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14.1: Food Security - Biology

14.1: Food Security - Biology



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Progress continues in the fight against hunger, yet an unacceptably large number of people lack the food they need for an active and healthy life. The latest available estimates indicate that about 795 million people in the world – just over one in nine –still go to bed hungry every night, and an even greater number live in poverty (defined as living on less than $1.25 per day). Poverty—not food availability—is the major driver of food insecurity. Improvements in agricultural productivity are necessary to increase rural household incomes and access to available food but are insufficient to ensure food security. Evidence indicates that poverty reduction and food security do not necessarily move in tandem. The main problem is lack of economic (social and physical) access to food at national and household levels and inadequate nutrition (or hidden hunger). Food security not only requires an adequate supply of food but also entails availability, access, and utilization by all—people of all ages, gender, ethnicity, religion, and socioeconomic levels.

From Agriculture to Food Security

Agriculture and food security are inextricably linked. The agricultural sector in each country is dependent on the available natural resources, as well as the politics that govern those resources. Staple food crops are the main source of dietary energy in the human diet and include things such as rice, wheat, sweet potatoes, maize, and cassava.

Food security

Food security is essentially built on four pillars: availability, access, utilization and stability. An individual must have access to sufficient food of the right dietary mix (quality) at all times to be food secure. Those who never have sufficient quality food are chronically food insecure.

When food security is analyzed at the national level, an understanding not only of national production is important, but also of the country’s access to food from the global market, its foreign exchange earnings, and its citizens’ consumer choices. Food security analyzed at the household level is conditioned by a household’s own food production and household members’ ability to purchase food of the right quality and diversity in the market place. However, it is only at the individual level that the analysis can be truly accurate because only through understanding who consumes what can we appreciate the impact of sociocultural and gender inequalities on people’s ability to meet their nutritional needs.The definition of food security is often applied at varying levels of aggregation, despite its articulation at the individual level. The importance of a pillar depends on the level of aggregation being addressed. At a global level, the important pillar is foodavailability. Does global agricultural activity produce sufficient food to feed all the world’s inhabitants? The answer today is yes, but it may not be true in the future given the impact of a growing world population, emerging plant and animal pests and diseases, declining soil productivity and environmental quality, increasing use of land for fuel rather than food, and lack of attention to agricultural research and development, among other factors.

The third pillar, food utilization, essentially translates the food available to a household into nutritional security for its members. One aspect of utilization is analyzed in terms of distribution according to need. Nutritional standards exist for the actual nutritional needs of men, women, boys, and girls of different ages and life phases (that is, pregnant women), but these “needs” are often socially constructed based on culture. For example, in South Asia evidence shows that women eat after everyone else has eaten and are less likely than men in the same household to consume preferred foods such as meats and fish. Hidden hunger commonly results from poor food utilization: that is, a person’s diet lacks the appropriate balance of macro- (calories) and micronutrients (vitamins and minerals). Individuals may look well nourished and consume sufficient calories but be deficient in key micronutrients such as vitamin A, iron, and iodine.

When food security is analyzed at the national level, an understanding not only of national production is important, but also of the country’s access to food from the global market, its foreign exchange earnings, and its citizens’ consumer choices. However, it is only at the individual level that the analysis can be truly accurate because only through understanding who consumes what can we appreciate the impact of sociocultural and gender inequalities on people’s ability to meet their nutritional needs.

Food stability is when a population, household, or individual has access to food at all times and does not risk losing access as a consequence of cyclical events, such as the dry season. When some lacks food stability, they have malnutrition, a lack of essential nutrients. This is economically costly because it can cost individuals 10 percent of their lifetime earnings and nations 2 to 3 percent of gross domestic product (GDP) in the worst-affected countries (Alderman 2005). Achieving food security is even more challenging in the context of HIV and AIDS. HIV affects people’s physical ability to produce and use food, reallocating household labor, increasing the work burden on women, and preventing widows and children from inheriting land and productive resources.

