Status and determinants of intra-household food allocation in rural Nepal
Background/objectives Understanding of the patterns and predictors of intra-household food allocation could enable nutrition programmes to better target nutritionally vulnerable individuals. This study aims to characterise the status and determinants of intra-household food and nutrient allocation i...
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| Veröffentlicht in: | European journal of clinical nutrition 2018-11, Vol.72 (11), p.1524-1536 |
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| creator | Harris-Fry, Helen A. Paudel, Puskar Shrestha, Niva Harrisson, Tom Beard, B. James Jha, Sonali Shrestha, Bhim P. Manandhar, Dharma S. Costello, Anthony M. D. L. Cortina-Borja, Mario Saville, Naomi M. |
| description | Background/objectives
Understanding of the patterns and predictors of intra-household food allocation could enable nutrition programmes to better target nutritionally vulnerable individuals. This study aims to characterise the status and determinants of intra-household food and nutrient allocation in Nepal.
Subjects/methods
Pregnant women, their mothers-in-law and male household heads from Dhanusha and Mahottari districts in Nepal responded to 24-h dietary recalls, thrice repeated on non-consecutive days (
n
= 150 households; 1278 individual recalls). Intra-household inequity was measured using ratios between household members in food intakes (food shares); food-energy intake proportions (‘food shares-to-energy shares’, FS:ES); calorie-requirement proportions (‘relative dietary energy adequacy ratios’, RDEARs) and mean probability of adequacy for 11 micronutrients (MPA ratios). Hypothesised determinants were collected during the recalls, and their associations with the outcomes were tested using multivariable mixed-effects linear regression models.
Results
Women’s diets (pregnant women and mothers-in-law) consisted of larger FS:ES of starchy foods, pulses, fruits and vegetables than male household heads, whereas men had larger FS:ES of animal-source foods. Pregnant women had the lowest MPA (37%) followed by their mothers-in-law (52%), and male household heads (57%). RDEARs between pregnant women and household heads were 31% higher (log-RDEAR coeff=0.27 (95% CI 0.12, 0.42),
P
|
| doi_str_mv | 10.1038/s41430-017-0063-0 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_5924867</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A572600333</galeid><sourcerecordid>A572600333</sourcerecordid><originalsourceid>FETCH-LOGICAL-c595t-70de4092952eb39f3f2d303cffa50264330799888574dff95137b432878cc3073</originalsourceid><addsrcrecordid>eNp1kUuLFDEUhYMoTjv6A9xIgSBuSm9yk0plIwyDj4FBF-o6pKuSrhrSSZtUDfjvTehxHoKrLM6Xc--5h5CXFN5RwP595pQjtEBlC9BhC4_IhnLZtaLj8JhsQAneIoA8Ic9yvgIoomRPyQlTKPoOcEMuvi9mWXNjwtiMdrFpPwcTltxE18xhSaad4prtFP3YuBjHxngfB7PMMRS9SWsyvvlqD8Y_J0-c8dm-uHlPyc9PH3-cf2kvv32-OD-7bAehxNJKGC0HxZRgdovKoWMjAg7OGQGs44ggler7Xkg-OqcERbnlyHrZD0PR8JR8OPoe1u3ejoOtW3p9SPPepN86mlk_VMI86V281kIx3nfV4O2NQYq_VpsXvZ_zYL03wZasmioFvC-DoaCv_0Gv4ppCiacZrYsiF3hH7Yy3eg4ulrlDNdVnQrIOALFSb-5RkzV-mXL0az1lfgjSIzikmHOy7jYbBV1718fedeld1951XfTV_aPc_vhbdAHYEchFCjub7pL83_UPC4G1UA</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2130793453</pqid></control><display><type>article</type><title>Status and determinants of intra-household food allocation in rural Nepal</title><source>MEDLINE</source><source>SpringerLink Journals</source><creator>Harris-Fry, Helen A. ; Paudel, Puskar ; Shrestha, Niva ; Harrisson, Tom ; Beard, B. James ; Jha, Sonali ; Shrestha, Bhim P. ; Manandhar, Dharma S. ; Costello, Anthony M. D. L. ; Cortina-Borja, Mario ; Saville, Naomi M.</creator><creatorcontrib>Harris-Fry, Helen A. ; Paudel, Puskar ; Shrestha, Niva ; Harrisson, Tom ; Beard, B. James ; Jha, Sonali ; Shrestha, Bhim P. ; Manandhar, Dharma S. ; Costello, Anthony M. D. L. ; Cortina-Borja, Mario ; Saville, Naomi M.</creatorcontrib><description>Background/objectives
Understanding of the patterns and predictors of intra-household food allocation could enable nutrition programmes to better target nutritionally vulnerable individuals. This study aims to characterise the status and determinants of intra-household food and nutrient allocation in Nepal.
