Help me modify the below json data to have only one correct option rather than having two equally correct options in some of the entries so that the users would not be confused. Modify the explanations too accordingly, avoid using lables to answer choices in the explanation as we would be randomizing the options while presenting the questions and give me the complete json code.

[
  {
    "id": 1233,
    "type": "chartsquestion",
    "question": "The United Nations Environmental Programme (UNEP) has been tracking global renewable energy investments across different sectors. Their latest report presents data on investments in solar, wind, and hydroelectric power over the past decade. The data shows significant variations in investment patterns among these three renewable energy sources.\n\nAnalysts are particularly interested in understanding the trends and implications of these investments. They want to determine which renewable energy source has seen the most consistent growth and might be the most promising for future development. Additionally, they are curious about how the investment patterns might reflect technological advancements, policy changes, or shifts in global energy priorities.\n\nBased on the data provided in the chart, which of the following conclusions is best supported regarding the investment trends in renewable energy sources?",
    "options": [
      "Wind power has seen the most consistent year-over-year growth in investments.",
      "Solar power shows the most dramatic increase in investments over the five-year period.",
      "Hydroelectric power investments have remained relatively stable compared to other sources.",
      "Investments in wind power have outpaced those in solar power each year."
    ],
    "answer": "Solar power shows the most dramatic increase in investments over the five-year period.",
    "explanation": "The correct answer is 'Solar power shows the most dramatic increase in investments over the five-year period.' This conclusion is best supported by the data presented in the chart.\n\nLet's analyze each option based on the provided data:\n\n1. 'Wind power has seen the most consistent year-over-year growth in investments.' This is incorrect. Wind power investments show inconsistent growth patterns:\n - 2019 to 2020: 3.26% increase\n - 2020 to 2021: 3.15% decrease\n - 2021 to 2022: 2.97% decrease\n - 2022 to 2023: 9.92% increase\n The fluctuations indicate that wind power investments have not seen consistent growth.\n\n2. 'Solar power shows the most dramatic increase in investments over the five-year period.' This is correct. Solar power investments have increased significantly:\n - 2019: $131.1 billion\n - 2023: $337.4 billion\n - Total increase: 157.36% over five years\n - Year-over-year growth rates:\n 2019 to 2020: 13.35%\n 2020 to 2021: 38.56%\n 2021 to 2022: 49.59%\n 2022 to 2023: 9.55%\n This represents the most dramatic and consistent increase among the three energy sources.\n\n3. 'Hydroelectric power investments have remained relatively stable compared to other sources.' While hydroelectric investments show less dramatic changes compared to solar, it's not the best-supported conclusion. Hydroelectric investments do show growth:\n - 2019: $15.6 billion\n - 2023: $20.2 billion\n - Total increase: 29.49% over five years\n - Year-over-year changes vary from -4.68% to 13.50%\n\n4. 'Investments in wind power have outpaced those in solar power each year.' This is incorrect. Solar investments surpassed wind from 2020 onwards:\n - 2020: Solar $148.6 billion vs Wind $142.7 billion\n - 2021: Solar $205.9 billion vs Wind $138.2 billion\n - 2022: Solar $308.0 billion vs Wind $134.1 billion\n - 2023: Solar $337.4 billion vs Wind $147.4 billion\n\nAdditional insights:\n- Total investments over the five-year period:\n Solar: $1,131.0 billion\n Wind: $700.6 billion\n Hydroelectric: $87.7 billion\n- Solar power shows the highest total investment and the most significant growth.\n- Wind power investments have remained relatively stable, with a slight overall increase.\n- Hydroelectric power, while showing growth, has the lowest total investment among the three.\n\nThe data clearly demonstrates that solar power has experienced the most dramatic growth in investments, with substantial year-over-year increases. This trend suggests that solar power might be seen as the most promising renewable energy source for future development, possibly due to technological advancements, decreasing costs, or favorable policy environments.\n\nThis question tests the ability to analyze trends over time, compare different data sets, calculate percentage changes, and draw evidence-based conclusions from numerical data - all important skills for interpreting and using data in real-world contexts.",
    "quiztype": "rwcomprehension",
    "chartData": {
      "type": "table",
      "data": {
        "title": "Global Investments in Renewable Energy Sources (Billions of Dollars)",
        "headers": ["Year", "Solar", "Wind", "Hydroelectric"],
        "rows": [
          {"Year": "2019", "Solar": "131.1", "Wind": "138.2", "Hydroelectric": "15.6"},
          {"Year": "2020", "Solar": "148.6", "Wind": "142.7", "Hydroelectric": "17.1"},
          {"Year": "2021", "Solar": "205.9", "Wind": "138.2", "Hydroelectric": "16.3"},
          {"Year": "2022", "Solar": "308.0", "Wind": "134.1", "Hydroelectric": "18.5"},
          {"Year": "2023", "Solar": "337.4", "Wind": "147.4", "Hydroelectric": "20.2"}
        ]
      }
    }
  },
  {
    "id": 1234,
    "type": "chartsquestion",
    "question": "The global smartphone market has been highly competitive over the past few years, with several major brands vying for market dominance. Market research firms have been tracking the market share of these brands to understand consumer preferences and industry trends.\n\nAnalysts are particularly interested in identifying which brands have shown consistent growth or decline, and how market dynamics have shifted over time. They also want to understand how factors such as technological innovations, pricing strategies, and brand loyalty might be influencing these trends.\n\nBased on the data provided in the chart, which of the following conclusions is best supported regarding the global smartphone market share trends?",
    "options": [
      "Samsung has maintained the highest market share throughout the five-year period.",
      "Apple shows the most consistent year-over-year growth in market share.",
      "Huawei experienced the most dramatic decline in market share over the five-year period.",
      "Xiaomi has overtaken all other brands except Samsung and Apple by 2023."