Obesity

Obesity means having too much body fat. It is not the same as overweight, which means weighing too much. Obesity has become a significant global health challenge, yet is preventable and reversible. Over the past 20 years, a global overweight/obesity epidemic has emerged, initially in industrial countries and now increasingly in low- and middle-income countries, particularly in urban settings, resulting in a triple burden of undernutrition, micronutrient deficiency, and overweight/obesity. There is significant variation by region; some have very high rates of undernourishment and low rates of obesity, while in other regions the opposite is true (Figure (PageIndex{1})).

However, obesity has increased to the extent that the number of overweight people now exceeds the number of underweight people worldwide. The economic cost of obesity has been estimated at $2 trillion, accounting for about 5% of deaths worldwide. Almost 30% of the world’s population, or 2.1 billion people, are overweight or obese, 62% of whom live in developing countries.

Obesity accounts for a growing level and share of worldwide noncommunicable diseases, including diabetes, heart disease, and certain cancers that can reduce quality of life and increase public health costs of already under-resourced developing countries. The number of overweight children is projected to double by 2030. Driven primarily by increasing availability of processed, affordable, and effectively marketed food, the global food system is falling short with rising obesity and related poor health outcomes. Due to established health implications and rapid increase in prevalence, obesity is now a recognized major global health challenge.


Food preservation includes the handling or treating of food to prevent or slow down spoilage. Preservation guards against foodborne illnesses and also protects the flavor, color, moisture content, or nutritive value of food. There are many different ways to preserve food. Some methods that have been practiced for generations include curing, smoking, pickling, drying, salting, fermenting, canning, freezing, and refrigeration. Others methods include:

  • Pasteurization. This technique exposes the food/beverage to high heat for a short period of time. This method is effective in killing microorganisms that may cause spoilage or foodborne illness. Since the food/beverage is only exposed for a short amount of time (typically less than 20 seconds), taste and quality are not impacted.
  • Aseptic packaging. Food and beverages are first sterilized using ultra-high temperatures, then cooled and placed in sterile containers that are then sealed.
  • Irradiation. This process involves treating food with ionizing radiation, which kills the bacteria and parasites that cause toxicity and disease. Irradiated food must be labeled with a Radura symbol (see Figure (PageIndex<1>)) 2 .

The relationship between food security and quality of life among pregnant women

Background: Household food insecurity through influencing the quality and sufficiency of nutrition can have considerable effects on individuals' health. Previous studies have shown the relationship between household food insecurity and quality of life among adults, infants, and people of minority ethnicity. However, no studies have been conducted on household food insecurity and quality of life among pregnant women. This study aimed to investigate the effect of food insecurity on quality of life among pregnant women in Qazvin city, Iran.

Methods: This cross-sectional study was conducted between May 2017 and November 2017 on 394 pregnant women. A random cluster sampling method was used to select eight urban health and medical centers from four geographical regions of Qazvin city, Iran. In the selected centers, pregnant women were recruited using eligibility inclusion criteria. Data was collected using the SF-36 Health-related Quality of Life, Household Food Insecurity Access Scale and a demographic questionnaire for recording the women's gestational and demographic information through interviews. Descriptive and inferential statistics including Chi-square test, one-way analysis of variance with Bonferroni post-hoc test and multiple linear regression were used for data analysis. P < 0.05 was considered statistically significant.

Results: Food insecurity was reported in 43.9% of the pregnant women. Overall pregnant women's quality of life had the highest score (Mean ± SD) in the domain of 'social performance' (76.4 ± 21) and the lowest one in the domain of 'role limitation due to physical reasons' (60.5 ± 43). Pregnant women with food insecurity had the lowest score in role limitation due to physical reasons domain of quality of life (68.6 ± 40.4, 61.3 ± 45.5 & 51.3 ± 47.7 respectively for mild, moderate and sever food insecurity). The results of multiple linear regression showed that one unit reduction of household food security significantly decreased the total quality of life score by 5.2 score (95% CI: -9.7, - 0.7) among the mild food insecure group, 10.8 score (95% CI: -17.1, - 4.6) among the moderate food insecure group and 14.1 score (95% CI: -19.7, - 8.5) among the sever food insecure group.