Subjects/methods
Pregnant women, their mothers-in-law and male household heads from Dhanusha and Mahottari districts in Nepal responded to 24-h dietary recalls, thrice repeated on non-consecutive days (
n
= 150 households; 1278 individual recalls). Intra-household inequity was measured using ratios between household members in food intakes (food shares); food-energy intake proportions (‘food shares-to-energy shares’, FS:ES); calorie-requirement proportions (‘relative dietary energy adequacy ratios’, RDEARs) and mean probability of adequacy for 11 micronutrients (MPA ratios). Hypothesised determinants were collected during the recalls, and their associations with the outcomes were tested using multivariable mixed-effects linear regression models.
Results
Women’s diets (pregnant women and mothers-in-law) consisted of larger FS:ES of starchy foods, pulses, fruits and vegetables than male household heads, whereas men had larger FS:ES of animal-source foods. Pregnant women had the lowest MPA (37%) followed by their mothers-in-law (52%), and male household heads (57%). RDEARs between pregnant women and household heads were 31% higher (log-RDEAR coeff=0.27 (95% CI 0.12, 0.42),
P
< 0.001) when pregnant women earned more or the same as their spouse, and log-MPA ratios between pregnant women and mothers-in-law were positively associated with household-level calorie intakes (coeff=0.43 (0.23, 0.63),
P
< 0.001, per 1000 kcal).
Conclusions
Pregnant women receive inequitably lower shares of food and nutrients, but this could be improved by increasing pregnant women’s cash earnings and household food security.</description><identifier>ISSN: 0954-3007</identifier><identifier>EISSN: 1476-5640</identifier><identifier>DOI: 10.1038/s41430-017-0063-0</identifier><identifier>PMID: 29358603</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>692/308/174 ; 692/699/1702/295 ; Adequacy ; Adolescent ; Adult ; Animal-based foods ; Clinical Nutrition ; Diet ; Energy Intake ; Epidemiology ; Family Characteristics ; Family Relations ; Feeding Behavior ; Female ; Food ; Food and nutrition ; Food intake ; Food security ; Food sources ; Food Supply ; Households ; Humans ; Income ; Internal Medicine ; Male ; Medicine ; Medicine & Public Health ; Metabolic Diseases ; Micronutrients ; Micronutrients - administration & dosage ; Middle Aged ; Nepal ; Nutrient status ; Nutrients ; Nutrition ; Nutritional Requirements ; Nutritional Status ; Pregnancy ; Pregnant women ; Public Health ; Regression analysis ; Regression models ; Rural Population ; Sex Factors ; Statistical analysis ; Stock prices ; Young Adult</subject><ispartof>European journal of clinical nutrition, 2018-11, Vol.72 (11), p.1524-1536</ispartof><rights>The Author(s) 2018</rights><rights>COPYRIGHT 2018 Nature Publishing Group</rights><rights>2018. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c595t-70de4092952eb39f3f2d303cffa50264330799888574dff95137b432878cc3073</citedby><cites>FETCH-LOGICAL-c595t-70de4092952eb39f3f2d303cffa50264330799888574dff95137b432878cc3073</cites><orcidid>0000-0003-2367-908X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1038/s41430-017-0063-0$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1038/s41430-017-0063-0$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29358603$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Harris-Fry, Helen A.</creatorcontrib><creatorcontrib>Paudel, Puskar</creatorcontrib><creatorcontrib>Shrestha, Niva</creatorcontrib><creatorcontrib>Harrisson, Tom</creatorcontrib><creatorcontrib>Beard, B. James</creatorcontrib><creatorcontrib>Jha, Sonali</creatorcontrib><creatorcontrib>Shrestha, Bhim P.</creatorcontrib><creatorcontrib>Manandhar, Dharma S.</creatorcontrib><creatorcontrib>Costello, Anthony M. D. L.</creatorcontrib><creatorcontrib>Cortina-Borja, Mario</creatorcontrib><creatorcontrib>Saville, Naomi M.</creatorcontrib><title>Status and determinants of intra-household food allocation in rural Nepal</title><title>European journal of clinical nutrition</title><addtitle>Eur J Clin Nutr</addtitle><addtitle>Eur J Clin Nutr</addtitle><description>Background/objectives
Understanding of the patterns and predictors of intra-household food allocation could enable nutrition programmes to better target nutritionally vulnerable individuals. This study aims to characterise the status and determinants of intra-household food and nutrient allocation in Nepal.
