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Abstract
Introduction
Methods
Results
Discussion and conclusions
References
Joel Gittelsohn, Sangeeta Mookherji, and Gretel PeltoJoel Gittelsohn is affiliated with the Center for Human Nutrition and the Division of Human Nutrition in the Department of International Health at the Johns Hopkins University School of Hygiene and Public Health in Baltimore, Maryland, USA. Sangeeta Mookherji is affiliated with the Division of Health Systems in the Department of International Health at the Johns Hopkins University School of Hygiene and Public Health. Gretel Pelto is affiliated with the World Health Organization in Geneva.Mention of the names of firms and commercial products does not imply endorsement by the United Nations University.
This paper operationalizes household food security and links it to household food consumption patterns in rural Nepal. Food security has long been used as a macro-level indicator of agricultural stability by both agricultural and economic researchers. However, little work has been done to operationalize it at the household level. We view household food security as reflecting three different dimensions: past food supply, current food stores, and future supply of food adequate to meet the needs of all household members. A key method is the construction of scales that capture these different aspects of household food security. When operationalized in this way, household food security is associated with increased consumption of non-staple foods in this setting. Past household food security is associated with increased frequency of meat consumption and increased variety of food consumed. Current household food security predicts a higher frequency of meat and dairy intake and greater dietary variety. Future household food security is associated with increased total dietary variety and future consumption of dairy products. We feel that this conceptual approach to assessing household food security, i.e., the use of scales to measure past, current, and future components of food security, can be used as a framework in other settings.
Food security has long been used as an important macro-level indicator of agricultural stability and progress for both agricultural and economic researchers. However, little work has been done to operationalize the concept at the household level. We view household food security as a concept that integrates environmental, economic, and cultural factors in a manner that can provide a useful tool for predicting dietary patterns within the household. These factors affect the manner in which households manage their food resources, either by affecting initial food selection and acquisition or by affecting the use of food once it has been selected. Household food security is an outcome of these decisions.
This paper seeks to further the operationalization of household food security in three ways. First, a theoretical framework for household food security is presented, describing the set of relevant independent, intervening, and dependent variables. Second, a framework for operationalization is presented, using data collected from rural households in Nepal. Third, the relevance of household food security, measured at the micro level, is examined through regression models that predict household food security and that use household food security to predict diversity of diet at the household level.
Food security and household food security: An economic perspective
Economic approaches to food security have traditionally focused on assessing aggregate levels of food supply, agricultural production, and the balance of agricultural trade [1-6]. In the 1970s, food security was defined at the macro level as the ability to avoid short-term deficits in aggregate food supply [7], and it was directly linked to grain stocks at the global and national level [8]. At the micro level, food security was conceptualized primarily as the ability to successfully weather transitory shocks to food supply, such as drought, floods, market failure, or civil strife [9]. The focus was on food staples (i.e., grains), national stores of grain, and agricultural policy that ensured stable supplies and stores of grain. Most importantly, food security was conceptualized as the outcome measure of agricultural policies.
As world food supplies stabilized at more than adequate levels and hunger and malnutrition continued to be prevalent, it became clear that aggregate food supply was not a useful proxy for food consumption at the household or individual level. From an economic perspective, malnutrition was increasingly recognized as the individual-level manifestation of a complex combination of household, community, regional, national, and international factors [10-12]. Seminal work on the phenomenon of famine by Sen [13] brought attention to the issue of access to food by households and by individuals, which could be constrained by economic, social, and cultural factors and was most often a chronic, not transitory, condition at the household level. Food insecurity could occur at the household level, and was occurring, in the absence of regional and national food insecurity.
The neoclassical economic theory of household production added further to the concept of food security by emphasizing the decision-making processes within the household that determine how scarce resources are allocated. Since households have limited access to resources and strive to fulfil a variety of basic needs, procurement of food competes with acquisition of health services and other goods and services. Therefore, food needs are not necessarily the most dominant basic needs for a given households subsistence or survival [9].
Interest focused on household food security as a measure that would link national-, regional-, and community-level measures of food security to household food consumption and individual nutritional status. Household food security is seen as a concept that will relate agricultural policy to issues of nutrition [12]. Once household food security was identified as an important variable in the food security-nutritional status continuum, a variety of definitions and conceptual frameworks of household food security were proposed from the agricultural economic perspective. Whereas previous definitions of macro-level food security focused on food availability (supply), most of the recent household food security frameworks are concerned primarily with household access to food, although all recognize that access is just one component of household food security. The issue of food distribution at the community level is also addressed by some of the frameworks, in that all groups in a society are viewed as requiring equal access to sufficient food.
The International Fund for Agricultural Development concisely defines household food security as the capacity of a household to procure a stable and sustain-able basket of adequate food [14]; however, some of the terminology used is difficult to operationalize. Adequacy may be defined in terms of quality and quantity of food, which contribute to a diet that meets the nutritional needs of all household members. Stability refers to the households ability to procure food across seasons and transitory shortages, the more traditional definition of food security. Sustainability is the most complex of the terms, encompassing issues of resource use and management, human dignity, and self-reliance, among others [14].
