Trends in renal function in Northern Sweden 1986–2014: data from the seven cross-sectional surveys within the Northern Sweden MONICA study

Objective The prevalence of chronic kidney disease (CKD) is increasing globally, and CKD is closely related to cardiovascular disease (CVD). CKD and CVD share several risk factors (RF), such as diabetes, hypertension, obesity and smoking, and the prevalence of these RF has changed during the last decades, and we aimed to study the effect on renal function over time. Design Repeated cross-sectional population-based studies. Setting The two Northern counties (Norr- and Västerbotten) in Sweden. Participants Within the MONitoring Trends and Determinants of CArdiovascular Disease (MONICA) study, seven surveys were performed between 1986 and 2014, including participants aged 25–64 years (n=10 185). Interventions None. Measures Information on anthropometry, blood pressure and cardiovascular risk factors was collected. Creatinine and cystatin C were analysed in stored blood samples and the estimated glomerular filtration rate (eGFR) calculated using the creatinine-based Lund–Malmö revised and Chronic Kidney Disease Epidemiology Collaboration (eGFRcrea) equations as well as the cystatin C-based Caucasian, Asian, Paediatric and Adult cohort (CAPA) equation (eGFRcysC). Renal function over time was analysed using univariable and multivariable linear regression models. Results Renal function, both eGFRcrea and eGFRcysC, decreased over time (both p<0.001) and differed between counties and sexes. In a multivariable analysis, study year remained inversely associated with both eGFRcrea and eGFRcysC (both p<0.001) after adjustment for classical cardiovascular RF. Conclusion Renal function has deteriorated in Northern Sweden between 1986 and 2014.

[1]  A. Bollmann,et al.  Prevalence, outcomes, and cost of chronic kidney disease in a contemporary population of 2·4 million patients from 11 countries: The CaReMe CKD study , 2022, The Lancet regional health. Europe.

[2]  N. Perico,et al.  Glomerular hyperfiltration , 2022, Nature Reviews Nephrology.

[3]  S. Söderberg,et al.  Smoking tobacco is associated with renal hyperfiltration , 2021, Scandinavian journal of clinical and laboratory investigation.

[4]  L. Nilsson,et al.  Comparison of dietary trends between two counties with and without a cardiovascular prevention programme: a population-based cross-sectional study in northern Sweden , 2021, Public Health Nutrition.

[5]  Y. Kim,et al.  Causal effects of education on chronic kidney disease: a Mendelian randomization study , 2020, Clinical kidney journal.

[6]  T. Wada,et al.  Age differences in the relationships between risk factors and loss of kidney function: a general population cohort study , 2020, BMC Nephrology.

[7]  L. G. Vu,et al.  Global, regional, and national burden of chronic kidney disease, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017 , 2020, The Lancet.

[8]  D. Bell,et al.  Clinical Characteristics of and Risk Factors for Chronic Kidney Disease Among Adults and Children , 2019, JAMA network open.

[9]  H. Wada,et al.  Serum Cystatin C, a Sensitive Marker of Renal Function and Cardiovascular Disease, Decreases After Smoking Cessation , 2019, Circulation reports.

[10]  M. Woodward,et al.  Socioeconomic disadvantage and the risk of advanced chronic kidney disease: results from a cohort study with 1.4 million participants. , 2019, Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association.

[11]  C. Ronco,et al.  Cardiorenal Syndrome: Classification, Pathophysiology, Diagnosis, and Treatment Strategies: A Scientific Statement From the American Heart Association. , 2019, Circulation.

[12]  S. Söderberg,et al.  Comparison of trends in cardiovascular risk factors between two regions with and without a community and primary care prevention programme , 2018, European journal of preventive cardiology.

[13]  J. Sommar,et al.  Time trends and exposure determinants of lead and cadmium in the adult population of northern Sweden 1990–2014 , 2017, Environmental research.

[14]  Fan Zhang,et al.  Effects of RAAS Inhibitors in Patients with Kidney Disease , 2017, Current Hypertension Reports.

[15]  M. Neovius,et al.  Healthcare costs in chronic kidney disease and renal replacement therapy: a population-based cohort study in Sweden , 2016, BMJ Open.

[16]  S. Hallan,et al.  Long-term trends in the prevalence of chronic kidney disease and the influence of cardiovascular risk factors in Norway. , 2016, Kidney international.

[17]  J. Jansson,et al.  Long term trends in control of hypertension in the Northern Sweden MONICA study 1986–2009 , 2015, BMC Public Health.

[18]  M. Ishizaki,et al.  Different association of cigarette smoking with GFR estimated from serum creatinine and that from serum cystatin C in the general population , 2015, Clinical and Experimental Nephrology.

