|Year : 2019 | Volume
| Issue : 3 | Page : 203-208
Are household food security, nutrient adequacy, and childhood nutrition clustered together? A cross-sectional study in Bankura, West Bengal
Satabdi Mitra1, Dipta Kanti Mukhopadhyay2, Aditya Prasad Sarkar3, Indrajit Saha4
1 Assistant Professor, Department of Community Medicine, JG Institute of Medical Sciences, Kolkata, West Bengal, India
2 Associate Professor, Department of Community Medicine, College of Medicine and Sagore Dutta Hospital, Kolkata, West Bengal, India
3 Associate Professor, Department of Community Medicine, B.S. Medical College, Bankura, West Bengal, India
4 Professor and HOD, Department of Community Medicine, B.S. Medical College, Bankura, West Bengal, India
|Date of Web Publication||20-Sep-2019|
Dipta Kanti Mukhopadhyay
Lokepur, Near N.C.C. Office, Bankura - 722 102, West Bengal
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Research on different measures of food security and their interrelation in order to identify vulnerable households are scarce in India. Objectives: The objective was to assess household food security (HHFS), nutrient adequacy, dietary diversity, and nutritional status of under-five children along with their interrelation in the slums of Bankura Municipality, West Bengal. Methods: A cross-sectional study was conducted during 2016–2017 among 240 households using two-stage 30-cluster random sampling. Information regarding socioeconomic characteristics, availability, and utilization of different poverty alleviation schemes was collected. HHFS was assessed by a validated HHFS scale-short form in Bengali and nutrient adequacy with 24-h recall method. The eldest under-five child in the family was measured for anthropometry using standard procedure and for dietary diversity with the Individual Dietary Diversity Score. Results: Overall, 74 (29.1%) households had “food security,” whereas 102 (44.3%) and 64 (26.6%) had, respectively, low and very low food security. Among 190 under-five children, 63 (35.3%) had single and 50 (25.5%) had multiple anthropometric failures. Overall, 89 (36.1%) households were deficient for both energy and protein and 111 (47.6%) had deficiency of either of these two. Indicators on the utilization of different poverty alleviation schemes were associated with low/very low food security. A “Composite Index of Food Scarcity” comprising of HHFS, nutrient adequacy, and dietary diversity was proposed which was found to have dose–response relationship with grades of anthropometric failure of under-five children. Conclusions: An index comprising of three indicators might help identify the vulnerable households in relation to food security more effectively than a single indicator.
Keywords: Anthropometric failure, Composite Index of Food Scarcity, household food security, Individual Dietary Diversity Score, nutrient adequacy
|How to cite this article:|
Mitra S, Mukhopadhyay DK, Sarkar AP, Saha I. Are household food security, nutrient adequacy, and childhood nutrition clustered together? A cross-sectional study in Bankura, West Bengal. Indian J Public Health 2019;63:203-8
|How to cite this URL:|
Mitra S, Mukhopadhyay DK, Sarkar AP, Saha I. Are household food security, nutrient adequacy, and childhood nutrition clustered together? A cross-sectional study in Bankura, West Bengal. Indian J Public Health [serial online] 2019 [cited 2020 Nov 30];63:203-8. Available from: https://www.ijph.in/text.asp?2019/63/3/203/267221
| Introduction|| |
The Universal Declaration of Human Rights, 1948, proclaimed in Article 25 that, “Everyone has the right to a standard of living adequate for the health and well-being of himself and of his family, including food…” After a decline at 777 million in 2015, world hunger showed a sharp rise again, with the estimated number of undernourished people increased to 815 million in 2016. The Sustainable Development Goal 2 calls to “end hunger, achieve food security, improve nutrition and promote sustainable agriculture” by 2030. The United Nations Decade of Action on Nutrition (2016–2025) added impetus toward efforts at eradicating hunger and preventing all forms of malnutrition globally.
At the 1996 World Food Summit, 182 nations agreed and adopted to define food security as “the access at all times by all people to adequate amounts of safe, nutritious and culturally acceptable food for an active and healthy life in socially acceptable ways.” Until the 1980s when food security was mostly concerned with national and global facets, the focus shifted toward accessibility to food at household and individual levels and became an “organizing principle” in development. In 2016, the Food and Agriculture Organization (FAO) estimated a prevalence of undernourishment being 11.0% globally and 14.4% for the Indian subcontinent. Following the Food Insecurity Experience Scale, severe food insecurity comprises 9.3% globally and 11.1% nationally.
