Lukasz Aleksandrowicz

Suicide mortality in India: a nationally representative survey

BACKGROUND WHO estimates that about 170,000 deaths by suicide occur in India every year, but few epidemiological studies of suicide have been done in the country. We aimed to quantify suicide mortality in India in 2010. METHODS The Registrar General of India implemented a nationally representative mortality survey to determine the cause of deaths occurring between 2001 and 2003 in 1·1 million homes in 6671 small areas chosen randomly from all parts of India. As part of this survey, fieldworkers obtained information about cause of death and risk factors for suicide from close associates or relatives of the deceased individual. Two of 140 trained physicians were randomly allocated (stratified only by their ability to read the local language in which each survey was done) to independently and anonymously assign a cause to each death on the basis of electronic field reports. We then applied the age-specific and sex-specific proportion of suicide deaths in this survey to the 2010 UN estimates of absolute numbers of deaths in India to estimate the number of suicide deaths in India in 2010. FINDINGS About 3% of the surveyed deaths (2684 of 95,335) in individuals aged 15 years or older were due to suicide, corresponding to about 187,000 suicide deaths in India in 2010 at these ages (115,000 men and 72,000 women; age-standardised rates per 100,000 people aged 15 years or older of 26·3 for men and 17·5 for women). For suicide deaths at ages 15 years or older, 40% of suicide deaths in men (45,100 of 114,800) and 56% of suicide deaths in women (40,500 of 72,100) occurred at ages 15-29 years. A 15-year-old individual in India had a cumulative risk of about 1·3% of dying before the age of 80 years by suicide; men had a higher risk (1·7%) than did women (1·0%), with especially high risks in south India (3·5% in men and 1·8% in women). About half of suicide deaths were due to poisoning (mainly ingestions of pesticides). INTERPRETATION Suicide death rates in India are among the highest in the world. A large proportion of adult suicide deaths occur between the ages of 15 years and 29 years, especially in women. Public health interventions such as restrictions in access to pesticides might prevent many suicide deaths in India. FUNDING US National Institutes of Health.

Trends in selective abortions of girls in India: analysis of nationally representative birth histories from 1990 to 2005 and census data from 1991 to 2011

BACKGROUND Indias 2011 census revealed a growing imbalance between the numbers of girls and boys aged 0-6 years, which we postulate is due to increased prenatal sex determination with subsequent selective abortion of female fetuses. We aimed to establish the trends in sex ratio by birth order from 1990 to 2005 with three nationally representative surveys and to quantify the totals of selective abortions of girls with census cohort data. METHODS We assessed sex ratios by birth order in 0·25 million births in three rounds of the nationally representative National Family Health Survey covering the period from 1990 to 2005. We estimated totals of selective abortion of girls by assessing the birth cohorts of children aged 0-6 years in the 1991, 2001, and 2011 censuses. Our main statistic was the conditional sex ratio of second-order births after a firstborn girl and we used 3-year rolling weighted averages to test for trends, with differences between trends compared by linear regression. FINDINGS The conditional sex ratio for second-order births when the firstborn was a girl fell from 906 per 1000 boys (99% CI 798-1013) in 1990 to 836 (733-939) in 2005; an annual decline of 0·52% (p for trend=0·002). Declines were much greater in mothers with 10 or more years of education than in mothers with no education, and in wealthier households compared with poorer households. By contrast, we did not detect any significant declines in the sex ratio for second-order births if the firstborn was a boy, or for firstborns. Between the 2001 and 2011 censuses, more than twice the number of Indian districts (local administrative areas) showed declines in the child sex ratio as districts with no change or increases. After adjusting for excess mortality rates in girls, our estimates of number of selective abortions of girls rose from 0-2·0 million in the 1980s, to 1·2-4·1 million in the 1990s, and to 3·1-6·0 million in the 2000s. Each 1% decline in child sex ratio at ages 0-6 years implied 1·2-3·6 million more selective abortions of girls. Selective abortions of girls totalled about 4·2-12·1 million from 1980-2010, with a greater rate of increase in the 1990s than in the 2000s. INTERPRETATION Selective abortion of girls, especially for pregnancies after a firstborn girl, has increased substantially in India. Most of Indias population now live in states where selective abortion of girls is common. FUNDING US National Institutes of Health, Canadian Institute of Health Research, International Development Research Centre, and Li Ka Shing Knowledge Institute.

