Data_Sheet_1_Community Management of Acute Malnutrition (CMAM) in Odisha, India: A Multi-Stakeholder Perspective.DOCX

<p>India remains home to nearly one-third of the world's children with severe and acute malnutrition (SAM). The present study looks at the function and implementation of a Community Management of Severe Acute Malnutrition (CMAM) programme for treatment of children with SAM in Odisha, an Indian state. A cross-sectional study design using qualitative techniques with direct observation of process and infrastructure was adopted to explore the views of stakeholders on the programme implementation. The study focuses on Kandhamal, a district in Odisha, and was conducted during June–August, 2015. Of the district and community level stakeholders involved in CMAM programme, 49 were selected as study participants using purposive sampling. In-depth interviews were conducted to obtain relevant information. Data was analyzed using data analysis software, atlas.ti version 7. The analysis demonstrated the overall acceptability, feasibility and economic viability of the programme. Additionally, the study identified several enablers (such as good response from child, village leadership involvement, multisectoral participation etc.) and barriers (such as limited awareness, increased work load, irregular staff payment etc.) linked to programme implementation. Interactions with beneficiaries and stakeholders also provided the real picture on the ground. The study emphasizes the need for stakeholders to work responsibly and in unison, and need for beneficiaries to accept, participate and contribute to the programme. In view of maximum impact, the study recommends that CMAM programmes be implemented with existing primary healthcare facilities. The study also outlines future scope for policy-level interventions and support to ensure sustainability of this healthcare delivery model.</p

Comparison of CFA between AS and CR cases.

<p>CFA levels of 30 asymptomatic Mf carriers and 31 cryptic individuals were taken in to consideration for comparison. They are age sex matched and other parameters has been taken care as narrated in the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0199090#pone.0199090.t002" target="_blank">Table 2</a>.</p

Profile of IgG and IgG subclasses against different filarial recombinant antigens.

<p>Plasma levels of IgG and IgG subclasses against stage specific recombinant filarial antigens were analyzed by ELISA. Whole IgG against five recombinant antigens such as ALT-1, ALT-2, CPI 2 SPN 2 and Val-2 (A) and IgG isotypes against ALT-1 (B), ALT-2 (C) and CPI-2 (D) were depicted. Mean of 30 and 31 samples were shown.</p

Details and intensity of infection in two study group.

<p>Details and intensity of infection in two study group.</p

Profile of IgG and IgG subclasses against different filarial antigens.

<p>Plasma levels of IgG and IgG subclasses were analyzed by ELISA. IgG against whole somatic antigen of adult Setaria worm (A) and Setaria MF (B) were analyzed. IgG isotypes against somatic antigen of adult setaria worm were analysed (C). Mean of 30 and 31 samples were shown.</p

Anti-sheath antibody between AS and CR cases.

<p>Anti-sheath antibody between AS and CR cases.</p

Association between number of NCDs and healthcare utilisation.

<p>Association between number of NCDs and healthcare utilisation.</p

Mf status of cryptic individuals followed up for 18 and 36 months in village Kanapur and Jatni.

<p>Mf status of cryptic individuals followed up for 18 and 36 months in village Kanapur and Jatni.</p

Socio-demographic correlates of multimorbidity in SAGE countries.

<p>Notes</p><p>1. Multimorbidity defined as two or more chronic conditions in the same individual</p><p>2. Additional covariates included in the model in China: provinces; Ghana: ethnic groups (Akan, Ga-Adangbe, and others); India: states; South Africa: provinces, ethnic groups (back, white, coloured, and others).</p><p>3. Country dummy variables were included in the model to adjust for heterogeneity among countries in the pooled analysis.</p><p>Socio-demographic correlates of multimorbidity in SAGE countries.</p

Association between number of NCDs and out-of-pocket spending.

<p><b>Notes:</b> Figures in the last column are regression coefficients and 95% CI for the variable “number of NCD” from regression models adjusting for all covariates. Log-linear models is used to estimate both outpatient and inpatient out-of-pocket spending outcomes.</p><p>Association between number of NCDs and out-of-pocket spending.</p