Policy-oriented food insecurity estimation and mapping at district level in Pakistan



Figure 3. District food insecurity incidence in Pakistan, 2015

Source: authors' own work.

Food insecurity density at the district level. This section presents a detailed analysis of specific food insecurity density in the district as well as comparison with the food insecurity incidence analysis of the districts under consideration.

The estimates of food insecurity density at the district level are shown in Table C. It has been identified that the situation regarding food insecurity status in Karachi has turned upside down mainly because Karachi is the second least food insecure one in terms of food insecurity incidence. Therefore, Karachi has been characterized with the highest figure of food insecure people (6.4 million) based district level food insecurity density estimates. ICA [30] indicated Karachi under the category of low vulnerability to food insecurity. Contrarily, top-20 districts with most food insecure people are from the province of Punjab except Peshawar and Karachi which belong to KP and Sindh. Similarly, it has been identified that 20 of the most food insecure districts were from Balochistan according to the food insecurity incidence analysis. Some of the districts, including Karachi City, Lahore, Rahim Yar Khan, Faisalabad, Muzaffargarh, Multan, Gujranwala, Bahawalpur, Rawalpindi, and Sheikhupura have a food insecurity density ranging from 6.43 to 2.24 million.

Similarly, Washuk district from Balochistan is the most food insecure district in terms of food insecurity incidence. In addition, Washuk is reported as highly vulnerable to food insecurity in ICA [30]. However, Washuk is found to be the 13th least food insecure district having only 0.17 million food insecure people. In addition, other districts in Balochistan namely Zhob, Dera Bugti, Kachhi, Jhal Magsi, Chagai, Mastung, Nushki, Sibi, Kharan, Harnai, Ziarat, Kohlu and Barkhan, were included in top-20 districts with more than 80 % households being food insecure. All of these 20 districts from Balochistan come under the category of high vulnerability to food insecurity [30]. These districts are now among the 20 least food insecure districts having food insecure people less than 0.20 million.

On the other hand, there were only 10 districts with the worst food insecurity situation from Balochistan according to SDPI [29]. Furthermore, district of Sheerani has been identified as the least food insecure having 0.05 million food insecure people. Earlier, Sheerani district was the 35th most food insecure with more than 80 % households being food insecure according to the food insecurity incidence analysis. According to the ICA [30] Sheerani fall under the category of highly vulnerable areas to food insecurity in Pakistan.

The map analysis in Figure 4 highlights food insecurity at the district level. Karachi is the only district in the province of Sindh that is the most food insecure with more than 6.0 million food insecure people. Therefore, Karachi is located in the red zone, whereas Lahore is the second most food insecure district from the province of Punjab with approximately 5.50 million food insecure people. Therefore, Lahore district is represented by orange whereas yellow region indicates that Rahim Yar Khan is the third most food insecure district from the province of Punjab with more than four million food insecure people. On the other hand, green regions represent the districts with food insecure people ranging from 2.0 to 3.78 million mainly from the provinces of Sindh and Punjab. Finally, dark blue regions represent the districts, mostly from the provinces of Balochistan and KP having number of food insecure people below one million.

Figure 4. Food insecurity density at the district level in Pakistan, 2015

Source: authors' own estimation.

Overall, food insecurity density at the district level according to each province reveals that the districts of Balochistan, except Killa Abdullah, have less than

7 million food insecure people. Similarly, districts of KP have less than one million food insecure people except Peshawar where food insecurity is higher reaching a total of 1.81 million. In addition, districts of Sindh, except Karachi, have less than two million food insecure people. Karachi has maximum number of food insecure people reaching almost 6.0 million. Interestingly, some districts in Punjab have lower levels of food insecurity with less than one million food insecure people, whereas others have higher numbers of food insecure people ranging from 2 to 6 million. For instance, the district of Chakwal has 0.52 million food insecure people, whereas the districts of Kasur, Rahim Yar Khan, Faisalabad, and Lahore have 2.00, 3.78, 4.12, and 5.50 million food insecure people, respectively. Finally, grey regions represent FATA and districts of Punjgur and Kach from Balochistan with no available data.

The analysis of food insecurity density estimates at the district level has pointed to the fact that there are many districts with high food insecurity incidence level and relatively small number of food insecure people. On the other hand, there are many districts with low food insecurity incidence and a large number of food insecure people as expected.

Finally, the Table 1 presents the comparison of different study's results. This study shows that Pakistan has not achieved improvement in food security situation.

