<|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:"Food insecurity in Venezuelan migrants in Trinidad and Tobago using the food insecurity experience scale."
Abstract:"Economic, political, humanitarian and health crises in Venezuela have resulted in mass out migration -thousands of Venezuelans emigrated to Trinidad and Tobago. However, little is known about their food security status in the host country. This study assessed the food security status among Venezuelan migrants and asylum seekers in Trinidad and Tobago and tested the validity of the online application of the food insecurity experience scale (FIES), a tool to measure food insecurity, in a small group. This convenience, cross-sectional study applied an online questionnaire to 433 Venezuelan migrants in Trinidad and Tobago in 2020. Snowball sampling was used to connect to migrants based on their access to locally-based NGO service providers, and organizations directly connected to the Venezuelan migrant community. Researchers applied the 12-month reference period to the FIES to measure food insecurity at the individual level. Descriptive analyses, Rasch modeling and binary logistic regression were conducted. Overall, 61.9% of respondents displayed behaviors characterized as severely food insecure. Significant differences in food security status were observed when categories of employment status (p = 0.032) and paying rent (p = 0.005) were considered. There were greater proportions of unemployed individuals who were severely food insecure (67.6%) compared to those who were employed (56.7%). There were greater proportions of individuals paying rent who were severely food insecure (62.6%) compared to those who were not paying rent (50.0%). Logistic regression with adjusted odds ratios and 95% confidence intervals revealed that food insecurity was less likely among migrants who were employed (OR 0.112, 95% CI 0.016-0.763) relative to those who were not employed, while food insecurity was more likely among migrants who were paying rent (OR 7.325, 95% CI 1.965-27.312) relative to those not paying rent. The FIES was consistent in assessing food security status. These findings provide a rapid assessment that can be used to galvanize international, national and community-level stakeholders to devise and target responses to assist migrants experiencing food insecurity.."
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 = [];
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Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:
Q1 = [1];
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Food insecurity in Venezuelan migrants in Trinidad and Tobago using the food insecurity experience scale
Economic, political, humanitarian and health crises in Venezuela have resulted in mass out migration -thousands of Venezuelans emigrated to Trinidad and Tobago. However, little is known about their food security status in the host country. This study assessed the food security status among Venezuelan migrants and asylum seekers in Trinidad and Tobago and tested the validity of the online application of the food insecurity experience scale (FIES), a tool to measure food insecurity, in a small group. This convenience, cross-sectional study applied an online questionnaire to 433 Venezuelan migrants in Trinidad and Tobago in 2020. Snowball sampling was used to connect to migrants based on their access to locally-based NGO service providers, and organizations directly connected to the Venezuelan migrant community. Researchers applied the 12-month reference period to the FIES to measure food insecurity at the individual level. Descriptive analyses, Rasch modeling and binary logistic regression were conducted. Overall, 61.9% of respondents displayed behaviors characterized as severely food insecure. Significant differences in food security status were observed when categories of employment status (p = 0.032) and paying rent (p = 0.005) were considered. There were greater proportions of unemployed individuals who were severely food insecure (67.6%) compared to those who were employed (56.7%). There were greater proportions of individuals paying rent who were severely food insecure (62.6%) compared to those who were not paying rent (50.0%). Logistic regression with adjusted odds ratios and 95% confidence intervals revealed that food insecurity was less likely among migrants who were employed (OR 0.112, 95% CI 0.016-0.763) relative to those who were not employed, while food insecurity was more likely among migrants who were paying rent (OR 7.325, 95% CI 1.965-27.312) relative to those not paying rent. The FIES was consistent in assessing food security status. These findings provide a rapid assessment that can be used to galvanize international, national and community-level stakeholders to devise and target responses to assist migrants experiencing food insecurity.