Journal of the New Zealand Medical Association, 14-December-2012, Vol 125 No 1367
Emergency food storage for organisations and citizens in New Zealand: results of optimisation modelling
Nhung Nghiem, Mary-Ann Carter, Nick Wilson
New Zealand is subject to wide range of natural disasters including: “earthquakes, volcanic eruptions, tsunamis, storms, floods and landslides”.1 In particular, the country lies in a geologically unstable zone with major fault lines running for much of the length of the country. Most recently an earthquake on 22 February 2011 caused widespread destruction of Christchurch with 182 deaths and 6659 people injured in the initial 24 hours.2
Flooding, due to intense or prolonged rain, is by far the most frequent natural disaster to impact on New Zealand.1 Flooding disasters, as well as severe storms, may also become more common with climate change.3 New Zealand’s population growth may also contribute to the impact of flooding disasters, if house building continues on flood plains and low-lying coastal areas. Pandemics and economic disasters can also potentially cause disruptions to basic societal functions, including food supply.
Due to the risk of these disasters, New Zealand civil defence authorities encourage preparation measures—including emergency food storage. Food storage of “non-perishable food (canned or dried food)” for a minimum of 3 days is encouraged and a civil defence website provides tips on the type of dried and canned foods which can be stored.4 More specific lists of foods, but with no explicit consideration of cost or nutritional value, are detailed on local government websites (e.g., Porirua City Council5).
Yet there is evidence that such types of disaster preparations are not fully made by the New Zealand population (e.g., while 92% of respondents in a flood-prone area reported having canned food, only 27% had bottled water).6 Indeed, food insecurity is a significant problem for low-income populations in New Zealand,7–9 and so it is likely that such households often have no emergency food supplies. A recent study found that in the preceding 12 months, 50% of the families in a longitudinal study reported that they had been “forced to buy cheaper food in order to afford other necessities” and 13% of the families “reported having used food grants or food banks”.10
Due to the high prevalence of obesity and over-weight, most New Zealanders actual carry many days of stored energy in their bodies in fat deposits. Nevertheless, for optimal physical functioning in a disaster setting, on-going access to food containing carbohydrates, protein and fat is highly desirable. This is particularly the case for those contributing to disaster rescue and relief work and those subject to increased energy requirements (e.g., via physical activity and exposure to cold). Similarly, food can provide psychological comfort, prevent additional anxiety associated with hunger, and facilitate going to sleep at night. Preparing and eating food with others may also contribute to a sense of normality and communal experience in a disaster setting.
A particular method for identifying low-cost foods that meet nutrient requirements is through linear programming. For example, this technique has been used to consider optimisation of diets in a number of studies (e.g., in France,11 for a cancer prevention diet,12 a diet without processed foods,13 and for designing the “Thrifty Food Plan”14—albeit using a non-linear programming for the latter). Given this background, the aim of this study was to perform optimisation analyses for the New Zealand context to inform emergency food stockpiling policies that organisations can promote (e.g., civil defence) and that citizens can consider.
Initial food selection—Given the thousands of different food products for sale in New Zealand, we had to take a simplified approach for selecting food products to include in the modelling. We therefore used dried, processed or canned foods from:
Scenarios—The first scenario (EP-B) considered achieving daily dietary energy intake for men at the lowest cost, and included foods which required cooking (Table 1). The second (EP-NC) added the requirement that foods did not need to be cooked (while also allowing some foods to be able to be sprouted or soaked before eating). The next scenario (EP-H) included foods that were optimised for low-cost, but also to meet all nutrient requirements for men (albeit with a higher iron requirement to increase relevance for women). The last scenario (EP-NS) considered the situation of zero spoilage (e.g., well-organised storage by institutions).
Table 1. Specific scenarios used for the optimisation modelling for determining emergency foods for storage
Data inputs (price and nutrients)—For food items from the FPI we used the relevant price data (monthly data averaged over multiple stores nationally for the 12 months of 2011).15 But for other food items, we used online supermarket data (Countdown, January 2012), or the lowest in-store (e.g., bulk bin) prices from New World or Countdown supermarkets (both in Karori, Wellington). We ignored prices on “specials” and only considered non-bulk products (i.e., ≤1.5 kg).
