Changing Food Patterns across the Seasons in Rural Pakistan: Analysis of Food Variety, Dietary...

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Changing Food Patterns across theSeasons in Rural Pakistan: Analysis ofFood Variety, Dietary Diversity andCalorie IntakeAbid Hussain a , Farhad Zulfiqar b & Abdul Saboor ca International Centre for Integrated Mountain Development ,Kathmandu , Nepalb School of Environment, Resources and Development , AsianInstitute of Technology , Pathumthani , Thailandc Department of Economics and Agricultural Economics , PMAS-AridAgriculture University , Rawalpindi , PakistanPublished online: 24 Feb 2014.

To cite this article: Abid Hussain , Farhad Zulfiqar & Abdul Saboor (2014) Changing Food Patternsacross the Seasons in Rural Pakistan: Analysis of Food Variety, Dietary Diversity and Calorie Intake,Ecology of Food and Nutrition, 53:2, 119-141, DOI: 10.1080/03670244.2013.792076

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Ecology of Food and Nutrition, 53:119–141, 2014Copyright © Taylor & Francis Group, LLCISSN: 0367-0244 print/1543-5237 onlineDOI: 10.1080/03670244.2013.792076

Changing Food Patterns across the Seasonsin Rural Pakistan: Analysis of Food Variety,

Dietary Diversity and Calorie Intake

ABID HUSSAINInternational Centre for Integrated Mountain Development, Kathmandu, Nepal

FARHAD ZULFIQARSchool of Environment, Resources and Development, Asian Institute of Technology,

Pathumthani, Thailand

ABDUL SABOORDepartment of Economics and Agricultural Economics, PMAS-Arid Agriculture University,

Rawalpindi, Pakistan

This comparative study investigated variations in food patternsacross the seasons in rural Pakistan through assessing the changesin food variety, dietary diversity and calorie intake. It analyzed thesituation using the primary information of 97 and 114 householdssurveyed in summer and winter respectively. Findings revealed asignificant difference of households’ food variety, dietary diversityand calorie intake across the seasons. In the winter, households’food basket was more diverse, showing 30%, 13%, and 8% risein food variety, dietary diversity, and caloric intake, respectively,due mainly to the changes in food choices in winter. Rural house-holds preferred to consume items from nutritious food groups (i.e.,dried fruits and nuts, oilseeds, and locally preserved foods) duringthe severe cold weather. However, they did not substitute signifi-cantly the items from basic food groups (i.e., cereals, vegetablesand legumes, tubers, and dairy products), with those belongingto nutritious groups. Based on findings, it is concluded that foodvariety, dietary diversity and calorie intake fluctuate across theseasons, therefore surveys of dietary patterns and calorie intake inone particular season may not be reliable, and food security status

Address correspondence to Abid Hussain, Food Security Economist, International Centrefor Integrated Mountain Development (ICIMOD), GPO Box 3226 (Kathmandu), Khumaltar,Laltipur, Nepal. E-mail: [email protected]

119

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120 A. Hussain et al.

of households may not be generalized on the basis of one seasonsurvey.

KEYWORDS caloric intake, dietary diversity scores (DDS), foodpatterns, food variety scores (FVS), Pakistan, summer, winter

Secure nutrition addresses not only the required level of calorie intake butalso the proper balance of food items in households’ food basket. Therefore,food patterns with higher diversity of food groups and variety of items withvast range of micro- and macro-nutrients are the underlying factors of house-holds’ nutrition security (Keding et al. 2012; Bouis and Hunt 1999; Hoddinottand Yohannes 2002; Steyn et al. 2006). Food patterns with less diversityof diets result in lower nutritional quality, thereby leading to a declinein calorie intake (Keding et al. 2012). Therefore, food patterns throughimproved dietary diversity are likely to improve calorie intake as shownby the food production program launched by Helen Keller International inBangladesh about two decades ago where improved food diversity subse-quently enhanced the calorie intake (Iannotti, Cunningham, and Ruel 2009).In particular, rural households are supposed to have easy access to locallyproduced vegetables, fruits, pulses, eggs, and dairy products that may have apositive impact on dietary quality (Olney et al. 2009), and it may also reducemortality rate (Bernstein et al. 2002; Lee et al. 2011; Wahlqvist, Kouris-Blazos,and Savige et al. 2002). There are also some evidences that food choices ofthe people may depend on seasonal changes (Hadley and Patil 2007). Suchindications are more obvious in rural areas (Keding et al. 2012) where ruralfolks change their dietary patterns to cope with the severity of the weather.Therefore, there are chances of changes in food variety and dietary diversity,thereby inducing changes in calorie intake across the seasons.

Dietary diversity should not be confused with food quantity. Dietarydiversity scores (DDS) clearly reflect overall dietary quality (Hatloy, Torheim,and Oshaug 1998; Torheim et al. 2004), whereas the food variety scores(FVS) account only for diversity of foods (Keding et al. 2012). Furthermore,different forms of an increase in dietary diversity and food variety mustbe distinguished (Keding et al. 2012). A simple increase, for instance, inFVS could result from either consumption of food items from the samegroup or from the different group. If it is from same group, it would justimprove FVS but not DDS. On the other hand, if FVS is improved fromconsumption of food items from a nutritionally distinct food group, it wouldimprove both FVS and DDS. A greater nutritional diversity is usually desirablefor a balanced diet (Burgess and Glasauer 2004), which consequently mayimprove households’ calorie intake (Keding et al. 2012; Brown et al. 2002).Therefore, dietary diversity scores should be enhanced with a measure ofdietary quality.

