Abstract
Background
Chronic kidney disease (CKD) is common in aging men and women. In contrast to other European countries, Germany lacks CKD registries. The aim of this study was to determine the incidence of CKD stages 2–5 in men and women in Germany. Furthermore, differences between the sexes in terms of comorbidities, potentially inappropriate medications (PIM), and healthcare utilization were examined.
Methods
In this retrospective observational study, claims data from members of a statutory health insurance fund aged 18 years or older with incident CKD between 2011 and 2018 were analyzed. Incident CKD was defined as having two confirmed diagnoses of CKD stages 2–5 from outpatient care or one primary or secondary diagnosis from inpatient care.
Results
The age- and sex-standardized incidence of all CKD stages was 945/100 000 persons between 2011 and 2018. Incident CKD, especially stages 3 and 4, occurred more frequently in women, while the incidence of stages 2 and 5 was higher in men. While women visited their GP more frequently and were prescribed PIMs more often, men were more likely to visit a nephrologist and were more often hospitalized after the incident CKD diagnosis.
Conclusion
More awareness needs to be raised towards the early detection of CKD and the use of PIMs, especially in women. Improved care coordination is needed to avoid an overprovision of patients with uncomplicated incident stages and ensure that patients with advanced CKD stages get timely access to specialist care.
Keywords: chronic kidney disease, claims data, healthcare utilization, potentially inappropriate medications, sex
Graphical Abstract
Graphical Abstract.
KEY LEARNING POINTS.
What is already known about this subject?
Chronic kidney disease (CKD) is frequently found in ageing women in men, and the incidence and prevalence of the disease is generally higher in women compared with men.
Differences between men and women are likely due to complex interactions between biological, lifestyle as well as socio-demographic factors, and have not been fully understood.
Germany lacks CKD registries and therefore data for patients with CKD is sparse.
What this study adds?
Higher incidence rates of CKD stages 2–5 were found in women compared with men. The incidence of stages 3 and 4 was higher in women, while stages 2 and 5 were more often diagnosed in men.
Men and women differed in terms of most cardiovascular, metabolic as well as renal comorbidities. Potentially inadequate medications (PIM) were more frequently prescribed in women.
While women with incident CKD visited a general practitioner (GP) more frequently, men were more likely to visit a nephrologist and were more often hospitalized in the first year after the incident CKD diagnosis.
What impact this may have on practice or policy?
Increased awareness is needed to avoid the use of PIMs in patients with CKD, especially in women.
The coordination of care should be improved to ensure that patients with advanced stages of CKD get timely access to specialist care and to avoid a possible overprovision of patients with lower, uncomplicated incident CKD stages, who can be monitored and treated by a GP alone.
INTRODUCTION
Chronic kidney disease (CKD) is mainly found in older adults and affects both men and women [1]. Even though the age-standardized prevalence of CKD has decreased in Germany by 4.7% since the 1970s [2], it is still one of the highest compared with other European countries [3].
There is growing evidence that sex (biological) and gender (socio-cultural) are important factors in the etiology, progression and therapy of CKD [4]. Previous studies found a higher prevalence of CKD in women than in men, especially in non-dialysis-dependent stages [5–7]. The disease seems to progress more rapidly in men with higher rates of renal replacement therapy and increased mortality [2, 5, 8]. Those differences are likely due to complex interactions between biological, lifestyle and socio-demographic factors and have not been fully understood [4, 7]. Disparities between the sexes in healthcare delivery and access to healthcare may contribute as modifying factors, especially in those with advanced CKD [2, 4].
Patients with CKD are at an increased risk for overall morbidity and (cardiovascular) mortality [1, 2, 9, 10]. The prevention of disease progression is the primary goal of therapy and is closely linked to early detection and adequate treatment of the underlying disease [3]. Healthcare data of patients with CKD can provide valuable knowledge to improve therapeutic management. In contrast to other European countries [11], Germany lacks CKD registries and therefore, data on the incidence of CKD are sparse.
The aim of this study was to determine the incidence of CKD stages 2–5 in men and women in Germany using claims data. A further aim was to explore possible differences between the sexes in terms of comorbidities, lifestyle factors and medications, and to analyze the utilization of in- and outpatient healthcare in this cohort of adults with incident CKD.
MATERIALS AND METHODS
Data source and data set
In this retrospective cohort study, data from a regional statutory health insurance fund [Allgemeine Ortskrankenkasse (AOK) Baden-Württemberg] from both outpatient and inpatient care were analyzed covering a study period from 2011 to 2018. The health insurance fund counted 4 250 889 members in 2018, corresponding to 36.6% of the inhabitants of the federal state of Baden-Württemberg.
Data were anonymized in a two-step process by the statutory health insurance fund prior to data transmission. The data set comprised socio-demographic information (age, sex, area of residence [12]), quarter and year of death, insurance time, and data from inpatient and outpatient care [International Classification of Diseases 10th revision, German modification (ICD-10-GM) codes, Anatomical Therapeutic Chemical (ATC) Classification System codes], as well as data on dialysis (hemo- and peritoneal dialysis). ICD-10-GM codes were available from both in- and outpatient care, whereas ATC codes were available from outpatient care only.
