India has experienced rapid urbanisation, straining the healthcare system. The National Urban Health Mission was launched in 2013 to improve access to public healthcare, particularly among socio-economically disadvantaged urban populations. This study aimed to assess whether inequalities in maternal and newborn health (MNH) service coverage and outcomes between richer and poorer groups have improved at public and private sources across urban India in the last two decades. We used pooled data from four national cross-sectional surveys, the District Level Household Surveys from 2002 to 2008 and National Family Health Surveys from 2015 to 2021, covering 94,826 and 108,152 births in urban India, respectively. We analysed trends in coverage of antenatal, delivery, and postnatal care services and neonatal mortality by source across wealth deciles, and summarised inequalities using the slope index of inequality, concentration index, and inequality pattern index. The study found that coverage of all MNH services, and to a lesser extent neonatal survival, increased substantially between 2002-2008 and 2015-2021 in urban India. Improvements were steeper among the poorest groups. Coverage by public health facilities notably increased, and neonatal mortality rates were lower at public than private facilities, particularly among the poorest. However, the poorest decile remained well behind all other groups, reflecting bottom inequalities. Rapid improvements with reduced inequalities in MNH service coverage appear to be driven by increased access to public sector services in urban India. It remains critical for the public healthcare system to understand and address the particular needs of the poorest groups to reduce ongoing bottom MNH inequalities in urban India.

IntroductionIndia’s progress in reducing maternal and neonatal mortality since the 1990s was faster than the regional average. We systematically analysed how national health policies, services for maternal and newborn health, and socioeconomic contextual changes, drove these mortality reductions.MethodsThe study’s mixed-methods design integrated quantitative trend analyses of mortality, intervention coverage and equity since the 1990s, using the sample registration system and national surveys, with interpretive understandings from policy documents and 13 key informant interviews.ResultsIndia’s maternal mortality ratio (MMR) declined from 412 to 103 maternal deaths per 100 000 live births between 1997–1998 and 2017–2019. The neonatal mortality rate (NMR) declined from 46 to 22 per 1000 live births between 1997 and 2019. The average annual rate of mortality reduction increased over time. During this period, coverage of any antenatal care (57%–94%), quality antenatal care (37%–85%) and institutional delivery (34%–90%) increased, as did caesarean section rates among the poorest tertile (2%–9%); these coverage gains occurred primarily in the government (public) sector. The fastest rates for increasing coverage occurred during 2005–2012.The 2005–2012 National Rural Health Mission (which became the National Health Mission in 2012) catalysed bureaucratic innovations, additional resources, pro-poor commitments and accountability. These efforts occurred alongside smaller family sizes and improvements in macroeconomic growth, mobile and road networks, women’s empowerment, and nutrition. These together reduced high-risk births and improved healthcare access, particularly among the poor.ConclusionRapid reduction in NMR and MMR in India was accompanied by increased coverage of maternal and newborn health interventions. Government programmes strengthened public sector services, thereby expanding the reach of these interventions. Simultaneously, socioeconomic and demographic shifts led to fewer high-risk births. The study’s integrated methodology is relevant for generating comprehensive knowledge to advance universal health coverage.

BackgroundIndia’s progress in reducing maternal and newborn mortality since the 1990s has been exemplary across diverse contexts. This paper examines progress in two state clusters: higher mortality states (HMS) with lower per capita income and lower mortality states (LMS) with higher per capita income.MethodsWe characterised state clusters’ progress in five characteristics of a mortality transition model (mortality levels, causes, health intervention coverage/equity, fertility and socioeconomic development) and examined health policy and systems changes. We conducted quantitative trend analyses, and qualitative document review, interviews and discussions with national and state experts.ResultsBoth clusters reduced maternal and neonatal mortality by over two-thirds and half respectively during 2000–2018. Neonatal deaths declined in HMS most on days 3–27, and in LMS on days 0–2. From 2005 to 2018, HMS improved coverage of antenatal care with contents (ANCq), institutional delivery and postnatal care (PNC) by over three-fold. In LMS, ANCq, institutional delivery and PNC rose by 1.4-fold. C-sections among the poorest increased from 1.5% to 7.1% in HMS and 5.6% to 19.4% in LMS.Fewer high-risk births (to mothers <18 or 36+ years, birth interval <2 years, birth order 3+) contributed 15% and 6% to neonatal mortality decline in HMS and LMS, respectively. Socioeconomic development improved in both clusters between 2005 and 2021; HMS saw more rapid increases than LMS in women’s literacy (1.5-fold), household electricity (by 2-fold), improved sanitation (3.2-fold) and telephone access (6-fold).India’s National (Rural) Health Mission’s financial and administrative flexibility allowed states to tailor health system reforms. HMS expanded public health resources and financial schemes, while LMS further improved care at hospitals and among the poorest.ConclusionTwo state clusters in India progressed in different mortality transitions, with efforts to maximise coverage at increasingly advanced levels of healthcare, alongside socioeconomic improvements. The transition model characterises progress and guides further advances in maternal and newborn survival.