Household food security: An anthropological perspective
Anthropology has a great deal to contribute to the conceptualization of household food security. Anthropologists have traditionally collected information on food provisioning, preparation, and consumption practices as part of their ethnographic descriptions of cultural settings [15-19]. Anthropological perspectives on food have focused on eliciting indigenous belief systems surrounding food, such as food classification, food proscriptions and prescriptions, and so on.
Ecological and medical anthropologists have investigated household responses to food shortages, with a particular emphasis on understanding and identifying adaptive strategies for subsistence [20-22]. Although household food security has not been a common component of anthropological studies, in recent years anthropologists have turned their attention to examining food security at the community level [23, 24]. Anthropologists have a number of tools at their disposal for investigating household food security. The primary focus of anthropology is on human belief, perception, and behaviour at the community, household, and individual levels. Through intensive study of small groups, anthropologists are in a good position to uncover the subtle dynamics that mark household-level decision making and activity and to understand this behaviour to a certain degree from the point of view of the people themselves.
Theoretical framework
The theoretical framework presented here draws on both anthropological and economic perspectives. The ecological approach in nutritional anthropology typically considers the physical and social environments, social organization, available technology for food production, and cultural and ideological systems when assessing the determinants of food choices and diet [25]. Economists see household income as the key potential shock to household food security, along with market food prices. At a more micro level, it is important to acknowledge other types of coping strategies and social mechanisms that function to buffer the effects of income and price fluctuations. Food gifts, loans, and other mechanisms often alleviate short-term stresses on household food supply [26].
Our framework (fig. 1) begins at the macro level of agricultural policies regarding both production and trade that influence food supply. Regional food supplies are affected by governmental inter-regional trade policies, seasonality, and climate. The state of regional food supplies determines what foods are available in the community-level markets where households go to sell, trade, and purchase foods for consumption. Community food markets are affected by seasonality and climate, but also by a host of cultural factors. The cultural factors are primarily rules that determine food selection by households and patterns of inter-household food sharing. The household is a multilevel construct, with cultural factors influencing not only food selection and preparation but also intra-household allocation of food. Individual dietary intake is the outcome of the intra-household distribution of the food available in the family. Community-level factors, such as the health services available and the status of sanitation and water supply, are included as exogenous variables that influence individual nutritional status through morbidity.
Figure 2 describes the household-level dynamics in more detail. At the household level, food security is determined by a households current food supplies, past stable food supply, and potential future supply. Potential future food supply is a function of the households available resources, such as capital (e.g., land), labour, and time. Between household food security and individual nutritional status are patterns of food distribution within the household and individual food consumption, which may include differences in dietary quality and quantity. Gittelsohn [27,28] has looked at the complexity of factors affecting intra-household food allocation and has found that in rural Nepal culturally specific food-serving behaviours result in nutritional penalties against women. Other exogenous factors include the composition of the household (number of members, structures, female or male headed, number of females versus males, etc.) and factors affecting the social and economic status of the household (land ownership, earned income, caste, education, etc.). Morbidity, a variable that is affected by community-level factors and also by household-level factors such as food preparation and hygiene practices, also affects an individuals nutritional status [12,29].
Using the theoretical framework proposed above, this paper addresses the following key questions:
» Can an appropriate and reliable measure of food security be operationalized at the household level, and what would such a measure look like?FIG. 1. Broad conceptual framework for examining household food security» How does household food security relate to household food intake and dietary diversity (as a proxy for dietary quality at the household level)?
» How does household food security relate to other determinants at the household level, including socio-economic status and (in the case of Nepal) caste?
Framework for operationalizing household food security
We view household food security as reflecting three different dimensions: the past (stable) food supply, the current food stores, and the anticipated future supply of food adequate to meet the nutritional needs of all household members. We define a secure past food supply as reflected by the stable flow of food into the household, its storage and consumption within the household, and its flow out of the household. The flow of foods into a household via different modes (self-production, purchase, receipt as gifts, etc.) should theoretically meet or exceed the outflow of food sold, paid as rent, given to others, etc. Our definition of current food security is the presence of sufficient household stores (defined broadly) to meet the immediate nutritional needs of the household members. In agricultural communities we define future food security as that portion of existing food stores which is invested in planting and in feed to animals to ensure adequate food supplies in the future.
Figure 3 presents a provisional theoretical model that will be tested with empirical data from Nepal. Essentially, it is a model of food flow through the Nepali household that illustrates the relationships outlined above. The assumptions behind this model of household food security revolve around a concept of general household food stores. The various means by which foods enter and leave the household represent a pattern of interactions. Households differ in their use of one or more pathways for obtaining and reallocating food. The model incorporates time-specific data on current food stores. Information collected about food flow through the household during the course of the preceding year can be used to give a picture of past household food security. By using a food-flow model for household access to food, we can address issues of both adequacy and stability of food supply. This approach is similar to those used in other studies to estimate household-level food security; however, the flow of food out of the household is typically not included in their estimations [29]. Finally, the model permits an examination of food resources allocated for the purpose of producing food some time in the future.
