nhanes.samp.adult <- structure(list(ID = c(63147L, 57165L, 69465L, 57313L, 56047L, 57056L, 54643L, 53095L, 67434L, 60273L, 58162L, 58284L, 62180L, 70881L, 60165L, 69896L, 67785L, 67285L, 69403L, 65620L, 67190L, 51912L, 71564L, 66522L, 60740L, 58845L, 70225L, 70702L, 62634L, 59541L, 55369L, 60321L, 67290L, 55590L, 63510L, 58543L, 62575L, 63297L, 56903L, 69767L, 71581L, 63445L, 69521L, 62720L, 59171L, 70064L, 60375L, 53154L, 60369L, 70251L, 58838L, 67627L, 58824L, 62415L, 55947L, 65133L, 64676L, 56715L, 66547L, 58972L, 52268L, 55436L, 67516L, 70196L, 55487L, 70358L, 70438L, 62229L, 57650L, 59453L, 56254L, 64514L, 58622L, 55709L, 62616L, 55567L, 55189L, 56900L, 58225L, 64336L, 67887L, 60152L, 54732L, 64803L, 61051L, 52152L, 67668L, 69097L, 61085L, 67118L, 71119L, 60854L, 66439L, 55676L, 63391L, 54939L, 55456L, 71093L, 63721L, 70581L, 58611L, 52120L, 67834L, 60186L, 67192L, 57267L, 55250L, 69170L, 51991L, 61582L, 62674L, 67897L, 57287L, 63560L, 70359L, 64882L, 62720L, 53526L, 69460L, 63288L, 58185L, 69207L, 69516L, 62301L, 69421L, 61964L, 61684L, 68440L, 64526L, 56723L, 53351L, 52265L, 51780L, 68301L, 61687L), SurveyYr = structure(c(2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L), .Label = c("2009_10", "2011_12"), class = "factor"), Gender = structure(c(2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L), .Label = c("female", "male"), class = "factor"), Age = c(41L, 48L, 50L, 74L, 27L, 26L, 41L, 52L, 56L, 39L, 32L, 72L, 35L, 23L, 49L, 49L, 38L, 70L, 61L, 25L, 36L, 27L, 25L, 46L, 26L, 63L, 25L, 26L, 68L, 49L, 40L, 38L, 25L, 26L, 56L, 39L, 24L, 50L, 24L, 56L, 36L, 21L, 74L, 58L, 74L, 38L, 21L, 55L, 38L, 43L, 62L, 25L, 59L, 27L, 75L, 47L, 56L, 29L, 65L, 42L, 29L, 57L, 47L, 37L, 23L, 44L, 42L, 31L, 26L, 26L, 59L, 31L, 52L, 59L, 37L, 40L, 64L, 31L, 41L, 31L, 67L, 42L, 36L, 35L, 44L, 70L, 70L, 31L, 51L, 33L, 36L, 61L, 48L, 26L, 70L, 30L, 25L, 50L, 22L, 63L, 48L, 25L, 33L, 34L, 55L, 56L, 24L, 51L, 35L, 39L, 33L, 71L, 33L, 40L, 80L, 65L, 58L, 62L, 50L, 58L, 69L, 30L, 74L, 23L, 68L, 80L, 25L, 46L, 49L, 28L, 27L, 25L, 54L, 59L, 57L), AgeDecade = structure(c(5L, 5L, 6L, 8L, 3L, 3L, 5L, 6L, 6L, 4L, 4L, 8L, 4L, 3L, 5L, 5L, 4L, 8L, 7L, 3L, 4L, 3L, 3L, 5L, 3L, 7L, 3L, 3L, 7L, 5L, 5L, 4L, 3L, 3L, 6L, 4L, 3L, 6L, 3L, 6L, 4L, 3L, 8L, 6L, 8L, 4L, 3L, 6L, 4L, 5L, 7L, 3L, 6L, 3L, 8L, 5L, 6L, 3L, 7L, 5L, 3L, 6L, 5L, 4L, 3L, 5L, 5L, 4L, 3L, 3L, 6L, 4L, 6L, 6L, 4L, 5L, 7L, 4L, 5L, 4L, 7L, 5L, 4L, 4L, 5L, 8L, 8L, 4L, 6L, 4L, 4L, 7L, 5L, 3L, 8L, 4L, 3L, 6L, 3L, 7L, 5L, 3L, 4L, 4L, 6L, 6L, 3L, 6L, 4L, 4L, 4L, 8L, 4L, 5L, NA, 7L, 6L, 7L, 6L, 6L, 7L, 4L, 8L, 3L, 7L, NA, 3L, 5L, 5L, 3L, 3L, 3L, 6L, 6L, 6L), .Label = c(" 0-9", " 10-19", " 20-29", " 30-39", " 40-49", " 50-59", " 60-69", " 70+"), class = "factor"), AgeMonths = c(NA, 586L, NA, 889L, 329L, 316L, 503L, 632L, NA, 472L, 391L, 868L, NA, NA, 596L, NA, NA, NA, NA, NA, NA, 332L, NA, NA, 313L, 760L, NA, NA, NA, 593L, 486L, 464L, NA, 322L, NA, 473L, NA, NA, 296L, NA, NA, NA, NA, NA, 897L, NA, 259L, 665L, 465L, NA, 748L, NA, 712L, NA, 910L, NA, NA, 356L, NA, 513L, 356L, 694L, NA, NA, 281L, NA, NA, NA, 321L, 320L, 714L, NA, 624L, 712L, NA, 489L, 777L, 380L, 499L, NA, NA, 515L, 440L, NA, 532L, 845L, NA, NA, 614L, NA, NA, 742L, NA, 318L, NA, 367L, 308L, NA, NA, NA, 587L, 300L, NA, 411L, NA, 683L, 296L, NA, 430L, 478L, NA, NA, 398L, NA, NA, NA, NA, 744L, NA, NA, 828L, NA, NA, NA, NA, NA, 304L, NA, NA, 342L, 325L, 307L, 658L, NA, 693L ), Race1 = structure(c(4L, 1L, 4L, 4L, 4L, 3L, 4L, 4L, 4L, 1L, 4L, 4L, 4L, 4L, 1L, 4L, 4L, 2L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 4L, 5L, 4L, 4L, 4L, 5L, 3L, 3L, 4L, 4L, 4L, 4L, 3L, 4L, 1L, 3L, 4L, 1L, 4L, 4L, 4L, 4L, 2L, 5L, 4L, 3L, 4L, 5L, 1L, 3L, 2L, 4L, 4L, 4L, 5L, 5L, 4L, 2L, 4L, 1L, 5L, 3L, 4L, 4L, 4L, 4L, 5L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 4L, 4L, 4L, 4L, 3L, 4L, 2L, 4L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 4L, 1L, 4L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 1L, 5L, 1L, 4L, 1L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L), .Label = c("Black", "Hispanic", "Mexican", "White", "Other"), class = "factor"), Race3 = structure(c(5L, NA, 5L, NA, NA, NA, NA, NA, 5L, NA, NA, NA, 5L, 5L, NA, 5L, 5L, 3L, 5L, 5L, 5L, NA, 5L, 5L, NA, NA, 5L, 5L, 5L, NA, NA, NA, 5L, NA, 5L, NA, 5L, 5L, NA, 6L, 4L, 4L, 5L, 5L, NA, 5L, NA, NA, NA, 4L, NA, 2L, NA, 5L, NA, 5L, 3L, NA, 5L, NA, NA, NA, 2L, 4L, NA, 5L, 5L, 5L, NA, NA, NA, 3L, NA, NA, 1L, NA, NA, NA, NA, 5L, 1L, NA, NA, 5L, NA, NA, 5L, 3L, NA, 5L, 5L, NA, 4L, NA, 3L, NA, NA, 5L, 5L, 5L, NA, NA, 5L, NA, 5L, NA, NA, 4L, NA, NA, 5L, 5L, NA, 5L, 5L, 5L, 5L, NA, 3L, 2L, NA, 2L, 5L, 2L, 5L, NA, NA, 5L, 5L, NA, NA, NA, NA, 5L, NA), .Label = c("Asian", "Black", "Hispanic", "Mexican", "White", "Other"), class = "factor"), Education = structure(c(4L, 3L, 5L, 5L, 2L, 3L, 5L, 2L, 5L, 2L, 4L, 5L, 5L, 5L, 3L, 3L, 2L, 5L, 5L, 5L, 5L, 2L, 3L, 5L, 2L, 2L, 5L, 3L, 2L, 3L, 5L, 5L, 4L, 5L, 4L, 4L, 4L, 5L, 5L, 4L, 3L, 4L, 4L, 5L, 3L, 3L, 5L, 4L, 5L, 3L, 4L, 5L, 3L, 4L, 3L, 5L, 4L, 4L, 5L, 1L, 4L, 1L, 4L, 1L, 4L, 4L, 5L, 5L, 5L, 5L, 2L, 2L, 3L, 3L, 1L, 3L, 4L, 3L, 5L, 2L, 4L, 5L, 3L, 4L, 5L, 4L, 4L, 2L, 4L, 4L, 4L, 3L, 3L, 4L, 4L, 5L, 3L, 3L, 3L, 2L, 5L, 2L, 4L, 4L, 4L, 4L, 5L, 1L, 4L, 5L, 5L, 5L, 4L, 3L, 4L, 5L, 5L, 5L, 1L, 5L, 2L, 3L, 4L, 2L, 4L, 4L, 5L, 4L, 5L, 1L, 5L, 5L, 5L, 3L, 3L), .Label = c("8th Grade", "9 - 11th Grade", "High School", "Some College", "College Grad"), class = "factor"), MaritalStatus = structure(c(3L, 3L, 1L, 6L, 4L, 4L, 3L, 4L, 3L, 3L, 3L, 3L, 3L, 4L, 3L, 4L, 3L, 6L, 1L, 4L, 3L, 3L, 3L, 3L, 2L, 6L, 3L, 3L, 3L, 1L, 3L, 3L, 4L, 3L, 3L, 3L, 3L, 3L, 4L, 1L, 3L, 4L, 3L, 3L, 3L, 1L, 4L, 4L, 3L, 3L, 3L, 4L, 6L, 3L, 3L, 3L, 2L, 3L, 3L, 1L, 4L, 1L, 4L, 4L, 2L, 1L, 3L, 3L, 3L, 2L, 1L, 2L, 3L, 3L, 3L, 3L, 1L, 3L, 3L, 2L, 3L, 3L, 2L, 3L, 4L, 1L, 6L, 3L, 3L, 1L, 3L, 3L, 4L, 4L, 3L, 3L, 2L, 2L, 4L, 3L, 5L, 3L, 4L, 4L, 3L, 3L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 3L, 4L, 3L, 3L, 2L, 3L, 2L, 2L, 2L, 4L, 3L, 1L, 3L), .Label = c("Divorced", "LivePartner", "Married", "NeverMarried", "Separated", "Widowed"), class = "factor"), HHIncome = structure(c(6L, 6L, 7L, 8L, 11L, 3L, 9L, 1L, 12L, 8L, 7L, 11L, 5L, 10L, 5L, 12L, 4L, 6L, 6L, 11L, 11L, 1L, 2L, 12L, 10L, 10L, 10L, 8L, 8L, 7L, 11L, 12L, 7L, 12L, 12L, 8L, NA, 11L, 7L, 7L, 10L, 1L, 6L, 12L, 7L, 7L, 6L, 1L, 12L, NA, 11L, 12L, 3L, 12L, NA, 3L, 10L, 10L, 12L, 6L, 12L, NA, 6L, 5L, 6L, 8L, 12L, 6L, 10L, 11L, 3L, 4L, 4L, 11L, 4L, 9L, NA, 7L, 12L, 7L, 11L, 12L, 4L, 6L, 11L, 9L, 5L, 3L, 12L, 6L, 12L, 10L, 7L, 12L, 7L, NA, 5L, 12L, 8L, 7L, 10L, NA, 8L, 8L, 8L, 3L, 10L, 10L, 7L, 7L, 6L, 12L, 6L, 7L, 11L, 11L, 12L, 12L, 10L, NA, 12L, 5L, 9L, NA, 7L, 4L, 8L, NA, 8L, 7L, 12L, 11L, 12L, 12L, 12L), .Label = c(" 0-4999", " 5000-9999", "10000-14999", "15000-19999", "20000-24999", "25000-34999", "35000-44999", "45000-54999", "55000-64999", "65000-74999", "75000-99999", "more 99999"), class = "factor"), HHIncomeMid = c(30000L, 30000L, 40000L, 50000L, 87500L, 12500L, 60000L, 2500L, 