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The objective of the current study is to identify the risk factors for malnutrition among the age of under-five children’s in Pakistan. This is secondary data analysis for the data taken from Pakistan Demographic and Health Survey (PDHS 2017–18) and was analyzed by implementing quantile regression analysis. The sample size included 12,708 alive children in the study, for which the data collection period was from November 22, 2017, to April 30, 2018. The prevalence of malnutrition among boys is high (51.2%). Older age mother’s children have more prevalence of malnutrition (20.7%). A child born with small body size (underweight: Q0.25: − 0.625; Q0.50: − 0.623; Q0.75: − 0.426 and wasting: Q0.50: − 0.513); having uneducated mother (underweight: Q0.25: − 0.387; Q0.50: − 0.247; Q0.75: − 0.328), belonged to a poor household (underweight: Q0.50: − 0.251),residing in rural areas (underweight: Q0.25: − 0.443), not following properly breastfeeding practices (underweight: Q0.50: − 0.439; Q0.75: − 0.438) have negative effect on different measures of malnutrition and this effect is significantly raises across different quantiles of stunting , wasting and underweight (at p value < 0.01 and < 0.05). Older age mother (stunting: Q0.50: 0.777; Q0.75: 1.078; underweight Q0.20: 0.568; Q0.50: 0.429; Q0.75: 0.524) and higher birth order number (stunting: Q0.50: 0.415; Q0.75: 0.535), have a positive effect on three measures of under-nutrition and this effect is gradual raises at different quantile of stunting, wasting and underweight. Elder and smoker mothers were proved associated risk factors of both stunting and being underweight in Pakistan. Moreover, Proper breastfeeding practices, better economic status, average or above the average birth weight of the child, and milk consumption are found protective factors against stunting, wasting, and underweight children in Pakistan.

Objectives: To develop an externally validated multivariable prognostic model for an underprivileged dialysis population.Methods: This was a multicenter retrospective cohort study of 5 years duration from January 2013 to December 2017. A total of 758 patients (37.5% female; mean±SD age, 44.26±14.77 years) were enrolled for construction of the prognostic model. The data were analyzed using a proportional hazards model to identify predictors of survival. Three risk groups were identified at the 25th and 75th percentiles of the resultant prognostic index. The model was externally validated with another dataset of 622 dialysis patients. Original ArticleResults: The prognostic index included 5 predictor variables: hemoglobin, serum potassium, interdialytic weight gain, serum albumin, and duration of dialysis, which had good predictive performance on the calibration and discrimination aspects of the model (Harrell's c statistic: 0.748, Gonen and Heller k statistic: 0.647, Somers' D statistic: 0.496, calibration slope: 1.156). There were significant interaction effects between weight and hemoglobin, weight and albumin, albumin and potassium, and albumin and hemoglobin. Conclusions:We developed an externally validated model that contained 5 routinely collected prognosticators and confirmed its calibration and discrimination abilities in obtaining reliable prognostic estimates in developing countries. The model will assist clinicians in deciding the prognosis of dialysis patients. The application of this model in different clinical settings of developing countries can indicate interesting findings regarding public health.

BackgroundEvery year, 2 million babies are stillborn in the world. Globally, there has been a decline in the stillbirth rate of 2%. Despite advancements in prenatal care and the implementation of new medical technologies, the incidence of early stillbirths remains unchanged. A slight decrease in the rate of late-term stillbirth has been observed. Pakistan ranked third in South Asia for having the highest stillbirth rate. Compared to its neighbors and other developing nations, Pakistan has shown a lack of progress in reducing maternal and neonatal fatalities. Therefore, the purpose of this study is to use a multivariate decomposition analysis to examine the trends and factors that have contributed to the change in the stillbirth rate over time.MethodsTo conduct this study, we used a secondary data analysis approach and analyzed data from the Pakistan Demographic and Health Survey (PDHS) of 2012–2013 and 2017–2018). For the analysis, a total sample of 15,068 births in 2017–2018 and 13,558 births in the PDHS from 2012 to 2013 were taken into account. Using the MVDCMP function within STATA version 15 statistical software, a logit-based multivariate decomposition model was fitted to determine the variables that influence the change in stillbirth. The current study used two cross-sectional surveys to identify important risk factors for stillbirths.ResultsOver the past 5 years, Pakistan's stillbirth rate has risen from 3.98 to 5.75%. According to the total multivariate decomposition analysis, the change in coefficient (change in the effect of attributes) accounted for 81.17% of the overall change in the proportion of stillbirths. In contrast, the change in endowment was not statistically significant. Changes in maternal education, individual and community-level wealth status, and mode of delivery all significantly impacted the rate of stillbirths over time.ConclusionStillbirths increased in Pakistan from 2012 to 2017. Stillbirths are observed more frequently for women residing in Punjab, Sindh, and rural areas. A major concern that is directly related to the prevalence of stillbirths in Pakistan is the lack of accessible, affordable, and high-quality maternal healthcare facilities. Older, overweight, and uneducated women are more likely to have stillbirths than women who deliver vaginally. High parity and short birth intervals also accelerated the rate of stillbirths. An effective remedy to control stillbirths is the provision of accessible and affordable healthcare services. Awareness campaigns for the health education of pregnant women should focus on raising awareness to support better pregnancy outcomes for poor women living in communities with higher education levels. The risk of stillbirth can be reduced by offering free diagnostics for early detection of birth complications in low-resource settings and referring these cases to knowledgeable gynecologists for safe delivery.