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Changing Food Patterns in Rural Pakistan 121

As reported elsewhere (Keding et al. 2012; Hatloy et al. 1998; Torheimet al. 2004), dietary diversity and food variety can be improved with con-sumption of a large number of food groups and food items. For households,the choice of food is determined especially by quality, taste, health andeconomic factors (Gupta 2009; Lilley 1996). However, most studies revealedthat households’ choice and consumption of diverse food is determined bythe price factor (Lilley 1996; Drewnowski, Darmon, and Briend 2004; Loet al. 2012; Monsivais and Drewnowski 2007; Kettings, Sinclair, and Voevodin2009). Therefore, the low income groups prefer low-priced food items (i.e.sugars, cereals, and pulses) rather than expensive items (i.e., meats, bak-ery products, and fruits) (Drewnowski and Darmon 2005; Monsivais andDrewnowski 2007). Though the price factor is an important considerationwhile investigating households’ food diversity (Engler-Stringer 2010; Langand Caraher 2001), however it cannot be generalized for all groups of peo-ple varying in terms of traditional trends and consumption history across theseasons and regions (USDA 2011; FAO 2009). Households’ choice of fooditems and diversity may also depend on some non-economic factors includ-ing the complex human behaviors and seasonal changes particularly in ruralareas (Hadley and Patil 2007; Koster 2007; Keding et al. 2012). In SouthAsian countries (i.e., Pakistan, Nepal, and India), price and income influ-ence the overall consumption of food items during all seasons (Hussain andRoutray 2012). However, an unnoted but very significant change across theseasons, due mainly to the inclusion of cultural/local food items to cope withthe severity of climatic conditions (FAO 2009), has not been investigated tillnow. Cognizant of this possibility, this study tried to investigate the fact in thePunjab province of Pakistan where mainly four seasons (i.e., autumn, spring,winter, and summer), are observed. However, this study considered changesin food patterns across two seasons—summer and winter—only. The mainobjective of this study was to test whether seasonal change induced changesin food patterns via the changes in food variety, dietary diversity and calorieintake across the seasons in rural Pakistan. In this study, the term “food pat-tern” is considered as the general composition of food basket (i.e., types offood items and groups) of rural households in a particular season.

METHOD

Study Area and Data Collection

This study is based on a field survey carried out in the Toba Tek Singhdistrict of Punjab Province of Pakistan (figure 1) that is characterized byextremely cold and hot seasons. During the extremely hot summer monthsof June and July, the temperature may reach 45–48 ◦C whereas in the coldmonths of December and January it falls to 0–5 ◦C (PSD 2006; DOIP 2009).

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FIGURE 1 Map of study area District Toba Tek Singh, Punjab, Pakistan.

The extreme seasonal conditions and diversity in production of food com-modities were the main reasons to select this district as the study area.It is important to mention here that this district is considered as one ofthe most food secure districts of Pakistan where food availability through-out the year is more than the domestic need since the district produces allseasonal food items (GOP-DOA 2009). Domestically produced food in the

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district comprises of diverse food items/groups (i.e., cereals, pulses, veg-etables, fruits, sugar, tubers, processed foods, meat, eggs, dairy items, andoilseeds/oils), and an average availability of locally produced food is nearly2900 kcal/day/AE (GOP-DOA 2009; FSA 2003, 2009). However, some of theitems such as dried fruits, apple, banana, peach and nuts are being tradedin from Northern Pakistan. Likewise, surplus food items of the study districtparticularly cereals, citrus, poultry, egg and dairy products are being tradedout to other parts of the country. Nevertheless, the net food availability andits diversity is not a problem in any season for residents of the study area(Hussain and Thapa 2012; FSA 2003, 2009). Moreover, income opportunitiesfor rural people also remain the same during the whole year due mainlyto local agricultural processing industry including those of two sugar mills,45 cotton ginning factories, 43 rice and flour mills, 13 oil expellers, and6 poultry feed mills (DOIP 2009). In addition, the district has diverse non-agricultural business activities including the major shoe-making industry andcoarse cloth (locally known as khhaddar) weaving mills in the area. Servicessector, overseas labor and cross-district opportunities also add to the stabilityof the income opportunities for the people. Thus, it can be assumed thatthere is no serious issue of seasonality in income opportunities in the studyarea, and people have almost equal income opportunities in all seasons. So,the changes in the food patterns across the season may depend on the peo-ple’s choices to cope with the severity of seasons. Therefore, it was decidedto investigate the changing choices of diverse food items across the extrememonths of summer and winter.

