Research Article

What Determines Food Security among the Farm Households of Khyber Pakhtunkhwa, Pakistan? A Binary Logistic Regression Analysis

Muhammad Azam1*, Shaista Naz1*, Malik Muhammad Shafi2, Muhammad Jamil Afridi3 and Ahmad Waheed4

1Department of Rural Development, Amir Muhammad Khan Campus, Mardan, The University of Agriculture, Peshawar, Khyber Pakhtunkhwa, Pakistan; 2Insitute of Development Studies (IDS), The University of Agriculture, Peshawar, Khyber Pakhtunkhwa, Pakistan; Department of Food Science and Technology, The University of Agriculture, Peshawar, Khyber Pakhtunkhwa, Pakistan; 4Department of Pakistan Study, Amir Muhammad Khan Campus, Mardan, The University of Agriculture, Peshawar, Khyber Pakhtunkhwa, Pakistan.

Received | August 31, 2021; Accepted | November 08, 2022; Published | December 26, 2022

*Correspondence | Muhammad Azam and Shaista Naz, Department of Rural Development, Amir Muhammad Khan Campus, Mardan, The University of Agriculture, Peshawar, Khyber Pakhtunkhwa, Pakistan; Email: azamkhan2090.ak@gmail.com

Citation | Azam, A., S. Naz, M.M. Shafi, M.J. Afridi and A. Waheed. 2022. What determines food security among the farm households of Khyber Pakhtunkhwa, Pakistan? A binary logistic regression analysis. Sarhad Journal of Agriculture, 38(5): 346-354.

DOI | https://dx.doi.org/10.17582/journal.sja/2022/38.5.346.354

Keywords | Food security, Determinants, Binary logistic regression, Farm households, Copping strategies

Copyright: 2022 by the authors. Licensee ResearchersLinks Ltd, England, UK.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Introduction

The issue of food insecurity is at its rising level around the world (Nkomoki et al., 2019). It has been reported that 11% of the world population is facing food insecurity and thus making the issue global in nature. In this regard, Sustainable Development Goals (SDGs) has included food insecurity as its second goal, which calls for a commitment to end hunger, cut down food insecurity, and improve nutrition by 2030 (FAO, 2017). Food insecurity is more prevalent in the developing countries due to a number of reasons such as growing population, increased intensity of global warming and climate change like droughts, floods and extreme variability in temperature. All these factors put pressure on the food production systems and thus threatened the existing food security situation in the developing countries (Apanovich and Mazur, 2018; Ahmed et al., 2017; Porter et al., 2014). Higher food demand and inadequate crop productivity, along-with the food price hike had negatively affected not only access to food but also the availability of food among the poor and low income households in the developing countries (Harvey et al., 2018).

Among the developing countries, Pakistan faces food insecurity with considerable intensity made the country affected (Ahmed et al., 2017; Sher et al., 2018). The national level statistics indicated that 60% of the country’s population is reported as food insecure (WFP, 2017) along with further 67% of households’ are unable to meet their nutritional demands in their existing food expenditure budgets (WFP, 2016). This is due to the fact that the country is poverty stricken and hit by environmental disasters, which resulted in the aggravation of the problem of food insecurity (Bashir et al., 2013). Although, some progress can be seen over the time in terms of achieving food security. But still the problem of food insecurity exists as of the total 131 districts, 80 are facing some degree of food insecurity in the country (WFP, 2010).

In Pakistan, about two-third of the population lives in rural areas, which has direct or indirect dependency on the agriculture sector for their food and livelihood (Ahmed et al., 2017). Majority of the rural populations are comprised of small-scale farm households (owner of 2 hectares of land or less) and had further limitations in terms of access to resources and services (Abid et al., 2011). Although, at the national level some self-sufficiency in overall crop production has been achieved but the majority of the small scale farms are facing the problems of poverty, reduced crop productivity and food insecurity as well (Bashir et al., 2012).

Food insecurity served as a multidimensional concept and thus affected by various factors which may further vary from region to region, nation to nation, and community to community over time. These various factors have been categorized into mainly three components such as food availability, food accessibility, and food utilization. The first component is related to the assurance of adequate amount of food availability for all the individuals within a country. Availability of food can be ensured through its production at household levels, imports, and through food assistance or other domestic output. The second component of food accessibility is related to the ownership of resources for the attainment of nourishing diet and these resources must be available to all households. It shows that this component depends on income level, food prices, and income distribution within the households. The third componentas food utilization is related to the nutritional requirements from food and food safety (Bashir et al., 2013).