Various nutrition and social assistance programs for vulnerable population are operating with varied coverage at national, state, and local levels.
For many years, age-adjusted caloric intake was the indicator of choice for the measurement of food security at household level and anthropometric measurement of nutritional status at individual level. Questionnaires to record the coping behavior of people toward food insecurity and scarcity were developed later and were used widely for rapid field-level survey. Per capita caloric intake refers to the quantity of food, not the quality, while questionnaire methods are liable to the interpretation of interviewee and interviewer, and certain terms such as “balanced diet” were found to be difficult to comprehend in resource-constrained settings like India. Inclusion of dietary diversity score to these measurements was suggested to catch the quality issue in food security. The first step to address food security is to identify the vulnerable households. Till date, there is no indicator which can comprehensively assess the household food security (HHFS). As these three indicators assess three different aspects of food security, aggregating them might help in identifying vulnerable households in relation to food security effectively.
In this context, the current study was conducted with the objectives of assessing HHFS, nutrient adequacy, dietary diversity, and nutritional status of under-five children along with their interrelation in the slums of Bankura Municipality, West Bengal.
| Materials and Methods|| |
Study design and setting
A community-based, cross-sectional, descriptive study was conducted from 2016 to 2017 among 246 slums in Bankura Municipality area. The Bankura municipality covers the geographic area of the headquarter town of Bankura district and is situated in the south-western part of the state of West Bengal, India. It is habituated by 137,386 people over 19.06 km2 in 29,807 households over 24 wards.,
Study population, sample size, and sampling technique
Considering the prevalence of food security as 53%, 95% of confidence level, 10% of absolute precision, 15% of nonresponse rate, and adopting design effect of 2, the sample size was calculated as 220, which was rounded up to 240 for this two-stage, 30-cluster survey. All the households (n = 9268) in the 246 slums constituted the sampling frame. In the first stage, thirty slums were selected through probability proportional to size method. A list of households who were residing for 10 years or more in each selected slum was prepared with the help of Anganwadi workers. In the second stage, the selected slum was divided into four arbitrary quadrants, and two households from each quadrant were selected by simple random sampling, so the number of households in each cluster was eight.
Study tools and methods of data collection
After obtaining written informed consent, head of the household or any adult female involved in cooking and purchasing food was approached through house-to-house visit with a predesigned, pretested, semi-structured interview schedule pertaining to the sociodemographics of the family. HHFS was assessed with validated Bengali version of HHFS Scale Short Form., Households that responded negative answers to six items or only a positive answer were designated to have high or marginal food security, households with 2–4 positive answers were classified as with low food security, and those answered 5–6 positive answers were classified to have very low food security. Following the National Sample Survey Organization, monthly per capita expenditure (MPCE) was calculated for food. The respondents were inquired on holding of below poverty line (BPL)/Antyodaya Anna Yojana (AAY) Card, availing of social assistance such as old age or widow or disability pension, and regular utilization of targeted public distribution system (TPDS).
Assessment of nutritional status of children
The eldest under-five child of the household was examined clinically for feature(s) of nutrient deficiency and measured anthropometrically for height/length for age, weight for age, and weight for height/length. They were classified with the Composite Index of Anthropometric Failure (CIAF) into seven subgroups as A – no failure, B – wasting only, C – wasting and underweight, D – wasting, stunting, and underweight, E – stunting and underweight, F – stunting only, and Y – underweight only. These groups were subsequently regrouped as children with no failure, children with single failure (Groups B, F, and Y), and children with multiple failures (Groups C, D, and E) based on the severity.
Assessment of dietary intake
Individual Dietary Diversity Score (IDDS-16) in last 24 hours was assessed for children aged 6 months or more. It was based on consumption of 16 common food groups like cereals; legumes, nuts & seeds; Dark green leafy vegetables; Vitamin-A rich fruits & vegetables; milk & milk products; fish & sea food etc. IDDS-16 score was categorized as high, medium and low if the individuals consumed >6, 4-5 and <3 food groups respectively in last 24 hours.
