INDIA
IFPRI Publications on India
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Language
Sharma, Kriti; Kumar, Anjani; Kumar, Nalini Ranjan. 2024
Singh, Arshdeep; Arora, Kashish; Babu, Suresh Chandra. 2024
Banerjee, Archis; Kumar, Neha; Quisumbing, Agnes R.. 2024
Belton, Ben; Breisinger, Clemens; Kassim, Yumna; Pal, Barun Deb; Narayanan, Sudha; Zhang, Xiaobo. 2024
Kumar, Neha; Raghunathan, Kalyani; Quisumbing, Agnes R.; Scott, Samuel P.; Menon, Purnima; Thai, Giang; Gupta, Shivani; Nichols, Carly; WINGS study team. 2024
Ray, Soumyajit; Raghunathan, Kalyani; Bhanjdeo, Arundhita; Heckert, Jessica. 2024
IFPRI. 2024
Ragasa, Catherine; Kyle, Jordan; Yasmin, Sabina; Pande, Harshita; Basu, Sampurna; Sharma, Aanshi. 2024
HER+ uses impactful gender research to address the four dimensions of gender inequality by applying gender-transformative approaches to address harmful norms. It does this by bundling innovations for women’s empowerment, leveraging social protection to increase women’s access to and control over resources, and promoting inclusive governance and policies for increased resilience. HER+ will generate learning and evidence on levers and entry points to disrupt the foundations of inequality in agrifood systems (AFS).
Beniwal, Ezaboo; Kishore, Avinash. 2024
Ragasa, Catherine; Kyle, Jordan; Yasmin, Sabina; Pande, Harshita; Basu, Sampurna; Sharma, Aanshi. 2024
HER+ uses impactful gender research to address the four dimensions of gender inequality by applying gender-transformative approaches to address harmful norms. It does this by bundling innovations for women’s empowerment, leveraging social protection to increase women’s access to and control over resources, and promoting inclusive governance and policies for increased resilience. HER+ will generate learning and evidence on levers and entry points to disrupt the foundations of inequality in agrifood systems (AFS).
Nguyen, Phuong; Mai, Lan T.; Kachwaha, Shivani; Sanghvi, Tina; Mahmud, Zeba; Zafimanjaka, Maurice G.; Walissa, Tamirat; Ghosh, Sebanti; Kim, Sunny S.. 2024
Bhanjdeo, Arundhita. 2024
Sanil, Richu; Falk, Thomas; Meinzen-Dick, Ruth S.; Priyadarshini, Pratiti. 2024
Chakrabarti, Suman; Christopher, Anita; Scott, Samuel P.; Kishore, Avinash; Nguyen, Phuong H.. 2024
Methods Data from the Indian National Family Health Surveys (2005–06, 2015–16, 2019–21), Annual Health Survey (2013), and District Level Household Survey (2012), were used to conduct difference-in-differences (DID) analysis, comparing Bihar (n = 10,733 men, n = 88,188 women) and neighbouring states (n = 38,674 men, n = 284,820 women) before and after the ban. Outcomes included frequent (daily or weekly) alcohol consumption, underweight, obesity, hypertension, diabetes, and intimate partner violence. A triple difference model adding male–female interaction to the DID model was also estimated. Attributable averted cases were calculated to estimate the impact of the ban.
Verger, Eric O.; Eymard-Duvernay, Sabrina; Bahya-Batinda, Dang; Hanley-Cook, Giles T.; Argaw, Alemayehu; Becquey, Elodie; Diop, Loty; Gelli, Aulo; Harris-Fry, Helen; Kachwaha, Shivani; Kim, Sunny S.; Nguyen, Phuong Hong; Saville, Naomi M.; Tran, Lan Mai; Zagré, Rock R.; Landais, Edwige; Savy, Mathilde; Martin-Prevel, Yves; Lachat, Carl. 2024
ElDidi, Hagar; Rawat, Shivanyaa; Meinzen-Dick, Ruth S.; Chaturvedi, Rahul; Sanil, Richu. 2024
Singh, Shri K.; Chauhan, Alka; Alderman, Harold; Avula, Rasmi; Dwivedi, Laxmi K.; Kapoor, Rati; Meher, Trupti; Menon, Purnima; Nguyen, Phuong; Pedgaonker, Sarang; Puri, Parul; Chakrabarti, Suman. 2024
Ch, Lakshmi Durga; Bharath, Yandrapu; Bliznashka, Lilia; T., Vijay Kumar; Jonnala, Veerendra; Chekka, Vijayalakshmi; Yebushi, Srileka; Roy, Aditi; Venkateshmurthy, Nikhil Srinivasapura; Prabhakaran, Poornima; Jaacks, Lindsay M.. 2024
Methods A cross-sectional assessment was conducted in 2021–2022 of 50 intervention villages where the nutrition-sensitive agroecology program had been implemented since 2018 and 79 control villages where only the agroecology program had been implemented. Data on self-reported dietary intake, caregiver-reported early child development, anthropometric measurements, and hemoglobin concentrations were collected using standardized procedures by trained Nutrition Farming Fellows, who were also responsible for implementing the program.
Results A sample of 3,511 households (1,121 intervention and 2,390 control) participated in the survey. Dietary diversity scores (DDS) among women and men were mean (SD) 6.53 (±1.62) and 6.16 (±1.65), respectively, in intervention villages and 5.81 (±1.58) and 5.39 (±1.61), respectively, in control villages (p<0.01). DDS among children 6–24 months of age in intervention and control villages was 2.99 (±1.52) and 2.73 (±1.62), respectively (p<0.01). Children <2 years of age were less likely to be anemic in intervention versus control villages (59% versus 69%, p<0.01). Children 18–35 months age in intervention villages had higher child development scores than children in control villages (all p<0.05). Conclusion Nutrition-sensitive agroecological programs may be effective in improving diets, nutrition, and child development in rural India.
