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The current study assessed intake of iron-and-folic-acid (IFA) tablet/syrup (grouped into none, < 100 d of IFA consumption or < 100 IFA and ≥ 100 d of IFA consumption or ≥ 100 IFA) among prospective mothers and its association with various stages of low-birth weight (ELBW, extremely low-birth weight; VLBW, very low-birth weight and LBW, low-birth weight) and neonatal mortality (death during day 0–1, 2–6, 7–27 and 0–27) in India.
The cross-sectional, nationally representative, 2015–2016 National Family Health Survey (NFHS-4) data were used. Weighted descriptive analysis and multiple binary logistic regression modelling were used.
NFHS-4 covered 640 districts from thirty-seven states and union territories of India.
A total of 120 374 and 143 675 index children aged 0–59 months were included to analyse LBW and neonatal mortality, respectively.
Overall, 30·7 % mothers consumed ≥ 100 IFA in 2015–2016, and this estimate ranged from 0·0 % in Zunheboto district of Nagaland state to 89·5 % in Mahe district of Puducherry of India. Multiple regression analysis revealed that children of mothers who consumed ≥ 100 IFA had lower odds of ELBW, VLBW, LBW and neonatal mortality during day 0–1, as compared with mothers who did not buy/receive any IFA. Consumption of IFA (< 100 IFA and ≥ 100 IFA) had a protective association with neonatal death during day 7–27 and 0–27. Consumption of IFA was not associated with neonatal death during day 2–6.
While ≥ 100 IFA consumption during pregnancy was found to be associated with preventing select types of LBW and neonatal mortality, a large variation in coverage of ≥ 100 IFA consumption across 640 districts is concerning.
Rough sleeping is a chronic experience faced by some of the most disadvantaged people in modern society. This paper describes work carried out in partnership with Homeless Link (HL), a UK-based charity, in developing a data-driven approach to better connect people sleeping rough on the streets with outreach service providers. HL's platform has grown exponentially in recent years, leading to thousands of alerts per day during extreme weather events; this overwhelms the volunteer-based system they currently rely upon for the processing of alerts. In order to solve this problem, we propose a human-centered machine learning system to augment the volunteers' efforts by prioritizing alerts based on the likelihood of making a successful connection with a rough sleeper. This addresses capacity and resource limitations whilst allowing HL to quickly, effectively, and equitably process all of the alerts that they receive. Initial evaluation using historical data shows that our approach increases the rate at which rough sleepers are found following a referral by at least 15% based on labeled data, implying a greater overall increase when the alerts with unknown outcomes are considered, and suggesting the benefit in a trial taking place over a longer period to assess the models in practice. The discussion and modeling process is done with careful considerations of ethics, transparency, and explainability due to the sensitive nature of the data involved and the vulnerability of the people that are affected.
The role of sociodemographic and economic characteristics in mental distress has been rarely investigated in Indonesia.
To investigate the prevalence of common mental disorders (CMD) and identify any associations between mental distress and sociodemographic and economic characteristics among communities living in urban and rural (peri-urban) areas.
A community-based household survey was conducted in the province of Aceh, Indonesia, in 2018. The 20-item Self Reporting Questionnaire (SRQ-20) screening tool was used to measure symptoms of CMD. Information on sociodemographic characteristics, family functioning, labour market outcomes and healthcare costs was collected. Multivariate regressions were conducted to analyse the relationships between the measures of mental distress and sociodemographic and economic characteristics.
We found that 14% of the respondents had CMD symptoms. SRQ-20 scores were higher for female, older and lower-educated individuals. CMD prevalence was higher among non-married participants and clustered within families. Participants with CMD perceive their families as performing significantly better in the dimensions of affective involvement and behaviour control compared with their counterparts. Their work was more often affected by negative feelings; they were also twice as likely to report a recent physical or mental health complaint and faced twice the treatment costs compared with their non-affected counterparts.
The prevalence of mental disorders is especially high in disadvantaged population groups. Moreover, mental distress is associated with a lower perceived productivity and a higher physical health burden.
We have used the 20 largest radio continuum catalogues contained in VizieR (CDS) to determine radio continuum spectra between wavelengths of 2cm and 1m. For 67,000 out of the 3.5 million catalogued sources we could extract radio spectra with measurements at at least three independent frequencies (Vollmer et al. 2005, A&A, 431, 1177). These have been validated by comparison with existing spectral indices from the literature. This work allowed us to investigated the compatibility between the 20 radio continuum catalogues (Vollmer et al. 2005, A&A, 436, 757). Our radio spectra data base was searched for Gigahertz peaked source candidates, which we then observed quasi-simultaneously with the Effelsberg 100-m radio telescope at 6cm (4.85GHz), 2.8cm (10.45GHz), and 9mm (32GHz). This represents an efficient procedure to discover new Gigahertz peaked sources, which are believed to be AGNs at the beginning of their radio evolution. In our sample of more than 200 sources we find more than 50% bona fide GPS sources. In addition, we can estimate the percentage of variable sources in our multi-epoch sample of radio sources which show an inverted spectrum. We are generalizing the method by using VO capabilities to: (i) identify pertinent radio catalogues in the VO registry using Uniform Content Descriptions (UCDs); all catalogues containing a user defined set of UCDs (e.g., PHOT_FLUX_RADIO* for a radio flux, POS_EQ_RA and POS_EQ_DEC for the position) are located in the VO registry and listed for further queries; (ii) extract relevant data, the user can easily assign a row of a given catalogue to a row of a previously defined output catalogue; and (iii) normalize these for the determination of radio spectra; units can be converted, aconymes can be created, flags can be created, etc. This procedure allows to homogenize the information retrieved from a heterogenuous set of catalogues. For this purpose software allowing semi-automated information retrieval is being developed at the CDS within the framework of the European VO-TECH project. The potential usage of all available radio catalogues will strongly increase the number of independent radio source cross-correlations and radio spectra. Our aim is to include more than 100 radio catalogues into the radio spectra determination software. The results are progressively being made available to the community through the CDS services.
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