Conclusions: Screening of the household food security status during the primary prenatal care can identify high-risk pregnant women to improve the quantity and quality of their diet. Moreover multi-level actions including policy-making, supplying resources, and providing appropriate services are needed to ensure that pregnant women have access to high-quality foods.

Keywords: Food insecurity Health-related quality of life Pregnancy.

Conflict of interest statement

The research proposal was approved by the Research Review Board affiliated with Qazvin Faculty of Nursing and Midwifery (decree code: IR.QUMS.REC.1394.351 in the Ethics Committee affiliated with Qazvin University of Medical Sciences). Permissions to enter health and medical centers were obtained from authorities of Qazvin University of Medical Sciences. Next, the researcher introduced himself to the women. After expressing objectives, assuring the participants about confidentiality of their data and possibility of withdrawing from the study, the written informed consent form was signed by those women who were willing to participate in this research.

The authors declare that they have no competing interests.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Methods

Setting and study participants

This study was conducted at a community health center in Chelsea, Massachusetts. Chelsea is a diverse city where approximately 60% of the residents speak languages other than English and 62% of the population is Hispanic (12). Income below 200% of the federal poverty level was reported by 43% of health center patients (13).

From October 1, 2009, through March 31, 2010, all patients seen at the adult medicine practice were offered screening to assess food insecurity. Follow-up data on BMI were collected through August 31, 2013. All patients aged 18 years or older who visited the adult medicine clinic during the study period were eligible for the quantitative study. For the qualitative study, all patients with a measured BMI who reported food insecurity were eligible.

This study was approved by the Partners HealthCare Institutional Review Board, with waiver of informed consent for the secondary use of clinical data in the quantitative study. Focus group participants gave written informed consent.

Assessment of food insecurity and BMI

Food insecurity was assessed at visit check-in (Appendix A) as part of determining eligibility for the Food for Family Program, which provides food pantry information, nutrition counseling, and other food resources to food insecure patients (14). A patient was considered to have reported food insecurity if he or she responded affirmatively to either of the 2 following questions: 1) In the past month, was there any day when you or anyone in your family went hungry because you did not have enough money for food? 2) Would you be interested in having someone contact you to talk more about getting food resources for you and your family?

The primary outcome for this study was BMI, taken by trained clinic staff at routine clinic visits. The BMI derived from the weight and height measurements taken during the visit when food insecurity was assessed was considered the baseline value.

For comparison in the quantitative analyses, we created a matched cohort from patients who visited the adult medicine practice during the time of the screening program but did not report food insecurity. This cohort was matched with food insecure patients on the basis of age, sex, and race/ethnicity in a 10:1 ratio. Controls could be matched to more than 1 food insecure participant.

Covariates

We considered several covariates that may be associated with food insecurity, BMI, or both (3,8,10), which were abstracted from a repository of electronic health data. These included age, sex, race/ethnicity, educational attainment (<high school diploma vs &gehigh school diploma), insurance (commercial, Medicare, Medicaid, or none/self-pay), and primary language spoken (English vs non-English). We used median household income, assessed at the block group level using United States Census data (15), to indicate neighborhood differences.

To evaluate the association between food insecurity and BMI, we compared participants who screened positive for food insecurity to their matched controls. Similar to data quality assurance procedures used in the National Health and Nutrition Examination Survey (NHANES) (16), values for weight or height that were above the national 99th percentile or below the 1st percentile were flagged for review. Of 40,013 observations, we excluded 7 weight values of less than 5 kg and 6 weight values greater than 640 kg as not physiologically reasonable. No height measurements were excluded. We then conducted descriptive statistics and compared the groups at baseline using &chi 2 tests for dichotomous variables and t tests or Wilcoxon tests (when distributions were non-normally distributed) for continuous variables. In this pragmatic study, we relied on data obtained in routine clinical care. This process resulted in an unbalanced design with varying intervals between measurements, so we used longitudinal linear mixed effect models to determine if changes in BMI (and weight) over time differed by food security status, using a time-by-food-security interaction term and accounting for repeated measures within patients with random effects modeling. We conducted both unadjusted longitudinal analyses and analyses adjusted for the covariates described above, including age, race/ethnicity, and sex to account for differences that persisted despite matching. All quantitative analyses were conducted with SAS version 9.3 (SAS Institute). Because weight has a curvilinear relationship with age, increasing through middle age and then decreasing among older adults (17), we modeled age with both a linear and a quadratic term.

