For each name in name, adds one column age_at_{name} (numeric,
years) computed as:
$$age\_at\_event = age\_col + (event\_date - baseline\_date) / 365.25$$
Arguments
- data
(data.frame or data.table) UKB phenotype data.
- name
(character) One or more output prefixes, e.g.
c("disease", "disease_icd10", "outcome"). Each producesage_at_{name}.- baseline_col
(character) Name of the baseline date column (e.g.
"date_baseline").- age_col
(character) Name of the age-at-baseline column (e.g.
"age_recruitment").- date_cols
(character or NULL) Named character vector mapping each name to its event date column, e.g.
c(disease = "disease_date", outcome = "outcome_date").NULL(default) triggers auto-detection as{name}_date.- status_cols
(character or NULL) Named character vector mapping each name to its status column.
NULL(default) triggers auto-detection.
Details
The value is NA for participants who did not experience the event
(status is FALSE / 0) or who lack an event date.
Auto-detection per name (when date_cols / status_cols
are NULL):
date_col- looked up as{name}_date.status_col- looked up first as{name}_status, then as{name}(logical column); if neither exists all rows with a non-NAdate are treated as cases.
data.table pass-by-reference: new columns are added in-place.
Examples
dt <- ops_toy(scenario = "association", n = 100)
#> ✔ ops_toy: 100 participants | 33 columns | scenario = "association" | seed = 42
derive_age(dt, name = "dm", baseline_col = "p53_i0", age_col = "p21022")
#> ℹ age_at_dm: n=9, median=60.2, range=[38.4, 76.6]
#> ✔ derive_age: 1 event processed.
#> eid p31 p53_i0 p21022 p21001_i0 bmi_cat p20116_i0
#> <int> <fctr> <IDat> <int> <num> <fctr> <fctr>
#> 1: 10000001 Male 2006-03-23 66 21.80 Normal Never
#> 2: 10000002 Male 2008-07-02 49 23.27 Normal Never
#> 3: 10000003 Female 2006-11-21 64 33.28 Obese Never
#> 4: 10000004 Male 2010-07-04 67 25.23 Overweight Never
#> 5: 10000005 Male 2009-10-15 61 20.31 Normal Never
#> 6: 10000006 Female 2008-08-08 44 27.10 Overweight Previous
#> 7: 10000007 Male 2006-10-23 49 24.20 Normal Previous
#> 8: 10000008 Female 2006-05-29 56 29.45 Overweight Current
#> 9: 10000009 Male 2008-09-22 56 34.08 Obese Current
#> 10: 10000010 Male 2010-05-12 44 20.74 Normal Never
#> 11: 10000011 Female 2006-04-10 42 28.70 Overweight Previous
#> 12: 10000012 Male 2008-09-25 53 26.67 Overweight Previous
#> 13: 10000013 Male 2006-10-25 53 31.13 Obese Never
#> 14: 10000014 Female 2007-02-06 67 24.94 Normal Current
#> 15: 10000015 Female 2006-04-01 65 30.80 Obese Never
#> 16: 10000016 Male 2008-02-20 40 16.60 Underweight Never
#> 17: 10000017 Male 2009-04-19 44 35.49 Obese Current
#> 18: 10000018 Female 2008-12-13 42 30.96 Obese Never
#> 19: 10000019 Female 2008-04-30 61 25.37 Overweight Previous
#> 20: 10000020 Male 2006-10-15 65 18.23 Underweight Previous
#> 21: 10000021 Male 2007-12-21 70 29.74 Overweight Never
#> 22: 10000022 Female 2010-11-17 70 28.86 Overweight Never
#> 23: 10000023 Male 2006-03-01 52 26.17 Overweight Never
#> 24: 10000024 Male 2009-08-01 50 27.03 Overweight Previous
#> 25: 10000025 Female 2008-04-28 59 22.99 Normal Previous
#> 26: 10000026 Female 2010-07-02 65 28.23 Overweight Never
#> 27: 10000027 Female 2008-08-26 56 27.82 Overweight Previous
#> 28: 10000028 Male 2007-01-12 66 24.66 Normal Current
#> 29: 10000029 Female 2007-09-30 66 18.85 Normal Never
#> 30: 10000030 Male 2007-03-03 69 30.05 Obese Never
#> 31: 10000031 Male 2007-03-18 59 29.25 Overweight Previous
#> 32: 10000032 Male 2009-02-09 43 21.60 Normal Previous
#> 33: 10000033 Female 2007-08-07 59 17.43 Underweight Previous
#> 34: 10000034 Male 2009-08-01 50 27.33 Overweight Never
#> 35: 10000035 Female 2008-08-08 56 24.30 Normal Never
#> 36: 10000036 Male 2010-03-17 48 27.59 Overweight Never
#> 37: 10000037 Female 2009-03-10 56 19.08 Normal Current
#> 38: 10000038 Female 2010-10-08 69 20.92 Normal Never
#> 39: 10000039 Male 2008-08-26 52 32.17 Obese Previous
#> 40: 10000040 Male 2006-11-07 70 28.42 Overweight Never
#> 41: 10000041 Female 2008-06-30 69 29.43 Overweight Never
#> 42: 10000042 Female 2007-04-19 67 36.18 Obese Never
#> 43: 10000043 Female 2008-03-21 70 26.91 Overweight Current
#> 44: 10000044 Male 2010-04-27 56 15.19 Underweight Never
#> 45: 10000045 Female 2006-02-11 68 28.04 Overweight Current
#> 46: 10000046 Male 2008-01-30 59 32.64 Obese Previous
