FACTOID # 9: Sick people is Switzerland stay in hospital for longer than the people of any other nation - almost 10 days, on average. Switzerland also has the world's highest number of hospital beds per capita.
 
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Correlations > Health Statistics > Drug access

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Correlations between Health > Drug access ...

Variable Strength
...and  Agriculture > Area > Sorghum (inverse) 71% [plot | correlate | graph]
...and  Crime > Bribery victims (inverse) 53% [plot | correlate | graph]
...and  Labor > Total work time > Females (inverse) 52% [plot | correlate | graph]
...and  Agriculture > Yield > Rice 51% [plot | correlate | graph]
...and  Economy > Growth competitiveness score 48% [plot | correlate | graph]
...and  Economy > Technology index 48% [plot | correlate | graph]
...and  Media > Mobile phones 46% [plot | correlate | graph]
...and  Education > Pupils reaching grade 5 45% [plot | correlate | graph]
...and  Economy > Macroeconomic environment index 45% [plot | correlate | graph]
...and  Economy > Technological achievement 45% [plot | correlate | graph]
...and  Environment > Environmental agreement compliance 43% [plot | correlate | graph]
...and  Economy > Public institution index 41% [plot | correlate | graph]
...and  Education > Female teachers > Lower secondary 40% [plot | correlate | graph]
...and  People > Male population > Age 85-89 > % of the total 40% [plot | correlate | graph]
...and  People > Total population > Age 85-89 > % of the total 40% [plot | correlate | graph]
...and  Agriculture > Area > Rye (inverse) 40% [plot | correlate | graph]
...and  Agriculture > Yield > Sorghum 39% [plot | correlate | graph]
...and  Education > Average years of schooling of adults 39% [plot | correlate | graph]
...and  Health > Intestinal diseases death rate (inverse) 38% [plot | correlate | graph]
...and  Education > Proportion of 15 year-olds in secondary education 38% [plot | correlate | graph]
...and  Labor > Total work time > Females over males (inverse) 38% [plot | correlate | graph]
...and  Health > Tobacco > Cigarette consumption 37% [plot | correlate | graph]
...and  People > Gender development 37% [plot | correlate | graph]
...and  Education > Proportion of 16 year-olds in secondary education 37% [plot | correlate | graph]
...and  Economy > GDP per capita in 1973 37% [plot | correlate | graph]
...and  Economy > GDP per capita in 1820 37% [plot | correlate | graph]
...and  Health > Probability of not reaching 60 (inverse) 37% [plot | correlate | graph]
...and  Economy > Innovation 37% [plot | correlate | graph]
...and  People > Female population > Age 85-89 > % of the total 36% [plot | correlate | graph]
...and  Education > Primary teacher age > Proportion aged 40-49 36% [plot | correlate | graph]
...and  People > Persons per room (inverse) 36% [plot | correlate | graph]
...and  Media > Phone subscribers 35% [plot | correlate | graph]
...and  Agriculture > Exports to USA > Onions (inverse) 35% [plot | correlate | graph]
...and  Economy > Informal economy (inverse) 34% [plot | correlate | graph]
...and  Economy > Human Development Index 34% [plot | correlate | graph]
...and  People > Male population > Age 90-94 > % of the total 34% [plot | correlate | graph]
...and  Agriculture > Area > Sunflowerseed (inverse) 33% [plot | correlate | graph]
...and  Environment > Ecological footprint 33% [plot | correlate | graph]
...and  Health > Dependency ratio per 100 (inverse) 33% [plot | correlate | graph]
...and  People > Women > Maternal mortality ratio adjusted (inverse) 33% [plot | correlate | graph]
...and  Health > Healthy life expectancy at birth, years > Males 32% [plot | correlate | graph]
...and  Health > Probability of dying before 5 > Females (inverse) 32% [plot | correlate | graph]
...and  Education > Teacher qualifications > Years experience > Age 13 (inverse) 32% [plot | correlate | graph]
...and  Transportation > Motor vehicles 32% [plot | correlate | graph]
...and  Health > Healthy life expectancy at birth, years > Total population 32% [plot | correlate | graph]
...and  People > Total population > Age 90-94 > % of the total 32% [plot | correlate | graph]
...and  Agriculture > Value added (inverse) 31% [plot | correlate | graph]
...and  Education > Primary teacher age > Proportion aged 30-39 (inverse) 31% [plot | correlate | graph]
...and  Health > Life expectancy at birth, years > Males 31% [plot | correlate | graph]
...and  Health > Probability of reaching 65 > Male 31% [plot | correlate | graph]
Average: 39%

About Correlations:

A correlation is a statistical measure of similarity between at least two given sets of data. NationMaster's correlations compare two variables from our database and reveal statistical relationships between them. The percentages you see represent the strength (or likelihood) that a change in the topic variable is matched by a change in the listed variables below it. But remember: These correlations do not imply causation, that is, one does not necessarily cause the other. Also, not all variables contain all countries, rather subsets of countries matched together.

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NOTES:

  • Outliers have been removed only where they are outside 3 standard deviations of the mean.
  • Only variable pairs where at least 15 countries match for each have been considered.
  • Strength is given by the correlation coefficient (R squared). It is the fraction of variation in Y that can be attributed to the variation in X. 100% signifies a perfect fit (R squared of 1). The top 50 such stats are displayed


DEFINITION: Population with access to essential drugs 2000. The data on access to essential drugs are based on statistical estimates received from World Health Organization (WHO) country and regional offices and regional advisers and through the World Drug Situation Survey carried out in 1998-99. These estimates represent the best information available to the WHO Department of Essential Drugs and Medicines Policy to date and are currently being validated by WHO member states. The department assigns the estimates to four groupings: very low access (0-49%), low access (50-79%), medium access (80-94%) and good access (95-100%). These groupings, used here in presenting the data, are often employed by the WHO in interpreting the data, as the actual estimates may suggest a higher level of accuracy than the data afford. b.

SOURCE: WHO (World Health Organization). 2001. Correspondence on access to essential drugs. Department of Essential Drugs and Medecines Policy. February. Geneva

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