BACKGROUND:The reductions in mortality levels among children under five years are observed in most populations, including populations that were lagging the progress in the past. However, the reduction is not uniform across ages during childhood. The mortality declines within the first month have shown relatively slow progress. Early initiation of breastfeeding and discarding pre-lacteal feed protects the newborn from acquiring infection and, thereby, reduces mortality. This paper assesses the change in the prevalence of early initiation of breastfeeding and pre-lacteal feed along with their associated factors, and their association with neonatal mortality in India.METHODS:We used data from the three rounds of National Family Health Surveys conducted during 2005-06, 2015-16 and 2019-21 in India. We used bivariate and multivariate analyses to examine prevalence rates, risk factors, and relationships between breastfeeding practices, including early initiation of breastfeeding and pre-lacteal feed, and neonatal mortality.RESULTS:Early initiation of breastfeeding within one hour after birth increased rapidly from 25% in 2005-06 to 42% in 2019-21, and the pre-lacteal feeding practice declined from 57% in 2005-06 to 15% in 2019-21. Pre-lacteal feed is lower in states/districts where early breastfeeding initiation is predominant and vice versa. The role of health professionals during pregnancy and the first two days after delivery significantly improved breastfeeding practice. Further, the findings suggest that an early breastfeeding initiation is associated with lower neonatal mortality, whereas pre-lacteal feed is not harmful compared to late breastfeeding initiation.CONCLUSION:Prevalence of pre-lacteal feed reduced, and initiation of early breastfeeding increased considerably after the launch of the National Rural Health Mission in India. However, after 2015-16, early breastfeeding initiation has stagnated, and the decline in pre-lacteal feed has slowed down. The future program needs special attention to emphasize the availability and accessibility of breastfeeding advisers and observers in health facilities to help mitigate adverse neonatal outcomes.

India has the highest number of newborn deaths worldwide, with 0·5 million deaths within the first month of life annually; Nigeria, Pakistan, Ethiopia, and the Democratic Republic of the Congo together accounted for nearly half of the 2·4 million global newborn deaths in 2019.1WHONewborns: improving survival and well-being.https://www.who.int/news-room/fact-sheets/detail/newborns-reducing-mortalityDate: 2020Date accessed: June 5, 2022Google Scholar Understanding the causes of neonatal infections (eg, bacterial or viral) is crucial to achieve further reductions in neonatal mortality among lagging populations, where infections are a major causes of all neonatal deaths. In The Lancet Global Health, Melissa Arvay and colleagues address this knowledge gap meticulously and help to identify the causes of infections and case management.2Arvay ML Shang N Qazi SA et al.Infectious aetiologies of neonatal illness in south Asia classified using WHO definitions: a primary analysis of the ANISA study.Lancet Glob Health. 2022; 10: e1289-e1297Summary Full Text Full Text PDF PubMed Scopus (1) Google Scholar Arvay and colleagues did a population-based longitudinal study among young infants aged 0–59 days in Bangladesh, India, and Pakistan, aiming to describe the spectrum of infectious causes of acute neonatal illness categorised using the 2015 WHO case definitions of critical illness, clinical severe infection, and fast-breathing only. Arvay and colleagues found that the proportion of illness attributable to bacterial infection was 32·7% in the critical illness group, 15·6% in the clinical severe infection group, and 8·8% in the fast-breathing group; however, an infectious cause was not identified in 58–82% of these infants. For future reductions in neonatal mortality, it is essential to develop simple procedures that facilitate the identification of critical cases among neonates and standardised operating procedures for management, in both clinical and community settings (eg, by health workers such as accredited social health activists [ASHAs] and auxiliary nurse midwives).3Government of IndiaNational Rural Health Mission (2005–2012).https://nhm.gov.in/images/pdf/guidelines/nrhm-guidelines/mission_document.pdfDate accessed: June 1, 2022Google Scholar, 4Government of IndiaNational Health Mission.https://nhm.gov.in/index4.php?lang=1&level=0&linkid=445&lid=38Date: 2017Date accessed: June 1, 2022Google Scholar Most deliveries in India, Bangladesh, and Pakistan now occur in a health facility; however, discharge might happen earlier than recommended due to unavoidable reasons. The recent round of demographic and health surveys showed that 66% of all births in Pakistan5National Institute of Population StudiesPakistan demographic and health survey 2017–18.https://dhsprogram.com/pubs/pdf/FR354/FR354.pdfDate: 2019Date accessed: July 17, 2022Google Scholar and half of all births in Bangladesh6National Institute of Population Research and TrainingBangladesh demographic and health survey 2017–18.https://dhsprogram.com/pubs/pdf/FR344/FR344.pdfDate: 2020Date accessed: July 17, 2022Google Scholar in 2017–18 occurred in a health facility. In 2019–21,7International Institute for Population SciencesNational family health survey 5, 2019–21.http://rchiips.org/nfhs/NFHS-5Reports/NFHS-5_INDIA_REPORT.pdfDate: 2022Date accessed: June 5, 2022Google Scholar 20% of women in India who had a vaginal delivery stayed in a health facility for less than 24 hours. For caesarean section deliverys, 12% of women stayed in the health facility for less than 3 days; this includes 4% of women who stayed for less than 6 hours. These proportions were much higher in Pakistan5National Institute of Population StudiesPakistan demographic and health survey 2017–18.https://dhsprogram.com/pubs/pdf/FR354/FR354.pdfDate: 2019Date accessed: July 17, 2022Google Scholar and Bangladesh.6National Institute of Population Research and TrainingBangladesh demographic and health survey 2017–18.https://dhsprogram.com/pubs/pdf/FR344/FR344.pdfDate: 2020Date accessed: July 17, 2022Google Scholar For example, in 2017–18, 84% of women in Pakistan and 41% of women in Bangladesh who had a vaginal delivery stayed in a hospital for less than 24 h. Furthermore, 26% of women in Pakistan and 2% of women in Bangladesh who had a caesarean section delivery stayed in a health facility for less than 3 days. To explore the potential implications of the facility-to-home transition in India, we analysed age-specific mortality rates for the first week after birth from five National Family Health Survey7International Institute for Population SciencesNational family health survey 5, 2019–21.http://rchiips.org/nfhs/NFHS-5Reports/NFHS-5_INDIA_REPORT.pdfDate: 2022Date accessed: June 5, 2022Google Scholar rounds. Our analysis indicates that, in India, the age-specific mortality rates during the first week of life remained unchanged until 2005–06. The mortality rates showed notable improvement after 2005–06, when several innovations to improve maternal and newborn survival were introduced. However, a crucial point emerging from this analysis is that the mortality rate on day 3 is substantially higher than on day 2 in all the surveys, suggesting a poor transition of care from hospital to household (figure). This finding calls for special attention to the management of newborn health status when the newborn baby is moved from the health facility to the home. This attention is crucial, as the social settings (including maternal and household characteristics), are often poor among the vulnerable populations that continue to show higher neonatal mortality rates. Consequently, health system improvements might play a small role in future reductions in neonatal mortality in India. Multipronged efforts, including an effective, low-cost health system combined with a responsive programme for dealing with social determinants locally might need greater attention. Given that the causal factors of neonatal infections do not have specific symptoms, identifying such factors is difficult. By using cohort data on infants aged 0–59 months (healthy controls and those with possible serious bacterial infection) in Bangladesh, India, and Pakistan, the Arvay study examines the relevance of WHO classifications of critically ill, clinical severe infection, and isolated fast breathing. The study highlights the limitations and non-specificity of the WHO case definitions for infectious causes of illness, and advances our understanding of infection among critically ill neonates in times when neonatal mortality reduction is a global challenge. This study is a crucial step in the right direction; however, more rigorous research is required in this area. We declare no competing interests. Infectious aetiologies of neonatal illness in south Asia classified using WHO definitions: a primary analysis of the ANISA studyOur modelled results generally support the revised WHO case definitions, although a revision of the most severe case definition could be considered. Clinical criteria do not clearly differentiate between young infants with and without infectious aetiologies. Our results highlight the need for improved point-of-care diagnostics, and further study into neonatal deaths and episodes with no identified aetiology, to ensure antibiotic stewardship and targeted interventions. Full-Text PDF Open Access

Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$ per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings In 2019, health spending globally reached $8. 8 trillion (95% uncertainty interval [UI] 8.7-8.8) or $1132 (1119-1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total, $40.4 billion (0.5%, 95% UI 0.5-0.5) was development assistance for health provided to low-income and middle-income countries, which made up 24.6% (UI 24.0-25.1) of total spending in low-income countries. We estimate that $54.8 billion in development assistance for health was disbursed in 2020. Of this, $13.7 billion was targeted toward the COVID-19 health response. $12.3 billion was newly committed and $1.4 billion was repurposed from existing health projects. $3.1 billion (22.4%) of the funds focused on country-level coordination and $2.4 billion (17.9%) was for supply chain and logistics. Only $714.4 million (7.7%) of COVID-19 development assistance for health went to Latin America, despite this region reporting 34.3% of total recorded COVID-19 deaths in low-income or middle-income countries in 2020. Spending on health is expected to rise to $1519 (1448-1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.

BackgroundHalf of the world's missing female births occur in India, due to sex-selective abortion. It is unknown whether selective abortion of female fetuses has changed in recent years across different birth orders. We sought to document the trends in missing female births, particularly among second and third children, at national and state levels.MethodsWe examined birth histories from five nationally representative household surveys (National Family Health Surveys 1–4 and District Level Household Survey 2) to compute the conditional sex ratio (defined as the number of girls born per 1000 boys depending on previous birth sex) in India during 1981–2016. We estimated decadal variation in conditional sex ratio for 1987–96, 1997–2006, and 2007–16, and quantified trends in the numbers of missing female births for the states constituting >95% of India's population, as well as in 5-year intervals for each survey round. We used multivariate logistic regression to calculate the odds ratio of a second (or third) girl depending on the sex of the earlier child (or children), adjusting for education, wealth, religion, caste, and place of residence.FindingsWe assessed 2·1 million birth histories across the five surveys. Applying the conditional sex ratios from the surveys to national births, we found that 13·5 million female births were missing during the three decades of observation (1987–2016), on the basis of a natural sex ratio of 950 girls per 1000 boys. Missing female births increased from 3·5 million in 1987–96 to 5·5 million in 2007–16. Contrasting the conditional sex ratio from the first decade of observation (1987–96) to the last (2007–16) showed worsening for the whole of India and almost all states, among both birth orders. Punjab, Haryana, Gujarat, and Rajasthan had the most skewed sex ratios, comprising nearly a third of the national totals of missing second-born and third-born females at birth. From about 1986, the conditional sex ratio for second-order or third-order births after an earlier daughter or daughters diverged notably from that after an earlier son or sons. From 1981 to 2016, the sex ratio for second-born children after an earlier daughter decreased from 930 (99% CI 869–990) to 885 (859–912), and that for third-born children after two earlier daughters decreased from 968 (866–1069) to 788 (746–830). The probability of missing girls was mostly determined by earlier daughters, even after considering wealth quintile and education levels. The conditional sex ratio among the richest and most educated mothers was most distorted compared with lower wealth and education groups, and generally decreased with time, until a modest improvement in 2007–16.InterpretationIn contrast to the substantial improvements in female child mortality in India, missing female births, driven by selective abortion of female fetuses, continues to increase across the states. Inclusion of a question on sex composition of births in the forthcoming census would provide local information on sex-selective abortion in each village and urban area of the country.FundingNone.TranslationFor the Hindi translation of the abstract see Supplementary Materials section.