In Khyber Pakhtunkhwa province, low level of income is considered as the major problem among other prevailing factors, which resulting the problem of food insecurity (Sher et al., 2018). The issue of food insecurity in the province has caught little attention of the researchers (Sher et al., 2018), despite its importance towards achieving the national target of 2nd SDG. To achieve this, the issue needs to be studied so that not only the current existing food insecurity status of the farm households will be estimated but also factors which can solve the issue at the household level can be identified. Moreover, the study of coping strategies of farm households in dealing with food insecurity can also give a useful insight. Keeping this in view, the present study is carried out to assess the determinants of food security among the farm households of Khyber Pakhtunkhwa, Pakistan through the use of binary logistic regression. This research study specifically asks the following research questions: (1) what is the situation of food insecurity among the farm households; (2) what are the various factors which determine food security among the farm households? (3) How do farm households cope with food insecurity in the study area?

Materials and Methods

Study area

This research was carried out to assess the determinants of food security among the farm households of Khyber Pakhtunkhwa (KP), Pakistan through the use of binary logistic regression. In the KP, the incidence of poverty has been found high which limited the access of households to purchase food (FAO, 2017). Moreover, 56% of the province’ population has been found food insecure (FAO, 2017). These reasons have provided ample support to not only select the province as the study area but also to find out the determinants of food security so that the issue may be solved at household level through the adoption of certain measures. The target study area is the randomly selected district Mardan of the province (explained in the upcoming sub-section). This district is the second largest districts of the KP and surrounded by Risalpur, Charsadda, Yar Hussain, Takhtbhai and Katlang respectively. The district has an estimated population of 2,373,061 and 311,868 households and the population growth rate is estimated at 2.58% per annum (Population Census, 2017).

Sampling technique and sample size

Multistage sampling technique was adopted to select the target study site, villages, and sampled respondents of the district Mardan. In the second stage, two tehsils from the district has been chosen, while in the third stage, two union councils were selected randomly. At fourth stage, two villages from each union council have been nominated randomly. In the final stage, farm households were selected randomly through the use of a household list which has been provided by the district Nazims of the respective union councils. Proportional allocation of the sample size among the villages has been done (Table 1). This research used the household level data (Naz et al., 2020) and the target households were the farm households. For the selection of a representative sample size, Cochran (1963) formula was used and a sample size of 188 farm households was eventually drawn.

Data collection

In this study, pre-tested questionnaire was used for primary data collection during March to May, 2018 from the farm household heads. Interview method was employed to collect data from the selected respondents. Course of interviews was conducted in the light of communal research principles and ethics and also prior permission from the respondents was sought (Khan et al., 2017; Naz et al., 2018). The trust of the respondents was gained through the explanation of data usage for research purpose only and the privacy of the data. The unwilling respondents were replaced with other respondents so that the data from 188 households may be collected.

 

Table 1: Sampled households distribution in the study area.

Selected tehsil	Selected village	Farm households	Sampled households
Mardan	Bakhshali	1449	52
	Chamdheri	338	12
Katlang	Sawaldher	2656	96
	Gulibagh	780	28
Total		5223	188

 

Analytical techniques

For the achievement of specific research objectives, the collected data were subjected to the selected analytical techniques such as descriptive statistics, frequencies, percentages, rank orders, and binary logistic regression.

Current study used the DIA (Dietary Intake Assessment) as a measure of food insecurity due to the fact that the respondents of the study belong to low income groups mainly with small landholdings, thus securing an adequate amount of food was enough for them rather than focusing on the nutritional facts of the food. The selected method, used a threshold level defined by the GoP (2450 Kcal/day/person) for the rural population (GoP, 2003) on the basis of which food secure and food insecure households were categorized or differentiated. This study used a threshold level for the determination of food security status of farm households, data regarding the previous week consumed food items were collected and converted into kcal/day and then into kcal/day/A.E. (adult equivalent). The obtained results were then compared with the minimum requirements per day per A.E. Accordingly, the food secure household’s caloric consumption was found greater than or equal to 2450 Kcal/day/AE, while the food insecure household’s consumption had less than 2450 Kcal/day/AE. Per capita calorie calculation were adjusted for age and gender of the household members as well (Supplementary Table 1).