In view of the requirement of the study design “comparative study”,the survey was conducted in two phases in 2011. In the first phase, house-holds were surveyed in the month of June that was extremely hot monthof the summer. Likewise, in second phase, households were interviewedin the month of December that was extremely cold month of the winter.There are total 184,998 rural households in Toba Tek Singh district (PCO1998). By using Yamane’s formula (1967), a sample size of 70 householdsfor each phase was determined at 95% confidence level and ±12% marginof error but, in actuality, 97 and 114 households were randomly selectedand surveyed in summer and winter respectively. Yamane’s formula is givenbelow:

n = N/(1 + Ne2)Where;

n = Sample size

N = Total rural households in the district

E = Precision which is set at 12 % (0.12)

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While conducting the field survey, services of local interviewers wereacquired keeping in view their proficiency in local languages (i.e., Punjabiand Saraiki), and ease to contact rural households. For the first phase ofsurvey in June, 2011, two union councils1 were randomly selected from thelist of union councils in the district. Thereafter, five villages from each unioncouncil and subsequently 8–10 households from each village were selectedrandomly for survey. A total of 97 households were interviewed during thefirst phase. For the second phase of data collection in December, 2011, sameunion councils were targeted keeping in view the similarity of households’socioeconomic characteristics. Selection of new union councils might havecaused unwanted biasness of estimates due to the change in socioeconomiccharacteristics. Therefore, it was decided to select the same union councilsyet the villages and households were reselected randomly to allow the inde-pendency of the sample. A total of 114 households were surveyed during thesecond phase. It is worthy to mention that it was not possible to survey thesame households in the second phase due to various reasons, such as house-holds’ unavailability, unwillingness to provide data twice, migration to otherplaces, and busy farming schedule. Based on these reasons, it was decided toresample the households in the second phase. However, statistics in table 1show that despite the resampling, the socioeconomic characteristics showednegligible difference.

In both phases, data of food items consumed were collected for continu-ous seven days. In this regard, data sheets translated into Urdu (the nationallanguage) were provided to household heads who were briefed by inter-viewers about its filling for the said period. All required information (i.e.,demographic characteristics, income, food expenditures, and food items andgroups) was printed on the sheets leaving blank spaces in the next columnto be filled by households. Income and food expenditure data were col-lected as an accumulative figure of the whole month. However, data of fooditems were collected for seven continuous days. In this regard, householdheads were briefed by interviewers to write down the names of items inthe first column of the data sheet and their quantities in the second columnwhenever they consume those items. Moreover, food items were classifiedinto 16 major food-groups on datasheets (table 2), and each group was com-prised of several food items including those of usual as well as cultural/localfood items. It is worthwhile to mention that quantities of food items were inkilograms and grams, whereas some of the items were reported in numbers(e.g., eggs and bananas), which were converted into kilograms using thestandard methods followed by various studies on nutrition security (Hussain2010; FSA 2003, 2009).

1 A local administrative unit comprising of 5 to 10 villages.

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TABLE 1 Socio-Economic Characteristics of Samples

Frequency Mean values

Characteristics SpecificationSummer(n=114)

Winter(n=114)

Summer(n=114)

Winter(n=114)

Meandifference

Householdhead’s sex

Male = 1Female = 0

9106

10608

0.94 0.93 −0.01(0.021)4.00

Householdhead’s age

Years - - 47 51 (7.070)

Literacy level Illiterate = 0 09 13 −0.13∗

Secondaryschool = 1

33 44 (0.068)

Bachelordegree = 2

36 39 1.67 1.54

Above bache-lor = 3

19 18

Household size Number - - 7.43 7.45 0.02(0.190)

Householddependencyratio

Number ofdepen-dents/Householdsize

- - 0.75 0.80 0.05(0.084)

Main occupation Agriculture = 1 65 71 −0.05Otherwise = 0 32 43 0.67 0.62 (0.094)

Knowledge ofdietarydiversity andcalorie intake

Yes = 1 17 25 0.18 0.22 0.04∗

(0.021)

No = 0 80 891.49

Household’sincome

Pakrupees/day/Adult Equivalent

- - 103.20 104.69 (1.320)

∗p < 0.10 for t test.No value of mean difference is significant at 1% and 5% levels.Figures in parentheses are respective standard errors.

Data Analysis

Setting the household level as the unit of analysis for this study, three mainaspects of nutrition security, dietary diversity, food variety and calorie intake,are estimated to investigate the changes in food patterns across the seasons.The dietary diversity scores (DDS) and food variety scores (FVS) are thequalitative measures that can reflect households’ access to a diversity of dietand food items (FAO 2007). In other words, DDS and FVS represent the over-all dietary quality of rural households and may also be associated with theircalorie intake (Keding et al. 2012; Savy et al. 2005). In this study, DDS wascalculated by summing the number of different food groups consumed by

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TABLE 2 Food Groups

Food groups Food items

Cereals • Wheat, rice and maize: Including bread, chapatti or roti, bun andnaan

Vegetables • Fresh vegetables: eggplant, bottle gourd, carrot, radish, ridge gourd,cauliflower, capsicum, lady finger, cucumber, onion, bitter gourd,pumpkin, cabbage, spinach, coriander, fenugreek, mongray (seedpods of radish) and green chili

• Saag (local name of cooked form of mustard leaves that looks likegreen paste)

• Dry vegetables i.e. Khushk methi (dry fenugreek)Tubers • Potato

• Sweet potatoPulses and

legumes• Bean, chickpea, mung-bean, cowpea, pea and lentils i.e. daal masoor

& daal mashFresh fruits • Kinnow, frooter (orange), mango, garma-sarda, guava, apple,

banana, falsa, jaman, apricot, plum, melon, water melon, strawberry,mulberry, guava, pomegranate, date, grapes, lychee, lime, lemon,cherry, pineapple, grape fruit, chakotra, peach, and pear

Dry fruits andnuts

• Dry Fruits: Anjeer (dry figs), zardaloo (dry apricot) and chhawara(dry dates)

