Television Viewing Time and Risk of Chronic Kidney Disease in Adults: The AusDiab Study

Television Viewing Time and Risk of Chronic Kidney Disease in Adults: The AusDiab Study

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Abstract

Background: Television viewing time, independent of physical activity, is associated

with a number of chronic diseases and related risk factors; however, its relationship with

chronic kidney disease is unknown. Purpose: To examine the cross-sectional and

prospective relationships of television viewing time with biomarkers of chronic kidney

disease. Methods: Participants of the Australian Diabetes, Obesity and Lifestyle Study

(AusDiab) attended baseline (n=10,847) and 5-year follow-up (n=6,293) examination.

Results: Television viewing was significantly associated with increased odds of prevalent

albuminuria and low estimated glomerular filtration rate. In gender-stratified analyses this

pattern was seen for men, but not for women. In longitudinal analyses, odds of de novo

albuminuria and low estimated glomerular filtration rate were increased only in unadjusted

models. Conclusions: Television viewing time may be related to markers of chronic kidney

disease directly, and through intertwined associated risk factors such as diabetes,

hypertension and obesity.

Keywords: chronic kidney disease; physical activity; sedentary behavior; obesity

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Introduction

It has been estimated that 16% of Australian adults have some degree of chronic

kidney disease (1). While only a small proportion of these individuals will progress to end-

stage kidney disease, the sequelae of chronic kidney disease include significantly increased

risk of cardiovascular disease and impaired quality of life (2, 3). Chronic kidney disease may

be diagnosed without knowledge of the underlying cause by detection of markers of kidney

damage in the blood or urine.

Persistent elevation in either the amount of total protein, or specifically the amount of

albumin, being excreted in the urine are signs of kidney damage. Glomerular filtration rate is

considered the best overall measure of kidney function, theoretically indicating the filtration

rate of a single nephron multiplied by the number of functional nephrons. In clinical practice,

glomerular filtration rate is usually estimated from clearance of creatinine, a natural product

of muscle metabolism. As kidney function declines, the concentration of creatinine in the

blood rises, and this can be detected on a routine blood test. Persistent albuminuria and

reduced kidney function (measured according to estimated glomerular filtration rate) are the

principal markers of chronic kidney disease (4). Both albuminuria and a low estimated

glomerular filtration rate predict accelerated loss of kidney function, end-stage kidney failure,

cardiovascular morbidity and premature mortality (3, 5, 6).

Lack of moderate- to vigorous-intensity physical activity is a risk factor for many

common chronic diseases (7), and has been linked with risk of chronic kidney disease (8, 9).

New evidence indicates that sedentary behavior is associated with obesity, abnormal

glucose metabolism and other indicators of cardio-metabolic dysfunction, independent of

moderate- to vigorous-intensity physical activity time (10). Evidence suggests that sedentary

behavior contributes to the development of chronic disease through its well-acknowledged

contribution to reduced overall energy expenditure and through unique physiological

processes such as regulation of lipoprotein lipase (11, 12). The large skeletal muscles

involved in posture and upright movement are largely inactive during sedentary behaviors

such as television viewing or sitting at a computer. This may impede the body’s ability to

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regulate blood lipids as well as reducing overall cumulative daily energy expenditure (11,

12).

Technological and social factors have made prolonged sitting commonplace during

both occupational and leisure time (13). Within epidemiological and health-behavior

research, the measurement of adults’ sedentary time has largely focused on leisure-time

activities, in particular television viewing time (14), which accounts for over 40% of the

leisure-time sedentary behavior of Australian adults (15). Television viewing time,

independent of physical activity, is associated with chronic-disease risk biomarkers,

including higher waist circumferences, and elevated levels of plasma glucose and lipids (16-

18); however, it is unknown whether television viewing time is associated with chronic kidney

disease. Given that glucose dysregulation is a key risk factor for the development of chronic

kidney disease, it is probable that sedentary behavior plays at least an indirect role as a

modifiable risk factor for the development and progression of kidney damage. This is

suggested by the previous observation that insufficient physical activity is a stronger

predictor of risk of kidney damage due to diabetic nephropathy than other forms of chronic

kidney disease (9). Additional pathways by which sedentary behavior may increase risk of

kidney damage include altered haemodynamics associated with obesity, though factors

associated with central adiposity such as lipid abnormalities and inflammation are suggested

to contribute to progressive loss of kidney function (19). Whether sedentary behavior is

directly or indirectly linked with chronic kidney disease has not been investigated.