For identifying the determinants of food security, the binary logistic regression analysis was used following several studies (Sher et al., 2018; Ahmad et al., 2017; Ahmad and Abah, 2015; Muche and Koricho, 2014; Sultana and Kiani, 2011; Bashir et al., 2013). Reason behind the selection of binary logistic regression was that food security being the dependent variable has a binary form The households who had a per capita daily calorie intake equal to or above the mentioned threshold level were termed as food secured and marked as ‘1’ and those below the mentioned threshold level were regarded as food insecure and thus marked as ‘0’. After, the review of relevant literature, the independent variables have been selected for the binary logistic regression analysis which served as the determinants of food security. The fitted binary logistic regression equation has been provided as below.

FHFSi= βi + β1X1 + β2 X2 + β3X3 +β4X4+ β5X5 + β6X6 + β7X7 + β8X8 + β9D1 + β10D2+e ….(1)

Where; FHFS= Food security status of farming households (food insecure “0”, food secure “1”); βi= The constant term; β1-10=the co-efficients of the independent variables; X1= Household head’s age in years; X2= Schooling years of the respondent; X3= Household size in number; X4= Total land size in hectares; X5= Total household income/month in PKR; X6= Farming experience in years; X7= Number of small ruminants; X8= Number of large ruminants; D= Tenancy status (1=land owner, 0= otherwise); D2= Family type (1= nuclear, 0=joint).

Current research study analyzed the coping strategies of farm households during food stress through frequencies, percentages, and rank orders mainly.

Results

Socioeconomic characteristics

Data regarding the socio-economic characteristics of the respondents have been presented in Table 1. Data show that the mean age of the household head was found as 55.90 years. Most of the respondents were found to be uneducated with a mean value of 1.01 schooling years. The mean household size in the study area was 5.80 persons with an average landholding of 1.44 acre. Monthly average income of the household was found as Rs. 26186.17/= in the area. on the average basis a household kept, 0.57 and 1.14 small and large ruminants. Respondents were found to be experienced in farming with an average value of, 20.20 years of farming experience.

Food security status

Data of the food security status of the study area showed that 65% of the total sampled households were food secure, while only 35% farm households were food insecure.

 

Table 2: Socio-economic characteristics of farm households.

Variable	Minimum	Maximum	Mean	Std. Deviation
Household head’s age	37	72	55.90	8.361
Schooling years	0	14	1.01	2.823
Household size	2	11	5.80	1.703
Land size	1	3	1.44	0.609
Farming experience	4	40	20.20	7.348
Small ruminants	0	3	0.57	0.919
Large ruminants	0	11	1.14	0.938
Monthly income	10000	70000	26186.17	9473.996

 

Table 3: The food security situation among farm households.

Response categories	Frequency	Percentage
Food secure households	122	65
Food insecure households	66	35
Total households	188	100

 

Determinants of farm households’ food security

The results of binary logistic regression show that Negelkerke R square value is 0.596, i.e., 59.6% variability in outcome variable (food security status of household) is accounted by for the predictors/independent variables (Table 4). In the Hosmer and Leme show test (used as overall goodness of fit of the model), P-value was found greater than 5% level of significance, therefore it is concluded that model fit is good. From p-value column of logistic regression table of predictors, it is concluded that the predictor household size is highly significant at 1% level of significance with an odd ratio of 0.586. The variables like monthly income (odd ratio=17.02), family type (odd ratio=25.544), tenancy status (odd ratio=0.542) and small ruminants (odd ratio=0.757) were significant at 5% and 10% respectively, while all other variables have insignificant effect on food security status of farm households.

Coping strategies of farm households

Data regarding coping strategies among farm households show that 20%, 24%, 25%, 28%, 1%, and 2% of farm households had adopted eating of less preferred food, reduction in the quantity of food, borrowing of food from friends and relatives, borrowing of money to purchase food items, mothers limit their own food intake to ensure that their children get enough to eat, and skipping of one or two meals per day by the household members, respectively (Table 5).

 

Table 4: Determinants of food security among farm households using binary logistic regression model.