• Nuts: chalghoza (pine-nut), pistachio, walnut, cashew-nut and peanutDairy products • Milk, curd/yogurt, whey, milk-cream, milk powder, ice creamMeats • Poultry meat, beef, mutton and fishEggs • Hen eggs, duck eggsFats and oils • Ghee, desi ghee, vegetable oil, butter and margarineSpices/

condiments• Pepper, Zeera (cumin), daal cheeni (cinnamon), bari alaichi (big

cardamom), laong (clove), chhoti alaichi (green cardamom),kish-mish (raisins), khopra (dry coconut), garlic, ginger, onion-seedand turmeric

Beverages • All soft drinks: juices and non-alcoholic carbonated drinksOilseed • Coriander seeds, flax seeds, sesame seeds, mustard seeds and

fenugreek seedSugar and sweets • Sugars: Refined white sugar, brown sugar, and brown sugar cubes

(locally known as gurh)• Sugar confectioneries: sweets locally known as mithai• Honey

Processed foods • Bakery products: custard, burger, biscuit, rus, cookies, pies and cake• Infant food items• Miscellaneous Items: jelly, chocolates, candies, toffees etc.

Locally preserved • Pickles of raw mango, lemon and green chili (spiced and preserved inmustard oil)

foods • Murabba : Raw mango and apple preserved in sugar syrup

Note. Italic letters show the local names of cultural/local food items.Source: Field Survey in 2011 was conducted by authors. Details are given in methodology part.

the household over the period of seven days, thus, the household dietarydiversity score (DDS) was created. However, presently no internationalaccord exists on which food groups to include in the scores (FAO 2007).Therefore, 16 different food groups were selected for this study (table 2)based on food items found during the survey and in line with existing liter-ature regarding local food habits (FAO 1970; West, Pepping, and Temalilwa1988). Likewise, FVS was calculated by summing up all single food items

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(shown in second column of table 2) consumed over a period of seven days.There is advantage of the DDS and FVS used in the analysis. Firstly, the scoreis based on seven-day food consumption and might strongly represent long-term dietary habits. It could not cause misclassification as through one-timeevents such as weddings or funerals (Kant et al. 1993).

Regarding the calorie intake, in this study, food secure household hasbeen defined as the one whose calorie intake is equal to or greater thanthe minimum daily calorie requirement as per National Food Security Line(2350 kcal/day/adult equivalent). A household with lower calorie intake thanNFSL is considered to be food insecure or undernourished. Therefore, thisstudy is very important to investigate the fluctuation in calorie intake withrespect to NFSL in response to seasonal changes. In Analysis, calorie intake(per adult equivalent) for all seven days was estimated separately, and finallythe average of seven days was approximated as “calorie intake (kcal) per dayper adult equivalent.” During the estimations, total quantity of each food item(in kilogram or gram) at household level was converted to calories follow-ing the nutritional charts presented by FAO (FAO 2001) and United StatesDepartment of Agriculture (USDA-NDSR 2009). Subsequently, daily caloriessupply was divided by the number of adult equivalents (AE) of a householdin order to obtain an estimate comparable across households and groupswith different sizes, and to compare with NFSL that is based on AE. Sameconversion criteria were used by preceding national studies (FSA 2003, 2009;Hussain and Routray 2012). Simple count of household members (called ashousehold size) cannot be used to compare the income, expenditure andcalorie intake situation of the households and groups. Adult equivalencescale is very reliable alternative which assigns different weights to house-hold members according to a variety of characteristics, usually age and sex(Sabates et al. 2001; Deaton and Muellbauer 1986). When applied to inter-household and inter-group analysis, adult equivalence scales are employedto adjust household income, expenditure and calorie intake to permit wel-fare comparisons across the households and groups of different sizes andcomposition (Sabates, Gould, and Villarreal 2001; Lazear and Michael 1980;Blaylock 1991; Deaton and Muellbauer 1986). Cognizant of the above facts,in this study household sizes were converted into “adult equivalents” (AE)using the national criteria framed for food security analysis of Pakistan (tablesA2 and A3). This conversion has mitigated the chances of estimation biaswhich was likely to occur due to the change in composition, of households(i.e., sex and age) within and between the groups.

To estimate the mean differences between values of DDS, FVS andcalorie intake of summer and winter seasons, t-unpaired test was appliedusing the Stata 11.1 software for statistical analysis, since the data werenormally distributed. The unpaired t-test was the most suitable measure ofestimating mean differences in values across the seasons since the two inde-pendent random samples were surveyed in the both phases (Altman 1991;Armitage and Berry 1994).

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RESULTS

Socioeconomic Characteristics of Samples

In order to minimize the chances of estimation bias due to the selec-tion of two different groups of households in winter and summer, thisstudy tried to survey the households from the same union council withalmost similar socioeconomic characteristics. The statistical comparison ofthe socioeconomic characteristics of both groups also revealed that they arenot significantly different from each other (table 1). Most characteristics, suchas household head’s sex and age, household size, dependency ratio, occupa-tion and income, did not show any significant mean difference between thevalues of both groups. However, literacy level and knowledge of dietarydiversity and calorie intake showed some significance (at 10% level) ofmean differences. The literacy level of first group (surveyed in summer)was slightly higher than the second group (surveyed in winter) whereas thestatistical difference of “knowledge of dietary diversity and calorie intake”was vice versa. Nevertheless, the difference of these two characteristics athigher level of significance may not be a serious concern in inducing anyestimation bias.