Chakrabarti, Suman; Ajjampur, Sitara S. R.; Waddington, Hugh Sharma; Kishore, Avinash; Nguyen, Phuong H.; Scott, Samuel. 2024
Kumar, Anjani; Mishra, Ashok K.; Signh, A. K.; Saroj, Sunil; Madhaven, Misha; Joshi, Pramod Kumar. 2024
Jian, Junyan. 2024
Kumar, Anjani; Mishra, Ashok K.; Sonkar, Vinay K.; Roy, Devesh. 2024
Kumar, Anjani; Elumalai, K. 2024
Kumar, Anjani; Sen, Biswajit; Saroj, Sunil. 2024
Neufeld, Lynnette M.; Nordhagen, Stella; Leroy, Jef L.; Aberman, Noora-Lisa; Barnett, Inka; Wouabe, Eric Djimeu. 2024
International Food Policy Research Institute. 2024
Kumara T M, Kiran; Birthal, Pratap Singh; Meena, Dinesh Chand; Kumar, Anjani. 2024
Kosec, Katrina; Kyle, Jordan; Narayanan, Sudha; Raghunathan, Kalyani; Ray, Soumyajit. 2024
Govindaraj, Mahalingam; Pujar, Mahesh. 2023
Rwamigisa, Patience B.; Namyenya, Angella; Butele, Cosmas Alfred; Shah, Mansi; Githuku, Fridah; Njung’e, Dennis. Washington, DC 2023
Akbar, Nusrat; Kumar, Anjani. New Delhi, India 2023
Nikita, Rajkumari; Ghosh, Anwesha; Yash; Kumar, Chakresh; Mandal, Arkaprava; Saini, Nirupama; Dubey, Sourabh Kumar; Gogoi, Kalpajit; Rajts, Francois; Belton, Ben; Bhadury, Punyasloke . 2023
Pal, Barun Deb; Ajmani, Manmeet; Thurlow, James; Pauw, Karl. Washington, DC 2023
Pal, Barun Deb; Ajmani, Manmeet; Thurlow, James; Pauw, Karl. Washington, DC 2023
Pal, Barun Deb; Ajmani, Manmeet; Thurlow, James; Pauw, Karl. Washington, DC 2023
Aladesuru, Damilola; Kasule, James Billy; Joshi, Garima. Washington, DC 2023
Rajts, Francois; Dubey, Sourabh Kumar; Gogoi, Kalpajit; Das, Rashmi Ranjan; Biswal, Saurava Kumar; Padiyar, Arun Panemangalore; Rajendran, Suresh; Thilsted, Shakuntala Haraksingh; Mohan, Chadag Vishnumurthy; Belton, Ben. 2023
Methods: To address this gap, we conducted breeding trials at a private hatchery in Odisha, India, from July to September 2022, to identify standardized methods for the hatchery-based mass production of mola seed. Breeding was induced using a synthetic gonadotropin-releasing hormone analog (SGnRHa) at 0.5 mL and 0.25 mL per kg of body weight of female fish and male fish, respectively. Fish spawned in double hapas in breeding tanks.
Results: The average fertilization, spawning, and hatching rates over 10 breeding cycles were 81%, 82%, and 85%, respectively. A total of 8.5 million fertilized eggs and 6.4 million hatchlings were produced. The survival of fry during larval rearing trials at a stocking rate of 500 hatchlings/m2 was 58% after 22 days. The mola hatchlings and fry were sold to 29 farmers at prices comparable to those of Indian major carp.
Discussion: This article makes a unique contribution to the literature by documenting the entire process of hatchery-based mass mola seed production, including broodfish collection and maintenance, hormone dose optimization, breeding arrangements, breeder characteristics, breeding behavior and performance fecundity, larval rearing, and seed sales to farmers. This information is intended to serve as a protocol to be followed by any individual or institution with an interest in mola breeding and represents an important contribution to the development of nutrition-sensitive aquaculture.
Akber, Nusrat; Kumar, Anjani; Bathla, Seema. Washington, DC 2023
Barooah, Prapti; Alvi, Muzna; Ringler, Claudia. Washington, DC 2023
Kannan, Elumalai; Kumar, Anjani. Washington, DC 2023
Halimatussadiah, Alin; Buchori, Damayanti; Carazo, Felipe; Swinnen, Johan; Adriansyah, Muhammad; Ghiffari, Muhammad Nur; Algamar, Rizal; Anky, Wildan Al Kautsar. 2023
Alvi, Muzna; Ward, Patrick; Makhija, Simrin; Spielman, David J..
Narayanan, Sudha. 2023
Reddy, Anugu Amarender; Babu, Suresh; Kumar, Parmod; Kumar, Soora Naresh . 2023
This chapter mainly discusses where does India stand today in terms of its agriculture when compared to its independence in 1947? As the data for 1947 for most of the indicators is not available, 1951 is considered the base year and compared the various indicators for the year 2021.
Narayanan, Sudha; Vijayabaskar, M.; Srinivasan, Sharada . 2023
Palani Samy, Venkatesh; Vellaichamy, Sangeetha; Girish Kumar, Jha; Sharma, Nitin; Babu, Suresh C. . 2023
family members. We assigned the weights based on principal component analysis (PCA). Then, we examine the extent of empowerment and nutrition outcomes of the family members across the wealth category and place of residence (rural-urban setting). Finally, we validate the WEI by analyzing the relationship between WEI and nutrition outcomes of family members through logit analysis. We used Uttar Pradesh data from National Family Health Survey (NFHS) -5 conducted in 2019-21 for the study. We found a positive relationship between household wealth and women's empowerment, indicating the vulnerability of women in poor families, especially in rural areas. Our results also suggested that women's
empowerment differs across educational backgrounds and places of residence. Finally, we found that the prevalence of malnutrition is negatively associated with women's empowerment, especially children and women. These findings highlight the need for promoting women's empowerment-based policies and interventions to address the malnutrition problem
Kumar, K. Nirmal Ravi; Reddy, M. Jagan Mohan; Babu, Suresh Chandra. 2023
Kosec, Katrina; Kyle, Jordan; Narayanan, Sudha; Raghunathan, Kalyani. Washington, DC 2023
Carrillo, Lucia; Meinzen-Dick, Ruth Suseela; Priyadarshini, Pratiti; Sanil, Richu. New Delhi, India 2023
Alvi, Muzna; Ringler, Claudia; Bryan, Elizabeth. 2023
However, to date, most climate change policies, investments, and interventions remain gender-blind. As a result, they might exacerbate gender inequalities in food systems by, for instance, increasing women’s labor burden and time poverty, reducing their access to and control over income and assets, and reducing their decision-making power.