Fast track — ArticlesTrends in selective abortions of girls in India: analysis of nationally representative birth histories from 1990 to 2005 and census data from 1991 to 2011

BACKGROUND Indias 2011 census revealed a growing imbalance between the numbers of girls and boys aged 0-6 years, which we postulate is due to increased prenatal sex determination with subsequent selective abortion of female fetuses. We aimed to establish the trends in sex ratio by birth order from 1990 to 2005 with three nationally representative surveys and to quantify the totals of selective abortions of girls with census cohort data. METHODS We assessed sex ratios by birth order in 0·25 million births in three rounds of the nationally representative National Family Health Survey covering the period from 1990 to 2005. We estimated totals of selective abortion of girls by assessing the birth cohorts of children aged 0-6 years in the 1991, 2001, and 2011 censuses. Our main statistic was the conditional sex ratio of second-order births after a firstborn girl and we used 3-year rolling weighted averages to test for trends, with differences between trends compared by linear regression. FINDINGS The conditional sex ratio for second-order births when the firstborn was a girl fell from 906 per 1000 boys (99% CI 798-1013) in 1990 to 836 (733-939) in 2005; an annual decline of 0·52% (p for trend=0·002). Declines were much greater in mothers with 10 or more years of education than in mothers with no education, and in wealthier households compared with poorer households. By contrast, we did not detect any significant declines in the sex ratio for second-order births if the firstborn was a boy, or for firstborns. Between the 2001 and 2011 censuses, more than twice the number of Indian districts (local administrative areas) showed declines in the child sex ratio as districts with no change or increases. After adjusting for excess mortality rates in girls, our estimates of number of selective abortions of girls rose from 0-2·0 million in the 1980s, to 1·2-4·1 million in the 1990s, and to 3·1-6·0 million in the 2000s. Each 1% decline in child sex ratio at ages 0-6 years implied 1·2-3·6 million more selective abortions of girls. Selective abortions of girls totalled about 4·2-12·1 million from 1980-2010, with a greater rate of increase in the 1990s than in the 2000s. INTERPRETATION Selective abortion of girls, especially for pregnancies after a firstborn girl, has increased substantially in India. Most of Indias population now live in states where selective abortion of girls is common. FUNDING US National Institutes of Health, Canadian Institute of Health Research, International Development Research Centre, and Li Ka Shing Knowledge Institute.

The Impacts of Dietary Change on Greenhouse Gas Emissions, Land Use, Water Use, and Health : A Systematic Review

Food production is a major driver of greenhouse gas (GHG) emissions, water and land use, and dietary risk factors are contributors to non-communicable diseases. Shifts in dietary patterns can therefore potentially provide benefits for both the environment and health. However, there is uncertainty about the magnitude of these impacts, and the dietary changes necessary to achieve them. We systematically review the evidence on changes in GHG emissions, land use, and water use, from shifting current dietary intakes to environmentally sustainable dietary patterns. We find 14 common sustainable dietary patterns across reviewed studies, with reductions as high as 70–80% of GHG emissions and land use, and 50% of water use (with medians of about 20–30% for these indicators across all studies) possible by adopting sustainable dietary patterns. Reductions in environmental footprints were generally proportional to the magnitude of animal-based food restriction. Dietary shifts also yielded modest benefits in all-cause mortality risk. Our review reveals that environmental and health benefits are possible by shifting current Western diets to a variety of more sustainable dietary patterns.

Comparison of physician-certified verbal autopsy with computer-coded verbal autopsy for cause of death assignment in hospitalized patients in low- and middle-income countries: systematic review.