Dietary survey was conducted for consecutive 3 days with 24-h recall method inquiring on the type and amount of foods consumed including anything consumed outside the household in the preceding 24 h excluding days designated as fast, feast, or festivals. Considering the criteria of the Indian Council of Medical Research, the recommended allowances for a sedentary reference individual were considered as adult consumption unit (ACU) for energy and protein. Accordingly, the total ACUs for energy and protein for the households were calculated, and deficiency or excess consumption of energy and protein per ACU was calculated for each household. Consumption of <90% of ACU was considered as inadequate consumption. Households were categorized as having no inadequacy, inadequacy in one nutrient, and inadequacy in both energy and protein.
The schedule was pretested in a similar slum outside the selected slums. The kappa and adjusted kappa for all items of the HHFS questionnaire were >0.8, and Cronbach's alpha of the questionnaire was 0.82, showing good internal consistency.
The data were codified and double entered in an MS Excel spreadsheet and checked for consistency. The proportion of different grades of HHFS, dietary diversity, nutrient adequacy, and CIAF was expressed in percentage, and binary logistic regression analysis was done to examine the association between HHFS and other correlates after adjustment for clustering. For this purpose, households with low and very low food security were considered as having food insecurity and those with high/marginal food security were considered as households with food security. A Composite Index of Food Scarcity (CIFS) was created comprising of HHFS, nutrient adequacy, and IDDS-16. High/marginal food security, no inadequacy of nutrients, and dietary intake of ≥6 food groups were given a score of “0,” whereas very low food security, inadequacies of both energy and protein, and dietary consumption of ≤3 food groups received a score of “2,” and mild-to-moderate grades in those indicators were given the score of “1.” Scores of the individual variables were added up to get the total score of the index. Cluster analysis was done to examine the conglomeration of categories of HHFS, nutrient adequacy, and dietary diversity according to the different grades of anthropometric failure. The association between CIFS and CIAF was examined with Chi-square test for trend.
Ethical clearance was obtained from the institutional ethics committee of the concerned medical college along with written permission from the appropriate authorities such as Bankura Municipality and Child Development Project Officer, Bankura, West Bengal.
| Results|| |
A total of 240 households participated in the survey and among them, 190 (79.2%) households had at least one under-five child.
Overall, 190 (79.2%) families were Hindu by birth and belief and 131 (54.6%) belonged to scheduled caste. Majority (186 [77.5%]) of the families were headed by male members and 77 (32.1%) of them did not attend school, 71 (29.6%) were just literate, and most of them were underemployed or involved in unorganized sector such as rickshaw pulling, daily labor, rolling of handmade cigarettes called “beedis,” and as domestic servant.
The average family size was 5.53 (±2.4), and the ratio of total to earning members of households was 3.38 (±1.3). The MPCE for food was Rs. 650 (±33.2) and for nonfood items including health expenses was Rs. 219 (±9.1). Classification tree analysis showed that among those (125 [52.1%]) having MPCE-food ≤Rs. 656, 98 (78.4%) had low/very low food security.
Among the respondents, 168 (70.0%) received commodities under TPDS regularly, BPL/AAY card holding was reported by 185 (77.1%) respondents, and only 16 (6.7%) respondents did receipt of any social assistance in the preceding 3 months.
Among the 190 under-five children, 112 (58.9%) were male; the mean age for male children was 24.9 (±12.7) months and for female children was 36.24 (±11.5) months. Twenty-one children were below 6 months of age. Regarding parental education, 59 (31.1%) fathers and 116 (61.1%) mothers were illiterate or just literate, and 131 (69.0%) mothers were homemaker.
Extent of household food security, nutrient adequacy, dietary diversity, and undernutrition
As summarized in [Table 1], among the 240 households surveyed, 70.9% of households had food insecurity and nearly one-fourth (26.6%) had very low food security. Only 16.2% of the households consumed ≥90% of the recommended amount of energy and protein and more than one-third (36.1%) had deficiency in both. Among 190 under-five children, 60.8% had anthropometric failure including 50 (25.5%) children having multiple failures. Among 169 children aged ≥6 months, dietary diversity was high (≥6 food groups) among 19.3% only, whereas 37.2% had low (≤3 food groups) dietary diversity.