Variable	Odd ratio	Wald statistics	Sig.
Constant	3.056	0.341	.559NS
Age of the household head	0.994	0.044	0.833NS
Schooling years	1.016	0.059	0.808NS
Household size	0.586	17.852	0.000***
Land size	1.013	0.002	0.968NS
Monthly income	17.02	4.602	0.101
Farming experience	0.979	0.601	0.438NS
Tenancy status	0.542	2.346	0.126*
Number of small ruminants	0.968	2.341	0.126*
Number of large ruminants	0.991	0.002	0.967
Family type	25.544	4.190	0.041**

Hosmer and lemeshow test= 0.220; -2 Log likelihood= 210.885; Nagelkerke R Square= 0.596; NS: Non-Significant; *: Significant at 15% significance level; **: Significant at 05% significance level; ***: Significant at 01% significance level.

 

Table 5: Coping strategies of farm households.

Coping strategies	Frequency	Percentage	Rank order
Eating of less preferred food by the household members	100	20	4th
Reduction in the quantity of food by the household members	119	24	3rd
Borrowing of food from friends and relatives by the household members	122	25	2nd
Borrowing of money to purchase food items by the household members	140	28	1st
Mothers limit their own food intake to ensure that their children get enough to eat	06	01	6th
Skipping of one or two meals per dayby the household members	08	02	5th
Total	495	100	--

Note: Multiple responses were allowed in this section.

 

Discussion

Food insecurity being a global issue has its deep roots in Pakistan including the Khyber Pakhtunkhwa province where a total of 56% population has been found food insecure (FAO, 2017). The current study found 35% of farm households as being food insecure in the province which shows that the issue prevailed even among the food producers. The issue of food insecurity has been considered as a multifaceted concept and thus various factor sat household level determine it. In this regard, the study found that household size, monthly income, tenancy status, family type, and number of small ruminants had significantly affected the food security situation of farm households. These results are in conformity with past studies like Sher et al. (2018); Bashir (2013); and Bashir et al. (2012). In this regard, it has been reported by Mango et al. (2014) that households with more number of members were more prone to the problem of food insecurity as compared to the small sized households as they have to feed less number of people. Similarly, various researchers have also that large sized households are usually burdened in terms of feeding more people and thus usually found as food insecure (Ahmed and Abah, 2014, 2015; Irohibe and Agwu, 2014; Nigogi and Urassa, 2014; Idrisa et al., 2008). These results further imply that small sized households were usually in nuclear family type with fewer dependents and thus lower consumption requirements as compared to the large sized households which usually came from the joint family type (Irohibe and Agwu, 2014; Idrisa et al., 2008). This relationship has been also confirmed by this study result where family type has been found as the significant determinant of food security among farm households.

The positive and significant relationship between food security and monthly income has been conformed in the literature by various researchers who noted that higher income levels of households provided them with increased access to food and thus the household became food secure (Leza and Kuma, 2015; Asmelash, 2014; Beyene and Much, 2010), Pakistan (Ahmed et al., 2017; Cheema and Abass, 2016; Bashir et al., 2012, 2013), and in Nepal (Joshi and Joshi, 2016).

Tenancy status plays an important role in the determination of food security among farm households. It has been found the tenants were found more food insecure as compared to land owners. This finding has been confirmed in the literature by various researchers (Bashir et al., 2013). Likewise, livestock ownership also served as an important determinant of food security among farm households (Mango et al., 2014). During food shortages or agricultural stresses and shocks the livestock are sold out to get food at its earliest. In addition, livestocks provide food in the shape of dairy products at household level. The cash earned from livestock products are also utilized for purchasing food items (Naz et al., 2018). The relationship between livestock ownership and food security has been also confirmed by studies like Dawit (2017) and Aragie and Genanu (2017) who reported that food secure households possessed a relatively higher number of livestock than food insecure households, thus, increase number of livestock ensures food security. Among the livestock types, the small ruminants like goats, sheep etc. meet the financial needs of household along with the food requirements (Naz and Khan, 2018; Mango et al., 2014). Thus, the more the number of small ruminants, the more the household was likely to be food secure.

Households coped with food insecurity using various strategies. This study found some of the common coping strategies to include: eating less preferred food, reduction in quantity of food, borrowing food from friends and relatives, borrowing money to buy food, mothers limiting their own food intake in order to ensure that their children get enough to eat, and skipping one or two meals per day. The results are in line with the findings of previous studies that found the use of non-preferred food (Grobler, 2014), reduction in quality and quantity of food (Sharrif and Khor, 2008), lending money for food (Olayiwola et al., 2017), food receiving from relatives, neighbors and other family members (Sharrif and Khor, 2008).

