You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 retails
【Schema】
# Table: customer
[
(c_custkey:INTEGER, Primary Key, Examples: [1, 2, 3]),
(c_mktsegment:TEXT, Examples: [BUILDING, MACHINERY, FURNITURE]),
(c_nationkey:INTEGER, Examples: [8, 16, 11]),
(c_name:TEXT, Examples: [Customer#000000001, Customer#000000002, Customer#000000003]),
(c_address:TEXT, Examples: [KwX3hMHjZ6, ioUn,eqTTXOdo, YddJqmIdouNT9Yj]),
(c_phone:TEXT, Examples: [937-241-3198, 906-965-7556, 328-750-7603]),
(c_acctbal:REAL, Examples: [3560.03, 7550.21, -926.96]),
(c_comment:TEXT)
]
# Table: supplier
[
(s_suppkey:INTEGER, Primary Key, Examples: [1, 2, 3]),
(s_nationkey:INTEGER, Examples: [13, 5, 22]),
(s_comment:TEXT),
(s_name:TEXT, Examples: [Supplier#000000001, Supplier#000000002, Supplier#000000003]),
(s_address:TEXT, Examples: [,wWs4pnykQOFl8mgVCU8EZMXqZs1w]),
(s_phone:TEXT, Examples: [800-807-9579, 348-617-6055, 471-986-9888]),
(s_acctbal:REAL, Examples: [3082.86, 3009.73, 9159.78])
]
# Table: region
[
(r_regionkey:INTEGER, Primary Key, Examples: [0, 1, 2]),
(r_name:TEXT, Examples: [AFRICA, AMERICA, ASIA]),
(r_comment:TEXT)
]
# Table: orders
[
(o_orderdate:DATE, Examples: [1995-04-19]),
(o_orderkey:INTEGER, Primary Key, Examples: [1, 2, 3]),
(o_custkey:INTEGER, Examples: [73100, 92861, 44875]),
(o_orderpriority:TEXT, Examples: [4-NOT SPECIFIED, 1-URGENT, 5-LOW]),
(o_shippriority:INTEGER, Examples: [0]),
(o_clerk:TEXT, Examples: [Clerk#000000916, Clerk#000000373, Clerk#000000485]),
(o_orderstatus:TEXT, Examples: [P, O, F]),
(o_totalprice:REAL, Examples: [203198.56, 317719.99, 146674.98]),
(o_comment:TEXT)
]
# Table: part
[
(p_partkey:INTEGER, Primary Key, Examples: [1, 2, 3]),
(p_type:TEXT, Examples: [LARGE PLATED TIN]),
(p_size:INTEGER, Examples: [31, 4, 30]),
(p_brand:TEXT, Examples: [Brand#43, Brand#55, Brand#53]),
(p_name:TEXT, Examples: [burlywood plum powder puff mint]),
(p_container:TEXT, Examples: [LG BAG, LG CASE, WRAP CASE]),
(p_mfgr:TEXT, Examples: [Manufacturer#4, Manufacturer#5, Manufacturer#1]),
(p_retailprice:REAL, Examples: [901.0, 902.0, 903.0]),
(p_comment:TEXT, Examples: [blithely busy reque])
]
# Table: lineitem
[
(l_shipdate:DATE, Examples: [1995-08-16]),
(l_orderkey:INTEGER, Primary Key, Examples: [1, 2, 4]),
(l_discount:REAL, Examples: [0.1, 0.09, 0.02]),
(l_extendedprice:REAL, Examples: [58303.08, 16947.7, 63642.9]),
(l_suppkey:INTEGER, Examples: [6296, 8776, 3859]),
(l_quantity:INTEGER, Examples: [33, 10, 34]),
(l_returnflag:TEXT, Examples: [N, A, R]),
(l_partkey:INTEGER, Examples: [98768, 23771, 113858]),
(l_linestatus:TEXT, Examples: [O, F]),
(l_tax:REAL, Examples: [0.06, 0.08, 0.07]),
(l_commitdate:DATE, Examples: [1995-07-12]),
(l_receiptdate:DATE, Examples: [1995-09-14]),
(l_shipmode:TEXT, Examples: [RAIL, TRUCK, SHIP]),
(l_linenumber:INTEGER, Primary Key, Examples: [1, 2, 3]),
(l_shipinstruct:TEXT, Examples: [NONE, TAKE BACK RETURN, COLLECT COD]),
(l_comment:TEXT, Examples: [carefully bo])
]
# Table: nation
[
(n_nationkey:INTEGER, Primary Key, Examples: [0, 1, 2]),
(n_name:TEXT, Examples: [ALGERIA, ARGENTINA, BRAZIL]),
(n_regionkey:INTEGER, Examples: [0, 1, 3]),
(n_comment:TEXT)
]
# Table: partsupp
[
(ps_partkey:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ps_suppkey:INTEGER, Primary Key, Examples: [2, 2502, 5002]),
(ps_supplycost:REAL, Examples: [400.75, 702.61, 383.95]),
(ps_availqty:INTEGER, Examples: [1111, 3999, 7411]),
(ps_comment:TEXT)
]
【Foreign keys】
customer.c_nationkey=nation.n_nationkey
supplier.s_nationkey=nation.n_nationkey
orders.o_custkey=customer.c_custkey
lineitem.l_orderkey=orders.o_orderkey
lineitem.l_partkey=partsupp.ps_partkey
lineitem.l_suppkey=partsupp.ps_suppkey
nation.n_regionkey=region.r_regionkey
partsupp.ps_partkey=part.p_partkey
partsupp.ps_suppkey=supplier.s_suppkey

    【Question】
    Calculate the percentage of countries that belong to the American region. the American region refers to r_name = 'America'; percentage = divide(count(n_name where r_name = 'America'), count(n_name)) * 100%

    【Evidence】
    the American region refers to r_name = 'America'; percentage = divide(count(n_name where r_name = 'America'), count(n_name)) * 100%

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT CAST(SUM(IIF(T1.r_name = 'America', 1, 0)) AS REAL) * 100 / COUNT(T2.n_name) FROM region AS T1 INNER JOIN nation AS T2 ON T1.r_regionkey = T2.n_regionkey