Purpose This study aims to examine sociodemographic characteristics, levels and patterns of mortality experiences amongst Indian prisoners over the past two decades (1998–2018). Design/methodology/approach This study used prison statistics in India to analyze occupancy rate, percentage distribution, annual/decadal change, male–to–female ratios, prison mortality rate and causes of natural/unnatural deaths. Findings During 1998–2018, prisons in India grew by 18% and prisoners by 69%, leading to overcrowded jails. Males outnumbered female prisoners. Seventy percent of prisoners had an educational attainment level lower than 10th grade. In 2018, over 14 per 1,000 prisoners suffered from a mental illness and 384 per 100,000 died. Unnatural deaths accounted for 8%–11% of all prisoner deaths; 84% were by suicide. Illness accounted for 95% of all natural deaths in 2018; one–quarter was due to heart diseases. Research limitations/implications The study did not establish an association between sociodemographic characteristics with mental illness and mortality due to the non-availability of data. Social implications The pattern of a deteriorating living environment, rise in mental illnesses and mortality among Indian prisoners calls for immediate action from the authorities to protect them. Almost all unnatural deaths were by suicide (mostly by hanging). This detailed study would help authorities to take corrective measures for prisoner safety and well-being. There is also a need to develop a scientific database for this population. Originality/value To the best of the authors’ knowledge, this is the first study to examine morbidity and mortality experiences of the prisoner population using national statistics.

Globally, countries have followed demographic transition theory and transitioned from high levels of fertility and mortality to lower levels. These changes have resulted in the improved health and well-being of people in the form of extended longevity and considerable improvements in survival at all ages, specifically among children and through lower fertility, which empowers women. India, the second most populous country after China, covers 2.4% of the global surface area and holds 18% of the world’s population. The United Nations 2019 medium variant population estimates revealed that India would surpass China in the year 2030 and would maintain the first rank after 2030. The population of India would peak at 1.65 billion in 2061 and would begin to decline thereafter and reach 1.44 billion in the year 2100. Thus, India’s experience will pose significant challenges for the global community, which has expressed its concern about India’s rising population size and persistent higher fertility and mortality levels. India is a country of wide socioeconomic and demographic diversity across its states. The four large states of Uttar Pradesh, Bihar, Madhya Pradesh, and Rajasthan accounted for 37% of the country’s total population in 2011 and continue to exhibit above replacement fertility (that is, the total fertility rate, TFR, of greater than 2.1 children per woman) and higher mortality levels and thus have great potential for future population growth. For example, nationally, the life expectancy at birth in India is below 70 years (lagging by more than 3 years when compared to the world average), but the states of Uttar Pradesh and Rajasthan have an average life expectancy of around 65–66 years. The spatial distribution of India’s population would have a more significant influence on its future political and economic scenario. The population growth rate in Kerala may turn negative around 2036, in Andhra Pradesh (including the newly created state of Telangana) around 2041, and in Karnataka and Tamil Nadu around 2046. Conversely, Uttar Pradesh, Bihar, Madhya Pradesh, and Rajasthan would have 764 million people in 2061 (45% of the national total) by the time India’s population reaches around 1.65 billion. Nationally, the total fertility rate declined from about 6.5 in early 1960 to 2.3 children per woman in 2016, a result of the massive efforts to improve comprehensive maternal and child health programs and nationwide implementation of the national health mission with a greater focus on social determinants of health. However, childhood mortality rates continue to be unacceptably high in Uttar Pradesh, Bihar, Rajasthan, and Madhya Pradesh (for every 1,000 live births, 43 to 55 children die in these states before celebrating their 5th birthday). Intertwined programmatic interventions that focus on female education and child survival are essential to yield desired fertility and mortality in several states that have experienced higher levels. These changes would be crucial for India to stabilize its population before reaching 1.65 billion. India’s demographic journey through the path of the classical demographic transition suggests that India is very close to achieving replacement fertility.

CONTEXT Hygienic use of absorbent products during menstruation is a challenge for young women in India, especially among the underprivileged, who lack knowledge and access to resources. Reuse of menstrual absorbents can be unhygienic and result in adverse health and other outcomes. METHODS Data from the 2015-2016 National Family Health Survey-4 for 233,606 menstruating women aged 15-24 were used to examine levels and correlates of exclusive use of disposable absorbents during menstruation. Bivariate and logistic regression analyses were conducted to identify disparities in exclusive use by such characteristics as caste, mass media exposure and interaction with health workers. RESULTS Exclusive use of disposable absorbents was low among young women overall (37%), and varied substantially by caste and other characteristics. Compared with women from general castes, those from scheduled castes, scheduled tribes and other backward classes had reduced odds of exclusive disposable absorbent use (odds ratios, 0.8-0.9). Disposable absorbent use was negatively associated with lower levels of education and household wealth, and rural residence. Compared with women who reported daily media exposure, those exposed less frequently had reduced odds of disposable absorbent use (0.7-0.9). Among those who recently met with a health worker, odds of use were lower if menstrual hygiene had not been discussed (0.9). CONCLUSIONS Promoting awareness of proper menstrual hygiene-through education, media campaigns and discussion with reproductive health workers-and targeted interventions to disseminate and subsidize the purchase of disposable sanitary napkins should be pursued to address health disparities.