Subjects/methods
Pregnant women, their mothers-in-law and male household heads from Dhanusha and Mahottari districts in Nepal responded to 24-h dietary recalls, thrice repeated on non-consecutive days (
n
= 150 households; 1278 individual recalls). Intra-household inequity was measured using ratios between household members in food intakes (food shares); food-energy intake proportions (‘food shares-to-energy shares’, FS:ES); calorie-requirement proportions (‘relative dietary energy adequacy ratios’, RDEARs) and mean probability of adequacy for 11 micronutrients (MPA ratios). Hypothesised determinants were collected during the recalls, and their associations with the outcomes were tested using multivariable mixed-effects linear regression models.
Results
Women’s diets (pregnant women and mothers-in-law) consisted of larger FS:ES of starchy foods, pulses, fruits and vegetables than male household heads, whereas men had larger FS:ES of animal-source foods. Pregnant women had the lowest MPA (37%) followed by their mothers-in-law (52%), and male household heads (57%). RDEARs between pregnant women and household heads were 31% higher (log-RDEAR coeff=0.27 (95% CI 0.12, 0.42),
P
< 0.001) when pregnant women earned more or the same as their spouse, and log-MPA ratios between pregnant women and mothers-in-law were positively associated with household-level calorie intakes (coeff=0.43 (0.23, 0.63),
P
< 0.001, per 1000 kcal).
Conclusions
Pregnant women receive inequitably lower shares of food and nutrients, but this could be improved by increasing pregnant women’s cash earnings and household food security.</description><subject>692/308/174</subject><subject>692/699/1702/295</subject><subject>Adequacy</subject><subject>Adolescent</subject><subject>Adult</subject><subject>Animal-based foods</subject><subject>Clinical Nutrition</subject><subject>Diet</subject><subject>Energy Intake</subject><subject>Epidemiology</subject><subject>Family Characteristics</subject><subject>Family Relations</subject><subject>Feeding Behavior</subject><subject>Female</subject><subject>Food</subject><subject>Food and nutrition</subject><subject>Food intake</subject><subject>Food security</subject><subject>Food sources</subject><subject>Food Supply</subject><subject>Households</subject><subject>Humans</subject><subject>Income</subject><subject>Internal Medicine</subject><subject>Male</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Metabolic Diseases</subject><subject>Micronutrients</subject><subject>Micronutrients - administration & dosage</subject><subject>Middle Aged</subject><subject>Nepal</subject><subject>Nutrient status</subject><subject>Nutrients</subject><subject>Nutrition</subject><subject>Nutritional Requirements</subject><subject>Nutritional Status</subject><subject>Pregnancy</subject><subject>Pregnant women</subject><subject>Public Health</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Rural Population</subject><subject>Sex Factors</subject><subject>Statistical analysis</subject><subject>Stock prices</subject><subject>Young Adult</subject><issn>0954-3007</issn><issn>1476-5640</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp1kUuLFDEUhYMoTjv6A9xIgSBuSm9yk0plIwyDj4FBF-o6pKuSrhrSSZtUDfjvTehxHoKrLM6Xc--5h5CXFN5RwP595pQjtEBlC9BhC4_IhnLZtaLj8JhsQAneIoA8Ic9yvgIoomRPyQlTKPoOcEMuvi9mWXNjwtiMdrFpPwcTltxE18xhSaad4prtFP3YuBjHxngfB7PMMRS9SWsyvvlqD8Y_J0-c8dm-uHlPyc9PH3-cf2kvv32-OD-7bAehxNJKGC0HxZRgdovKoWMjAg7OGQGs44ggler7Xkg-OqcERbnlyHrZD0PR8JR8OPoe1u3ejoOtW3p9SPPepN86mlk_VMI86V281kIx3nfV4O2NQYq_VpsXvZ_zYL03wZasmioFvC-DoaCv_0Gv4ppCiacZrYsiF3hH7Yy3eg4ulrlDNdVnQrIOALFSb-5RkzV-mXL0az1lfgjSIzikmHOy7jYbBV1718fedeld1951XfTV_aPc_vhbdAHYEchFCjub7pL83_UPC4G1UA</recordid><startdate>20181101</startdate><enddate>20181101</enddate><creator>Harris-Fry, Helen A.