[19]  M. M. Joosten,et al.  Socioeconomic disparities in chronic kidney disease: a systematic review and meta-analysis. , 2015, American journal of preventive medicine.

[20]  N. Braun,et al.  Clinical Course and Long-Term Outcome of Hantavirus-Associated Nephropathia Epidemica, Germany , 2015, Emerging infectious diseases.

[21]  Frank Kee,et al.  BiomarCaRE: rationale and design of the European BiomarCaRE project including 300,000 participants from 13 European countries , 2014, European Journal of Epidemiology.

[22]  Anders Larsson,et al.  Generation of a new cystatin C-based estimating equation for glomerular filtration rate by use of 7 assays standardized to the international calibrator. , 2014, Clinical chemistry.

[23]  L. Hansson,et al.  The revised Lund-Malmö GFR estimating equation outperforms MDRD and CKD-EPI across GFR, age and BMI intervals in a large Swedish population , 2014, Clinical chemistry and laboratory medicine.

[24]  Chi Pang Wen,et al.  Chronic kidney disease and cardiovascular risk: epidemiology, mechanisms, and prevention , 2013, The Lancet.

[25]  J. Coresh,et al.  Change in the estimated glomerular filtration rate over time and risk of all-cause mortality. , 2013, Kidney international.

[26]  J. Jansson,et al.  Comparison of blood pressure measurements between an automated oscillometric device and a Hawksley random-zero sphygmomanometer in the northern Sweden MONICA study , 2012, Blood pressure monitoring.

[27]  V. Salomaa,et al.  Trends in estimated kidney function: the FINRISK surveys , 2012, European Journal of Epidemiology.

[28]  S. Söderberg,et al.  Large improvements in major cardiovascular risk factors in the population of northern Sweden: the MONICA study 1986–2009 , 2011, Journal of internal medicine.

[29]  L. Wallentin,et al.  Relation between renal function, presentation, use of therapies and in‐hospital complications in acute coronary syndrome: data from the SWEDEHEART register , 2010, Journal of internal medicine.

[30]  W. Hörl.  Nonsteroidal Anti-Inflammatory Drugs and the Kidney , 2010, Pharmaceuticals.

[31]  C. Schmid,et al.  A new equation to estimate glomerular filtration rate. , 2009, Annals of internal medicine.

[32]  Christopher H Schmid,et al.  Factors other than glomerular filtration rate affect serum cystatin C levels. , 2009, Kidney international.

[33]  T. Olsson,et al.  Trends in Obesity and Its Distribution: Data From the Northern Sweden MONICA Survey, 1986–2004 , 2008 .

[34]  I. Heilberg,et al.  Influence of muscle mass and physical activity on serum and urinary creatinine and serum cystatin C. , 2008, Clinical journal of the American Society of Nephrology : CJASN.

[35]  J. Jansson,et al.  Time trends in population cholesterol levels 1986–2004: influence of lipid‐lowering drugs, obesity, smoking and educational level. The northern Sweden MONICA study , 2006, Journal of internal medicine.

[36]  B. Eriksen,et al.  The progression of chronic kidney disease: a 10-year population-based study of the effects of gender and age. , 2006, Kidney international.

[37]  Charles E McCulloch,et al.  Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. , 2004, The New England journal of medicine.

[38]  D. Spiegelman,et al.  Factors influencing serum cystatin C levels other than renal function and the impact on renal function measurement. , 2004, Kidney international.

[39]  B. Stegmayr,et al.  The events registration and survey procedures in the Northern Sweden MONICA Project , 2003, Scandinavian journal of public health. Supplement.

[40]  H. Hillege,et al.  Obesity and target organ damage: the kidney , 2002, International Journal of Obesity.

[41]  A. Koivisto,et al.  Renal function and blood pressure five years after puumala virus-induced nephropathy. , 2000, Kidney international.

[42]  D. DuBois,et al.  A formula to estimate the approximate surface area if height and weight be known , 1989 .

[43]  J. Leduc,et al.  Epidemiology of nephropathia epidemica in Sweden. , 1987, The Journal of infectious diseases.

[44]  OUP accepted manuscript , 2022, Clinical Kidney Journal.

[45]  J. Jansson,et al.  Long term trends in control of hypertension in the Northern Sweden MONICA study , 2015 .

[46]  T. Olsson,et al.  Trends in Obesity and Its Distribution: Data From the Northern Sweden MONICA Survey, 1986–2004 , 2008 .

[47]  E. Ejerblad,et al.  Socio-economic status and chronic renal failure: a population-based case-control study in Sweden. , 2003, Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association.

[48]  GraspingEric Paulospaulos,et al.  Trends in the , 2003 .

[49]  Murray Epstein.  Alcohol’s Impact on Kidney Function , 1997, Alcohol health and research world.