Operationalizing household food security according to a household food-flow model has the potential to incorporate food adequacy, stability, and sustainability (to a more limited degree) into measurement of food security. This provides a more comprehensive measure of household food security and can permit associations between household-level measures and individual-level measures to be investigated. The food-flow model is relevant for a variety of economic environments, both rural and urban, and for subsistence farming, cash cropping, or market-dominated food procurement.
Description of the research site
The data used to operationalize household food security come from the principal authors dissertation research, conducted from November 1986 through August 1987 in Pahargaon (a pseudonym) Village Development Committee (formerly called a panchayat) in the western hills of Nepal. A total of 115 households were randomly sampled, representing 767 individuals in six villages. The villages included in the study area lie along the slopes of hills at altitudes ranging from 3,500 to 4,800 feet. Agricultural fields range from approximately 10,00 feet (down in the river valley) up to 5,000 feet. The lower river valley fields (irrigated cropland, or khet) are considered more valuable because they are more productive. All study households owned some land, but for many the amount was inadequate for subsistence. A system of land rental (adhiyaa) is well established in Pahargaon, in which landowners permit villagers to cultivate plots of land and receive half of the harvested produce as payment.
FIG. 2. Detailed framework of food security within the household
FIG. 3. Food flow through the Nepali household
Villages in Pahargaon are largely isolated from the larger market areas and centres of power for the region. The area around Pahargaon is heavily deforested, and villagers must walk three to five hours to obtain firewood. Water is available mainly from ground springs, which vary in distance from a few minutes to a half-hour round-trip walk from Pahargaon households. Ethnically, Pahargaon is composed of members of all four main caste groups in the Hindu Varna system: Brahmin, Chhetri, Vaisya, and Shudra. There are notable differences between higher and lower castes in terms of education, occupation, wealth, and, consequently, political power. In rural Nepal these differences extend also to food proscriptions related to caste status and thereby to diet.
Data-collection techniques
Before the initiation of data collection using structured instruments, exploratory qualitative research was conducted using key informant interviewing, focus groups, and unstructured observation techniques. This period of preliminary ethnographic data collection assisted in developing culturally appropriate and valid quantitative instruments for later phases of the research and contributed to the final interpretation of the quantitative data results.
Structured data collection was focused on four key areas. All four instruments were administered from January to April 1996. This is generally the period of greatest food availability in the panchayat. The household food-frequency instrument was administered a second time in almost all study households approximately three to five months later from June to August 1996. From June to August is the pre-monsoon and early monsoon season, which is generally regarded as the period of greatest food scarcity in the panchayat.
Household and individual demographic data, including information on caste status, age, and sex, were collected using a survey administered to the male head of the household.
Economic status indicators were collected at the household level from the male head of the household, including ownership of land, animals, and material possessions and quality of the house.
Household food stores and usage patterns were obtained through a structured interview. The male head of the household was asked to estimate the amounts of 20 key foods (identified in the ethnographic survey) acquired by the household over the preceding 12 months and how the food had been used by household members (an indicator of past food security). He was also asked to describe the amounts of each food currently in storage (an indicator of current food security), limited to storable foods, such as grains and tubers. In addition, the respondent was asked to describe the amount of land currently planted and the numbers of each kind of animal currently owned (indicators of future food security).
The accuracy of recall by the informant over an extended period of time was of concern. Accuracy was enhanced by several methods:
» Different means of food inflow and outflow were identified by ethnographic methods and distinguished from one another. For instance, respondents were asked not only the total amount of rice that came into the household, but also how much rice they produced on their land, received as payment, received as gifts, received in trade, or purchased.Household food consumption patterns were estimated using a weekly food-frequency instrument. This instrument was administered twice in each study household. The female head of the household was asked to report the number of times any household members had consumed 70 different foods during the previous week and to give an estimate of the amount of food consumed by household members each time (familiar household measures were used to estimate quantity). The 70 foods were identified as the most commonly consumed through preliminary ethnographic interviews with key informants; however, additional spaces were provided for other foods.» Information was cross-checked during the interview, both within and between foods, and with other questions. The total food coming into the household should be roughly equal to the amount reportedly flowing out of the household, plus the amounts reported as eaten and stored. A household owning a lot of rice-producing land but reporting very low rice production would be asked to explain the inconsistency.
» Respondents were encouraged to report quantities using a variety of local measures, which were later translated into grams.
» Other household members, especially those involved in agricultural production, were encouraged to participate during the interview and often served to refresh the memory of the principal respondent.
Scale and score construction
This section describes how we operationalized food security at the micro level of the household. A key method was the construction of scales and scores that captured the complexity of the factors that make up household food security [30]. Separate exploratory factor analyses were conducted to identify key components of three different scales representing past, current, and future household food security. Factor analysis is an appropriate analytic method when the investigator wants to identify key constructs underlying a set of data [31]. The method has been used in dietary studies to identify patterns of food consumption for specific populations [32-34]. Although we initially experimented with developing our own scoring system, we soon discovered that the complexity of the data (multiple sources of food, multiple ways that food could leave the household, multiple styles of managing food resources) necessitated an analysis strategy that would permit underlying patterns to emerge, effectively summarize data, and provide optimal weights for component variables.
