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The New Zealand Medical Journal

 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
Abstract
Aims New Zealand (NZ), is a country subject to a wide range of natural disasters, some of which (e.g., floods and storms) may increase in frequency and severity with the effects of climate change. To improve disaster preparations, we aimed to use scenario development and linear programming to identify the lowest-cost foods for emergency storage.
Methods We used NZ food price data (e.g., from the Food Price Index) and nutritional data from a NZ food composition database. Different scenarios were modelled in Excel and R along with uncertainty analysis.
Results A collection of low-cost emergency storage foods that meet daily energy requirements for men were identified e.g., at a median purchase cost of NZ$2.21 per day (equivalent to US$1.45) (95% simulation interval = NZ$2.04 to 2.38). In comparison, the cost of such a collection of foods which did not require cooking, was NZ$3.67 per day. While meeting all nutritional recommendations (and not just energy) is far from essential in a disaster setting, if such nutritionally optimised foods are purchased for storage, then the cost would be higher (NZ$7.10 per day). Where a zero level of food spoilage was assumed (e.g., storage by a government agency), the cost of purchasing food for storage was as low as NZ$1.93 per day.
Conclusions 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 could be considered by organisations who participate in disaster relief (civil defence) but also by citizens.

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.

Methods

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:
  • The foods used in compiling the country’s Food Price Index (FPI).15
  • A list in previous work that identified low-cost sources of protein in New Zealand.16
  • Those unprocessed foods that were found in the “bulk bins” of a supermarket and the low-cost canned foods (convenience sample in the capital city, Wellington).
  • The lists of selected foods from a previous nutrition optimisation study in France.11
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
Aim of specific scenario
Additional details on the constraints
EP-B) Baseline scenario, trying to achieve the lowest cost for dried and canned foods
To minimise the daily cost while obtaining the target dietary energy (kJ) detailed in Table 3 and no other nutrient targets. To ensure some modest level of variety (and to protect from some types of foods perishing without being replaced in time), a maximum limit of 100 g per specific food was set except for the amount of vegetable oil (set at 4 tablespoons, i.e., 60 g).
EP-NC) As per Scenario EP-B but only for no-cooking required foods
As above for Scenario EP-B, but only for foods that can be eaten without cooking (e.g., including all canned items in Table 2 such as canned meat/fish, canned pulses, canned fruit, canned vegetables, canned spaghetti, vegetable oil, olive oil, powdered milk etc). But we included grains that could be soaked and then eaten e.g., wholemeal oats. Also included were foods that can be soaked in water and sprouted within a few days e.g., lentils, and dried peas. In this scenario the maximum amount of vegetable oil was set lower than for EP-B (at 2 tablespoons, i.e., 30 g). The lower limit for all foods that were selected in the optimisation process was 10 g.
EP-H) As per Scenario EP-B but to meet all the daily nutritional requirements for men (maximising health)
As above for Scenario EP-B, but where all the nutritional requirements for men are achieved (see Table 3). This can be considered a luxury in disaster circumstances but would give reassurance to those groups who are particularly interested in maintaining good nutrition e.g., for children, pregnant women, lactating women, and adults with chronic health problems. Also in this Scenario, we increased the maximum limit to 200 g per any particular food to ensure that there was a feasible solution in the optimisation process.
EP-NS) As per Scenario EP-B but with no spoilage (e.g., very well-organised storage)
As above for Scenario EP-B, but where there is zero spoilage assumed e.g., very well-organised storage by citizens or by an institution or disaster relief organisation.
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:
  • “High spoilage” at 20% for stockpiled foods that are at particular risk of being damaged by “pantry moths” (e.g., Plodia interpunctella), and weevils e.g., the wheat weevil (Sitophilus granaries) and the rice weevil (Sitophilus oryzae) that are established in New Zealand. Pantry moths may also be an increasing problem in New Zealand.18
  • “Moderate” at 10% for food that can still be damaged by rodents which can eat through plastic wrapping.
  • “Low” at 5% for cans which can rust or glass containers which can break.
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)
Food category / items
Scenario EP-B (All)
Scenario EP-NC (no cooking required)
Price (NZD per 100 g)
Spoilage assumption: point estimate (%)
Spoilage uncertainty interval (%)#
Grains and cereals