During the study period, height was not consistently recorded in the electronic health record, which led to 24% of food insecure patients and 38% of matched controls lacking height data needed to calculate a BMI. To ensure that missing height data did not introduce bias, we conducted sensitivity analyses using weight in kilograms, which was available for all patients, as the outcome variable, in what were otherwise the same models used for the BMI analysis.

Qualitative analysis

The purpose of the focus groups was to understand barriers to healthy eating among patients with food insecurity and to learn successful strategies to avoid obesity despite adverse circumstances (positive deviance). We developed a focus group guide by reviewing behavior theories from the health belief model (18), social cognitive theory (19), and the people and places framework (20). Some sample questions were adapted from the flexible consumer behavior survey module used in fielding NHANES 2009&ndash2010 (21). The focus group guide was piloted and translated before use (Appendix B).

Patients who reported food insecurity and had BMI data available were selected at random and invited to participate the focus groups. Our maximum number of contact attempts was 3. Participants were stratified on the basis of BMI (BMI >30 kg/m 2 vs &le30 kg/m 2 ) and primary language spoken (English vs Spanish). Prospective participants were offered lunch and $12 in grocery store coupons or $10 gift cards for participation.

We planned to have 4 focus groups, 1 for each stratum. However, because of limited participation, we completed 1 focus group among English-speaking participants with BMI >30 kg/m 2 (n = 7), 2 English-language focus groups with participants with BMI &le30 kg/m 2 (n = 2 for each), and one Spanish-language focus group combining BMI strata (n = 10).

The focus groups were digitally recorded and then transcribed verbatim. From these records, emergent themes were identified by individual reviewers, who undertook open coding of the data. Next, coders met and reached consensus about themes. One source of influence for thinking about the themes as they emerged was the theory of people and places (20). This framework is an ecological model of health, which organizes factors that might support or thwart health. Key factors include attributes of people, including skills such as budgeting and portion control, and attributes of places, including local community organizations, or state and national policies and programs. Once themes emerged, we presented our findings to the Healthy Chelsea Coalition, a nonmedical community organization concerned with obesity in Chelsea, and community health care providers, who found these themes to be in accord with their experience.


Food Insecurity And Negative Health Outcomes

The USDA, in consultation with other federal agencies, academics, and members of the policy community, developed the food insecurity measure used in the United States in part because of the myriad negative health outcomes that were thought to be associated with food insecurity. Understanding the existence of certain negative health outcomes that stem from food insecurity is of direct importance to health care professionals and to the policy makers and program administrators charged with improving health and well-being. After the introduction of the CPS-FSS, dozens of papers have examined whether food insecurity is associated with poor health outcomes. Controlling for other confounding factors, such as income, is especially important because many of the determinants of food insecurity are also determinants of health.


Which Food Security Determinants Predict Adequate Vegetable Consumption among Rural Western Australian Children?

Improving the suboptimal vegetable consumption among the majority of Australian children is imperative in reducing chronic disease risk. The objective of this research was to determine whether there was a relationship between food security determinants (FSD) (i.e., food availability, access, and utilisation dimensions) and adequate vegetable consumption among children living in regional and remote Western Australia (WA). Caregiver-child dyads (n = 256) living in non-metropolitan/rural WA completed cross-sectional surveys that included questions on FSD, demographics and usual vegetable intake. A total of 187 dyads were included in analyses, which included descriptive and logistic regression analyses via IBM SPSS (version 23). A total of 13.4% of children in this sample had adequate vegetable intake. FSD that met inclusion criteria (p ≤ 0.20) for multivariable regression analyses included price promotion quality location of food outlets variety of vegetable types financial resources and transport to outlets. After adjustment for potential demographic confounders, the FSD that predicted adequate vegetable consumption were, variety of vegetable types consumed (p = 0.007), promotion (p = 0.017), location of food outlets (p = 0.027), and price (p = 0.043). Food retail outlets should ensure that adequate varieties of vegetable types (i.e., fresh, frozen, tinned) are available, vegetable messages should be promoted through food retail outlets and in community settings, towns should include a range of vegetable purchasing options, increase their reliance on a local food supply and increase transport options to enable affordable vegetable purchasing.