#> 47: 10000047 Male 2009-06-28 40 37.53 Obese Previous
#> 48: 10000048 Male 2010-01-04 56 18.63 Normal Never
#> 49: 10000049 Male 2010-08-20 40 19.87 Normal Never
#> 50: 10000050 Male 2006-01-25 67 22.32 Normal Never
#> 51: 10000051 Female 2007-12-04 41 20.40 Normal Never
#> 52: 10000052 Female 2010-04-17 70 22.65 Normal Never
#> 53: 10000053 Female 2009-06-15 47 25.18 Overweight Previous
#> 54: 10000054 Male 2007-06-10 70 19.59 Normal Never
#> 55: 10000055 Female 2007-09-15 55 37.40 Obese Never
#> 56: 10000056 Male 2006-09-19 42 26.79 Overweight Previous
#> 57: 10000057 Male 2010-03-08 44 25.74 Overweight Previous
#> 58: 10000058 Female 2008-07-31 52 28.93 Overweight Never
#> 59: 10000059 Female 2006-10-26 51 26.41 Overweight <NA>
#> 60: 10000060 Female 2010-01-09 40 25.47 Overweight Never
#> 61: 10000061 Male 2007-12-21 69 34.32 Obese Never
#> 62: 10000062 Male 2007-01-04 58 25.01 Overweight Previous
#> 63: 10000063 Male 2007-05-27 67 19.14 Normal Never
#> 64: 10000064 Male 2008-01-28 70 28.32 Overweight Never
#> 65: 10000065 Male 2009-10-24 44 24.27 Normal Previous
#> 66: 10000066 Female 2008-01-24 54 23.33 Normal Previous
#> 67: 10000067 Female 2008-03-09 63 20.33 Normal Never
#> 68: 10000068 Male 2008-05-11 45 28.56 Overweight Current
#> 69: 10000069 Male 2009-06-01 62 25.24 Overweight Previous
#> 70: 10000070 Female 2008-02-13 55 29.04 Overweight Previous
#> 71: 10000071 Female 2009-05-22 49 24.91 Normal Never
#> 72: 10000072 Female 2006-10-21 46 22.58 Normal Never
#> 73: 10000073 Female 2007-08-30 70 33.08 Obese <NA>
#> 74: 10000074 Female 2010-03-22 48 24.71 Normal <NA>
#> 75: 10000075 Female 2008-02-03 48 31.41 Obese Never
#> 76: 10000076 Male 2008-02-22 64 19.59 Normal Previous
#> 77: 10000077 Female 2007-06-30 42 23.64 Normal Never
#> 78: 10000078 Female 2007-03-02 57 24.72 Normal Current
#> 79: 10000079 Female 2007-04-16 60 24.05 Normal Never
#> 80: 10000080 Female 2006-07-07 54 33.62 Obese <NA>
#> 81: 10000081 Male 2006-09-11 67 26.07 Overweight Previous
#> 82: 10000082 Female 2006-09-25 67 27.54 Overweight Never
#> 83: 10000083 Female 2007-10-02 54 21.02 Normal Previous
#> 84: 10000084 Male 2009-12-04 68 22.19 Normal Never
#> 85: 10000085 Male 2006-02-10 64 31.69 Obese Never
#> 86: 10000086 Male 2009-05-01 59 33.12 Obese Never
#> 87: 10000087 Female 2010-05-21 64 33.07 Obese Never
#> 88: 10000088 Female 2008-04-03 55 18.61 Normal Never
#> 89: 10000089 Female 2007-10-26 61 37.47 Obese Previous
#> 90: 10000090 Female 2009-01-26 63 31.79 Obese Never
#> 91: 10000091 Male 2007-06-21 40 26.05 Overweight Never
#> 92: 10000092 Female 2006-12-14 68 30.07 Obese Never
#> 93: 10000093 Female 2006-04-17 45 20.86 Normal Previous
#> 94: 10000094 Male 2006-11-13 50 20.17 Normal Never
#> 95: 10000095 Male 2008-11-03 48 26.47 Overweight Never
#> 96: 10000096 Male 2006-06-11 61 19.61 Normal Previous
#> 97: 10000097 Female 2007-09-28 65 27.25 Overweight Never
#> 98: 10000098 Female 2007-12-07 61 33.34 Obese Previous
#> 99: 10000099 Male 2010-06-19 61 20.51 Normal Previous
#> 100: 10000100 Male 2010-04-17 59 22.14 Normal Never
#> eid p31 p53_i0 p21022 p21001_i0 bmi_cat p20116_i0
#> <int> <fctr> <IDat> <int> <num> <fctr> <fctr>
#> p1558_i0 p21000_i0 p22189 tdi_cat p54_i0
#> <fctr> <fctr> <num> <fctr> <fctr>
#> 1: Never White 0.80 Q4 (most deprived) Edinburgh
#> 2: Daily or almost daily White 3.43 Q4 (most deprived) Sheffield
#> 3: Once or twice a week White -7.00 Q1 (least deprived) Leeds
#> 4: Once or twice a week White -3.55 Q2 Sheffield
#> 5: Three or four times a week White -2.30 Q2 Newcastle
#> 6: Three or four times a week White -6.62 Q1 (least deprived) Liverpool
#> 7: Three or four times a week White -3.70 Q1 (least deprived) Nottingham
#> 8: One to three times a month White -3.79 Q1 (least deprived) Manchester
#> 9: Once or twice a week White -3.61 Q1 (least deprived) Bristol
#> 10: Special occasions only White -7.00 Q1 (least deprived) Bristol
#> 11: Once or twice a week White -0.62 Q3 Nottingham
#> 12: Special occasions only White -3.32 Q2 Leeds
#> 13: Once or twice a week White 3.57 Q4 (most deprived) Sheffield
#> 14: Three or four times a week White 1.25 Q4 (most deprived) Birmingham
#> 15: Special occasions only White -5.95 Q1 (least deprived) Leeds
#> 16: Three or four times a week White -0.99 Q3 Leeds
