A prevalência da pandemia COVID-19 (SARS-CoV-2) na população idosa, principalmente institucionalizada, ocorre por ser este o cenário em que o isolamento social é difícil em uma situação como a de uma pandemia. A vulnerabilidade dessa população está ligada aos aspectos fisiológicos do envelhecimento, que impactam na eficácia do sistema imunológico, desencadeando morbimortalidade por doenças infecciosas.
In this way, aging has become a global phenomenon in full exponential growth, showing the success of public health and socioeconomic development policies. However, there are new challenges for society that this presents. Our society needs to adapt to this new scenario, maximize the functional capacity and health of the elderly and promote their social inclusion and safe participation. [1]. In view of this, there are social consequences of the aging population and new public health issues arising that affect European countries, such as Italy, in particular [2]. In Italy, the profile of the elderly population is of a group with a high prevalence of non-communicable chronic diseases (NCCDs) and associated comorbidities [1]. In Italy, aging is a common and growing phenomenon. Italy is considered the country with the second largest number of elderly people [2], along with a mortality rate that has decreased by more than 50% in the last 30 years, mainly due to the reduction in cardiovascular diseases [3].
The COVID-19 pandemic (SARS-CoV-2) has caused considerable mortality in populations considered at risk, such as the elderly population, especially those who are institutionalized, a scenario in which social isolation is difficult in a situation such as a pandemic. The vulnerability of this population is linked with the physiological aspects of aging, which impact the effectiveness of the immune system, triggering morbidity and mortality from infectious diseases [4].
Thus, it is necessary to investigate the main factors that make institutionalized elderly people more vulnerable to death. Fragility is a condition that worsens with advancing age and with COVID-19 infection, especially for the hospitalized elderly, who tend to develop a more accentuated presentation of the classic symptoms of the disease [5].
The objective of this study was to synthesize the factors associated with the mortality of elderly Italian people diagnosed with coronavirus who lived in institutions or who were hospitalized because of the disease.
The main morbidities presented by the elderly in the studies were: dementia [6], diabetes [7][8], chronic kidney disease [7] and hypertension [8], showing that NCCDs had a key role to play in these cases.
Table 2 shows the descriptive analysis of the quantitative variables according to the survivors and non-survivors, and Table 3 shows the effect size, in SDM and 95% CI, of the variables affecting mortality.
Variables | SMD (95% CI) | I2 | Z | p-Value |
---|
Variables | RR (95% CI) | I2 | Z | p-Value |
---|---|---|---|---|
Age (years) | 3.10 (2.79; 3.40) | 99.9% | 19.76 | <0.001 |
Charlson Index | 1.74 (1.56; 1.92) | |||
Male | 0.98 (0.67; 1.43) | 89.3 | 0.10 | 0.919 |
- | 19.33 | <0.001 | ||
Chronic diseases | 1.20 (0.94; 1.54) | - | 1.48 | 0.139 |
Cancer | 1.60 (0.60; 4.23) | - | 0.92 | 0.356 |
Diabetes | 1.90 (1.53; 2.37) | 62.7 | 5.73 | <0.001 |
Cardiovascular diseases/coronary artery disease | 1.80 (0.85; 3.80) | 92.0 | 1.53 | 0.125 |
COPD 1 | 2.19 (1.54; 3.10) | 0.0 | 4.39 | <0.001 |
Immunodeficiencies | 5.28 (0.26; 108.12) | - | 1.08 | 0.280 |
Chronic kidney disease | 3.96 (2.65; 5.91) | 0.0 | 6.73 | <0.001 |
Metabolic disease | 1.51 (0.60;3.75) | - | 0.89 | 0.374 |
Obesity | 1.28 (0.78; 2.10) | 60.8 | 0.99 | 0.322 |
Hypertension | 1.37 (1.24; 1.51) | 69.3 | 6.25 | <0.001 |
FH 2 | 3.27 (2.49; 4.29) | - | 8.55 | <0.001 |
Dementia | 3.67 (2.43; 5.55) | - | 6.17 | <0.001 |
Smoking | 0.74 (0.32;1.71) | - | 0.70 | 0.483 |
Variables | Non-Survivors | Survivors | ||||
---|---|---|---|---|---|---|
N | Mean | SD | N | Mean | SD | |
Age (years) | ||||||
Iacarinno et al. (2020) | 188 | 79.6 | 0.8 | 1304 | 64.7 | 0.4 |
Stroppa et al. (2020) | 9 | 74.44 | 7.21 | 16 | 68.38 | 10.16 |
Bonetti et al. (2020) | 70 | 75.4 | 14.99 | 74 | 62.63 | 14.97 |
Charlson Index | ||||||
Iacarinno et al. (2020) | 188 | 4.37 | 0.14 | 1403 | 2.63 | 0.05 |
Table 4 shows the descriptive analysis of qualitative variables according to the survivors and non-survivors, and Table 5 shows the effect size, in RR and 95% CI, of the variables affecting mortality.
The analysis of quantitative variables showed that the risk of mortality was higher in individuals with diabetes (RR, 1.90; 95% CI, 1.53; 2.37), COPD (RR, 2.19; 95% CI, 1.54; 3.10), chronic kidney disease (RR, 3.96; 95% CI, 2.65; 5.91), hypertension (RR, 1.37; 95% CI, 1.24; 1.51), FH (RR, 3.27; 95% CI, 2.49; 4.29) or dementia (RR, 3.67; 95% CI, 2.43; 5.55) ( Table 4 ).