Introduction

The World Health Organization stated a pandemic by severe acute respiratory syndrome coronavirus SARS-Cov2 (COVID-19) in March 2020 [1] with devastating implications for populations, healthcare systems, and economies globally. Understanding the predictors of mortality by COVID-19 is essential for targeting preventing efforts around the world. Extensive literature has proven that age, obesity [2], cardiovascular disease [3, 4], hypertension [5], and type 2 diabetes [6] are established predictors of adverse COVID-19 but we have yet to understand whether socioeconomic determinants play a role on mortality risk.

Based in the “Social Determinants of Health” approach and the ecosocial epidemiology, the cumulative and dynamic interplay processes of exposure, susceptibility, and resistance, which influences health at the singular and general levels, could have been an important factor to understand processes which shape population health—as well as the COVID-19 pandemic [7–11].

Some studies have already suggested that socioeconomic deprivation [12–14], such as crowding conditions [15], living in poorly ventilated spaces [16, 17], and social inequality have a major impact on the transmission of the virus [18]. We also know that these effects may be higher for pregnant women [19]. There is evidence that there is an over-representation of black, Asian and minority ethnic in the COVID-19 positive groups [20–23].

Other communicable and non-communicable disease pandemics show similar socioeconomic patterns [24]. People living in neighborhoods with a high concentration of poverty are more likely to develop diabetes [25, 26], chronic obstructive pulmonary disease [27], and air obstruction [28].

Yet, we do not know what the mechanisms behind such relationship may be. We studied the role of socioeconomic conditions on the effects of COVID-19 by dividing its potential impacts on two mechanisms: those related with living in crowding conditions, and those related directly with income poverty. Closed environments may facilitate secondary transmission of coronavirus disease [17].

The association between COVID-19 and some social determinants in Mexico has been studied [7, 29–32], however, some important questions remain with this topic. Thus, the present study explores the association of living in municipalities with higher rates of crowding conditions and poverty and the risk of mortality from COVID-19 in Mexico. In this sense, we hypothesize that a) the risk of mortality will be higher for individuals living in municipalities with higher rates of crowding conditions and poverty, and b) the risk of mortality will be higher for individuals with obesity, diabetes, and hypertension and living in municipalities with higher rates of crowding conditions.

Methods

Results

Characteristics of individuals tested positive COVID-19

Sociodemographic characteristics of the 3478514 individuals who tested positive for COVID-19 according to levels of crowding conditions are listed in Table 1. Compared to those living in municipalities with lower rates of crowding conditions a higher proportion of municipalities with higher rates of indigenous population, population with incomplete elementary school and illiterate was observed among individuals living in municipalities with higher rates of crowding conditions. In terms of poverty and income distribution, Gini index was higher among those who live in municipalities with higher rates of crowding conditions, we also observed that these individuals live in municipalities with higher rates of multidisciplinary poverty and extreme multidisciplinary poverty when compared to the individuals living in municipalities with lower rates of crowding conditions. Gaps and vulnerabilities such as food insecurity, social security and health services were more present in subjects living in municipalities with higher rates of crowding conditions. People living in municipalities with worse crowding conditions were more likely to have a diagnosis of obesity, type 2 diabetes and hypertension compared to those living in municipalities with lower rates of crowding conditions.

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Table 1. Sociodemographic characteristics and chronic conditions of patients with COVID-19 according to the municipality level of crowding conditions.

https://doi.org/10.1371/journal.pone.0264137.t001

Role of overcrowding conditions and poverty on mortality

Crude and adjusted hazard ratios and 95% CIs of mortality amongst those who tested positive for COVID-19 are presented in Table 2. Living in a municipality with higher rate of crowding conditions increased the risk of dying from COVID-19 by 8% (95% CI: 1.03, 1.14). Living in a municipality with higher rates of indigenous background was associated with an increased risk of dying from COVID-19 (HR = 1.10; 95% CI: 1.04, 1.17). Individuals living in a municipality with higher rates of illiteracy (HR = 1.09; 95% CI: 1.03, 1.11), poverty (HR = 1.17; 95% CI: 1.14, 1.19), food insecurity (HR = 1.04; 95% CI 1.02, 1.06), limited access to social security (HR = 1.10; 95% CI: 1.08, 1.13) and limited health services (HR = 1.06; 95% CI: 1.04, 1.08) had a higher risk of dying from COVID-19.