100000L, 50000L, 40000L, 87500L, 22500L, 70000L, 22500L, 100000L, 17500L, 30000L, 30000L, 87500L, 87500L, 2500L, 7500L, 100000L, 70000L, 70000L, 70000L, 50000L, 50000L, 40000L, 87500L, 100000L, 40000L, 100000L, 100000L, 50000L, NA, 87500L, 40000L, 40000L, 70000L, 2500L, 30000L, 100000L, 40000L, 40000L, 30000L, 2500L, 100000L, NA, 87500L, 100000L, 12500L, 100000L, NA, 12500L, 70000L, 70000L, 100000L, 30000L, 100000L, NA, 30000L, 22500L, 30000L, 50000L, 100000L, 30000L, 70000L, 87500L, 12500L, 17500L, 17500L, 87500L, 17500L, 60000L, NA, 40000L, 100000L, 40000L, 87500L, 100000L, 17500L, 30000L, 87500L, 60000L, 22500L, 12500L, 100000L, 30000L, 100000L, 70000L, 40000L, 100000L, 40000L, NA, 22500L, 100000L, 50000L, 40000L, 70000L, NA, 50000L, 50000L, 50000L, 12500L, 70000L, 70000L, 40000L, 40000L, 30000L, 100000L, 30000L, 40000L, 87500L, 87500L, 100000L, 100000L, 70000L, NA, 100000L, 22500L, 60000L, NA, 40000L, 17500L, 50000L, NA, 50000L, 40000L, 100000L, 87500L, 100000L, 100000L, 100000L), Poverty = c(1.4099999999999999, 1.3600000000000001, 2.1600000000000001, 4.1600000000000001, 3.5099999999999998, 0.39000000000000001, 2.3300000000000001, 0.050000000000000003, 5, 1.3500000000000001, 1.5900000000000001, 5, 0.87, 4.7599999999999998, 0.87, 2.8599999999999999, 1.21, 2.8900000000000001, 2.8599999999999999, 2.75, 4.5, 0.17000000000000001, 0.35999999999999999, 5, 3.1699999999999999, 4.46, 4.4199999999999999, 1.48, 3.0600000000000001, 1.9099999999999999, 3.3999999999999999, 4.9900000000000002, 0.089999999999999997, 5, 5, 1.6899999999999999, NA, 5, 3.8799999999999999, 1.97, 2.8199999999999998, 0.01, 2.04, 5, 2.29, 2.2000000000000002, 1.3600000000000001, 0.089999999999999997, 5, NA, 5, 5, 1.29, 5, NA, 0.93000000000000005, 3.6699999999999999, 2.8100000000000001, 5, 1.72, NA, NA, 1.47, 0.78000000000000003, 0, 4.4100000000000001, 5, 1.3100000000000001, 2.9500000000000002, 3.6899999999999999, 1.1100000000000001, 0.81000000000000005, 1.24, 4.2000000000000002, 0.68999999999999995, 2.7200000000000002, NA, 1.6699999999999999, 5, 1.21, 5, 5, 0.97999999999999998, 1.1599999999999999, 5, 5, 0.97999999999999998, 0.40000000000000002, 5, 1.3400000000000001, 5, 4.6699999999999999, 1.53, 4.5099999999999998, 1.1499999999999999, NA, 1.0900000000000001, 5, 2.4300000000000002, 2.8599999999999999, 3.8199999999999998, NA, 2.75, 1.3899999999999999, 2.7000000000000002, 0.81999999999999995, 3.1699999999999999, 2.9500000000000002, 1.5900000000000001, 1.22, 1.1599999999999999, 5, 0.96999999999999997, 1.1699999999999999, 5, 5, 5, 5, 2.4399999999999999, NA, 4.21, 1.52, 3.7400000000000002, NA, 2.6400000000000001, 1.55, 0.92000000000000004, NA, 1.95, 2.29, 5, 5, 5, 0.63, 5), HomeRooms = c(6L, 6L, 10L, 7L, 7L, 5L, 9L, 6L, 7L, 6L, 4L, 12L, 6L, 6L, 8L, 1L, 5L, 6L, 2L, 3L, 8L, 5L, 5L, 9L, 6L, 6L, 6L, 6L, 7L, 5L, 9L, 6L, 13L, 7L, 5L, 7L, 7L, 7L, 2L, 9L, 5L, 3L, 8L, 7L, 6L, 6L, 5L, 4L, 5L, 6L, 6L, 8L, 7L, 11L, 4L, 5L, 6L, 7L, 10L, 4L, 6L, 2L, 5L, 2L, 1L, 7L, 9L, 4L, 6L, 3L, 7L, 4L, 3L, 10L, 4L, 5L, 5L, 6L, 6L, 6L, 8L, 11L, 6L, 4L, 4L, 5L, 3L, 3L, 8L, 5L, 6L, 7L, 6L, 8L, 5L, 8L, 3L, 8L, 2L, 7L, 6L, 5L, 2L, 3L, 5L, 5L, 6L, 6L, 9L, 7L, 4L, 9L, 7L, 8L, 8L, 9L, 7L, 9L, 6L, 11L, 6L, 4L, 10L, 7L, 5L, 4L, 4L, 3L, 6L, 3L, 4L, 3L, 7L, 1L, 7L), HomeOwn = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 3L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 3L, 2L, 1L, 1L, 3L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L), .Label = c("Own", "Rent", "Other"), class = "factor"), Work = structure(c(2L, 2L, 2L, 2L, 3L, 3L, 3L, 2L, 3L, 3L, 2L, 2L, 3L, 3L, 2L, 3L, 2L, 3L, 3L, 3L, 3L, 2L, 2L, 3L, 3L, 2L, 3L, 3L, 2L, 2L, 3L, 3L, 2L, 3L, 3L, 3L, 2L, 3L, 3L, 2L, 3L, 1L, 2L, 3L, 2L, 3L, 3L, 2L, 2L, 3L, 3L, 3L, 2L, 3L, 3L, 2L, 3L, 3L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 3L, 1L, 2L, 3L, 3L, 3L, 1L, 3L, 3L, 3L, 2L, 3L, 3L, 2L, 3L, 3L, 2L, 3L, 2L, 3L, 3L, 2L, 3L, 3L, 2L, 3L, 3L, 3L, 1L, 3L, 3L, 2L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 3L, 2L, 3L, 3L, 3L, 3L, 3L, 2L, 3L, 2L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("Looking", "NotWorking", "Working"), class = "factor"), Weight = c(106.8, 77.400000000000006, 70.5, 61.700000000000003, 70.299999999999997, 92.599999999999994, 55.600000000000001, 82, 88.200000000000003, 119, 122.59999999999999, 69.400000000000006, 89, 78.799999999999997, 69.299999999999997, 74.599999999999994, 65.099999999999994, 89.700000000000003, 116.2, 57.399999999999999, 93.099999999999994, 95.900000000000006, 100.90000000000001, 71.299999999999997, 50.200000000000003, 101.09999999999999, 113.09999999999999, 65.299999999999997, 103.3, 112.09999999999999, 75.599999999999994, 96.400000000000006, 108.59999999999999, 49, 57.799999999999997, 105, 54.399999999999999, 94.200000000000003, 57.600000000000001, 125.09999999999999, 134.90000000000001, 59.399999999999999, 78.700000000000003, 73.799999999999997, 82.200000000000003, 74.299999999999997, 39.700000000000003, 76.900000000000006, 77.900000000000006, 72.799999999999997, 103.59999999999999, 112.7, 114.3, 76.400000000000006, 65.299999999999997, 79.099999999999994, 55.899999999999999, 103.09999999999999, 98.5, 59.100000000000001, 65.299999999999997, 71.900000000000006, 95.299999999999997, 87.799999999999997, 69.700000000000003, 59.5, 108.3, 84.099999999999994, 61.700000000000003, 68.299999999999997, 51.700000000000003, 53, 119.90000000000001, 85.400000000000006, 51.799999999999997, 90.299999999999997, 80.5, 86.5, 108.7, 98.5, 57, 89, 161.69999999999999, 99.700000000000003, 64.200000000000003, 92.900000000000006, 96.599999999999994, 79.400000000000006, 70.400000000000006, 81.5, 92.299999999999997, 104.5, 90.099999999999994, 69.099999999999994, 88.5, 58.700000000000003, 71.5, 78.5, 51.600000000000001, 66.599999999999994, 139.09999999999999, 102.40000000000001, 76.299999999999997, 84.299999999999997, 76.5, 57.299999999999997, 137.59999999999999, 78.400000000000006, 82.5, 62.200000000000003, 59.700000000000003, 44, 104.5, 98.900000000000006, 86.700000000000003, 91.900000000000006, 73.799999999999997, 95.099999999999994, 89.200000000000003, 93.599999999999994, 53.700000000000003, 187.5, 88.099999999999994, 101.90000000000001, 65.400000000000006, 51.700000000000003, 73.700000000000003, 80.700000000000003, 98.799999999999997, 75.599999999999994, 83.799999999999997, 69.200000000000003, 53.899999999999999, 107.59999999999999, 121.59999999999999), Length = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_ ), HeadCirc = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), Height = c(188.80000000000001, 168.19999999999999, 161.80000000000001, 158.09999999999999, 168.09999999999999, 165.80000000000001, 155.59999999999999, 156.40000000000001, 181.40000000000001, 178.09999999999999, 164.19999999999999, 166, 178.69999999999999, 174.69999999999999, 168.59999999999999, 177.09999999999999, 163.09999999999999, 156.59999999999999, 171.09999999999999, 160.69999999999999, 184.5, 158.19999999999999, 169.09999999999999, 162.59999999999999, 168.40000000000001, 