Wholemeal flour
Yesw

0.14
20
12–28
White flour (wheat, standard)
Yesw

0.14
20
12–28
Pasta (dried)
Yesw

0.21
20
12–28
Rice (white)
Yesw

0.25
20
12–28
Oats (whole grain, raw)
Yesw
Yesw
0.32
20
12–28
Semolina
Yesw

0.38
20
12–28
Spaghetti (canned)
Yesw **
Yesw **
0.40
5
3–7
Pop corn
Yes

0.79
20
12–28
Couscous
Yesw

0.99
20
12–28
Breakfast biscuits (e.g.,“Weetbix”)
Yesw
Yesw
0.55
20
12–28
Fruit & vegetables





Canned vegetables (“generic brand” tomatoes diced, lowest cost canned vegetables)
Yes*
Yes*
0.24
5
3–7
Canned fruit (“generic brand” fruit salad in syrup, lowest cost canned fruit)
Yes*
Yes*
0.26
5
3–7
Canned fruit (“generic brand” apricot halves)
Yes*
Yes*
0.27
5
3–7
Fruit juice (apple)
Yes
Yes
0.31
5
3–7
Peaches (canned)
Yes
Yes
0.42
5
3–7
Sultanas
Yes
Yes
0.57
10
6–14
Raisins
Yes
Yes
0.79
10
6–14
Meat, fish and dairy





Milk (powdered, skim)
Yesw
Yesw
1.00
10
6–14
Sardines (canned)
Yes*
Yes*
1.22
5
3–7
Tuna (canned)
Yes*
Yes*
1.30
5
3–7
Canned ham (“lite” and “spiced”)
Yes**
Yes**
1.66
5
3–7
Canned sheep meat (“corned lamb”, lowest cost sheep meat)
Yes**
Yes**
1.67
5
3–7
Canned chicken (chicken chunks in spring water)
Yes**
Yes**
2.11
5
3–7
Pastrami (“Instore Deli” lowest cost pastrami/salami, made from beef)
Yes**
Yes**
2.87
10
6–14
Pulses





Dried peas
Yesw
Yes (sprouting)w
0.34
10
6–14
Lentils (canned)
Yes*
Yes*
0.65
5
3–7
Lentils (dried brown)
Yesw
Yes (sprouting)w
0.99
10
6–14
Seeds and nuts





Spreads (peanut butter)
Yes
Yes
0.61
5
3–7
Nuts (peanuts)
Yes
Yes
1.09
10
6–14
Sunflower seeds
Yes
Yes
1.29
10
6–14
Coconut cream
Yes*
Yes*
0.36
5
3–7
Other





Soft drink
Yes
Yes
0.16
5
3–7
Potato crisps (plain)
Yes
Yes
1.17
10
6–14
Sugar (white)
Yes
Yes
0.20
10
6–14
Salt (table)
Yes
Yes
0.24
5
3–7
Oil (vegetable, blend)
Yes
Yes
0.47
5
3–7
Tomato sauce
Yes
Yes
0.52
5
3–7
Olive oil
Yes
Yes
1.10
5
3–7
Biscuit (chocolate coated)
Yes
Yes
1.55
10
6–14
Chocolate (dark)
Yes
Yes
1.55
10
6–14
Notes:
* 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)
Nutrient
EARs or other target values used in the modelling
Standard deviation (SD) (% of EAR)19
Comment on constraints
Energy (kJ) (using estimated energy requirement (EER),19 averaged for 4 adult age-groups at the mid-range level of physical activity of 1.6 MJ/day)
11,450 kJ
1.6
Intake must reach or exceed this EER in the modelled scenario.
Saturated fatty acids (g)
For an upper limit we used 12% of total energy (27.5 g)
10**
Intake must be equal/below this upper limit.
Polyunsaturated fatty acids (g) (current intake in New Zealanders from the NZANS20)
13.1 (current)
10**
These current levels must be reached/exceeded.
Protein (g)
52
12
EARs must be reached/exceeded.
Dietary fibre (g) [Adequate intake = AI]
30 (AI)
10**
AI must be reached/exceeded.
Minerals (selected)



Calcium (mg)
840
10
EARs must be reached/exceeded.
Iron (mg)
8
18
In this case we used the EAR value for women (8mg) rather than the value for men (6mg). This is the only nutrient in this table where there is a higher value for women than for men.
Potassium (adequate intake) (mg)
3800 (AI)
10**
EARs must be reached/exceeded.
Selenium (μg)
60
10
EARs must be reached/exceeded.
Sodium (mg) (upper level)
2300 (upper limit)
10**
Upper limit must be equal/below this level. The NHMRC Report actually suggests a target of 1600mg/day (70mmol) for men and women.
Zinc (mg)
12
10
EARs must be reached/exceeded.
Vitamins (selected)



Vitamin A (μg RE)
625
20
EARs must be reached/exceeded. Upper limit is 3000 for men.
Thiamin (mg)
1.0
10
EARs must be reached/exceeded.
Vitamin C (mg)
30
21
As above.
Vitamin E (Adequate intake: as alpha-tocopherol equivalents) (mg)
10 (AI)
10**
As above.
Notes:
* 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.