Keywords: child food security regional and remote Australia vegetables.

Conflict of interest statement

Potential perceived conflict of interest: Stephanie L. Godrich is a consultant of Foodbank WA, a food relief organisation that delivers nutrition education and cooking sessions with WA schools and communities.


Materials and Methods

Study Areas.

Three different representative maize planting regions in China were selected: Northeast China (45–55 °N, 110–125 °E), the North China Plain in central-eastern China (32–41 °N, 113–120 °E), and Northwest China (34–40 °N, 105–115 °E). These three areas provide ≈80% of Chinese maize production.

Integrated Soil–Crop System Management.

A total 66 experiments were conducted in three main maize production areas, including 16 in the North China Plain in central-eastern China, 11 in Northeast China, and 39 in Northwest China. At a given site, the most appropriate crop system combination of planting date, crop maturity, and plant population was designed according to long-term weather data and the Hybrid-Maize simulation model. In the Northeast and Northwest China, maize is planted in the spring, with a single crop each year thus planting date, varieties, and density all could be modified by the ISSM approach. In the North China Plain, maize is double-cropped each year with winter wheat, and therefore the maize planting date cannot be changed. However, plant density can be increased, and varieties with longer growth period can be selected within the double-cropping system.

Nitrogen fertilizer application was based on the IRNM approach (with soil mineral N testing) in three initial experiments (28, 29, 36) and on the “simplified IRNM” approach (without soil testing) in another 63 experiments. For the IRNM approach, the maize growth period was divided into five periods: from planting to six-leaf stage (V6), V6 to 10-leaf stage (V10), V10 to anthesis (R1), R1 to blister stage (R2), and R2 to physiological maturity (R6). We sought to have 80, 130, 130, 140, and 120 kg ha −1 of N, respectively, available to the crop in each of these periods. For the “simplified IRNM” approach, the total N fertilizer rate for the whole maize growing season was calculated according to expected yields and the N input–output balance. The proportion of N applied during each period was calculated according to a maize crop N demand curve, with the largest amount N fertilizer applied during rapid growth stages.

All experimental fields received appropriate amounts of phosphorus and potassium fertilizer according to soil testing, weeds were well controlled, and no obvious water or pest stress was observed during the maize growing season. Soil tillage and pest management were optimized according to local ecological conditions in this ISSM approach. Maize was planted in the spring and rain-fed in all experiments in Northeast China and most in Northwest China maize was planted in summer and irrigated in all experiments in the North China Plain and some in Northwest China. Irrigation was optimized according to local ecological conditions in the ISSM approach.

Farmers’ Practice.

In this study, 4,548 farmers from 64 counties in five provinces were surveyed. A multistage sampling technique was used to select representative farmers for inquiry. In each county, 4–14 townships were randomly selected, then four to six villages were randomly selected in each township, and then 8–10 farmers were randomly surveyed to determine the form of fertilizer they used, application rate, timing, technique, and grain yield in past year.

High-Yielding Studies.

We summarized published information from 43 sites in which high-yielding studies had been carried out. Of these data, 29 sites were published in journals (37–39), and 14 sites came from a project workshop (40). These sites were distributed in the main maize production areas in China all sites sought to maximize yields regardless of the cost of agricultural inputs, and all made use of favorable combinations of soil, climate, and crop management in selected fields.

Statistical Analysis.

We used the Hybrid-Maize model (29) to simulate maize yield potentials. The yield potential is defined here as the modeled maximum yield that could be achieved under the management, soil, and weather conditions specified it is not the same parameter as the yield ceiling. Hybrid-Maize requires daily weather variables: total solar radiation, minimum air temperature, and maximum air temperature. Other input settings include crop variety, water regime, and soil properties. In this study, we simulated maize yield potential in all 66 experiments in our ISSM studies and in all 43 sites where high-input, high-yielding studies had been reported.