    ],
    "answer": "Huawei experienced the most dramatic decline in market share over the five-year period.",
    "explanation": "The correct answer is 'Huawei experienced the most dramatic decline in market share over the five-year period.' This conclusion is best supported by the data presented in the table.\n\nLet's analyze each option:\n\n1. 'Samsung has maintained the highest market share throughout the five-year period.' This is incorrect. While Samsung does have the highest share in most years, Apple surpassed it in 2023 with 20.1% compared to Samsung's 19.4%.\n\n2. 'Apple shows the most consistent year-over-year growth in market share.' This is incorrect. Apple's market share fluctuates, decreasing from 2019 to 2020, then increasing from 2020 to 2023, but not consistently every year.\n\n3. 'Huawei experienced the most dramatic decline in market share over the five-year period.' This is correct. Huawei's market share dropped significantly from 17.0% in 2019 to 2.4% in 2023, the largest decrease among all brands.\n\n4. 'Xiaomi has overtaken all other brands except Samsung and Apple by 2023.' While Xiaomi did show growth, this statement is not entirely accurate. In 2023, Xiaomi (12.5%) is behind Oppo (13.2%) as well as Samsung and Apple.\n\nThe data clearly shows that Huawei experienced the most dramatic change, with a sharp decline in market share from 17.0% in 2019 to 2.4% in 2023. This trend likely reflects significant challenges faced by the company, possibly due to external factors such as trade restrictions.\n\nThis question tests the ability to analyze trends over time, compare different data sets, and identify the most significant changes in a competitive market landscape.",
    "quiztype": "rwcomprehension",
    "chartData": {
      "type": "table",
      "data": {
        "title": "Global Smartphone Market Share (%)",
        "headers": ["Brand", "2019", "2020", "2021", "2022", "2023"],
        "rows": [
          {"Brand": "Samsung", "2019": "21.6", "2020": "19.5", "2021": "20.1", "2022": "21.6", "2023": "19.4"},
          {"Brand": "Apple", "2019": "13.0", "2020": "12.5", "2021": "15.9", "2022": "18.8", "2023": "20.1"},
          {"Brand": "Huawei", "2019": "17.0", "2020": "14.1", "2021": "8.4", "2022": "4.3", "2023": "2.4"},
          {"Brand": "Xiaomi", "2019": "8.9", "2020": "10.7", "2021": "12.5", "2022": "13.1", "2023": "12.5"},
          {"Brand": "Oppo", "2019": "8.6", "2020": "8.7", "2021": "9.5", "2022": "9.0", "2023": "13.2"}
        ]
      }
    }
  },
  {
    "id": 1235,
    "type": "chartsquestion",
    "question": "Climate scientists and policymakers have been closely monitoring global CO2 emissions from various sectors to understand the main contributors to climate change and to develop effective mitigation strategies. The data collected over the past five years shows the CO2 emissions from five major sectors: Energy, Industry, Agriculture, Transportation, and Buildings.\n\nResearchers are particularly interested in identifying which sectors have shown the most significant changes in emissions and how these trends might reflect the effectiveness of current climate policies or technological advancements. They also want to understand which sectors might require more focused attention in future climate action plans.\n\nBased on the data provided in the chart, which of the following conclusions is best supported regarding the trends in global CO2 emissions by sector?",
    "options": [
      "The Energy sector has consistently been the largest contributor to CO2 emissions throughout the five-year period.",
      "The Transportation sector shows the most significant decrease in emissions over the five-year period.",
      "Emissions from the Agriculture sector have remained relatively stable compared to other sectors.",
      "The Buildings sector has overtaken the Industry sector in emissions by 2023."