#> 17: Three or four times a week White -3.20 Q2 Sheffield
#> 18: Once or twice a week Other 1.54 Q4 (most deprived) Bristol
#> 19: Once or twice a week Black -1.13 Q3 Liverpool
#> 20: Once or twice a week Asian -3.08 Q2 Oxford
#> 21: One to three times a month White 0.10 Q3 Edinburgh
#> 22: Special occasions only White -0.81 Q3 Liverpool
#> 23: Once or twice a week White -1.83 Q2 Nottingham
#> 24: One to three times a month White 5.16 Q4 (most deprived) Newcastle
#> 25: Never White -2.99 Q2 Liverpool
#> 26: Special occasions only White -2.81 Q2 Nottingham
#> 27: Three or four times a week Other -6.25 Q1 (least deprived) Edinburgh
#> 28: Once or twice a week White -1.43 Q3 Bristol
#> 29: One to three times a month White 1.55 Q4 (most deprived) Edinburgh
#> 30: Never Other -7.00 Q1 (least deprived) Newcastle
#> 31: One to three times a month Asian -2.10 Q2 Leeds
#> 32: Special occasions only White -5.08 Q1 (least deprived) Nottingham
#> 33: One to three times a month White 3.31 Q4 (most deprived) Birmingham
#> 34: Three or four times a week White 3.05 Q4 (most deprived) Oxford
#> 35: Daily or almost daily Asian -0.23 Q3 Bristol
#> 36: Daily or almost daily White 3.27 Q4 (most deprived) Nottingham
#> 37: Once or twice a week White -4.08 Q1 (least deprived) Liverpool
#> 38: Daily or almost daily White 1.74 Q4 (most deprived) Nottingham
#> 39: Never White -3.17 Q2 Edinburgh
#> 40: Special occasions only White -0.27 Q3 Edinburgh
#> 41: One to three times a month White -2.26 Q2 Sheffield
#> 42: Three or four times a week White -2.19 Q2 Liverpool
#> 43: Once or twice a week White 0.45 Q3 Newcastle
#> 44: Once or twice a week White -5.47 Q1 (least deprived) Newcastle
#> 45: Three or four times a week Black -2.10 Q2 Leeds
#> 46: Three or four times a week Other -0.75 Q3 Bristol
#> 47: Special occasions only Mixed -2.59 Q2 Edinburgh
#> 48: Daily or almost daily White -0.97 Q3 Edinburgh
#> 49: Three or four times a week White -2.32 Q2 Manchester
#> 50: Never White 3.88 Q4 (most deprived) Oxford
#> 51: Once or twice a week White 0.99 Q4 (most deprived) Birmingham
#> 52: Special occasions only White 8.19 Q4 (most deprived) Liverpool
#> 53: One to three times a month Asian -3.84 Q1 (least deprived) Manchester
#> 54: Three or four times a week White 1.31 Q4 (most deprived) Leeds
#> 55: Never White 5.41 Q4 (most deprived) Bristol
#> 56: Three or four times a week White -0.34 Q3 Manchester
#> 57: Three or four times a week White -4.77 Q1 (least deprived) Birmingham
#> 58: Special occasions only White -4.52 Q1 (least deprived) Edinburgh
#> 59: Once or twice a week White -1.41 Q3 Sheffield
#> 60: Three or four times a week White 2.89 Q4 (most deprived) Nottingham
#> 61: Once or twice a week White 1.10 Q4 (most deprived) Liverpool
#> 62: Once or twice a week White -7.00 Q1 (least deprived) Newcastle
#> 63: Once or twice a week Asian -3.54 Q2 Sheffield
#> 64: Once or twice a week Asian -1.33 Q3 Newcastle
#> 65: Three or four times a week White -5.97 Q1 (least deprived) Sheffield
#> 66: Three or four times a week Other 0.92 Q4 (most deprived) Birmingham
#> 67: One to three times a month White -7.00 Q1 (least deprived) Liverpool
#> 68: Never White -0.84 Q3 Newcastle
#> 69: Special occasions only White -2.55 Q2 Oxford
#> 70: Daily or almost daily White -2.87 Q2 Bristol
#> 71: Three or four times a week White -2.21 Q2 Nottingham
#> 72: Never White -0.29 Q3 Sheffield
#> 73: Once or twice a week White -0.03 Q3 Nottingham
#> 74: Once or twice a week White -2.02 Q2 Birmingham
#> 75: Special occasions only White -7.00 Q1 (least deprived) Sheffield
#> 76: One to three times a month White -5.91 Q1 (least deprived) Edinburgh
#> 77: One to three times a month White -6.00 Q1 (least deprived) Bristol
#> 78: Once or twice a week White 1.14 Q4 (most deprived) Leeds
#> 79: Never White -2.08 Q2 Newcastle
#> 80: Never White -0.44 Q3 Nottingham
#> 81: Once or twice a week White -6.29 Q1 (least deprived) Sheffield
#> 82: Special occasions only White -3.01 Q2 Oxford
#> 83: One to three times a month White 0.50 Q3 Bristol
#> 84: Daily or almost daily White -1.87 Q2 Bristol
#> 85: Daily or almost daily White -1.67 Q3 Edinburgh
#> 86: Three or four times a week White -1.53 Q3 Leeds
#> 87: Special occasions only Asian 2.57 Q4 (most deprived) Sheffield
#> 88: One to three times a month Asian -3.27 Q2 Birmingham