</creator><creator>Paudel, Puskar</creator><creator>Shrestha, Niva</creator><creator>Harrisson, Tom</creator><creator>Beard, B. James</creator><creator>Jha, Sonali</creator><creator>Shrestha, Bhim P.</creator><creator>Manandhar, Dharma S.</creator><creator>Costello, Anthony M. D. 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James ; Jha, Sonali ; Shrestha, Bhim P. ; Manandhar, Dharma S. ; Costello, Anthony M. D. L. ; Cortina-Borja, Mario ; Saville, Naomi M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c595t-70de4092952eb39f3f2d303cffa50264330799888574dff95137b432878cc3073</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>692/308/174</topic><topic>692/699/1702/295</topic><topic>Adequacy</topic><topic>Adolescent</topic><topic>Adult</topic><topic>Animal-based foods</topic><topic>Clinical Nutrition</topic><topic>Diet</topic><topic>Energy Intake</topic><topic>Epidemiology</topic><topic>Family Characteristics</topic><topic>Family Relations</topic><topic>Feeding Behavior</topic><topic>Female</topic><topic>Food</topic><topic>Food and nutrition</topic><topic>Food intake</topic><topic>Food security</topic><topic>Food sources</topic><topic>Food Supply</topic><topic>Households</topic><topic>Humans</topic><topic>Income</topic><topic>Internal Medicine</topic><topic>Male</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Metabolic Diseases</topic><topic>Micronutrients</topic><topic>Micronutrients - administration & dosage</topic><topic>Middle Aged</topic><topic>Nepal</topic><topic>Nutrient status</topic><topic>Nutrients</topic><topic>Nutrition</topic><topic>Nutritional Requirements</topic><topic>Nutritional Status</topic><topic>Pregnancy</topic><topic>Pregnant women</topic><topic>Public Health</topic><topic>Regression analysis</topic><topic>Regression models</topic><topic>Rural Population</topic><topic>Sex Factors</topic><topic>Statistical analysis</topic><topic>Stock prices</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Harris-Fry, Helen A.</creatorcontrib><creatorcontrib>Paudel, Puskar</creatorcontrib><creatorcontrib>Shrestha, Niva</creatorcontrib><creatorcontrib>Harrisson, Tom</creatorcontrib><creatorcontrib>Beard, B. James</creatorcontrib><creatorcontrib>Jha, Sonali</creatorcontrib><creatorcontrib>Shrestha, Bhim P.</creatorcontrib><creatorcontrib>Manandhar, Dharma S.</creatorcontrib><creatorcontrib>Costello, Anthony M. D. L.</creatorcontrib><creatorcontrib>Cortina-Borja, Mario</creatorcontrib><creatorcontrib>Saville, Naomi M.</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Neurosciences Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>British Nursing Database</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Biological Science Database</collection><collection>Research Library (Corporate)</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest Central (New)</collection><collection>ProQuest One Academic (New)</collection><collection>ProQuest Health & Medical Research Collection</collection><collection>ProQuest One Academic Middle East (New)</collection><collection>ProQuest One Health & Nursing</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Applied & Life Sciences</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>European journal of clinical nutrition</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Harris-Fry, Helen A.</au><au>Paudel, Puskar</au><au>Shrestha, Niva</au><au>Harrisson, Tom</au><au>Beard, B. James</au><au>Jha, Sonali</au><au>Shrestha, Bhim P.</au><au>Manandhar, Dharma S.</au><au>Costello, Anthony M. D. L.</au><au>Cortina-Borja, Mario</au><au>Saville, Naomi M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Status and determinants of intra-household food allocation in rural Nepal</atitle><jtitle>European journal of clinical nutrition</jtitle><stitle>Eur J Clin Nutr</stitle><addtitle>Eur J Clin Nutr</addtitle><date>2018-11-01</date><risdate>2018</risdate><volume>72</volume><issue>11</issue><spage>1524</spage><epage>1536</epage><pages>1524-1536</pages><issn>0954-3007</issn><eissn>1476-5640</eissn><abstract>Background/objectives