Magalhaes, Marilia; Kawerau, Laura; Kweyu, Janerose; Pathak, Vishak. Washington, DC 2023
Welk, Lukas; Barooah, Prapti; Kato, Edward; Ndegwa, Michael K.. Washington, DC 2023
Welk, Lukas. Washington, DC 2023
Negi, Digvijay Singh; Kumar, Anjani; Birthal, Pratap Singh; Tripathi, Gaurav. Article in press
Alvi, Muzna; Barooah, Prapti; Gupta, Shweta; Saini, Smriti. Washington, DC 2023
Gómez, Eduardo J.. Washington, DC; Oxford, UK 2023
Barrett, Christopher B.. Washington, DC; Oxford, UK 2023
Srinivas, Krishna Ravi; Anand, P. K.; Babu, Suresh . 2023
Singh, Vartika; Stevanović, Miodrag; Jha, Chandan Kumar; Beier, Felicitas; Ghosh, Ranjan Kumar; Lotze-Campen, Hermann; Popp, Alexander. 2023
Govindaraj, Mahalingam; Pujar, Mahesh . Singapore 2023
Elumalai, Kanan; Kumar, Anjani. Article in press
Venkata, Nagesh Kumar Mallela; Vittal, Ramya; Setaboyine, Maheshwaramma; Kuyyamudi, Ganapathy N.; Govindaraj, Mahalingam; Kosnam, Kavitha; Kalisetti, Vanisree . 2023
Bhargava, Anil K.; Lybbert, Travis J.; Spielman, David J.. 2023
Kamar, Abul; Roy, Devesh; Pradhan, Mamata; Saroj, Sunil. Washington, DC 2023
Trade moves food from surplus to deficit regions and hence is crucial for maintaining a stable food supply. Historically, the global supply of cereals has been stable (Bradford et al. 2022); this implies that trade (or the lack of it) can be directly mapped onto area-specific food insecurity. At the same time, shocks leading to trade disruption can pose serious challenges, particularly for countries with high import penetration in food.
Alvi, Muzna Fatima.
Cooper, Bethany; Crase, Lin; Burton, Michael; Rigby, Dan; Alam, Mohammad Jahangir; Kishore, Avinash . 2023
Dwivedi, Laxmi Kant; Puri, Parul; Pant, Anjali; Chauhan, Alka; Scott, Samuel; Sigh, Shrikant; Pedgaoker, Sarang; Nguyen, Phuong. 2023
The double burden of malnutrition (DBM), characterized by concurrent undernutrition and overnutrition, is a growing global concern. Families share resources and eating behaviors and programs often target households, yet evidence of the DBM at the family level is scarce.
Objectives
This study examined trends and inequality in the intrahousehold DBM in India between 2006 and 2021.
Methods
Data were from 3 waves of India’s National Family Health Survey (NFHS 2006, 2016, and 2021). We examined 3 types of household member (with children aged <5 y) combinations: mother–child (N = 328,039 across 3 waves), father–child, and parent (mother and father)–child (N = 47,139 for each pair). The DBM was defined as one or more individuals with undernutrition (either wasting or stunting in children or underweight in adults) and one or more overweight individuals within the same household. DBM was examined over time, at national and subnational levels, and by residence and wealth. Results Nearly all DBM was in the form of an overweight parent and an undernourished weight or stunted child. The prevalence of parent–child DBM increased from 15% in 2006 to 26% in 2021. Father–child pairs experienced the most rapid DBM increase, from 12% in 2006 to 22% in 2021, an 83% increase, driven by increasing overweight among men. In 2021, the DBM was highest in North-Eastern and Southern states, and among relatively rich households from urban areas. The increase in the DBM was faster in rural areas and among poor households compared with that in urban areas and rich households. Urban–rural and rich–poor inequalities in the DBM have decreased over time. Conclusions The intrahousehold DBM has increased over time, affecting 1 in 4 households in India in 2021. Family-based interventions that can simultaneously address child underweight and parent overweight are required to address India’s increasing intrahousehold DBM.
Barooah, Prapti; Alvi, Muzna; Ringler, Claudia; Pathak, Vishal . 2023
OBJECTIVE: We aim to understand policy and implementation gaps in reaching women farmers with climate-smart agriculture (CSA) practices and study how women and men farmer's different roles in agriculture shape their needs and access to complementary services needed to adapt to climate change.
METHODS: An extensive review of India's agriculture and climate policies and program and a series of focus group discussions with farmers in Gujarat, India to discuss constraints and potential entry points for better reaching women farmers with CSA practices.
RESULTS AND CONCLUSION: Women's increased vulnerability to climate change and reduced access to CSA practices can be attributed to limited land ownership, poor access to credit, reduced access to information and formal extension, and multiple pressures on their time. Village cooperatives and self-help groups can be leveraged to support women's access to agricultural information and adoption of CSA practices.
SIGNIFICANCE: This paper highlights constraints to information and extension access by Indian women farmers that could impede the widespread adoption of CSA practices. It fills an important knowledge gap in designing gender-responsive policies and inclusive agricultural extension systems to promote adoption of CSA practices among smallholder farmers.
Elumalai, K.; Kumar, Anjani. 2023
Nuthalapati, Chandra S.; Beero, Susanto K.; Kumar, Anjani; Sonkar, Vinay; Areef, Mulla . 2023
Neupane, Sumanta; Jangid, Manita; Scott, Samuel P.; Kim, Sunny S.; Murira, Zivai; Heidkamp, Rebecca; Carducci, Bianca; Menon, Purnima. 2024
Singh, Shri Kant; Chauhan, Alka; Sharma, Santosh Kumar; Puri, Parul; Pedgaonkar, Sarang; Dwivedi, Laxmi Kant; Taillie, Lindsey Smith . 2023
Raabe, Katharina. Washington, DC 2008
Kumar, Anjani; Bathla, Seema; Verma, Smriti. 2023
Ray, Soumyajit; Ashok, Sattvika; Avula, Rasmi; Nguyen, Phuong Hong; Hemalatha, R.; Singh, S. K.; Chamois, Sylvie; Menon, Purnima. New Delhi, India 2023
Takeshima, Hiroyuki. Article in press
Fan, Shenggen. Washington, DC 2002
Cheng, Fuzhi; Orden, David. Washington, D.C. 2005
Wanmali, Sudhir. Washington, DC 1983
Pant, Anjali; Patwardhan, Sharvari; Nguyen, Phuong Hong; Scott, Samuel; Avula, Rasmi; Hemalatha, R.; Singh, S.K.; Chamois, Sylvie; Menon, Purnima. New Delhi, India 2023
Jhaveri, Neha R.; Poveda, Natalia E.; Kachwaha, Shivani; Comeau, Dawn L.; Nguyen, Phuong Hong; Young, Melissa F. . 2023
Objective: This qualitative study aimed to: (1) examine pregnant women’s experiences of key nutrition-related behaviors (ANC attendance, consuming a diverse diet, supplement intake, weight gain monitoring, and breastfeeding intentions); (2) examine the influence of family members on these behaviors; and (3) identify key facilitators and barriers that affect behavioral adoption.