Table 1 Comparison of results with district food insecurity assessments conducted by FSA Pakistan 2009 and ICA Pakistan 2017

District	Food Insecurity Incidence, %	Food Insecurity Incidence (FSA 2009), %	Food Insecurity Vulnerability Incidence* (ICA 2017)	District	Food Insecurity Incidence, %	Food Insecurity Incidence (FSA 2009)	Food Insecurity Vulnerability Incidence* (ICA 2017)	District	Food Insecurity Incidence	Food Insecurity Incidence (FSA 2009)	Food Insecurity Vulnerability Incidence* (ICA 2017)
1	2	3	4	5	6	7	8	9	10	11	12
1. Washuk (B)	93.44	NE	41.70	39. Naushahro Feroze (S)	78.05	39.30	27.22	77. Swat (KP)	66.38	54.20	25.60
2. Killa Abdullah (B)	92.19	64.30	43.70	40. Tando Muhammad Khan (S)	77.82	34.30	39.76	78. Gujranwala (P)	66.28	37.00	8.35
3. Khuzdar (B)	91.50	63.90	35.21	41. Dadu (S)	77.72	49.20	28.92	79. Dera Ismail Khan (KP)	65.80	56.00	33.14
4. Awaran (B)	90.92	67.20	45.43	42. Badin (S)	77.13	40.00	39.29	80. Mandi Bahauddin (P)	65.75	31.60	16.15
5. Ziarat (B)	90.92	57.90	42.79	43. Rahim Yar Khan (P)	77.10	39.00	30.68	81. Peshawar (KP)	65.63	49.30	15.02
6. Jhal Magsi (B)	90.91	52.10	44.78	44. Muzaffargarh (P)	76.79	49.90	34.99	82. Nankana Sahib (P)	65.49	NE	15.58
7. Nasirabad (B)	89.81	41.40	41.09	45. Matiari (S)	76.59	33.50	30.67	83. Kohistan (KP)	65.16	73.50	61.40
8. Gwadar (B)	89.75	53.60	29.70	46. Sanghar (S)	76.27	25.00	31.21	84. Sialkot (P)	65.11	29.20	11.08
9. Jaffarabad (B)	89.51	41.60	37.22	47. Shaheed Benazirabad (S)	76.08	57.50	33.61	85. Sahiwal (P)	64.94	33.80	20.06
10. Dera Bugti (B)	89.45	82.40	52.21	48. Sujawal (S)	76.01	NE	43.69	86. Shangla (KP)	64.92	60.90	NE
11. Kharan (B)	89.28	60.60	50.10	49. Larkana (S)	75.48	37.30	25.23	87. Sargodha (P)	64.82	39.90	20.24
12. Harnai (B)	89.22	NE	46.52	50. Jamshoro (S)	75.16	36.00	32.94	88. Nowshera (KP)	64.42	47.50	17.33
13. Kohlu (B)	89.18	NE	53.56	51. Umerkot (S)	74.22	59.40	41.82	89. Faisalabad (P)	64.16	31.90	10.68
14. Chagai (B)	87.69	NE	21.62	52. Thatta (S)	74.00	39.10	39.67	90. Lower Dir (KP)	64.10	64.50	24.79
15. Kachhi (B)	87.58	NE	45.80	53. Kasur (P)	73.92	40.20	16.49	91. Bannu (KP)	64.07	52.10	29.31
16. Mastung (B)	87.27	65.00	31.00	54. Buner (KP)	73.64	60.60	31.03	92. Toba Tek Singh (P)	63.61	29.90	16.27
17. Nushki (B)	87.00	69.60	33.79	55. Mirpur Khas (S)	73.48	38.60	35.17	93. Narowal (P)	63.40	43.50	19.32
18. Sibi (B)	86.46	56.00	36.38	56. Tank (KP)	73.26	60.00	35.00	94. Khushab (P)	63.25	48.30	21.35
19. Barkhan (B)	85.90	62.20	47.50	57. Bahawalpur (P)	73.21	43.60	27.86	95. Mianwali (P)	63.18	44.00	24.75
20. Zhob (B)	85.46	67.00	50 94	58. Bhakkar (P)	72.74	40.80	30.54	96. Lahore (P)	62.17	29.10	3.87
21. Pishin (B)	85.28	58.20	33.94	59. Upper Dir (KP)	72.03	75.60	39.59	97. Lakki Marwat (KP)	61.75	66.30	32.84
22.Kashmore (S)	84.94	NE	35.68	60. Bahawalnagar (P)	71.98	33.30	24.81	98. Batagram (KP)	60.69	50.40	33.32
23. Ghotki (S)	83.89	NE	31.75	61. Layyah (P)	71.60	37.40	24.51	99. Hangu (KP)	60.57	54.20	25.63
24. Kalat (B)	83.82	64.20	38.53	62. Lodhran (P)	70.94	39.00	28.48	100. Kohat (KP)	59.69	52.60	21.60
25. Jacobabad (S)	83.72	38.70	36.54	63. Tharparkar (S)	70.77	53.40	44.17	101. Swabi (KP)	59.60	53.00	20.96
26. Las Bela (B)	83.64	49.80	39.92	64. Chiniot (P)	70.65	NE	19.92	102. Malakand PA (KP)	59.43	61.00	20.41
27. Musakhel (B)	83.59	78.50	47.16	65. Khanewal (P)	70.26	39.20	24.45	103. Gujrat (P)	59.26	38.00	8.58
28. Quetta (B)	82.85	40.90	15.13	66. Multan (P)	69.75	44.60	21.36	104. Karak (KP)	58.62	63.70	27.26
29. Shikarpur (S)	82.63	32.40	30.22	67. Sheikhupura (P)	69.63	35.80	13.62	105. Attock (P)	57.09	41.90	10.52
30. Khairpur (S)	81.55	50.40	26.88	68. Vehari (P)	69.56	35.40	21.96	106. Jhelum (P)	56.13	34.30	6.34
31. Sukkur (S)	81.24	66.90	21.95	69. Charsadda (KP)	69.55	54.70	24.28	107. Rawalpindi (P)	55.28	28.60	5.08
32. Qambar Shahdadkot(S)	81.12	44.10	32.66	70. Okara (P)	69.40	36.10	23.59	108. Islamabad (FCT)	54.07	23.60	0.87
33. Loralai (B)	80.60	68.80	43.60	71. Hyderabad (S)	68.99	46.60	14.87	109. Chakwal (P)	53.66	41.70	7.67
34. Rajanpur (P)	80.34	55.30	39.78	72. Jhang (P)	68.67	38.70	27.63	110. Haripur (KP)	53.45	40.20	15.16
35. Sheerani (B)	80.31	NE	49.57	73. Pakpattan (P)	68.45	29.90	25.91	111. Mansehra (KP)	53.20	46.70	23.83
36. Killa Saifullah (B)	78.82	57.00	47.04	74. Hafizabad (P)	67.62	34.30	17.07	112. Chitral (KP)	51.06	60.70	21.29
37. Dera Ghazi Khan (P)	78.52	55.00	37.20	75. Mardan (KP)	67.03	51.30	19.95	113. Karachi City (S)	49.85	38.00	3.94
38. Tando Allah Yar (S)	78.32	59.50	32.38	76. Tor Ghar (KP)	66.43	NE	NE	114. Abbottabad (KP)	44.27	40.60	16.10

