Advertisement
American Journal of Kidney Diseases

Association of Cardiovascular Health Measures With Cardiovascular Disease and Mortality in CKD: A UK Biobank Study

  • Tingting Geng
    Affiliations
    Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, Ministry of Education Key Lab of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

    Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
    Search for articles by this author
  • Yan-Bo Zhang
    Affiliations
    Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
    Search for articles by this author
  • Qi Lu
    Affiliations
    Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, Ministry of Education Key Lab of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
    Search for articles by this author
  • Zhenzhen Wan
    Affiliations
    Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, Ministry of Education Key Lab of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
    Search for articles by this author
  • An Pan
    Correspondence
    Address for Correspondence: An Pan, PhD, School of Public Health, Tongji Medical Colleage, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan 430030, China.
    Affiliations
    Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
    Search for articles by this author
  • Gang Liu
    Correspondence
    Address for Correspondence: Gang Liu, PhD
    Affiliations
    Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, Ministry of Education Key Lab of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
    Search for articles by this author
Published:March 18, 2022DOI:https://doi.org/10.1053/j.ajkd.2022.01.432
      To the Editor:
      CKD is a serious global public health issue associated with high morbidity and mortality.
      GBD Chronic Kidney Disease Collaboration
      Global, regional, and national burden of chronic kidney disease, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017.
      In 2010, the American Heart Association developed Life’s Simple 7 (LS7), a composite score including 4 lifestyle factors (smoking, BMI, diet, physical activity) and 3 metabolic factors (cholesterol level, BP, and glycemic status) to reflect cardiovascular health.
      • Lloyd-Jones D.M.
      • Hong Y.
      • Labarthe D.
      • et al.
      Defining and setting national goals for cardiovascular health promotion and disease reduction: the American Heart Association's Strategic Impact Goal through 2020 and beyond.
      Several studies have shown that adherence to combined lifestyle factors may reduce the risk of CVD and mortality among patients with CKD
      • Schrauben S.J.
      • Hsu J.Y.
      • Amaral S.
      • Anderson A.H.
      • Feldman H.I.
      • Dember L.M.
      Effect of kidney function on relationships between lifestyle behaviors and mortality or cardiovascular outcomes: a pooled cohort analysis.
      • Ricardo A.C.
      • Anderson C.A.
      • Yang W.
      • et al.
      Healthy lifestyle and risk of kidney disease progression, atherosclerotic events, and death in CKD: findings from the Chronic Renal Insufficiency Cohort (CRIC) Study.
      • Ricardo A.C.
      • Madero M.
      • Yang W.
      • et al.
      Adherence to a healthy lifestyle and all-cause mortality in CKD.
      ; however, evidence regarding associations of LS7 score with future cardiovascular outcomes and mortality among patients with CKD is scarce.
      Thus, we prospectively examined the associations of LS7 score with incident CVD events, ischemic heart disease (IHD), heart failure (HF), and all-cause mortality among patients with CKD using data from the UK Biobank Study, a large prospective cohort study.
      • Palmer L.J.
      UK Biobank: bank on it.
      The current analysis included 21,071 patients with CKD after excluding individuals with incomplete information on any LS7 factor (n = 6,537), prevalent CVD cases (n = 7,334), or indications of kidney replacement therapy (n = 52; Fig S1). Participants were considered to have CKD if they had eGFR <60 mL/min/1.73 m2, albuminuria (UACR >30 mg/g), or a CKD diagnosis based on ICD-10 (N18) via linkage with electronic health records.
      To account for the competing risk of death, we used multivariable-adjusted Fine-Gray subdistribution hazard models to estimate the associations of LS7 score with risks of incident CVD and subtypes of CVD events. For all-cause mortality, multivariable-adjusted Cox regression models were used. HRs were adjusted for age, sex, ethnicity, education, Townsend deprivation index (TDI), alcohol intake, sleep duration, family history of CVD, and baseline eGFR.