Methods: We conducted a qualitative study with in-depth interviews with 24 pregnant women, 13 husbands, and 15 mothers-in-law (MIL). We analyzed data through a thematic approach using the Capability-Opportunity-Motivation-Behavior (COM-B) framework.
Results: For ANC checkups and maternal weight gain monitoring, key facilitators were frontline worker home visits, convenient transportation, and family support, while the primary barrier was low motivation and lack understanding of the importance of ANC checkups. For dietary diversity, there was high reported capability (knowledge related to the key behavior) and most family members were aware of key recommendations; however, structural opportunity barriers (financial strain, lack of food availability and accessibility) prevented behavioral change. Opportunity ranked high for iron and folic acid supplement (IFA) intake, but was not consistently consumed due to side effects. Conversely, lack of supply was the largest barrier for calcium supplement intake. For breastfeeding, there was low overall capability and several participants described receiving inaccurate counseling messages.
Conclusion: Key drivers of maternal nutrition behavior adoption were indicator specific and varied across the capability-opportunity-motivation behavior change spectrum. Findings from this study can help to strengthen future program effectiveness by identifying specific areas of program improvement.
Bouis, Howarth E.. 2002
Bouis, Howarth; Gulati, Ashok . Noida, India 2020
Bouis, Howarth E.; Gulati, Ashok. 2020
Avula, Rasmi, ed.. New Delhi, India 2023
Narayanan, Sudha; Naraparaju, Karthikeya; Gerber, Nicolas
. 2023
Connors, Kaela; Jaacks, Lindsay M.; Awasthi, Ananya; Becker, Karoline; Kerr, Rachel Bezner; Fivian, Emily; Gelli, Aulo; Harris-Fry, Helen; Heckert, Jessica; Kadiyala, Suneetha; Martinez, Elena; Santoso, Marianne V.; Young, Sera L.; Bliznashka, Lilia. 2023
Methods: In this secondary analysis of cross-sectional data, we used data from four cluster-randomised controlled trials done in Burkina Faso, India, Malawi, and Tanzania. We assessed women's empowerment using indicators from the Women's Empowerment in Agriculture Index. Farm-level crop diversity measures were the number of food crops grown, number of food groups grown, and if nutrient-dense crops were grown. We used a two-stage modelling approach. First, we analysed covariate-adjusted country-specific associations between women's empowerment and crop diversity indicators using multivariable generalised linear models. Second, we pooled country-specific associations using random-effects models.
Findings: The final analytic sample included 1735 women from Burkina Faso, 4450 women from India, 547 women from Malawi, and 574 women from Tanzania. Across all countries, compared with households in which women provided input into fewer productive decisions, households of women with greater input into productive decisions produced more food crops (mean difference 0·36 [95% CI 0·16–0·55]), a higher number of food groups (mean difference 0·16 [0·06–0·25]), and more nutrient-dense crops (percentage point difference 3 [95% CI 3–4]). Across all countries, each additional community group a woman actively participated in was associated with cultivating a higher number of food crops (mean difference 0·20 [0·04–0·35]) and a higher number of food groups (mean difference 0·11 [0·03–0·18]), but not more nutrient-dense crops. In pooled associations from Burkina Faso and India, asset ownership was associated with cultivating a higher number of food crops (mean difference 0·08 [0·04–0·12]) and a higher number of food groups (mean difference 0·05 [0·04–0·07]), but not more nutrient-dense crops.
Interpretation: Greater women's empowerment was associated with higher farm-level crop diversity among low-income agricultural households, suggesting that it could help enhance efforts to strengthen food system resilience.
Narayanan, Sudha; Negi, Digvijay S.; Gupta, Tanu. 2023
Kumar, Anjani; Roy, Devesh; Tripathi, Gaurav; Joshi, Pramod Kumar. Article in press
Kumar, Anjani; Saroj, Sunil; Mishra, Ashok K.. 2023
Kumar, K. Nirmal; Mishra, S. N.; Shafiwu, Adinan Bahahudeen; Gajanan, Shailendra N.; Babu, Suresh Chandra; Neelima, A. Sandhya. 2023
Raghunathan, Kalyani; Alvi, Muzna Fatima; Sehgal, Mrignyani. 2023
Sanghvi, Tina; Nguyen, Phuong Hong; Forissier, Thomas; Ghosh, Sebanti; Zafimanjaka, Maurice; Walissa, Tamirat; Mahmud, Zeba; Kim, Sunny S.. 2023
Mothkoor, Venugopal; Reddy, Murali; Koganti, Dharani. Montpellier, France 2023
Neupane, Sumanta; Scott, Samuel; Piwoz, Ellen; Kim, Sunny S.; Menon, Purnima; Nguyen, Phuong Hong. 2023
Narayanan, Sudha; Parmar, Milee; Pandey, Ritesh . London, United Kingdom 2023
Feed the Future Innovation Lab for Small Scale Irrigation. 2023
Adhikari, Roshan; Kramer, Berber; Ward, Patrick S.; Foster, Timothy; Sharma, Varun; Gaur, Pushkar; Pattnaik, Subhransu. Washington, DC 2023
- Using a survey with 900 men and women farmers in Odisha, India, we find that women and men have similar farming practices and input use in general, but women face more difficulties in hiring labor and transplant rice later than men.
- Using biophysical crop models, we show that this delay in transplanting lowers expected yields and increases risk exposure for women farmers.
- Direct-seeded rice (DSR) is a promising alternative method for establishing rice that can help to mitigate the risks posed by climate change. Our findings indicate DSR is especially beneficial for women farmers.
- Gender-responsive policies are needed to ensure that women farmers have equitable access to agricultural insurance and risk-reducing technologies.
Raghunathan, Kalyani; Kumar, Neha; Gupta, Shivani; Chauhan, Tarana; Kathuria, Ashi Kohli; Menon, Purnima. 2023
Kim, Sunny S.; Ashok, Sattvika; Avula, Rasmi; Mahapatra, Tanmay; Gokhale, Priya; Walton, Shelley; Heidkamp, Rebecca A.; Munos, Melinda K.. 2023
Counseling on infant and young child feeding (IYCF) to support optimal breastfeeding and complementary feeding practices is an essential intervention, and accurate coverage data is needed to identify gaps and monitor progress. However, coverage information captured during household surveys has not yet been validated.
Objectives
We examined the validity of maternal reports of IYCF counseling received during community-based contacts and factors associated with reporting accuracy.