The principal-factor method was used to identify components of each scale [31]. A combination of scree test (a plot of the eigenvalues of the factors) and assessment of the proportion of the variance accounted for by the factors was used to determine the number of factors to be retained for rotation (conducted using the varimax method). In interpreting the rotated factor pattern, a selected item was considered to load on a given factor if the loading was 0.40 or greater for that factor and was less than 0.40 for all other factors. No item was permitted to load on more than one factor. Factor scores for each item in the three scales were computed by multiplying its value by its factor weighting. Reliability for all scales was assessed by calculating coefficient alpha [35].
Past food stability scale
To obtain some indication of past food supply stability (PASTFDSC), respondents were asked to recall the flow of 20 key foods into and out of the household during the 12 months leading up to the interview date. The foods were rice, shuto (dried ginger), wheat, corn, mustard, potatoes, barley, lentils, millet, soya beans, peanuts, vegetables, fruit, milk, eggs, goat, chicken, buffalo, and pig. The respondents were asked to estimate the amount of each food coming into household stores through five specific pathways: production, purchase, gift, payment, and trade. The respondents were then asked to estimate how much of these foods left household stores through six pathways: consumed by household members, sold, traded, given to others, paid in rent, and fed to animals. Payment includes food received as rent for land use. Trade indicates food traded for other types of food. Gifts can mean food received either as a gift or, as many low-caste families do, as compensation for services rendered (e.g., leatherwork, blacksmithing, or tailoring). All 20 food categories were combined on the basis of source (how they came into the household) and use (how they left the household). Each of these scores was then adjusted according to household caloric requirements (to account for age and sex composition differences between households). These adjusted variables were then converted into common units by recoding each score into quartiles.
Factor analysis was then used to identify the main patterning in the scores. Most loaded on factor 1 (amount of food stored, sold, given in rent, produced, fed to animals, or given as gifts). Traded (either received or given) food consistently loaded on its own factor (factor 2). Food purchased (bought) and food received as pay consistently loaded on their own factor (factor 3). A second round of correlation analysis was conducted to verify the factor analysis findings. The final Cronbachs alpha of the six-item PASTFDSC scale was 0.747, indicating a reliable unidimensional scale. Finally, confirmatory factor analysis was used to generate standardized scoring coefficients for these items to use as weights when combining the items into a single-scale score. All items loaded onto one factor. The final PASTFDSC variable had a mean of 1.61, a standard deviation of 1.06, a median of 1.63, and a range of 0 to 3.42 and was approximately normally distributed. A high score on the PASTFDSC therefore indicates that in comparison with households with lower scores, the household produced a lot of its food, had a lot of food in stores, gave out a lot of food in rent (and therefore had people working on its land), gave out a lot of food as gifts, and used a lot of food to feed its animals.
Current food supply/stores scale
The current food security scale (CURRFDSC) reflects household food stores at the time of the household interview. The 20 foods recorded in the household food stores and usage instrument were combined into 8 food groups. For example, rice, corn, wheat, and millet stores were combined into the grains group. Factor analysis and correlation analysis were used to select food-store variables to constitute a unidimensional scale. The final scale included grains, vegetables, nuts and beans, and milk (based on current productivity estimates of milk-producing animals) and had a Cronbachs alpha of 0.711. Factor analysis was then used to generate weights that were used to combine the four food groups into one scale. Univariate statistics on the scale CURRFDSC indicated a fairly normal distribution, with a mean of 1.5, a standard deviation of 0.96, and a range of 0 to 3.26.
Future food productivity scale
This scale reflects the amount of land currently planted in a variety of crops and the numbers of work animals and meat- or milk-producing animals currently owned as a means of indicating the potential of the household to produce food in the near future (FUTUFDSC). For each of 11 planted food crops, the amount planted in seed (e.g., the amount of rice seed) in the current year was weighted by the proportion of total land that was owned or rented by the household. Plantings on rented land were weighted by 0.5, since the household would only receive half of what they planted. These foods included those crops that are most commonly planted in large quantities and not in kitchen gardens (except tirmilo [an indigenous black oilseed] and mustard).
For fruits and vegetables, households were only asked whether or not they grew a particular variety on their own land. Correlation analysis was done to construct additive fruit variety (13 items, alpha=0.825) and vegetable variety (18 items, alpha=0.881) subscales. In terms of animals, correlational analysis resulted in an additive subscale that included numbers of cows, bulls, goats, and buffaloes (alpha=0.530).
Each of these scores - 13 planted foods (amounts planted), fruit variety subscale, vegetable variety subscale, and animal ownership subscale - was then converted into quartiles. Correlation analysis was done on the converted variables to construct a scale for future household food security. Thirteen items remained in the final scale: fruits subscale, vegetables subscale, animals subscale, and the following planted crops: tirmilo/baari, peanuts/baari, millet/baari, lentils/baari, potatoes/baari, mustard/baari, corn/baari, wheat/baari, wheat/khet, and rice/khet. (Baari is unirrigated cropland and khet is irrigated cropland.) The final scale (FUTUFDSC) has an acceptable Cronbachs alpha of 0.784. The scale values have a normal distribution, with a mean of 14.7, a standard deviation of 7.09, and a range of 0 to 30.