163.80000000000001, 182.59999999999999, 181.09999999999999, 177.90000000000001, 180, 161.5, 163.59999999999999, 177.69999999999999, 156.59999999999999, 163.59999999999999, 176.40000000000001, 157.40000000000001, 175.5, 159.5, 166.09999999999999, 186.69999999999999, 140, 173.90000000000001, 168.09999999999999, 160.19999999999999, 153, 151.59999999999999, 184.59999999999999, 163, 166.5, 187.09999999999999, 172.90000000000001, 166.90000000000001, 169, 174.90000000000001, 163, 153.5, 173.30000000000001, 187.5, 170.5, 166.30000000000001, 156.90000000000001, 168.80000000000001, 168.5, 161.5, 168.80000000000001, 173.09999999999999, 171.40000000000001, 153.19999999999999, 175.09999999999999, 154.90000000000001, 153.90000000000001, 175.69999999999999, 188.19999999999999, 164, 179.90000000000001, 179.69999999999999, 182.09999999999999, 178.69999999999999, 179.59999999999999, 157.40000000000001, 185.19999999999999, 183, 185.09999999999999, 165.80000000000001, 180.09999999999999, 174.19999999999999, 166.19999999999999, 168.09999999999999, 161.80000000000001, 191.30000000000001, 164.30000000000001, 159.30000000000001, 174.19999999999999, 169.90000000000001, 168.59999999999999, 168.19999999999999, 169.19999999999999, 168.09999999999999, 154.5, 183, 159.09999999999999, 164.5, 182.30000000000001, 165.09999999999999, 171.19999999999999, 167.80000000000001, 152.30000000000001, 169.19999999999999, 182.80000000000001, 166.5, 160.59999999999999, 156.19999999999999, 178.19999999999999, 181.80000000000001, 182.40000000000001, 168.09999999999999, 170.59999999999999, 174.30000000000001, 165.19999999999999, 156.69999999999999, 164.80000000000001, 176.19999999999999, 175.59999999999999, 158.80000000000001, 164.30000000000001, 162.5, 177.90000000000001, 158.09999999999999, 174.30000000000001, 180.59999999999999, 184.40000000000001, 160.09999999999999, 181.59999999999999, 173.5), BMI = c(30, 27.359999999999999, 26.899999999999999, 24.68, 24.879999999999999, 33.689999999999998, 22.960000000000001, 33.520000000000003, 26.800000000000001, 37.520000000000003, 45.469999999999999, 25.190000000000001, 27.899999999999999, 25.800000000000001, 24.379999999999999, 23.800000000000001, 24.5, 36.600000000000001, 39.700000000000003, 22.199999999999999, 27.300000000000001, 38.32, 35.299999999999997, 27, 17.699999999999999, 37.68, 33.899999999999999, 19.899999999999999, 32.600000000000001, 34.600000000000001, 28.989999999999998, 36.020000000000003, 34.399999999999999, 19.98, 21.600000000000001, 33.740000000000002, 22, 30.600000000000001, 22.640000000000001, 45.299999999999997, 38.700000000000003, 30.300000000000001, 26, 26.100000000000001, 32.030000000000001, 31.699999999999999, 17.27, 22.57, 29.32, 26.300000000000001, 29.59, 37.700000000000003, 41.030000000000001, 26.699999999999999, 21.350000000000001, 29.800000000000001, 23.699999999999999, 34.329999999999998, 28, 20.329999999999998, 23.609999999999999, 29.210000000000001, 33.399999999999999, 30.899999999999999, 26.719999999999999, 20.899999999999999, 36.100000000000001, 28.600000000000001, 26.289999999999999, 22.280000000000001, 21.550000000000001, 22.399999999999999, 38.840000000000003, 24.109999999999999, 19.300000000000001, 27.899999999999999, 24.93, 26.09, 34.039999999999999, 30.5, 23, 25.949999999999999, 48.280000000000001, 29.100000000000001, 23.350000000000001, 28.640000000000001, 31.800000000000001, 28.699999999999999, 24.91, 31.100000000000001, 25.199999999999999, 38.710000000000001, 35.5, 22.77, 30.699999999999999, 20.649999999999999, 25.27, 27.399999999999999, 18.300000000000001, 27.899999999999999, 41.539999999999999, 40.450000000000003, 28.199999999999999, 25.370000000000001, 28.100000000000001, 19.550000000000001, 48.869999999999997, 33.799999999999997, 28.82, 18.609999999999999, 21.5, 17.100000000000001, 42.829999999999998, 31.100000000000001, 26.199999999999999, 27.600000000000001, 26.100000000000001, 32.68, 29.399999999999999, 34.299999999999997, 21.870000000000001, 69, 28.399999999999999, 33, 25.899999999999999, 19.149999999999999, 27.91, 25.5, 39.5, 24.879999999999999, 25.690000000000001, 20.350000000000001, 21.030000000000001, 32.600000000000001, 40.399999999999999), BMICatUnder20yrs = structure(c(NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_), .Label = c("UnderWeight", "NormWeight", "OverWeight", "Obese"), class = "factor"), BMI_WHO = structure(c(NA, 3L, 3L, 2L, 2L, 4L, 2L, 4L, 3L, 4L, 4L, 3L, 3L, 3L, 2L, 2L, 2L, 4L, 4L, 2L, 3L, 4L, 4L, 3L, 1L, 4L, 4L, 2L, 4L, 4L, 3L, 4L, 4L, 2L, 2L, 4L, 2L, 4L, 2L, 4L, 4L, 4L, 3L, 3L, 4L, 4L, 1L, 2L, 3L, 3L, 3L, 4L, 4L, 3L, 2L, 3L, 2L, 4L, 3L, 2L, 2L, 3L, 4L, 4L, 3L, 2L, 4L, 3L, 3L, 2L, 2L, 2L, 4L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 2L, 3L, 4L, 3L, 2L, 3L, 4L, 3L, 3L, 4L, 3L, 4L, 4L, 2L, 4L, 2L, 3L, 3L, 1L, 3L, 4L, 4L, 3L, 3L, 3L, 2L, 4L, 4L, 3L, 2L, 2L, 1L, 4L, 4L, 3L, 3L, 3L, 4L, 3L, 4L, 2L, 4L, 3L, 4L, 3L, 2L, 3L, 3L, 4L, 2L, 3L, 2L, 2L, 4L, 4L), .Label = c("12.0_18.5", "18.5_to_24.9", "25.0_to_29.9", "30.0_plus"), class = "factor"), Pulse = c(88L, 70L, 76L, 64L, 74L, 78L, 82L, 96L, 44L, 60L, 72L, 88L, 66L, 66L, 116L, 68L, 68L, 70L, NA, 78L, 60L, 98L, 96L, 60L, 92L, 62L, 80L, 76L, 70L, 88L, 60L, 78L, 80L, 66L, 64L, NA, 86L, 78L, 78L, 82L, 102L, 64L, 68L, 84L, 72L, 86L, 80L, 94L, 66L, 96L, 64L, 76L, 68L, 74L, 62L, 94L, 72L, 94L, 76L, 76L, 60L, 76L, 80L, 64L, 66L, 76L, 64L, 78L, 62L, 58L, 64L, 88L, 78L, 56L, 82L, 64L, 90L, 56L, 88L, 82L, 60L, 70L, 64L, 76L, 80L, 54L, 76L, 62L, 64L, 76L, 62L, 68L, 56L, 74L, 58L, 56L, 60L, 74L, 62L, 82L, 44L, 96L, 70L, 66L, NA, 50L, 82L, 80L, 80L, 72L, 80L, 64L, 98L, NA, 68L, 62L, 84L, 80L, 62L, 60L, 76L, 74L, 98L, 72L, 76L, 52L, 76L, 58L, 62L, 70L, 60L, 80L, 78L, 70L, 66L), BPSysAve = c(112L, 123L, 152L, 132L, 107L, 126L, 111L, 114L, 137L, 122L, 124L, 103L, 107L, 113L, 118L, 120L, 92L, 152L, NA, 103L, 129L, 92L, 124L, 110L, 111L, 106L, 112L, 123L, 130L, 95L, 124L, 118L, 125L, 98L, 111L, NA, 133L, 110L, 101L, 160L, 127L, 102L, 112L, 128L, 125L, 98L, 91L, 129L, 139L, 120L, 146L, 135L, 112L, 91L, 164L, 123L, 129L, 104L, 123L, 151L, 122L, 130L, 126L, 95L, 113L, 112L, 122L, 122L, 120L, 129L, 132L, 107L, 127L, 117L, 109L, 115L, 114L, 113L, 136L, 120L, 134L, 107L, 117L, 126L, 101L, 118L, 160L, 112L, 124L, 113L, 117L, 108L, 124L, 108L, 137L, 106L, 106L, 129L, 118L, 114L, 154L, 114L, 102L, 118L, NA, NA, 127L, 129L, 121L, 101L, 99L, 113L, 128L, NA, 129L, 130L, 128L, 107L, 133L, 169L, 130L, 108L, 134L, 118L, 138L, 152L, 113L, 93L, 136L, 109L, 110L, 107L, 131L, 202L, 124L), BPDiaAve = c(76L, 69L, 103L, 81L, 58L, 75L, 76L, 71L, 77L, 78L, 89L, 66L, 66L, 54L, 85L, 77L, 58L, 84L, NA, 74L, 66L, 66L, 78L, 79L, 61L, 70L, 86L, 74L, 73L, 70L, 82L, 78L, 95L, 65L, 67L, NA, 66L, 79L, 64L, 87L, 56L, 57L, 59L, 76L, 77L, 71L, 55L, 74L, 95L, 84L, 74L, 83L, 59L, 53L, 67L, 61L, 69L, 62L, 75L, 85L, 61L, 85L, 81L, 45L, 66L, 69L, 69L, 84L, 55L, 72L, 65L, 73L, 81L, 66L, 73L, 74L, 63L, 73L, 90L, 77L, 69L, 62L, 71L, 93L, 61L, 78L, 84L, 76L, 75L, 61L, 67L, 50L, 79L, 68L, 79L, 65L, 54L, 78L, 