Development of improved estimators of finite population mean in simple random sampling with dual auxiliaries and its application to real world problems.

In general, the incorporation of supplementary information reduces the Mean Square Error (MSE) and, consequently, enhances the precision of estimating a population parameter. This improvement relies on the appropriate application of a suitable function, with careful consideration. This study introduces two innovative families of estimators for the finite population mean, both of which exhibit superior performance in scenarios involving dual auxiliary information in simple random sampling. Expressions up to the first-order approximation, for bias, and Mean Square Error were derived, and the conditions under which these proposed families surpassed the existing estimators. Our evaluation involved the use of both real and simulated data to compute the Mean Square Error and Percent Relative Efficiency (PRE) of the estimators. A comparative analysis revealed that under the specified conditions, both proposed families yielded more precise results.

Investigating socioeconomic disparities of Kangaroo mother care on preterm infant health outcomes.

Several studies have been conducted to examine the complicated relationships between various factors that influence Kangaroo mother care (KMC) for preterm infants. However, the extended socio-economic model has not been seen in any of the previous studies that looked into the factors related to KMC and how it affects the health outcomes of babies born before in our study population. This study examines the various dimensions of KMC implementation and its influence on the health outcomes of premature infants. The current cross-sectional study was carried out in South Punjab, Pakistan, covering both private and public KMC units in obstetrics and gynecology departments. The study included a sample size of 719 patients and was conducted during a period covering 21 September 2022 to 14 October 2023. Multinomial logistic regression analysis is employed to ascertain the factors by using SPSS-26 (SPSS Inc., Chicago, IL). The use of folic acid (OR: 1.44; 95% CI: 0.87-3.11) and factor anemia (OR: 8.82; 95% CI: 1.69-14.59) no significantly correlated with better health outcomes, while environmental toxin exposure had a negative impact (OR: 0.90). The findings underscore the need for comprehensive interventions and policies to bridge socioeconomic gaps, ensuring all preterm infants benefit from KMC.

Assessing socio-ecological factors on caesarean section and vaginal delivery: an extended perspective among women of South-Punjab, Pakistan.

Research was conducted employing the extended socio-ecological model (ESEM) to examine factors associated with cesarean sections (CSs) and vaginal deliveries (VDs) among the women in our study population. Using the ESEM to determine South-Punjab and Pakistani women's mode of delivery predictors. The cross-sectional study with a sample size of 908 patients was conducted through private and public obstetrics and gynecology departments in South Punjab, Pakistan, from 12 June 2022 to 29 May 2023. The Chi-square analysis compared baseline variables, delivery outcomes and delivery methods. Logistic regression analysis is used to determine predictive factors. The study revealed that 75.66% of women had CS, while 24.34% had VD. Education level, age, residential area and fetal presentation all had significant associations with mode of delivery. Logistic regression analysis suggested that gynecologist recommendation, belief in CS safety, abnormal fetal presentation, maternal anemia and meconium aspiration syndrome were all significant predictors of CS. The ESEM model concluded that age, fatigue and women's preference for CS due to its reliability for her and her fetus were predictive factors for mode of delivery choices among South-Punjab Pakistani women.

Risk factors identification of COVID-19 patients with chronic obstructive pulmonary disease: A retrospective study in Punjab-Pakistan.

BACKGROUND: Accessibility to the immense collection of studies on noncommunicable diseases related to coronavirus disease of 2019 (COVID-19) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an immediate focus of researchers. However, there is a scarcity of information about chronic obstructed pulmonary disease (COPD), which is associated with a high rate of infection in COVID-19 patients. Moreover, by combining the effects of the SARS-CoV-2 on COPD patients, we may be able to overcome formidable obstacles factors, and diagnosis influencers. MATERIALS AND METHODS: A retrospective study of 280 patients was conducted at DHQ Hospital Muzaffargarh in Punjab, Pakistan. Negative binomial regression describes the risk of fixed successive variables. The association is described by the Cox proportional hazard model and the model coefficient is determined through log-likelihood observation. Patients with COPD had their survival and mortality plotted on Kaplan-Meier curves. RESULTS: The increased risk of death in COPD patients was due to the effects of variables such as cough, lower respiratory tract infection (LRTI), tuberculosis (TB), and body-aches being 1.369, 0.693, 0.170, and 0.217 times higher at (95% confidence interval [CI]: 0.747-1.992), (95% CI: 0.231-1.156), (95% CI: 0.008-0.332), and (95% CI: -0.07 to 0.440) while it decreased 0.396 in normal condition. CONCLUSION: We found that the symptoms of COPD (cough, LRTI, TB, and bodyaches) are statistically significant in patients who were most infected by SARS-CoV-2.

Intolerance of uncertainty across stress, anxiety, and depression among university students in Pakistan: A descriptive cross-sectional study.

Background: The mental health issues due to COVID-19, such as intolerance of uncertainty (IOU), anxiety, stress, and depression, have attracted extensive attention from researchers. The challenges for Pakistani university students could be worse than developed countries due to the lack of online courses/programs and online mental health support provided by academic institutions. Therefore, the current study aims to assess the intolerance of uncertainty, depression, anxiety, and stress of Pakistani university students after the second wave of COVID-19 and the relationship among these constructs. Methods: A convenience cross-sectional sampling method was used to collect data from university students in Pakistan between January 2021 and April 2022 via a structured online questionnaire. The Descriptive analysis focused on frequencies, percentages, mean, and standard deviation (SD) were calculated on IOU-12 and DASS-21. Covariance for the research model and confirmatory factor analyses fit indices for the IOU-12 and DASS-21 were analyzed by AMOS statistical packages. Results: As expected, anxiety, depression, and stress persist among Pakistani university students. On average, they report mild to moderate mental health problems regarding anxiety, depression, stress, and intolerance of uncertainty. Our results indicate a strong positive relationship among the three emotional distress components - anxiety, depression, and stress. However, our results suggest no significant relationship between IOU and the three subcomponents of emotional distress (anxiety, depression, and stress). Limitations: First, the cross-sectional survey design means we cannot conclude on the causal relations. Second, the self-report questionnaire embeds subjectivity issues. Last, the generalizability of the sample to the whole student population in Pakistan is limited, considering the sampling method. Conclusion: This study expanded the current knowledge in the psychological health domain (intolerance of uncertainty, anxiety, depression, and stress) due to the COVID-19 pandemic. In practice, higher education institutions should further mitigate university students' mental health issues. For researchers, our findings inspire future studies to delve into the relationship between IOU and mental health issues due to COVID-19 since our findings display contrary evidence for various reasons.