Data analysis
The effect of the three measures of household food security on household food consumption patterns was examined using multiple regression. Separate models were run to examine the effects of past, current, and future food security on the frequency of consumption of different food groups and on the variety of foods consumed by the household (both between and within food groups). Scale scores for each of the three measures were converted into quartiles, with the second, third, and fourth quartiles entered into the models as dummy variables. The primary outcome variables for the analyses were based on the food-frequency results. These data were summarized by calculating additive scores by food group (grains, beans, green leafy vegetables, tubers, other vegetables, fruits, meats, and dairy products). Dietary variety, a proxy for dietary quality, was calculated in two ways: as total food group variety (whether or not one or more foods were consumed within each food group; maximum score, 8) and as total food group intensity (summing all foods in all food groups; maximum score, 30).
Other variables included in the models were dummy variables for caste (Brahmin, Chhetri, and Vaisya were included; Sudra, the lowest-caste group, was not included) and socio-economic status (the second and third terciles were included; the lowest tercile was not included), based on the total value of all possessions. In addition, an independency ratio (number of adult male and female household members aged 15 to 60/number of children and elderly in the household) was calculated and incorporated into the models. Standardized beta coefficients were generated for each of the models. Statistical analysis was performed using the SAS statistical package (SAS/STST version 6.11, SAS Institute, Cary, NC, USA).
Tables 1 to 3 present models examining the relationships between the three measures of household food security and weekly frequency of consumption of foods in eight groups. In general, caste status and socio-economic status were more associated with frequency of consumption of the different food groups than the food security scales. Being Brahmin or, to a lesser degree, Chhetri, was associated with significantly more frequent consumption of green leafy vegetables, tubers, and dairy products and significantly less frequent consumption of meat. Households in the upper terciles of socio-economic status tended to be more likely to consume green leafy vegetables and tubers. It is important to note that caste and socio-economic status are highly correlated in this setting (Spearmans r=.3666), with higher-caste households tending to be of higher socio-economic status. Independency ratio did not have a significant effect. High scores for past and current household food security were associated with more frequent consumption of meat and, to a lesser degree, of dairy products.
TABLE 1. Relationship between past food security variables and frequency of household consumption of different food groups (standardized beta coefficients) (N= 114 households)
Independent variable |
Food group |
|||||||
Grains |
Beans |
Green leafy vegetables |
Tubers |
Other vegetables |
Fruits |
Meat |
Dairy products |
|
F |
nsa |
ns |
2.419 |
2.406 |
ns |
ns |
3.725 |
3.182 |
R2 |
|
|
0.172 |
0.171 |
|
|
0.242 |
0.214 |
PASTQ4 |
|
|
-0.16 |
-0.04 |
|
|
0.26** |
0.20 |
PASTQ3 |
|
|
0.13 |
-0.17 |
|
|
0.10 |
0.05 |
PASTQ2 |
|
|
-0.04 |
-0.09 |
|
|
0.03 |
0.04 |
Brahmin |
|
|
0.21* |
0.21* |
|
|
-0.39** |
0.41*** |
Chhetri |
|
|
0.06 |
-0.07 |
|
|
-0.26** |
0.03 |
Vaisya |
|
|
-0.11 |
-0.17 |
|
|
0.13 |
0.08 |
SESL3 |
|
|
0.12 |
0.26** |
|
|
0.008 |
0.09 |
SESL2 |
|
|
0.18* |
0.13 |
|
|
0.01 |
0.08 |
Independency ratio |
|
|
-0.08 |
-0.02 |
|
|
0.10 |
-0.02 |
a. ns = not significant.TABLE 2. Relationship between current food security variables and frequency of household consumption of different food groups (standardized beta coefficients) (N=114 households)
* p<.10.
** p<.05.
*** p<.01.
Independent variable |
Food group |
|||||||
Grains |
Beans |
Green leafy vegetables |
Tubers |
Other vegetables |
Fruits |
Meat |
Dairy products |
|
F |
1.902 |
nsa |
1.774 |
2.314 |
ns |
ns |
3.564 |
3.6 |
R2 |
0.140 |
|
0.132 |
0.165 |
|
|
0.234 |
0.236 |
CURRQ4 |
0.004 |
|
-0.08 |
0.12 |
|
|
0.23* |
0.28** |
CURRQ3 |
0.16 |
|
0.06 |
0.01 |
|
|
0.19* |
0.19 |
CURRQ2 |
0.18 |
|
-0.03 |
-0.03 |
|
|
0.06 |
0.10 |
Brahmin |
-0.06 |
|
0.22* |
0.15 |
|
|
-0.43*** |
0.34*** |
Chhetri |
-0.01 |
|
0.04 |
-0.12 |
|
|
-0.3** |
-0.04 |
Vaisya |
0.25* |
|
-0.12 |
-0.18 |
|
|
0.08 |
0.02 |
SESL3 |
0.18 |
|
0.07 |
0.22* |
|
|
0.06 |
0.10 |
SESL2 |
0.14 |
|
0.16 |
0.14 |
|
|
0.05 |
0.10 |
Independency ratio |
0.04 |
|
-0.04 |
-0.05 |
|
|
0.10 |
-0.04 |
a. ns = not significant.Tables 4 to 6 model the relationships between the three household food security scales and the dietary variety scores. In these models, past, present, and future household food security and socio-economic status are all associated with the dependent variables. Caste status and independency ratio are not significant in any of the models. Higher socio-economic status appears to be particularly related to total food group variety score. On the other hand, the highest quartiles for the past and current household food security scores are associated with total food group intensity. Current and future food security scores are associated with total food group variety.