Study population
The study population comprised all members of the statutory health insurance fund, who were at least 18 years of age and had an incident diagnosis of stages 2–5 of CKD between 2011 and 2018. CKD stage 1 [glomerular filtration rate (GFR) 90 to <120 mL/min/1.73 m2] was not included in the analysis since the coding quality of this stage is presumably poor in Germany. Stages of CKD were defined according to GFR categories proposed by the KDIGO 2012 Clinical Practice Guideline [1] and using the following ICD-10-GM codes:
Stage 2 (GFR 60 to <90 mL/min/1.73 m2): N18.82, N18.2
Stage 3 (GFR 30 to <60 mL/min/1.73 m2): N18.83, N18.3
Stage 4 (GFR 15 to <30 mL/min/1.73 m2): N18.84, N18.4
Stage 5 (GFR <15 mL/min/1.73 m2): N18.5
In contrast to the KDIGO guideline, ICD-10-GM does not differentiate between CKD stages 3a and 3b, and therefore CKD stage 3 was not further subdivided in this analysis.
A CKD diagnosis from outpatient care was recorded as an incident diagnosis if it occurred in two quarters within 1 year (M2Q criterion) and if it was a confirmed diagnosis [13]. If the M2Q criterion was met, the first quarter with a CKD diagnosis was defined as the incident quarter. In the inpatient setting, one primary or secondary diagnosis of CKD was sufficient to be counted as an incident diagnosis. When multiple stages of CKD occurred in the incident quarter, the higher stage was chosen as the incident stage. To ensure that the recorded incident diagnosis was indeed the first one, we determined a 2-year period prior to the incident diagnosis that could not contain any previous CKD diagnosis. In addition, patients with CKD had to be insured with the same statutory health insurance fund at least 2 years prior to the incident diagnosis. Patients were excluded if they had a history of kidney transplantation or received chronic dialysis (≥12 sessions of hemodialysis per quarter or one session of peritoneal dialysis) prior to the incident CKD diagnosis. An overview of all exclusion criteria is shown in Fig. 1. The final study population consisted of 282 836 men and women with incident CKD stages 2 to 5 between 2011 and 2018.
Figure 1:
Flow-chart of study exclusion criteria. CKD, chronic kidney disease; RRT, renal replacement therapy.
Information on the definition of comorbidities, lifestyle factors and healthcare utilization can be found in the Supplementary materials and methods.
Statistical analysis
Differences between men and women were analyzed using Chi2-test for nominal variables, Student's t-test for metric variables, and Wilcoxon–Mann–Whitney test for ordinal and non-normally distributed metric variables, respectively. The annual incidence of CKD was directly standardized according to the age and sex distribution of the German standard population in 2011 [14]. The 95% confidence intervals were calculated for the age- and sex-standardized incidence rates assuming that they follow a normal distribution.
The association between sex and the number of hospitalizations in the first year after the incident CKD diagnosis was examined using negative binomial regression. More detailed information on the regression analysis can be found in the Supplementary materials and methods.
All statistical analyses were conducted using IBM SPSS for Windows, version 27 (IBM Corp., Armonk, NY, USA). This study was reported according to the Strengthening the Reporting of Observational studies in Epidemiology (STROBE) statement. Ethics approval for this study was obtained from the Ethics Committee of the University Medical Faculty and the University Hospital Tübingen (reference number: 380/2020BO).
RESULTS
Incident stages 2–5 of CKD were found in 282 836 men and women aged 18 years or older. Baseline characteristics of the study population stratified by sex and incident CKD stage are shown in Table 1 and Supplementary data, Table S1. The mean age of the whole study population was 76 years (SD ±11 years). Women made up 56% of the study population and were significantly older than men at the time of the incident diagnosis.
Table 1:
Baseline characteristics of adults with incident CKD between 2011 and 2018 stratified by sex and incident stage (n = 282 836).
