Our analysis reveals the hidden socioeconomic inequality that exist behind cheap masks. In facing the challenges of future emerging infectious diseases, it is important to address the inequity to ensure equal access to affordable qualified personal protection equipment.

Keywords: COVID-19; family economic status; hidden socioeconomic inequality; particle filtration efficiency; personal protection equipment; the quality of masks.

Figure 1

(A) The proportion of masks with unqualified filtration efficiency against sampling date. (B) The histogram of filtration efficiency rate distribution. (C) The filtration efficiency of masks collected in the survey against production date. (D) The filtration efficiency of masks with additional samples against production date.

Figure 2

The procedure of testing the particle filtration efficiency of masks (calculation of particle filtration efficiency = (ambient particle concentration−behind the mask particle concentration) / ambient particle concentration).

Figure 3

(A) The forest plot of logistic regression results estimating the relationships between particle filtration efficiency of masks and family economic status (full sample). (B) The forest plot of logistic regression results estimating the relationships between particle filtration efficiency of masks and family economic status (samples collected in Guangzhou). (C) The forest plot of logistic regression results estimating the relationships between particle filtration efficiency of masks and family economic status (samples collected in Changsha). (D) The forest plot of logistic regression results estimating the relationships between whether the particle filtration efficiency of the mask is qualified and family economic status (full sample). (E) The forest plot of logistic regression results estimating the relationships between whether the masks are individually wrapped and family economic status (full sample). (F) The forest plot of logistic regression results estimating the relationships between whether the masks have the unique patterns or special designs and family economic status (full sample).