* p<.10.
** p<.05.
*** p<.01.
Tables 7 to 9 present models depicting the relationships between the three household food security scales and frequency of consumption from the eight food groups in the second round of household food frequencies. In general, the effects of caste and socio-economic status are much the same as those shown in tables 1 to 3. High-caste status is associated with increased frequency of intake of beans, green leafy vegetables, dairy products, and tubers in some instances. Higher socio-economic status is associated with increased frequency of intake of beans, tubers, meat, and dairy products. Past and current food security are negatively associated with green leafy vegetable intake. Future food security is only associated with increased frequency of consumption of dairy products.
TABLE 3. Relationship between future food security variables and frequency of household consumption of different food groups (standardized beta coefficients) (n=114 households)
Independent variable |
Food group |
|||||||
Grains |
Beans |
Green leafy vegetables |
Tubers |
Other vegetables |
Fruits |
Meat |
Dairy products |
|
F |
nsa |
ns |
1.856 |
2.321 |
ns |
ns |
3.224 |
2.965 |
R2 |
|
|
0.137 |
0.166 |
|
|
0.216 |
0.203 |
FUTUQ4 |
|
|
-0.03 |
0.02 |
|
|
0.03 |
0.09 |
FUTUQ3 |
|
|
0.12 |
-0.04 |
|
|
-0.001 |
0.03 |
FUTUQ2 |
|
|
0.08 |
0.16 |
|
|
-0.13 |
-0.04 |
Brahmin |
|
|
0.22* |
0.16 |
|
|
-0.36*** |
0.42*** |
Chhetri |
|
|
0.02 |
-0.11 |
|
|
-0.21* |
0.05 |
Vaisya |
|
|
-0.14 |
-0.2 |
|
|
0.11 |
0.06 |
SESL3 |
|
|
0.06 |
0.19 |
|
|
0.10 |
0.12 |
SESL2 |
|
|
0.14 |
0.13 |
|
|
0.06 |
0.10 |
Independency ratio |
|
|
-0.04 |
-0.04 |
|
|
0.10 |
-0.03 |
a. ns = not significant.TABLE 4. Relationship between past food security variables and variety of household consumption of different food groups (standardized beta coefficients) (N=114 households)
* p<.10.
** p<.05.
*** p<.01.
Independent variable |
Dependent variable |
|
Total food group variety (across food groups) |
Total food group variety and intensity of consumption
(across and within food groups) |
|
P |
1.777* |
1.921* |
R2 |
0.132 |
0.141 |
PASTQ4 |
0.18 |
0.28** |
PASTQ3 |
0.09 |
0.21* |
PASTQ2 |
0.01 |
0.12 |
Brahmin |
0.04 |
0.04 |
Chhetri |
-0.06 |
0.03 |
Vaisya |
0.02 |
0.18 |
SESL3 |
0.28** |
0.18 |
SESL2 |
0.22** |
0.13 |
Independency ratio |
-0.07 |
-0.14 |
* p<.10.TABLE 5. Relationship between current food security variables and variety of household consumption of different food groups (standardized beta coefficients) (N=114 households)
** p<.05.
*** p<.01.
Independent variable |
Dependent variable |
|
Total food group variety (across food groups) |
Total food group variety and intensity of consumption
(across and within food groups) |
|
F |
2.541** |
2.100** |
R2 |
0.179 |
0.153 |
CURRQ4 |
0.28** |
0.32** |
CURRQ3 |
0.13 |
0.16 |
CURRQ2 |
-0.04 |
0.18 |
Brahmin |
0.01 |
0.02 |
Chhetri |
-0.11 |
-0.03 |
Vaisya |
0.001 |
0.13 |
SESL3 |
0.27** |
0.22* |
SESL2 |
0.25** |
0.15 |
Independency ratio |
-0.08 |
-0.15* |
* p<.10.Similar patterns were observed when the effects of the three household food security scales on the two dietary variety scores were examined, calculated from the second round of food frequencies. Higher caste is particularly associated with increased variety of foods consumed at the household level.