Nutrient values for the foods were obtained from the “New Zealand food composition database” (New nutrient database in 2012: http://www.foodcomposition.co.nz/foodfiles). Nutrient intakes were adjusted to account for food spoilage (see below).
Spoilage estimates—We found no data on the rates of spoilage of stored food in New Zealand (and international data on household food wastage was not considered applicable17). So we made informed guesses as follows for the condition of stored emergency food at the one-year point:
We applied these estimates as per the details in Table 2, but also in one Scenario (EP-NS) we assumed no loss from spoilage or other storage related losses.
Table 2. Foods entered into the model, price data inputs and spoilage factors (foods ordered by increasing price within each food category)
* These canned foods may be preferable to eat when heated – but most people would probably consider it reasonable to eat these foods cold in emergency situations.
** All these foods are pre-cooked or cured and can be eaten directly out of the can.
w Requires stored water (e.g., for cooking or to make up liquid milk from powdered milk).
# We used the formula: 95%UI=(2SD)/Mean with standard deviation (SD) = 20% of the point estimate.
Approach to mathematical modelling—We used the simplex algorithm to solve this linear programming problem (see Briend et al,21 for a detailed description of the linear programming). The scenarios were modelled in Microsoft Excel 2010 (Excel Solver, Simplex method).
Approaches to uncertainty—For food prices we generally used the variation in the monthly prices (from the FPI data, fitting to gamma distributions). For non-FPI foods we applied the same patterns used for the FPI foods (e.g., from the median values of the “fresh fruit and vegetable” grouping). With regards to food spoilage, we applied a beta distribution for the total food spoilage proportion with the uncertainty values as per Table 2.
There is also heterogeneity in nutrient requirements for men and so we utilised the uncertainty data identified in nutritional guidelines for Australia and New Zealand (Table 3, and applying normal distributions). But for the target energy intake we derived uncertainty values from the published survey results (based on the 95%CIs in the NZANS20 we assumed a normal distribution with SD = 184.4).
We then coded the models and ran 2000 iterations for a representative scenario in the R programming language (version 2.14.1, lpSolve package).
Table 3. Nutrient levels used for targets or constraints used for the achieving all nutrients scenario (Scenario EP-H) with most of these being “estimated average requirements” (EARs)* of nutrients per day for adult men (based on values set for Australia and New Zealand19 unless otherwise stated)
* The focus here was on the range for healthy adult men. Different values may apply to children, adolescents, pregnant and breastfeeding women, and older people. The EAR is defined as “a daily nutrient level estimated to meet the requirements of half of the healthy individuals in a particular life stage and gender group.” In some cases “adequate intake” (AI) was used. This is “the average daily nutrient intake level based on observed or experimentally-determined approximations or estimates of nutrient intake by a group (or groups) of apparently healthy people that are assumed to be adequate. The NHMRC did not set an EAR for carbohydrate due to limited data.
** No standard deviation (SD) was found, and hence SD was set at 10% of the EAR.
The cost of purchasing emergency food supplies to ensure adequate dietary energy (and ignoring other nutrients) was only $2.22 per day (Scenario EP-B, Table 4). The uncertainty analysis around the results of Scenario EP-B is shown in Table 5. This indicates a fairly narrow range of daily costs for the optimised selection of low-cost foods (95% simulation interval [SI] = $2.04 to $2.38). Our requirement for a mix of foods (up to a maximum weight of 100g) increased the cost slightly in Scenario EP-B. However, without such a constraint only flour and vegetable oil would have been selected in Scenario EP-B (i.e., these appear to be the cheapest two foods providing dietary energy).
For emergency food that did not require cooking (Scenario EP-NC) the cost was slightly higher (at $3.67) than Scenario EP-B. Nevertheless, one of the selected foods (dried peas) would require time to sprout.
For the stored emergency foods designed to meet all daily nutritional requirements for men, the purchase cost was substantially higher at $7.10 per day (Scenario EP-H). However, the variety of foods was improved compared to that of the above-mentioned Scenarios (i.e., 10 vs 7 food items). Moreover, this was the only scenario in which the optimisation process involved the selection of fruit or vegetable products.