Abstract In India, non-communicable diseases (NCDs) accounted for nearly 62% of all deaths in 2016. Four NCDs – high blood pressure, diabetes, asthma and heart disease – together accounted for over 34% of these deaths. Using data from two rounds of the India Human Development Surveys (IHDSs), levels and changes in the prevalence rates of the four NCDs (based on diagnosed cases) among adults aged 15–69 years in India between 2004–05 and 2011–12 were examined by socioeconomic and demographic factors and for five broad occupation categories. The socioeconomic and demographic risk factors for each of these NCDs were determined using multiple linear logistic regression analysis of pooled data from two rounds of the IHDS. The results showed that while urban residence, age, female sex and education were associated with higher odds of high blood pressure, diabetes and heart disease, household economic status was associated with higher odds for all four NCDs. Furthermore, increased higher odds of high blood pressure, diabetes and heart disease were found for the legislator/senior official/professional occupation group compared with non-workers. Skilled agricultural/elementary workers had lower odds of high blood pressure, diabetes, asthma and heart disease. Craft/machine-related trade workers had higher odds of high blood pressure and diabetes, and reduced odds of asthma and heart disease. Compared with non-workers, the odds ratios for asthma were lower for all other occupational categories. During the two study decades, the Government of India implemented several programmes designed to improve the health and well-being of its people. However, more focused attention on the adult population is needed, and special attention should be paid to the issue of the occupational health of the working population through the strict implementation of work place safety protocols and the removal of potential health hazards.

The present chapter reflects on health care availability, utilization and pattern of morbidity in the slum. The first part deals with the general profile of the public health, proximate causes of the ill health, which provides insight about the general profile of the infrastructure and basic amenities position vis a vis slum. The second part is related the health care utilization in slums namely services of the medical institutions, charges of the private medical institutions and clinics, source of treatment, reason for choosing the source of treatment, satisfaction with the treatment, user charge. This section also includes access to the health care services in the slums and the mode of transport used for the utilization of the health care services. The third aspect of the study is related to the pattern of morbidity in slums includes illness in the last month, ailment on the survey date, hospitalisation in one year, average morbidity and hospitalisation rate in one year of three slums, type of ailment, ailment of the head of the household, ailment of the family members, no of days of inactivity and lastly analysis of the common problems and health status of slum dwellers, treatment sought and the proximate reasons for the ailments in slums been done.

Importance:Understanding causes and correlates of health loss among children and adolescents can identify areas of success, stagnation, and emerging threats and thereby facilitate effective improvement strategies. Objective:To estimate mortality and morbidity in children and adolescents from 1990 to 2017 by age and sex in 195 countries and territories. Design, Setting, and Participants:This study examined levels, trends, and spatiotemporal patterns of cause-specific mortality and nonfatal health outcomes using standardized approaches to data processing and statistical analysis. It also describes epidemiologic transitions by evaluating historical associations between disease indicators and the Socio-Demographic Index (SDI), a composite indicator of income, educational attainment, and fertility. Data collected from 1990 to 2017 on children and adolescents from birth through 19 years of age in 195 countries and territories were assessed. Data analysis occurred from January 2018 to August 2018. Exposures:Being under the age of 20 years between 1990 and 2017. Main Outcomes and Measures:Death and disability. All-cause and cause-specific deaths, disability-adjusted life years, years of life lost, and years of life lived with disability. Results:Child and adolescent deaths decreased 51.7% from 13.77 million (95% uncertainty interval [UI], 13.60-13.93 million) in 1990 to 6.64 million (95% UI, 6.44-6.87 million) in 2017, but in 2017, aggregate disability increased 4.7% to a total of 145 million (95% UI, 107-190 million) years lived with disability globally. Progress was uneven, and inequity increased, with low-SDI and low-middle-SDI locations experiencing 82.2% (95% UI, 81.6%-82.9%) of deaths, up from 70.9% (95% UI, 70.4%-71.4%) in 1990. The leading disaggregated causes of disability-adjusted life years in 2017 in the low-SDI quintile were neonatal disorders, lower respiratory infections, diarrhea, malaria, and congenital birth defects, whereas neonatal disorders, congenital birth defects, headache, dermatitis, and anxiety were highest-ranked in the high-SDI quintile. Conclusions and Relevance:Mortality reductions over this 27-year period mean that children are more likely than ever to reach their 20th birthdays. The concomitant expansion of nonfatal health loss and epidemiological transition in children and adolescents, especially in low-SDI and middle-SDI countries, has the potential to increase already overburdened health systems, will affect the human capital potential of societies, and may influence the trajectory of socioeconomic development. Continued monitoring of child and adolescent health loss is crucial to sustain the progress of the past 27 years.

Background India had the largest number of under-5 deaths of all countries in 2015, with substantial subnational disparities. We estimated national and subnational all-cause and cause-specific mortality among children younger than 5 years annually in 2000-15 in India to understand progress made and to consider implications for achieving the Sustainable Development Goal (SDG) child survival targets. Methods We used a multicause model to estimate cause-specific mortality proportions in neonates and children aged 1-59 months at the state level, with causes of death grouped into pneumonia, diarrhoea, meningitis, injury, measles, congenital abnormalities, preterm birth complications, intrapartum-related events, and other causes. AIDS and malaria were estimated separately. The model was based on verbal autopsy studies representing more than 100 000 neonatal deaths globally and 16 962 deaths among children aged 1-59 months at the subnational level in India. By applying these proportions to all-cause deaths by state, we estimated cause-specific numbers of deaths and mortality rates at the state, regional, and national levels. Findings In 2015, there were 25.121 million livebirths in India and 1.201 million under-5 deaths (under-5 mortality rate 47.81 per 1000 livebirths). 0.696 million (57.9%) of these deaths occurred in neonates. There were disparities in child mortality across states (from 9.7 deaths [Goa] to 73.1 deaths [Assam] per 1000 livebirths) and regions (from 29.7 deaths [the south] to 63.8 deaths [the northeast] per 1000 livebirths). Overall, the leading causes of under-5 deaths were preterm birth complications (0.330 million [95% uncertainty range 0.279-0.367]; 27.5% of under-5 deaths), pneumonia (0.191 million [0 -168-0.219]; 15.9%), and intrapartum-related events (0.139 million [0.116-0-165]; 11.6%), with cause-of-death distributions varying across states and regions. In states with very high under-5 mortality, infectious-disease-related causes (pneumonia and diarrhoea) were among the three leading causes, whereas the three leading causes were all non-communicable in states with very low mortality. Most states had a slower decline in neonatal mortality than in mortality among children aged 1-59 months. Ten major states must accelerate progress to achieve the SDG under-5 mortality target, while 17 are not on track to meet the neonatal mortality target. Interpretation Efforts to reduce vaccine-preventable deaths and to reduce geographical disparities should continue to maintain progress achieved in 2000-15. Enhanced policies and programmes are needed to accelerate mortality reduction in high-burden states and among neonates to achieve the SDG child survival targets in India by 2030. Copyright (C) The Author(s). Published by Elsevier Ltd.