    ],
    "answer": "The Energy sector has consistently been the largest contributor to CO2 emissions throughout the five-year period.",
    "explanation": "The correct answer is 'The Energy sector has consistently been the largest contributor to CO2 emissions throughout the five-year period.' This conclusion is best supported by the data presented in the table.\n\nLet's analyze each option:\n\n1. 'The Energy sector has consistently been the largest contributor to CO2 emissions throughout the five-year period.' This is correct. The Energy sector has the highest emissions in each year from 2019 to 2023, ranging from 33.1 to 35.2 billion metric tons of CO2.\n\n2. 'The Transportation sector shows the most significant decrease in emissions over the five-year period.' This is incorrect. While Transportation emissions do decrease from 8.5 in 2019 to 7.8 in 2023, this is not the most significant change. The Industry sector, for example, shows a larger decrease from 12.5 to 11.3 over the same period.\n\n3. 'Emissions from the Agriculture sector have remained relatively stable compared to other sectors.' While this statement is somewhat true, as Agriculture emissions show less variation compared to other sectors, it's not the best-supported conclusion given the other options and the primary trend in the data.\n\n4. 'The Buildings sector has overtaken the Industry sector in emissions by 2023.' This is incorrect. In 2023, the Industry sector still has higher emissions (11.3) compared to the Buildings sector (8.9).\n\nThe data clearly shows that the Energy sector has been the largest contributor to CO2 emissions throughout the five-year period, with a significant gap between its emissions and those of other sectors. This trend suggests that the Energy sector might require particular attention in climate mitigation strategies.\n\nThis question tests the ability to compare data across different categories over time, identify consistent trends, and draw evidence-based conclusions from numerical data.",
    "quiztype": "rwcomprehension",
    "chartData": {
      "type": "table",
      "data": {
        "title": "Global CO2 Emissions by Sector (Billion Metric Tons)",
        "headers": ["Sector", "2019", "2020", "2021", "2022", "2023"],
        "rows": [
          {"Sector": "Energy", "2019": "33.1", "2020": "31.5", "2021": "33.8", "2022": "34.7", "2023": "35.2"},
          {"Sector": "Industry", "2019": "12.5", "2020": "11.8", "2021": "12.2", "2022": "11.9", "2023": "11.3"},
          {"Sector": "Agriculture", "2019": "5.3", "2020": "5.2", "2021": "5.4", "2022": "5.3", "2023": "5.5"},
          {"Sector": "Transportation", "2019": "8.5", "2020": "7.2", "2021": "7.6", "2022": "7.9", "2023": "7.8"},
          {"Sector": "Buildings", "2019": "8.7", "2020": "8.5", "2021": "8.8", "2022": "9.1", "2023": "8.9"}
        ]
      }
    }
  },
  {
    "id": 1236,
    "type": "chartsquestion",
    "question": "Education researchers and policymakers have been tracking global literacy rates across different regions to understand progress in education and identify areas that need more support. The data collected over the past five years shows literacy rates for five major world regions: North America, Europe, Asia, Africa, and South America.\n\nAnalysts are particularly interested in identifying which regions have shown the most significant improvements in literacy rates and how these trends might reflect the effectiveness of educational policies or socio-economic factors. They also want to understand which regions might require more focused attention and resources to improve literacy rates.\n\nBased on the data provided in the chart, which of the following conclusions is best supported regarding the trends in global literacy rates by region?",
    "options": [
      "North America has maintained the highest literacy rate throughout the five-year period.",
      "Africa shows the most significant increase in literacy rates over the five-year period.",
      "Asia's literacy rate has surpassed that of South America by 2023.",
      "Europe's literacy rate has remained relatively stable compared to other regions."
    ],
    "answer": "Africa shows the most significant increase in literacy rates over the five-year period.",
    "explanation": "The correct answer is 'Africa shows the most significant increase in literacy rates over the five-year period.' This conclusion is best supported by the data presented in the table.\n\nLet's analyze each option:\n\n1. 'North America has maintained the highest literacy rate throughout the five-year period.' This is incorrect. While North America does have high literacy rates, Europe consistently shows slightly higher rates throughout the period.\n\n2. 'Africa shows the most significant increase in literacy rates over the five-year period.' This is correct. Africa's literacy rate increased from 66.7% in 2019 to 72.9% in 2023, an increase of 6.2 percentage points, which is the largest increase among all regions.\n\n3. 'Asia's literacy rate has surpassed that of South America by 2023.' This is incorrect. In 2023, South America's literacy rate (94.5%) is still higher than Asia's (92.8%).\n\n4. 'Europe's literacy rate has remained relatively stable compared to other regions.' While this statement is somewhat true, as Europe's literacy rate shows less variation compared to regions like Africa, it's not the best-supported conclusion given the other options and the primary trend in the data.\n\nThe data clearly shows that Africa has experienced the most significant improvement in literacy rates over the five-year period, with a consistent year-over-year increase. This trend suggests that educational initiatives in Africa might be having a positive impact, although there is still room for improvement to reach the levels of other regions.\n\nThis question tests the ability to compare data across different categories over time, identify the most significant changes, and draw evidence-based conclusions from numerical data.",
    "quiztype": "rwcomprehension",
    "chartData": {
      "type": "table",
      "data": {
        "title": "Global Literacy Rates by Region (%)",
        "headers": ["Region", "2019", "2020", "2021", "2022", "2023"],
        "rows": [
          {"Region": "North America", "2019": "96.1", "2020": "96.3", "2021": "96.5", "2022": "96.7", "2023": "96.9"},
          {"Region": "Europe", "2019": "97.2", "2020": "97.4", "2021": "97.5", "2022": "97.7", "2023": "97.8"},
          {"Region": "Asia", "2019": "90.1", "2020": "90.8", "2021": "91.5", "2022": "92.2", "2023": "92.8"},
          {"Region": "Africa", "2019": "66.7", "2020": "68.2", "2021": "69.8", "2022": "71.4", "2023": "72.9"},
          {"Region": "South America", "2019": "93.1", "2020": "93.5", "2021": "93.8", "2022": "94.2", "2023": "94.5"}
        ]
      }
    }
  },
  {
    "id": 1237,
    "type": "chartsquestion",
    "question": "In response to the global pandemic and subsequent economic recovery efforts, central banks worldwide have been adjusting interest rates. The data shows monthly interest rate changes for five major economies over the past 18 months.\n\nEconomists are particularly interested in understanding how different countries have responded to economic challenges and inflationary pressures. They want to identify which economies have been most aggressive in their monetary policy and how these decisions might impact global economic recovery.\n\nBased on the data provided in the chart, which of the following conclusions is best supported regarding the trends in interest rate adjustments across these major economies?",
    "options": [
      "The United States has consistently maintained the highest interest rates throughout the period.",
      "The European Union shows the most gradual and steady increase in interest rates.",
      "Japan has kept its interest rates relatively stable compared to other economies.",
      "The United Kingdom demonstrates the most volatile interest rate changes."