Where zero spoilage was assumed (i.e., well-organised storage in Scenario EP-NS), the cost of purchasing food for storage was as low as NZ$ 1.93 per day.
Table 4. Foods per person per day (with weights) included in the various emergency food scenarios as a result of the optimisation process
* Flour with oil in EP-B and EP-NS could be used to make scones or rotis. Flour and water in EP-H could be cooked as damper (potentially with some of the sugar used). Additional ingredients would improve the range of options e.g., baking powder, herbs.
Table 5: Uncertainty analysis of selected foods included in the daily dietary scenario for the lowest cost collection of emergency foods (2000 iterations of Scenario EP-B)
* These results are influenced by a small number of values that are outside of the 95%SI.
Main findings and interpretation—This study was able to identify relatively low-cost collections of foods for emergency storage for as low as NZ$ 2.21 per day in the baseline Scenario (EP-B). For the recommended 3 days of food storage per person, this totals to only around $7 per person. The cost was slightly more for storing foods that don’t require cooking (i.e., $11 for 3 days of foods in Scenario EP-NC).
These prices suggest that food storage for emergencies should be feasible for nearly all New Zealand families. Nevertheless, given the issues around food insecurity (see Introduction), the Ministry of Civil Defence and Emergency Management (and other government agencies), may need to assume that home-stored food will not be available for some families. Indeed, this should probably be the default assumption anyway for disasters where buildings are severely damaged by floods or earthquakes and citizens cannot access any of their own household food stockpiles.
This study found that purchasing healthier foods for storage (that meets all daily nutrient requirements for men for 3 days), did cost somewhat more at around $21 for one man for 3 days. Storing these healthier foods are unlikely to be feasible for some low-income families dealing with food insecurity. However, achieving optimal nutrition for a few days is generally relatively inconsequential in disaster situations.
Emergency storage recommendations could focus on ensuring families store non-perishable foods providing sufficient energy with suggested alternatives to provide additional nutrients for special population groups such as children, pregnant and lactating women.
Study strengths and weaknesses—Particular strengths of this study were that it appears to be the first such approach (to our knowledge) of optimising emergency foods for storage in the New Zealand situation. We also included uncertainty analysis, which appears to be rare in such optimisation studies. Yet some specific limitations should be noted as outlined below:
Some of these issues could be addressed by future research such as studies on food spoilage levels in the New Zealand environment. Other optimisation work could consider other issues e.g., what emergency food is best for New Zealand to provide to Pacific Island countries damaged by cyclones.
Possible implications—From a government agency perspective (e.g., civil defence and even the military), these results could inform the promotion of cost-effective food storage decisions for disaster relief planning at the community and household levels. While these agencies do not stockpile emergency food supplies themselves, if they ever decide that this is a worthwhile option then many other issues would be relevant. For example, the economies around food rotation to reduce costs (e.g., consumption by the military on a routine basis); the costs of warehousing; volume and weights of food (if helicopter airlifts were being considered); and what are the foods that are best suited for preparation in a field-kitchen, etc.
At the household level, this information on the cost and nutrition of emergency food may provide reassurance that such planning need not be expensive. But there are other considerations that citizens are likely to be interested in when it comes to emergency food storage:
In summary, it appears to cost very little to purchase basic emergency foods for storage in the current New Zealand setting. The lists of the foods identified in this study could potentially be promoted by organisations who participate in disaster relief (civil defence and the military) but also acted on by citizens.
Competing interests: Nil.
Author information: Nhung Nghiem, Assistant Research Fellow; Mary-Ann Carter, Assistant Research Fellow, Nick Wilson, Associate Professor; Department of Public Health, University of Otago, Wellington
Acknowledgements: This project was part of nutritional optimisation work for the BODE3 programme which receives funding support from the Health Research Council of New Zealand (Project number 10/248).The authors also thank Professor Tony Blakely, Dr Giorgi Kvizhinadze and Dr Linda Cobiac for helpful advice.
Correspondence: Dr Nick Wilson, Department of Public Health, University of Otago Wellington, PO Box 7343 Wellington South, New Zealand. Email firstname.lastname@example.org
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