Conclusions and Recommendations

This study portrays that farm households of the study area face food insecurity challenge. Some of the factors affecting their food security status include household size and tenancy status which were found to be negative determinants, while monthly income, family type status, and ownership of small ruminants served as the positive determinants of food security. In this regard, effective measures from both the public and private sides are important to address the issue.

The specific measures include control of the household size through the implementation of family planning program with religious point of view and the rearing of small ruminants like goats and sheep etc. Thus, the government and non-government interventions especially gearing towards the livestock sector can minimize the problem of food insecurity in the study area. These interventions are of immense importance because the farm households are taking efforts through the adoption of various coping strategies such as borrowing of money to purchase food items and borrowing of food from friends and relatives. However, these coping strategies are not effective in terms of achieving food security in the long run. In this regard, the livelihood or income diversification is an important strategy to be employed by farm households through the help of public and private agencies. It will help the farm households to not only cope with food insecurity but will also be able to further improve their livelihoods and thus achieve the ultimate aim of agricultural and rural development as well. An important consideration to deal with food insecurity in the province is that such studies may be conducted at large study sites and also with more variables so as to generate more detailed results that can inform comprehensive programs.

Acknowledgements

The authors acknowledge the rural households whose cooperations led top the completion of this research study. The authors also acknowledge the department of Rural Development, Amir Muhammad Khan Campus, Mardan, The University of Agriculture, Peshawar for the provision of institutional facilities to complete this research study in time.

Novelty Statement

Food insecurity being a problem of the area can be tackled by investing in the socioeconomic factors like education and employment opportunities in the livestock sector.

Author’s Contribution

Muhammad Azam: Conceived the idea and was involved in all the research study steps i.e. data collection, writing etc.

Shaista Naz: Supervised the overall research study, analysis, and overall writing.

Malik Muhammad Shafi: Helped in designing of questionnaire and model fixation.

Muhammad Jamil Afridi: Helped in the theoretical framework, editing and proof reading.

Ahmad Waheed: Contributed in data collection, sampling technique and sample size calculations.

Supplementary Material

There is supplementary material associated with this article. Access the material online at: http://dx.doi.org/10.17582/journal.sja/

Conflict of interest

The authors have declared no conflict of interest.

References

Abid, M., M. Ashfaq, S. Hassan and N. Fatima. 2011. A resource use efficiency analysis of small Bt cotton farmers in Punjab, Pakistan. Pak. J. Agric. Sci., 48: 65–71.

Abid, M., J. Schilling, J. Scheffran and F. Zulfiqar. 2016. Climate change vulnerability, adaptation and risk perceptions at farm level in Punjab, Pakistan. Sci. Total Environ., 547: 447–460. https://doi.org/10.1016/j.scitotenv.2015.11.125

Ahmad, F.F., and P.O. Abah. 2014. Determinants of food security among low-income households in Maiduguri Metropolis of Borno State, Nigeria. Asian J. Social. Sci. Humanities, 3(1): 74-86.

Ahmed, F.C.E. and P.O. Abah. 2015. Analysis of food security among farming households in Borno State, Nigeria. J. Agric. Eco. Environ. Soc. Sci., 1(1): 130–141.

Ahmed, U.I., L. Ying, M.K. Bashir, M. Abid, and F. Zulfiqar. 2017. Status and determinants of small farming households’ food security and role of market access in enhancing food security in rural Pakistan. PLoS One, 12(10): e0185466. https://doi.org/10.1371/journal.pone.0185466

Apanovich, N. and R.E. Mazur. 2018. Determinants of seasonal food security among smallholder farmers in south-central Uganda. Agric. Food Secur., 7: 87. https://doi.org/10.1186/s40066-018-0237-6

Aragie, T., and S. Genanu. 2017. Level and determinants of food security in north Wollo zone (Amhara region Ethiopia). J. Food Secur., 5(6): 232-247. https://doi.org/10.12691/jfs-5-6-4

Asmelash, M., 2014. Rural household food security status and its determinants the case of Laelaymychew Woreda centre zone of Tigrai, Ethiopia. J. Agric. Ext. Rural Dev., 6(5): 162-167. https://doi.org/10.5897/JAERD2013.0555

Bashir, M.K., S. Schilizzi and R. Pandit. 2012a. Food security and its determinants at the crossroads in Punjab, Pakistan. Working Paper 1206, School of Agricultural and Resource Economics. Australia: University of Western Australia, Crawley

Bashir, M.K., S. Schilizzi and R. Pandit. 2013. Regional sensitivity of rural household food security: The case of Punjab, Pakistan. J. Anim. Plant Sci., 23(4): 1200-1206.