Results and Discussion

Food Security Among Households and Per Capita Monthly Food Expenditure

Table 2 reports the estimates of the food insecurity levels of the households studied. Based on food insecurity measure generated from the adopted poverty measure, food insecurity head count (P0) represents the proportion of household below the food security line (Foster et al. 1984). Food insecurity depth (P1) represents the expenditure proportion required to allow households below the food security line acquire the minimum food expenditure that moves them out of food insecurity. The food insecurity severity index (P2) represents how severe the insecurity situation among the households was. With the MPCHFE of ₦ 3965.495 and food security line estimated at ₦ 2643.663. Food insecurity incidence of 23.20% was found indicating that 76.8% of the households were food secure. Meanwhile ₦ 218.10 additional food expenditure is needed to draw a food insecure household out of food insecurity domain as indicated by the 5.5% food insecurity points.

Distribution of Food Insecurity Indices by Socio-Economic Characteristics

As shown in Table 3, households were described through their socio-economic characteristics based on the food insecurity measure generated by the adopted Foster et al. (1984). Higher count (P0) implies higher incidence of food insecurity, higher P1 implies higher depth of food insecurity and higher P2 values implies more severe food insecurity situation. Incidence of food insecurity of 33% was higher among the male household heads than the 29% found among their female counterparts. Among the male headed households, 8.3% increase in per capita food expenditure is needed to draw the food insecure households to food insecurity line as against 7.7% increase required for the female-headed households. Though contrary to expectation, this results agree with Adekoya (2014). The probable reason for this result may be due the role of women regarding food preparation and child care which makes them spend their income on food and their children’s needs (Fortmann 2009).

Food insecurity incidence increased with age as could be seen across the age categories. It was highest (84.1%) among households headed by individuals within 76–100 years age bracket. Highest depth (2.99%) and severity (11.8%) were also among household headed by individuals within this age bracket, which agrees with the findings by Ogundipe et al. (2019). However, households headed by individuals in the extreme age categories of ≤ 25 years and ≥ 101 years experienced no food insecurity. This could be due to the fact that while households headed by individuals that were ≤ 25 years old are more economically active and could engage in profitable livelihood activities (Umeh and Asogwa 2012 Matchaya and Chilonda 2012), those headed individuals that were ≥ 101 were aged and as opined by Cai et al. (2012), these elderly individuals would most likely enjoy remittance supports from their migrant children and family members.

With respects to household size, larger households had more incidences of food insecurity. While households with ≤ 5 members had 6.4% food insecurity incidence, those with ≥ 16 members had 71.4% incidence. In consonance with Adekoya (2014), the same trend was found with regards to both depth and severity of food insecurity given the highest values of 24.4% and 10.9%, respectively among households with ≥ 16 members. Although incidence of food insecurity decreased with the size of maize farm cultivated among the households, it is surprising and contrary to expectation that households cultivating 16–20 hectare of maize farm had the highest (100%) food insecurity incidence and corresponding 68.8% and 47.4% for depth and severity of food insecurity, respectively. These findings may well be due to inefficiency in resource use as found by Opaluwa et al. (2014) among maize farmers in Kogi State, Nigeria.

Determinants of Food Security Among Households

We present in Table 4 the drivers of food security among the smallholder maize farmers in Ogun State, Nigeria. Additionally, we assessed the gender differential of drivers of food security among the maize farming households. The results show that distance from village to the nearest town, participation in GESS, gender of household head, household size, visit from extension agents in the last 3 years, participation in field days/seminar training, access to improved farm input, total farming experience, value of output, access to market information, membership of any association and access to credit significantly affect food security among the maize farmers in the study area.