We used data from a prospective, population-based study of Australian adults to

examine the cross-sectional and prospective relationships of television viewing time with

chronic kidney disease biomarkers (albuminuria and estimated glomerular filtration rate).

We hypothesized that prolonged periods of television viewing would be associated with a

higher prevalence of chronic kidney disease, and with the onset of new disease, and that

these relationships would be independent of physical activity and adiposity.

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Methods

Study sample and design

The Australian Diabetes, Obesity and Lifestyle Study (AusDiab) is a prospective

study of diabetes and related risk factors in representative sample of the national population

aged 25 years and over. A detailed description of the methodology has been previously

published (20). A stratified cluster-sampling method was used, with a total of 25,984

households in 42 selected clusters approached, from which 20,347 eligible adults

participated in an initial interview. Of this number, 11,247 took part in baseline biomedical

examinations, which occurred 1999-2001. For the purpose of this study, we excluded

participants who had missing values for any of the required variables (n=400). This left a

final baseline sample of 10,847 (4,878 men and 5,969 women). From this baseline cohort,

6,293 participants with complete urinalysis and serum creatinine measurements taken during

five-year follow-up examinations in 2004-2005 formed the study population for the

longitudinal analyses (see Figure 1). The study was approved by the Ethics Committee of

the International Diabetes Institute, and written informed consent was obtained from all

participants.

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INSERT FIGURE 1 ABOUT HERE

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Data collection

At both data collection time-points, participants attended their local survey site after

an overnight fast (minimum eight hours). The specific measurement protocols have been

described in previous publications (20, 21). In brief, participants underwent a physical

examination that included blood pressure measurements, collection of blood by

venipuncture, collection of a random spot morning urine specimen and a standard 75g oral

glucose tolerance test (with the exception of those who had failed to fast). Participants who

reported existing diabetes and those who were pregnant were also excluded from the oral

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glucose tolerance test, as increases in blood glucose can cause nausea and vomiting in

these groups. Blood and urine samples were transferred to a central laboratory for analysis

(baseline: HITECH Pathology, Clayton, Victoria; follow-up: Gribbles Pathology, Clayton,

Victoria). Waist circumference was measured halfway between the lower ribs and the iliac

crest in a horizontal plane using a steel measuring tape. Hip circumference was measured

at the widest point over the buttocks. Two waist and hip measurements were taken, and if

the variation between measurements was greater than 2cm, then a third measurement was

taken. Obesity was defined as a waist to hip ratio (cm/cm) of >1.0 in males and >0.85 in

females.

The following demographic and health-related attributes were assessed using

an interviewer-administered questionnaire: educational attainment (did you complete the

highest year of secondary school available, yes/no), employment (do you have a full time or

part time job of any kind, yes/no), heavy alcohol consumption (have you ever considered

yourself a heavy drinker, yes/no), smoking (do you currently smoke cigarettes, cigars, pipes,

or any other tobacco products, yes/no), use of blood pressure lowering medication (are you

currently taking tablets for high blood pressure, yes/no), and prior cardiovascular events

(have you ever been told by a doctor or nurse that you have any of the following: angina,

heart attack or stroke, yes/no). Presence of diabetes was defined as current use of insulin

or glucose lowering medications, or a fasting or post load glucose value in the diabetic range

(≥ 7.0 mmol/l for fasting; ≥ 11.1 mmol/l for 2-hour glucose) (22).

The Active Australia Survey, a standard instrument used in Australian adult

population surveys (23, 24), was used to assess physical activity. Participants reported the

amount of time they spent each week walking for transport or recreation, in other moderate-

intensity physical activities and in vigorous-intensity physical activities. Total weekly physical

activity was calculated by adding together the time spent in each activity category (vigorous

activity was double-weighted to account for additional energy expenditure) (23). Current

Australian public-health guidelines advocate achieving the equivalent of 150 minutes of

moderate-intensity activity per week (25). Based on these guidelines, participants were

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categorized as being either insufficiently active (149 minutes or less per week) or sufficiently

active (150 minutes or more per week).