    ],
    "answer": "Japan has kept its interest rates relatively stable compared to other economies.",
    "explanation": "The correct answer is 'Japan has kept its interest rates relatively stable compared to other economies.' This conclusion is best supported by the data presented in the table.\n\nLet's analyze each option:\n\n1. 'The United States has consistently maintained the highest interest rates throughout the period.' This is incorrect. While the US does have high rates towards the end of the period, it doesn't consistently have the highest rates throughout.\n\n2. 'The European Union shows the most gradual and steady increase in interest rates.' This is not entirely accurate. The EU does show an increase, but it's not the most gradual or steady compared to other economies.\n\n3. 'Japan has kept its interest rates relatively stable compared to other economies.' This is correct. Japan's interest rates remain at -0.1% throughout the entire 18-month period, showing no change at all.\n\n4. 'The United Kingdom demonstrates the most volatile interest rate changes.' While the UK does show significant changes, it's not necessarily the most volatile when compared to the changes seen in the US or EU.\n\nThe data clearly shows that among all the economies represented, Japan's interest rates remained constant at -0.1% for the entire period. This stability stands in stark contrast to the more dynamic changes seen in other major economies, reflecting Japan's long-standing policy of maintaining very low interest rates to stimulate economic growth.\n\nThis question tests the ability to compare trends across different categories over time, identify consistent patterns, and draw evidence-based conclusions from numerical data in the context of global economic policies.",
    "quiztype": "rwcomprehension",
    "chartData": {
      "type": "table",
      "data": {
        "title": "Monthly Interest Rates for Major Economies (%)",
        "headers": ["Month", "USA", "EU", "Japan", "UK", "Canada"],
        "rows": [
          {"Month": "Jan 2022", "USA": "0.25", "EU": "0.00", "Japan": "-0.10", "UK": "0.25", "Canada": "0.25"},
          {"Month": "Apr 2022", "USA": "0.50", "EU": "0.00", "Japan": "-0.10", "UK": "0.75", "Canada": "1.00"},
          {"Month": "Jul 2022", "USA": "2.50", "EU": "0.50", "Japan": "-0.10", "UK": "1.25", "Canada": "2.50"},
          {"Month": "Oct 2022", "USA": "3.25", "EU": "1.25", "Japan": "-0.10", "UK": "2.25", "Canada": "3.75"},
          {"Month": "Jan 2023", "USA": "4.50", "EU": "2.00", "Japan": "-0.10", "UK": "3.50", "Canada": "4.50"},
          {"Month": "Apr 2023", "USA": "5.00", "EU": "3.00", "Japan": "-0.10", "UK": "4.25", "Canada": "4.50"},
          {"Month": "Jun 2023", "USA": "5.25", "EU": "3.50", "Japan": "-0.10", "UK": "5.00", "Canada": "4.75"}
        ]
      }
    }
  },
  {
    "id": 1238,
    "type": "chartsquestion",
    "question": "The rapid development and deployment of artificial intelligence (AI) technologies have sparked intense debate about their potential impact on various job sectors. A recent study has tracked the estimated percentage of jobs at high risk of AI automation across different industries over the past three years.\n\nPolicymakers and industry leaders are keen to understand which sectors are most vulnerable to AI disruption and how quickly the landscape is changing. This information is crucial for developing strategies to mitigate potential job losses and to identify areas where reskilling and upskilling initiatives are most urgently needed.\n\nBased on the data provided in the chart, which of the following conclusions is best supported regarding the trends in AI's potential impact on job sectors?",
    "options": [
      "The healthcare sector shows the highest risk of job automation across all years.",
      "The finance industry demonstrates the most rapid increase in automation risk.",
      "Manufacturing jobs have remained relatively stable in terms of automation risk.",
      "The education sector shows the lowest risk of AI automation throughout the period."