| Women | Men | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Total | CKD stage 2 | CKD stage 3 | CKD stage 4 | CKD stage 5 | Total | CKD stage 2 | CKD stage 3 | CKD stage 4 | CKD stage 5 | |
| n = 158 727 | n = 47 848 | n = 94 457 | n = 14 463 | n = 1959 | n = 124 109 | n = 44 171 | n = 68 902 | n = 8818 | n = 2218 | |
| Socio-demographic characteristics | ||||||||||
| Age, years, mean ± SD | 78 ± 11 | 74 ± 12 | 80 ± 10 | 81 ± 10 | 75 ± 14 | 74 ± 11 | 71 ± 12 | 76 ± 11 | 77 ± 12 | 70 ± 11 |
| Area of residence | ||||||||||
| Peripheral area | 45 124 (28.4) | 13 987 (29.2) | 26 525 (28.1) | 4056 (28.0) | 556 (28.4) | 35 399 (28.5) | 13 199 (29.9) | 19 057 (27.7) | 2539 (28.8) | 604 (27.2) |
| Intermediate area | 53 645 (33.8) | 16 127 (33.7) | 31 880 (33.8) | 4998 (34.6) | 640 (32.7) | 40 492 (32.6) | 14 407 (32.6) | 22 452 (32.6) | 2937 (31.4) | 696 (31.4) |
| Central area | 59 511 (37.5) | 17 605 (36.8) | 35 784 (37.9) | 5371 (37.1) | 751 (38.3) | 47 722 (38.5) | 16 388 (37.1) | 27 120 (39.4) | 3311 (37.5) | 903 (40.7) |
| Not specified | 447 (0.3) | 129 (0.3) | 268 (0.3) | 28 (0.3) | 12 (0.6) | 496 (0.4) | 177 (0.4) | 273 (0.4) | 31 (0.4) | 15 (0.7) |
| Lifestyle factors | ||||||||||
| Smokinga | 8634 (5.4) | 3192 (6.7) | 4689 (5.0) | 636 (4.4) | 117 (6.0) | 16 185 (13.0) | 6110 (13.8) | 8693 (12.6) | 1064 (12.1) | 318 (14.3) |
| Obesitya | 50 332 (31.7) | 15 149 (31.7) | 30 239 (32.0) | 4365 (30.2) | 574 (29.6) | 34 614 (27.9) | 12 579 (28.5) | 19 280 (28.0) | 2218 (25.2) | 537 (24.2) |
| Alcohola | 3084 (1.9) | 906 (1.9) | 1822 (1.9) | 286 (2.0) | 70 (3.6) | 9392 (7.6) | 3166 (7.2) | 5249 (7.6) | 737 (8.4) | 240 (10.8) |
| History of disease/comorbidities | ||||||||||
| Diabetes mellitus | ||||||||||
| Type 1 | 522 (0.3) | 200 (0.4) | 261 (0.3) | 53 (0.4) | 8 (0.4) | 507 (0.4) | 217 (0.5) | 250 (0.4) | 30 (0.3) | 10 (0.5) |
| Type 2 | 74 688 (47.1) | 20 559 (43.0) | 45 713 (48.4) | 7484 (51.7) | 932 (47.6) | 60 183 (48.5) | 20 396 (46.2) | 34 473 (50.0) | 4307 (48.8) | 1007 (45.4) |
| Hyperlipidemia | 92 470 (58.3) | 27 618 (57.7) | 55 967 (59.3) | 7955 (55.0) | 930 (47.5) | 73 934 (59.6) | 26 462 (59.9) | 41 671 (60.5) | 4716 (53.5) | 1085 (48.9) |
| Hypertension | 143 414 (90.4) | 40 740 (85.1) | 87 565 (92.7) | 13 419 (92.9) | 1680 (85.8) | 108 128 (87.1) | 37 056 (83.9) | 61 570 (89.4) | 7745 (87.8) | 1757 (79.2) |
| Stroke | 19 351 (12.2) | 4914 (10.3) | 12 361 (13.1) | 1887 (13.0) | 189 (9.6) | 16 186 (13.0) | 4996 (11.3) | 9827 (14.3) | 1143 (13.0) | 220 (9.9) |
| Ischemic heart disease | 52 875 (33.3) | 13 277 (27.7) | 33 803 (35.8) | 5238 (36.2) | 557 (28.4) | 53 581 (43.2) | 17 255 (39.1) | 31 819 (46.2) | 3766 (42.7) | 741 (33.4) |
| Heart failure | 60 747 (38.3) | 13 773 (28.8) | 39 322 (41.6) | 6928 (47.9) | 724 (37.0) | 44 418 (35.8) | 12 775 (38.9) | 27 318 (39.6) | 3640 (41.3) | 685 (30.9) |
| Atrial fibrillation/flutter | 38 918 (24.5) | 8503 (17.8) | 25 774 (27.3) | 4200 (29.0) | 441 (22.5) | 31 572 (25.4) | 9081 (20.6) | 19 597 (28.4) | 2438 (27.6) | 456 (20.6) |
| PAD | 25 292 (15.3) | 6103 (12.8) | 15 417 (16.3) | 2485 (17.2) | 287 (14.7) | 28 379 (22.9) | 8684 (19.7) | 17 087 (24.8) | 2127 (24.1) | 481 (21.7) |
| Acute renal failure | 389 (0.2) | 72 (0.2) | 235 (0.2) | 66 (0.5) | 16 (0.8) | 426 (0.3) | 104 (0.2) | 258 (0.4) | 44 (0.5) | 20 (0.9) |
| Glomerulonephritis | 5960 (3.8) | 1554 (3.2) | 3625 (3.8) | 704 (4.9) | 77 (3.9) | 5927 (4.8) | 1816 (4.1) | 3543 (5.1) | 473 (5.4) | 95 (4.3) |
| Nephritic syndrome | 824 (0.5) | 247 (0.5) | 426 (0.5) | 116 (0.8) | 35 (1.8) | 872 (0.7) | 292 (0.7) | 417 (0.6) | 120 (1.4) | 43 (1.9) |
| Nephrotic syndrome | 291 (0.2) | 84 (0.2) | 135 (0.1) | 58 (0.4) | 14 (0.7) | 370 (0.3) | 105 (0.2) | 175 (0.3) | 64 (0.7) | 26 (1.2) |