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Table 2. Hazard ratios (95% confidence intervals) for mortality amongst those tested positive for COVID-19.

https://doi.org/10.1371/journal.pone.0264137.t002

Interaction between living in municipalities with overcrowding conditions, access to health services and chronic conditions

We tested the joint association between living in municipalities with higher rates of crowding conditions and access to health services and chronic conditions with mortality from COVID-19 (Figs 1 and 2). In Fig 1, the reference group for comparisons was composed of subjects living in municipalities with lower rates of crowding conditions and subjects living in municipalities with higher rates of access to health services. Relative to the reference group, the HR of the individuals living in a municipality with higher rates of crowding conditions and individuals living in municipalities with lower rates of access to health services was 1.53 (95% CI: 1.40, 1.67; P for interaction <0.001). Additionally, we observed that relative to the reference group, the HR of the group living in a municipality with higher rates of crowding conditions and living with type 2 diabetes was 1.20 (95% CI: 1.14, 1.27; P for interaction <0.001).

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Fig 1. Interaction between crowding conditions and access to health services and mortality on patients with COVID-19.

https://doi.org/10.1371/journal.pone.0264137.g001

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Fig 2.

Interaction between crowding conditions and a) Obesity, b) Type 2 diabetes and c) Hypertension and mortality on patients with COVID-19.

https://doi.org/10.1371/journal.pone.0264137.g002

Discussion

The aim of the present study was to explore the association between crowding conditions and poverty and the mortality risk from COVID-19 in Mexico, with additional emphasis in other social determinants like some deficiencies (e.g. food insecurity) and vulnerabilities (e.g. indigenous population, illiteracy), as well as the interaction with some comorbidities. From a total of 3478514 cases who tested positive for COVID-19, our data suggests that municipalities with higher rates of crowding conditions, and higher rates of poverty (measured by the income below the welfare line) are associated with higher risk of mortality from COVID-19 in Mexican adult population. In addition, we also found, that in municipalities with higher rates of conditions like being indigenous, illiterate, food insecure, lack of access to social security, health services, from places with <5,000 inhabitants increase the risk of dying from COVID-19.

Also, there is multiple evidence suggesting that noncommunicable diseases and COVID-19 may be associated at different levels, increasing the probability of severe disease and death [34, 38]. Furthermore, given the high burden of disease attributable to non-communicable diseases in Mexico, it is necessary to generate information on their contribution to the risk of mortality from COVID-19. Our findings suggest that individuals living in a municipality with higher rates of crowding conditions and living with obesity, hypertension, and/or diabetes, were associated to a higher risk of mortality from COVID-19.

Our study suggests that social inequalities, like higher rates of crowding conditions and poverty have a relevant contribution and role in the COVID-19 pandemic in Mexico. Our analysis found that patients living in municipalities with higher rates of crowding conditions had 8% (95% CI: 1.03, 1.14; P trend <0.001) higher risk to die from COVID-19, compared to those living in a municipality with lower rates of crowding conditions. A recent study conducted by Krieger et al. [39] found a similar association; households in the highest crowding group had greater risk ratios (RR = 1.7; 95% CI: 1.0, 2.9) of mortality from COVID19 compared to those in lowest crowding group. In this sense, previous studies have suggested that higher rates of crowding conditions has been related to certain factors such as poor ventilation, air pollution and poor sanitation within homes which has been related with infectious diseases, particularly respiratory diseases [40]. Additionally, other study has proposed that higher rates of crowding conditions could increase anxiety, stress and depressive symptoms which has been related with obesity and other non-communicable diseases via low grade inflammation and this could also explain the relation with COVID-19 [41].

Initially in Mexico, the spread of COVID-19 began in subjects of high socioeconomic status who live in more developed municipalities of the country; however, our data suggest that more vulnerable populations living in small areas, which are exposed to a persistent and historical context of social deprivation, have been more affected by COVID-19. Thus, we observed that patients living in municipalities with higher rates of poverty had 17% (95% CI: 1.14, 1.19; P trend <0.001) higher risk of mortality from COVID-19, compared to those living in municipalities with lower rates of poverty. Consistent with our findings, previous studies have suggested that poverty and other vulnerabilities are associated with an increased risk of mortality from COVID-19 [39, 42–44].

These findings are of concern specially since these populations lack the resources to implement or adopt preventive measures. For example, given their socio-economic conditions, having no financial reserves, and depending on emergency government assistance, they will scarcely be able to adhere to special recommendations such as social isolation, wearing masks, and hand hygiene. Also, the lack of access to minimum resources, such as potable clean water and basic sanitation (e.g. drainage) can increase the risk of illness due to COVID-19, as observed with other respiratory diseases [45].