Food Variety and Dietary Diversity

During field survey, majority of households did not agree the statementthat prices of food items could influence their choices across the seasons.However, data analysis has substantiated the provided qualitative informa-tion. The income of households did not show much change across theseasons. However, spending on food items revealed an increase of 5.71%in winter (table 3). Also, the proportion of food expenditures in the house-hold income showed only 3% rise in winter as compared to summer seasondue mainly to the inclusion of some expensive food items, such as driedfruits and nuts (table A1), in food basket in response to seasonal change.Although, a notable rise in prices of such items was observed in winter, yetthe households preferred to increase consumption of those despite the neg-ligible increase in their income (table 4). On the other hand, consumption offresh fruits decreased in winter in spite of some decline in prices (table A1).

Findings revealed that a significant improvement in the values of FVSand DDS has been observed as compared to the summer season (table 5).

TABLE 3 Household Income and Food Expenditures

Pak Rupees/day/AEIncome and FoodExpenditures Summer Winter % Change

Income (I) 103.20 104.69 1.44Food Expenditures (FE) 73.71 77.92 5.71Ratio(%) = FE

I×100 71 74 3.00

Source: Field Survey in 2011 was conducted by authors. Details are given in methodology part.

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TAB

LE4

Cal

orie

Inta

ke,Fo

od

Var

iety

and

Die

tary

Div

ersi

tyA

cross

the

Seas

ons

Sum

mer

(n=9

7)W

inte

r(n

=114

)

Food

groups

Mea

n(S

tandar

der

rors

)M

edia

n(R

ange

)

Mea

n(S

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edia

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ean

diffe

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ge

Food

variet

y26

.93

2735

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348.

2010

.274

1∗∗∗

30sc

ore

s(0

.516

3)(1

7−39

)(0

.591

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4−51

)(0

.798

)D

ieta

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447

8.45

101.

013.

550∗∗

∗13

score

(0.2

344)

(6−1

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6)(7

−16)

(0.2

85)

Cal

orie

inta

ke(k

cal/

day

/A

E)

2,27

2.14

2057

2,44

9.05

2280

176.

912.

4789

∗∗08

(50.

17)

(153

7−32

21)

(50.

10)

(162

6−34

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(71.

36)

Not

e.Val

ues

at95

%CI.

∗∗∗

p<

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Surv

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2011

was

conduct

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auth

ors

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ethodolo

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129

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TAB

LE5

Food

Var

iety

Score

san

dCal

orie

Inta

ke

Food

variet

ysc

ore

sCal

orie

inta

ke(k

cal/

day

/A

E)

Food

groups

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mer

(n=9

7)W

inte

r(n

=114

)M

ean

diffe

rence

t-va

lues

Sum

mer

(n=9

7)W

inte

r(n

=114

)M

ean

diffe

rence

t-

valu

es

Cer

eals

1.52

(0.1

7)1.

92(0

.25)

0.40

(0.3

1)1.

2773

1212

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1223

(41.

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)0.

1955

Veg

etab

les

4.14

(0.1

2)4.

72(0

.18)

0.58

(0.2

2)2.

5849

∗∗12

1(7

.15)

124

(7.6

7)03

(10.

61)

0.28

27Tuber

s1.

08(0

.07)

1.12

(0.1

1)0.

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0.29

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(0.9

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(1.4

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0.56

15Puls

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34(0

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2.46

(0.1

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0.47

3571

(4.5

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(3.6

4)03

(5.7

7)0.

5202

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hFr

uits

2.34

(0.1

0)2.

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1.42

1869

(5.0

9)47

(3.1

6)−2

2(5

.81)

3.78

58∗∗

∗

Dry

Fruits

and

Nuts

0.79

(0.0

4)3.

66(0

.32)

2.87

(0.3

5)8.

2238

∗∗∗

02(0

.19)

53(4

.11)

51(4

.46)

11.4

333∗∗

∗

Dai

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duct

s2.

66(0

.23)

2.79

(0.1

6)0.

13(0

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0.47

4413

3(8

.02)

146

(11.

21)

13(1

4.23

)0.

9136

Mea

ts1.

35(0

.09)

2.10

(0.0

7)0.

75(0

.11)

6.66

85∗∗

∗98

(5.6

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(3.4

5)−1

1(6

.44)

1.70

70∗

Egg

s0.

92(0

.06)

0.98

(0.0

5)0.

06(0

.07)

0.77

4536

(5.0

8)52

(4.9

9)16

(7.1

6)2.

2355

∗∗

Fats

and

Oils

1.44

(0.0

9)1.

67(0

.07)

0.23

(0.1

1)2.

0450

∗∗33

4(7

.84)

359

(10.

64)

25(1

3.62

)1.

8360

∗

Spic

es/co

ndim

ents

2.14

(0.1

3)2.

34(0

.23)

0.20

(0.2

8)0.

7227

14(1

.89)

18(2

.01)

04(2

.79)

1.43

33B

ever

ages

1.34

(0.1

0)0.

99(0

.06)

−0.3

5(0

.11)

3.10

14∗∗

∗23

(1.2

3)21

(0.8

9)−0

2(1

.49)

1.34

30O

ilsee

d0.

77(0

.09)

2.65

(0.2

4)1.