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Burning velocity of different chemicals is estimated using a model from mixed population considering inverted Kumaraswamy (IKum) distribution for component parts. Two estimation techniques maximum likelihood estimation (MLE) and Bayesian analysis are applied for estimation purposes. BEs of a mixture model are obtained using gamma, inverse beta prior, and uniform prior distribution with two loss functions. Hyperparameters are determined through the empirical Bayesian method. An extensive simulation study is also a part of the study which is used to foresee the characteristics of the presented model. Application of the IKum mixture model is presented through a real dataset. We observed from the results that Linex loss performed better than squared error loss as it resulted in lower risks. And similarly gamma prior is preferred over other priors.

Child malnutrition persists in low-resource countries such as Pakistan, indicating an urgent need for interventions and policies aimed to address this critical population health issue. The World Health Organization Global Target 2025 includes the reduction of malnourishment in the form of stunting, wasting, and low weight. This study aims to examine the prevalence of factors associated with three measures of child malnutrition, i.e., stunting, wasting, and low weight in Pakistan. This study uses a secondary data analysis design based on data from Pakistan Demographic and Health Survey (2017-18) that used a two-stage cluster sampling approach. National level data covering urban and rural areas were used for this study consisting of 4,226 children less than 5 years of age. Univariate and multivariable analyses using logistic regression models were conducted. Over 23% of the children were underweight, 8.0% suffered wasting, and 37.7% were stunted. Children with small size at birth (<45.7 cm), those who were average in size (45.7 to 60 cm) at birth were less likely to be stunted (AOR, 0.4890) and underweight (AOR, 0.538). Children with large size at birth (>60 cm) were also less likely to be stunted (AOR, 0.288) and underweight (AOR, 0.538). Children who consumed fresh milk were less likely to be classified as wasted (AOR, 0.524) than those children who did not consume fresh milk. The children in high- and middle-economic status families were less likely to be stunted, underweight, or wasted. Children of mothers who had secondary and higher education were less likely to be stunted (AOR, 0.584) and were less likely to be underweight (AOR, 0.668) than illiterate mothers’ children. Children of working mothers were less likely to be wasted compared to children of nonworking mothers (AOR, 0.287). Maternal BMI is also inversely associated with being underweight because overweight and obese mothers were less likely to have underweight children (AOR, 0.585). Our findings reflect a need to design targeted public health policies and community-based education that emphasize the mother’s education on nutrition health and provide socioeconomic resources that enable mothers to provide dietary needs that prevent malnutrition.

Keeping in view the political shifts in the wake of 9/11 incident, new social and political trends/concepts have emerged which affected the nations across the world particularly the Muslim world, wherein a wave of extremism and conservatism was seen to be set in. In consequence, Pakistan embarked upon to make reforms in the curriculum to avoid that wave. Accordingly, Musharraf government has adopted education reform under the banner of enlightened moderation and introduced curriculum to construct Pakistani nationalism in the context of liberal citizenship to curtail the issues like extremism and conservatism spread under the slogan of Islamization. This study pinpoints the overall impact of Musharraf policy changes upon curriculum and its role in the construction of liberal citizenship. This study uses secondary data in the shape of policy texts and curriculum of social studies. This study uses discourse analysis to analyse policy text and curriculum. The findings of the study have pointed out that the government has introduced modern contents such as life skills and scientific knowledge to tackle prevailing issues by removing biased and outdated contents from existing curricula. This study has recommended that effective policy measures to construct liberal citizenship should only be realized with effective implementation.