Understanding of the patterns and predictors of intra-household food allocation could enable nutrition programmes to better target nutritionally vulnerable individuals. This study aims to characterise the status and determinants of intra-household food and nutrient allocation in Nepal.
Subjects/methods
Pregnant women, their mothers-in-law and male household heads from Dhanusha and Mahottari districts in Nepal responded to 24-h dietary recalls, thrice repeated on non-consecutive days (
n
= 150 households; 1278 individual recalls). Intra-household inequity was measured using ratios between household members in food intakes (food shares); food-energy intake proportions (‘food shares-to-energy shares’, FS:ES); calorie-requirement proportions (‘relative dietary energy adequacy ratios’, RDEARs) and mean probability of adequacy for 11 micronutrients (MPA ratios). Hypothesised determinants were collected during the recalls, and their associations with the outcomes were tested using multivariable mixed-effects linear regression models.
Results
Women’s diets (pregnant women and mothers-in-law) consisted of larger FS:ES of starchy foods, pulses, fruits and vegetables than male household heads, whereas men had larger FS:ES of animal-source foods. Pregnant women had the lowest MPA (37%) followed by their mothers-in-law (52%), and male household heads (57%). RDEARs between pregnant women and household heads were 31% higher (log-RDEAR coeff=0.27 (95% CI 0.12, 0.42),
P
< 0.001) when pregnant women earned more or the same as their spouse, and log-MPA ratios between pregnant women and mothers-in-law were positively associated with household-level calorie intakes (coeff=0.43 (0.23, 0.63),
P
< 0.001, per 1000 kcal).
Conclusions
Pregnant women receive inequitably lower shares of food and nutrients, but this could be improved by increasing pregnant women’s cash earnings and household food security.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>29358603</pmid><doi>10.1038/s41430-017-0063-0</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0003-2367-908X</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | European journal of clinical nutrition, 2018-11, Vol.72 (11), p.1524-1536 |
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| language | eng |
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| source | MEDLINE; SpringerLink Journals |
| subjects | 692/308/174 692/699/1702/295 Adequacy Adolescent Adult Animal-based foods Clinical Nutrition Diet Energy Intake Epidemiology Family Characteristics Family Relations Feeding Behavior Female Food Food and nutrition Food intake Food security Food sources Food Supply Households Humans Income Internal Medicine Male Medicine Medicine & Public Health Metabolic Diseases Micronutrients Micronutrients - administration & dosage Middle Aged Nepal Nutrient status Nutrients Nutrition Nutritional Requirements Nutritional Status Pregnancy Pregnant women Public Health Regression analysis Regression models Rural Population Sex Factors Statistical analysis Stock prices Young Adult |
| title | Status and determinants of intra-household food allocation in rural Nepal |
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