64L, 70L, 91L, 56L, 71L, 69L, NA, NA, 83L, 79L, 67L, 55L, 67L, 65L, 62L, NA, 68L, 83L, 76L, 77L, 75L, 71L, 21L, 72L, 68L, 54L, 75L, 68L, 66L, 66L, 79L, 71L, 62L, 62L, 69L, 99L, 66L), BPSys1 = c(114L, 128L, 144L, 146L, 106L, 126L, 116L, 116L, 134L, 124L, 128L, 106L, 108L, 116L, NA, 116L, 94L, 156L, NA, NA, 128L, 92L, NA, 118L, 108L, 112L, NA, 118L, 132L, 94L, 130L, 118L, 126L, 90L, 112L, NA, 130L, 112L, 100L, 160L, 126L, 104L, 114L, 122L, 122L, 98L, 96L, 120L, 144L, 114L, 146L, 132L, 106L, 98L, 168L, 116L, 126L, 114L, 136L, 150L, 122L, 126L, 130L, 94L, 104L, 114L, 126L, 126L, 126L, 128L, 134L, 114L, 130L, 116L, 100L, 112L, 116L, 108L, NA, 122L, 138L, 106L, 116L, 126L, 94L, 118L, 160L, 114L, 130L, 114L, 112L, 110L, 130L, 108L, 138L, 106L, 108L, 126L, 118L, 112L, 158L, 108L, 98L, 124L, NA, NA, 130L, 144L, 122L, 100L, 106L, 136L, 128L, NA, 132L, 132L, 122L, NA, 130L, 172L, 128L, 110L, 126L, 112L, 136L, 158L, 110L, 92L, 134L, 108L, 108L, 118L, 136L, 202L, 128L), BPDia1 = c(78L, 78L, 104L, 84L, 62L, 86L, 72L, 66L, 78L, 70L, 94L, 72L, 62L, 60L, NA, 74L, 60L, 90L, NA, NA, 70L, 66L, NA, 84L, 52L, 70L, NA, 68L, 74L, 74L, 84L, 76L, 100L, 60L, 62L, NA, 68L, 84L, 62L, 84L, 66L, 60L, 62L, 74L, 74L, 68L, 46L, 74L, 90L, 82L, 78L, 84L, 62L, 56L, 68L, 72L, 74L, 62L, 82L, 86L, 64L, 88L, 82L, 42L, 68L, 66L, 70L, 82L, 48L, 74L, 68L, 66L, 80L, 64L, 80L, 70L, 68L, 70L, NA, 76L, 66L, 72L, 72L, 92L, 62L, 78L, 86L, 72L, 72L, 68L, 54L, 52L, 76L, 68L, 80L, 58L, 64L, 78L, 64L, 72L, 90L, 56L, 74L, 74L, NA, NA, 84L, 78L, 74L, 52L, 70L, 64L, 66L, NA, 70L, 76L, 74L, NA, 76L, 80L, 42L, 62L, 64L, 44L, 82L, 68L, 60L, 70L, 78L, 72L, 64L, 64L, 62L, 108L, 70L), BPSys2 = c(114L, 126L, 150L, 130L, 108L, 130L, 112L, 116L, 140L, 120L, 124L, 102L, 108L, 112L, 110L, 120L, 90L, 150L, NA, 102L, 130L, NA, 124L, 106L, 110L, 108L, 112L, 124L, 130L, 96L, 124L, 118L, 126L, 100L, 112L, NA, 132L, 108L, 104L, 162L, 126L, 108L, 114L, 128L, 134L, 98L, 92L, 126L, 142L, 116L, 148L, 136L, 114L, 90L, 162L, 122L, 134L, 102L, 118L, 148L, 120L, 132L, 126L, 98L, 112L, 114L, 124L, NA, 118L, 134L, 136L, 108L, 124L, 116L, 108L, 116L, 114L, 112L, 132L, 124L, 142L, 108L, 116L, 128L, 104L, 124L, 160L, 112L, 124L, 114L, 116L, 106L, 122L, 110L, 138L, 106L, 108L, 128L, 122L, 116L, 152L, 114L, 100L, 118L, NA, NA, 128L, 134L, 124L, 100L, 96L, 114L, 126L, NA, 128L, 130L, 128L, 108L, 132L, 172L, 128L, 108L, 132L, 118L, 146L, 152L, 112L, 96L, 136L, 110L, 110L, 102L, 128L, 204L, 124L), BPDia2 = c(76L, 76L, 106L, 80L, 52L, 74L, 76L, 72L, 76L, 80L, 90L, 64L, 66L, 54L, 84L, 76L, 60L, 86L, NA, 70L, 66L, NA, 78L, 74L, 62L, 70L, 86L, 76L, 70L, 72L, 82L, 78L, 96L, 66L, 68L, NA, 60L, 80L, 66L, 86L, 58L, 58L, 58L, 74L, 78L, 72L, 58L, 72L, 94L, 84L, 74L, 82L, 64L, 52L, 68L, 62L, 70L, 66L, 74L, 82L, 60L, 86L, 84L, 40L, 62L, 70L, 72L, NA, 56L, 72L, 66L, 78L, 82L, 68L, 72L, 76L, 64L, 72L, 86L, 82L, 68L, 68L, 74L, 94L, 60L, 80L, 84L, 80L, 76L, 58L, 68L, 50L, 80L, 68L, 78L, 62L, 52L, 76L, 64L, 74L, 94L, 58L, 66L, 70L, NA, NA, 88L, 80L, 70L, 56L, 68L, 64L, 58L, NA, 68L, 84L, 74L, 76L, 72L, 74L, 42L, 76L, 70L, 52L, 74L, 68L, 66L, 66L, 76L, 70L, 64L, 62L, 70L, 100L, 72L), BPSys3 = c(110L, 120L, 154L, 134L, 106L, 122L, 110L, 112L, 134L, 124L, 124L, 104L, 106L, 114L, 126L, 120L, 94L, 154L, NA, 104L, 128L, NA, NA, 114L, 112L, 104L, NA, 122L, 130L, 94L, 124L, 118L, 124L, 96L, 110L, NA, 134L, 112L, 98L, 158L, 128L, 96L, 110L, 128L, 116L, 98L, 90L, 132L, 136L, 124L, 144L, 134L, 110L, 92L, 166L, 124L, 124L, 106L, 128L, 154L, 124L, 128L, 126L, 92L, 114L, 110L, 120L, 122L, 122L, 124L, 128L, 106L, 130L, 118L, 110L, 114L, 114L, 114L, 140L, 116L, 126L, 106L, 118L, 124L, 98L, 112L, 160L, 112L, 124L, 112L, 118L, 110L, 126L, 106L, 136L, 106L, 104L, 130L, 114L, 112L, 156L, 114L, 104L, 118L, NA, NA, 126L, 124L, 118L, 102L, 102L, 112L, 130L, NA, 130L, 130L, 128L, 106L, 134L, 166L, 132L, 108L, 136L, 118L, 130L, 152L, 114L, 90L, 136L, 108L, 110L, 112L, 134L, 200L, 124L), BPDia3 = c(76L, 62L, 100L, 82L, 64L, 76L, 76L, 70L, 78L, 76L, 88L, 68L, 66L, 54L, 86L, 78L, 56L, 82L, NA, 78L, 66L, NA, NA, 84L, 60L, 70L, NA, 72L, 76L, 68L, 82L, 78L, 94L, 64L, 66L, NA, 72L, 78L, 62L, 88L, 54L, 56L, 60L, 78L, 76L, 70L, 52L, 76L, 96L, 84L, 74L, 84L, 54L, 54L, 66L, 60L, 68L, 58L, 76L, 88L, 62L, 84L, 78L, 50L, 70L, 68L, 66L, 84L, 54L, 72L, 64L, 68L, 80L, 64L, 74L, 72L, 62L, 74L, 94L, 72L, 70L, 56L, 68L, 92L, 62L, 76L, 84L, 72L, 74L, 64L, 66L, 50L, 78L, 68L, 80L, 68L, 56L, 80L, 64L, 66L, 88L, 54L, 76L, 68L, NA, NA, 78L, 78L, 64L, 54L, 66L, 66L, 66L, NA, 68L, 82L, 78L, 78L, 78L, 68L, 0L, 68L, 66L, 56L, 76L, 68L, 66L, 66L, 82L, 72L, 60L, 62L, 68L, 98L, 60L), Testosterone = c(390.16000000000003, NA, 8.1699999999999999, NA, NA, NA, NA, NA, 327.88999999999999, NA, NA, NA, 401.77999999999997, 320.44, NA, 293.58999999999997, 13.51, 20.879999999999999, 214.34999999999999, 19.550000000000001, 17.699999999999999, NA, 252.03, 20.530000000000001, NA, NA, 167, 566, 270.69999999999999, NA, NA, NA, 260.31999999999999, NA, 20.789999999999999, NA, 23.100000000000001, 246.81999999999999, NA, 413.72000000000003, 231.22, 27.800000000000001, 422, 137.91999999999999, NA, 9.9000000000000004, NA, NA, NA, 17, NA, 306.61000000000001, NA, 75.859999999999999, NA, 7.21, 20.93, NA, 233.65000000000001, NA, NA, NA, 14.76, 368.22000000000003, NA, 26.41, 259.62, 31.969999999999999, NA, NA, NA, 34.299999999999997, NA, NA, 23.030000000000001, NA, NA, NA, NA, 312.49000000000001, 7.7800000000000002, NA, NA, 345.11000000000001, NA, NA, 26.800000000000001, 604.11000000000001, NA, 31.960000000000001, 611.30999999999995, NA, 20, NA, 261.67000000000002, NA, NA, 537.23000000000002, 41.090000000000003, 39.600000000000001, NA, NA, 50.060000000000002, NA, 18.399999999999999, NA, NA, 10.949999999999999, NA, NA, 44.740000000000002, NA, NA, 402.31, 544.38, 614, 137.91999999999999, NA, 255.74000000000001, 14.99, NA, 23.579999999999998, 260.42000000000002, 505, 26.969999999999999, NA, NA, 651.52999999999997, 10.01, NA, NA, NA, NA, 354.31999999999999, NA), DirectChol = c(1.1899999999999999, 1.22, 2.4300000000000002, NA, 1.8400000000000001, 1.3999999999999999, 1.24, 1.6000000000000001, 1.1100000000000001, 0.84999999999999998, 0.93000000000000005, 1.9399999999999999, 0.84999999999999998, 1.24, 2.8399999999999999, 0.97999999999999998, 0.93000000000000005, 1.3400000000000001, 1.6299999999999999, 1.55, 1.24, 1.1100000000000001, 0.84999999999999998, 1.3999999999999999, 1.73, 1.29, 0.93000000000000005, 1.3200000000000001, 1.3200000000000001, 0.78000000000000003, 1.29, 0.88, 0.78000000000000003, 1.6799999999999999, 1.6000000000000001, 1.4199999999999999, 1.1599999999999999, 0.84999999999999998, 1.8100000000000001, 0.91000000000000003, 1.29, 1.6599999999999999, 1.03, 1.47, 1.47, 1.0600000000000001, 1.8899999999999999, 2.48, 1.55, 1.8600000000000001, 1.45, 1.71, 1.0900000000000001, 1.99, 1.55, 1.29, 1.27, 0.91000000000000003, 1.1100000000000001, 3.7200000000000002, 1.0600000000000001, NA, 1.45, 1.03, 1.29, 1.73, 1.0600000000000001, 1.29, 0.97999999999999998, 1.1599999999999999, 