<|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:"Symptom profiles of late-life anxiety and depression: The influence of migration, religion and loneliness."
Abstract:"Objective To examine (1) clinically relevant anxiety with comorbid depression in an older population, and the presentation of subthreshold symptoms; (2) to assess anxiety and levels of comorbid depression associated with migration, religion, loneliness and long-term illness. Methods Analysis of Wave 1 of The Irish Longitudinal Study on Ageing (TILDA) (2009-2011). Latent class analysis (LCA) was used to define indicative diagnoses of anxiety and depression. We then assessed associations between sociodemographic and socioeconomic factors, past migration, religious practice, social network, loneliness and long-term illness. Results For those with clinically relevant anxiety, LCA derived three classes of self-reported depression: low, subthreshold and high. Approximately 19% were comorbid, and a further 37% reported subthreshold depression. Compared to those with low/no symptoms of depression, those classed as comorbid were more likely to be male, had lower education levels, had spent more time abroad, lower religious attendance, a limited social network, were lonelier and had a long-term life-limiting illness. Those with subthreshold levels of depression reported a more restricted social network and more moderate levels of loneliness. Conclusion Findings support the actuality of comorbidity of both disorders. Consequently, government health strategy on detecting and managing social engagement, loneliness, and psychological disorders in older people may require a more granulated approach.."
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: 

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Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:

Symptom profiles of late-life anxiety and depression: The influence of migration, religion and loneliness
Objective To examine (1) clinically relevant anxiety with comorbid depression in an older population, and the presentation of subthreshold symptoms; (2) to assess anxiety and levels of comorbid depression associated with migration, religion, loneliness and long-term illness. Methods Analysis of Wave 1 of The Irish Longitudinal Study on Ageing (TILDA) (2009-2011). Latent class analysis (LCA) was used to define indicative diagnoses of anxiety and depression. We then assessed associations between sociodemographic and socioeconomic factors, past migration, religious practice, social network, loneliness and long-term illness. Results For those with clinically relevant anxiety, LCA derived three classes of self-reported depression: low, subthreshold and high. Approximately 19% were comorbid, and a further 37% reported subthreshold depression. Compared to those with low/no symptoms of depression, those classed as comorbid were more likely to be male, had lower education levels, had spent more time abroad, lower religious attendance, a limited social network, were lonelier and had a long-term life-limiting illness. Those with subthreshold levels of depression reported a more restricted social network and more moderate levels of loneliness. Conclusion Findings support the actuality of comorbidity of both disorders. Consequently, government health strategy on detecting and managing social engagement, loneliness, and psychological disorders in older people may require a more granulated approach.