| Tubulointerstitial nephritis | 2476 (1.6) | 749 (1.6) | 1453 (1.5) | 233 (1.6) | 41 (2.1) | 1096 (0.9) | 382 (0.9) | 382 (0.9) | 597 (0.9) | 89 (1.0) |
| Polycystic kidney disease | 507 (0.3) | 155 (0.3) | 281 (0.3) | 58 (0.4) | 13 (0.7) | 630 (0.5) | 221 (0.5) | 340 (0.5) | 52 (0.6) | 17 (0.8) |
| Amyloidosis | 184 (0.1) | 33 (0.1) | 117 (0.1) | 22 (0.2) | 12 (0.6) | 225 (0.2) | 52 (0.1) | 141 (0.2) | 25 (0.3) | 7 (0.3) |
| Affective mood disorders | 59 373 (37.4) | 18 060 (37.7) | 35 580 (37.7) | 5093 (35.2) | 640 (32.7) | 26 476 (21.3) | 9599 (21.7) | 14 706 (21.3) | 1764 (20.0) | 407 (18.3) |
| Dementia | 10 391 (6.5) | 2468 (5.2) | 6710 (7.1) | 1119 (7.7) | 94 (4.8) | 5908 (4.8) | 1780 (4.0) | 3529 (5.1) | 510 (5.8) | 89 (4.0) |
| Rheumatologic disease | 23 219 (14.6) | 6892 (14.4) | 14 105 (14.9) | 1965 (13.6) | 257 (13.1) | 12 690 (10.2) | 4208 (9.5) | 7289 (10.6) | 966 (11.0) | 227 (10.2) |
| Hyperaldosteronism | 337 (0.2) | 77 (0.2) | 223 (0.2) | 25 (0.2) | 2 (0.1) | 300 (0.2) | 90 (0.2) | 175 (0.3) | 30 (0.3) | 5 (0.2) |
| Thyroid disease | 68 082 (43) | 21 589 (45) | 40 158 (43) | 5627 (39) | 708 (36) | 26 184 (21) | 9363 (21) | 14 730 (21) | 1703 (19) | 388 (18) |
| Hyperuricemia | 31 513 (20) | 7238 (15) | 20 148 (21) | 3688 (26) | 439 (22) | 35 747 (29) | 11 114 (25) | 21 285 (31) | 2749 (31) | 599 (27) |
| Chronic obstructive lung disease | 34 161 (22) | 10 042 (21) | 20 697 (22) | 3050 (21) | 372 (19) | 32 710 (26) | 10 973 (25) | 18 885 (27) | 2342 (27) | 510 (23) |
| Chronic liver disease | 19 682 (12) | 6024 (13) | 11 680 (12) | 1654 (11) | 254 (13) | 20 873 (17) | 7444 (17) | 11 560 (17) | 1479 (17) | 390 (18) |
| Acute viral hepatitis | 615 (0.4) | 205 (0.4) | 351 (0.4) | 49 (0.3) | 10 (0.5) | 638 (0.5) | 213 (0.5) | 365 (0.5) | 43 (0.5) | 26 (1) |
| HIV/AIDs | 109 (0.1) | 33 (0.1) | 61 (0.1) | 13 (0.1) | 2 (0.1) | 197 (0.2) | 71 (0.2) | 105 (0.2) | 5 (0.1) | 16 (0.7) |
| IBD | 1661 (1) | 539 (1) | 963 (1) | 135 (0.9) | 25 (1) | 1434 (1) | 538 (1) | 771 (1) | 100 (1) | 25 (1) |
| Any malignancies | 34 586 (22) | 9683 (20) | 21 222 (23) | 3247 (23) | 434 (22) | 36 001 (29) | 11 252 (26) | 21 335 (31) | 2832 (32) | 582 (26) |
| Multiple myeloma | 516 (0.3) | 111 (0.2) | 282 (0.3) | 95 (0.7) | 28 (1) | 497 (0.4) | 114 (0.3) | 304 (0.4) | 52 (0.6) | 27 (1) |
Data are presented as n (%) unless otherwise indicated.
aSmoking: ICD-10 code F17 (behavioral disorders due to smoking); obesity: ICD-10 codes E65, E66, E67, E68; alcohol: ICD-10 code F10 (behavioral disorders due to alcohol).
HIV, human immunodeficiency virus; IBD, inflammatory bowel disease; ICD-10, International Classification of Diseases 10th revision.
Incidence of CKD
The average age- and sex-standardized incidence of all CKD stages was 945/100 000 persons between 2011 and 2018. Figure 2 and Supplementary data, Table S2 show the crude and age- and sex-standardized incidence of CKD stages 2–5. With an average annual incidence of 541/100 000 persons, CKD stage 3 was the most frequent of all stages, followed by stage 2 with an average annual incidence of 313/100 000 persons. The incidence of CKD stages 4 and 5 was 77/100 000 and 14/100 000 persons, respectively (see Table 2 and Supplementary data, Table S2). Over the years, a trend towards decreasing incidence rates was observed in CKD stages 4 and 5, whereas the incidence rate of CKD stage 3 proved to be more consistent apart from a peak in 2013. The incidence rate of CKD stage 2 has increased continuously since 2012 except for 2018.
Figure 2:
Age- and sex-standardized incidence of chronic kidney disease in adults between 2011 and 2018. The 95% confidence intervals are presented as transparent areas behind each curve.
