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Title: Association of Obesity and Incidence of Chronic Kidney Disease: A Nationwide Population-Based Cohort Study in Taiwan
Running title: Obesity and Chronic Kidney disease
Introduction: Increase in body fat is known related to inflammatory cytokine production, which activates the renin-angiotensin-aldosterone system to elevate the risks of the development of chronic kidney disease (CKD).
Methods: A nationally representative sample of the general population was selected from the Taiwan National Health Interview Survey (NHIS) in 2000, 2005, and 2009, using a multistage systematic sampling process. The subjects were interviewed by a standardized face-to-face questionnaire to obtain information on their demographics, socioeconomic status, family medical history, health behaviors, and body mass index (BMI). BMI was categorized as underweight (<18.5 kg/m2), normal (18.5–23.9 kg/m2), overweight (24–26.9 kg/m2), and obesity (≥27 kg/m2). Univariate and multivariate Cox regression analyses were used to estimate the effect of baseline BMI on the CKD incidence.
Results: A total of 45,012 subjects (mean age of 42.03 years old and 51.1% males) were analyzed. During 383,137 person-years of follow-up, 1,913 new-onset CKD cases were identified. With confounding control, the relative risk of new-onset CKD was significantly higher for obese group comparing to normal-weight group (adjusted hazard ratio=1.32; 95% confidence interval, 1.17-1.49), with a significant linear trend observed (p<0.001).
Conclusions: Obese subjects were found at an increased risk of CKD.
Key words: epidemiology, obesity, chronic kidney disease, body mass index
- Obese (body mass index≥27 kg/m2) subjects were found at an increased risk of incidence of chronic kidney disease, comparing to normal-weight group.
- The statistically significant exposure-response gradient of body mass index to the incidence of chronic kidney disease remained after adjustment for the potential confounding factors with a significant linear trend observed.
The increasing prevalence of chronic kidney disease (CKD), which could lead to end-stage renal disease and increased cardiovascular morbidity and mortality, is a worldwide problem.(1) Risk factors of CKD include advanced age, diabetes, hypertension, dyslipidemia, smoking, nephrotoxins, and obesity.(2, 3) Obesity has been reported to lead to CKD through the development of diabetes and hypertension, as well as through mechanisms related to changes in various hemodynamic, metabolic, mechanical, and inflammatory processes.(4, 5)
Body mass index (BMI) is the most basic and common method for measuring obesity. BMI is not a perfect measure for obesity, because it does not directly assess body fat. However, studies have shown that BMI is strongly correlated with the gold-standard methods for measuring body fat.(6) Moreover, it is an easy way for clinicians to screen for patients who might be at greater risk of health problems due to their body fat.(7) The most commonly used BMI classification was established by the World Health Organization in 1997 and published in 2000. According to the World Health Organization definition, a BMI ≥30 kg/m2 is considered as obesity. As Asian populations develop negative health consequences at a lower BMI than Caucasians do, some nations have redefined obesity; for example, in Japan, obesity is defined as a BMI >25 kg/m2, while in China, a BMI of >28 kg/m2 is used.(8, 9)In Taiwan, overweight is defined as a BMI of 24–26.9 kg/m2, and obesity as BMI ≥27 kg/m2.(10)
Previous studies have investigated the association of obesity and CKD; however, diverse results were observed among subjects from different regions and ethnicities, owing to different obesity definitions and study settings.(11-14) In particular, the previous studies were limited to specific populations and were inadequately controlled for potential confounders.(11-14) Stengel et al. examined data from a nonconcurrent cohort study of 9,082 U.S. adults, aged 30–74 years, who participated in the second National Health and Nutrition Examination Survey from 1976 through 1980. The authors reported that morbidly obese subjects (BMI ≥35 kg/m2) had a significantly higher relative risk of kidney disease compared with normal-weight subjects (BMI 18.5–24.9 kg/m2); however, the risk was not increased for those classified as overweight (BMI 25–29.9 kg/m2) or obese (BMI 30–34.9 kg/m2).(11) Gelber et al. evaluated a cohort of 11,104 initially healthy men who participated in the Physicians’ Health Study in the U.S and found that, compared with participants in the lowest BMI quintile (BMI<22.7 kg/m2), those in the highest quintile (BMI>25.1 kg/m2) had significant increased risks of kidney disease after adjusting for potential confounders.(12) Iseki et al. examined the relationship between BMI and the development of end-stage renal disease using data from a 1983 community-based screening in Okinawa, Japan. The results showed that individuals with the highest quartile of BMI (≥25.5 kg/m2) had increased risks for developing end-stage renal disease compared with those with the lowest quartile of BMI (BMI<21.0 kg/m2).(13)
However, the association between obesity and CKD in Asian populations has not been well investigated. We hypothesized that obesity (BMI ≥27 kg/m2) is associated with increased risks of the development of CKD in the general Taiwanese population and conducted the present study using data from the National Health Interview Survey (NHIS) to address this hypothesis.
