RESUMEN
Background: Unmeasured confounding is the primary obstacle to causal inference in observational research. We aimed to illuminate the association between exposure to influenza vaccination (IV) within six months before contracting the coronavirus disease (COVID-19) and COVID-19 hospitalization in relation to unmeasured confounding using the E-value method. Materials and Methods: Information about 367 patients, 103 of whom (28.07 %) had received IV, and confounders included sex, age, occupation, cigarette smoking, opium, and comorbidities were collected. We estimated the interest association using the inverse probability weighted (IPW) method. There was no information on some potential unmeasured confounders, such as socioeconomic status. Therefore, we computed E-value as a sensitivity analysis, which is the minimum strength of unmeasured confounding to explain away an exposure-outcome association beyond the measured confounders completely. Results: IPW denoted 1.12 (95% CI: 0.71 to 1.29) times greater risk of COVID-19 hospitalization in patients exposed to IV than in unexposed individuals. Sensitivity analysis demonstrated that an E-value (95% CI) of 1.49 (1.90 to 2.15) is required to shift the RR and the corresponding confidence Interval (CI) lower and upper limits toward the null. Moreover, if they had been omitted, the most computed E-values for measured confounders were relatively larger than for unmeasured confounders. Conclusion: According to the context of the measured confounders, if they had been omitted, an E-value of 1.16 to 1.76, a weaker confounding could fully explain away the reported association, suggesting that no relationship exists between IV and COVID-19 hospitalization.
RESUMEN
BACKGROUND: Mortality rate in low-birth-weight infants is almost 30 times more than that in those with normal weight, so the birth of low-birth-weight infants is one of the most serious health problems in the world. Therefore, this nested case-control study was conducted to investigate the risk factors associated with low birth weight among infants in the rural population of Kerman province. METHODS: This nested case-control study was performed in rural areas of Kerman province, southeastern Iran. Case (n = 155) and control (n = 310) groups were selected using risk set sampling. Data were analyzed through Point and distance estimation (OR, CI) using conditional logistic regression method by Stata-12 software. RESULTS: The results of multivariate analysis showed that maternal BMI [OR = 0.3, CI 95% (0.1, 0.9)], gestational age [OR = 3.8, CI 95% (0.9, 6.1)], history of stillbirth [OR = 4.8, CI 95% (1.3, 11)], history of pregnancy bleeding [OR = 3.7, CI 95% (0.7, 9)], pregnancy craving [OR = 3, CI 95% (1.1, 3.8)], and the level of health workers' care [OR = 0.4, CI 95% (0.1, 0.9)] are the risk factors affecting LBW in infants (P < 0.05). CONCLUSIONS: Low birth weight is a multifactorial phenomenon. Therefore, raising public awareness, providing nutritional counseling to pregnant mothers, regular referral to health homes to receive health care, and identifying risk factors and referral to higher level specialists and health centers can be effective in reducing the risk of birth of LBW infants.