Notes. NE - No Estimates;

*% ages calculated from the estimates reported in ICA Pakistan 2017;

(B) - Balochistan; (S) - Sindh; (P) - Punjab; (KP) - Khyber Pakhtunkhwa.

Source: authors' own estimation comparison with 2009 and 2017 estimates.

The above comparison and generalization showed that this study helped highlight areas affected by food insecurity for which SDPI did not have estimates [29]. Additionally, this study highlighted the districts with greater food insecure population, which were not indicated in ICA [30], rather, those districts were presented as less vulnerable to food insecurity in ICA [30]. Finally, this study indicated the figure of actual food insecure districts in contrast with ICA [30], in which, districts vulnerable to food insecurity have been indicated.



Conclusions

Food insecurity maps play an important role in efficient resource allocation by governments and other international organizations. However, the geographically disaggregated food insecurity estimates based on large integrated datasets in Pakistan are not sufficiently explored. In this study, we have analyzed food insecurity at the district level with special reference to Pakistan by integrating PSLM 2014-2015 and HIES 2015-2016 datasets. The analysis includes estimation and mapping of district specific food insecurity incidence as well as district specific food insecurity density based on SAE approach. The results reveal that the overall food security situation in Pakistan has not improved. For instance, approximately two-third households fail to make even the subsistence food expenditures at national level. Similarly, at provincial level, Balochistan has been identified to be the most food insecure and KP is the least food insecure province. In addition, the results indicate that Washuk is the most food insecure whereas Abbottabad is the least food insecure district in Pakistan.