Results

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
Food items selected by the optimisation process (for further details see Table 2)
Total food weights suggested per day (g) by Scenario
“EP-B” (baseline scenario)
“EP-NC” (no cooking required)
“EP-H” (all daily nutrients achieved)
“EP-NS” (no spoilage considered)
Food that requires cooking




White flour
100*
0
0
100
Rice (white)
100
0
0
100
Pasta (dried)
100
0
0
100
Wholemeal flour
0
0
200*
0
Food that can be eaten without cooking



Peanut butter
100
100
51
85
Sugar
100
100
14
100
Oats (whole grain, raw)
74
100
0
100
Oil (vegetable, blend)
60
30
0
60
Peas (dried) [requires sprouting]
0
100
200
0
Sultanas
0
100
0
0
Peanuts, raw
0
96
0
0
Breakfast biscuits (“Weetbix”)
0
10
0
0
Peaches (canned)
0
0
200
0
Fruit salad (canned)
0
0
200
0
Apricots (canned)
0
0
200
0
Tomatoes (canned)
0
0
200
0
Sardines
0
0
183
0
Tomato sauce
0
0
145
0
Total food weights consumed per day (g) (excluding added water)
634
636
1594
645
Number of food items
7
8
10
7
Cost to purchase (NZD)
$2.22
$3.67
$7.10
$1.93
Cost in US$ per day
$1.46
$2.41
$4.66
$1.27
* 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)
Food item selected by the optimisation process
Solutions (food weight – g/day)
Mean
Median
Lower 95% simulation interval (SI) bound
Upper 95%SI bound
Pasta (dried)
100
100
100
100
Rice (white)
100
100
100
100
Sugar
100
100
100
100
Peanut butter
92
100
25
100
White flour
84
100
0
100
Oil (vegetable, blend)
60
60
60
60
Oats (whole grain, raw)*
51
61
0
100
Peas (dried) [can be sprouted]*
34
0
0
100
Wholemeal flour*
16
0
0
100
Semolina*
3
0
0
54
Total food weight
640
621
385
914
Cost to purchase (NZD)
$2.21
$2.21
$2.04
$2.38
* These results are influenced by a small number of values that are outside of the 95%SI.

Discussion

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:
  • The process for food selection was not exhaustive and we may have missed certain low-cost food items that are suitable for long-term storage.
  • We were conservative with the pricing data and so may have over-estimated the “real world” prices given that some citizens may focus on buying “specials” and buy in bulk (e.g., 25 kg sacks of rice cost significantly less ($0.18–0.22 per 100g) than smaller amounts such as the $0.25 used in Table 2). While we used the prices of some “generic” brands (e.g., “Home Brand”), the foods covered by generic brands vary between supermarket chains and can result in large savings compared to branded foods (as per an Australian study22). Also for foods not covered by the FPI, we used prices from relatively typical supermarkets and not those from one New Zealand supermarket chain that specialises in low prices. Finally, organisations preparing emergency food stores could also potentially get lower-priced food through bulk purchase arrangements.
  • The spoilage estimates were crude and not informed by any New Zealand specific studies (since none appear to have been done).
  • For the nutrient analysis in one scenario, some of the nutrient values obtained may be on the optimistic side as overcooking may occur with some foods with associated loss of micronutrients.
  • We have only presented results for adult men and other groups will have differing nutrient requirements. Nevertheless, men have higher dietary energy requirements and higher nutrient requirements (except for iron) than other population groups (and we used the EAR for women which is greater than the EAR for men).
  • There are likely to be more uncertainties than we modelled, for example future changes in price of food.
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:
  • Use of more routinely consumed foods that can be rotated as part of routine or occasional meals (to reduce the wastage associated with spoilage of stored emergency foods).
  • Foods that reflect cultural preferences or other personal preferences e.g., vegetarian, gluten-free etc.
  • Foods that are also suitable for feeding companion animals during a disaster (e.g., canned fish or meat that can also be given to cats and dogs), if actual extra pet food was not stored.
  • Foods that are particularly low in sodium to reduce the risk of thirst at times of potential water-supply shortages. But on the other hand, some higher salt foods may have lower spoilage rates.
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 nick.wilson@otago.ac.nz
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