Methods
Direct observations of home visits conducted by community workers in 40 villages in Bihar, India served as the “gold standard” to maternal reports of IYCF counseling received during 2-wk follow-up surveys (n = 444 mothers with children less than 1 y of age, interviews matched to direct observations). Individual-level validity was assessed by calculating sensitivity, specificity, and AUC. Population-level bias was measured using the inflation factor (IF). Multivariable regression models were used to examine factors associated with response accuracy.
Results
Prevalence of IYCF counseling during home visits was very high (90.1%). Maternal report of any IYCF counseling received in the past 2 wk was moderate (AUC: 0.60; 95% CI: 0.52, 0.67), and population bias was low (IF = 0.90). However, the recall of specific counseling messages varied. Maternal report of any breastfeeding, exclusive breastfeeding, and dietary diversity messages had moderate validity (AUC > 0.60), but other child feeding messages had low individual validity. Child age, maternal age, maternal education, mental stress, and social desirability were associated with reporting accuracy of multiple indicators.
Conclusions
Validity of IYCF counseling coverage was moderate for several key indicators. IYCF counseling is an information-based intervention that may be received from various sources, and it may be challenging to achieve higher reporting accuracy over a longer recall period. We consider the modest validity results as positive and suggest that these coverage indicators may be useful for measuring coverage and tracking progress over time.
Owais, Aatekah; Rizvi, Arjumand; Jawwad, Muhammad; Horton, Susan; Das, Jai K.; Merritt, Catherine; Moreno, Ralfh; Asfaw, Atnafu G.; Rutter, Paul; Nguyen, Phuong Hong; Menon, Purnima; Bhutta, Zulfiqar A.. 2023
Avula, Rasmi, ed.. New Delhi, India 2023
Saroj, Sunil; Roy, Devesh; Kamar, Abul; Pradhan, Mamata. Washington, DC 2023
The innovations in international trade literature that explains both the emergence as well as levels and the nature of trade flows through value chain integration necessitates examining trade-based exchanges at the highest possible levels of product disaggregation. Developments in trade theory emphasize that it is individual firms not countries that trade and analysis needs to incorporate firm characteristics in decisions and ability for exporting and importing. Firms are the appropriate unit of analysis for trade flows. It helps several paradoxes once the import of firm heterogeneity is understood.
Despite the substantive importance of granular level data and the significant level of disaggregated product-level bilateral trade flow data and enhanced computing power that are becoming available, most studies have tended to rely on analysis with high level of aggregation. Recent research on firm heterogeneity in international trade highlights the importance of extensive margins i.e., new products, new partners, new varieties, and cumulative of these i.e., new prices in trade patterns and firms' responses to trade liberalization and other policy changes. However, the high dimensionality of the data and the large number of responses to changes can easily overwhelm researchers. Additionally, bigger data sets may contain more noise, which can mask important systematic patterns. In analysis of trade flows, notwithstanding the rising incidence of differentiated products (varieties) and value chains that transcend national boundaries, methods in agri-food trade analysis in particular have not kept pace in terms of empirical methods and suitable data.
Shiferaw, Bekele; Kebede, Tewodros; Ratna Reddy, V.. Washington, DC 2008
Kamar, Abul; Roy, Devesh. Washington, DC 2023
in intra-regional trade among BIMSTEC member countries. Importantly the low share of intra BIMSTEC trade is not due to greater integration with supra-BIMSTEC partners. This policy note seeks to spell out some of the key agricultural trade policy-related challenges in the BIMSTEC region and their implications for economic integration in the area.
Nair, Sapna; Ashok, Sattvika; Menon, Purnima; Avula, Rasmi. New Delhi, India 2023
Government of Odisha; International Food Policy Research Institute (IFPRI). Washington, DC 2023
Aditi, Kumari; Abbhishek, Kumar; Chander, Girish; Singh, Ajay; Falk, Thomas; Mequanint, Melesse B.; Cuba, Perumal; Anupama, G.; Mandpati, Roja; Nagaraji, Satish. 2023
Qureshy, Lubina Fatimah; Alderman, Harold; Manchanda, Navneet. 2023
Falk, Thomas; Zhang, Wei; Meinzen-Dick, Ruth Suseela; Bartels, Lara; Sanil, Richu; Priyadarshini, Pratiti; Soliev, Ilkhom. 2023
Babu, Suresh Chandra; Zhou, Yuan. 2023
Indian policies related to youth entrepreneurship have evolved rapidly over the past decade. It is a recognition that the youth force, particularly in agriculture and allied sectors, is key to the effective inclusiveness and engagement of youth and women in improving the livelihood and long-term transformation of the agriculture sector. Further, given the recent policy reforms and the associated challenges, studying opportunities for youth in the agriculture sector becomes paramount to guiding the policy and program implementation process from the youth entrepreneurial perspective.
Indian policymakers operating in the agricultural and rural development sectors recognize youth entrepreneurship as a critical driver for transforming these sectors. Policy and program interventions at the national level reflect this recognition. Recent economic growth in the last two decades in India has also brought the needed preconditions for youth entrepreneurship. Yet the challenges for entering business opportunities for youth in agriculture remain. There are several structural constraints related to access to technology, finance, institutional support, market access, and business mentorship. These challenges are accentuated further by the needed skills and experience relevant for initiating and running businesses, which remain a significant challenge for the youth in rural India.
Urfels, Anton; Mausch, Kai; Harris, Dave; McDonald, Andrew J.; Kishore, Avinash; Singh, Vartika. 2023
Kim, Sunny S.; Ashok, Sattvika; Avula, Rasmi; Mahapatra, Tanmay; Gokhale, Priya; Walton, Shelley; Heidkamp, Rebecca; Munos, Melinda. 2023
Objectives: We examined the validity of maternal report of IYCF counseling received during community-based contacts and factors associated with reporting accuracy.
Methods: Direct observations of home visits conducted by community workers in 40 villages in Bihar, India, served as the “gold standard” to maternal report of IYCF counseling received during 2-week follow-up surveys (n=444 mothers with children less than 1 year of age, interviews matched to direct observations). Individual-level validity was assessed by calculating sensitivity, specificity, and area under ROC curve (AUC). Population-level bias was measured using the inflation factor (IF). Multivariable regression models were used to examine factors associated with response accuracy.