#> 89: Once or twice a week White 0.86 Q4 (most deprived) Edinburgh
#> 90: Special occasions only White 1.58 Q4 (most deprived) Leeds
#> 91: Special occasions only White -5.11 Q1 (least deprived) Leeds
#> 92: Special occasions only White -0.91 Q3 Nottingham
#> 93: Once or twice a week White -1.34 Q3 Leeds
#> 94: Three or four times a week White 1.99 Q4 (most deprived) Manchester
#> 95: Three or four times a week White 1.63 Q4 (most deprived) Edinburgh
#> 96: One to three times a month White -1.31 Q3 Birmingham
#> 97: Never White -0.86 Q3 Newcastle
#> 98: Never Asian -3.60 Q1 (least deprived) Oxford
#> 99: Three or four times a week White -1.93 Q2 Leeds
#> 100: Special occasions only White -4.59 Q1 (least deprived) Nottingham
#> p1558_i0 p21000_i0 p22189 tdi_cat p54_i0
#> <fctr> <fctr> <num> <fctr> <fctr>
#> p22009_a1 p22009_a2 p22009_a3 p22009_a4 p22009_a5 p22009_a6 p22009_a7
#> <num> <num> <num> <num> <num> <num> <num>
#> 1: -0.167301 0.933511 2.897550 -0.757824 -0.543123 2.264042 -0.103786
#> 2: -0.130656 -0.074242 -0.883626 -0.866477 0.382939 0.892482 -1.832869
#> 3: -0.695522 -0.161808 0.655151 1.481191 -1.482718 -0.056449 -0.884601
#> 4: -0.350102 -1.579292 2.850919 -0.360459 0.554321 0.662341 -0.839361
#> 5: -0.189017 -1.045546 -0.232221 1.113754 -0.424829 -0.786348 1.260438
#> 6: 0.487763 0.469422 1.713567 0.181759 -0.745351 -1.574422 -0.224634
#> 7: 1.113334 -0.189777 -1.174456 0.525355 -0.874051 0.310874 -0.174565
#> 8: -2.225075 -0.701756 0.449677 -0.981061 0.004636 -2.518291 -0.711998
#> 9: 1.931000 -1.482116 -1.048883 -0.001996 0.350714 -0.877872 -0.023321
#> 10: 2.552516 2.119578 -1.481499 -0.119282 0.487663 -0.259697 -1.888016
#> 11: -1.159945 1.135382 -0.860095 -1.425225 -1.050909 1.225714 0.932839
#> 12: -0.708580 -0.862927 -1.046773 -0.487112 -0.642048 0.938000 0.728238
#> 13: 0.792713 -0.612063 -0.441223 -0.266867 -0.640479 0.766055 1.390336
#> 14: -0.077583 0.208381 -0.878694 0.233189 0.627576 -0.748508 -0.200386
#> 15: 1.295207 -0.070480 -0.012304 -0.405856 0.625887 1.238896 0.833432
#> 16: 0.498677 1.230273 0.684850 0.706107 2.128189 -0.169632 -1.209094
#> 17: -1.311384 0.052728 -0.923160 0.639357 0.726324 1.603320 0.742694
#> 18: 0.442729 0.067270 0.092131 -2.044178 -0.625239 -1.385054 0.322781
#> 19: -1.210134 -2.960872 -2.035076 -1.150163 -0.742389 -0.354183 1.110548
#> 20: -0.133701 -0.131156 0.141690 -1.517083 1.662553 -0.001632 1.022367
#> 21: -0.170740 -1.642790 0.416128 -0.369165 -0.154790 0.596080 -1.111288
#> 22: -0.906373 -0.459291 -1.067637 1.839604 1.221634 -0.480439 0.475287
#> 23: 1.387616 -0.799935 0.545423 0.333075 0.626241 0.466225 1.912456
#> 24: 0.007661 0.450120 2.361409 -1.265078 1.006358 -2.066581 -0.545649
#> 25: 0.432320 -0.243610 0.123427 0.438279 -0.348570 -0.448025 0.756541
#> 26: 2.069727 -0.386402 -0.285265 -0.342766 -1.151348 -0.371689 0.143223
#> 27: -0.299172 -0.543567 2.692738 0.139121 0.448878 0.214664 -0.087507
#> 28: 0.120326 -0.104971 0.771484 0.125064 0.844916 -0.646570 0.721604
#> 29: -0.247386 -1.608625 0.430888 -1.532547 0.430944 -1.178652 0.979477
#> 30: 1.032127 1.000861 1.607881 1.266611 1.666383 0.181938 -0.494343
#> 31: 0.391515 -0.109583 1.650372 0.934360 0.066167 0.186619 0.242835
#> 32: -0.488463 0.758399 -1.354097 -0.425153 -1.118262 -1.265316 0.750022
#> 33: 0.949933 2.158866 0.697077 -1.484392 0.485248 -1.209753 -1.244037
#> 34: -1.088838 -0.910272 -0.510066 -1.600966 -0.202024 -0.256062 1.458202
#> 35: 0.194449 1.129814 -0.458790 0.926501 1.035667 -0.036373 -0.921121
#> 36: -1.907991 1.367496 -0.776384 0.899950 -0.571400 0.988561 1.938695
#> 37: 0.695940 0.868715 -2.407559 -0.668240 -0.765660 0.422093 0.086772
#> 38: 0.059473 0.455355 0.811362 0.477883 -1.547452 1.682402 -0.577265
#> 39: -0.030321 1.724934 -0.864614 0.447563 -1.291301 0.214723 1.460351
#> 40: -1.279446 -0.459397 1.300186 1.673892 -1.171313 1.352227 0.106569
#> 41: -0.246897 -0.700109 0.594137 0.523136 -2.340479 -1.494254 1.700074
#> 42: 1.659156 0.234757 -1.996892 1.932536 0.697402 -0.964946 -0.412815
#> 43: 0.951393 0.275043 -0.924795 0.250014 0.763674 -0.960835 -0.521562
#> 44: 0.836329 1.180017 1.363546 0.747652 -0.985942 -1.768034 -0.217890
#> 45: 0.689379 1.107090 -0.525076 1.001080 -0.151333 0.286674 -1.394531
#> 46: 0.680120 0.173266 -2.188498 -0.078138 0.497549 -1.994878 0.441582