Beyene, F., and M. Muche. 2010. Determinants of food security among rural households of central Ethiopia. Q. J. Int. Agric., 49(4): 299-318.

Cheema, A.R., and Z. Abbas. 2016. Determinants of food insecurity in Pakistan. Pak. J. Appl. Eco., 26(2): 183-213.

Cochran, W.G. 1963. Sampling techniques, 2nd Ed., New York: John Wiley and Sons, Inc.

Dawit, D., 2017. Determinants of rural household food security in Wolaita Zone: The case of Humbo Woreda. J. Poverty Invest. Dev. 32: 65-82.

Farzana, F.D., A.S. Rahman, S. Sultana, M.J. Raihan, M.A. Haque and J.L. Waid. 2017. Coping strategies related to food insecurity at the household level in Bangladesh. PLoS One, 12(4): https://doi.org/10.1371/journal.pone.0171411

Food and Agriculture Organisation (FAO), 2017. The state of food security and nutrition in the world 2017. Building Resilience for Peace and Food Security; FAO: Rome, Italy.

Food and Agriculture Organization of the United Nations (FAO), 2017. The state of food security and nutrition in the world: building resilience for peace and food security. http://www.fao.org/3/a-I7695e.pdf.

GOP, 2003. Economic survey of Pakistan, 2002-03. Ministry of food and agriculture. Finance Division, Economic Advisor’s Wing, Islamabad, Pakistan

Grobler, W.C.J., 2014. Food insecure household coping strategies: The case of a low-income neighbourhood in South Africa. Mediterr. J. Soc. Sci., 5(13): 100-106. https://doi.org/10.5901/mjss.2014.v5n13p100

Sher, G., F. Rabbi and U. Hayat. 2018. Food insecurity and its determinants in rural Khyber Pakhtunkhwa, Pakistan. Asian J. Agric. Biol., 6(3): 308-315.

Harvey, C.A., M. Saborío-Rodríguez, M.R. Martinez-Rodriguez, B. Viguera, A. Chain-Guadarrama, R. Vignola and F. Alpizar. 2018. Climate change impacts and adaptation among smallholder farmers in Central America. Agric. Food Secur., 7(57): 1–20. https://doi.org/10.1186/s40066-018-0209-x

Hussain, A., G. RasuL, B. Mahapatra and S. Tuladhar. 2016. Household food security in the face of climate change in the Hindu-Kush Himalayan region. Food Sec., 8(5): 921–937. https://doi.org/10.1007/s12571-016-0607-5

Idrisa, Y.L., M.M. Gwary, and H. Shehu. 2008. Analysis of food security status among farming household in Jere local government of borno state, Nigeria. J. Trop. Agric. Food, Environ. Ext., 7(3): 199-205. https://doi.org/10.4314/as.v7i3.45552

Irohibe, I.J. and A.E. Agwu. 2014. Assessment of food security situation among farming households in rural areas of Kano State, Nigeria. J. Cent. Eur. Agric., 15(1): 94-107. https://doi.org/10.5513/JCEA01/15.1.1418

Joshi, G.R., and N.B. Joshi. 2016. Determinants of household food security in the eastern region of Nepal. SAARC J. Agric., 14(2): 174-188. https://doi.org/10.3329/sja.v14i2.31257

Khan, W., N. Khan and S. Naz. 2017. Beekeeping in federally administered tribal areas of Pakistan; Opportunities and constraints. Sarhad J. Agric., 33(3): 459-465. https://doi.org/10.17582/journal.sja/2017/33.3.459.465

Leza. T., and B. Kuma, 2015. Determinants of rural farm household food security in Boloso Sore district of Wolaita zone in Ethiopia. Asian J. Agric. Ext. Eco. Sociol., 5(2): 57-68. https://doi.org/10.9734/AJAEES/2015/14833

Mango, N., B. Zamasiya, C. Makate, K. Nyikahadzoi, and S. Siziba. 2014. Factors influencing household food security among smallholder farmers in the Mudzi district of Zimbabwe. Dev. S. Afr., 31(4): 625–640. https://doi.org/10.1080/0376835X.2014.911694

Mary, O.A., and E.M. Igbokwe. 2014. Food security and coping strategies among ethnic groups in north central Nigeria. Dev. Country Stud., 4(8): 31-44. www.iiste.org

Maung, T.W., 2017. Study on food security status and coping strategies of rural households in Myingyan Township, Dry Zone Area, Myanmar.