Table 2:
Utilization of outpatient care in adults with incident chronic kidney disease stratified by sex and incident stage (n = 209 498).
| Women | Men | |||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Total | CKD stage 2 | CKD stage 3 | CKD stage 4 | CKD stage 5 | P-value | Total | CKD stage 2 | CKD stage 3 | CKD stage 4 | CKD stage 5 | P-value | P-value | ||||
| No visit to nephrologist | 103 735 (88) | 35 830 (92) | 61 077 (88) | 6339 (73) | 489 (46) | <.001a | 74 979 (82) | 31 764 (89) | 39 754 (81) | 2973 (60) | 488 (38) | <.001a | <.001a | |||
| Visit to nephrologist | 14.504 (12) | 3.017 (8) | 8.521 (12) | 2.389 (27) | 577 (54) | 16 290 (18) | 3928 (11) | 9542 (19) | 2026 (41) | 784 (62) | ||||||
| Time to 1st visit to nephrologist in quarters, median (IQR) | 1 (0–6) | 1 (0–7) | 1 (0–7) | 0 (0–4) | 0 (0–1) | <.001b | 1 (0–6) | 1 (0–8) | 1 (0–7) | 0 (0–3) | 0 (0–0) | <.001b | <.585c | |||
| Frequency of visits to nephrologist in quarters/yeard | <.001b | <.001b | <.001c | |||||||||||||
| <1 quarter/year | 7104 (49) | 1633 (54) | 4528 (53) | 842 (35) | 101 (18) | 7467 (46) | 2148 (55) | 4647 (49) | 531 (26) | 141 (18) | ||||||
| 1–<2 quarters/year | 3659 (25) | 812 (27) | 2192 (26) | 575 (24) | 80 (14) | 4143 (25) | 978 (25) | 2573 (27) | 495 (24) | 97 (12) | ||||||
| 2–<3 quarters/year | 1947 (13) | 349 (12) | 1077 (13) | 456 (19) | 65 (11) | 2268 (14) | 504 (13) | 1303 (14) | 386 (19) | 75 (10) | ||||||
| 3–<4 quarters/year | 1132 (8) | 158 (5) | 528 (6) | 352 (15) | 94 (16) | 1518 (9) | 212 (5) | 769 (8) | 401 (20) | 136 (14) | ||||||
| 4 quarters/year | 662 (5) | 65 (2) | 196 (2) | 164 (7) | 237 (41) | 884 (5) | 86 (2) | 250 (3) | 213 (11) | 335 (43) | ||||||
| No visit to GP | 176 (0.1) | 38 (0.1) | 115 (0.2) | 16 (0.2) | 7 (0.7) | <.001a | 199 (0.2) | 63 (0.2) | 114 (0.2) | 13 (0.03) | 9 (0.7) | <.001a | <.001a | |||
| Visit to GP | 118 063 (100) | 38 809 (100) | 69 483 (100) | 8712 (100) | 1059 (99) | 91 060 (100) | 35 629 (100) | 49 182 (100) | 4986 (100) | 1263 (99) | ||||||
| Frequency of visits to GP in quarters/yeard | <.001b | <.001b | <.001c | |||||||||||||
| <1 quarter/year | 479 (0.4) | 168 (0.4) | 249 (0.4) | 38 (0.4) | 24 (2) | 576 (0.6) | 234 (0.7) | 269 (0.5) | 41 (0.8) | 32 (3) | ||||||
| 1–<2 quarters/year | 900 (0.8) | 371 (1) | 426 (0.6) | 68 (0.8) | 35 (3) | 1159 (1) | 498 (1) | 511 (1) | 86 (2) | 64 (5) | ||||||
| 2–<3 quarters/year | 1962 (2) | 897 (2) | 910 (1) | 114 (1) | 41 (4) | 2375 (3) | 1149 (3) | 992 (2) | 139 (3) | 95 (8) | ||||||
| 3–<4 quarters/year | 11 291 (10) | 4592 (12) | 5891 (9) | 684 (8) | 124 (12) | 11 096 (12) | 4863 (14) | 5440 (11) | 590 (12) | 203 (16) | ||||||
| 4 quarters/year | 103 431 (88) | 32 781 (85) | 62 007 (89) | 7808 (90) | 835 (79) | 75 854 (83) | 28 885 (81) | 41 970 (85) | 4130 (83) | 869 (69) | ||||||
Data are presented as n (%) unless otherwise indicated.
aChi2-test was used to test for differences between the 4 CKD stages and between men and women.
bKruskall–Wallis test was used to test for differences between CKD stages.
cWilcoxon–Mann–Whitney test was used to test for differences between men and women.
dTotal number of quarters with a visit divided by observation time in years.
Figure 3 and Supplementary data, Table S2 show crude and age-standardized annual incidence rates of the different CKD stages stratified by sex. In general, the incidence of CKD was higher in women than men (947/100 000 women versus 860/100 000 men) between 2011 and 2018. The annual incidence rate of CKD stage 2 was higher in men than in women until a turning point in 2016, while incidence rates of stages 3 and 4 proved to be higher in women than men throughout the observation period. Incident CKD stage 5 was more often diagnosed in men than in women.
Figure 3:
Age-standardized incidence of chronic kidney disease in adults between 2011 and 2018 stratified by sex. The 95% confidence intervals are presented as transparent areas behind each the curve.
Lifestyle factors, comorbidities and potentially inappropriate medications
Further baseline characteristics of the study population are shown in Table 1 and Supplementary data, Table S1. Men and women differed significantly concerning all lifestyle factors. In general, obesity was present in approximately 30% of the study population, while the prevalence of smoking and alcohol consumption was 9% and 4%, respectively. While smoking and alcohol consumption were more prevalent in men, women were more frequently obese.