    ],
    "answer": "The finance industry demonstrates the most rapid increase in automation risk.",
    "explanation": "The correct answer is 'The finance industry demonstrates the most rapid increase in automation risk.' This conclusion is best supported by the data presented in the table.\n\nLet's analyze each option:\n\n1. 'The healthcare sector shows the highest risk of job automation across all years.' This is incorrect. While healthcare does show increasing risk, it does not have the highest percentages across all years.\n\n2. 'The finance industry demonstrates the most rapid increase in automation risk.' This is correct. The finance sector shows the most dramatic increase, from 15% in 2021 to 45% in 2023, a 30 percentage point increase over just three years.\n\n3. 'Manufacturing jobs have remained relatively stable in terms of automation risk.' This is not accurate. Manufacturing shows a notable increase from 30% to 40% over the three-year period.\n\n4. 'The education sector shows the lowest risk of AI automation throughout the period.' While education does have lower percentages compared to some sectors, it's not consistently the lowest across all years.\n\nThe data clearly shows that the finance industry has experienced the most rapid and significant increase in estimated job automation risk. This trend likely reflects the increasing capabilities of AI in handling complex financial tasks, data analysis, and decision-making processes traditionally performed by human professionals in the finance sector.\n\nThis question tests the ability to compare trends across different categories over a specific time period, identify the most significant changes, and draw evidence-based conclusions from numerical data in the context of technological disruption in the job market.",
    "quiztype": "rwcomprehension",
    "chartData": {
      "type": "table",
      "data": {
        "title": "Estimated Percentage of Jobs at High Risk of AI Automation by Industry",
        "headers": ["Industry", "2021", "2022", "2023"],
        "rows": [
          {"Industry": "Finance", "2021": "15%", "2022": "30%", "2023": "45%"},
          {"Industry": "Healthcare", "2021": "10%", "2022": "15%", "2023": "25%"},
          {"Industry": "Manufacturing", "2021": "30%", "2022": "35%", "2023": "40%"},
          {"Industry": "Retail", "2021": "20%", "2022": "25%", "2023": "35%"},
          {"Industry": "Education", "2021": "5%", "2022": "10%", "2023": "15%"}
        ]
      }
    }
  },
  {
    "id": 1239,
    "type": "chartsquestion",
    "question": "In light of growing concerns about climate change and energy security, many countries have been investing heavily in renewable energy sources. The data shows the percentage of electricity generated from renewable sources for five major economies over the past decade, measured at two-year intervals.\n\nEnvironmental scientists and policymakers are particularly interested in understanding which countries have made the most significant progress in transitioning to renewable energy and how recent global events, such as the COVID-19 pandemic and geopolitical tensions, might have influenced these trends.\n\nBased on the data provided in the chart, which of the following conclusions is best supported regarding the trends in renewable energy adoption across these major economies?",
    "options": [
      "Germany has consistently maintained the highest percentage of renewable energy throughout the decade.",
      "The United States shows the most rapid increase in renewable energy adoption in recent years.",
      "China demonstrates the most significant overall increase in renewable energy percentage from 2013 to 2023.",
      "India's renewable energy adoption has remained relatively stagnant compared to other countries."
    ],
    "answer": "China demonstrates the most significant overall increase in renewable energy percentage from 2013 to 2023.",
    "explanation": "The correct answer is 'China demonstrates the most significant overall increase in renewable energy percentage from 2013 to 2023.' This conclusion is best supported by the data presented in the table.\n\nLet's analyze each option:\n\n1. 'Germany has consistently maintained the highest percentage of renewable energy throughout the decade.' While Germany does have high percentages, it's not consistently the highest throughout the entire period.\n\n2. 'The United States shows the most rapid increase in renewable energy adoption in recent years.' The US does show increases, but they're not necessarily the most rapid compared to other countries, especially China.\n\n3. 'China demonstrates the most significant overall increase in renewable energy percentage from 2013 to 2023.' This is correct. China's renewable energy percentage increased from 20% in 2013 to 55% in 2023, a 35 percentage point increase, which is the largest among the countries shown.\n\n4. 'India's renewable energy adoption has remained relatively stagnant compared to other countries.' This is not accurate. India shows a notable increase from 15% in 2013 to 40% in 2023.\n\nThe data clearly shows that China has made the most dramatic progress in increasing its share of electricity generated from renewable sources over the decade. This trend likely reflects China's massive investments in renewable energy technologies, particularly solar and wind power, as part of its efforts to combat air pollution and reduce carbon emissions.\n\nThis question tests the ability to analyze long-term trends across different categories, identify the most significant changes over an extended period, and draw evidence-based conclusions from numerical data in the context of global efforts to address climate change.",
    "quiztype": "rwcomprehension",
    "chartData": {
      "type": "table",
      "data": {
        "title": "Percentage of Electricity Generated from Renewable Sources",
        "headers": ["Country", "2013", "2015", "2017", "2019", "2021", "2023"],
        "rows": [
          {"Country": "China", "2013": "20%", "2015": "25%", "2017": "35%", "2019": "40%", "2021": "50%", "2023": "55%"},
          {"Country": "USA", "2013": "13%", "2015": "15%", "2017": "18%", "2019": "22%", "2021": "25%", "2023": "30%"},
          {"Country": "Germany", "2013": "25%", "2015": "32%", "2017": "38%", "2019": "42%", "2021": "45%", "2023": "50%"},
          {"Country": "India", "2013": "15%", "2015": "18%", "2017": "20%", "2019": "25%", "2021": "35%", "2023": "40%"},
          {"Country": "Brazil", "2013": "30%", "2015": "35%", "2017": "40%", "2019": "45%", "2021": "48%", "2023": "52%"}
        ]
      }
    }
  },
  {
    "id": 1240,
    "type": "chartsquestion",
    "question": "The International Coffee Organization has been tracking global coffee consumption patterns across different regions. Their latest report presents data on per capita coffee consumption in kilograms for five major world regions over the past five years. This data provides insights into changing consumer preferences and cultural shifts in beverage consumption.\n\nMarket analysts are particularly interested in understanding regional trends and their implications for the global coffee industry. They want to identify which regions show the most potential for market growth and how these consumption patterns might reflect economic development, westernization of diets, or changes in work culture.\n\nBased on the data provided in the chart, which of the following conclusions is best supported regarding the trends in global coffee consumption by region?",
    "options": [
      "Europe has maintained the highest per capita coffee consumption throughout the five-year period.",
      "Asia shows the most significant percentage increase in coffee consumption over the five-year period.",
      "North America's coffee consumption has remained relatively stable compared to other regions.",
      "Africa has surpassed South America in per capita coffee consumption by 2023."
