Risk Assessment For Longitudinal Trajectories Of Modifiable Lifestyle Factors On Chronic Kidney Disease Burden in China: A Population-based Study

ABSTRACT 

Background: Chronic kidney disease (CKD) is an important contributor to morbidity and mortality from noncommunicable diseases. We aimed to examine the longitudinal trajectories in risk factors, estimate their impact on CKD burden in China from 1991 to 2011, and project trends in the next 20 years. Methods: We used data from a cohort of the China Health and Nutrition Survey and applied the comparative risk assessment method to estimate the number of CKD events attributable to all non-optimal levels of each risk factor. Results: In 2011, current smoking was the leading individual attributable factor for CKD burden in China responsible for 7.9 (95% confidence interval [CI], 7.5–8.3) million CKD cases with a population-attributable fraction of 8.7% (95% CI, 6.0–11.6), while the rates of smoking have reduced and may have mitigated the increase in CKD. High triglyceride (TG) and high systolic blood pressure (SBP) were the leading metabolic risk factors responsible for 6.8 (95% CI, 6.4–7.1) million and 5.8 (95% CI, 5.5–6.1) million CKD-attributable cases, respectively. Additionally, the number of CKD cases associated with high body mass index (BMI), high diastolic blood pressure (DBP), high plasma glucose, and low high-density lipoprotein cholesterol (HDL-C) was 5.4 (95% CI, 5.1–5.6), 3.9 (95% CI, 3.7–4.1), 3.0 (95% CI, 2.8–3.1) and 2.6 (95% CI, 2.5–2.8) million, respectively. Conclusions: Current smoking, high TG, and high SBP were the top three risk factors that contributed to the CKD burden in China. Increased BMI, DBP, plasma glucose, and decreased HDL-C were also associated with the increase in CKD burden

Keywords: chronic kidney disease; lifestyle; longitudinal trajectories; comparative risk assessment

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INTRODUCTION 

With the rapid development of the social economy and the improvement of living standards, people's lifestyles are changing. Increasing evidence suggests that lifestyles play an important role in the prevention and development of non-communicable diseases, especially diabetes, obesity, metabolic syndrome, cardiovascular diseases, and tumor, all of which are the risk factors for the occurrence and development of chronic kidney disease (CKD). CKD is an important contributor to cardiovascular events, morbidity, and mortality, and this disease has been a worldwide public health problem. The global prevalence of CKD is about 8–16% and still increasing dramatically.1 In 2017, the global cases of all-stage CKD were 697.5 million and the all-age prevalence of CKD increased 29.3% since 1990. Furthermore, the global all-age mortality rate from CKD increased by 41.5% between 1990 and 2017.2 The Global Burden of Disease, Injuries, and Risk Factors Study (GBD) ranks CKD as the 12th leading cause of death out of 133 conditions.3

China is the world's largest developing country. In the past 4 decades, China has seen rapid demographic and epidemiological transitions, along with accelerated urbanization and industrialization, which led to a dramatic shift in diet from traditional to Western dietary patterns and a steep decline in physical activity levels. Fundamental transformations in overall population health have occurred and are continuing. In 2017, high systolic blood pressure (SBP), smoking, and high-sodium diet were among the leading three risk factors contributing to deaths and disability-adjusted life-years (DALYs) in China.4 Yanping Li et al found that high blood pressure, increased body mass index (BMI), decreased physical activity, smoking, and unhealthy dietary factors contribute to the burden of cardiovascular disease and diabetes in China.5,6 Previous studies have shown that CKD is largely preventable and treatable: adherence to healthy dietary patterns, physical activity, and not smoking were associated with a lower risk of incident CKD.7–10 However, there has been no comprehensive estimation of the longitudinal trajectories of lifestyle factors and their related CKD burden up to now.

Therefore, we use the data from an ongoing open cohort of the China Health and Nutrition Survey (CHNS)11 to describe the time trends in lifestyle risk factors related to CKD from 1991 to 2011 and estimate the number of CKD cases attributable to suboptimal levels of these risk factors, to evaluate current public health policies, provide guidance for future CKD prevention and health promotion, and promote the Healthy China 2030 plan.