To our knowledge, there are no previous studies evaluating the joint effect of crowding conditions and lack of access to health services with the risk of mortality from COVID-19. Our results suggest that patients living in municipalities with higher rates of crowding conditions and with lower rates of access to health services had 53% (95% CI: 1.34, 1.72; P for interaction <0.001) higher risk to die from COVID-19, compared with those patients living in municipalities with lower rates of crowding conditions and living in municipalities with higher rates of access to health services.

We also found a joint effect of living in municipalities with higher rates crowding conditions and living with certain comorbidities like obesity, diabetes, and/or hypertension, and the risk of mortality from COVID-19. For example: our data proposed that compared with patients living in municipalities with lower rates of crowding conditions and without obesity, patients living with obesity and living in municipalities with higher rates crowding conditions had 1.15 times higher risk of dying from COVID-19.

As these communities face crowding conditions, poverty, lack of access to health care, food insecurity, lack of access to basic sanitation services, among other deficiencies, there is a need to focus more on the underlying factors that put them at higher risk. For that reason, in these vulnerable groups the governments should place more emphasis on their social distancing behaviors and assess their needs for basic resources such as food, medicine, personal protective equipment and other essential supplies necessary to socially distance themselves during the current pandemic.

COVID-19 has the potential to substantially exacerbate socioeconomic and ethnic inequalities in health, unless measures are taken to mitigate these inequalities [46]. Thus, policy response is essential to guarantee that the health system is reactive to the requirements of these vulnerable groups.

The present study has some important limitations. First, collider bias is an important problem and could result in several ways, including differential healthcare requesting, differential examination and differential diagnosis. Despite this, we did not find evidence to suggest that differential medical care seeking, or testing would explain the pattern of results observed in our study. Second, as we noted in a previous study [34], Although the information is from subjects from all over Mexico, patients who were asymptomatic or who were treated at home are not part of our data, so our study represents only those most severe cases of COVID-19, and the results observed cannot be extrapolated to non-severe COVID-19 cases. Moreover, since sentinel units were not randomly designated, our results are not likely to be representative of the entire Mexican population. Furthermore, at the national level, by protocol, tests were only performed on those patients with severe respiratory conditions, and to a lesser extent on subjects with mild respiratory conditions; therefore, our results may underestimate how living in municipalities with higher rates of crowding and higher rates of poverty are associated with the COVID-19 prognosis, as it is highly likely that people living in municipalities with higher rates of crowding and higher rates of poverty have less access to health services. In addition, in relation of the association with non-communicable diseases, the protocol mentioned above may also underestimate the relationships, as those with mild respiratory conditions will have a better prognosis. Finally, our indicators of crowding, poverty, vulnerabilities, and other conditions, share these indicators at the municipality level; thus, it does not reflect the condition of the individual but that of the municipality where people live.

Although the limitations, the present study has some strengths. Comparative studies between crowding conditions and poverty as well as other vulnerabilities associated with the risk of mortality from COVID-19 are scarce; therefore, our findings may help identify these relations. Although it is probable that our results are not representative of the entire population, our study contains nationwide data. Lastly, as previously reported [34], multivariate analysis, due to our large sample size, reduce de possibility of confounding factors.

Conclusion

This study adds information that emphasize that vulnerable communities have a greater risk of mortality from COVID-19. Our data suggest that patients living in municipalities with higher rates of crowding conditions, higher rates of poverty, and higher rates of other conditions; indigenous population, illiterate, food insecurity, lack of access to social security, lack of access to health services had higher risk of mortality from COVID-19. Also, we found a joint effect of living in municipalities with higher rates of crowding conditions and living with certain comorbidities like obesity, diabetes, and/or hypertension, and the risk of mortality from COVID-19 in Mexican population.

In Mexico, the COVID-19 pandemic is a systemic crisis linked to human development since we have seen that it affects less developed and more vulnerable localities. Policies to reduce vulnerabilities and develop strategies need to consider the following points: 1) adoption of effective evidence-based prevention mechanisms that consider collective risk and the social context; 2) expand and prepare the health system at all levels; 3) guarantee social protection; and 4) develop strategies that promote vaccination of vulnerable populations.

Supporting information

Acknowledgments

We thank Mariel White for her support in proofreading.