    ],
    "answer": "Asia shows the most significant percentage increase in coffee consumption over the five-year period.",
    "explanation": "The correct answer is 'Asia shows the most significant percentage increase in coffee consumption over the five-year period.' This conclusion is best supported by the data presented in the table.\n\nLet's analyze each option:\n\n1. 'Europe has maintained the highest per capita coffee consumption throughout the five-year period.' This is correct, but not the most significant trend. Europe's consumption remains the highest, ranging from 6.8 to 7.2 kg per capita.\n\n2. 'Asia shows the most significant percentage increase in coffee consumption over the five-year period.' This is correct and the most notable trend. Asia's consumption increased from 1.3 kg in 2019 to 2.1 kg in 2023, a 61.5% increase, which is the largest percentage growth among all regions.\n\n3. 'North America's coffee consumption has remained relatively stable compared to other regions.' This is somewhat true but not the most significant observation. North America's consumption shows a slight increase from 4.5 to 4.8 kg over the five years.\n\n4. 'Africa has surpassed South America in per capita coffee consumption by 2023.' This is incorrect. In 2023, Africa's consumption (1.1 kg) remains lower than South America's (5.1 kg).\n\nThe data clearly shows that Asia has experienced the most significant growth in coffee consumption, with a consistent year-over-year increase. This trend suggests that the Asian market might offer the most potential for future growth in the coffee industry, possibly due to factors such as increasing westernization of diets, rising disposable incomes, or changing work cultures that embrace coffee consumption.\n\nThis question tests the ability to compare data across different categories over time, calculate percentage changes, identify the most significant trends, and draw evidence-based conclusions from numerical data.",
    "quiztype": "rwcomprehension",
    "chartData": {
      "type": "table",
      "data": {
        "title": "Global Per Capita Coffee Consumption by Region (kg/person/year)",
        "headers": ["Region", "2019", "2020", "2021", "2022", "2023"],
        "rows": [
          {"Region": "Europe", "2019": "6.8", "2020": "6.9", "2021": "7.0", "2022": "7.1", "2023": "7.2"},
          {"Region": "North America", "2019": "4.5", "2020": "4.6", "2021": "4.6", "2022": "4.7", "2023": "4.8"},
          {"Region": "South America", "2019": "4.8", "2020": "4.9", "2021": "5.0", "2022": "5.0", "2023": "5.1"},
          {"Region": "Asia", "2019": "1.3", "2020": "1.5", "2021": "1.7", "2022": "1.9", "2023": "2.1"},
          {"Region": "Africa", "2019": "0.8", "2020": "0.9", "2021": "0.9", "2022": "1.0", "2023": "1.1"}
        ]
      }
    }
  },
  {
    "id": 1241,
    "type": "chartsquestion",
    "question": "The World Health Organization has been tracking the prevalence of major non-communicable diseases (NCDs) across different age groups globally. Their latest report presents data on the percentage of people affected by five common NCDs: cardiovascular diseases, cancer, chronic respiratory diseases, diabetes, and mental health disorders.\n\nHealth policymakers are particularly interested in understanding how these diseases affect different age groups and how the prevalence changes across the lifespan. This information is crucial for developing targeted prevention strategies, allocating healthcare resources, and planning long-term public health initiatives.\n\nBased on the data provided in the chart, which of the following conclusions is best supported regarding the prevalence of non-communicable diseases across different age groups?",
    "options": [
      "Mental health disorders show the highest prevalence across all age groups.",
      "The prevalence of cardiovascular diseases increases most dramatically with age.",
      "Cancer rates remain relatively stable across all age groups compared to other NCDs.",
      "Diabetes shows the lowest prevalence in the youngest age group but increases significantly in older age groups."