1.1100000000000001, 1.1100000000000001, 1.27, 1.1599999999999999, 1.4199999999999999, 1.27, 1.03, 1.3200000000000001, 1.29, 1.0900000000000001, 1.73, 1.1399999999999999, 1.53, 0.69999999999999996, 1.1399999999999999, 1.1899999999999999, 0.93000000000000005, 1.5, 1.9099999999999999, 1.1899999999999999, 1.3700000000000001, 1.0900000000000001, 2.2200000000000002, 1.53, 1.4199999999999999, 1.8600000000000001, 1.6799999999999999, 1.29, 1.3200000000000001, 1.29, 0.93000000000000005, 1.76, 1.5, NA, 2.4300000000000002, 1.55, 0.97999999999999998, 1.24, 1.1899999999999999, 1.9399999999999999, 1.99, 2.3300000000000001, 1.29, 0.97999999999999998, 1.78, 1.9099999999999999, 1.47, 1.3400000000000001, 0.93000000000000005, 1.3200000000000001, 0.97999999999999998, 0.95999999999999996, 1.22, 1.1399999999999999, 1.8600000000000001, 2.2200000000000002, 1.8400000000000001, 1.3700000000000001, 1.03, 1.27, 1.8899999999999999, 1.5, 1.3200000000000001, 1.0900000000000001, 1.0600000000000001 ), TotChol = c(4.8399999999999999, 3.75, 5.9199999999999999, NA, 4.7800000000000002, 6.96, 5.7699999999999996, 6.0300000000000002, 5.25, 5.6600000000000001, 8.1500000000000004, 5.3499999999999996, 3.7000000000000002, 5.0700000000000003, 6.2599999999999998, 6.9800000000000004, 3.3599999999999999, 5.1699999999999999, 6.1500000000000004, 3.75, 3.8500000000000001, 5.4000000000000004, 4.5800000000000001, 4.2400000000000002, 4.29, 5.2800000000000002, 4.7800000000000002, 4.1600000000000001, 5.2199999999999998, 6.3099999999999996, 4.4699999999999998, 4.3700000000000001, 5.3300000000000001, 4.0899999999999999, 6.0999999999999996, 4.6299999999999999, 5.6100000000000003, 3.1800000000000002, 3.96, 4.2400000000000002, 5.3300000000000001, 4.9699999999999998, 4.2400000000000002, 6.4400000000000004, 3.7000000000000002, 4.9900000000000002, 4.2699999999999996, 5.4800000000000004, 4.9699999999999998, 5.4000000000000004, 7.1900000000000004, 5.1500000000000004, 5.6399999999999997, 5.8399999999999999, 4.5999999999999996, 4.0300000000000002, 7.9400000000000004, 4.8399999999999999, 6.1799999999999997, 6.3899999999999997, 4.7599999999999998, NA, 5.5599999999999996, 5.9199999999999999, 4.0099999999999998, 5.4000000000000004, 6.3099999999999996, 3.5699999999999998, 3.8500000000000001, 4.9100000000000001, 4.4000000000000004, 4.9100000000000001, 8.7699999999999996, 4.5999999999999996, 4.0300000000000002, 5.2000000000000002, 7.21, 3.8999999999999999, 6.96, 3.6699999999999999, 4.6799999999999997, 4.5, 5.1699999999999999, 4.5999999999999996, 6.1299999999999999, 5.79, 4.4500000000000002, 6.1500000000000004, 5.0700000000000003, 4.3700000000000001, 3.4700000000000002, 4.4699999999999998, 4.8600000000000003, 4.71, 4.2699999999999996, 5.2199999999999998, 5.5599999999999996, 6.0300000000000002, 3.54, 6.8300000000000001, 4.1600000000000001, 6.4900000000000002, 4.5999999999999996, NA, 5.6600000000000001, 4.9400000000000004, 5.5099999999999998, 5.8700000000000001, 4.9699999999999998, 4.4000000000000004, 6.5700000000000003, 5.79, 3.8300000000000001, 4.4000000000000004, 4.9400000000000004, 5.9000000000000004, 6.4400000000000004, 5.6100000000000003, 5.2800000000000002, 4.5999999999999996, 3.7000000000000002, 4.4199999999999999, 5.4299999999999997, 4.5499999999999998, 5.0899999999999999, 5.2199999999999998, 5.7699999999999996, 6, 5.5899999999999999, 4.2699999999999996, 6.1299999999999999, 3.8799999999999999, 5.79, 7.4000000000000004, 5.8700000000000001), UrineVol1 = c(57L, 49L, 30L, 33L, 150L, 100L, 17L, 56L, 104L, 272L, 120L, 29L, 350L, 156L, 37L, 167L, 10L, 261L, 103L, 270L, 117L, 103L, 303L, 170L, 49L, 321L, 91L, 131L, 50L, 56L, 36L, 149L, 171L, 117L, 164L, 118L, 7L, 56L, 190L, 34L, 190L, 43L, 154L, 94L, 39L, 181L, 350L, 38L, 180L, 44L, 215L, 86L, 30L, 41L, 34L, 1L, 270L, 402L, 107L, 51L, 246L, 15L, 80L, 75L, 29L, 95L, 98L, 290L, 41L, 309L, 24L, 17L, 298L, 90L, 17L, 92L, 143L, 288L, 74L, 163L, 65L, 119L, 36L, 87L, 18L, 261L, 91L, 51L, 57L, 123L, 225L, NA, 154L, 153L, 50L, 197L, 122L, 179L, 81L, 38L, 90L, 122L, 371L, 18L, 134L, 355L, 122L, 56L, 275L, 92L, 11L, 38L, 53L, 76L, 118L, 102L, 94L, 61L, 60L, 136L, 109L, 101L, 38L, 171L, 95L, 61L, 27L, 88L, 36L, 248L, 366L, 59L, 135L, 51L, 161L), UrineFlow1 = c(0.073999999999999996, 0.55100000000000005, 1.304, 0.67300000000000004, 0.34200000000000003, 0.91700000000000004, 0.28299999999999997, 0.34599999999999997, 0.98999999999999999, NA, 0.61199999999999999, 0.33000000000000002, 2.593, 0.84299999999999997, 0.36599999999999999, 1.8979999999999999, 0.17199999999999999, 1.825, NA, 1.9419999999999999, 1.4810000000000001, 1.1319999999999999, 1.1020000000000001, 4.048, 0.32200000000000001, 12.346, 0.54500000000000004, 1.008, 0.48499999999999999, 0.073999999999999996, 0.31900000000000001, 3.3860000000000001, 0.46200000000000002, 1.1699999999999999, 3.4169999999999998, 0.48199999999999998, 0.050999999999999997, 0.33900000000000002, 3.0649999999999999, 0.35399999999999998, 1.377, 0.249, 0.85999999999999999, 0.93999999999999995, 0.51300000000000001, 1.905, 2.1339999999999999, 0.19900000000000001, 1.208, 0.45800000000000002, 1.044, 0.91500000000000004, 0.20399999999999999, 0.53200000000000003, 0.18099999999999999, 0.010999999999999999, 2.5230000000000001, 3.165, 0.80500000000000005, 0.378, 1.9370000000000001, 0.188, 0.879, 0.113, 0.27400000000000002, 0.21099999999999999, 1.4199999999999999, 4.6029999999999998, 0.14999999999999999, 5.2370000000000001, 0.58499999999999996, 0.128, 1.3300000000000001, 0.58399999999999996, 0.111, 1.26, 4.0860000000000003, 3.032, 0.372, 0.79500000000000004, 0.69099999999999995, 0.436, 0.85699999999999998, 0.59999999999999998, 0.27300000000000002, 1.032, 1.5169999999999999, 0.61399999999999999, 1.2130000000000001, 0.72799999999999998, NA, NA, 0.60199999999999998, 1.244, 0.316, 0.496, 1.3560000000000001, 4.5899999999999999, 0.14099999999999999, 0.19800000000000001, 0.92800000000000005, NA, 1.734, 0.66700000000000004, 2.1269999999999998, 1.972, 0.66700000000000004, 0.47099999999999997, 2.778, 0.40899999999999997, 0.14499999999999999, 0.55900000000000005, 0.58899999999999997, 0.96199999999999997, 1.0089999999999999, 2.488, 0.93999999999999995, 0.25800000000000001, 0.75, 1.0069999999999999, 1.5569999999999999, 0.79500000000000004, 0.18099999999999999, 0.371, 1.0109999999999999, 0.37, 0.45800000000000002, 1.1000000000000001, 0.45600000000000002, 1.5800000000000001, 0.91500000000000004, 0.378, 1.0800000000000001, 0.68899999999999995, 1.2110000000000001 ), UrineVol2 = c(NA, NA, 114L, 122L, NA, NA, 61L, NA, NA, NA, NA, 49L, NA, NA, NA, NA, 201L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 231L, NA, NA, 56L, NA, 90L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 125L, NA, 63L, NA, NA, NA, NA, NA, 62L, NA, NA, 155L, NA, NA, NA, NA, NA, 53L, 160L, NA, NA, 23L, NA, NA, NA, NA, NA, NA, NA, 84L, NA, 55L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 101L, NA, NA, NA, NA, NA, NA, 35L, 25L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 60L, NA, NA, NA, 314L, NA, 33L, NA, NA, NA, NA, NA, NA ), UrineFlow2 = c(NA, NA, 1.1180000000000001, 1.22, NA, NA, 0.40699999999999997, NA, NA, NA, NA, 0.41199999999999998, NA, NA, NA, NA, 1.0920000000000001, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1.8480000000000001, NA, NA, 0.28999999999999998, NA, 0.50600000000000001, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.77200000000000002, NA, 0.55300000000000005, NA, NA, NA, NA, NA, 0.41899999999999998, NA, NA, 2.5409999999999999, NA, NA, NA, NA, NA, 0.52500000000000002, 1.905, NA, NA, 0.19500000000000001, NA, NA, NA, NA, NA, NA, NA, 0.53500000000000003, NA, 0.61099999999999999, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1.4850000000000001, NA, NA, NA, NA, NA, NA, 0.32700000000000001, 0.14299999999999999, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.46200000000000002, NA, NA, NA, 2.8039999999999998, NA, 0.55000000000000004, NA, NA, NA, NA, NA, NA), Diabetes = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L), .Label = c("No", "Yes"), class = "factor"), DiabetesAge = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 63L, NA, NA, NA, 49L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 27L, NA, NA, NA, NA, 24L, NA, 50L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 38L, NA, NA, NA, NA, NA, NA, NA, NA, 55L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 40L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 12L, NA, NA, NA, NA, NA, NA, 56L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 42L), HealthGen = structure(c(4L, 4L, 2L, 2L, 4L, 4L, 3L, 4L, NA, 1L, 4L, 2L, 3L, 2L, NA, 3L, 3L, 1L, 2L, 2L, 4L, 4L, 3L, 2L, 3L, 4L, 3L, 4L, 3L, 4L, 3L, 3L, 3L, 1L, 2L, NA, 1L, 3L, 1L, 3L, 4L, 2L, 3L, 3L, 2L, 4L, 3L, 4L, NA, 1L, 2L, 3L, 4L, 2L, NA, 3L, 4L, 2L, 1L, 1L, 1L, 5L, 3L, 4L, 3L, 3L, 2L, 3L, 4L, 3L, 4L, 3L, 3L, 4L, 3L, 3L, 1L, 2L, 4L, 3L, 2L, 2L, 2L, NA, NA, 3L, 3L, 3L, 3L, 3L, 2L, 4L, 3L, NA, 3L, 1L, 1L, 2L, 3L, 2L, 3L, 3L, 2L, 3L, 4L, 3L, 4L, 4L, 2L, 2L, 1L, 2L, NA, 3L, 2L, 1L, 3L, 2L, 4L, NA, NA, 4L, 4L, 1L, 3L, 3L, 2L, 2L, 3L, 2L, 2L, 2L, 1L, 4L, 4L), .Label = c("Excellent", "Vgood", "Good", "Fair", "Poor"), class = "factor"), DaysPhysHlthBad = c(12L, 20L, 0L, 0L, 2L, 0L, 4L, 0L, NA, 0L, 20L, 2L, 0L, 2L, NA, 7L, 2L, 2L, 0L, 0L, 20L, 30L, 0L, 0L, 15L, 30L, 0L, 2L, 0L, 10L, 0L, 0L, 0L, 0L, 0L, NA, 0L, 2L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 7L, 0L, 30L, NA, 0L, 0L, 0L, 2L, 2L, NA, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 2L, 0L, 0L, 1L, 0L, 0L, 0L, 4L, 30L, 0L, 30L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, NA, NA, 0L, 2L, 0L, 30L, 3L, 0L, 0L, 0L, NA, 0L, 0L, 0L, 0L, 0L, 2L, 7L, 15L, 4L, 0L, 0L, 2L, 20L, 0L, 0L, 2L, 0L, 9L, NA, 0L, 0L, 0L, 0L, 0L, 0L, NA, NA, 3L, 30L, 3L, 0L, 14L, 2L, 0L, 3L, 2L, 1L, 0L, 0L, 0L, 30L), DaysMentHlthBad = c(30L, 30L, 0L, 0L, 0L, 0L, 5L, 5L, NA, 0L, 10L, 0L, 8L, 3L, NA, 14L, 2L, 0L, 0L, 4L, 10L, 30L, 20L, 2L, 30L, 30L, 0L, 0L, 0L, 2L, 0L, 5L, 0L, 4L, 0L, NA, 30L, 0L, 2L, 0L, 0L, 10L, 0L, 0L, 0L, 14L, 3L, 10L, NA, 5L, 6L, 4L, 15L, 1L, NA, 20L, 0L, 0L, 0L, 0L, 5L, 0L, 3L, 0L, 5L, 0L, 0L, 0L, 0L, 4L, 6L, 13L, 0L, 0L, 0L, 0L, 0L, 2L, 0L, 14L, 0L, 1L, 3L, NA, NA, 0L, 7L, 0L, 0L, 5L, 0L, 2L, 0L, NA, 0L, 0L, 0L, 0L, 7L, 10L, 2L, 30L, 0L, 0L, 30L, 3L, 15L, 0L, 0L, 1L, 30L, 0L, NA, 2L, 0L, 0L, 0L, 0L, 0L, NA, NA, 7L, 0L, 2L, 0L, 30L, 0L, 0L, 5L, 15L, 0L, 0L, 0L, 0L, 0L), LittleInterest = structure(c(2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, NA, 1L, 1L, 1L, 2L, 2L, NA, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, NA, 3L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 3L, NA, 1L, 1L, 2L, 3L, 1L, NA, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 3L, 1L, 1L, 2L, NA, NA, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, NA, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, NA, 1L, 1L, 1L, 1L, 1L, 1L, NA, NA, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L), .Label = c("None", "Several", "Most"), class = "factor"), Depressed = structure(c(2L, 1L, 1L, 1L, 1L, 1L, 2L, 3L, NA, 1L, 1L, 1L, 2L, 1L, NA, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, NA, 3L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 3L, NA, 1L, 1L, 1L, 3L, 1L, NA, 3L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 3L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 3L, 1L, 1L, 2L, NA, NA, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, NA, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 3L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, NA, 2L, 1L, 1L, 1L, 1L, 1L, NA, NA, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L), .Label = c("None", "Several", "Most"), class = "factor"), nPregnancies = c(NA, NA, 3L, 3L, 2L, NA, 3L, 2L, NA, NA, 7L, 3L, NA, NA, NA, NA, 4L, 1L, NA, NA, 1L, 7L, NA, 4L, 3L, NA, NA, NA, NA, NA, 5L, 2L, NA, NA, 2L, NA, 2L, NA, NA, NA, NA, NA, NA, NA, 2L, 3L, NA, NA, NA, NA, NA, NA, 4L, 3L, NA, 6L, 3L, NA, NA, NA, NA, 3L, 3L, NA, 1L, NA, NA, 1L, 2L, NA, 7L, 2L, NA, NA, 3L, NA, NA, NA, NA, NA, 3L, NA, 1L, NA, NA, NA, 2L, NA, 2L, 5L, NA, 6L, 3L, NA, NA, 2L, NA, NA, NA, 6L, NA, 4L, NA, NA, 4L, NA, NA, 2L, NA, NA, 2L, 3L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 4L, NA, NA, 3L, 2L, NA, NA, 1L, NA, NA), nBabies = c(NA, NA, 3L, 3L, 2L, NA, 3L, 2L, NA, NA, 2L, 3L, NA, NA, NA, NA, 3L, 1L, NA, NA, 1L, 4L, NA, 2L, 2L, NA, NA, NA, NA, NA, 2L, 2L, NA, NA, 2L, NA, 2L, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, 3L, 1L, NA, 4L, 2L, NA, NA, NA, NA, 2L, 2L, NA, NA, NA, NA, 1L, 2L, NA, 3L, 0L, NA, NA, 3L, NA, NA, NA, NA, NA, 2L, NA, 1L, NA, NA, NA, 2L, NA, 2L, 3L, NA, 4L, 2L, NA, NA, 2L, NA, NA, NA, 6L, NA, 1L, NA, NA, 2L, NA, NA, 2L, NA, NA, 2L, 2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 4L, NA, NA, 2L, 1L, NA, NA, 1L, NA, NA), Age1stBaby = c(NA, NA, 27L, 23L, 17L, NA, 31L, 22L, NA, NA, 23L, 20L, NA, NA, NA, NA, 17L, NA, NA, NA, NA, 17L, NA, 26L, 17L, NA, NA, NA, NA, NA, 34L, 29L, NA, NA, 29L, NA, 20L, NA, NA, NA, NA, NA, NA, NA, 25L, NA, NA, NA, NA, NA, NA, NA, 19L, NA, NA, 20L, 25L, NA, NA, NA, NA, 20L, 24L, NA, NA, NA, NA, NA, 21L, NA, 22L, NA, NA, NA, 16L, NA, NA, NA, NA, NA, 19L, NA, NA, NA, NA, NA, 26L, NA, 22L, 25L, NA, 20L, 25L, NA, NA, 24L, NA, NA, NA, 22L, NA, NA, NA, NA, 17L, NA, NA, 33L, NA, NA, 31L, 27L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 23L, NA, NA, 33L, NA, NA, NA, NA, NA, NA), SleepHrsNight = c(9L, 3L, 6L, 6L, 6L, 6L, 6L, 4L, 7L, 4L, 8L, 8L, 7L, 6L, 4L, 4L, 5L, 8L, 5L, 7L, 7L, 4L, 6L, 8L, 4L, 6L, 6L, 6L, 8L, 6L, 7L, 7L, 7L, 7L, 7L, 6L, 6L, 9L, 7L, 7L, 8L, 8L, 8L, 6L, 7L, 7L, 7L, 6L, 7L, 8L, 6L, 8L, 6L, 9L, 6L, 6L, 7L, 10L, 9L, 8L, 8L, 10L, 8L, 8L, 8L, 8L, 8L, 6L, 7L, 7L, 6L, 6L, 6L, 7L, 8L, 7L, 7L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 9L, 6L, 8L, 8L, 8L, 5L, 6L, 8L, 6L, 5L, 8L, 8L, 7L, 6L, 9L, 7L, 7L, 2L, 8L, 6L, 8L, 8L, 8L, 9L, 6L, 7L, 7L, 6L, 7L, 7L, 9L, 8L, 6L, 7L, 7L, 8L, 6L, 8L, 9L, 11L, 9L, 5L, 7L, 6L, 6L, 6L, 6L, 8L, 6L, 8L, 6L), SleepTrouble = structure(c(2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L), .Label = c("No", "Yes"), class = "factor"), PhysActive = structure(c(1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L), .Label = c("No", "Yes"), class = "factor"), PhysActiveDays = c(NA, 3L, 4L, 7L, NA, NA, NA, NA, 4L, NA, 3L, NA, NA, NA, NA, NA, 5L, NA, 5L, 3L, 3L, NA, 5L, 5L, NA, NA, 5L, NA, NA, NA, 5L, 1L, 7L, 2L, 1L, 5L, 2L, NA, 4L, NA, NA, 6L, 2L, NA, NA, 2L, NA, NA, 2L, 5L, 3L, NA, NA, NA, NA, NA, NA, NA, 7L, 1L, 3L, NA, NA, NA, 2L, NA, NA, NA, 4L, 2L, 7L, 5L, NA, NA, NA, 2L, 5L, NA, 5L, NA, 6L, 2L, NA, 3L, NA, 7L, 2L, NA, NA, 4L, 5L, NA, 6L, 3L, NA, 5L, 1L, 3L, NA, 3L, NA, NA, 4L, 4L, 1L, 3L, 4L, NA, 1L, NA, NA, NA, 5L, NA, NA, NA, NA, NA, NA, NA, 7L, NA, NA, NA, NA, 6L, 5L, NA, NA, 3L, 6L, 3L, 6L, 5L, 3L), TVHrsDay = structure(c(3L, NA, 3L, NA, NA, NA, NA, NA, 4L, NA, NA, NA, 4L, 2L, NA, 3L, 1L, 6L, 6L, 2L, 2L, NA, 7L, 4L, NA, NA, 7L, 3L, 7L, NA, NA, NA, 6L, NA, 3L, NA, 2L, 5L, NA, 6L, 5L, 5L, 6L, 3L, NA, 4L, NA, NA, NA, 4L, NA, 5L, NA, 1L, NA, 4L, 4L, NA, 5L, NA, NA, NA, 7L, 4L, NA, 3L, 5L, 3L, NA, NA, NA, 5L, NA, NA, 5L, NA, NA, NA, NA, 4L, 4L, NA, NA, 4L, NA, NA, 5L, 3L, NA, 3L, 5L, NA, 6L, NA, 5L, NA, NA, 6L, 7L, 5L, NA, NA, 4L, NA, 2L, NA, NA, 3L, NA, NA, 2L, 3L, NA, 4L, 3L, 6L, 3L, NA, 5L, 2L, NA, 5L, 6L, 5L, 6L, NA, NA, 4L, 3L, NA, NA, NA, NA, 4L, NA), .Label = c("0_hrs", "0_to_1_hr", "1_hr", "2_hr", "3_hr", "4_hr", "More_4_hr"), class = "factor"), CompHrsDay = structure(c(3L, NA, 3L, NA, NA, NA, NA, NA, 7L, NA, NA, NA, 3L, 6L, NA, 1L, 1L, 5L, 1L, 6L, 3L, NA, 7L, 4L, NA, NA, 6L, 2L, 3L, NA, NA, NA, 4L, NA, 2L, NA, 3L, 2L, NA, 5L, 3L, 5L, 4L, 4L, NA, 2L, NA, NA, NA, 1L, NA, 5L, NA, 4L, NA, 1L, 2L, NA, 3L, NA, NA, NA, 3L, 1L, NA, 2L, 3L, 2L, NA, NA, NA, 2L, NA, NA, 1L, NA, NA, NA, NA, 3L, 5L, NA, NA, 5L, NA, NA, 4L, 4L, NA, 4L, 4L, NA, 1L, NA, 1L, NA, NA, 1L, 5L, 2L, NA, NA, 7L, NA, 2L, NA, NA, 1L, NA, NA, 3L, 4L, NA, 4L, 1L, 1L, 4L, NA, 1L, 2L, NA, 1L, 1L, 3L, 3L, NA, NA, 2L, 2L, NA, NA, NA, NA, 2L, NA), .Label = c("0_hrs", "0_to_1_hr", "1_hr", "2_hr", "3_hr", "4_hr", "More_4_hr"), class = "factor"), TVHrsDayChild = c(NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_), CompHrsDayChild = c(NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_), Alcohol12PlusYr = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, NA, 2L, 2L, 1L, 2L, 2L, NA, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, NA, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, NA, 1L, 2L, 2L, 2L, 1L, NA, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, NA, NA, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, NA, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, NA, 2L, 2L, 2L, 2L, 2L, 2L, NA, NA, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("No", "Yes"), class = "factor"), AlcoholDay = c(2L, NA, 1L, 1L, 5L, 12L, 1L, 12L, NA, NA, NA, 1L, 1L, 11L, NA, 5L, NA, NA, 1L, 2L, NA, NA, NA, 2L, 6L, 1L, 4L, 10L, 1L, 1L, 3L, NA, NA, 2L, 2L, NA, 2L, NA, 1L, NA, 12L, NA, 1L, 1L, 1L, NA, 3L, NA, NA, NA, 2L, 7L, 1L, NA, NA, 2L, 1L, 5L, 2L, 2L, 3L, NA, 2L, NA, 3L, 1L, 4L, 1L, NA, 1L, 1L, 4L, 5L, 1L, NA, 6L, 1L, 5L, 3L, 12L, 1L, 1L, NA, NA, NA, 2L, NA, 2L, 1L, 2L, 2L, 1L, 3L, NA, 6L, 2L, 8L, 9L, 3L, 2L, 2L, 5L, 1L, 5L, 3L, 2L, 3L, NA, 6L, NA, 1L, 2L, NA, 5L, 1L, 2L, 1L, 1L, 5L, NA, NA, 1L, 5L, 2L, 1L, NA, 1L, 5L, 2L, 1L, 1L, 1L, NA, 6L, 2L ), AlcoholYear = c(2L, 0L, 364L, 52L, 24L, 168L, 4L, 364L, NA, 0L, 0L, 4L, 2L, 52L, NA, 6L, 0L, 0L, 1L, 156L, 0L, 0L, 0L, 5L, 52L, 24L, 48L, 156L, 104L, 104L, 3L, 0L, 0L, 12L, 260L, NA, 3L, 0L, 260L, NA, 12L, NA, 364L, 2L, 4L, NA, 24L, 0L, NA, NA, 52L, 104L, 2L, NA, NA, 260L, 12L, 5L, 312L, 96L, 60L, NA, 36L, 0L, 24L, 24L, 208L, 12L, 0L, 52L, 6L, 24L, 24L, 52L, NA, 5L, 6L, 6L, 208L, 2L, 6L, 104L, 0L, NA, NA, 24L, NA, 100L, 156L, 52L, 156L, 3L, 6L, NA, 1L, 24L, 52L, 260L, 6L, 12L, 104L, 9L, 1L, 52L, 260L, 364L, 52L, NA, 8L, 0L, 8L, 156L, NA, 1L, 312L, 52L, 2L, 156L, 52L, NA, NA, 5L, 364L, 48L, 168L, NA, 36L, 156L, 180L, 260L, 208L, 52L, 0L, 208L, 40L), SmokeNow = structure(c(NA, 1L, NA, 1L, 2L, 2L, 1L, 2L, NA, NA, NA, NA, NA, NA, 2L, 2L, 2L, NA, 1L, NA, 2L, 2L, NA, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, 1L, NA, 1L, 2L, NA, 2L, 2L, NA, 1L, NA, 2L, NA, 2L, 1L, NA, 2L, NA, 2L, NA, NA, NA, NA, 2L, 1L, NA, 1L, NA, NA, 2L, 2L, 2L, 2L, NA, 1L, 2L, 1L, NA, 2L, NA, NA, NA, 1L, NA, 2L, 1L, NA, NA, 1L, 1L, NA, 2L, 2L, 1L, NA, NA, 2L, NA, NA, 1L, 2L, 1L, NA, 2L, 2L, NA, NA, NA, NA, NA, NA, NA, NA, 1L, NA, NA, 1L, 2L, NA, NA, NA, 2L, NA, 1L, NA, NA, 2L, NA, NA, 1L, NA, NA, 2L, NA), .Label = c("No", "Yes" ), class = "factor"), Smoke100 = structure(c(1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L), .Label = c("No", "Yes"), class = "factor"), Smoke100n = structure(c(1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L), .Label = c("Non-Smoker", "Smoker"), class = "factor"), SmokeAge = c(NA, 11L, NA, 18L, 14L, 14L, 10L, 30L, NA, NA, NA, NA, NA, NA, 11L, 16L, 15L, NA, 14L, NA, NA, 15L, NA, 19L, 12L, 18L, 16L, 7L, 17L, 15L, NA, NA, NA, NA, NA, 23L, NA, NA, NA, NA, NA, NA, 19L, NA, 22L, 30L, NA, 22L, NA, NA, 22L, NA, 17L, NA, 15L, 15L, NA, 22L, NA, 18L, NA, NA, NA, NA, 19L, 15L, NA, 19L, NA, NA, 12L, 18L, 17L, 18L, NA, 17L, 18L, 25L, NA, 24L, NA, NA, NA, 15L, NA, 14L, 18L, NA, NA, 14L, 16L, NA, 14L, 16L, 14L, NA, NA, 45L, NA, NA, 17L, 14L, 14L, NA, 14L, 17L, NA, NA, NA, NA, NA, NA, NA, NA, 26L, NA, NA, 22L, 15L, NA, NA, NA, 19L, NA, 16L, NA, NA, 12L, NA, NA, 18L, NA, NA, 16L, NA), Marijuana = structure(c(2L, 2L, 1L, NA, 2L, 2L, 2L, 1L, NA, 1L, 2L, NA, 1L, 2L, NA, 2L, 1L, NA, NA, 2L, 2L, 1L, 2L, 2L, 2L, NA, 2L, 2L, NA, 2L, 2L, 2L, 1L, 1L, 2L, NA, 1L, 2L, 2L, 1L, 2L, 2L, NA, 2L, NA, 1L, 1L, 1L, NA, 1L, NA, 2L, 1L, 1L, NA, 2L, 1L, 2L, NA, 1L, 1L, NA, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, NA, 1L, NA, 1L, 2L, 2L, NA, 2L, 2L, NA, NA, NA, NA, 1L, 1L, 2L, 2L, NA, 2L, NA, NA, 2L, 1L, 2L, 2L, NA, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, NA, NA, NA, 1L, NA, NA, 2L, NA, 1L, NA, NA, 2L, NA, 2L, NA, NA, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L), .Label = c("No", "Yes"), class = "factor"), AgeFirstMarij = c(16L, 17L, NA, NA, 11L, 14L, 11L, NA, NA, NA, 17L, NA, NA, 20L, NA, 15L, NA, NA, NA, 19L, 17L, NA, 24L, 15L, 12L, NA, 15L, 9L, NA, 46L, 19L, 20L, NA, NA, 18L, NA, NA, 14L, 20L, NA, 20L, 21L, NA, 19L, NA, NA, NA, NA, NA, NA, NA, 14L, NA, NA, NA, 15L, NA, 19L, NA, NA, NA, NA, NA, NA, 17L, 15L, 18L, NA, NA, NA, NA, 16L, 15L, 19L, NA, NA, NA, NA, 15L, 13L, NA, 15L, 16L, NA, NA, NA, NA, NA, NA, 16L, 14L, NA, 14L, NA, NA, 19L, NA, 24L, 15L, NA, 19L, 18L, 19L, NA, 16L, 18L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 19L, NA, NA, NA, NA, 17L, NA, 16L, NA, NA, NA, 12L, 14L, 16L, 17L, 17L, 16L, 14L, NA), RegularMarij = structure(c(1L, 2L, 1L, NA, 2L, 2L, 2L, 1L, NA, 1L, 2L, NA, 1L, 1L, NA, 2L, 1L, NA, NA, 1L, 2L, 1L, 1L, 1L, 2L, NA, 1L, 2L, NA, 2L, 1L, 1L, 1L, 1L, 2L, NA, 1L, 1L, 1L, 1L, 2L, 1L, NA, 1L, NA, 1L, 1L, 1L, NA, 1L, NA, 2L, 1L, 1L, NA, 2L, 1L, 1L, NA, 1L, 1L, NA, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, NA, 