Results: Prevalence of IYCF counseling during home visits was very high (90.1%). Maternal report of any IYCF counseling received in the past 2 weeks was moderate (AUC=0.60, 95% CI: 0.52, 0.67), and population bias was low (IF=0.90). However, recall of specific counseling messages varied. Maternal report of any breastfeeding, exclusive breastfeeding, and dietary diversity messages had moderate validity (AUC>0.60), but other child feeding messages had low individual validity. Child age, maternal age, maternal education, mental stress, and social desirability were associated with reporting accuracy of multiple indicators.
Conclusions: Validity of IYCF counseling coverage was moderate for several key indicators. IYCF counseling is an information-based intervention that may be received from various sources, and it may be challenging to achieve higher reporting accuracy over a longer recall period. We consider the modest validity results as positive and suggest that these coverage indicators may be useful for measuring coverage and tracking progress over time.
S. J., Balaji; Sharma, Purushottam; P., Venkatesh; Kapoor, Shreya. New Delhi, India 2022
import tariffs.
Smith, Lisa C.; Byron, Elizabeth. Washington, DC 2005
Karyadi, Elvina; Reddy, J. C.; Dearden, Kirk A.; Purwanti, Tutut; Asri, Eriana; Roquero, Loreto B.; Juguan, Jocelyn A.; Sapitula-Evidente, Anjali; Alam, M. K.; Das, Susmita; Nair, Gopa K.; Srivastava, Anuj; Raut, Manoj K.. 2023
Gune, Soyra; Christopher, Anita; Scott, Samuel; Nguyen, Phuong Hong; Joe, William; Singh, S. K.; Dwivedi, L. K.; Pedgaonkar, Sarang; Puri, Parul; Chauhan, Alka; Yadav, Kapil; Chamois, Sylvie . New Delhi, India 2023
Christopher, Anita; Gune, Soyra; Avula, Rasmi; Nguyen, Phuong Hong; Menon, Purnima; Singh, S. K.; Dwivedi, L. K.; Pedgaonkar, Sarang; Puri, Parul; Chauhan, Alka; . New Delhi, India 2023
Kapoor, Rati; Singh, Nishmeet; Nguyen, Phuong Hong; Singh, S. K. ; Dwivedi, L. K.; Pedgaonkar, Sarang; Puri, Parul; Chauhan, Alka; Khandelwal, Shweta; Chamois, Sylvie. New Delhi, India 2023
Takeshima, Hiroyuki; Saroj, Sunil; Kumar, Anjani. Washington, DC 2023
ElDidi, Hagar; Khurana, Ritika; Zhang, Wei; Jadav, Maheshkumar Kalidas; Guha, Chiranjit; Priyadarshini, Pratiti; Guo, Zhe; Sandhu, Harpinder; Nagendra, Harini; Meinzen-Dick, Ruth Suseela. Washington, DC 2023
Narayanan, Sudha. 2022
Gupta, Manavi; Kishore, Avinash; Scott, Samuel; Chakraborty, Shreya; Chellattan, Prakashan Veettil; Choudhury, Samira; Krupnik, Timothy; Kumar, Neha; Neupane, Sumanta; Patwardhan, Sharvari; Sununtnasuk, Celeste; Urfels, Anton; Menon, Purnima. Washington, DC 2022
TAFSSA (Transforming Agrifood Systems in South Asia), a CGIAR Regional Integrated Initiative, aims to address these challenges by delivering actionable evidence and scalable innovations across these regions through a coordinated program of research and engagement from farmer to consumer.
One of the roadblocks to addressing these challenges is the lack of credible and high-resolution data on food systems in the region. The TAFSSA food systems assessment aims to provide a reliable, accessible and integrated evidence base that links farm production, market access, dietary patterns, climate risk responses, and natural resource management in Bangladesh, India, Nepal and Pakistan. It is intended to be a multi-year assessment.
Scott, Samuel; Neupane, Sumanta; Menon, Purnima; Kishore, Avinash; Krupnik, Timothy. Washington, DC 2022
This research note presents findings on the availability of diet-related data in publiclyavailable population-based surveys conducted in Bangladesh, India, Nepal, and Pakistan in the last decade. It is intended to be used by researchers and policymakers to understand the data landscape and identify measurement priorities for future surveys.
KEY FINDINGS
• Data on diets for older children and adolescents are captured less frequently than
for younger children and women of reproductive age.
• Data are mostly available on food group consumption and for infants and young
children; data on consumption of unhealthy foods is poor.
• Few surveys capture quantity of foods consumed; estimating nutrient intake from
population-based surveys is therefore not possible.
• Only Bangladesh currently has large-scale publicly available and repeated rounds of
data on dietary intakes for multiple age groups.
• Dietary data are essential to shape public policy on nutrition; financial and technical
investments are needed to scale up data availability in South Asia.
Vos, Rob; Martin, Will; Resnick, Danielle. Washington, D.C. 2022
Barooah, Prapti; Alvi, Muzna Fatima; Ringler, Claudia; Pathak, Vishal. Washington, D.C. 2022
Patwardhan, Sharvari; Kapoor, Rati; Scott, Samuel; Nguyen, Phuong Hong; Chamois, Sylvie; Singh, S.K.; Dwivedi, L.K.; Pedgaonkar, Sarang; Puri, Parul; Chauhan, Alka; Laxmaiah, Avula; Menon, Purnima . New Delhi, India 2023
MEASUREMENT| NFHS asks women (15-49 years) and men (15-54 years) how frequently (daily, weekly, occasionally or never) they consume nine food groups including two unhealthy food groups (Figure 1). The 2020 Nutrient Requirements for Indiansoutlines the quantity per day of vegetarian foods to be consumed as part of a balanced diet (ICMR-NIN, 2020). The guidelines indicate that pulses can be replaced with animal-source foods for non-vegetarians. Thus, for this Data Note we constructed an additional indicator –daily consumption of pulses or egg or fish or chicken or meat –to estimate any protein consumption (Figure 1). Estimates are first presented at the national levelto provide an overall view of how diets have changed from 2005-06 to 2019-21. On subsequent pages, we show trends between 2015-16 and 2019-21 by stateand district.
USE| This data note provides a broad view of diet patterns among adults and should be used for further inquiry by stakeholders including researchers, policymakers, and program staff at multiple levels. We recognize that NFHS is not a detailed dietary survey and does not ask about individual food items or the quantity of food consumed. Thus, this data note should be used as a starting point for discussion and to identify major areas of improvement in consumption and measurement.
