99 research outputs found

    Essential health information available for India in the public domain on the internet

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    <p>Abstract</p> <p>Background</p> <p>Health information and statistics are important for planning, monitoring and improvement of the health of populations. However, the availability of health information in developing countries is often inadequate. This paper reviews the essential health information available readily in the public domain on the internet for India in order to broadly assess its adequacy and inform further development.</p> <p>Methods</p> <p>The essential sources of health-related information for India were reviewed. An extensive search of relevant websites and the PubMed literature database was conducted to identify the sources. For each essential source the periodicity of the data collection, the information it generates, the geographical level at which information is reported, and its availability in the public domain on the internet were assessed.</p> <p>Results</p> <p>The available information related to non-communicable diseases and injuries was poor. This is a significant gap as India is undergoing an epidemiological transition with these diseases/conditions accounting for a major proportion of disease burden. Information on infrastructure and human resources was primarily available for the public health sector, with almost none for the private sector which provides a large proportion of the health services in India. Majority of the information was available at the state level with almost negligible at the district level, which is a limitation for the practical implementation of health programmes at the district level under the proposed decentralisation of health services in India.</p> <p>Conclusion</p> <p>This broad review of the essential health information readily available in the public domain on the internet for India highlights that the significant gaps related to non-communicable diseases and injuries, private health sector and district level information need to be addressed to further develop an effective health information system in India.</p

    Impact of an in-built monitoring system on family planning performance in rural Bangladesh

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    <p>Abstract</p> <p>Background</p> <p>During 1982–1992, the Maternal and Child Health Family Planning (MCH-FP) Extension Project (Rural) of International Centre for Diarrhoeal Disease Research, Bangladesh (ICDDR,B), in partnership with the Ministry of Health and Family Welfare (MoHFW) of the Government of Bangladesh (GoB), implemented a series of interventions in Sirajganj Sadar sub-district of Sirajganj district. These interventions were aimed at improving the planning mechanisms and for reviewing the problem-solving processes to build an effective monitoring system of the interventions at the local level of the overall system of the MOHFW, GoB.</p> <p>Methods</p> <p>The interventions included development and testing of innovative solutions in service-delivery, provision of door-step injectables, and strengthening of the management information system (MIS). The impact of an in-built monitoring system on the overall performance was assessed during the period from June 1995 to December 1996, after the withdrawal of the interventions in 1992.</p> <p>Results</p> <p>The results of the assessment showed that Family Welfare Assistants (FWAs) increased household-visits within the last two months, and there was a higher use of service-delivery points even after the withdrawal of the interventions. The results of the cluster surveys, conducted in 1996, showed that the selected indicators of health and family-planning services were higher than those reported by the Bangladesh Demographic and Health Survey (BDHS) 1996–1997. During June 1995-December, 1996, the contraceptive prevalence rate (CPR) increased by 13 percentage points (i.e. from 40% to 53%). Compared to the national CPR (49%), this increase was statistically significant (p < 0.05).</p> <p>Conclusion</p> <p>The in-built monitoring systems, including effective MIS, accompanied by rapid assessments and review of performance by the programme managers, have potentials to improve family planning performance in low-performing areas.</p

    Hardship financing of healthcare among rural poor in Orissa, India

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    <p>Abstract</p> <p>Background</p> <p>This study examines health-related "hardship financing" in order to get better insights on how poor households finance their out-of-pocket healthcare costs. We define hardship financing as having to borrow money with interest or to sell assets to pay out-of-pocket healthcare costs.</p> <p>Methods</p> <p>Using survey data of 5,383 low-income households in Orissa, one of the poorest states of India, we investigate factors influencing the risk of hardship financing with the use of a logistic regression.</p> <p>Results</p> <p>Overall, about 25% of the households (that had any healthcare cost) reported hardship financing during the year preceding the survey. Among households that experienced a hospitalization, this percentage was nearly 40%, but even among households with outpatient or maternity-related care around 25% experienced hardship financing.</p> <p>Hardship financing is explained not merely by the wealth of the household (measured by assets) or how much is spent out-of-pocket on healthcare costs, but also by when the payment occurs, its frequency and its duration (e.g. more severe in cases of chronic illnesses). The location where a household resides remains a major predictor of the likelihood to have hardship financing despite all other household features included in the model.</p> <p>Conclusions</p> <p>Rural poor households are subjected to considerable and protracted financial hardship due to the indirect and longer-term deleterious effects of how they cope with out-of-pocket healthcare costs. The social network that households can access influences exposure to hardship financing. Our findings point to the need to develop a policy solution that would limit that exposure both in quantum and in time. We therefore conclude that policy interventions aiming to ensure health-related financial protection would have to demonstrate that they have reduced the frequency and the volume of hardship financing.</p

    Randomised controlled trial evaluating the effectiveness and cost-effectiveness of 'Families for Health', a family-based childhood obesity treatment intervention delivered in a community setting for ages 6 to 11 years

