4 research outputs found
Hydrographic, seasonal diversity, distribution and abundance of phytoplankton in coastal waters off Cochin - south-eastern Arabian Sea
319-326Phytoplanktons are the key primary producers in the ocean; their growth mainly depends on various physico-chemical parameters. In this study, a total of 73 species of phytoplanktons from 48 genera were identified from Cochin coastal waters. Diatoms dominated the phytoplankton community followed by dinoflagellates. Asterionellopsis glacialis, Chaetoceros decipiens and Chaetoceros curvisetum were the major diatoms noticed during the study period. The results revealed relatively high species diversity in the pre-monsoon season when compared to monsoon and post-monsoon seasons. The hierarchical multidimensional scaling of phytoplankton communities using PRIMER 6 revealed maximum similarity between the species from stations 1 and 2 during monsoon season. The canonical correspondence analysis was done using PAST version 2.17c. The results showed that post-monsoon stations were characterized by high dissolved oxygen, low temperature, phosphate, ammonia and silicate. Phytoplanktons, such as Rhizosolenia sp., Thalasionema sp., Navicula sp. were found to be strongly linked to these parameters. A bloom of Skeletonema costatum was also observed during the study period
Mapping of variations in child stunting, wasting and underweight within the states of India: the Global Burden of Disease Study 2000โ2017
Background
To inform actions at the district level under the National Nutrition Mission (NNM), we assessed the prevalence trends of child growth failure (CGF) indicators for all districts in India and inequality between districts within the states.
Methods
We assessed the trends of CGF indicators (stunting, wasting and underweight) from 2000 to 2017 across the districts of India, aggregated from 5โฏรโฏ5โฏkm grid estimates, using all accessible data from various surveys with subnational geographical information. The states were categorised into three groups using their Socio-demographic Index (SDI) levels calculated as part of the Global Burden of Disease Study based on per capita income, mean education and fertility rate in women younger than 25 years. Inequality between districts within the states was assessed using coefficient of variation (CV). We projected the prevalence of CGF indicators for the districts up to 2030 based on the trends from 2000 to 2017 to compare with the NNM 2022 targets for stunting and underweight, and the WHO/UNICEF 2030 targets for stunting and wasting. We assessed Pearson correlation coefficient between two major national surveys for district-level estimates of CGF indicators in the states.
Findings
The prevalence of stunting ranged 3.8-fold from 16.4% (95% UI 15.2โ17.8) to 62.8% (95% UI 61.5โ64.0) among the 723 districts of India in 2017, wasting ranged 5.4-fold from 5.5% (95% UI 5.1โ6.1) to 30.0% (95% UI 28.2โ31.8), and underweight ranged 4.6-fold from 11.0% (95% UI 10.5โ11.9) to 51.0% (95% UI 49.9โ52.1). 36.1% of the districts in India had stunting prevalence 40% or more, with 67.0% districts in the low SDI states group and only 1.1% districts in the high SDI states with this level of stunting. The prevalence of stunting declined significantly from 2010 to 2017 in 98.5% of the districts with a maximum decline of 41.2% (95% UI 40.3โ42.5), wasting in 61.3% with a maximum decline of 44.0% (95% UI 42.3โ46.7), and underweight in 95.0% with a maximum decline of 53.9% (95% UI 52.8โ55.4). The CV varied 7.4-fold for stunting, 12.2-fold for wasting, and 8.6-fold for underweight between the states in 2017; the CV increased for stunting in 28 out of 31 states, for wasting in 16 states, and for underweight in 20 states from 2000 to 2017. In order to reach the NNM 2022 targets for stunting and underweight individually, 82.6% and 98.5% of the districts in India would need a rate of improvement higher than they had up to 2017, respectively. To achieve the WHO/UNICEF 2030 target for wasting, all districts in India would need a rate of improvement higher than they had up to 2017. The correlation between the two national surveys for district-level estimates was poor, with Pearson correlation coefficient of 0.7 only in Odisha and four small north-eastern states out of the 27 states covered by these surveys.
Interpretation
CGF indicators have improved in India, but there are substantial variations between the districts in their magnitude and rate of decline, and the inequality between districts has increased in a large proportion of the states. The poor correlation between the national surveys for CGF estimates highlights the need to standardise collection of anthropometric data in India. The district-level trends in this report provide a useful reference for targeting the efforts under NNM to reduce CGF across India and meet the Indian and global targets.