BackgroundComputer-coded verbal autopsy (CCVA) methods to assign causes of death (CODs) for medically unattended deaths have been proposed as an alternative to physician-certified verbal autopsy (PCVA). We conducted a systematic review of 19 published comparison studies (from 684 evaluated), most of which used hospital-based deaths as the reference standard. We assessed the performance of PCVA and five CCVA methods: Random Forest, Tariff, InterVA, King-Lu, and Simplified Symptom Pattern.MethodsThe reviewed studies assessed methods’ performance through various metrics: sensitivity, specificity, and chance-corrected concordance for coding individual deaths, and cause-specific mortality fraction (CSMF) error and CSMF accuracy at the population level. These results were summarized into means, medians, and ranges.ResultsThe 19 studies ranged from 200 to 50,000 deaths per study (total over 116,000 deaths). Sensitivity of PCVA versus hospital-assigned COD varied widely by cause, but showed consistently high specificity. PCVA and CCVA methods had an overall chance-corrected concordance of about 50% or lower, across all ages and CODs. At the population level, the relative CSMF error between PCVA and hospital-based deaths indicated good performance for most CODs. Random Forest had the best CSMF accuracy performance, followed closely by PCVA and the other CCVA methods, but with lower values for InterVA-3.ConclusionsThere is no single best-performing coding method for verbal autopsies across various studies and metrics. There is little current justification for CCVA to replace PCVA, particularly as physician diagnosis remains the worldwide standard for clinical diagnosis on live patients. Further assessments and large accessible datasets on which to train and test combinations of methods are required, particularly for rural deaths without medical attention.

Performance criteria for verbal autopsy-based systems to estimate national causes of death: development and application to the Indian Million Death Study.

BackgroundVerbal autopsy (VA) has been proposed to determine the cause of death (COD) distributions in settings where most deaths occur without medical attention or certification. We develop performance criteria for VA-based COD systems and apply these to the Registrar General of India’s ongoing, nationally-representative Indian Million Death Study (MDS).MethodsPerformance criteria include a low ill-defined proportion of deaths before old age; reproducibility, including consistency of COD distributions with independent resampling; differences in COD distribution of hospital, home, urban or rural deaths; age-, sex- and time-specific plausibility of specific diseases; stability and repeatability of dual physician coding; and the ability of the mortality classification system to capture a wide range of conditions.ResultsThe introduction of the MDS in India reduced the proportion of ill-defined deaths before age 70 years from 13% to 4%. The cause-specific mortality fractions (CSMFs) at ages 5 to 69 years for independently resampled deaths and the MDS were very similar across 19 disease categories. By contrast, CSMFs at these ages differed between hospital and home deaths and between urban and rural deaths. Thus, reliance mostly on urban or hospital data can distort national estimates of CODs. Age-, sex- and time-specific patterns for various diseases were plausible. Initial physician agreement on COD occurred about two-thirds of the time. The MDS COD classification system was able to capture more eligible records than alternative classification systems. By these metrics, the Indian MDS performs well for deaths prior to age 70 years. The key implication for low- and middle-income countries where medical certification of death remains uncommon is to implement COD surveys that randomly sample all deaths, use simple but high-quality field work with built-in resampling, and use electronic rather than paper systems to expedite field work and coding.ConclusionsSimple criteria can evaluate the performance of VA-based COD systems. Despite the misclassification of VA, the MDS demonstrates that national surveys of CODs using VA are an order of magnitude better than the limited COD data previously available.

Performance of four computer-coded verbal autopsy methods for cause of death assignment compared with physician coding on 24,000 deaths in low- and middle-income countries

BackgroundPhysician-coded verbal autopsy (PCVA) is the most widely used method to determine causes of death (CODs) in countries where medical certification of death is uncommon. Computer-coded verbal autopsy (CCVA) methods have been proposed as a faster and cheaper alternative to PCVA, though they have not been widely compared to PCVA or to each other.MethodsWe compared the performance of open-source random forest, open-source tariff method, InterVA-4, and the King-Lu method to PCVA on five datasets comprising over 24,000 verbal autopsies from low- and middle-income countries. Metrics to assess performance were positive predictive value and partial chance-corrected concordance at the individual level, and cause-specific mortality fraction accuracy and cause-specific mortality fraction error at the population level.ResultsThe positive predictive value for the most probable COD predicted by the four CCVA methods averaged about 43% to 44% across the datasets. The average positive predictive value improved for the top three most probable CODs, with greater improvements for open-source random forest (69%) and open-source tariff method (68%) than for InterVA-4 (62%). The average partial chance-corrected concordance for the most probable COD predicted by the open-source random forest, open-source tariff method and InterVA-4 were 41%, 40% and 41%, respectively, with better results for the top three most probable CODs. Performance generally improved with larger datasets. At the population level, the King-Lu method had the highest average cause-specific mortality fraction accuracy across all five datasets (91%), followed by InterVA-4 (72% across three datasets), open-source random forest (71%) and open-source tariff method (54%).ConclusionsOn an individual level, no single method was able to replicate the physician assignment of COD more than about half the time. At the population level, the King-Lu method was the best method to estimate cause-specific mortality fractions, though it does not assign individual CODs. Future testing should focus on combining different computer-coded verbal autopsy tools, paired with PCVA strengths. This includes using open-source tools applied to larger and varied datasets (especially those including a random sample of deaths drawn from the population), so as to establish the performance for age- and sex-specific CODs.