On the other hand, the SAE based food insecurity density estimates at the district level have provided quite the opposite results. For instance, Karachi is ranked as the most food insecure in terms of food insecurity density whereas Washuk is ranked as the 13th least food insecure district. Similarly, the top-20 districts with most food insecure population, except for Peshawar and Karachi, are from the province of Punjab. Finally, the Sheerani district that was categorized under high food insecurity incidence, has the least food insecure population.

In addition, the district level food insecurity maps based on incidence and density estimates are significant in locating the food insecure districts as well as the districts that are highly concentrated with food insecure population. The analysis also revealed that many districts with a low food insecurity incidence have a lot of food insecure people. Furthermore, the results of this study have strong policy implications in relation with the disaggregated level of food insecurity estimation in Pakistan. The obtained information based on food insecurity maps at the district level can ultimately guide the government and policy makers for targeted allocation of resource and solution oriented planning. However, policy interventions guided only by the results of food insecurity incidence might cause deprivation of the real beneficiaries. Therefore, both, food insecurity intensity and density dimensions should be considered during the formulating of food insecurity alleviation programs and policies as well as allocation of resources. In addition, the policy interventions should consider the district level or household level effects within food insecure districts as socio-economic factors may differ across households in determining the food insecurity intensity.

Finally, it is recommended that the policy makers consider food insecurity density and incidence for targeted interventions at the district level in Pakistan. This study can serve as a guideline for local actions to reduce food insecurity. In addition, efforts at district level for combating food insecurity in Pakistan may bring promising results as compared to an inflexible national approach. Long term targeted food assistance and cash assistance programs in the most food insecure districts of Balochistan such as Washuk, Killa Abdullah, Khuzdar, Awaran and Ziarat may result in improving the economic and physical access to food. Additionally, policy intervention should focus on providing financial assistance to the number of food insecure people in the areas with low food insecurity incidence, such an example is Karachi where the largest number of food insecure people are located.

Future studies could be performed with rural / urban apartheid at district level for highlighting the differences in food insecurity prevalence among the rural and urban segments in Pakistan.



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Appendix

Table A Provincial food insecurity incidence in Pakistan

Ranking	Province	Food Insecurity Incidence, %
1	Balochistan	89.45
2	Sindh	71.72
3	Punjab	65.35
4	Khyber Pakhtunkhwa	63.43

Source: authors' own estimation.

Table B Food insecurity incidence at the district level in Pakistan

Ran king	District	Pro vince	Food Insecurity Incidence, %	Ran king	District	Pro vince	Food Insecurity Incidence, %	Ran king	District	Pro vince	Food Insecurity Incidence, %
1	Washuk	B	93.44	39	Naushahro Feroze	S	78.05	77	Swat	KP	66.38
2	Killa Abdullah	B	92.19	40	Tando Muhammad Khan	S	77.82	78	Gujranwala	P	66.28
3	Khuzdar	B	91.50	41	Dadu	S	77.72	79	Dera Ismail Khan	KP	65.80
4	Awaran	B	90.92	42	Badin	S	77.13	80	Mandi Bahauddin	P	65.75
5	Ziarat	B	90.92	43	Rahim Yar Khan	P	77.10	81	Peshawar	KP	65.63
6	Jhal Magsi	B	90.91	44	Muzaffargarh	P	76.79	82	Nankana Sahib	P	65.49
7	Nasirabad	B	89.81	45	Matiari	S	76.59	83	Kohistan	KP	65.16
8	Gwadar	B	89.75	46	Sanghar	S	76.27	84	Sialkot	P	65.11
9	Jaffarabad	B	89.51	47	Shaheed Benazirabad	S	76.08	85	Sahiwal	P	64.94
10	Dera Bugti	B	89.45	48	Sujawal	S	76.01	86	Shangla	KP	64.92
11	Kharan	B	89.28	49	Larkana	S	75.48	87	Sargodha	P	64.82
12	Harnai	B	89.22	50	Jamshoro	S	75.16	88	Nowshera	KP	64.42
13	Kohlu	B	89.18	51	Umerkot	S	74.22	89	Faisalabad	P	64.16
14	Chagai	B	87.69	52	Thatta	S	74.00	90	Lower Dir	KP	64.10
15	Kachhi	B	87.58	53	Kasur	P	73.92	91	Bannu	KP	64.07
16	Mastung	B	87.27	54	Buner	KP	73.64	92	Toba Tek Singh	P	63.61
17	Nushki	B	87.00	55	Mirpur Khas	S	73.48	93	Narowal	P	63.40
18	Sibi	B	86.46	56	Tank	KP	73.26	94	Khushab	P	63.25
19	Barkhan	B	85.90	57	Bahawalpur	P	73.21	95	Mianwali	P	63.18
20	Zhob	B	85.46	58	Bhakkar	P	72.74	96	Lahore	P	62.17
21	Pishin	B	85.28	59	Upper Dir	KP	72.03	97	Lakki Marwat	KP	61.75
22	Kashmore	S	84.94	60	Bahawalnagar	P	71.98	98	Batagram	KP	60.69
23	Ghotki	S	83.89	61	Layyah	P	71.60	99	Hangu	KP	60.57
24	Kalat	B	83.82	62	Lodhran	P	70.94	100	Kohat	KP	59.69
25	Jacobabad	S	83.72	63	Tharparkar	S	70.77	101	Swabi	KP	59.60
26	Las Bela	B	83.64	64	Chiniot	P	70.65	102	Malakand PA	KP	59.43
27	Musakhel	B	83.59	65	Khanewal	P	70.26	103	Gujrat	P	59.26
28	Quetta	B	82.85	66	Multan	P	69.75	104	Karak	KP	58.62
29	Shikarpur	S	82.63	67	Sheikhupura	P	69.63	105	Attock	P	57.09
30	Khairpur	S	81.55	68	Vehari	P	69.56	106	Jhelum	P	56.13
31	Sukkur	S	81.24	69	Charsadda	KP	69.55	107	Rawalpindi	P	55.28
32	Qambar Shahdadkot	S	81.12	70	Okara	P	69.40	108	Islamabad	FCT	54.07
33	Loralai	B	80.60	71	Hyderabad	S	68.99	109	Chakwal	P	53.66
34	Rajanpur	P	80.34	72	Jhang	P	68.67	110	Haripur	KP	53.45
35	Sheerani	B	80.31	73	Pakpattan	P	68.45	111	Mansehra	KP	53.20
36	Killa Saifullah	B	78.82	74	Hafizabad	P	67.62	112	Chitral	KP	51.06
37	Dera Ghazi Khan	P	78.52	75	Mardan	KP	67.03	113	Karachi City	S	49.85
38	Tando Allah Yar	S	78.32	76	Tor Ghar	KP	66.43	114	Abbottabad	KP	44.27