** p<.05.
*** p<.01.
TABLE 6. Relationship between future food security variables and variety of household consumption of different food groups (standardized beta coefficients) (N=114 households)
Independent variable |
Dependent variable |
|
Total food group variety (across food groups) |
Total food group variety and intensity of consumption
(across and within food groups) |
|
F |
2.166** |
1.783* |
R2 |
0.157 |
0.133 |
FUTUQ4 |
0.24* |
0.19 |
FUTUQ3 |
0.12 |
0.19 |
FUTUQ2 |
-0.03 |
0.02 |
Brahmin |
0.04 |
0.06 |
Chhetri |
-0.07 |
0.04 |
Vaisya |
-0.03 |
0.13 |
SESL3 |
0.23* |
0.18 |
SESL2 |
0.22** |
0.14 |
Independency ratio |
-0.06 |
-0.13 |
* p<.10.TABLE 7. Relationship between past food security variables and future frequency of household consumption of different food groups (standardized beta coefficients) (N=103 households)
** p<.05.
*** p<.01.
Independent variable |
Food group |
|||||||
Grains |
Beans |
Green leafy vegetables |
Tubers |
Other vegetables |
Fruits |
Meat |
Dairy products |
|
F |
nsa |
2.059 |
5.071 |
2.639 |
2.092 |
ns |
1.751 |
3.476 |
R2 |
|
0.166 |
0.329 |
0.203 |
0.168 |
|
0.145 |
0.252 |
PASTQ4 |
|
-0.147 |
-0.274** |
-0.109 |
0.431*** |
|
-0.046 |
0.111 |
PASTQ3 |
|
-0.200 |
-0.229** |
-0.139 |
0.064 |
|
-0.170 |
0.124 |
PASTQ2 |
|
-0.058 |
-0.253** |
0.147 |
0.216* |
|
-0.122 |
-0.068 |
Brahmin |
|
0.072 |
0.571*** |
0.265** |
0.174 |
|
-0.058 |
0.430*** |
Chhetri |
|
0.290** |
0.116 |
0.022 |
0.152 |
|
-0.042 |
0.340** |
Vaisya |
|
0.284** |
0.004 |
-0.144 |
0.169 |
|
0.050 |
0.242* |
SESL3 |
|
0.299** |
0.058 |
0.245** |
-0.098 |
|
-0.185 |
0.174 |
SESL2 |
|
0.345*** |
0.045 |
-0.044 |
-0.061 |
|
-0.331*** |
0.016 |
Independency ratio |
|
-0.040 |
-0.148* |
-0.010 |
0.117 |
|
-0.111 |
0.004 |
a. ns = not significant.TABLE 8. Relationship between current food security variables and future frequency of household consumption of different food groups (standardized beta coefficients) (N=103 households)
* p<.10.
** p<.05.
*** p<.01.
Independent variable |
Food group |
|||||||
Grains |
Beans |
Green leafy vegetables |
Tubers |
Other vegetables |
Fruits |
Meat |
Dairy products |
|
F |
nsa |
1.991 |
4.557 |
1.750 |
ns |
ns |
2.000 |
3.586 |
R2 |
|
0.162 |
0.306 |
0.145 |
|
|
0.162 |
0.258 |
CURRQ4 |
|
-0.056 |
-0.118 |
-0.042 |
|
|
0.165 |
0.201 |
CURRQ3 |
|
-0.088 |
-0.221* |
-0.011 |
|
|
-0.066 |
0.031 |
CURRQ2 |
|
0.086 |
-0.111 |
-0.012 |
|
|
-0.046 |
-0.031 |
Brahmin |
|
0.034 |
0.575*** |
0.237* |
|
|
-0.096 |
0.440*** |
Chhetri |
|
0.270* |
0.126 |
0.001 |
|
|
-0.093 |
0.317** |
Vaisya |
|
0.271* |
0.041 |
-0.128 |
|
|
0.061 |
0.241* |
SESL3 |
|
0.278** |
-0.014 |
0.201* |
|
|
-0.248** |
0.155 |
SESL2 |
|
0.335*** |
0.021 |
-0.055 |
|
|
-0.337*** |
0.016 |
Independency ratio |
|
-0.059 |
-0.145 |
-0.033 |
|
|
-0.136 |
0.011 |
a. ns = not significant.TABLE 9. Relationship between future food security variables and future frequency of household consumption of different food groups (standardized beta coefficients) (N=103 households)
* p<.10.
** p<.05.
*** p<.01.
Independent variable |
Food group |
|||||||
Grains |
Beans |
Green leafy vegetables |
Tubers |
Other vegetables |
Fruits |
Meat |
Dairy products |
|
F |
nsa |
1.769 |
4.161 |
1.917 |
ns |
ns |
ns |
3.533 |
R2 |
|
0.146 |
0.287 |
0.157 |
|
|
|
0.255 |
FUTUQ4 |
|
-0.094 |
-0.081 |
-0.051 |
|
|
|
0.219* |
FUTUQ3 |
|
-0.026 |
-0.010 |
0.088 |
|
|
|
0.173 |
FUTUQ2 |
|
-0.049 |
-0.034 |
0.045 |
|
|
|
0.010 |
Brahmin |
|
0.018 |
0.513*** |
0.213 |
|
|
|
0.431*** |
Chhetri |
|
0.251* |
0.053 |
-0.010 |
|
|
|
0.310** |
Vaisya |
|
0.272* |
-0.006 |
-0.147 |
|
|
|
0.167 |
SESL3 |
|
0.289** |
0.015 |
0.209 |
|
|
|
0.104 |
SESL2 |
|
0.352*** |
0.037 |
-0.056 |
|
|
|
-0.002 |
Independency ratio |
|
-0.049 |
-0.138 |
-0.030 |
|
|
|
0.033 |
a. ns = not significant.