    ],
    "answer": "The prevalence of cardiovascular diseases increases most dramatically with age.",
    "explanation": "The correct answer is 'The prevalence of cardiovascular diseases increases most dramatically with age.' This conclusion is best supported by the data presented in the table.\n\nLet's analyze each option:\n\n1. 'Mental health disorders show the highest prevalence across all age groups.' This is incorrect. While mental health disorders have high prevalence in younger age groups (18-29: 25%, 30-44: 22%), they are surpassed by cardiovascular diseases in older age groups (60-74: 38%, 75+: 45%).\n\n2. 'The prevalence of cardiovascular diseases increases most dramatically with age.' This is correct. Cardiovascular diseases show the most significant increase from the youngest to the oldest age group:\n - 18-29: 5%\n - 30-44: 12%\n - 45-59: 25%\n - 60-74: 38%\n - 75+: 45%\n This represents a 40 percentage point increase from the youngest to the oldest age group, the largest increase among all NCDs.\n\n3. 'Cancer rates remain relatively stable across all age groups compared to other NCDs.' This is incorrect. Cancer rates show a notable increase with age:\n - 18-29: 2%\n - 30-44: 5%\n - 45-59: 12%\n - 60-74: 20%\n - 75+: 25%\n While the increase is not as dramatic as cardiovascular diseases, it's still significant.\n\n4. 'Diabetes shows the lowest prevalence in the youngest age group but increases significantly in older age groups.' While this statement is partially true (diabetes has the lowest prevalence in the 18-29 age group at 1%), it's not the most significant trend in the data. The increase in diabetes prevalence (from 1% to 20%) is less dramatic than the increase in cardiovascular diseases.\n\nThe data clearly shows that cardiovascular diseases demonstrate the most dramatic increase in prevalence with age, rising from 5% in the 18-29 age group to 45% in the 75+ age group. This 40 percentage point increase is the largest among all the NCDs presented in the data.\n\nThis question tests the ability to compare trends across different categories and age groups, identify the most significant changes, and draw evidence-based conclusions from tabular data.",
    "quiztype": "rwcomprehension",
    "chartData": {
      "type": "table",
      "data": {
        "title": "Prevalence of Non-Communicable Diseases by Age Group (%)",
        "headers": ["Disease", "18-29", "30-44", "45-59", "60-74", "75+"],
        "rows": [
          {"Disease": "Cardiovascular diseases", "18-29": "5", "30-44": "12", "45-59": "25", "60-74": "38", "75+": "45"},
          {"Disease": "Cancer", "18-29": "2", "30-44": "5", "45-59": "12", "60-74": "20", "75+": "25"},
          {"Disease": "Chronic respiratory diseases", "18-29": "8", "30-44": "10", "45-59": "15", "60-74": "22", "75+": "28"},
          {"Disease": "Diabetes", "18-29": "1", "30-44": "5", "45-59": "12", "60-74": "18", "75+": "20"},
          {"Disease": "Mental health disorders", "18-29": "25", "30-44": "22", "45-59": "18", "60-74": "15", "75+": "12"}
        ]
      }
    }
  },
  {
    "id": 1242,
    "type": "chartsquestion",
    "question": "A global health organization has been tracking the prevalence of mental health disorders across different age groups in various countries. The data shows the percentage of people diagnosed with anxiety disorders in five countries over the past five years.\n\nResearchers are particularly interested in understanding how cultural, economic, and social factors might influence the prevalence and diagnosis of anxiety disorders across different age groups and nations. They want to explore whether there are common trends across countries or if certain nations show unique patterns that might reflect specific societal changes or healthcare practices.\n\nBased on the data provided in the chart, which of the following conclusions best demonstrates a critical analysis of the trends in anxiety disorder prevalence across different age groups and countries?",
    "options": [
      "All countries show a consistent increase in anxiety disorder prevalence across all age groups over the five-year period.",
      "The 18-29 age group consistently has the highest prevalence of anxiety disorders across all countries and years.",
      "Country E demonstrates the most significant overall increase in anxiety disorder prevalence, suggesting potential societal or healthcare system changes.",
      "The data reveals a complex interplay of factors affecting anxiety disorder prevalence, with varying trends across age groups and countries."