#> 47: -1.575690 -0.274206 3.197166 2.119135 0.840360 0.888606 -0.181488
#> 48: -1.732749 1.599261 0.576559 0.726264 0.410687 0.074206 -1.680047
#> 49: -0.525538 -2.009432 -0.275499 1.255804 0.435147 0.444397 0.535166
#> 50: 1.429044 -0.717711 2.323594 0.330100 0.196470 0.155193 0.137362
#> 51: 0.575568 0.419859 1.989531 1.291995 -1.033330 1.499038 0.182607
#> 52: -0.744880 -1.197410 0.480334 -0.002671 0.180129 0.329162 -0.113193
#> 53: 0.179211 0.324316 -1.602547 0.775425 1.000050 0.479179 -0.232366
#> 54: 0.239595 -0.720025 -0.395356 0.566818 -0.688364 -1.827809 -0.733823
#> 55: -0.381587 -0.503789 0.312776 1.234527 1.020051 0.858410 0.810055
#> 56: 0.565436 -0.744124 -0.915944 0.464898 0.516926 -0.267368 0.764403
#> 57: -0.142441 0.986380 -0.959187 0.179023 0.184234 -2.015487 1.062917
#> 58: 0.449610 -0.099491 -0.769075 -0.539391 -0.006873 0.189082 -1.050795
#> 59: 0.618100 -0.439168 -2.683505 -0.957746 1.735772 0.234917 -0.994984
#> 60: -0.378783 0.744348 1.531720 -1.202093 0.082428 0.681543 0.806601
#> 61: -0.346357 2.444763 0.921607 0.861231 -0.704033 0.610251 0.997658
#> 62: -0.641436 0.043339 -1.187295 -1.339344 0.413983 0.560116 -0.461048
#> 63: 0.402366 0.158722 -0.203531 0.624485 -0.582102 1.985917 -0.892021
#> 64: 0.334889 1.685726 -1.059116 -0.592947 -0.753884 1.619047 0.311166
#> 65: 0.068446 0.193289 0.661301 1.023763 -1.903373 0.186894 -1.231792
#> 66: -0.611944 -0.882818 -0.332906 0.860530 0.308242 -0.141437 0.502593
#> 67: 0.543230 -0.133278 1.264496 -0.663122 -0.405181 -0.746803 1.684135
#> 68: -1.106325 0.404407 0.990355 -0.435484 0.718920 0.965741 -2.053853
#> 69: -0.360561 0.609211 -1.928178 -0.934663 -0.756139 -0.879028 -0.629417
#> 70: -0.342652 -1.061653 -0.598284 -1.914276 -0.008274 -0.098032 0.710796
#> 71: 2.227117 1.696409 -1.289007 0.998890 -0.169303 1.019345 1.498547
#> 72: -1.413860 1.410223 -0.109967 0.294895 0.316556 -0.121652 -0.222923
#> 73: 1.249920 0.519783 0.294869 1.442109 -0.529953 0.456449 0.077967
#> 74: 1.146313 -0.570967 -1.400769 0.141037 1.010218 1.741749 0.333853
#> 75: -0.056931 -0.198385 0.818769 2.266482 0.011785 2.061114 1.267259
#> 76: 0.582482 -2.593127 0.837653 -0.659794 1.971097 1.378662 0.875927
#> 77: -0.449376 -1.197001 1.101297 -0.320500 2.608759 1.791927 -0.306598
#> 78: -0.437955 -1.275881 -1.305436 -1.096012 0.711149 -0.855787 -0.396869
#> 79: 0.204910 -0.669991 -0.557275 1.295048 -0.933696 -0.233608 0.270180
#> 80: 0.042636 1.669832 0.900621 0.080041 -0.050675 2.301381 -0.817080
#> 81: -0.139272 -0.241529 0.419947 1.514879 -0.452631 0.857142 -1.917899
#> 82: 1.413752 0.445831 -0.744557 -0.267573 1.483337 0.907279 -0.517595
#> 83: 0.725290 -0.536687 -0.034238 1.192664 1.382043 1.253812 0.269575
#> 84: 0.987208 0.628084 0.887786 1.592171 -0.512487 0.723844 0.150112
#> 85: -0.194773 0.894203 -1.391524 -0.996382 -0.043814 1.678971 -0.106967
#> 86: -0.771525 1.233174 0.249135 -1.013929 -1.091040 -0.677469 -1.541558
#> 87: 1.458821 0.520863 -1.664315 0.391663 0.853451 -0.381682 0.117164
#> 88: 0.409313 1.990056 -1.355402 -0.194529 0.563230 -0.484124 0.266182
#> 89: -0.691749 -0.952480 1.025397 0.305606 1.256291 -0.541260 2.029844
#> 90: 0.037466 0.625552 -1.391470 0.193761 -1.103960 -0.199618 -2.410035
#> 91: -0.619324 0.733247 -1.719858 -0.344900 0.366664 1.646931 -1.020434
#> 92: 0.145205 -0.581965 -0.885423 -1.197448 -0.516070 -0.879529 0.331663
#> 93: 1.084440 0.983395 -1.508749 -0.961515 0.914284 0.449303 -1.248321
#> 94: -0.478056 0.428493 0.133504 -1.550929 1.307789 1.834468 1.811659
#> 95: 0.117106 0.449927 -0.660418 -0.019580 -0.838963 -1.788062 1.262700
#> 96: 0.472257 1.196945 0.606116 0.594261 0.402567 0.902497 0.419379
#> 97: -0.557529 -0.075401 0.218462 1.172127 -1.090599 -1.008859 -0.683376
#> 98: -1.691285 0.645190 -0.816992 -0.690283 0.548400 1.432515 0.182231
#> 99: -0.207965 -0.236807 -0.498946 0.698759 -1.377343 0.801679 0.088018
#> 100: -0.851645 0.146521 0.047505 -1.379739 2.178992 0.372175 0.721259
#> p22009_a1 p22009_a2 p22009_a3 p22009_a4 p22009_a5 p22009_a6 p22009_a7
#> <num> <num> <num> <num> <num> <num> <num>
#> p22009_a8 p22009_a9 p22009_a10 grs_bmi dm_status dm_date dm_timing
#> <num> <num> <num> <num> <lgcl> <IDat> <int>
#> 1: -0.513748 0.046552 0.787167 1.112519 FALSE <NA> 0
#> 2: -0.145144 -1.121485 -0.837124 -2.007132 TRUE 1998-09-15 1
#> 3: 0.390236 -0.781560 0.168652 3.795837 FALSE <NA> 0
