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

CKD is a serious global public health issue associated with high morbidity and mortality.1GBD Chronic Kidney Disease CollaborationGlobal, regional, and national burden of chronic kidney disease, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017.Lancet. 2020; 395: 709-733Abstract Full Text Full Text PDF PubMed Scopus (1729) Google Scholar 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.2Lloyd-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: 586-613Crossref PubMed Scopus (2807) Google Scholar Several studies have shown that adherence to combined lifestyle factors may reduce the risk of CVD and mortality among patients with CKD3Schrauben 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: 663-675Crossref PubMed Scopus (7) Google Scholar, 4Ricardo 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: 412-424Abstract Full Text Full Text PDF PubMed Scopus (107) Google Scholar, 5Ricardo 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: 602-609Crossref PubMed Scopus (34) Google Scholar; 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.6Palmer L.J. UK Biobank: bank on it.Lancet. 2007; 369: 1980-1982Abstract Full Text Full Text PDF PubMed Scopus (155) Google Scholar 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≥5No. 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 ± 8.8Male 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 ± 2.81Sleep 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 ± 3.0Systolic BP, mm Hg148.2 ± 19.5147.8 ± 20.1145.0 ± 21.7141.2 ± 22.5129.1 ± 22.1Diastolic BP, mm Hg86.1 ± 10.986.7 ± 11.085.0 ± 11.382.7 ± 11.277.3 ± 11.3Antihypertension 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 ± 40.0Lipid-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 ± 3.3Diabetes 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/gaAvailable 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. Open table in a new tab 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. 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 ScoreCategorical Analysis by LS7 ScoreP for Linear TrendContinuous Analysis, per Each LS7 FactorPAF%bTheoretically 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≥5Incident 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)aAdjusted 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)aAdjusted 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)aAdjusted 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)aAdjusted 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. Open table in a new tab Abbreviations: HR, hazard ratio; PAF, population attributable fraction. 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. 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. 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. The authors declare they have no other relevant financial interests. We are grateful to all UK Biobank participants and all involved in building the UK Biobank study. 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/). 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. Download .pdf (.58 MB) Help with pdf files Supplementary File (PDF)Figures S1-S2; Item S1; Tables S1-S4.