Background India accounts for a disproportionate burden of global childhood illnesses. To inform policies and measure progress towards achieving child health targets, we estimated the annual national and state-specific childhood mortality and morbidity attributable to Streptococcus pneumoniae and Haemophilus influenzae type b (Hib) between 2000 and 2015. Methods In this modelling study, we used vaccine clinical trial data to estimate the proportion of pneumonia deaths attributable to pneumococcus and Hib. The proportion of meningitis deaths attributable to each pathogen was derived from pathogen-specific meningitis case fatality and bacterial meningitis case data from surveillance studies. We applied these proportions to modelled state-specific pneumonia and meningitis deaths from 2000 to 2015 prepared by the WHO Maternal and Child Epidemiology Estimation collaboration (WHO/MCEE) on the basis of verbal autopsy studies from India. The burden of clinical and severe pneumonia cases attributable to pneumococcus and Hib was ascertained with vaccine clinical trial data and state-specific all-cause pneumonia case estimates prepared by WHO/MCEE by use of risk factor prevalence data from India. Pathogen-specific meningitis cases were derived from state-level modelled pathogen-specific meningitis deaths and state-level meningitis case fatality estimates. Pneumococcal and Hib morbidity due to non-pneumonia, non-meningitis (NPNM) invasive syndromes were derived by applying the ratio of pathogen-specific NPNM cases to pathogen-specific meningitis cases to the state-level pathogen-specific meningitis cases. Mortality due to pathogen-specific NPNM was calculated with the ratio of pneumococcal and Hib meningitis case fatality to pneumococcal and Hib meningitis NPNM case fatality. Census data from India provided the population at risk. Findings Between 2000 and 2015, estimates of pneumococcal deaths in Indian children aged 1-59 months fell from 166000 (uncertainty range [UR] 110000-198000) to 68700 (44 600-86000), while Hib deaths fell from 82600 (52300-112000) to 15600 (9800-21500), representing a 58% (UR 22-78) decline in pneumococcal deaths and an 81% (59-91) decline in Hib deaths. In 2015, national mortality rates in children aged 1-59 months were 56 (UR 37-71) per 100000 for pneumococcal infection and 13 (UR 8-18) per 100000 for Hib. Uttar Pradesh (18900 [UR 12300-23600]) and Bihar (8600 [5600-10700]) had the highest numbers of pneumococcal deaths in 2015. Uttar Pradesh (9300 [UR 5900-12700]) and Odisha (1100 [700-1500]) had the highest numbers of Hib deaths in 2015. Less conservative assumptions related to the proportion of pneumonia deaths attributable to pneumococcus indicate that as many as 118000 (UR 69000-140000) total pneumococcal deaths could have occurred in 2015 in India. Interpretation Pneumococcal and Hib mortality have declined in children aged 1-59 months in India since 2000, even before nationwide implementation of conjugate vaccines. Introduction of the Hib vaccine in several states corresponded with a more rapid reduction in morbidity and mortality associated with Hib infection. Rapid scale-up and widespread use of the pneumococcal conjugate vaccine and sustained use of the Hib vaccine could help accelerate achievement of child survival targets in India. Copyright (C) 2019. The Author(s). Published by Elsevier Ltd.