#> 4: 0.587041 0.849904 -1.370266 -0.810869 TRUE 2008-11-13 1
#> 5: -0.286372 1.763791 -0.125879 -1.209738 FALSE <NA> 0
#> 6: -0.495943 0.845642 1.117461 -1.299356 FALSE <NA> 0
#> 7: 0.924200 -0.544836 0.703672 2.098385 FALSE <NA> 0
#> 8: -0.072024 0.255268 -0.768516 0.060629 FALSE <NA> 0
#> 9: -1.055995 0.299373 0.855199 -0.628283 FALSE <NA> 0
#> 10: -1.390912 0.320643 2.165224 -2.814081 FALSE <NA> 0
#> 11: 0.909071 -0.039317 -0.142555 4.319070 FALSE <NA> 0
#> 12: 0.323011 -1.144893 1.208135 2.432015 FALSE <NA> 0
#> 13: 0.341688 0.560505 0.651923 1.679245 FALSE <NA> 0
#> 14: 1.220941 -0.593338 -0.236288 -0.262025 FALSE <NA> 0
#> 15: 1.336775 -1.180515 1.317811 -4.272808 FALSE <NA> 0
#> 16: 0.700212 0.307627 -2.395244 -0.471017 FALSE <NA> 0
#> 17: -1.811648 -0.145087 -0.113747 1.552933 FALSE <NA> 0
#> 18: -0.413141 -0.421328 1.278114 -1.141379 FALSE <NA> 0
#> 19: -1.779408 -1.176677 0.728602 -2.045139 FALSE <NA> 0
#> 20: 1.146526 -0.473557 0.726265 4.007615 FALSE <NA> 0
#> 21: -0.685340 0.935616 1.591013 -3.268891 FALSE <NA> 0
#> 22: -2.398492 0.912726 0.104937 -1.686300 FALSE <NA> 0
#> 23: -0.224778 -0.750590 0.504524 -1.712540 FALSE <NA> 0
#> 24: -0.470312 -1.067609 0.750711 -1.356506 FALSE <NA> 0
#> 25: 0.868934 -1.393820 -0.828815 2.930402 FALSE <NA> 0
#> 26: -0.414759 0.102401 0.709549 -3.341034 FALSE <NA> 0
#> 27: 1.976477 1.193254 0.949915 0.320075 FALSE <NA> 0
#> 28: 0.460253 -1.152602 -0.578856 -0.175955 FALSE <NA> 0
#> 29: -1.133249 1.448074 -1.234602 4.131925 FALSE <NA> 0
#> 30: -1.784115 1.147506 -0.218770 2.916791 FALSE <NA> 0
#> 31: -0.393233 0.317042 0.040909 -0.687064 FALSE <NA> 0
#> 32: -0.766540 0.059312 -0.641766 3.139010 FALSE <NA> 0
#> 33: -0.380048 1.083632 -0.961509 -1.826761 FALSE <NA> 0
#> 34: 0.369668 -0.552428 0.674827 -2.582297 FALSE <NA> 0
#> 35: -0.624760 -0.500888 -0.916078 3.194869 FALSE <NA> 0
#> 36: -1.484233 -0.183452 0.285324 1.119072 FALSE <NA> 0
#> 37: 1.619381 -0.235934 0.357701 -3.707059 FALSE <NA> 0
#> 38: 1.738407 0.183452 1.114078 2.044085 FALSE <NA> 0
#> 39: 2.400472 0.972897 -0.011303 -0.378932 FALSE <NA> 0
#> 40: 0.778690 0.109329 -2.020795 -0.143612 FALSE <NA> 0
#> 41: -0.313916 -1.670299 0.617905 3.930156 FALSE <NA> 0
#> 42: 0.014044 0.851406 -0.112820 -0.293229 FALSE <NA> 0
#> 43: -1.114417 1.893908 1.595115 0.117318 FALSE <NA> 0
#> 44: 0.910697 -2.493136 0.543894 -0.710083 TRUE 1992-09-04 1
#> 45: -1.713390 1.438513 -1.656857 1.646235 FALSE <NA> 0
#> 46: -1.305510 0.500697 0.102100 2.050548 FALSE <NA> 0
#> 47: 1.507239 0.692184 -1.054246 2.585712 FALSE <NA> 0
#> 48: 3.133248 -0.566944 -2.054017 0.800476 FALSE <NA> 0
#> 49: 0.113771 0.944947 0.827422 -0.345213 FALSE <NA> 0
#> 50: 1.857904 0.818692 -1.941544 -5.237289 FALSE <NA> 0
#> 51: -1.006754 0.015412 1.628972 3.376442 FALSE <NA> 0
#> 52: 0.963567 1.054929 -0.361928 3.324530 FALSE <NA> 0
#> 53: -0.296041 0.702285 -0.627071 2.386326 TRUE 2022-09-14 2
#> 54: -1.570503 -0.066376 -0.913173 -0.304495 FALSE <NA> 0
#> 55: -0.300049 1.407734 -1.665463 3.023763 FALSE <NA> 0
#> 56: -0.209713 0.561766 0.416811 3.605354 FALSE <NA> 0
#> 57: -1.135752 -0.203529 -1.711356 1.395993 FALSE <NA> 0
#> 58: 0.243609 -1.510867 0.320175 0.708307 FALSE <NA> 0
#> 59: 0.098203 0.596490 -1.038427 -3.976459 FALSE <NA> 0
#> 60: 1.521948 -1.278926 0.522365 4.620757 FALSE <NA> 0
#> 61: 1.129567 -1.163182 0.745140 1.455922 FALSE <NA> 0
#> 62: 0.522403 -0.834386 0.233473 1.807813 FALSE <NA> 0
#> 63: 0.721989 -2.020874 -2.053818 3.331116 TRUE 2008-09-22 2
#> 64: -1.186532 -0.033770 -1.488432 0.534639 FALSE <NA> 0
#> 65: 2.117013 -0.901183 2.125311 -1.445652 TRUE 2022-09-19 2
#> 66: -1.362718 -1.184255 1.626202 0.183381 FALSE <NA> 0
#> 67: -0.151830 -0.448417 -0.019244 -1.733684 FALSE <NA> 0
#> 68: -1.571536 0.558629 0.938659 2.451179 FALSE <NA> 0
#> 69: -0.488841 0.093082 -1.198031 0.222814 FALSE <NA> 0
#> 70: 2.181226 0.596114 0.647176 0.506829 FALSE <NA> 0
#> 71: 0.508018 -0.684097 -0.795558 0.010229 FALSE <NA> 0
#> 72: -0.348058 0.362708 -0.871621 3.583781 FALSE <NA> 0
#> 73: 0.757766 1.534152 0.066684 -2.293654 TRUE 2014-04-04 2
#> 74: -0.642032 -1.054193 0.648037 0.384359 FALSE <NA> 0
#> 75: 0.596727 -0.033242 -0.569110 -2.999100 FALSE <NA> 0
#> 76: -0.157263 0.945490 -0.597577 0.751620 TRUE 2008-09-11 2
#> 77: -1.238714 0.239258 1.026813 0.795372 FALSE <NA> 0
