<|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:"Exploring reasons for ethnic disparities in diet- and lifestyle-related chronic disease for Asian sub-groups in New Zealand: a scoping exercise."
Abstract:"Objectives: The current study aimed to explore if the impact of various risk factors for chronic disease differed for people of Chinese, Indian and New Zealand European and Other (NZEO) ethnicities.Design: Data analysed for this paper was extracted from the 2003-04 and the 2006-07 NZ Health surveys for adults aged 25-70 which used a cross-sectional survey design. Data from both the survey waves were combined and all statistical analysis was done using SAS version 9.2 or 9.3. Ethnicity of participants was coded using a priority-based classification system as (1) Indian, (2) Chinese, (3) Other Asian, (4) NZEO, (5) Maori and (6) Pacific. Only data for Indians, Chinese and NZEO were used for the current study. Prevalence estimates and 95% confidence intervals for chronic disease and the associated risk factors were generated to describe the sample. Logistic regression analysis was used to examine whether the difference in the change in risk of chronic disease with different exposures was different according to ethnicity.Results: Higher deprivation resulted in increased risk of chronic disease in Indian and Chinese males but not in NZEO males (p =.03). There was a weak evidence for a differing effect of physical activity (p=.10) on chronic disease with the protective effect not seen in Indian or Chinese participants.Conclusion: The results of the current study indicate that some factors such as socio-economic deprivation and physical activity may impact differently on the prevalence of chronic disease according to ethnicity. The authors recommend further investigation of these factors using improved and innovative methodology and high-quality ethnicity data to better understand the factors underpinning ethnic disparities in disease prevalence among Asian sub-groups.."
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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 = [1];
Q2 = [3];
Q3 = [];
Q4 = [0];
Q5 = [1];
Q6 = [1].
Exploring reasons for ethnic disparities in diet- and lifestyle-related chronic disease for Asian sub-groups in New Zealand: a scoping exercise
Objectives: The current study aimed to explore if the impact of various risk factors for chronic disease differed for people of Chinese, Indian and New Zealand European and Other (NZEO) ethnicities.Design: Data analysed for this paper was extracted from the 2003-04 and the 2006-07 NZ Health surveys for adults aged 25-70 which used a cross-sectional survey design. Data from both the survey waves were combined and all statistical analysis was done using SAS version 9.2 or 9.3. Ethnicity of participants was coded using a priority-based classification system as (1) Indian, (2) Chinese, (3) Other Asian, (4) NZEO, (5) Maori and (6) Pacific. Only data for Indians, Chinese and NZEO were used for the current study. Prevalence estimates and 95% confidence intervals for chronic disease and the associated risk factors were generated to describe the sample. Logistic regression analysis was used to examine whether the difference in the change in risk of chronic disease with different exposures was different according to ethnicity.Results: Higher deprivation resulted in increased risk of chronic disease in Indian and Chinese males but not in NZEO males (p =.03). There was a weak evidence for a differing effect of physical activity (p=.10) on chronic disease with the protective effect not seen in Indian or Chinese participants.Conclusion: The results of the current study indicate that some factors such as socio-economic deprivation and physical activity may impact differently on the prevalence of chronic disease according to ethnicity. The authors recommend further investigation of these factors using improved and innovative methodology and high-quality ethnicity data to better understand the factors underpinning ethnic disparities in disease prevalence among Asian sub-groups.