* p<.10.
** p<.05.
*** p<.01.
We were able to operationalize three scales that each reflects a different aspect of household food security. Past household food security, as represented by patterns of food flow through the household during the previous year, is associated with increased frequency of meat consumption and increased variety of food consumed at the time of the interview. Its negative association with consumption of green leafy vegetables in the second household food-frequency survey performed three to four months later is perplexing and requires further investigation. Possibly more food-secure households are replacing their intake of green leafy vegetables with other foods. Current household food security, represented by household food stores, appears to be a useful predictor of increased frequency of meat and dairy intake and of overall dietary variety. Future household food security, represented by the amount of land planted in different crops and by animal holdings, is associated with increased total dietary variety and future consumption of dairy products. The lack of associations between future household food security and the second food-frequency measure is unexpected, as one would hope that measures of household food security would be useful in predicting inadequacies in household food supplies later in time. One possibility is that our second measure of household food consumption may have been taken too early. It was conducted during the pre-monsoon and monsoon season when most crops had not been harvested, and therefore we were apparently unable to see the effects of planting on household supply and consumption patterns. A limitation of this study was that the household food security measurements were performed cross-sectionally. Future studies would be wise to measure household food consumption 6,9, and even 12 months after the initial assessment of food security status. In addition, the concept of household food security also implies stability over time. Ideally, estimates of household food stores should be obtained several times throughout the year to capture the effects of seasonality and other secular trends.
No significant relationships were observed between the household food security scales and the current consumption of grains and beans. This was an expected result, as grains and beans constitute staple foods in this region and are consumed daily in all households. Nor were associations observed between the household food security scales and consumption of other vegetables and fruits. The availability of these foods is highly seasonal, which undoubtedly reduced the chance of finding significant associations.
It is clear also from the analyses that household food consumption patterns are the product of several factors in this setting. Socio-economic status plays a role in predicting the total dietary variety of foods consumed and the frequency of consumption of food groups such as beans, tubers, and green leafy vegetables. This finding agrees with other research in the region [36, 37].
Perhaps surprisingly, socio-economic status is not correlated or, in some cases, is negatively correlated with the consumption of meat and dairy products. The effect of caste status of the household is very strong and appears to predict consumption in every food group. In general, due to dietary prohibitions, members of higher castes (especially Brahmins) are much less likely to consume meat than members of lower castes. This finding helps to explain why socio-economic status is negatively correlated with meat consumption in this setting. On the other hand, members of higher castes are much more likely to consume dairy products and to eat green leafy vegetables.
Overall, the operationalization of household food security in research studies has traditionally focused on specific, easily measured aspects, such as current food supply, individual caloric intake, and so on, without capturing the complexity of household food security. It appears that the traditional economic focus on staple grain supply as the indicator of national food security has translated into a focus on total caloric intake and anthropometric status as primary indicators of household food security [38]. This definition overlooks the issue of stability in household food security as well as the role of dietary quality. Recent studies indicate that although total caloric consumption is correlated with consumption of other macronutrients, it is not necessarily correlated with micronutrient intake, particularly for vulnerable subgroups within the household [28]. Economic studies have found that the income elasticity of staple foods is much less than that of non-staple foods; this reinforces the need to look at dietary quality rather than quantity, since this is where the most variability among households occurs.
Operational frameworks used for empirical measurement of household food security therefore need to evolve to encompass a broader range of components, such as those identified in this paper. Our findings indicate that our three components of household food security - past stable supply, current stores, and future production - were differently associated with intakes of different foods. Both stability and adequacy of household food supply need to be included in the operationalization. Within adequacy of food supply, both the quantity and the quality of food should be measured.
The conceptual approach used here to operationalize household food security is based on the creation of three scales, representing past, current, and future food security. Factor analysis enabled us to construct these scales in the rural Nepalese setting as stability of food flow, current food stores, and investment in future food production, respectively. It will be important to further test and refine these scales in other settings. Further analytic work needs to be done to examine the relationship between these scales and individual dietary intake and nutritional status. Household food-frequency data, while relatively easy to collect, are a crude indicator of consumption patterns within the household and cannot reflect within-household differences.
We feel that we have developed a useful conceptual framework for food security at the household level that comes closer to capturing the complex dynamic that results in the household production of nutritional status and health. Using this conceptual framework, we were able to identify components of household food security that can serve as proximate determinants of household food consumption patterns, and perhaps eventually as indicators of individual dietary intake and nutritional status.
Acknowledgements
We gratefully acknowledge the field assistance of Meera Thapa Gittelsohn. This research was supported by grants from the Cultural Anthropology Program of the National Science Foundation, the Wenner-Gren Foundation for Anthropological Research, the University of Connecticut Health Center, and the Office of Health and Nutrition, US Agency for International Development, under Cooperative Agreement DAN 0045-A-00-5094-00 with Johns Hopkins University. We would also like to acknowledge the helpful comments of Anita V. Shankar and Margaret E. Bentley on earlier drafts.
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