Greenhouse gas emissions from agricultural food production to supply Indian diets : Implications for climate change mitigation

Highlights • Highest GHG emissions from food production are from rice and ruminant products.• Highest GHG emissions from consumption are from rice and livestock products.• Consumption choice can either increase or decrease total GHG emissions.

Naive Bayes classifiers for verbal autopsies: comparison to physician-based classification for 21,000 child and adult deaths

BackgroundVerbal autopsies (VA) are increasingly used in low- and middle-income countries where most causes of death (COD) occur at home without medical attention, and home deaths differ substantially from hospital deaths. Hence, there is no plausible “standard” against which VAs for home deaths may be validated. Previous studies have shown contradictory performance of automated methods compared to physician-based classification of CODs. We sought to compare the performance of the classic naive Bayes classifier (NBC) versus existing automated classifiers, using physician-based classification as the reference.MethodsWe compared the performance of NBC, an open-source Tariff Method (OTM), and InterVA-4 on three datasets covering about 21,000 child and adult deaths: the ongoing Million Death Study in India, and health and demographic surveillance sites in Agincourt, South Africa and Matlab, Bangladesh. We applied several training and testing splits of the data to quantify the sensitivity and specificity compared to physician coding for individual CODs and to test the cause-specific mortality fractions at the population level.ResultsThe NBC achieved comparable sensitivity (median 0.51, range 0.48-0.58) to OTM (median 0.50, range 0.41-0.51), with InterVA-4 having lower sensitivity (median 0.43, range 0.36-0.47) in all three datasets, across all CODs. Consistency of CODs was comparable for NBC and InterVA-4 but lower for OTM. NBC and OTM achieved better performance when using a local rather than a non-local training dataset. At the population level, NBC scored the highest cause-specific mortality fraction accuracy across the datasets (median 0.88, range 0.87-0.93), followed by InterVA-4 (median 0.66, range 0.62-0.73) and OTM (median 0.57, range 0.42-0.58).ConclusionsNBC outperforms current similar COD classifiers at the population level. Nevertheless, no current automated classifier adequately replicates physician classification for individual CODs. There is a need for further research on automated classifiers using local training and test data in diverse settings prior to recommending any replacement of physician-based classification of verbal autopsies.

Projected health effects of realistic dietary changes to address freshwater constraints in India: a modelling study

Summary Background The availability of freshwater for irrigation in the Indian agricultural sector is expected to decline over the coming decades. This might have implications for food production in India, with subsequent effects on diets and health. We identify realistic and healthy dietary changes that could enhance the resilience of the Indian food system to future decreases in water availability. Methods In this modelling study, we optimised typical dietary patterns in an Indian population sample to meet projected decreases in the availability of water per person for irrigation (blue water footprint) due to population growth (to 2025 and 2050). The optimised diets met nutritional guidelines and minimised deviation from existing patterns. Resulting changes in life-years lost due to coronary heart disease, stroke, diabetes, and cancers were modelled using life tables, and changes in greenhouse gas emissions associated with the production of diets were estimated. The primary outcomes of the model were changes in life-years per 100 000 total population over 40 years (to 2050). Findings The optimised diets had up to 30% lower blue water footprints and generally contained lower amounts of wheat, dairy, and poultry, and increased amounts of legumes. In the 2050 scenario, adoption of these diets would on average result in 6800 life-years gained per 100 000 total population (95% CI 1600–13 100) over 40 years. The dietary changes were accompanied by reductions in greenhouse gas emissions. The magnitude of the health and environmental effects varied between dietary patterns. Interpretation Modest changes in diets could help to address projected reductions in the availability of freshwater for irrigation in India. These dietary changes could also simultaneously reduce diet-related greenhouse gas emissions and improve diet-related health outcomes. Funding Wellcome Trust.