|Table 1: Distribution of households according to household food security and nutrient adequacy (n=240), dietary diversity (n=169), and anthropometric grades of under-five children (n=190) in the slums of Bankura, West Bengal|
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Correlates of household food security
Statistically significant association (P < 0.05) of households with food insecurity was noted with MPCE for food < Rs. 656.00 (adjusted odds ratio [AOR]: 2.50, 95% confidence interval [CI]: 1.50–4.16) and irregular utilization of TPDS (AOR: 2.79, 95% CI: 1.41–5.50) in cluster-adjusted binary logistic regression. The prevalence of food insecurity was higher in households having under-five children (72.1%), those possessing BPL/AAY card (70.3%), and those availing social assistance scheme (87.5%) compared to households without those characteristics. The Hosmer and Lemeshow test (χ2 = 9.37, P = 0.928) proved the regression model fit of the data well [Table 2].
|Table 2: Cluster-adjusted binary logistic regression showing variables associated with household food insecurity in the slums of Bankura, West Bengal (n=240)|
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On bivariate correlation, HHFS was revealed to have statistically significant positive correlation with IDDS-16 (ρ = 0.16, P = 0.01) and nutrient adequacy (ρ = 0.70, P < 0.001) and negatively correlated with CIAF (ρ = −0.14, P = 0.03).
It was noted in cluster analysis [Table 3] that in cluster-1, among the under-five children with no anthropometric failure, failure, majority, had high dietary diversity, high/marginal food security in households and inadequacy in intake of only one nutrient. On the other hand, in the severe most group in the spectrum consisting of children with multiple anthropometric failures, majority were found to have low dietary diversity, very low food security, and inadequacy of both energy and protein.
|Table 3: Cluster analysis showing the distribution of categories of variables toward different grades of the Composite Index of Anthropometric Failure in the slums of Bankura, West Bengal (n=169)|
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The Chi-square test for linear trend showed significant dose–response relationship between CIFS and CIAF [Table 4].
|Table 4: Association between the Composite Index of Food Scarcity (CIFS) and the Composite Index of Anthropometric Failure (CIAF) among under-five children in the slums of Bankura, West Bengal (n=169)|
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| Discussion|| |
The present study intended to assess the extent of food stress using three indicators namely experiential HHFS, nutrient adequacy, and dietary diversity as well as to examine whether aggregating these three indicators could help in identifying vulnerable households in relation to food security more effectively in the slums of Bankura Municipality, West Bengal.
As per experiential questionnaire method, less than one-third of the households of the slums had food security. While assessing nutrient adequacy, it was found that substantial majority of the households had deficient intake of either or both of energy and protein compared to the recommended allowances. There was a high correlation between HHFS and nutrient adequacy. Only around one-fifth of the households had optimum dietary diversity. Three in every five under-five children of the study area had anthropometric failure. Lower per capita expenditure in food and irregular utilization of public distribution system were significantly associated with HHFS. Poorer grades of HHFS, nutrient adequacy, and dietary diversity were clustered with multiple anthropometric failures, whereas higher grades of HHFS, dietary diversity, and deficiency in one nutrient were clustered with no anthropometric failure. The newly proposed CIFS was found to have a dose–response relationship with CIAF.
The proportion of HHFS in the slums of Bankura was higher than that reported by Chinnakali et al. from Delhi. However, another study from the slums of Vellore, Tamil Nadu, reported similar figure, while an earlier study in the slums of Delhi depicted a much better scenario,, although different experiential food security questionnaires were used in these studies. Using the same questionnaire, Mukhopadhyay et al. found slightly higher proportion of food security.
The proportion of households not having nutrient adequacy in either protein or energy was higher in the present study when compared to the earlier studies in different parts of West Bengal, although the cutoffs used were different in different studies.,,
The proportion of slum-dwelling children with anthropometric failures was comparable with that of tribal children in Bankura, but the proportion of multiple failures was almost double among the tribal children as reported by Mukhopadhyay and Biswas. However, two earlier studies among slum children in India reported much higher prevalence of anthropometric failures including multiple failures.,
Households with lower MPCE for food, irregular utilization of TPDS, and presence of under-five children were found to have an increased risk of experiential household food insecurity. Higher proportion of households with food insecurity was identified for BPL/AAY card and social assistance schemes. Similar findings were noted by Mukhopadhyay et al. in the tribal population of Bankura as well as Chinnakali et al. and Gopichandran et al. from North and South India, respectively.