88(0

.09)

6.88

18∗∗

∗09

(0.9

2)68

(3.4

7)59

(3.8

6)15

.294

6∗∗∗

Suga

ran

dsw

eats

2.18

(0.1

1)2.

38(0

.27)

0.20

(0.3

1)0.

6454

116

(4.1

1)12

7(5

.51)

11(7

.08)

1.55

46Pro

cess

edFo

ods

1.24

(0.0

4)1.

09(0

.04)

−0.1

5(0

.06)

2.36

96∗∗

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.57)

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2)4.

4427

∗∗∗

Loca

llypre

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edFo

ods

0.67

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8)7.

7782

∗∗∗

04(0

.96)

26(1

.69)

22(2

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10.8

091∗∗

∗

Figu

res

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enth

esis

are

resp

ectiv

est

andar

der

rors

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d∗∗

∗ p<

0.01

,∗∗

p<

0.05

,∗ p

<0.

10fo

rt

test

.So

urc

e:Fi

eld

Surv

eyin

2011

was

conduct

edby

auth

ors

.D

etai

lsar

egi

ven

inm

ethodolo

gypar

t.

130

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Both FVS and DDS overwhelmingly increased by 30% and 13% respectivelyin winter, implying that in winter, rural households’ food and dietary qualityimproved due to the consumption of higher number of food items comingfrom higher number of food groups. At least, eight food items increasedin their food basket compared to summer season. Likewise, increased DDSillustrated that their consumed food items came from more diverse foodgroups (table 5) in winter. FVS showed higher proportionate change as com-pared to DDS because it increased due to an increase of number of itemschosen mainly from same group. However, wherever FVS improved due tothe choice of items from nutritionally distinct food groups, it reflected inimprovement in DDS. Furthermore, range of food items and dietary diversityalso increased in winter as presented in table 5. Lower and upper limits ofFVS range increased respectively due to the inclusion of 7–12 more fooditems in the food basket during the cold conditions. Likewise, lower andupper limits of DDS improved respectively due to the inclusion of 1–2 morefood groups in the dietary patterns.

As mentioned above, chosen food items increased in winter, thereforeit is inevitable to go into the details of such change. There was no sig-nificant difference observed across the seasons in number of food itemsbelonging to cereals, tubers, pulses and legumes, fresh fruits, dairy prod-ucts, eggs, spices/condiments, and sugars and sweets. However, numberfood items arising from vegetables, dried fruits and nuts, meats, fats and oils,beverages, oilseed, processed foods, and locally preserved foods showedsignificant change in winter as depicted by their food variety scores in table4. Among all significant food groups, fresh fruits, beverages, and processedfoods showed decline in FVS in winter, whereas other groups showed con-siderable increase. Particularly groups of dried fruits and nuts, oilseeds, andlocally processed foods revealed very high increase in food variety scores,implying that in winter food items from these groups are more likely to bechosen for subsequent consumption.

Caloric Intake

Rural households were below the national food security line (2350kcal/day/AE) in summer. However, in winter, due to increased food varietyand dietary diversity in their food baskets, their calorie intake improved by8% and crossed the national food security line (table 5). Likewise, rangeof calorie intake also improved significantly. Details of calorie supply fromdifferent food groups revealed that improved food and dietary diversity interms of higher FVS (due to increase of items within group or cross-groupincrease “DDS”) for dried fruits and nuts, fats and oils, oilseed, meats, andlocally processed foods, has reflected in increased calorie supply from thesefood groups. However, among all groups, oilseed illustrated the highestincrease in calorie intake during winter. Likewise, declined food diversityfor processed foods in winter led to a significant decline in calorie supply

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from this food group. Among other groups, fresh fruits, beverages and eggsshowed consistent changes in calorie supply in response to changes in FVSbut with dissimilar significant levels. Nevertheless, overall calorie intakeincreased in winter in response to increased food verity and dietary diversityin the food patterns. However, proportionate change in calorie intake is notas higher as it was in the case of FVS. Logically, increased number of itemscannot guarantee an increase in calorie intake due to the high range ofvariations in nutritional value of food items. For example some vegetablesdo not have higher calories but possess higher fibers contents and vitamins.

Regarding the share of food groups in total caloric intake in both sea-sons, notably nearly 50% of calories in both seasons are coming from cereals.In winter, dried fruits and nuts, oilseed, eggs, and locally processed foodsshowed considerable increase whereas the share of cereals, meats and freshfruits declined. However, share of calories from other food groups remainedeither, nearly, the same or showed very little change.

DISCUSSION

Food patterns characterized by diverse food groups are essential determinantof dietary quality (Hatloy et al. 1998; Torheim et al. 2004). In addition, vari-ety of food items in a particular food group is also desirable for a balanceddiet (Burgess and Glasauer 2004; Keding et al. 2012). However, some stud-ies (e.g., Brown et al. 2002) revealed that food variety may not essentiallyresult in better calorie intake and health. In this study, food variety (FVS)and dietary diversity scores (DDS) increased in winter due to the inclusionof more food items and groups in the food basket in response to biggerchange in seasonal conditions from extremely hot to cold, thereby resultingin improvement of calorie intake by rural households. It has been observedthat changes in food patterns across the seasons were highly associated withpeople’s choices based on historical consumption trends to cope with sever-ity of weather conditions. Food prices and households’ income did not affectthe choice of food items. Rather, food variety, dietary diversity and calorieintake showed a notable improvement due to the inclusion of nutritious fooditems (i.e., oilseeds, dried fruits, and nuts) in the food basket, despite theincreased prices in winter, implying that seasonal change induced an impacton food patterns. It is consistent to preceding studies that seasonal changesmay influence the food patterns (FAO 2003; Keding et al. 2012; Frongilloand Nanama 2006; KFSSG 2011). However, those studies mainly showedthat such change was the consequences of the frequency and the durationof rainy seasons and their subsequent effects on food production, householdincome and food prices. Inversely, in the region selected for this study, nosuch seasonal shocks were observed because the agricultural land is fullyirrigated by canal systems. In some instances, rural food growers fulfilledtheir agricultural water requirements using the tube-wells. Therefore, there

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is not such possibility that seasonal changes would result in lower foodproductions even if rainfall magnitude and frequency decline.