Background Comprehensive and comparable estimates of health spending in each country are a key input for health policy and planning, and are necessary to support the achievement of national and international health goals. Previous studies have tracked past and projected future health spending until 2040 and shown that, with economic development, countries tend to spend more on health per capita, with a decreasing share of spending from development assistance and out-of-pocket sources. We aimed to characterise the past, present, and predicted future of global health spending, with an emphasis on equity in spending across countries. Methods We estimated domestic health spending for 195 countries and territories from 1995 to 2016, split into three categories-government, out-of-pocket, and prepaid private health spending-and estimated development assistance for health (DAH) from 1990 to 2018. We estimated future scenarios of health spending using an ensemble of linear mixed-effects models with time series specifications to project domestic health spending from 2017 through 2050 and DAH from 2019 through 2050. Data were extracted from a broad set of sources tracking health spending and revenue, and were standardised and converted to inflation-adjusted 2018 US dollars. Incomplete or low-quality data were modelled and uncertainty was estimated, leading to a complete data series of total, government, prepaid private, and out-of-pocket health spending, and DAH. Estimates are reported in 2018 US dollars, 2018 purchasing-power parity-adjusted dollars, and as a percentage of gross domestic product. We used demographic decomposition methods to assess a set of factors associated with changes in government health spending between 1995 and 2016 and to examine evidence to support the theory of the health financing transition. We projected two alternative future scenarios based on higher government health spending to assess the potential ability of governments to generate more resources for health. Findings Between 1995 and 2016, health spending grew at a rate of 4.00% (95% uncertainty interval 3.89-4.12) annually, although it grew slower in per capita terms (2.72% [2.61-2.84]) and increased by less than $ 1 per capita over this period in 22 of 195 countries. The highest annual growth rates in per capita health spending were observed in upper-middle-income countries (5.55% [5.18-5.95]), mainly due to growth in government health spending, and in lower-middle-income countries (3.71% [3.10-4.34]), mainly from DAH. Health spending globally reached $ 8.0 trillion (7.8-8.1) in 2016 (comprising 8.6% [8.4-8.7] of the global economy and $ 10.3 trillion [10.1-10.6] in purchasing-power parity-adjusted dollars), with a per capita spending of US$ 5252 (5184-5319) in high-income countries, $ 491 (461-524) in upper-middle-income countries, $ 81 (74-89) in lower-middle-income countries, and $ 40 (38-43) in low-income countries. In 2016, 0.4% (0.3-0.4) of health spending globally was in low-income countries, despite these countries comprising 10.0% of the global population. In 2018, the largest proportion of DAH targeted HIV/AIDS ($ 9.5 billion, 24.3% of total DAH), although spending on other infectious diseases (excluding tuberculosis and malaria) grew fastest from 2010 to 2018 (6.27% per year). The leading sources of DAH were the USA and private philanthropy (excluding corporate donations and the Bill & Melinda Gates Foundation). For the first time, we included estimates of China's contribution to DAH ($ 644.7 million in 2018). Globally, health spending is projected to increase to $ 15.0 trillion (14.0-16.0) by 2050 (reaching 9.4% [7.6-11.3] of the global economy and $ 21.3 trillion [19.8-23.1] in purchasing-power parity-adjusted dollars), but at a lower growth rate of 1.84% (1.68-2.02) annually, and with continuing disparities in spending between countries. In 2050, we estimate that 0.6% (0.6-0.7) of health spending will occur in currently low-income countries, despite these countries comprising an estimated 15.7% of the global population by 2050. The ratio between per capita health spending in high-income and low-income countries was 130.2 (122.9-136.9) in 2016 and is projected to remain at similar levels in 2050 (125.9 [113.7-138.1]). The decomposition analysis identified governments' increased prioritisation of the health sector and economic development as the strongest factors associated with increases in government health spending globally. Future government health spending scenarios suggest that, with greater prioritisation of the health sector and increased government spending, health spending per capita could more than double, with greater impacts in countries that currently have the lowest levels of government health spending. Interpretation Financing for global health has increased steadily over the past two decades and is projected to continue increasing in the future, although at a slower pace of growth and with persistent disparities in per-capita health spending between countries. Out-of-pocket spending is projected to remain substantial outside of high-income countries. Many low-income countries are expected to remain dependent on development assistance, although with greater government spending, larger investments in health are feasible. In the absence of sustained new investments in health, increasing efficiency in health spending is essential to meet global health targets.

Background Comparable estimates of health spending are crucial for the assessment of health systems and to optimally deploy health resources. The methods used to track health spending continue to evolve, but little is known about the distribution of spending across diseases. We developed improved estimates of health spending by source, including development assistance for health, and, for the first time, estimated HIV/AIDS spending on prevention and treatment and by source of funding, for 188 countries. Methods We collected published data on domestic health spending, from 1995 to 2015, from a diverse set of international agencies. We tracked development assistance for health from 1990 to 2017. We also extracted 5385 datapoints about HIV/AIDS spending, between 2000 and 2015, from online databases, country reports, and proposals submitted to multilateral organisations. We used spatiotemporal Gaussian process regression to generate complete and comparable estimates for health and HIV/AIDS spending. We report most estimates in 2017 purchasing-power parity-adjusted dollars and adjust all estimates for the effect of inflation. Findings Between 1995 and 2015, global health spending per capita grew at an annualised rate of 3.1% (95% uncertainty interval [UI] 3.1 to 3.2), with growth being largest in upper-middle-income countries (5.4% per capita [UI 5.3-5.5]) and lower-middle-income countries (4.2% per capita [4.2-4.3]). In 2015, $9.7 trillion (9.7 trillion to 9.8 trillion) was spent on health worldwide. High-income countries spent $6.5 trillion (6.4 trillion to 6.5 trillion) or 66.3% (66.0 to 66.5) of the total in 2015, whereas low-income countries spent $70.3 billion (69.3 billion to 71.3 billion) or 0.7% (0.7 to 0.7). Between 1990 and 2017, development assistance for health increased by 394.7% ($29.9 billion), with an estimated $37.4 billion of development assistance being disbursed for health in 2017, of which $9.1 billion (24.2%) targeted HIV/AIDS. Between 2000 and 2015, $562.6 billion (531.1 billion to 621.9 billion) was spent on HIV/AIDS worldwide. Governments financed 57.6% (52.0 to 60.8) of that total. Global HIV/AIDS spending peaked at 49.7 billion (46.2-54.7) in 2013, decreasing to $48.9 billion (45.2 billion to 54.2 billion) in 2015. That year, low-income and lower-middle-income countries represented 74.6% of all HIV/AIDS disability-adjusted life-years, but just 36.6% (34.4 to 38.7) of total HIV/AIDS spending. In 2015, $9.3 billion (8.5 billion to 10.4 billion) or 19.0% (17.6 to 20.6) of HIV/AIDS financing was spent on prevention, and $27.3 billion (24.5 billion to 31.1 billion) or 55.8% (53.3 to 57.9) was dedicated to care and treatment. Interpretation From 1995 to 2015, total health spending increased worldwide, with the fastest per capita growth in middle-income countries. While these national disparities are relatively well known, low-income countries spent less per person on health and HIV/AIDS than did high-income and middle-income countries. Furthermore, declines in development assistance for health continue, including for HIV/AIDS. Additional cuts to development assistance could hasten this decline, and risk slowing progress towards global and national goals. Copyright (c) 2018 The Author(s). Published by Elsevier Ltd.