Materials and Methods
The study population was derived from three rounds of the NHIS, a large national survey in Taiwan, conducted in 2001, 2005, and 2009. The NHIS is a periodical, cross-sectional health survey carried out jointly by the Bureau of Health Promotion, Department of Health, and the National Health Research Institutes in Taiwan. The survey selected a representative sample of the general Taiwan population using a multistage stratified systematic sampling design, based on the degree of urbanization, the geographic location, and the local administrative boundaries. The NHIS data were collected using a standardized face-to-face interview survey. The survey dataset provides information on the demographic characteristics, socioeconomic status, height, weight, and health behaviors, such as the smoking habits and alcohol consumption, of the study population.
The survey respondents who provided consent were linked to the Taiwan National Health Insurance (NHI) claims data for the years 2000–2013, which include data on ambulatory and inpatient care use. The NHI claims records contain information on diagnosis codes, the date of medical care use, the procedures/treatments used, and the characteristics of the medical care facilities, together with details of the physicians providing the services and each patient’s medical care expenditure. The Taiwan Bureau of National Health Insurance (BNHI) linked the NHIS data with the corresponding NHI data, using their personal identification numbers. This process conforms to the government’s confidentiality regulations. No person or medical care facility could be identified from the analytical dataset, as all identification numbers had been encrypted by the BNHI. The Institutional Review Board of Taipei City Hospital approved this study (IRB No.: TCHIRB-10404118-W).
Study Design and Sample
A retrospective cohort study was conducted to investigate the link between obesity and the incidence of CKD. Study subjects were selected from the NHIS respondents who had provided consent to link their survey data to their NHI records.
Main Explanatory Variable
The main explanatory variable was obesity. Each subject’s BMI (kg/m2) was retrieved from the individual NHIS records at baseline. Body weight and height were self-reported by the study subjects. BMI was categorized as underweight (<18.5 kg/m2), normal (18.5–23.9 kg/m2), overweight (24–26.9 kg/m2), and obesity (≥27 kg/m2).(10)
Controlling and Outcome Variables
According to the International Classification of Disease, 9th Revision Clinical Modification (ICD-9-CM), the outcome and controlling variables were defined as CKD (ICD-9-CM codes 580-589), diabetes (ICD-9-CM code 250), hypertension (ICD-9-CM codes 401–405), hyperlipidemia (ICD-9-CM code 272), urethral stones (ICD-9-CM codes 592.0, 592.1, 594.0, 594.1), and gouty arthritis (ICD-9-CM code 274), identified from the NHI claims records, using the presence of at least three ambulatory claims or one inpatient claim.(15)The study cohort was defined as subjects who were free of CKD at the beginning of the study period. Individuals who had been diagnosed with CKD before the NHIS were excluded from the analyses.
Univariate Cox’s proportional hazard analysis was used to compare the characteristics among the participants. The associations and significance of incident CKD and BMI were tested by multivariate Cox proportional hazard analysis. The trend test was used to examine the dose-response relationship between BMI and the incidence of CKD. All analyses were conducted using SAS 9.4 (SAS Institute Inc, Cary, NC).
Study Subject Selection
Out of 48,604 participants aged >18 years, 1,263 participants with existing CKD, 2,328 participants with missing BMI data, and one participant with missing sex data were excluded. Each person’s healthcare use in the NHI system was followed from the index date to December 31, 2013. The final analytical sample consisted of 45,012 individuals, with 22,546 men (50.1%) and 22,466 women (49.9%), and the overall mean (SD) age was 42.03 (16.18) years. Regarding the BMI classification, 7,123 (15.8%), 10,641 (23.6%), 24,159 (53.7%), and 3,089 (6.9%) of the subjects were classified as obese, overweight, normal-weight, and underweight, respectively.
Univariates Analyses of Risk Factors for Incident CKD
During 383,137 person-years of follow-up, new-onset CKD was identified in 65 (2.1%), 826 (3.4%), 533 (5.0%), and 489 (6.9%) underweight, normal-weight, overweight, and obese subjects, respectively (Table 1). As compared with individuals with normal weight, overweight and obese subjects had higher risks of CKD (overweight: hazard ratio [HR], 1.50; 95% confidence interval [CI], 1.35-1.68; p<0.001; obese: HR, 2.15; 95% CI, 1.92-2.40; p<0.001). Other factors associated with the incidence of CKD included old age, male sex, widowed/divorced/separated, ever smokers, diabetes, hypertension, hyperlipidemia, urethral stones, and gouty arthritis. Next, the exposure-response relationship of BMI and incidence of CKD was evaluated by using the trend test. The risk of incident CKD increased as the BMI increased (HR, 1.48; 95% CI, 1.41-1.56; p for trend<0.001).