Muche, M.B.E. and T. Koricho. 2014. Determinants of household food security among southwest Ethiopia Rural Households. Food. Sci. Tech., 2(7): 93-100. https://doi.org/10.13189/fst.2014.020701

Naz, S., N.P. Khan, H. Khan and Azra. 2020. Does women’s participation in livestock management enhance their empowerment? An insight from the tribal belt of Pakistan. Sarhad J. Agric., 36(3): 823-831. https://doi.org/10.17582/journal.sja/2020/36.3.823.831

Naz, S., N.P. Khan, N. Afsar and A.A. shah. 2018. Women’s participation and constraints in livestock management: A case of Khyber Pakhtunkhwa Province Pakistan. Sarhad J. Agric., 34(4): 917-923. https://doi.org/10.17582/journal.sja/2018/34.4.917.923

Naz, S. and N.P. Khan. 2018. Financial contribution of livestock at household level in Federally Administered Tribal Areas of Pakistan: An empirical perspective. Sarhad. J. Agri., 34(1):1-9. http://dx.doi.org/10.17582/journal.sja/2018/34.1.1.9

Ngongi. A.M., and J.K. Urassa. 2014. Farm household’s food production and households’ food security status: A case of Kahama district, Tanzania. Tanzania J. Agric. Sci., 13(2): 40-58.

Nkomoki, W., M. Bavorová and J. Banout. 2019. Factors associated with household food security in Zambia. Sustainability, 11: 2715. https://doi.org/10.3390/su11092715

Olayiwola, S., A.K. Tashikalma and Y.D. Giroh. 2017. Analysis of food security status and coping strategies among rural households in Oluyole local government area of Oyo state, Nigeria. FUW Trends Sci. Technol. J., 2(1): 28-32.

Pérez-Escamilla and Segall-Corrêa. 2008. Food insecurity measurement and indicators. Rev. Nutr., 21(suppl): 2008. https://doi.org/10.1590/S1415-52732008000700003

Poczta-Wajda, A., A. Sapa, Sebastian and M. Borychowski. 2020. Food insecurity among small-scale farmersin Poland. Agriculture, 10: 295. https://doi.org/10.3390/agriculture10070295

Population Census. 2017. Salient features of 6th population & housing census 2017. Pakistan Bureau of Statistics.

Porter, J.R., L. Xie, A.J. Challinor, K. Cochrane, S.M. Howden, M.M. Iqbal, D.B. Lobell and M.I. Travasso. 2014. Food security and food production systems. Climate Chang 2014 Impacts, Adapt Vulnerability - Contrib Work Gr II to Fifth Assess Rep. pp. 485–533.

Sheriff, Z.M., and G.L. Khor. 2008. Household food insecurity and coping strategies in a poor rural community in Malaysia. Nutr. Res. Pract., 2(1): 26-34. https://doi.org/10.4162/nrp.2008.2.1.26

Sultana, A., and A. Kiani. 2011. Determinants of food security at household level in Pakistan. Afr. J. Bus. Manage., 5(34): 12972-12979. https://doi.org/10.5897/AJBM11.1441

Tefera, T., and F. Tefera. 2014. Determinants of household’s food security and coping strategies for food shortfall in Mareko district, Guraghe Zone Southern Ethiopia. J. Food Secur., 2(3): 92-99.

WFP, 2015. World food programme. Análisis inicial del impacto de la sequía en la seguridad alimentaria en Guatemala, El-Salvador y Honduras. Technical Brief. pp.4.

WFP (World Food Program). 2016. Pakistan food security bulletin. Issue 4.

World Food Program, 2017. Pakistan www.wfp.org.

World Food Program, 2010. Countries: Threats to Food Security in Pakistan. www.wfp.org