      At recruitment, among 21,071 CKD patients (mean age, 59.0 years; 9,363 men [44.4%]), 28.0%, 29.4%, 24.0%, 13.0%, and 5.7% had 0-1, 2, 3, 4, and ≥5 LS7 factors at ideal levels, respectively. Table 1 shows participants with higher scores were more likely to be younger, women, higher educated, less deprived, non–daily drinkers, with lower levels of BMI, BP, cholesterol, and HbA1c. Further, they tended to have higher baseline eGFR and lower UACR. Participants included in the current analyses were more likely to be men, White, higher educated, less deprived, daily drinkers, and have higher BMI than those who were excluded owing to missing values (absolute standardized differences >10%; Table S1).
      Table 1Baseline Characteristics According to LS7 Score Among Patients With CKD in the UK Biobank Study (N = 21,071)
      CharacteristicLS7 Score
      ≤1234≥5
      No. of participants5,899 (28.0%)6,187 (29.4%)5,046 (24.0%)2,730 (13.0%)1,209 (5.7%)
      Age, y60.4 ± 7.059.3 ± 7.558.8 ± 7.957.8 ± 8.254.8 ± 8.8
      Male sex3,427 (58.1%)2,882 (46.6%)1,949 (38.6%)834 (30.6%)271 (22.4%)
      College or university degree544 (9.2%)619 (10.0%)583 (11.6%)355 (13.0%)188 (15.6%)
      White descent5,498 (94.7%)5,761 (94.5%)4,719 (94.5%)2,580 (95.5%)1,142 (95.3%)
      TDI−0.80 ± 3.27−1.19 ± 3.12−1.42 ± 3.00−1.55 ± 2.97−1.71 ± 2.81
      Sleep duration of 7-8 h/d3,675 (62.3%)4,043 (65.4%)3,421 (67.8%)1,884 (69.0%)871 (72.0%)
      Daily drinker1,344 (22.8%)1,303 (21.1%)974 (19.3%)469 (17.2%)177 (14.6%)
      Family history of CVD3,522 (59.7%)3,710 (60.0%)2,940 (58.3%)1,581 (57.9%)618 (51.1%)
      BMI, kg/m231.3 ± 5.229.3 ± 5.027.3 ± 4.825.1 ± 4.323.0 ± 3.0
      Systolic BP, mm Hg148.2 ± 19.5147.8 ± 20.1145.0 ± 21.7141.2 ± 22.5129.1 ± 22.1
      Diastolic BP, mm Hg86.1 ± 10.986.7 ± 11.085.0 ± 11.382.7 ± 11.277.3 ± 11.3
      Antihypertension medication3,370 (57.1%)2,629 (42.5%)1,721 (34.1%)678 (24.8%)164 (13.6%)
      Total cholesterol, mg/dL213.5 ± 51.5223.5 ± 46.5223.3 ± 44.4217.7 ± 43.7203.5 ± 40.0
      Lipid-lowering medication2,944 (49.9%)1,760 (28.5%)889 (17.6%)302 (11.1%)60 (5.0%)
      HbA1c, mmol/mol44.5 ± 13.937.8 ± 8.835.8 ± 6.734.7 ± 4.333.7 ± 3.3
      Diabetes medication1,357 (23.0%)416 (6.7%)119 (2.4%)17 (0.6%)1 (0.1%)
      Baseline eGFR category
       <45 mL/min/1.73 m2308 (5.2%)289 (4.7%)179 (3.6%)90 (3.3%)25 (2.1%)
       45-60 mL/min/1.73 m21,397 (23.7%)1,597 (25.8%)1,302 (25.8%)619 (22.7%)250 (20.7%)
       ≥60 mL/min/1.73 m24,194 (71.1%)4,301 (69.5%)3,565 (70.7%)2,021 (74.0%)934 (77.3%)
      UACR, mg/g
      Available for 16,346 patients. A total of 12,784 CKD patients were defined based on UACR≥30mg/g only.
      49.8 [32.9-99.0]45.9 [32.7-84.9]45.3 [33.1-82.0]46.3 [33.9-80.4]47.1 [34.2-83.7]
      Data given as mean ± SD, median [interquartile range], or number (%). Abbreviations: BMI, body mass index; BP, blood pressure; CKD, chronic kidney disease; CVD, cardiovascular disease; eGFR, estimated glomerular filtration rate; HbA1c, hemoglobin A1c; UACR, urinary albumin-creatinine ratio.
      a Available for 16,346 patients. A total of 12,784 CKD patients were defined based on UACR ≥30 mg/g only.
      There were 4,815 composite CVD, 2,115 IHD, and 896 HF events, along with 2,013 total deaths. Comparing LS7 score ≥5 with 0-1, the adjusted HRs were 0.54 (95% CI, 0.45-0.64) for total CVD, 0.38 (95% CI, 0.28-0.52) for IHD, 0.30 (95% CI, 0.17-0.52) for HF, and 0.57 (95% CI, 0.43-0.75) for all-cause mortality. The adjusted PAFs for incident CVD and mortality associated with LS7 score <4 were 25.2 (95% CI, 20.0-30.0) and 28.7 (95% CI, 19.3-37.0), suggesting that 25.2% and 28.7% of these cases would not have happened if all participants had ≥4 ideal LS7 factors (Table 2).
      Table 2HRs and PAFs for Incident CVD and Mortality According to LS7 Score
      Categorical Analysis by LS7 ScoreP for Linear TrendContinuous Analysis, per Each LS7 FactorPAF%
      Theoretically estimates the proportion of each outcome in this study population that could have been prevented if the population had≥4 LS7 factors at ideal levels.
      (<4 vs ≥4 LS7 Factor)
      ≤1234≥5
      Incident CVD25.2 (20.0-30.0)
       Cases/person-year1,798/55,4671,464/61,234997/51,412420/28,607136/12,9994,815/209,728
       HR (95% CI)
      Adjusted for age at recruitment (continuous, years), sex, ethnicity (White, non-White), TDI (continuous), and education (college or university degree, other professional qualifications, A/AS levels or equivalent or O levels/GCSEs, none of the above), alcohol intake (never/special occasions, monthly to weekly, daily), sleep duration (<7, 7-8,>8h/d), family history of CVD, and baseline eGFR.