Background Alcohol use is a leading risk factor for death and disability, but its overall association with health remains complex given the possible protective effects of moderate alcohol consumption on some conditions. With our comprehensive approach to health accounting within the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we generated improved estimates of alcohol use and alcohol-attributable deaths and disability-adjusted life-years (DALYs) for 195 locations from 1990 to 2016, for both sexes and for 5-year age groups between the ages of 15 years and 95 years and older. Methods Using 694 data sources of individual and population-level alcohol consumption, along with 592 prospective and retrospective studies on the risk of alcohol use, we produced estimates of the prevalence of current drinking, abstention, the distribution of alcohol consumption among current drinkers in standard drinks daily (defined as 10 g of pure ethyl alcohol), and alcohol-attributable deaths and DALYs. We made several methodological improvements compared with previous estimates: first, we adjusted alcohol sales estimates to take into account tourist and unrecorded consumption; second, we did a new meta-analysis of relative risks for 23 health outcomes associated with alcohol use; and third, we developed a new method to quantify the level of alcohol consumption that minimises the overall risk to individual health. Findings Globally, alcohol use was the seventh leading risk factor for both deaths and DALYs in 2016, accounting for 2.2% (95% uncertainty interval [UI] 1.5-3.0) of age-standardised female deaths and 6.8% (5.8-8.0) of age-standardised male deaths. Among the population aged 15-49 years, alcohol use was the leading risk factor globally in 2016, with 3.8% (95% UI 3.2-4-3) of female deaths and 12.2% (10.8-13-6) of male deaths attributable to alcohol use. For the population aged 15-49 years, female attributable DALYs were 2.3% (95% UI 2.0-2.6) and male attributable DALYs were 8.9% (7.8-9.9). The three leading causes of attributable deaths in this age group were tuberculosis (1.4% [95% UI 1. 0-1. 7] of total deaths), road injuries (1.2% [0.7-1.9]), and self-harm (1.1% [0.6-1.5]). For populations aged 50 years and older, cancers accounted for a large proportion of total alcohol-attributable deaths in 2016, constituting 27.1% (95% UI 21.2-33.3) of total alcohol-attributable female deaths and 18.9% (15.3-22.6) of male deaths. The level of alcohol consumption that minimised harm across health outcomes was zero (95% UI 0.0-0.8) standard drinks per week. Interpretation Alcohol use is a leading risk factor for global disease burden and causes substantial health loss. We found that the risk of all-cause mortality, and of cancers specifically, rises with increasing levels of consumption, and the level of consumption that minimises health loss is zero. These results suggest that alcohol control policies might need to be revised worldwide, refocusing on efforts to lower overall population-level consumption.

Background Achieving universal health coverage (UHC) requires health financing systems that provide prepaid pooled resources for key health services without placing undue financial stress on households. Understanding current and future trajectories of health financing is vital for progress towards UHC. We used historical health financing data for 188 countries from 1995 to 2015 to estimate future scenarios of health spending and pooled health spending through to 2040. Methods We extracted historical data on gross domestic product (GDP) and health spending for 188 countries from 1995 to 2015, and projected annual GDP, development assistance for health, and government, out-of-pocket, and prepaid private health spending from 2015 through to 2040 as a reference scenario. These estimates were generated using an ensemble of models that varied key demographic and socioeconomic determinants. We generated better and worse alternative future scenarios based on the global distribution of historic health spending growth rates. Last, we used stochastic frontier analysis to investigate the association between pooled health resources and UHC index, a measure of a country's UHC service coverage. Finally, we estimated future UHC performance and the number of people covered under the three future scenarios. Findings In the reference scenario, global health spending was projected to increase from US$10 trillion (95% uncertainty interval 10 trillion to 10 trillion) in 2015 to $20 trillion (18 trillion to 22 trillion) in 2040. Per capita health spending was projected to increase fastest in upper-middle-income countries, at 4.2% (3.4-5.1) per year, followed by lower-middle-income countries (4.0%, 3.6-4.5) and low-income countries (2.2%, 1.7-2.8). Despite global growth, per capita health spending was projected to range from only $40 (24-65) to $413 (263-668) in 2040 in low-income countries, and from $140 (90-200) to $1699 (711-3423) in lower-middle-income countries. Globally, the share of health spending covered by pooled resources would range widely, from 19.8% (10.3-38.6) in Nigeria to 97.9% (96.4-98.5) in Seychelles. Historical performance on the UHC index was significantly associated with pooled resources per capita. Across the alternative scenarios, we estimate UHC reaching between 5.1 billion (4.9 billion to 5.3 billion) and 5.6 billion (5.3 billion to 5.8 billion) lives in 2030. Interpretation We chart future scenarios for health spending and its relationship with UHC. Ensuring that all countries have sustainable pooled health resources is crucial to the achievement of UHC. Copyright (c) 2018 The Author(s). Published by Elsevier Ltd.