Multivariate Analyses for the Factors Associated with Incident CKD
A multivariate Cox regression model was used to identify independent factors associated with incident CKD (Table 3). After controlling for the subjects’ demographics and comorbidities, obese subjects were significantly associated with increased risks of CKD (adjusted HR [AHR], 1.32; 95% CI, 1.17-1.49; p<0.001). Other significant risk factors for incident CKD included male sex (AHR, 1.22; 95% CI, 1.09-1.36), smoking (AHR, 1.23; 95% CI, 1.05-1.45), diabetes (AHR, 1.57; 95% CI, 1.42-1.75), hypertension (AHR, 1.65; 95% CI, 1.46-1.86), urethral stones (AHR, 1.22; 95% CI, 1.05-1.41, and gouty arthritis (AHR, 1.76; 95% CI, 1.59-1.96). The statistically significant exposure-response gradient of BMI to the incidence of CKD by the linear trend test remained after adjustment for the above factors (HR, 1.13; 95% CI, 1.07-1.20; p for trend<0.001; Table 2).
Significant interactions were noted between BMI and diabetes, and between BMI and hypertension on the risk of incident CKD. Accordingly, we performed subgroup analyses in these subjects. Table 3 shows the results of the subgroup analyses of the association between obesity and incidence of CKD after stratifying the study subjects by age, sex, diabetes, and hypertension. Obesity was associated with a higher risk of incident CKD in all subgroups.
Our study results showed that obese subjects (BMI ≥27 kg/m2) had significantly increased risks of incident CKD compared with those with normal weight (BMI 18.5–23.9 kg/m2). Obesity is a major risk factor for diabetes, hypertension, and hyperlipidemia, all of which are known to contribute to the development of CKD.(16) Visceral adiposity causes inflammation and inflammatory cytokine (tumor necrosis factor and interleukin-6) production, which in turn result in impairment in insulin signaling and contribute to the development of diabetes.(17, 18) Diabetic nephropathy is characterized by excessive accumulation of extracellular matrix, thickening of the glomerular and tubular basement membranes, and increased amount of mesangial matrix, eventually resulting in progression to glomerulosclerosis and tubulointerstitial fibrosis.(19) Further, visceral fat and fat in the kidneys cause physical compression of the kidneys, activation of the renin-angiotensin-aldosterone system, and increased sympathetic nervous system activity, which may lead to hypertension.(20-22) Other factors such as inflammation, oxidative stress, and lipotoxicity may also contribute to obesity-mediated hypertension and renal dysfunction.(23) Features of hypertensive nephropathy include myointimal hyperplasia of the arterioles, hyaline arteriosclerosis, wrinkling of the basement membrane, collapse of the glomerular tuft, glomerulosclerosis, and tubulointerstitial involvement.(24)
In accordance with these mechanisms, interactions between diabetes and body weight, and between hypertension and body weight on the risk of incident CKD were noted in the present study. Previous studies have investigated the interaction between BMI and hypertension on the risk of kidney disease; however, the effects of the interaction between BMI and diabetes on the risk of kidney disease have been scarcely examined.(25, 26) Munkhaugen et al. analyzed data from the general Norwegian population, which revealed an interaction between blood pressure and BMI on the risk of end-stage renal disease or CKD-related death. Individuals with prehypertension were not at increased risk of serious kidney outcomes if the BMI was <30 kg/m2; however, the risk of CKD was found to increase substantially if prehypertension was present in obese participants (BMI ≥30 kg/m2).(25) Hsu et al. investigated a large cohort in northern California between 1964 and 1985 and reported that, compared with persons who had normal weight (BMI 18.5–24.9 kg/m2), those who were overweight (BMI 25.0–29.9 kg/m2) and obese (BMI ≥30 kg/m2) had significantly higher risks of incident end-stage renal disease, after adjustments for the baseline blood pressure level and diabetes mellitus. A higher BMI was independently associated with higher end-stage renal disease risk in all subgroups, including when the study population was analyzed according to the presence and absence of diabetes or hypertension.(26)
Previous studies have revealed that increased BMI is associated with increased risks of CKD in subjects with hypertension. Goncalves et al. evaluated whether longitudinal variations in BMI would reflect on changes in the estimated glomerular filtration rate (eGFR) in hypertensive individuals with excess body weight. The study showed a significant temporal association between changes in BMI and the eGFR in overweight and obese hypertensive patients.(27) Another cross-sectional study in an African population also confirmed the associations between high BMI (>25 kg/m2) and increased eGFR, effective renal plasma flow, and filtration fraction.(28) Further, the results from the Hypertension Detection and Follow-Up Program in Caucasian and African-American hypertensive adults also showed that both overweight (BMI 25–29.9 kg/m2) and obesity (≥30 kg/m2) were significantly associated with incident CKD.(29)
The current study showed that individuals with alcohol consumption had a significantly lower risk of incident CKD than those with no alcohol consumption (Table 2). However, the questionnaire regarding alcohol consumption was focused on the drinking pattern, and information on the total volume of alcohol consumed was not available. Epidemiological studies on the relation between alcohol consumption and CKD are scarce. In an Australian population-representative study, moderate-heavy alcohol consumption was suggested as an important modifiable risk factor for albuminuria in the general population.(30) In contrast, in a cohort study that passively followed a subset of participants in the second National Health and Nutrition Examination Survey, alcohol consumption did not appear as a risk factor for CKD.(11) Hence, the association between alcohol consumption and the development of CKD warrants further investigation.