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    Background: Effective programmes to help children manage their weight are required. ‘Families for Health’ focuses on a parenting approach, designed to help parents develop their parenting skills to support lifestyle change within the family. Families for Health version 1 showed sustained reductions in mean body mass index (BMI) z-score after 2 years in a pilot project. Objective: The aim was to evaluate its effectiveness and cost-effectiveness in a randomised controlled trial (RCT). Design: The trial was a multicentre, investigator-blind RCT, with a parallel economic and process evaluation, with follow-up at 3 and 12 months. Randomisation was by family unit, using a 1 : 1 allocation by telephone registration, stratified by three sites, with a target of 120 families. Setting: Three sites in the West Midlands, England, UK. Participants: Children aged 6–11 years who were overweight (≥ 91st centile BMI) or obese (≥ 98th centile BMI), and their parents/carers. Recruitment was via referral or self-referral. Interventions: Families for Health version 2 is a 10-week, family-based community programme with parallel groups for parents and children, addressing parenting, lifestyle, social and emotional development. Usual care was the treatment for childhood obesity provided within each locality. Main outcome measures: Joint primary outcome measures were change in children’s BMI z-score and incremental cost per quality-adjusted life-year (QALY) gained at 12 months’ follow-up (QALYs were calculated using the European Quality of Life-5 Dimensions Youth version). Secondary outcome measures included changes in children’s waist circumference, percentage body fat, physical activity, fruit/vegetable consumption and quality of life. Parents’ BMI and mental well-being, family eating/activity, parent–child relationships and parenting style were also assessed. The process evaluation documented recruitment, reach, dose delivered, dose received and fidelity, using mixed methods. Results: The study recruited 115 families (128 children; 63 boys and 65 girls), with 56 families randomised to the Families for Health arm and 59 to the ‘usual-care’ control arm. There was 80% retention of families at 3 months (Families for Health, 46 families; usual care, 46 families) and 72% retention at 12 months (Families for Health, 44 families; usual care, 39 families). The change in BMI z-score at 12 months was not significantly different in the Families for Health arm and the usual-care arm [0.114, 95% confidence interval (CI) –0.001 to 0.229; p = 0.053]. However, within-group analysis showed that the BMI z-score was significantly reduced in the usual-care arm (–0.118, 95% CI –0.203 to –0.034; p = 0.007), but not in the Families for Health arm (–0.005, 95% CI –0.085 to 0.078; p = 0.907). There was only one significant difference between groups for secondary outcomes. The economic evaluation, taking a NHS and Personal Social Services perspective, showed that mean costs 12 months post randomisation were significantly higher for Families for Health than for usual care (£998 vs. £548; p < 0.001). The mean incremental cost-effectiveness of Families for Health was estimated at £552,175 per QALY gained. The probability that the Families for Health programme is cost-effective did not exceed 40% across a range of thresholds. The process evaluation demonstrated that the programme was implemented, as planned, to the intended population and any adjustments did not deviate widely from the handbook. Many families waited more than 3 months to receive the intervention. Facilitators’, parents’ and children’s experiences of Families for Health were largely positive and there were no adverse events. Further analysis could explore why some children show a clinically significant benefit while others have a worse outcome. Conclusions: Families for Health was neither effective nor cost-effective for the management of obesity in children aged 6–11 years, in comparison with usual care. Further exploration of the wide range of responses in BMI z-score in children following the Families for Health and usual-care interventions is warranted, focusing on children who had a clinically significant benefit and those who showed a worse outcome with treatment. Further research could focus on the role of parents in the prevention of obesity, rather than treatment. Trial registration: Current Controlled Trials ISRCTN45032201. Funding: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 21, No. 1. See the NIHR Journals Library website for further project information

    Conventional and Molecular Breeding Approaches for Biofortification of Pearl Millet

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    Pearl millet [Pennisetum glaucum (L.) R. Br.] is an essential diet of more than 90 million people in the semi-arid tropics of the world where droughts and low fertility of soils cause frequent failures of other crops. It is an important nutri-rich grain cereal in the drier regions of the world grown on 26 mha by millions of farmers (IFAD 1999; Yadav and Rai 2013). This makes pearl millet the sixth most important crop in the world and fourth most important food crop of the India, next to rice, wheat, and maize with annual cultivation over an area of ~8 mha. Pearl millet is also primary food crop in sub-Saharan Africa and is grown on 15 mha (Yadav and Rai 2013). The significant increase in productivity of pearl millet in India is attributed to development and adoption of hybrids of early to medium duration maturity. More than 120 diverse hybrids/varieties have been released till date for various production environments. The heterosis breeding and improved crop management technologies increased productivity substantially achieving higher increased production of 9.80 mt in 2016–2017 from 2.60 mt in 1950–1951 in spite of declined of area under the crop by 20–30% over last two decades (Yadav et al. 2012)
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