Years of education negatively and significantly influence the probability that a household would be food insecure. Similar results were obtained in the three context considered (pooled, male-headed and female-headed households). This implies that a household becomes less vulnerable to food insecurity with increasing educational attainment. Imperatively, the higher the number of years of schooling, the lowers the probability that a household head, either headed by male or female, will be exposed to food insecurity. This conforms to other studies (Babatunde et al. 2010 Adeyemo and Olajide 2013 Adamu et al. 2015 Ogunniyi et al. 2016 Olagunju et al. 2019 Omotayo 2017). These studies suggested that education attainment decreases food insecurity headcount. Education is expected to lead to increased earning potential and improve occupational and geographical mobility of labour. Higher levels of educational attainment will provide higher levels of welfare (such as food security) for the household.

Distance to the nearest town positively influenced food insecurity status among the households. The result suggest that as the distance to the nearest town increases, probability of experiencing food insecurity increases by 30.4% only for the female-headed households. This implies that households living far from urban towns are more likely to be food insecure. This is due to the fact that such households may not be able to access input market which may in turn affect their productivity and income. Participation in the Federal government growth enhancement support scheme (GESS) programme positively influenced food insecurity among female-headed households. Participating in GESS programme increases the probability of being poor by 30.4% among the female-headed households. This is consistent with expectation, following the finding of Adenegan et al. (2018) and Omotayo et al. (2017) that participation GESS increased the farmers’ on-farm income.

Gender of household head is positively related to food insecurity status of farming households in the study area. The result show that being a male household head increases the probability of being food insecure by 9.9%points in the pooled data. Although this contradicts findings of Obayelu and Orosile (2015) and Awotide et al. (2011), but it complies with Milazzo and Van de Walle (2015) which found that the declining aggregate food insecurity incidence has been observed among the female-headed households in Africa. Interestingly, size of households had a positive and significant influence on their food insecurity status. An addition to the size of the household increases the probability of being food insecure by 5.7% points in the pooled estimates. The same unit addition increases the probability of being food insecure by 5.0% points and 87.4% points among male and female-headed households respectively. This is in line with previous studies (Omotesho et al. 2007 Ogunniyi et al. 2017, 2018) that found a similar relationship between household size and food security. The result suggest that intra-household food allocation may be affected with larger household size and food per capita expenditure may likely decline due to large family size.

Participating in field days/agricultural seminar training reduced the probability that the households would be food insecure by 16.3% points in the pooled analysis. Among the male-headed households participating in field days/agricultural seminar reduces probability of being food insecure by 25.7% points. The result suggests that training as a form of human capital development can boost income generating capacity and alleviate poverty and food insecurity (Khan and Ali 2014). Access to information about improved maize variety favoured food security as it reduces the probability of being food insecure by 12.9% points from the pooled estimates. The implication of this access to information about sources of improved seed varieties are more likely to be food secure. Whereas among the female headed households, access to such information reduces probability being food insecure by 98.5% points, it had no significant effect among the male-headed households. This food insecurity reduction may be due to the positive impact of such information on adoption of improved seed varieties and the associated boost in productivity as observed by Ndaghu et al. (2015).

Quantity of maize output recorded (kg) favoured food security among the households. The probability that the households would be food insecure decreased by 18% points based on the pooled estimates. While probability to experience food insecurity reduced by 19.7% points among the male-headed households, the contrary was found among female-headed households where probability of being food secure increased by 10.3% points per kg increase in quantity of maize output produced. However, this is contrary to expectation as women are believed to have less access to productive resources and as such less productive than their male counterpart as found by Tibesigwa and Visser (2016). Access to mobile phone communication favoured food security by reducing the probability of being food insecure by 15% points in the pooled estimates. This is justified as the use of mobile phone promote productivity, reduces transaction cost and boost farmers’ income (Ogunniyi and Ojebuyi 2016).

For the female-headed households however, probability of being food insecure increased by 41% points contrary to expectation. With respect to membership of any association, the pooled estimates showed that the probability of being food insecure reduced by 11.9% points. Likewise for both male and female-headed households, belonging to any association reduced probability of being food insecure by 15.3% and 19.9% points, respectively. By implication, belonging to such association is a form of social capital that may help farmers to increase their income by boosting their bargaining power for higher product pricing and lower input cost, which is in agreement with the report by Ahmed and Mesfin (2017). Finally, access to credit was a negative correlate of food security. Among female-headed household, having access to credit increase the probability of being food insecure by 2.7% points against a priori expectations. However, Ngema et al. (2018) reported similar situation among households in Maphumulo local municipal council of South Africa.