      1.00 (reference)0.84 (0.78-0.90)0.74 (0.69-0.81)0.62 (0.55-0.69)0.54 (0.45-0.64)<0.0010.87 (0.85-0.89)
      Incident IHD34.6 (27.3-41.2)
       Cases/person-year870/59,651651/64,999397/54,298154/29,85943/13,4352,115/222,243
       HR (95% CI)
      Adjusted for age at recruitment (continuous, years), sex, ethnicity (White, non-White), TDI (continuous), and education (college or university degree, other professional qualifications, A/AS levels or equivalent or O levels/GCSEs, none of the above), alcohol intake (never/special occasions, monthly to weekly, daily), sleep duration (<7, 7-8,>8h/d), family history of CVD, and baseline eGFR.
      1.00 (reference)0.80 (0.72-0.89)0.65 (0.58-0.73)0.51 (0.43-0.60)0.38 (0.28-0.52)<0.0010.82 (0.79-0.85)
      Incident HF29.5 (16.8-40.3)
       Cases/person-year383/62,633268/67,406159/55,69673/30,43213/13,584896/229,750
       HR (95% CI)
      Adjusted for age at recruitment (continuous, years), sex, ethnicity (White, non-White), TDI (continuous), and education (college or university degree, other professional qualifications, A/AS levels or equivalent or O levels/GCSEs, none of the above), alcohol intake (never/special occasions, monthly to weekly, daily), sleep duration (<7, 7-8,>8h/d), family history of CVD, and baseline eGFR.
      1.00 (reference)0.77 (0.66-0.91)0.63 (0.52-0.76)0.59 (0.46-0.76)0.30 (0.17-0.52)<0.0010.81 (0.77-0.86)
      All-cause mortality28.7 (19.3-37.0)
       Cases/person-year839/61,938581/66,155383/54,341155/29,61255/13,1582,013/225,204
       HR (95% CI)
      Adjusted for age at recruitment (continuous, years), sex, ethnicity (White, non-White), TDI (continuous), and education (college or university degree, other professional qualifications, A/AS levels or equivalent or O levels/GCSEs, none of the above), alcohol intake (never/special occasions, monthly to weekly, daily), sleep duration (<7, 7-8,>8h/d), family history of CVD, and baseline eGFR.
      1.00 (reference)0.76 (0.69-0.85)0.68 (0.60-0.77)0.56 (0.47-0.66)0.57 (0.43-0.75)<0.0010.84 (0.81-0.87)
      Abbreviations: HR, hazard ratio; PAF, population attributable fraction.
      a Adjusted for age at recruitment (continuous, years), sex, ethnicity (White, non-White), TDI (continuous), and education (college or university degree, other professional qualifications, A/AS levels or equivalent or O levels/GCSEs, none of the above), alcohol intake (never/special occasions, monthly to weekly, daily), sleep duration (<7, 7-8, >8 h/d), family history of CVD, and baseline eGFR.
      b Theoretically estimates the proportion of each outcome in this study population that could have been prevented if the population had ≥4 LS7 factors at ideal levels.
      The results were consistent in subgroup analyses stratified by age, sex, TDI, and baseline eGFR; no significant effect modifications were observed (Fig S2). The results were also largely unchanged when we excluded cases within 2 years of follow-up (Table S2), performed the analyses among CKD patients defined by baseline eGFR only (Table S3), or additionally adjusted for both eGFR and UACR (n = 16,346) (Table S4).
      This is among the first studies to investigate the association of LS7 score with risks of a wide range of CVD events and all-cause mortality among patients with CKD. Several limitations should be considered. First, self-reported, 1-time assessment of LS7 factors may result in some misclassification bias. Second, chronicity data for eGFR and UACR were not available. Third, UACR was only available among a subset population (n = 156,595), so selection bias may exist. Fourth, some baseline characteristics of participants included and excluded from the analysis owing to missing information on LS7 factors were slightly different, which may lead to selection bias. Fifth, a lack of ethnic diversity (94.7% White) may limit generalizability to other populations. Finally, owing to the observational design, residual confounding cannot be completely ruled out.
      In conclusion, our findings suggest that higher LS7 score is associated with a substantially lower risk of CVD events and mortality among patients with CKD, which has important public health implications and clinical relevance. Our data support that primary prevention should be promoted among patients with CKD. Additionally, the observed dose-response relationship indicates physicians should encourage patients that their cardiovascular health could benefit by adopting even 1 additional ideal LS7 factor.