#> 78: 1.478998 1.559877 1.680177 1.735415 FALSE <NA> 0
#> 79: -0.116865 1.346588 0.056694 0.865389 FALSE <NA> 0
#> 80: -0.213269 -0.592909 -1.279846 2.458429 FALSE <NA> 0
#> 81: -1.259517 0.541914 -0.125757 0.790624 FALSE <NA> 0
#> 82: 1.547862 -0.927617 0.613150 1.072206 FALSE <NA> 0
#> 83: -1.060049 -0.416424 -1.241282 4.260138 FALSE <NA> 0
#> 84: 0.417718 1.007493 -0.705653 2.923568 FALSE <NA> 0
#> 85: 0.979285 -0.046593 1.196560 4.501097 FALSE <NA> 0
#> 86: 1.625200 0.407063 1.969152 2.616720 FALSE <NA> 0
#> 87: 1.092664 0.834942 -1.303630 -0.435218 FALSE <NA> 0
#> 88: 1.181383 -1.083633 -0.477963 1.027267 FALSE <NA> 0
#> 89: 0.351038 -0.583397 0.140972 -3.391506 FALSE <NA> 0
#> 90: -0.229348 0.779649 0.347427 1.341631 FALSE <NA> 0
#> 91: -1.079871 -0.114588 -0.049849 0.500136 FALSE <NA> 0
#> 92: 0.163908 -0.602883 -0.711819 3.363004 FALSE <NA> 0
#> 93: 0.551015 -0.071739 0.887205 2.162489 FALSE <NA> 0
#> 94: -1.030558 -1.962338 0.611096 3.617868 FALSE <NA> 0
#> 95: 0.817969 -1.081126 0.026018 6.621269 FALSE <NA> 0
#> 96: -0.479302 0.151172 0.197983 -1.286283 FALSE <NA> 0
#> 97: 0.382433 -1.752126 -0.799891 0.559932 FALSE <NA> 0
#> 98: 0.005772 -0.008797 -0.020903 0.675616 FALSE <NA> 0
#> 99: -0.350911 0.177058 0.553070 -0.637142 FALSE <NA> 0
#> 100: -1.736724 -1.393123 -1.224651 5.190728 TRUE 1992-04-25 1
#> p22009_a8 p22009_a9 p22009_a10 grs_bmi dm_status dm_date dm_timing
#> <num> <num> <num> <num> <lgcl> <IDat> <int>
#> dm_followup_end dm_followup_years htn_status htn_date htn_timing
#> <IDat> <num> <lgcl> <IDat> <int>
#> 1: 2022-10-31 16.6078 FALSE <NA> 0
#> 2: 2022-10-31 NA FALSE <NA> 0
#> 3: 2022-10-31 15.9425 FALSE <NA> 0
#> 4: 2022-10-31 NA FALSE <NA> 0
#> 5: 2022-10-31 13.0431 FALSE <NA> 0
#> 6: 2022-10-31 14.2286 TRUE 2010-04-08 2
#> 7: 2022-10-31 16.0219 TRUE 2011-01-07 2
#> 8: 2022-10-31 16.4244 FALSE <NA> 0
#> 9: 2022-10-31 14.1054 FALSE <NA> 0
#> 10: 2022-10-31 12.4709 TRUE 2020-12-31 2
#> 11: 2022-10-31 16.5585 FALSE <NA> 0
#> 12: 2022-10-31 14.0972 TRUE 2009-09-10 2
#> 13: 2022-10-31 16.0164 FALSE <NA> 0
#> 14: 2022-10-31 15.7317 FALSE <NA> 0
#> 15: 2022-10-31 16.5832 FALSE <NA> 0
#> 16: 2022-10-31 14.6940 TRUE 2004-02-19 1
#> 17: 2022-10-31 13.5332 FALSE <NA> 0
#> 18: 2022-10-31 13.8809 FALSE <NA> 0
#> 19: 2022-10-31 14.5024 FALSE <NA> 0
#> 20: 2022-10-31 16.0438 TRUE 2016-10-01 2
#> 21: 2022-10-31 14.8611 FALSE <NA> 0
#> 22: 2022-10-31 11.9535 FALSE <NA> 0
#> 23: 2022-10-31 16.6680 FALSE <NA> 0
#> 24: 2022-10-31 13.2485 TRUE 2008-03-09 1
#> 25: 2022-10-31 14.5079 FALSE <NA> 0
#> 26: 2022-10-31 12.3313 TRUE 2010-12-23 2
#> 27: 2022-10-31 14.1793 FALSE <NA> 0
#> 28: 2022-10-31 15.8001 TRUE 1995-04-11 1
#> 29: 2022-10-31 15.0856 FALSE <NA> 0
#> 30: 2022-10-31 15.6632 FALSE <NA> 0
#> 31: 2022-10-31 15.6222 TRUE 2004-02-21 1
#> 32: 2022-10-31 13.7221 FALSE <NA> 0
#> 33: 2022-10-31 15.2334 TRUE 1992-04-04 1
#> 34: 2022-10-31 13.2485 TRUE 1996-10-03 1
#> 35: 2022-10-31 14.2286 FALSE <NA> 0
#> 36: 2022-10-31 12.6242 FALSE <NA> 0
#> 37: 2022-10-31 13.6427 FALSE <NA> 0
#> 38: 2022-10-31 12.0630 TRUE 1995-02-05 1
#> 39: 2022-10-31 14.1793 FALSE <NA> 0
#> 40: 2022-10-31 15.9808 TRUE 2000-10-26 1
#> 41: 2022-10-31 14.3354 TRUE 2005-08-29 1
#> 42: 2022-10-31 15.5346 FALSE <NA> 0
#> 43: 2022-10-31 14.6119 FALSE <NA> 0
#> 44: 2022-10-31 NA FALSE <NA> 0
#> 45: 2022-10-31 16.7173 FALSE <NA> 0
#> 46: 2022-10-31 14.7515 FALSE <NA> 0
#> 47: 2022-10-31 13.3415 FALSE <NA> 0
#> 48: 2022-10-31 12.8214 TRUE 1990-01-09 1
#> 49: 2022-10-31 12.1971 FALSE <NA> 0
#> 50: 2022-10-31 16.7639 FALSE <NA> 0
#> 51: 2022-10-31 14.9076 TRUE 2017-07-22 2
#> 52: 2022-10-31 12.5394 FALSE <NA> 0
#> 53: 2022-09-14 13.2485 FALSE <NA> 0
#> 54: 2022-10-31 15.3922 FALSE <NA> 0
#> 55: 2022-10-31 15.1266 TRUE 2009-11-30 2
#> 56: 2022-10-31 16.1150 TRUE 2009-01-07 2
#> 57: 2022-10-31 12.6489 FALSE <NA> 0
#> 58: 2022-10-31 14.2505 FALSE <NA> 0
#> 59: 2022-10-31 16.0137 TRUE 2003-07-05 1
#> 60: 2022-10-31 12.8077 FALSE <NA> 0
#> 61: 2022-10-31 14.8611 FALSE <NA> 0
#> 62: 2022-10-31 15.8220 FALSE <NA> 0
#> 63: 2008-09-22 1.3251 FALSE <NA> 0
#> 64: 2022-10-31 14.7570 FALSE <NA> 0
#> 65: 2022-09-19 12.9035 FALSE <NA> 0
#> 66: 2022-10-31 14.7680 FALSE <NA> 0
#> 67: 2022-10-31 14.6448 FALSE <NA> 0
#> 68: 2022-10-31 14.4723 TRUE 2009-12-18 2
#> 69: 2022-10-31 13.4155 TRUE 1998-12-30 1