Food choices may be influenced by economic (McIntyre 2003) and var-ious social and cultural factors (FAO 2009; USDA 2011; Mathey, Zandstra,and de Graaf 2000; Pollard, Kirk, and Cade 2002; Nestle and De-Sogra 1998).Economic factors, such as price and income, may influence the overall foodintake over the whole year (both cold and hot months) through inducingsome impact on food purchases as compared to similar season of previousyear (e.g., winter of 2010 vs. winter of 2011), yet the significant change inthe food patterns across the seasons, due mainly to the inclusion of cul-tural or traditional food items in one particular season (e.g., winter in thisstudy), is beyond the effect of prices and income (FAO 2009). Consistentwith this, the present study revealed that varying choices of food items (i.e.,usual and cultural), across the seasons are also among those critical factors,which drive the households to change their food patterns. Interviewers’ dis-cussions with household heads revealed that due to the extremely cold andhot conditions, they had to adjust their food patterns according to the bodyrequirements. For example, in the extremely hot months of summer theypreferred to drink a lot of beverages and eat perishable leafy vegetables andfresh fruits with higher water contents such as watermelon, garma-sarda,and muskmelon. In the extremely cold conditions, they increased the useof dried fruits and nuts, oilseeds, and locally preserved foods because theybelieved that these food groups could provide high energy to cope withextremely cold conditions. Therefore, consumption of dried fruits (e.g., figsand dates), and high-calorie nuts (e.g., pine nuts, pistachios, walnuts, andcashews) has become the norm in rural areas during the cold months. Thisis consistent with Prescott et al. (2002) that food choices may also be influ-enced by consumption history. In the study area, the consumption of oilseedalso increased in winter due to the increased demand (within households) oflocal dishes prepared from oilseed-cereals combination. Those dishes includ-ing alsi pinniyan, basin tikkiyan, maethay pinniyan and nashasta havehigher nutritional value. Therefore, inclusion of such food items in foodpatterns during winter season increased both food variety and dietary diver-sity that subsequently resulted in improved calorie intake (tables 4 and 5).Furthermore, calorie share of these food groups in total calorie intake alsoincreased significantly in winter (figure 2). Importantly, in winter, house-holds’ preference for expensive food groups (i.e., nuts and dried fruits,meat and eggs), invalidates the assumption that prices of food items mayoften affect adversely the food diversity and calorie intake (Lo et al. 2012;Wu 2009; Giskes et al. 2007; Kirkpatrick and Tarasuk 2006). Despite thehigher prices of these items, particularly the dried fruits and nuts, in thelocal markets (table A1), rural households prefer to consume in responseto seasonal changes based on their cultural choices (FAO 2009). Not onlyabove food groups played role in improving food quality and calorie intake

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but locally preserved food items such as murabbas (table 2), also contributedto the net change in winter. In addition, increased quantities of fats and oilsand egg also contributed significantly to calorie intake.

Despite the inclusion of new food items in the food patterns during thewinter, households did not substitute their primary food items. Almost, allrural households, irrespective of season and price, consume flat bread ofwheat flour (locally known as roti or chapati) three times a day (breakfast,lunch and dinner) mainly in combination with cooked vegetables, tubers,legumes and pulses (table 4). Moreover, dairy items (i.e., milk, whey, andyogurt), are also being consumed as primary food items in the study area.Therefore, rural households did not make significant changes in patterns ofthese items (table 4). However, due to the increased calorie share of driedfruits and nuts, oilseed and locally preserved foods, the share of cereals,vegetables, pulses and legumes and tubers changed slightly (figure 2).

Nevertheless, those rural households who were below the national foodsecurity line (2350 kcal/day/AE) in summer improved their calorie intake tocross the line in the winter (table 4). This study also validates that food vari-ety, dietary diversity and calorie intake fluctuate across the seasons, thereforesurveys of dietary patterns and calorie intake in particular season may notbe reliable particularly in the rural areas of Pakistan. Food security status of

0.00

10.00

20.00

30.00

40.00

50.00

60.00

summer

winter

FIGURE 2 Calorie share of food groups in total calorie intake across the seasons.

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households could not be generalized on the basis of one seasonal survey.Worthwhile to mention that recall data of 24 hours may have biased estima-tion due to the effect of some sudden events (e.g., social festivals, funerals,entertaining guests at home, or traveling) of some households. Likewise,when precise estimates are needed for frequency of intake of food groupsthat are rarely consumed (i.e., fruits and vegetables, animal protein foods,nuts, and dried fruits), the seven-day recall may be preferred (Arimond andRuel 2002; Kant et al. 1993). Thus, data based on seven-day recall are morehelpful to estimate the stable and precise situation. During the survey of thisstudy, it has been observed that some of the households showed very lowor very high food variety, dietary diversity, and calorie intake for 24 hoursrecall data whereas it was vice versa for data of seven days.