Coates et al. found that insufficient quantity, inadequate quality, uncertainty, worry, and lack of acceptability are universal experiences of household food insecurity. As noted by the FAO, despite our in-depth theoretical understanding, no perfect single measure exists that captures all aspects of food insecurity.,
Sethi et al. noted that questionnaires to record the coping behaviors of people to food stress, although used widely, have some limitations due to misinterpretation of some phrases or words. They also expressed major concern on the items related to “food quality” and therefore stressed on establishing external validity of experience-based HHFS scales. They suggested that addition of relevant indicators such as dietary diversity score may help to understand the access to food and nutrient adequacy. On the other hand, measures of consumption such as nutrient adequacy and dietary diversity focused primarily on the quantity and quality of food but not on the other attributes such as certainty and acceptability, which are psychosocial in nature. Experiential food security scale might help in assessing those attributes. The critical importance of the choice of indicators lies here, and multiple indicators can more accurately and reliably measure the level of food insecurity and can identify the vulnerable households. Hence, in the present study, a composite index comprising of experience-based HHFS, nutrient adequacy, and dietary diversity was proposed based on cluster analysis. It was noted that the composite index showed dose–response relationship with the CIAF.
Strengths and limitations of the study
On theoretical construct, the new index “CIFS,” framed in the current study covered the aspects of quantity, quality, uncertainty, and acceptability of food. As seen in the present study, it might help in identifying the vulnerable households having children with anthropometric failures effectively. The present study was conducted in a slum population of a small town; hence, external validity is subject to new research. As the methods of eliciting all the three indicators depended on recall, recall bias may creep in the findings.
| Conclusions|| |
The scenario of HHFS was dismal in the slums of Bankura Municipality, West Bengal, irrespective of the measurement tools, be it questionnaire method or assessment of dietary intake of nutrients. A significant interrelation between HHFS, nutrient adequacy, and dietary diversity was also noted. More than half of the children had anthropometric failures and almost one-fourth had multiple failures. Children with multiple failures clustered in the households which had deficiencies in two or more indicators among HHFS, nutrient adequacy, and dietary diversity. The “Composite Index of Food Scarcity,” comprising of HHFS, nutrient adequacy, and dietary diversity, was found to have a significant dose–response relationship with anthropometric failure of under-five children. Aggregating three indicators to assess the different facets of food security and subsequent development of a cutoff score may lead to its wider application in research and policy.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
United Nations, Resolution adopted by General Assembly: United Nations Millennium Declaration, Fifty-Fifth Sessions: Agenda Item 60(B). New York: Paper Presented on UN General Assembly; 18 September, 2000. p. 9. Available from: http://un.org/millennium/declaration
. [Last accessed on 2017 Sep 25].
Food and Agricultural Organization of United Nations. Rome Declaration on World Food Security and World Food Summit Plan of Action. Rome, Italy: Food and Agricultural Organization of United Nations; 1996.
Sustainable Development Solution Network: A Global Initiative for U.N. Indicators and Monitoring Framework for the SDGs. Revised Working Draft. Sustainable Development Solution Network; 2015.
Carlson SJ, Andrews MS, Bickel GW. Measuring food insecurity and hunger in the United States: Development of a national benchmark measure and prevalence estimates. J Nutr 1999;129:510S-6S.
Maxwell S, Frankenberger TR. Household Food Security: Concepts, Indicators, Measurements. A Technical Review. United Nation's Children's Funds-International Fund for Agricultural Development; 1992.
Planning Commission, Government of India. Twelfth Five Year Plan (2012-2017): Social Sectors: Vol. 3. New Delhi, India: Planning Commission, Government of India; 2013. p. 1-46.
Sethi V, Maitra C, Avula R, Unisa S, Bhalla S. Internal validity and reliability of experienced-based household food insecurity scales in Indian settings. Agric Food Secur 2017;6:21. Available from: https://doi.org/10.1186/s40066-017-0099-3
. [Last accessed on 2017 Dec 15].
Urban Statistics for Health Research and Assessment. Provisional Report: Bankura Municipality. Bankura, West Bengal: Urban Statistics for Health Research and Assessment; 2015.
Directorate of Census Operations, West Bengal. District Census Handbook – Bankura. Ser. 20., Part. 12B. Kolkata, India: Government of India; 2011.
Mukhopadhyay DK, Mukhopadhyay S, Biswas AB. Enduring starvation in silent population: A study on prevalence and factors contributing to household food security in the tribal population in Bankura, West Bengal. Indian J Public Health 2010;54:92-7.