The most frequent comorbidities were hypertension, hyperlipidemia, diabetes mellitus type 2, ischemic heart disease and heart failure. Men and women differed significantly in terms of all comorbidities, except for hyperaldosteronism. The higher burden of comorbidities in men compared with women was also reflected in significantly higher values of the Charlson Comorbidity Index. In turn, women were significantly more often prescribed potentially inappropriate medications (PIMs) than men (see Supplementary data, Table S1).
Healthcare utilization
Outpatient care
Table 2 shows the utilization of outpatient care stratified by sex and incident CKD stage. Almost all men and women consulted a general practitioner (GP) at least once during the observation period. Those with incident CKD stage 5 visited a GP less often compared with the other stages. While over 90% of women and men with incident CKD stages 2–4 visited a GP in three or more quarters per year, lower frequencies were of found in those with incident CKD stage 5, especially in men.
In total, 12% of women and 18% of men sought the care of a nephrologist during the whole observation period with more visits in the higher incident CKD stages (see Table 2). The majority of men and women with incident CKD stages 2–4 visited a nephrologist in fewer than one quarter on average during the observation period, whereas 43% of men and 41% of women with incident stage 5 consulted a nephrologist every quarter over the years. The median time until the first visit to a nephrologist was one quarter in both men and women independent of the incident CKD stage (see Table 2). In general, the higher the incident CKD stage, the earlier a visit to a nephrologist.
Inpatient care
The number of hospitalizations during the first year after the incident CKD diagnosis is shown in Table 3. Statistically significant differences between the four incident stages of CKD were found in men and women. The number of hospitalizations increased with higher incident CKD stages. In general, men were hospitalized more often than women.
Table 3:
Utilization of inpatient care in adults with incident chronic kidney disease stratified by sex and incident stage (n = 209 498).
| Women | Men | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Total | CKD stage 2 | CKD stage 3 | CKD stage 4 | CKD stage 5 | P-valuea | Total | CKD stage 2 | CKD stage 3 | CKD stage 4 | CKD stage 5 | P-valuea | P-valueb | |
| Number of hospitalizations during the 1st year, n (%) | <.001 | <.001 | <.001 | ||||||||||
| No hospitalization during the 1st year | 66 630 (56) | 24 772 (64) | 37.249 (54) | 4180 (48) | 429 (40) | 49 096 (54) | 21 620 (61) | 24 853 (50) | 2165 (43) | 458 (36) | |||
| 1 hospitalization | 26 274 (22) | 7626 (20) | 16 252 (23) | 2146 (25) | 250 (24) | 19 591 (22) | 7061 (20) | 11 109 (23) | 1162 (23) | 259 (20) | |||
| 2 hospitalizations | 12 439 (11) | 3366 (8) | 7939 (11) | 1095 (13) | 139 (13) | 10 062 (11) | 3293 (9) | 5872 (12) | 694 (14) | 203 (16) | |||
| 3 hospitalizations | 6277 (5) | 1618 (4) | 3968 (6) | 606 (10) | 85 (8) | 5402 (6) | 1647 (5) | 3214 (7) | 414 (8) | 127 (10) | |||
| 4 hospitalizations | 3107 (3) | 747 (2) | 1965 (3) | 338 (4) | 57 (5) | 3068 (3) | 914 (3) | 1815 (4) | 249 (5) | 90 (7) | |||
| 5 hospitalizations | 1547 (1) | 374 (1) | 981 (1) | 151 (2) | 43 (4) | 1689 (2) | 490 (1) | 1028 (2) | 123 (3) | 48 (4) | |||
| ≥6 hospitalizations | 1965 (2) | 446 (1) | 1244 (2) | 212 (2) | 63 (6) | 2351 (3) | 667 (2) | 1405 (3) | 192 (4) | 87 (7) | |||
aKruskall–Wallis test was used to test for differences between the four CKD stages in women and men.
bWilcoxon–Mann–Whitney test was used to test for differences between men and women.
Supplementary data, Table S3 shows the association of sex and other predictors with the number of hospitalizations in the first year after the incident CKD diagnosis. The risk of being hospitalized was 16% lower in women compared with men (incidence rate ratio 0.841, 95% confidence interval 0.830–0.852). Independent of sex, the hospitalization rate increased with higher incident CKD stage, higher Charlson Comorbidity Index score as well as increasing number of PIMs.
DISCUSSION
To our knowledge, this is the first study to determine the incidence of CKD in the German population. Previous studies from Germany focused solely on CKD prevalence [15–19]. The age- and sex-standardized annual incidence of CKD was 945/100 000 persons and a higher incidence rate of CKD stages 2–5 was found in women than men, with CKD stage 3 as the most frequently diagnosed stage among both sexes. The incidence of stages 3 and 4 proved to be higher in women, while stages 2 and 5 were more often diagnosed in men. Statistically significant differences between the sexes were found in almost all comorbidities, and PIMs were more frequently prescribed in women. While women visited a GP more frequently, men were more likely to visit a nephrologist and were more often hospitalized in the first year after the incident CKD diagnosis.