Neupane, Sumanta; Nguyen, Phuong Hong; Avula, Rasmi. New Delhi, India 2022
• Women’s diet is one of the immediate determinants of maternal and child nutrition
Objectives
• Examine dietary intake of women with children <2 years of age • Examine inequity in dietary intake by wealth status • Assess the role of food or cash transfers in maternal diet diversity Methods • Data came from a phone survey of 6,227 women in six states of India. • Dietary intake was assessed using the diet quality questionnaire which was then recategorized to calculate score for food diversity, consumption of healthy and unhealthy foods, and minimum diet diversity (MDD) for women. • Inequity in dietary intake was examined using wealth quintiles • Association between food and cash transfer on maternal diet was examined using multivariate regression analysis controlling for maternal, child, households' factors and state fixed effects.
Ray, Soumyjit; Singh, Ram. Delhi, India 2022
Ghosh, Parijat; Babu, Suresh Chandra; Debnath, Deepayan; Paneru, Khyam. 2022
Objective: The objective of the study was to investigate whether the chosen targeted extension package would significantly increase farmers’ rice yields or not.
Materials and Methods: We estimated a multiple linear regression model to determine the effect of several independent variables, including plot size, amount of money borrowed, and farmers’ income on the rice yield.
Results: We found that the rice yield among the farmers who received the extension package had increased compared to the group of farmers with no extension support. The regression coefficient of extension (1 = yes, 0 = no) is statistically significant (p-value = 0.063) at a 10% level of significance.
Conclusion: Assessing the impact of the targeted extension package on the farmers is important in utilizing good agricultural practices to increase rice productivity. We concluded that a targeted extension program is crucial for increasing rice yield among rural farmers in Southern India.
Patra, Nirmal K.; Babu, Suresh Chandra. 2023
Gupta, Manavi; Kishore, Avinash; Roy, Devesh; Saroj, Sunil. 2023
Avula, Rasmi, ed.. New Delhi, India 2022
Nguyen-Viet, Hung; Hoffmann, Vivian; Bett, Bernard; Fèvre, Eric; Moodley, Arshnee; Mateo-Sagasta, Javier; Mohan, Chadag; Daszak, Peter; Bonfoh, Bassirou. Nairobi, Kenya 2022
Sandhu, Harpinder; Zhang, Wei; Meinzen-Dick, Ruth Suseela; ElDidi, Hagar; Perveen, Saiqa; Sharma, Janvi; Kaur, Japneet; Priyadarshini, Pratiti. 2023
Zhang, Wei; Meinzen-Dick, Ruth Suseela; Valappanandi, Sanoop; Balakrishna, Raksha; Reddy, Hemalatha; Janssen, Marco A.; Thomas, Liya. 2022
Raghunathan, Kalyani; Kumar, Neha; Gupta, Shivani; Thai, Giang; Scott, Samuel; Choudhury, Avijit; Khetan, Madhu; Menon, Purnima; Quisumbing, Agnes R.. 2023
Bathla, Seema; Kumar, Anjani; Saroj, Sunil; Kumar, Ashutosh; Gupta, Neha. Mumbai, India 2022
Karachiwalla, Naureen; Kosec, Katrina; Kyle, Jordan; Narayanan, Sudha; Raghunathan, Kalyani. Washington, DC 2022
Yet, in the long history of public works programs, there has been limited research on how assets created under such workfare programs are selected, or how to increase the role of women or other marginalized groups in the decision-making process. The Act provides a list of permissible works that span natural resource management, individual and community assets, common infrastructure for women’s groups, and rural infrastructure more broadly. Given the scale of the program, the assets selected at the village level have tremendous potential to enhance rural resilience to unexpected shocks and crises, especially those related to climate change. This is important, as extreme weather events on the Indian subcontinent are increasing, both in frequency and in the magnitude of their impacts on agricultural productivity, household livelihoods, assets and incomes, and health and nutrition. These events, as well as their impacts on incomes, often affect women more severely (Mason and Agan 2015; Kosec et al. forthcoming).
Understanding how to enhance women’s voice and agency within the process of selecting community assets is important for three major reasons. First, women and men may have different asset preferences (Chattopadhyay and Duflo 2004). Recent time-use survey data from India find that women spend far more time on unpaid domestic and care work than men (eight times as much) (India, NSO 2019). Thus, women may place relatively more value on projects that reduce effort in collecting fuel and water, for example. If their voices are not included in the asset selection process, the village could miss out on a range of development projects that would improve overall productivity, resilience, and well-being. Second, where projects are built affects who benefits from them. Households that had MGNREGA assets built on their own land or that live near an asset cultivate more land, use more inputs (including their own labor), and have higher agricultural output (Gehrke 2015; Muralidharan et al. 2021). Ensuring that women influence asset placement is thus critical. Third, greater participation and inclusivity in the process of selecting community development projects can increase the perceived legitimacy and satisfaction with projects, as well as willingness to contribute toward their construction and maintenance (Olken 2010). Within MGNREGA, households that report playing a greater role in project selection also report greater satisfaction with the usefulness, quality, and maintenance of the projects (Ranaware et al. 2015).