Participants were asked to estimate total time spent watching television or

videos (hours and minutes) on weekdays and weekends during the previous week. These

values were summed to give total television viewing time per week, and then divided by

seven for hours of television viewing per day. This method of estimating television viewing

time has been shown to be reliable (intra-class correlation from a one week test-retest

protocol = 0.82 [0.75, 0.87]) and valid (criterion validity from a three-day sedentary behavior

log comparison, ρ = 0.30) (26). Three categories of television viewing time (≤ 2, 2 - 3.9 and

≥ 4 hours/day) were created, based on levels that have been previously associated with

chronic disease-related risk factors (27, 28).

Main outcome measures

Urine albumin and creatinine were measured on a morning spot urine sample.

Baseline urine creatinine was measured using the modified kinetic Jaffe reaction using an

Olympus AU600 auto-analyser and urine albumin measured by rate nephelometry using a

Beckman Array (Beckman/Coulter, Sydney, Australia). At follow-up, urine creatinine was

measured using the spectrophotometric-jaffe alkaline picrate method on a Roche Modular

(Roche Diagnostics), and urine albumin measured by nephelometry on a Beckman Immage

(Beckman Coulter, Inc.). Serum creatinine was measured at baseline and 5-year follow-up

by the modified kinetic Jaffe reaction, using the Olympus AU600 auto-analyser at baseline,

and in 2004-2005 the Roche Modular. Serum creatinine measurements were subsequently

calibrated to the Isotope Dilution Mass Spectrometry method by re-assaying stored

subsamples from both surveys (baseline n=239, follow-up n=295) at Monash Medical Centre

(Beckman/Coulter, Sydney, Australia). Glomerular filtration rate was estimated using the

“re-expressed” Modification of Diet in Renal Disease study prediction formula using the

calibrated serum creatinine values (4):

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glomerular filtration rate (mL/min/1.73 m2) = 175*[serum creatinine(mg/dl)-.15]*(age-0.203).

*(0.742 for women)

Cross-sectional outcomes were: albuminuria, defined as an albumin to creatinine

ratio >2.5 in men and >3.5 mg/mmol in women; and, low estimated glomerular filtration rate,

defined as estimated glomerular filtration rate<60 mL/min/1.73m2. In clinical settings, the

diagnosis of chronic kidney disease requires a glomerular filtration rate <60 mL/min/1.73m2

persistent for at least three months (4). However, in the AusDiab study (as in other large

scale cohort studies) only single measurements of serum creatinine were taken at baseline

and follow-up.

Five-year follow-up outcomes were: de novo albuminuria, defined as a doubling of

albumin to creatinine ratio over 5 years with a final albumin to creatinine ratio >2.5 in men

and >3.5 mg/mmol in women, in the absence of albuminuria at baseline; and, de novo low

estimated glomerular filtration rate, defined as a 5-year decline in estimated glomerular

filtration rate of >10% with estimated glomerular filtration rate >60 mL/min/1.73m2 at baseline

and a final estimated glomerular filtration rate <60 mL/min/1.73m2.

Statistical analyses

In cross-sectional analyses, logistic regression models were constructed to examine

the associations between television viewing time categories and dichotomous kidney

outcomes. Models were adjusted for age and gender, with subsequent adjustment for

lifestyle factors (physical activity, current smoking, heavy alcohol consumption, waist to hip

ratio, employment status), or for other relevant biomedical factors (prevalent diabetes, use of

blood pressure lowering medications, systolic blood pressure and serum total cholesterol).

Gender-specific models were then generated as men and women are known to differ in their

television viewing time (29) and health outcomes from prolonged viewing (17, 30).

Interaction terms were added to the fully-adjusted models to see whether there were any

differences in effect by obesity or physical activity category.

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In longitudinal analyses, logistic regression was used to determine the effect of

baseline television viewing category on age- and gender-adjusted probability of developing

de novo albuminuria or de novo low estimated glomerular filtration rate. There were

insufficient cases of de novo albuminuria or estimated glomerular filtration rate to allow

gender-specific analyses.