      Article Information

      Authors’ Contributions

      Study concept and design: TG, GL, AP; data acquisition: GL; data analysis/interpretation: TG, Y-BZ, QL, ZW, GL; supervision or mentorship: GL, AP. Each author contributed important intellectual content during manuscript drafting or revision and agrees to be personally accountable for the individual’s own contributions and to ensure that questions pertaining to the accuracy or integrity of any portion of the work, even one in which the author was not directly involved, are appropriately investigated, and resolved, including with documentation in the literature if appropriate.

      Support

      GL was funded by grants from National Natural Science Foundation of China (82073554), the Hubei Province Science Fund for Distinguished Young Scholars (2021CFA048), and the Fundamental Research Funds for the Central Universities (2021GCRC076). AP was supported by grants from National Natural Science Foundation of China ( 81930124 , 82021005 ) and the Fundamental Research Funds for the Central Universities (2021GCRC075). TG is funded by grants from the China Postdoctoral Science Foundation ( 2021M691129 ). Funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

      Financial Disclosure

      The authors declare they have no other relevant financial interests.

      Acknowledgements

      We are grateful to all UK Biobank participants and all involved in building the UK Biobank study.

      Data Sharing

      This research was conducted using the UK Biobank Resource under Application Number 68307. The UK Biobank data are available on application to the UK Biobank (www.ukbiobank.ac.uk/).

      Peer Review

      Received September 7, 2021. Evaluated by 2 external peer reviewers, with direct editorial input from a Statistics/Methods Editor, an Associate Editor, and the Editor-in-Chief. Accepted in revised form January 21, 2022.

      Supplementary Material

      References

        • GBD Chronic Kidney Disease Collaboration
        Global, regional, and national burden of chronic kidney disease, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017.
        Lancet. 2020; 395: 709-733
        • Lloyd-Jones D.M.
        • Hong Y.
        • Labarthe D.
        • et al.
        Defining and setting national goals for cardiovascular health promotion and disease reduction: the American Heart Association's Strategic Impact Goal through 2020 and beyond.
        Circulation. 2010; 121: 586-613
        • Schrauben S.J.
        • Hsu J.Y.
        • Amaral S.
        • Anderson A.H.
        • Feldman H.I.
        • Dember L.M.
        Effect of kidney function on relationships between lifestyle behaviors and mortality or cardiovascular outcomes: a pooled cohort analysis.
        J Am Soc Nephrol. 2021; 32: 663-675
        • Ricardo A.C.
        • Anderson C.A.
        • Yang W.
        • et al.
        Healthy lifestyle and risk of kidney disease progression, atherosclerotic events, and death in CKD: findings from the Chronic Renal Insufficiency Cohort (CRIC) Study.
        Am J Kidney Dis. 2015; 65: 412-424
        • Ricardo A.C.
        • Madero M.
        • Yang W.
        • et al.
        Adherence to a healthy lifestyle and all-cause mortality in CKD.
        Clin J Am Soc Nephrol. 2013; 8: 602-609
        • Palmer L.J.
        UK Biobank: bank on it.
        Lancet. 2007; 369: 1980-1982