The present study has some limitations that need to be considered. We analyzed self-reported information, including weight, height, education levels, household income, smoking status, and alcohol consumption, which might have introduced bias. Although the percentage of subjects refusing to provide consent to access the national health insurance data was low, the concern about selective missing for the detection of outcomes still exists. In addition, deaths were not recorded in the NHIS database, which may lead to bias from differences in the loss to follow-up. Because the mortality rate is higher for obese/underweight individuals than for normal-weight persons, this would lead to an underestimation of the association between obesity and incident CKD.(31) Moreover, this study only collected data on BMI at baseline, and the time-varying effect of BMI on CKD development was not evaluated. Although BMI tends to change only slightly over time, future studies should evaluate the time-varying effect of BMI on CKD development.(32) The present definition of CKD relied on the ICD-9-CM codes and prescription history, and the CKD outcomes may have been misclassified. This non-differential misclassification of outcome would most likely underestimate the effect of obesity/overweight on CKD development.
On the other hand, a major strength of this study is its retrospective cohort design, which avoids the problems of control selection in case-control studies and the obscured temporality in cross-sectional studies. We analyzed data from a nationally representative sample of the general population, and our results therefore have greater generalizability. In addition, the NHIS was designed and administered by an experienced national survey team and includes interview quality control. The study cohort was followed-up for at least three years, providing sufficient person-years to obtain a substantial number of CKD subjects and a certain level of statistical power. Finally, we adjusted for several important confounding variables, including socioeconomic status, smoking habits, alcohol consumption, and comorbidities, which were not available for many other related studies.
This cohort study of a general population in Taiwan suggests an association between BMI and the incidence of CKD, with obesity associated with a higher risk of new-onset CKD. In addition, we observed a strong linear dose-response relation of increasing BMI with higher risk of incident CKD. Since obesity is a preventable risk factor for CKD, our study suggests that maintaining a healthy weight is important for preventing the burden of CKD. Effective long-term weight reduction depends on permanent healthy eating habits and regular exercise. Both medical management and a comprehensive lifestyle program are essential to achieve a healthy life.
The authors are grateful to the members of the Research Office for Health Data, Department of Education and Research, Taipei City Hospital, Taiwan for their valuable contributions in data management and statistical analysis. This study was supported by the Department of Health, Taipei City Government (TPCH-104-005).
Disclosure of interest
The authors have no conflicts of interest or financial disclosures to report.
9. Zhou BF. Predictive values of body mass index and waist circumference for risk factors of certain related diseases in Chinese adults–study on optimal cut-off points of body mass index and waist circumference in Chinese adults. Biomed Environ Sci. 2002;15(1):83-96.
16. Klein S, Burke LE, Bray GA, Blair S, Allison DB, Pi-Sunyer X, et al.Clinical implications of obesity with specific focus on cardiovascular disease: a statement for professionals from the American Heart Association Council on Nutrition, Physical Activity, and Metabolism: endorsed by the American College of Cardiology Foundation. Circulation. 2004;110(18):2952-67.
18. Eckel RH, Kahn SE, Ferrannini E, Goldfine AB, Nathan DM, Schwartz MW, et al.Obesity and type 2 diabetes: what can be unified and what needs to be individualized? Diabetes Care. 2011;34(6):1424-30.
27. Goncalves Torres MR, Cardoso LG, de Abreu VG, Sanjuliani AF, Francischetti EA. Temporal relation between body mass index and renal function in individuals with hypertension and excess body weight. Nutrition. 2009;25(9):914-9.
28. Wuerzner G, Pruijm M, Maillard M, Bovet P, Renaud C, Burnier M, et al.Marked association between obesity and glomerular hyperfiltration: a cross-sectional study in an African population. Am J Kidney Dis. 2010;56(2):303-12.
32. Whitlock G, Lewington S, Sherliker P, Clarke R, Emberson J, Halsey J, et al.Body-mass index and cause-specific mortality in 900 000 adults: collaborative analyses of 57 prospective studies. Lancet. 2009;373(9669):1083-96.
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