    ],
    "answer": "The data reveals a complex interplay of factors affecting anxiety disorder prevalence, with varying trends across age groups and countries.",
    "explanation": "The correct answer is 'The data reveals a complex interplay of factors affecting anxiety disorder prevalence, with varying trends across age groups and countries.' This conclusion best demonstrates a critical analysis of the trends presented in the data.\n\nLet's analyze each option:\n\n1. 'All countries show a consistent increase in anxiety disorder prevalence across all age groups over the five-year period.' This is incorrect. While some countries and age groups show increases, the trends are not consistent across all countries and age groups. For example, Country A shows a decrease in prevalence for the 60+ age group from 9.2% in 2019 to 8.8% in 2023.\n\n2. 'The 18-29 age group consistently has the highest prevalence of anxiety disorders across all countries and years.' This is not universally true. While the 18-29 age group often has high prevalence rates, it's not consistently the highest across all countries and years. For instance, in Country E, the 30-44 age group has higher rates in some years (e.g., 16.0% vs. 17.2% for 18-29 in 2023).\n\n3. 'Country E demonstrates the most significant overall increase in anxiety disorder prevalence, suggesting potential societal or healthcare system changes.' While Country E does show notable increases, particularly in younger age groups (e.g., 18-29 group increasing from 12.8% in 2019 to 17.2% in 2023), this statement oversimplifies the complex patterns observed across different countries and age groups.\n\n4. 'The data reveals a complex interplay of factors affecting anxiety disorder prevalence, with varying trends across age groups and countries.' This is the most accurate conclusion based on the data. We observe:\n - Different trends across countries (e.g., overall increases in Countries B and E, more stable rates in Country C)\n - Varying patterns across age groups within countries (e.g., larger increases in younger age groups in some countries)\n - Inconsistent trends over time (some age groups and countries show increases, others decreases or stability)\n\nFor example:\n- Country A's 60+ group shows a slight decrease (9.2% to 8.8%) while its 18-29 group increases (15.2% to 17.1%).\n- Country C shows relatively stable rates across all age groups (e.g., 18-29 group only increasing from 16.8% to 17.3% over five years).\n- Country E shows significant increases across all age groups, with the most dramatic in younger groups (18-29 increasing from 12.8% to 17.2%).\n\nThis conclusion acknowledges the complexity of the data and suggests that multiple factors may be influencing anxiety disorder prevalence. It avoids oversimplification and encourages further investigation into the specific cultural, economic, and social factors that might explain these varied trends.\n\nThis question tests the ability to analyze complex data across multiple variables (countries, age groups, and time), identify nuanced patterns, and draw evidence-based conclusions that acknowledge the intricacy of real-world health trends.",
    "quiztype": "rwcomprehension",
    "chartData": {
      "type": "table",
      "data": {
        "title": "Prevalence of Anxiety Disorders by Country and Age Group (%)",
        "headers": ["Country", "Age Group", "2019", "2020", "2021", "2022", "2023"],
        "rows": [
          {"Country": "A", "Age Group": "18-29", "2019": "15.2", "2020": "16.0", "2021": "16.5", "2022": "16.8", "2023": "17.1"},
          {"Country": "A", "Age Group": "30-44", "2019": "13.8", "2020": "14.2", "2021": "14.5", "2022": "14.7", "2023": "14.9"},
          {"Country": "A", "Age Group": "45-59", "2019": "11.5", "2020": "11.7", "2021": "11.8", "2022": "11.9", "2023": "12.0"},
          {"Country": "A", "Age Group": "60+", "2019": "9.2", "2020": "9.1", "2021": "9.0", "2022": "8.9", "2023": "8.8"},
          {"Country": "B", "Age Group": "18-29", "2019": "14.5", "2020": "15.2", "2021": "16.0", "2022": "16.8", "2023": "17.5"},
          {"Country": "B", "Age Group": "30-44", "2019": "13.2", "2020": "13.8", "2021": "14.5", "2022": "15.2", "2023": "15.8"},
          {"Country": "B", "Age Group": "45-59", "2019": "11.0", "2020": "11.5", "2021": "12.0", "2022": "12.5", "2023": "13.0"},
          {"Country": "B", "Age Group": "60+", "2019": "8.5", "2020": "8.8", "2021": "9.2", "2022": "9.5", "2023": "9.8"},
          {"Country": "C", "Age Group": "18-29", "2019": "16.8", "2020": "17.0", "2021": "17.1", "2022": "17.2", "2023": "17.3"},
          {"Country": "C", "Age Group": "30-44", "2019": "15.5", "2020": "15.6", "2021": "15.7", "2022": "15.8", "2023": "15.9"},
          {"Country": "C", "Age Group": "45-59", "2019": "13.2", "2020": "13.3", "2021": "13.4", "2022": "13.5", "2023": "13.6"},
          {"Country": "C", "Age Group": "60+", "2019": "10.5", "2020": "10.6", "2021": "10.7", "2022": "10.8", "2023": "10.9"},
          {"Country": "D", "Age Group": "18-29", "2019": "13.5", "2020": "14.0", "2021": "14.2", "2022": "14.5", "2023": "14.8"},
          {"Country": "D", "Age Group": "30-44", "2019": "12.2", "2020": "12.5", "2021": "12.7", "2022": "12.9", "2023": "13.1"},
          {"Country": "D", "Age Group": "45-59", "2019": "10.0", "2020": "10.2", "2021": "10.3", "2022": "10.4", "2023": "10.5"},
          {"Country": "D", "Age Group": "60+", "2019": "7.8", "2020": "7.9", "2021": "8.0", "2022": "8.1", "2023": "8.2"},
          {"Country": "E", "Age Group": "18-29", "2019": "12.8", "2020": "13.5", "2021": "14.5", "2022": "15.8", "2023": "17.2"},
          {"Country": "E", "Age Group": "30-44", "2019": "11.5", "2020": "12.2", "2021": "13.2", "2022": "14.5", "2023": "16.0"},
          {"Country": "E", "Age Group": "45-59", "2019": "9.2", "2020": "9.8", "2021": "10.5", "2022": "11.2", "2023": "12.0"},
          {"Country": "E", "Age Group": "60+", "2019": "7.0", "2020": "7.4", "2021": "7.9", "2022": "8.5", "2023": "9.2"}
        ]
      }
    }
  }
  ]