Factors Associated with Postpartum Care during the Fourth Stage of Labor in Nepal: A Hospital-based Cross-sectional Study

Postnatal care is an important part of maternal and neonatal care, and life-threatening complications can occur during the postpartum period. Empirical information on the level of postpartum care services is generally scarce in Nepal. Key elements of postpartum care during the fourth stage of labor include providing proper nutrition, promoting breastfeeding, and helping the mother manage any physical discomforts or challenges that may arise. This study investigated the level of postpartum care services delivered during the fourth stage of labor in a tertiary-level hospital in the Chitwan district of Nepal. A descriptive cross-sectional hospital-based study was conducted among 148 women admitted for vaginal delivery. A set of structured observation checklists was developed and finalized based on the WHO Recommended Interventions for Improving Maternal and Newborn Health: Integrated Management of Pregnancy and Childbirth. The structured observation checklist had twenty-two items, including twelve critical steps. A good level of care was valid with a score of ≥ 90% based on total items, including all twelve critical steps of care, and a poor level of care was valid with a score \u3c90%. The purpose of the study was explained to and written informed consent was obtained from all respondents. Ethical approval was received from the Institutional Review Committee of Chitwan Medical College. One third (33.8%) of the women received a good level of postpartum care services. Women’s residence (p = .021), number of pregnancies (p =.002), and number of antenatal visits (p =.029) were significantly associated with the level of postpartum care during the fourth stage of labor. Going forward, it will be important for Nepal to enhance the capacity of clinicians or nurses to provide postpartum care as per WHO guidelines

Postpartum Care Services during the Fourth Stage of Labour in Bharatpur Hospital of Nepal

Background: Postnatal care is an important part of maternal care, as serious and life-threatening complications can occur in the postpartum period. So, this study was conducted to assess the level of postpartum care services during the fourth stage of labour in the maternity ward of Bharatpur hospital in the Chitwan district of Nepal. Methods: Cross-sectional hospital-based study was done among women admitted in the maternity ward for vaginal delivery in Bhartapur hospital in Chitwan. Total 218 sample size derived by using the formula; n= N/1+N (e²). A set of data collection tool was developed, pretested and finalized. Part-1 of the tool was related to socio-demographic features of respondents, Part-2 and 3 of the tool was used as a checklist to assess institutional characteristics and level of postpartum care services respectively. The structured checklist had twenty-two items including twelve critical steps. The purpose of the study explained to the respondents; verbal informed consent obtained from respondents and ethical approval from the Institutional review committee of Chitwan Medical College. Results: The significant association observed between postpartum care during the fourth stage of labour and residence of mothers (p=0.021). Conclusions: Postpartum care in Bharatpur hospital is poor and there is an urgent need to develop plans and programs to enhance the capacity of staffs and health institutions to provide postpartum care according to the WHO recommendation guideline.  

Child Trafficking and Associated Factors in Earthquake Affected Area of Nepal

Background: Recruitment, transportation, transfers, harboring, and/or receipt kidnapping of under 18 yrs child for the purpose of slavery, forced labor and exploitation is Child Trafficking. To assess the knowledge about child trafficking and factors associated with child trafficking in Gorkha district of Nepal Methods: Cross sectional study conducted to determine the knowledge and factors related to child trafficking in Gorkha district. Two urban municipalities selected purposively and other three rural municipalities were randomly selected.  Out of 160,772 households, total 300 households for survey was calculated by using Yamane formula (n) = N/ (1+Ne2). Wards of the municipalities were Primary Sampling Unit. Based on Population Proportionate Sampling technique; required number of households of each Wards was identified.  In Wards, households for survey were selected by using simple random method.  Head of the selected household were the respondent for household survey. Ten Key Informant Interviews were done with policemen, teachers, social workers, community leaders, stakeholders and six Focus Group Discussions were done with Youths (15-25 yrs), Parents and Social worker/teacher/community leader groups. Results: Remarkable proportions of respondents have correct knowledge about the child trafficking. Near relatives, unknown person, pears group, parents/family members and neighbor were common traffickers. During and after disaster is the most vulnerable time/event for child trafficking. False marriage, assuring lucrative job, asking for adoption and proposing good education were tricks of traffickers for child trafficking.  Homeless children, children travelling without parents, socially isolated children, children travelling at night, unprotected girl child like orphan, separated from family or without parent are most vulnerable for child Trafficking. Conclusions: Family, social groups, government officials and stakeholders should jointly initiate for anti child trafficking movement. School teacher and management committee should also take initiation to make fully aware to school going children about different dimension/aspect of Child Right and Child Trafficking

Palladium-based ferroelectrics and multiferroics : theory and experiment

Palladium normally does not easily substitute for Ti or Zr in perovskite oxides. Moreover, Pd is not normally magnetic (but becomes ferromagnetic under applied uniaxial stress or electric fields). Despite these two great obstacles, we have succeeded in fabricating lead zirconate titanate with 30% Pd substitution. For 20:80 Zr:Ti the ceramics are generally single-phase perovskite (>99%), but sometimes exhibit 1% PbPdO2, which is magnetic below T=90K. The resulting material is multiferroic (ferroelectric-ferromagnet) at room temperature. The processing is slightly unusual (>8 hrs in high-energy ball-milling in Zr balls), and the density functional theory provided shows that it occurs because of Pd+4 in the oversized Pb+2 site; if all Pd+4 were to go into the Ti+4 perovskite B-site, no magnetism would result.PostprintPeer reviewe

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Estimating permanent income and wealth of the US farm households

Farm households are unique in the way they derive income when compared to nonfarm households. Farm operators and spouses have dual income sources, from farm and off-farm activities. Further, farm households on an average possess higher wealth than nonfarm households. This article estimates permanent income for the US farm households using data from a large national farm level survey. The estimated income is then used to identify the determinants of wealth accumulation by the US farm households. Results confirm that permanent income is closely related to age of the operator, education, occupation, farm size, location and number of earners in the household. Along with age, permanent income is a significant determinant of household wealth. It was also found that the wealth-income curve is nonlinear, upward sloping, and convex. Hausman's specification test indicates that variations in farm household wealth is better explained by estimated permanent income than observed total household income. Off-farm income cannot be treated as residual or transitory income.

Estimating permanent income and wealth of the us farm households

Farm households are unique in the way they derive income when compared to nonfarm households. Farm operators and spouses have dual income sources, from farm and off-farm activities. Further, farm households on an average possess higher wealth than nonfarm households. This article estimates permanent income for the US farm households using data from a large national farm level survey. The estimated income is then used to identify the determinants of wealth accumulation by the US farm households. Results confirm that permanent income is closely related to age of the operator, education, occupation, farm size, location and number of earners in the household. Along with age, permanent income is a significant determinant of household wealth. It was also found that the wealth-income curve is nonlinear, upward sloping, and convex. Hausman\u27s specification test indicates that variations in farm household wealth is better explained by estimated permanent income than observed total household income. Off-farm income cannot be treated as residual or transitory income. © 2011 Taylor & Francis