#> 70: 2022-10-31 14.7132 TRUE 1990-01-03 1
#> 71: 2022-10-31 13.4428 TRUE 1991-11-29 1
#> 72: 2022-10-31 16.0274 FALSE <NA> 0
#> 73: 2014-04-04 6.5955 TRUE 2021-08-17 2
#> 74: 2022-10-31 12.6105 FALSE <NA> 0
#> 75: 2022-10-31 14.7406 FALSE <NA> 0
#> 76: 2008-09-11 0.5530 FALSE <NA> 0
#> 77: 2022-10-31 15.3374 TRUE 2016-10-05 2
#> 78: 2022-10-31 15.6660 TRUE 2004-02-08 1
#> 79: 2022-10-31 15.5428 FALSE <NA> 0
#> 80: 2022-10-31 16.3176 FALSE <NA> 0
#> 81: 2022-10-31 16.1369 FALSE <NA> 0
#> 82: 2022-10-31 16.0986 FALSE <NA> 0
#> 83: 2022-10-31 15.0801 TRUE 2004-10-01 1
#> 84: 2022-10-31 12.9062 FALSE <NA> 0
#> 85: 2022-10-31 16.7201 FALSE <NA> 0
#> 86: 2022-10-31 13.5003 FALSE <NA> 0
#> 87: 2022-10-31 12.4463 FALSE <NA> 0
#> 88: 2022-10-31 14.5763 FALSE <NA> 0
#> 89: 2022-10-31 15.0144 TRUE 2012-08-25 2
#> 90: 2022-10-31 13.7604 FALSE <NA> 0
#> 91: 2022-10-31 15.3621 TRUE 1996-02-12 1
#> 92: 2022-10-31 15.8795 FALSE <NA> 0
#> 93: 2022-10-31 16.5394 FALSE <NA> 0
#> 94: 2022-10-31 15.9644 TRUE 1997-07-21 1
#> 95: 2022-10-31 13.9904 FALSE <NA> 0
#> 96: 2022-10-31 16.3888 TRUE 2008-10-08 2
#> 97: 2022-10-31 15.0910 FALSE <NA> 0
#> 98: 2022-10-31 14.8994 FALSE <NA> 0
#> 99: 2022-10-31 12.3669 TRUE 2001-01-30 1
#> 100: 2022-10-31 NA FALSE <NA> 0
#> dm_followup_end dm_followup_years htn_status htn_date htn_timing
#> <IDat> <num> <lgcl> <IDat> <int>
#> htn_followup_end htn_followup_years age_at_dm
#> <IDat> <num> <num>
#> 1: 2022-10-31 16.6078 NA
#> 2: 2022-10-31 14.3299 39.20397
#> 3: 2022-10-31 15.9425 NA
#> 4: 2022-10-31 12.3258 65.36277
#> 5: 2022-10-31 13.0431 NA
#> 6: 2010-04-08 1.6646 NA
#> 7: 2011-01-07 4.2081 NA
#> 8: 2022-10-31 16.4244 NA
#> 9: 2022-10-31 14.1054 NA
#> 10: 2020-12-31 10.6393 NA
#> 11: 2022-10-31 16.5585 NA
#> 12: 2009-09-10 0.9582 NA
#> 13: 2022-10-31 16.0164 NA
#> 14: 2022-10-31 15.7317 NA
#> 15: 2022-10-31 16.5832 NA
#> 16: 2022-10-31 NA NA
#> 17: 2022-10-31 13.5332 NA
#> 18: 2022-10-31 13.8809 NA
#> 19: 2022-10-31 14.5024 NA
#> 20: 2016-10-01 9.9630 NA
#> 21: 2022-10-31 14.8611 NA
#> 22: 2022-10-31 11.9535 NA
#> 23: 2022-10-31 16.6680 NA
#> 24: 2022-10-31 NA NA
#> 25: 2022-10-31 14.5079 NA
#> 26: 2010-12-23 0.4764 NA
#> 27: 2022-10-31 14.1793 NA
#> 28: 2022-10-31 NA NA
#> 29: 2022-10-31 15.0856 NA
#> 30: 2022-10-31 15.6632 NA
#> 31: 2022-10-31 NA NA
#> 32: 2022-10-31 13.7221 NA
#> 33: 2022-10-31 NA NA
#> 34: 2022-10-31 NA NA
#> 35: 2022-10-31 14.2286 NA
#> 36: 2022-10-31 12.6242 NA
#> 37: 2022-10-31 13.6427 NA
#> 38: 2022-10-31 NA NA
#> 39: 2022-10-31 14.1793 NA
#> 40: 2022-10-31 NA NA
#> 41: 2022-10-31 NA NA
#> 42: 2022-10-31 15.5346 NA
#> 43: 2022-10-31 14.6119 NA
#> 44: 2022-10-31 12.5120 38.35729
#> 45: 2022-10-31 16.7173 NA
#> 46: 2022-10-31 14.7515 NA
#> 47: 2022-10-31 13.3415 NA
#> 48: 2022-10-31 NA NA
#> 49: 2022-10-31 12.1971 NA
#> 50: 2022-10-31 16.7639 NA
#> 51: 2017-07-22 9.6318 NA
#> 52: 2022-10-31 12.5394 NA
#> 53: 2022-10-31 13.3771 60.24846
#> 54: 2022-10-31 15.3922 NA
#> 55: 2009-11-30 2.2094 NA
#> 56: 2009-01-07 2.3025 NA
#> 57: 2022-10-31 12.6489 NA
#> 58: 2022-10-31 14.2505 NA
#> 59: 2022-10-31 NA NA
#> 60: 2022-10-31 12.8077 NA
#> 61: 2022-10-31 14.8611 NA
#> 62: 2022-10-31 15.8220 NA
#> 63: 2022-10-31 15.4305 68.32512
#> 64: 2022-10-31 14.7570 NA
#> 65: 2022-10-31 13.0185 56.90349
#> 66: 2022-10-31 14.7680 NA
#> 67: 2022-10-31 14.6448 NA
#> 68: 2009-12-18 1.6044 NA
#> 69: 2022-10-31 NA NA
#> 70: 2022-10-31 NA NA
#> 71: 2022-10-31 NA NA
#> 72: 2022-10-31 16.0274 NA
#> 73: 2021-08-17 13.9658 76.59548
#> 74: 2022-10-31 12.6105 NA
#> 75: 2022-10-31 14.7406 NA
#> 76: 2022-10-31 14.6886 64.55305
#> 77: 2016-10-05 9.2676 NA
#> 78: 2022-10-31 NA NA
#> 79: 2022-10-31 15.5428 NA
#> 80: 2022-10-31 16.3176 NA
#> 81: 2022-10-31 16.1369 NA
#> 82: 2022-10-31 16.0986 NA
#> 83: 2022-10-31 NA NA
#> 84: 2022-10-31 12.9062 NA
#> 85: 2022-10-31 16.7201 NA
#> 86: 2022-10-31 13.5003 NA
#> 87: 2022-10-31 12.4463 NA
#> 88: 2022-10-31 14.5763 NA
#> 89: 2012-08-25 4.8323 NA
#> 90: 2022-10-31 13.7604 NA
#> 91: 2022-10-31 NA NA
#> 92: 2022-10-31 15.8795 NA
#> 93: 2022-10-31 16.5394 NA
#> 94: 2022-10-31 NA NA
#> 95: 2022-10-31 13.9904 NA
#> 96: 2008-10-08 2.3272 NA
#> 97: 2022-10-31 15.0910 NA
#> 98: 2022-10-31 14.8994 NA
#> 99: 2022-10-31 NA NA
#> 100: 2022-10-31 12.5394 41.02327
#> htn_followup_end htn_followup_years age_at_dm
#> <IDat> <num> <num>