Discussion and conclusions

Studies into food insecurity and climate in Ethiopia are often founded on the presumption that drought causes food insecurity in Ethiopia, and that by extension efforts to reduce the impact of drought through early warning mechanisms, or in the introduction of drought-resilient crops, for example, can tackle food insecurity in the country (Bryan et al. 2009 Cooper and Coe 2011). The definition of drought here is critical. Linking total rainfall to food insecurity in Ethiopia can explain some of the very large-scale events that have occurred (such as in 1984), but this does not explain either the chronic production shortfall that is largely the result of failure to optimise yields, or the majority of acute crises that occur much more frequently and remain a significant challenge. Although the national annual rainfall total is a poor indicator of food insecurity disasters, a localised deficit in rainfall does correspond to localised food insecurity. These events most often occur in the same years that other areas of Ethiopia have average or above average rainfall, and are therefore not associated with widespread reduction in food availability. Drought does, of course lead to crop failure, but it does not have to result in food insecurity. Food security outcomes are as much, if not more, a result of how optimised the food system as a whole is to climate than it is a function of total availability. Therefore, looking at national, or even to some extent sub-national, rainfall variability is a misappropriation of climate as the causal factor for food insecurity in Ethiopia.

Huge gains have been made in improving the national and international response to food security disasters in Ethiopia, and the fact that far fewer people now die in such events than 20 or 30 years ago is a major achievement (FAOSTAT 2014). However, if the ambition is to achieve ‘zero hunger’ by 2030 (UN 2015), then improving the response and resilience to disasters is not enough. It requires recognition that the means to produce enough food to meet the nutritional needs of the whole population of Ethiopia is not limited by climate, but that access to food that is affected by climate and this is a feature of the food system, not an environmental limitation.

The two key aspects of underlying systemic causes of acute food insecurity in Ethiopia are the high proportion of smallholder farmers whose livelihoods depend on sufficient rainfall, and the fact that around 14% (CSA 2016) of the population make those climate-sensitive livelihoods on the very dry, marginal and highly variable land in the east and northeast of the country. Regardless of the levels of climate change projected for the next few decades (IPCC 2013), food insecurity could be addressed by firstly addressing the yield gaps in the most climate-suitable regions to increase national food availability, and secondly, diversifying the incomes of the approximately 13 million people in most climate-challenging regions away from agriculture. As long as these populations are dependent on local rainfall for both availability and access to food, they will continue to experience regular acute food insecurity. Action to improve resilience will reduce the frequency of these events, and improvements in early warning and disaster risk response will reduce the impact of these events, but unless there is a transformational change in the food system in these regions, food insecurity will not be eliminated.

Of course, making such substantial systemic changes is not an easy thing to achieve and are associated with political, social and cultural changes that are not trivial to implement. However, there is a danger that while working with existing systems to build resilience to climate variability through incremental adaptation could reduce the incidence and severity of acute food insecurity crises, it may also further embed communities in livelihoods that are dependent on regular humanitarian assistance to avoid catastrophe.

Climate variability, and indeed food insecurity, has always been a feature of Ethiopia, but the future threats and opportunities for the country require not simply adaptation but transformation. It is important that we fully understand the contribution of both the climate and the food system itself to national food insecurity, in order to address the unprecedented challenge of climate change and achieve the ambitious target of zero hunger by 2030.


Conclusions

This review suggests a compelling association between reduced food security and CVD risk with a particularly strong link between VLFS with CVD risk and evidence that each range of food security presents a unique risk for CVD. Future research using longitudinal individual-level data focusing on CVD outcomes will likely allow researchers to examine how different factors mediate the observed relationships between reduced food security and CVD risk over time, with appropriate adjustment of covariates such as cigarette smoking and physical activity. Policies and public health-based interventions are needed to identify the most vulnerable subgroups experiencing food insecurity, strengthen and enhance access to food assistance programs, and promote awareness and access to healthful foods and beverages to improve nutrition, food security, and cardiovascular health.


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