<|begin_of_text|><|start_header_id|>system<|end_header_id|>You are an expert on climate change, human mobility and migration. Answer the question truthfully.<|eot_id|><|start_header_id|>user<|end_header_id|>Here are the title and abstract of a scientific paper probably related to climate change, human mobility and migration..
Title:"Validity of the Food Insecurity Experience Scale (FIES) for Use in League of Arab States (LAS) and Characteristics of Food Insecure Individuals by the Human Development Index (HDI)."
Abstract:"Background: The Food Insecurity Experience Scale (FIES) is a UN FAO Voices of the Hungry (FAO-VoH) experiential metric of food insecurity (FI). It was pilot tested in some countries but not in Arab speaking ones and validated using global data. Yet, its psychometric properties may vary in the League of Arab States (LAS) due to cultural and linguistic differences. Objectives: 1) assess the validity of FIES for use in the LAS region, 2) determine the prevalence of FI, by gender, age group, and the human development index (HDI), and 3) examine sociodemographic characteristics of severe FI individuals. Methods: To assess the psychometric properties of FIES, Rasch modeling was applied to the 2014-2015 Gallop World Poll (GWP) in the LAS. Prevalence and characteristics of severely FI individuals were assessed using the 2014-2017 GWP data of 62,261 respondents. Results: Overall, FIES met the Rasch model assumptions of equal discrimination and conditional independence. Infit statistics for FIES items, in most LAS countries, were <1.3, indicating good internal validity. In Syria and Sudan, the item worried about not having enough food to eat had infits >1.3. Outfit statistics >2.0, indicating erratic responses, were noted in 26% of the LAS countries. Significant correlations were found (>= 0.4) between items in Algeria, Tunisia, and Lebanon. The overall prevalence of severe FI was 15.7%. At highest risk were those aged >= 50 y compared with younger adults (16.5% versus 15.5%, respectively, P <0.02), women compared with men (17.6% versus 14.1%, respectively, P <0.0001), and those in countries with low HDI compared with high HDI (24.9% versus 8.3%, respectively, P <0.0001). Conclusions: Overall, FIES is valid for measuring FI in the LAS. Cognitive testing of items with high outfit statistics and omission of correlated ones may improve the scale. Populations vulnerable to severe FI include older adults and women. These populations should be examined further.."
I have six questions you need to answer.
Q1: Is this article is about 'human migration mobility': 1 = yes; 0 = no. Answer with a number. Do not give a textual explanation.

Q2: What drivers of migration and mobility does the article study? 0 = 'other', 1 = 'climate', 2 = 'environment', 3 = 'economic', 4 = 'conflict', 5 = 'political', 6 = 'social', 7 = 'family'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q3: What is the overall sentiment of the article?:0 = 'neutral', 1 = 'negative', 2 = 'positive'. Answer with a number. Do not give a textual explanation.

Q4: What type of climate or environmental keywords are explicitly mentioned?:  0 = 'none', 1 = 'algal blooms', 2 = 'infestation', 3 = 'infectious diseases', 4 = 'ocean acidification', 5 = 'sea ice', 6 = 'acid rain', 7 = 'drought', 8 = 'cold wave', 9 = 'heat wave', 10 = 'glacial', 11 = 'wildfire', 12 = 'air pollution', 13 = 'biodiversity loss', 14 = 'coastal erosion', 15 = 'land degradation', 16 = 'deforestation', 17 = 'desertification', 18 = 'water pollution', 19 = 'diebacks', 20 = 'permafrost loss', 21 = 'sand mining', 22 = 'sea level rise', 23 = 'earthquake', 24 = 'tsunami', 25 = 'volcanic', 26 = 'flood', 27 = 'avalanche', 28 = 'landslide', 29 = 'downburst', 30 = 'thunderstorm', 31 = 'sandstorm', 32 = 'haze', 33 = 'storm', 34 = 'cyclone', 35 = 'blizzard', 36 = 'hail', 37 = 'snow', 38 = 'tornado', 39 = 'wind', 40 = 'hurricane', 41 = 'typhoon', 42 = 'other'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q5: What discipline does the article belong to?: 0 = 'other', 1 = 'social science', 2 = 'natural science', 3 = 'arts and humanities', 4 = 'multidiscipline and interdiscipline'. Answer with a number. Do not give a textual explanation.

Q6: Does the article apply quantitative and/or statistical analysis?: 0 = 'no', 1 = 'yes'. Answer with a number. Do not give a textual explanation.

Use the following template: 

Q1 = [];
Q2 = [];
Q3 = [];
Q4 = [];
Q5 = [];
Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:
Q1 = [0];
Q2 = [];
Q3 = [];
Q4 = [];
Q5 = [1];
Q6 = [1].
Validity of the Food Insecurity Experience Scale (FIES) for Use in League of Arab States (LAS) and Characteristics of Food Insecure Individuals by the Human Development Index (HDI)
Background: The Food Insecurity Experience Scale (FIES) is a UN FAO Voices of the Hungry (FAO-VoH) experiential metric of food insecurity (FI). It was pilot tested in some countries but not in Arab speaking ones and validated using global data. Yet, its psychometric properties may vary in the League of Arab States (LAS) due to cultural and linguistic differences. Objectives: 1) assess the validity of FIES for use in the LAS region, 2) determine the prevalence of FI, by gender, age group, and the human development index (HDI), and 3) examine sociodemographic characteristics of severe FI individuals. Methods: To assess the psychometric properties of FIES, Rasch modeling was applied to the 2014-2015 Gallop World Poll (GWP) in the LAS. Prevalence and characteristics of severely FI individuals were assessed using the 2014-2017 GWP data of 62,261 respondents. Results: Overall, FIES met the Rasch model assumptions of equal discrimination and conditional independence. Infit statistics for FIES items, in most LAS countries, were <1.3, indicating good internal validity. In Syria and Sudan, the item worried about not having enough food to eat had infits >1.3. Outfit statistics >2.0, indicating erratic responses, were noted in 26% of the LAS countries. Significant correlations were found (>= 0.4) between items in Algeria, Tunisia, and Lebanon. The overall prevalence of severe FI was 15.7%. At highest risk were those aged >= 50 y compared with younger adults (16.5% versus 15.5%, respectively, P <0.02), women compared with men (17.6% versus 14.1%, respectively, P <0.0001), and those in countries with low HDI compared with high HDI (24.9% versus 8.3%, respectively, P <0.0001). Conclusions: Overall, FIES is valid for measuring FI in the LAS. Cognitive testing of items with high outfit statistics and omission of correlated ones may improve the scale. Populations vulnerable to severe FI include older adults and women. These populations should be examined further.