Keywords
Child growth failureDistrict-levelGeospatial mappingInequalityNational Nutrition MissionPrevalenceStuntingTime trendsUnder-fiveUndernutritionUnderweightWastingWHO/UNICEF target
Subnational mapping of under-5 and neonatal mortality trends in India: the Global Burden of Disease Study 2000-17
Background India has made substantial progress in improving child survival over the past few decades, but a
comprehensive understanding of child mortality trends at disaggregated geographical levels is not available. We
present a detailed analysis of subnational trends of child mortality to inform efforts aimed at meeting the India
National Health Policy (NHP) and Sustainable Development Goal (SDG) targets for child mortality.
Methods We assessed the under-5 mortality rate (U5MR) and neonatal mortality rate (NMR) from 2000 to 2017 in
5 ร 5 km grids across India, and for the districts and states of India, using all accessible data from various sources
including surveys with subnational geographical information. The 31 states and groups of union territories were
categorised into three groups using their Socio-demographic Index (SDI) level, calculated as part of the Global Burden
of Diseases, Injuries, and Risk Factors Study on the basis of per-capita income, mean education, and total fertility rate
in women younger than 25 years. Inequality between districts within the states was assessed using the coefficient of
variation. We projected U5MR and NMR for the states and districts up to 2025 and 2030 on the basis of the trends from
2000 to 2017 and compared these projections with the NHP 2025 and SDG 2030 targets for U5MR (23 deaths and
25 deaths per 1000 livebirths, respectively) and NMR (16 deaths and 12 deaths per 1000 livebirths, respectively). We
assessed the causes of child death and the contribution of risk factors to child deaths at the state level.
Findings U5MR in India decreased from 83ยท1 (95% uncertainty interval [UI] 76ยท7โ90ยท1) in 2000 to 42ยท4 (36ยท5โ50ยท0)
per 1000 livebirths in 2017, and NMR from 38ยท0 (34ยท2โ41ยท6) to 23ยท5 (20ยท1โ27ยท8) per 1000 livebirths. U5MR varied
5ยท7 times between the states of India and 10ยท5 times between the 723 districts of India in 2017, whereas NMR varied
4ยท5 times and 8ยท0 times, respectively. In the low SDI states, 275 (88%) districts had a U5MR of 40 or more per
1000 livebirths and 291 (93%) districts had an NMR of 20 or more per 1000 livebirths in 2017. The annual rate of
change from 2010 to 2017 varied among the districts from a 9ยท02% (95% UI 6ยท30โ11ยท63) reduction to no significant
change for U5MR and from an 8ยท05% (95% UI 5ยท34โ10ยท74) reduction to no significant change for NMR. Inequality
between districts within the states increased from 2000 to 2017 in 23 of the 31 states for U5MR and in 24 states for
NMR, with the largest increases in Odisha and Assam among the low SDI states. If the trends observed up to
2017 were to continue, India would meet the SDG 2030 U5MR target but not the SDG 2030 NMR target or either of
the NHP 2025 targets. To reach the SDG 2030 targets individually, 246 (34%) districts for U5MR and 430 (59%) districts
for NMR would need a higher rate of improvement than they had up to 2017. For all major causes of under-5 death
in India, the death rate decreased between 2000 and 2017, with the highest decline for infectious diseases, intermediate
decline for neonatal disorders, and the smallest decline for congenital birth defects, although the magnitude of
decline varied widely between the states. Child and maternal malnutrition was the predominant risk factor, to which
68ยท2% (65ยท8โ70ยท7) of under-5 deaths and 83ยท0% (80ยท6โ85ยท0) of neonatal deaths in India could be attributed in 2017;
10ยท8% (9ยท1โ12ยท4) of under-5 deaths could be attributed to unsafe water and sanitation and 8ยท8% (7ยท0โ10ยท3) to air
pollution.
Interpretation India has made gains in child survival, but there are substantial variations between the states in the
magnitude and rate of decline in mortality, and even higher variations between the districts of India. Inequality between
districts within states has increased for the majority of the states. The district-level trends presented here can provide
crucial guidance for targeted efforts needed in India to reduce child mortality to meet the Indian and global child survival
targets. District-level mortality trends along with state-level trends in causes of under-5 and neonatal death and the risk
factors in this Article provide a comprehensive reference for further planning of child mortality reduction in India