Incidence of CKD
CKD is a common diagnosis in older adults [20, 21], which was also reflected in our study population. Previous studies reported varying incidence rates of CKD. With 170/100 000 population, a study from the UK with a similar median age reported a lower annual incidence rate compared with our study [20]. The Framingham Offspring study found incident kidney disease in 9400/100 000 of their community-based cohort with a mean age of 43 years [22]. A study in 3313 Iranian adults (≥20 years) reported an annual incidence of CKD stages 3–5 of more than 2000/100 000 [23], which is high compared with our results. Differences between previous studies and our study are likely due to different definitions or diagnostic criteria of CKD and deviating inclusion criteria.
Sex differences
Sex differences in the etiology, epidemiology and prognosis of CKD are well established in the literature [5–7, 24–27]. In line with our results, a Japanese study reported an annual incidence of CKD stage 3 or above that was lower in men (800/100 000) compared with women (1500/100 000) [28]. In contrast, Drey and colleagues found higher annual incidence rates of CKD among men in all age groups, especially those aged 80 years and older [20].
CKD, especially stage 2, is typically asymptomatic and mainly identified through routine check-ups or as incidental finding [29]. Men in our study population had a higher burden of comorbidities than women at the time of incident CKD diagnosis, which might have increased their chances of being incidentally diagnosed with CKD stage 2. In turn, women in our study population were significantly older at the time of the incident diagnosis. The fact that kidney function declines physiologically (and mostly asymptomatically) with age combined with a lower burden of comorbidities and higher life expectancy [6] might explain the higher incidence of CKD stages 3 and 4 in women in our study population [30].
Comorbidities and medications
Comorbidities and previous acute diseases were frequently found in our cohort of men and women with CKD. The most common causes of CKD in high- and middle-income countries are hypertension and diabetes mellitus [21]. Hypertension and heart failure were more often found in women in our study cohort, whereas other cardiovascular diseases and diabetes mellitus were more frequently diagnosed in men. In contrast to these frequent causes of CKD, rarer diseases such as polycystic kidney disease, amyloidosis and multiple myeloma were more frequently found in higher CKD stages, as well as nephritic and nephrotic syndrome as signs of glomerular damage. This could result from a more rapid deterioration of kidney function in patients with these diseases. Patients with polycystic kidney disease, for example, are known to experience a varying but fast GFR decline over the years [31]. In a meta-analysis containing data from 11 345 patients, the authors concluded that especially men with non-diabetic CKD experienced faster disease progression than women [32]. Differences between the sexes in terms of comorbidities might also be attributed to women being significantly older than men at the time of the incident CKD diagnosis.
Interestingly, women aged 65 years and older were more prone to being prescribed PIMs across all CKD stages than men. Since the kidney plays an important role in the pharmacokinetics of various medications, prescribing PIMs in patients with impaired kidney function might have detrimental effects. In line with our results, a study in 6392 patients with CKD identified female sex as a predictor for the use of kidney-based PIM [33]. A recent cross-sectional study using Medicare data found that the odds of women with CKD receiving PIMs were 1.25 times higher than men [34]. Therefore, medications that are taken on a regular basis should be re-evaluated by both GPs and nephrologists when (female) patients aged 65 years or older are diagnosed with CKD.
Inpatient and outpatient care
After being diagnosed with incident CKD, 12% of women and 18% of men in our study population were seen by a nephrologist. This proportion increased with higher incident CKD stages. These results are consistent with previous studies that reported significant associations of male sex, younger age and lower estimated GFR with both prior contact with a nephrologist and referral to a nephrologist, respectively [35, 36]. Referral to a nephrologist is advised in patients with a GFR <30 mL/min/1.73 m2 in current clinical practice guidelines [1], and accordingly, those with incident CKD stages 4 and 5 visited a nephrologist earlier after the incident diagnosis and more frequently than those with lower incident stages in our study population. Previous studies have shown that early nephrologist referral was associated with improved outcomes in patients with more advanced pre-dialysis CKD [36, 37]. The Chronic Renal Insufficiency Cohort study evaluated whether patients with mild to moderate CKD also benefited from referrals to specialists. They concluded that study participants who had prior contact with a nephrologist were more likely to be treated for CKD complications even though there was no statistically significant association with estimated GFR loss >50%, incident cardiovascular disease and death [35]. The guideline of the German College of General Practitioners and Family Physicians recommends basing the decision for the referral to a nephrologist depending on age, comorbidities, general health condition and preference of the patient, in addition to a reduced GFR [38]. This approach could avoid possible overprovision of patients with less complicated CKD and less advanced CKD stages, who can be treated by their GP alone. Nevertheless, the association between early and regular visits to nephrologists and long-term outcomes in men and women with CKD needs further investigation.
Men were more frequently hospitalized in the first year after the incident CKD diagnosis than women, and male sex remained a statistically significant predictor of the number of hospitalizations after adjusting for other factors. A possible explanation for higher hospitalization rates among men could be that kidney function declines faster in men than in women with CKD, requiring inpatient treatment [5–7]. Additionally, previous studies have shown that men with CKD were more likely to receive renal replacement therapy and suffer from cardiovascular events [39, 40], which could result in more hospital stays. Since we only analyzed hospitalizations due to all causes, we cannot make inferences about the reasons for the hospital stays in our study. A previous cohort study found that cardiovascular, genitourinary, digestive, endocrine, nutritional or metabolic, and respiratory causes were the most frequent among patients with CKD [41].