Note. B - Balochistan; S - Sindh; P - Punjab; KP - Khyber Pakhtunkhwa. Source: authors' own estimation.

Table C Food insecurity density at the district level in Pakistan

Ran king	District	Population	Food Insecurity Density	Food Insecurity Density (In Million)	Ran king	District	Population	Food Insecurity Density	Food Insecurity Density (In Million)
1	2	3	4	5	6	7	8	9	10
1	Karachi City	12906861	6433680	6.43	58	Swabi	1114258	664146	0.66
2	Lahore	8843249	5498182	5.50	59	Khushab	1028518	650506	0.65
3	Rahim Yar Khan	5348066	4123502	4.12	60	Islamabad	1193019	645086	0.65
4	Faisalabad	5889614	3778838	3.78	61	Umerkot	864589	641715	0.64
5	Muzaffargarh	3887101	2985013	2.99	62	Nowshera	971351	625709	0.63
6	Multan	3754034	2618497	2.62	63	Hafizabad	918667	621222	0.62
7	Gujranwala	3929469	2604291	2.60	64	Upper Dir	857602	617731	0.62
8	Bahawalpur	3319128	2429825	2.43	65	Bannu	929833	595731	0.60
9	Rawalpindi	4361061	2410982	2.41	66	Mansehra	1056086	561787	0.56
10	Sheikhupura	3212433	2236909	2.24	67	Tando Allah Yar	716487	561188	0.56
11	Sialkot	3355016	2184294	2.18	68	Jhelum	978516	549257	0.55
12	Dera Ghazi Khan	2564761	2013945	2.01	69	Buner	724949	533834	0.53
13	Kasur	2701741	1997085	2.00	70	Jamshoro	709168	532978	0.53
14	Khairpur	2279620	1858990	1.86	71	Jaffarabad	593865	531593	0.53
15	Peshawar	2765210	1814715	1.81	72	Matiari	690761	529044	0.53
16	Bahawalnagar	2518799	1812968	1.81	73	Chakwal	966607	518650	0.52
17	Vehari	2571864	1789098	1.79	74	Khuzdar	559213	511657	0.51
18	Okara	2540204	1762955	1.76	75	Tando M. Khan	643086	500448	0.50
19	Sargodha	2663323	1726443	1.73	76	Kohat	814850	486392	0.49
20	Khanewal	2421789	1701495	1.70	77	Thatta	648226	479713

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