Takeshima, Hiroyuki; Raghunathan, Kalyani; Kosec, Katrina. Washington, DC 2022
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Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Singh, Nishmeet; Nguyen, Phuong Hong; Jangid, Manita; Singh, Sudhir K.; Sarwal, Rakesh; Bhatia, Neena; Johnston, Robert; Joe, William; Menon, Purnima. New Delhi, India 2022
Ahmed, Akhter; Bakhtiar, M. Mehrab; Anowar, Sadat; Rahman, Mohammad Moshiur. Dhaka, Bangladesh 2021
Kishore, Avinash; McDonald, Andrew J.; Keil, Alwin; Srivastava, Amit; Craufurd, Peter; Kumar, Virender. 2022
Varshney, Deepak; Mishra, Ashok K.; Joshi, Pramod Kumar; Roy, Devesh. 2022
Patwardhan, Shavari; Tasciotti, Luca. 2023
Kumar, Shalander; Patan, Elias Khan; Pal, Barun Deb. 2023
Jha, Chandan Kumar; Ghosh, Ranjan Kumar; Saxena, Satyam; Singh, Vartika; Mosnier, Aline; Guzman, Katya Perez; Stevanović, Miodrag; Popp, Alexander; Lotze-Campen, Hermann. 2023
Nyangaresi, Annette M.; Friesen, Valerie M.; McClafferty, Bonnie; van der Merwe, Charl; Haswell, Daniel; Reyes, Byron; Mudyahoto, Bho; Mbuya, Mduduzi N. N.. Geneva, Switzerland 2022
Friesen, Valerie M; Mudyahoto, Bho; Birol, Ekin; Nyangaresi, Annette M; Reyes, Byron; Mbuya, Mduduzi N. N.. Geneva, Switzerland 2022
Saroj, Sunil; Kumar, Anjani; Joshi, Pramod Kumar. 2022
Varshney, Deepak; Joshi, Pramod Kumar; Kumar, Anjani; Mishra, Ashok K.; Dubey, Shantanu Kumar. 2022
Avula, Rasmi; Nguyen, Phuong Hong; Ashok, Sattvika; Sumati, Baja; Pant, Anjali; Walia, Monika; Kachwaha, Shivani; et al. 2022
Joshi, P. K.; Varshney, Deepak. Mumbai, India 2022
Patil, Sumeet R.; Nimmagadda, Sneha; Gopalakrishnan, Lakshmi; Avula, Rasmi; Bajaj, Sumati; Diamond-Smith, Nadia; Paul, Anushman; Menon, Purnima; Walker, Dilys. 2022
Place, Frank; Nierderle, Paulo; Sinclair, Fergus; Estrada Carmona, Natalia; Guéneau, Stéphane; Gitz, Vincent; Alpha, Arlene; Sabourin, Eric; Hainzelin, Etienne. Bogor, Indonesia 2022
Wenger, Michael J.; Murray-Kolb, Laura E.; Scott, Samuel; Boy, Erick; Haas, Jere D.. 2022
Methods: Male and female adolescents in rural India were screened for ID/IDA. Subjects consumed 2 meals/day for 6 months; half were randomly assigned to consume meals made from a standard grain (pearl millet) and half consumed meals made from an iron biofortified pearl millet (BPM). Prior to and then at the conclusion of the feeding trial, they completed a set of cognitive tests with concurrent electroencephalography (EEG).
Results: Overall, serum ferritin (sFt) levels improved over the course of the study. Ten of 21 possible measures of cognition showed improvements from baseline (BL) to endline (EL) that were larger for those consuming BPM than for those consuming the comparison pearl millet (CPM). Critically, the best model for the relationship between change in iron status and change in cognition had change in brain measures as a mediating factor, with both change in serum ferritin as a primary predictor and change in hemoglobin as a moderator.
Conclusions: A dietary intervention involving a biofortified staple grain was shown to be efficacious in improving blood iron biomarkers, behavioral measures of cognition, and EEG measures of brain function. Modeling the relationships among these variables strongly suggests multiple mechanisms by which blood iron level affects brain function and cognition.
Hughes, Karl Alan; Priyadarshini, Pratiti; Sharma, Himani; Lissah, Sanoop; Chorran, Tenzin; Meinzen-Dick, Ruth Suseela; Dogra, Atul; Cook, Nathan; Andersson, Krister. 2022
Saxena, Reka; Kumar, Anjani; Singh, Ritambhara; Paul, Ranjit Kumar; Raman, M. S.; Kumar, Rohit; Khan, Mohd Arshad; Agarwal, Priyanka. Article in press
Scott, Samuel; Lahiri, Anwesha; Sethi, Vani; de Wagt, Arjan; Menon, Purnima; Yadav, Kapil; Varghese, Mini; Joe, William; Vir, Sheila C.; Nguyen, Phuong Hong. 2022
Jha, Chandan Kumar; Singh, Vartika; Stevanovi´c, Miodrag; Dietrich, Jan Philipp; Mosnier, Aline. 2022
Roy, Devesh; Saroj, Sunil; Pradhan, Mamata. 2022
Sanghvi, Tina; Nguyen, Phuong Hong; Ghosh, Sebanti; Zafimanjaka, Maurice; Kim, Sunny S.. 2022
Saroj, Sunil; Pradhan, Mamata; Boss, Ruchira; Roy, Devesh. 2022
S. J., Balaji; Babu, Suresh Chandra. 2022
Kumar, Anjani; Sonkar, Vinay Kumar; Bathla, Seema. 2022
Kumar, Anjani; Mishra, Ashok K.; Saroj, Sunil; Rashid, Shahidur. 2022
Aggarwal, Nidhi; Narayanan, Sudha. 2023
Kumar, Anjani; Verma, Smriti; Saroj, Sunil; Prasad, Amit Mohan; Kishore, Avinash. 2023
Kishore, Avinash; Saini, Smriti; Alvi, Muzna Fatima. 2022
Scott, Samuel; Gupta, Shivani; Menon, Purnima; Raghunathan, Kalyani; Thai, Giang; Quisumbing, Agnes R.; Kumar, Neha. 2022
Objective: To understand the effects of a nutrition BCC intervention delivered through SHGs in rural India on intermediate outcomes and nutrition outcomes.
Methods: We compared 16 matched blocks where communities were supported to form SHGs and improve livelihoods; 8 blocks received a 3-year nutrition intensive (NI) intervention with nutrition BCC, agriculture- and rights-based information, facilitated by a trained female volunteer; another 8 blocks received standard activities (STD) to support savings/livelihoods. Repeated cross-sectional surveys of mother-child pairs were conducted in 2017-18 (n = 1609 pairs) and 2019-20 (n = 1841 pairs). We matched treatment groups over time and applied difference-in-difference regression models to estimate impacts on intermediate outcomes (knowledge, income, agriculture/livelihoods, rights, empowerment) and nutrition outcomes (child feeding, woman's diet, woman and child anthropometry). Analyses were repeated on households with at least one SHG member.
Results: 40% of women were SHG members and 50% were from households with at least one SHG member. Only 10% of women in NI blocks had heard of intervention content at endline. Knowledge improved in both NI and STD groups. There was a positive NI impact on knowledge of timely introduction of animal sourced foods to children (p<0.05) but not on other intermediate outcomes. No impacts were observed for anthropometry or diet indicators except child animal source food consumption (p<0.01). In households with at least one SHG member, there was a positive NI impact on child unhealthy food consumption (p<0.05). Conclusions: Limited impacts may be due to limited exposure or skills of volunteers, and a concurrent national nutrition campaign. Our findings add to a growing literature on SHG-based BCC interventions and the conditions necessary for their success.
Ratner, Blake D.; Larson, Anne M.; Barletti, Juan Pablo Sarmiento; ElDidi, Hagar; Catacutan, Delia; Meinzen-Dick, Ruth Suseela. 2022
Avula, Rasmi; Nguyen, Phuong Hong; Tran, Lan Mai; Kaur, Supreet; Bhatia, Neena; Sarwal, Rakesh; de Wagt, Arjan; Chaudhery, Deepika Nayar; Menon, Purnima. 2022