] [Full text]
Bickel G, Nord M, Price C, Hamilton W, Cook J. Guide to Measuring Household Food Security: Revised 2000. Alexandria VA: U.S. Department of Agriculture, Food and Nutrition Service; 2000.
Nord M, Andrews MS, Carlson SJ. Measuring Food Security in the United States: Household Food Security in United States, 2008: ERR-83. United States Department of Agriculture, Economic Research Services; 2009.
Government of India. National Sample Survey Organization: Report No. 523 (62/1.0/1): Household Consumer Expenditure in India, 2005-06: 62nd
Round. Ministry of Statistics and Programme Implementation. New Delhi, India: Government of India; 2008.
Department of Women & Child Development & Social Welfare, Government of West Bengal. Social Welfare Pension. Available from: www.wbswpension.gov.in/pages/wcd_about_scheme.php. [Last accessed on 2016 Jan 05].
Nandy S, Irving M, Gordon D, Subramanian SV, Smith GD. Poverty, child undernutrition and morbidity: New evidence from India. Bull World Health Organ 2005;83:210-6.
Food and Agriculture Organization. Guidelines for Measuring Household and Individual Dietary Diversity: Food and Nutrition Technical Assistance. Ver. 4. Rome, Italy: Food and Agriculture Organization; 2008.
Indian Council of Medical Research. Nutrient Requirement and Recommended Dietary Allowances for Indians, a Report of Expert Group of ICMR. Hyderabad, Andhra Pradesh, India: Indian Council of Medical Research; 2010. p. 40-1.
Chinnakali P, Upadhyay RP, Shokeen D, Singh K, Kaur M, Singh AK, et al.
Prevalence of household-level food insecurity and its determinants in an urban resettlement colony in North India. J Health Popul Nutr 2014;32:227-36.
Gopichandran V, Claudius P, Baby LS, Felinda A, Mohan VR. Household food security in urban Tamil Nadu: A survey in Vellore. Natl Med J India 2010;23:278-80.
Agarwal S, Sethi V, Gupta P, Jha M, Agnihotri A, Nord M. Experiential household food security in an urban underserved slum of North India. Food Secur 2009;1:239-50.
Ray SK, Biswas AB, Kumar S. A study of dietary pattern, household food security and nutritional profile of under-five children of a community of West Bengal. J Indian Med Assoc 2000;98:517-9, 522-3.
Ray SK, Biswas AB, Kumar S. A Comparative study of household food security and nutritional profile of under-five children in a rural and an urban community of West Bengal. Indian J Public Health 1997;42:136-47.
Bhattacherjee S, Datta S, Ray K, Mukhopadhyay DK. Nutrient adequacy and its correlation in a Sub-Himalayan region of West Bengal, India. J Family Med Prim Care 2016;5:314-9.
] [Full text]
Mukhopadhyay DK, Biswas AB. Food security and anthropometric failure among tribal children in Bankura, West Bengal. Indian Pediatr 2011;48:311-4.
Shit S, Taraphdar P, Mukhopadhyay DK, Sinhababu A, Biswas AB. Assessment of nutritional status by composite index for anthropometric failure: A study among slum children in Bankura, West Bengal. Indian J Public Health 2012;56:305-7.
] [Full text]
Rastogi S, Maheswari C, Raghav SK, Lala MK. Assessing burden of under-nutrition among under-five children of urban slum by using composite index of anthropometric failure in Ahmedabad city, Gujarat, India. Natl J Community Med 2017;8:496-500.
Coates J, Frongillo EA, Rogers BL, Webb P, Wilde PE, Houser R. Commonalities in the experience of household food insecurity across cultures: What are measures missing? J Nutr 2006;136:1438S-48S.
Webb P, Coates J, Frongillo EA, Rogers BL, Swindale A, Bilinsky P. Measuring household food insecurity: Why it's so important and yet so difficult to do. J Nutr 2006;136:1404S-8S.
Kirkland T, Kemp RS, Hunter LM, Twine WS. Toward improved understanding of food security: A methodological examination based in rural South Africa. Food Cult Soc 2013;16:65-84.
Frongillo EA Jr. Validation of measures of food insecurity and hunger. J Nutr 1999;129:506S-9S.
[Table 1], [Table 2], [Table 3], [Table 4]