Limitations
Claims data have been increasingly used for research purposes in recent years because they offer the opportunity to generate knowledge from comparatively large study cohorts. However, their use entails several limitations [42, 43] since this kind of data collection is not originally intended for research purposes but for the billing of health services.
In our study cohort, CKD incidence decreased in both men and women in 2018. This decrease can be explained by missing incident CKD cases from outpatient care for the fourth quarter of 2018. Diagnoses from outpatient care were only counted as incident if the M2Q criterium was satisfied, which entails the presence of a CKD diagnosis in two quarters within 1 year. Since the data set only contained reliable data until the fourth quarter of 2018, those who would have had an incident diagnosis from outpatient care in this last quarter were not represented in our data set.
Since there were no data available before 2009, we could not determine whether men and women might have had any earlier incident CKD diagnosis. We tried to minimize this potential bias by introducing a pre-observation period of 2 years, which could not contain previous CKD diagnoses. Nevertheless, we cannot completely rule out that CKD was already present previously.
Finally, we did not include patients with incident CKD stage 1 into our study population since the coding quality of this stage of CKD is presumably poor in Germany. Therefore, our results cannot be generalized to patients with incident CKD stage 1.
In conclusion, this study provides valuable insights into the epidemiology of CKD and the healthcare utilization in patients with CKD with a focus on sex-specific differences. Even though the incidence of more advanced stages of CKD seemed to decrease slightly over the years, more awareness needs to be raised towards the early detection of the disease. Increased awareness is also needed to avoid the use of PIMs in patients with CKD, especially in women. Additionally, we call for better coordination of care to ensure that patients with advanced stages of CKD get timely access to specialist care and to avoid a possible overprovision of patients with lower, uncomplicated incident CKD stages, who can be monitored and treated by a GP alone.
Supplementary Material
ACKNOWLEDGEMENTS
The Allgemeine Ortskrankenkasse (AOK) Baden-Württemberg kindly provided data for the analyses. We would like to thank Dr Hannah Fuhr for language editing the manuscript.
Contributor Information
Miriam Giovanna Colombo, Institute for General Practice and Interprofessional Care, University Hospital Tübingen, Germany.
Christian Förster, Institute for General Practice and Interprofessional Care, University Hospital Tübingen, Germany.
Stephanie Wallwiener, Department of Obstetrics and Gynecology, University Hospital of Heidelberg, Germany.
Kathrin Hassdenteufel, Department of Obstetrics and Gynecology, University Hospital of Heidelberg, Germany.
Sabine Hawighorst-Knapstein, Allgemeine Ortskrankenkasse (AOK) Baden-Württemberg, Corporate division for Medical Care Design, Germany.
Gudula Kirtschig, Allgemeine Ortskrankenkasse (AOK) Baden-Württemberg, Corporate division for Medical Care Design, Germany.
Ariane Chaudhuri, Allgemeine Ortskrankenkasse (AOK) Baden-Württemberg, Corporate division for Medical Care Design, Germany.
Simon Dally, Allgemeine Ortskrankenkasse (AOK) Baden-Württemberg, Corporate Division Control, Finances and Analytics, Germany.
Stefanie Joos, Institute for General Practice and Interprofessional Care, University Hospital Tübingen, Germany.
FUNDING
This study was funded by the Allgemeine Ortskrankenkasse (AOK) Baden-Württemberg. The funders had no role in study design and analysis, decision to publish or drafting of the manuscript.
AUTHORS’ CONTRIBUTIONS
M.G.C. designed the study, analyzed the data and wrote the manuscript. C.F. designed the study, and contributed to the interpretation of the results and the writing of the manuscript. S.W., K.H., S.H.-K., G.K. and A.C. gave input from their field of knowledge for the design of the study and the interpretation of the results and revised the manuscript. S.D. provided the data, contributed to the selection of the study cohort and revised the manuscript. S.J. is the project leader, designed the study and contributed to the interpretation of the results and the writing of the manuscript. All authors revised and approved the final version of the manuscript.
DATA AVAILABILITY STATEMENT
The data underlying this article were provided by Allgemeine Ortskrankenkasse (AOK) Baden-Württemberg under license and are not publicly available. Data are available upon reasonable request to the corresponding author with permission of AOK Baden-Württemberg.
CONFLICT OF INTEREST STATEMENT
This study was conducted as part of a joint project of the Allgemeine Ortskrankenkasse (AOK) Baden-Württemberg and the Institute for General Practice and Interprofessional Care of the University Hospital Tübingen. In the framework of this joint project M.G.C., C.F. and S.J. received funding from the AOK Baden-Württemberg. In the past 36 months, S.W. received a grant from the Federal Joint Committee (G-BA) Innovation Fund, consulting fees from TK health insurance (Techniker Krankenkasse) and participated in the Advisory Board of Digital Women's Health. All other authors have no conflict of interest to declare.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data underlying this article were provided by Allgemeine Ortskrankenkasse (AOK) Baden-Württemberg under license and are not publicly available. Data are available upon reasonable request to the corresponding author with permission of AOK Baden-Württemberg.