METHODS 

Study design and population Data were derived from CHNS, which was a nationally longitudinal study covering nine provinces in China since 1989 (representing 553 million people). Details about the CHNS study have been reported elsewhere.6 Briefly, the survey uses a multistage random-cluster sampling process to select samples in both urban and rural areas. All the members of the selected household were invited to participate in the study. The survey was approved by the institutional review committees of the University of North Carolina and the National Institute of Nutrition and Food Safety.

In the present study, we included eight rounds of data collection (1991, 1993, 1997, 2000, 2004, 2006, 2009, and 2011) and excluded participants who were <18 years of age or pregnant at the time of the survey. Data are available at http:==www.cpc. unc.edu=projects=china.

Information on demographic characteristics and lifestyle factors was obtained by well-trained staff using a structured questionnaire in each wave. Height, weight, and blood pressure were measured using standard procedures, and BMI was calculated as weight (kg) divided by height squared (m2 ); blood pressure was measured three times, and the mean value of three measurements was used. Laboratory indicators, including blood glucose, triglyceride (TG), and high-density lipoprotein cholesterol (HDL-C), were measured using standard laboratory procedures with methods of the glucose oxidase phenol 4- aminoantipyrine peroxidase, glycerol phosphate oxidase-paminophenazone, and enzymatic, respectively.

Risk factors selection In this comparative risk assessment, we selected risk factors of CKD based on the following criteria: 1) sufficient evidence suggested an association with CKD; 2) could be intervened; 3) exposure data were available in the study population. A total of seven factors were included: high SBP, high diastolic blood pressure (DBP), high BMI, current smoking, high TG, high glucose, and low HDL-C. Because only one measurement of blood indicators was available, we included the seven risk factors for the CKD burden estimate in 2011 and four non-blood factors for time trend analysis.

CKD cases We extracted the prevalence with a corresponding 95% confidence interval (CI) of Chinese CKD in 2010 from a published paper covering 47,204 participants.12 Total CKD cases were obtained by multiplying the prevalence of CKD by the population number according to the 2010 population census in China.

Attributable burden estimate

Relative risks (RRs) of risk factors for CKD were extracted from the most recent high-quality reviews or meta-analyses in China. When unavailable, we expanded the scope to Asia or other regions.

To assess the proportion of CKD cases attributable to nonoptimal levels of exposure, we used theoretical minimum risk exposure distribution (TMRED). In the comparative risk assessment framework, disease burden attributable to risk factors is calculated concerning an alternative (counterfactual) distribution of exposure, termed the TMRED.13,14 In the present study, the TMRED for current smoking was no smoking. For the other six risk factors, whose exposure of zero was impossible, the TMRED was set by levels with the lowest risk in epidemiological studies. The TMRED and sources of RRs of risk factors included are shown in Table 1. For categorical exposure, we calculated attributable burden according to the following formula, where population-attributable fraction (PAF) Pi is the fraction of the population in exposure category i, RRi is the RR for exposure category i, and n is the number of exposure categories.

For continuous exposure, we calculated attributable burden according to the following formula, where RR(x) is the RR at exposure level x, P1 (x) is the population distribution of exposure, P2 (x) is the counterfactual distribution of the theoretical minimum risk exposure, and m is the maximum exposure level.

Table 1. Sources and magnitudes of RRs for the effects of CKD

Statistical analysis 

The mean and standard error (SE) or percentage of each risk factor was calculated by age, gender, and residence in each wave, and a general linear mixed model was used to calculate covariate-adjusted means with adjustment for age, gender, residence, education, occupation, and provinces. To assess the time trends of each risk factor, the year of each wave was included in the model as a scored variable. 

We standardized the overall distribution of each risk factor in the joint classifications of age, sex, and residence in each wave using data from the 2010 Chinese Population Census as the reference. The number of CKD cases attributable to each risk factor was calculated by multiplying its PAF by the total CKD cases. Future trends prediction of four risk factors (SBP, DBP, BMI, current smoking) for 2013–2031 was conducted using a random-effects model within each stratum of age, sex, and residence among participants who completed at least three surveys during 1991– 2011. We performed the analysis using SAS 9.4 (SAS Institute, Cary, NC, USA).