1L, NA, 1L, 1L, 2L, NA, 1L, 1L, NA, NA, NA, NA, 1L, 1L, 1L, 2L, NA, 2L, NA, NA, 1L, 1L, 2L, 2L, NA, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, NA, NA, NA, 1L, NA, NA, 1L, NA, 1L, NA, NA, 2L, NA, 2L, NA, NA, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L), .Label = c("No", "Yes"), class = "factor"), AgeRegMarij = c(NA, 17L, NA, NA, 16L, 14L, 11L, NA, NA, NA, 20L, NA, NA, NA, NA, 15L, NA, NA, NA, NA, 17L, NA, NA, NA, 12L, NA, NA, 12L, NA, 46L, NA, NA, NA, NA, 22L, NA, NA, NA, NA, NA, 20L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 17L, NA, NA, NA, 15L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 17L, NA, NA, NA, NA, NA, 20L, 15L, 23L, NA, NA, NA, NA, NA, 15L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 17L, NA, 14L, NA, NA, NA, NA, 26L, 15L, NA, 19L, 24L, 19L, NA, NA, 18L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 17L, NA, 18L, NA, NA, NA, 12L, 18L, NA, NA, NA, NA, 16L, NA), HardDrugs = structure(c(2L, 1L, 1L, NA, 1L, 2L, 1L, 1L, NA, 1L, 2L, NA, 1L, 1L, NA, 2L, 2L, NA, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, NA, 1L, 1L, 1L, 1L, 2L, 1L, NA, 1L, NA, 1L, 1L, 1L, NA, 1L, 1L, 2L, 1L, 1L, NA, 1L, 1L, 2L, 1L, 1L, 1L, NA, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, NA, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, NA, NA, NA, NA, 1L, 1L, 1L, 2L, 1L, 1L, NA, NA, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, NA, NA, NA, 1L, NA, 1L, 1L, 1L, 1L, NA, NA, 1L, NA, 1L, 1L, NA, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L), .Label = c("No", "Yes"), class = "factor"), SexEver = structure(c(2L, 2L, 2L, NA, 2L, 2L, 2L, 2L, NA, 2L, 2L, NA, 2L, 2L, NA, 2L, 2L, NA, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, NA, 2L, 2L, 2L, 2L, 2L, 2L, NA, 2L, NA, 2L, 2L, 2L, NA, 2L, 2L, 2L, 2L, 2L, NA, 2L, 2L, 2L, 2L, 1L, 2L, NA, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, NA, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, NA, NA, NA, NA, 2L, 2L, 2L, 2L, 2L, 2L, NA, NA, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, NA, NA, NA, 2L, NA, 2L, 2L, 2L, 1L, NA, NA, 2L, NA, 2L, 2L, NA, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("No", "Yes"), class = "factor"), SexAge = c(15L, 17L, 17L, NA, 13L, 15L, 15L, 17L, NA, 21L, 16L, NA, 17L, 18L, NA, 16L, 13L, NA, 12L, 19L, 20L, 14L, 20L, 17L, 13L, 9L, 17L, 12L, 19L, 16L, 17L, 20L, NA, 19L, 19L, NA, 14L, 17L, 20L, 13L, 19L, 19L, NA, 18L, NA, 23L, 17L, 14L, NA, 17L, 18L, 20L, 19L, 20L, NA, 15L, 22L, 17L, 19L, NA, 15L, NA, 19L, 16L, 17L, 15L, 18L, 22L, 21L, 18L, 19L, 16L, 15L, 17L, NA, 15L, 16L, 16L, 17L, 15L, 18L, 16L, 16L, NA, NA, NA, NA, 18L, 21L, 14L, 15L, 18L, 13L, NA, NA, 18L, 18L, 14L, 17L, 20L, 21L, 9L, 14L, 15L, 15L, 13L, 17L, 33L, 16L, 17L, NA, NA, NA, 17L, NA, 18L, 18L, 21L, NA, NA, NA, 13L, NA, 13L, 16L, NA, 20L, 13L, 17L, 13L, 18L, 17L, 21L, 16L, 18L), SexNumPartnLife = c(50L, 81L, 4L, NA, 10L, 8L, 3L, 5L, NA, 5L, 45L, NA, 4L, 1L, NA, 25L, 5L, NA, 50L, 15L, 4L, 3L, 3L, 15L, 14L, 500L, 1L, 15L, 12L, 10L, 6L, 5L, 0L, 1L, 2L, NA, 5L, 30L, 10L, 2L, 5L, 7L, NA, 6L, NA, 2L, 2L, 6L, NA, 1L, 12L, 7L, 4L, 1L, NA, 10L, 4L, 3L, 6L, 0L, 7L, NA, 9L, 3L, 8L, 35L, 5L, 1L, 1L, 3L, 6L, 13L, 25L, 15L, NA, 3L, 30L, 4L, 10L, 30L, 7L, 14L, 23L, NA, NA, NA, NA, 4L, 2L, 6L, 40L, 1L, 7L, NA, NA, 6L, 2L, 800L, 300L, 2L, 1L, 30L, 13L, 5L, 6L, 34L, 3L, 1L, 7L, 1L, NA, NA, NA, 8L, NA, 10L, 6L, 7L, 0L, NA, NA, 5L, NA, 8L, 6L, NA, 1L, 100L, 12L, 11L, 20L, 5L, 1L, 20L, 2L), SexNumPartYear = c(1L, 10L, 1L, NA, 3L, 1L, 1L, 0L, NA, 5L, 2L, NA, 1L, 1L, NA, 2L, 2L, NA, NA, 2L, 3L, 1L, 1L, 1L, 1L, NA, 1L, 1L, NA, 1L, 1L, 1L, 0L, 1L, 1L, NA, 1L, 1L, 2L, 0L, 1L, 5L, NA, 0L, NA, 0L, 1L, 0L, NA, 1L, NA, 4L, 0L, 1L, NA, 1L, 1L, 1L, NA, 0L, 1L, NA, 2L, 3L, 4L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, NA, 1L, NA, 1L, 1L, 1L, NA, 1L, 1L, NA, NA, NA, NA, 1L, 0L, 0L, 1L, NA, 1L, NA, NA, 1L, 1L, 2L, 4L, NA, 0L, 2L, 0L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, NA, NA, NA, 1L, NA, NA, 0L, NA, 0L, NA, NA, 1L, NA, 1L, NA, NA, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L ), SameSex = structure(c(1L, 1L, 1L, NA, 1L, 1L, 1L, 1L, NA, 1L, 2L, NA, 1L, 1L, NA, 1L, 1L, NA, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, NA, 1L, 1L, 1L, 1L, 1L, 1L, NA, 1L, NA, 1L, 1L, 1L, NA, 1L, 1L, 1L, 1L, 1L, NA, 2L, 1L, 1L, 1L, 1L, 1L, NA, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, NA, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, NA, NA, NA, NA, 1L, 1L, 1L, 1L, 1L, 1L, NA, NA, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, NA, NA, NA, 1L, NA, 1L, 1L, 1L, 1L, NA, NA, 1L, NA, 1L, 1L, NA, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"), SexOrientation = structure(c(2L, 2L, 2L, NA, 2L, 2L, NA, 2L, NA, 2L, 2L, NA, 2L, 2L, NA, 2L, 2L, NA, NA, 2L, 2L, 2L, 2L, 2L, 2L, NA, 2L, 2L, NA, 2L, 2L, 2L, 2L, 2L, 2L, NA, 2L, 2L, NA, 2L, 2L, 2L, NA, 2L, NA, 2L, 2L, 2L, NA, 2L, NA, 2L, 2L, 2L, NA, 2L, 2L, 2L, NA, 2L, 2L, NA, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, NA, 2L, NA, 2L, 2L, 2L, NA, 2L, 2L, NA, NA, NA, NA, 2L, 2L, NA, 2L, NA, 2L, NA, NA, 2L, 2L, 2L, 2L, NA, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, NA, NA, NA, 2L, NA, NA, 2L, NA, 2L, NA, NA, 2L, NA, 2L, NA, NA, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("Bisexual", "Heterosexual", "Homosexual"), class = "factor"), PregnantNow = structure(c(NA, NA, NA, NA, 2L, NA, 2L, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, 2L, 2L, 2L, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, 2L, NA, 2L, NA, 2L, 2L, NA, 2L, NA, NA, 2L, NA, NA, NA, 2L, 2L, NA, 2L, 2L, NA, NA, NA, 1L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, 2L, NA, 2L, 2L, NA, NA, 2L, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, 2L, NA, 2L, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, 2L, NA, NA, 1L, 2L, NA, NA, NA, 2L, NA, NA, NA, 2L, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, 2L, NA, NA, 2L, 2L, NA, NA, NA, NA), .Label = c("Yes", "No", "Unknown"), class = "factor")), row.names = c(5534L, 2607L, 8722L, 2697L, 2121L, 2563L, 1457L, 715L, 7693L, 4133L, 3099L, 3156L, 5008L, 9484L, 4077L, 8975L, 7867L, 7615L, 8681L, 6763L, 7574L, 141L, 9812L, 7229L, 4342L, 3416L, 9138L, 9369L, 5253L, 3797L, 1811L, 4160L, 7618L, 1898L, 5728L, 3272L, 5212L, 5611L, 2500L, 8910L, 9827L, 5689L, 8756L, 5289L, 3604L, 9058L, 4195L, 745L, 4189L, 9150L, 3413L, 7806L, 3402L, 5122L, 2072L, 6534L, 6324L, 2423L, 7237L, 3481L, 322L, 1834L, 7746L, 9129L, 1858L, 9205L, 9250L, 5035L, 2851L, 3752L, 2211L, 6231L, 3305L, 1965L, 5243L, 1889L, 1723L, 2498L, 3128L, 6144L, 7917L, 4065L, 1497L, 6379L, 4495L, 259L, 7816L, 8548L, 4510L, 7544L, 9610L, 4405L, 7188L, 1941L, 5662L, 1584L, 1839L, 9599L, 5852L, 9301L, 3298L, 245L, 7887L, 4087L, 7576L, 2666L, 1756L, 8589L, 181L, 4737L, 5270L, 7925L, 2676L, 5760L, 9207L, 6426L, 5290L, 938L, 8718L, 5606L, 3109L, 8598L, 8752L, 5070L, 8697L, 4921L, 4801L, 8196L, 6237L, 2426L, 834L, 319L, 81L, 8129L, 4809L), class = c("tbl_df", "tbl", "data.frame"))