CONCLUSIONS

In addition to economic factors, food consumption patterns are determinedby various other factors including the seasonal choices made on the basis ofconsumption history to cope with severity of extreme weather conditions.Food patterns in the study area changed across the seasons causingsignificant changes in households’ food variety, dietary diversity and calorieintake. Compared to summer, diet was more diverse in winter with relativelyhigher calories due to the inclusion of the items chosen from nutritious foodgroups (i.e., dried fruits and nuts, oilseed, and locally preserved foods).Importantly, seasonal changes did not affect significantly the consumptionof primary food items (i.e., cereals, vegetables, pulses, tubers, legumes, anddairy products). Rather, while substituting items, households reduced theconsumption of beverages, fresh fruits and processed foods in winter toprocure more items from food groups like dried fruits and nuts, oilseedsand locally preserved foods.

Based on the findings, it can be stated that while assessing the house-hold food security situation of any population of interest, it would necessarilybe important to know about local climatic conditions and changing food pat-terns. Therefore, surveys of dietary patterns and calorie intake in one particu-lar season may not be reliable to generalize the status of rural household foodsecurity in developing countries in general, and Pakistan, in particular, whereextreme seasons are observed. Moreover, it is suggested that recall data of24 hours may yield biased estimation due to the effect of some suddenevents (e.g., social festivals, funerals, entertaining guests at home, or travel-ing) of some households. Therefore, data based on seven-day recall are morehelpful to estimate the precise and stable situation. Lastly, this study suggeststhe investigation of changing food patterns across the seasons in some foodinsecure regions/provinces of Pakistan, (i.e., FATA and Baluchistan), to vali-date the findings of this study. Such validation study may essentially consider

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the assessment of changes in micro and macro nutrients as well rather thanmerely studying food variety, dietary diversity and calorie intake.

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APPENDIX

TABLE A1 Average Prices of Food Items in the Study Area †

Pak Rupees�

Items Unit June, 2011 Dec, 2011 %Change

Wheat kg 22.72 25.9 14.00Wheat flour kg 27.70 29.5 6.50Rice Basmati kg 60.0 62.0 3.33Bread plain medium Size

(340g-400g)each 30.0 30.0 0.00

Fresh vegetables∗ kg 41.32 46.98 13.70Potato kg 31.15 21.13 −32.17Daal masoor kg 104.5 99.90 −4.40Mung-bean (split) kg 140.0 127.5 −8.93Daal mash kg 160.0 162.25 1.41Gram (split) kg 63.5 68.0 7.09Fresh fruits∗ kg 53.24 52.66 −1.09Dry fruits & nuts ∗ 250 g 195.2 218.8 12.09Milk fresh liter 50.0 50.0 0.00Curd kg 59.0 60.0 1.69Milk powder 500 g 230.0 245.0 6.52Beef kg 230.0 246.0 6.96Mutton kg 424.0 465.5 9.79Chicken live (farm) kg 123.0 120.35 −2.15Egg (farm hen) 1 dozen 66.4 98.05 47.67Oilseed (mustard oil) kg 165.0 180.0 9.09Cooking oil 2.5 liter 495.0 495.0 0.00Vegetable ghee (tin-pack) 2.5 kg 495.0 495.0 0.00Red chili powder kg 243 317.0 30.45Garlic kg 160.0 82.50 −48.44Sugar kg 68.5 53.8 −21.46Gurh kg 74.5 71.0 −4.70Salt powder kg 7.0 7.5 7.14Tea 200 g 151.32 131.6 −13.03

†Prices are based on Pakistan Bureau of Statistics Data (PBS, 2011; PBS, 2012) for Faisalabad Regionwhere study area is situated.∗Data obtained from local market committee during field survey (2011) .�Nearly 94 Pak Rupees are equal to 1 USD (Reference period September, 2012).

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TABLE A2 Adult Equivalence Scale (National Criteria)

GroupsAge classes

(year)Energy per person daily

requirement (kcal) Equivalent factor

<1.0 1010 0.429787200Children 01-04 1304 0.554893617

05-09 1768 0.752340426Males 10-14 2816 1.198297872

15-19 3087 1.31361702120-39 2760 1.17446808540-49 2640 1.12340425550-59 2460 1.04680851160+ 2146 0.913191489

Females 10-14 2464 1.04851063815-19 2322 0.98808510620-39 2080 0.88510638340-49 1976 0.84085106450-59 1872 0.79659574560+ 1632 0.694468085

National Average − 2350 1.000000

Source: GOP 2003.©Finance Division, Government of Pakistan. Reproduced by permission of Finance Division,Government of Pakistan. Permission to reuse most be obtained from the rightsholder.

TABLE A3 Conversion of Household Size to Adult Equivalent (AE)

Summer (n=97) Winter (n=114)

HouseholdSize

AdultEquivalent∗

HouseholdSize

AdultEquivalent∗

7.43 5.07 7.45 5.07

∗Calculated following the equivalent factor given in Table A2.Source: Field Survey in 2011 was conducted by authors. Details are given in methodology part.

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Changing Food Patterns across the Seasons in Rural Pakistan: Analysis of Food Variety, Dietary...

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