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1.
Comput Math Methods Med ; 2021: 4691477, 2021.
Article in English | MEDLINE | ID: mdl-34873415

ABSTRACT

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.


Subject(s)
Health Services Accessibility/trends , Maternal Health Services/trends , Adolescent , Adult , Bayes Theorem , Computational Biology , Female , Health Care Surveys , Health Services Accessibility/statistics & numerical data , Healthcare Disparities/statistics & numerical data , Healthcare Disparities/trends , Humans , Infant, Newborn , Logistic Models , Longitudinal Studies , Maternal Health Services/statistics & numerical data , Middle Aged , Pakistan , Pregnancy , Prenatal Care/statistics & numerical data , Prenatal Care/trends , Socioeconomic Factors , Young Adult
2.
Comput Math Methods Med ; 2021: 9908175, 2021.
Article in English | MEDLINE | ID: mdl-34938361

ABSTRACT

Semigroups are generalizations of groups and rings. In the semigroup theory, there are certain kinds of band decompositions which are useful in the study of the structure of semigroups. This research will open up new horizons in the field of mathematics by aiming to use semigroup of h-bi-ideal of semiring with semilattice additive reduct. With the course of this research, it will prove that subsemigroup, the set of all right h-bi-ideals, and set of all left h-bi-ideals are bands for h-regular semiring. Moreover, it will be demonstrated that if semigroup of all h-bi-ideals (B(H), ∗) is semilattice, then H is h-Clifford. This research will also explore the classification of minimal h-bi-ideal.


Subject(s)
Mathematical Concepts , Models, Statistical , Computational Biology , Fuzzy Logic , Humans
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