Bayesian Analysis of Trends in Utilization of Maternal Healthcare Services in Pakistan during 2006-2018.

OBJECTIVES: This study is aimed at investigating the time trends and disparities in access to maternal healthcare in Pakistan using Bayesian models. Study Design. A longitudinal study from 2006 to 2018. METHODS: The detailed analysis is based on the data from Pakistan Demographic and Health Survey (PDHS) conducted during 2006-2018. We have proposed Bayesian logistic regression models (BLRM) to investigate the trends of maternal healthcare in the country. Based on different goodness-of-fit criteria, the performance of proposed models has also been compared with repeatedly used classical logistic regression models (CLRM). RESULTS: The results from the analysis suggested that BLRM perform better than CLRM. The access to antenatal healthcare increased from 61% to 86% during years 2006-18. The utilization of medication also improved from 44% in 2006 to 60% in 2018. Despite the improvements from 2006 to 2018, every three out of ten women were not protected against neonatal tetanus, neither delivered in the health facility place nor availed with the skilled health provider at the time of delivery during 2018. Similarly, two-fifth mothers did not received any skilled postnatal checkup within two days after delivery. Additionally, the likelihood of MHS provided to mothers is in favor of mothers with lower ages, lower birth orders, urban residences, higher education, higher wealth quintiles, and residents of Sindh and Punjab. CONCLUSIONS: The gaps in utilization of MHS in different socioeconomic groups of the society have not decreased significantly during 2006-2018. Any future maternal health initiative in the country should focus to reduce the observed disparities among different socioeconomic sectors of the society.

Belief and Possibility Belief Interval-Valued N-Soft Set and Their Applications in Multi-Attribute Decision-Making Problems.

In this research article, we motivate and introduce the concept of possibility belief interval-valued N-soft sets. It has a great significance for enhancing the performance of decision-making procedures in many theories of uncertainty. The N-soft set theory is arising as an effective mathematical tool for dealing with precision and uncertainties more than the soft set theory. In this regard, we extend the concept of belief interval-valued soft set to possibility belief interval-valued N-soft set (by accumulating possibility and belief interval with N-soft set), and we also explain its practical calculations. To this objective, we defined related theoretical notions, for example, belief interval-valued N-soft set, possibility belief interval-valued N-soft set, their algebraic operations, and examined some of their fundamental properties. Furthermore, we developed two algorithms by using max-AND and min-OR operations of possibility belief interval-valued N-soft set for decision-making problems and also justify its applicability with numerical examples.

Six-minute walk distance, ECOG Performance Status, and Modified Borg Scale scores in a cohort of Pakistani patients with noncancerous end-stage liver disease selected for liver transplant.

OBJECTIVE: To evaluate the functional status of Pakistani patients with non-cancerous end-stage liver disease selected for liver transplant and to compare results acquired through various assessment tools. METHODS: The study was conducted at the Rehabilitation Medicine Department, Shifa International Hospital Islamabad, Pakistan, from August 2017 to November 2019 and comprised end-stage liver disease patients of either gender who had been selected for liver transplant. Assessment tools included the Six-Minute Walk Distance, Eastern Cooperative Oncology Group Performance Status and Modified Borg Dyspnoea Scale across age, gender, ethnicity, primary aetiology, and Model for end-stage liver disease score. Data were analysed using SPSS 20. RESULTS: Of 172 patients, 143(83%) were males; 99(58%) hailed from the Punjab province; and 118(71%) had hepatitis C as the most common aetiology. The overall mean age was 46.1±10.5 years (range: 14-70 years). The mean Six-Minute Walk Distance was 291.9±67.2m. Model for end-stage liver disease score had a significant inverse correlation with Six-Minute Walk Distance (p<0.01) and a significant positive correlation with Modified Borg Dyspnoea Scale (p=0.02) and Eastern Cooperative Oncology Group Performance Status scores (p<0.01). Age and ethnicity had no correlation with the variables (p>0.05). CONCLUSIONS: The Six-Minute Walk Distance was significantly low. The Model for end-stage liver disease score was inversely correlated with Six-Minute Walk Distance score, and positively correlated with Eastern Cooperative Oncology Group Performance Status and Modified Borg Dyspnoea Scale scores.