All statistical analyses were conducted using Stata Statistical Software version 10.1

(StatCorp, College Station, Texas). Standard errors of all logistic regression estimates were

corrected for the stratified-cluster sampling method used in the survey, to account for

potential intra-cluster correlation. In longitudinal analyses, standard errors were adjusted

according to applicable cluster and strata at baseline, not taking into account subsequent

movement between clusters or strata. Significance was accepted at p<0.05.

Results

Characteristics of the 10,847 participants who formed the baseline sample are shown

in Table 1. These descriptive data, presented across television viewing categories, show

graded relationships with chronic disease risk factors and outcomes, namely: waist to hip

ratio; obesity; diabetes; total serum cholesterol; systolic blood pressure; albumin to

creatinine ratio; and, estimated glomerular filtration rate. At five-year follow-up, the mean

age of participants was 55 years (standard deviation = 12 years), 46% were men and 57%

reported participating in 150 minutes or more of moderate-intensity physical activity per

week. Fifty-five per cent of participants reported watching less than two hours of television

per day; 36% watched between two and 3.9 hours; and 9% reported watching more than

four hours of television per day. The median albumin to creatinine ratio for participants at

five-year follow-up was 0.5 (inter-quartile range = 0.5) and the mean estimated glomerular

filtration rate was 76.1 mL/min/1.73m2 (standard deviation = 10.6 mL/min/1.73m2).

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INSERT TABLE 1 ABOUT HERE

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The results of the cross-sectional logistic regression analyses are shown in Table 2.

All unadjusted analyses revealed that, compared with participants who reported watching

less than two hours of television per day, participants who watched higher levels of television

had significantly increased odds of albuminuria and low estimated glomerular filtration rate.

However, after adjusting for age and gender, only participants who watched four or more

hours of television per day had significantly increased odds of prevalent albuminuria (odds

ratio = 1.28, 95% confidence interval: 1.01, 1.62) or low estimated glomerular filtration rate

(odds ratio = 1.26, 95% confidence interval: 1.00, 1.58). In gender-specific analyses, men

who reported four or more hours of television viewing had significant associations with

albuminuria after adjustment for age (odds ratio = 1.46, 95% confidence interval: 1.06, 2.01).

This association was robust to additional adjustment for biomedical factors (odds ratio =

1.44, 95% confidence interval: 1.03, 2.02), but was largely abrogated with adjustment for

lifestyle-related factors including physical activity, smoking, alcohol consumption, waist to hip

ratio and employment status (odds ratio = 1.19, 95% confidence interval: 0.86, 1.65).

A statistically significant association with prevalence of low estimated glomerular

filtration rate was observed for men in the highest television viewing category after

adjustment for age and lifestyle factors (odds ratio = 1.47, 95% confidence interval: 1.02,

2.12), and also after adjustment for age and biomedical factors (odds ratio = 1.58, 95%

confidence interval: 1.10, 2.27). A significant interaction between television viewing time and

obesity was found for men in the estimated glomerular filtration rate models. Amongst men

who were not obese (n=4,200), there were no statistically significant associations between

television viewing and low estimated glomerular filtration rate. In obese men (n=678),

compared with men who reported watching less than two hours of television per day, men

who watched higher levels were more likely to have low estimated glomerular filtration rate

after adjustment for age and lifestyle factors (2.0 – 3.9 hrs/day odds ratio = 2.51, 95%

confidence interval: 1.19, 5.30; ≥ 4 hrs/day odds ratio = 3.18, 95% confidence interval: 1.40,

7.27), and after adjustment for age and biomedical factors (2.0 – 3.9 hrs/day odds ratio =

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2.24, 95% confidence interval: 1.07, 4.69; ≥ 4 hrs/day odds ratio = 4.11, 95% confidence

interval: 1.80, 9.35).

There were no significant cross-sectional, multivariate associations for women.

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Baseline television viewing (2.0 – 3.9 hours per day compared with < 2 hours per

day) was significantly associated with five year onset of albuminuria (odds ratio = 1.59, 95%

confidence interval: 1.15, 2.20) and with de novo low estimated glomerular filtration rate

(odds ratio = 1.46, 95% confidence interval: 1.20, 1.77 for 2.0 – 3.9 hours/day; odds ratio =

2.04, 95% confidence interval: 1.48, 2.82 for ≥ 4.0 hours/day) in the unadjusted models.

However, none of the multivariate adjusted models for either de novo albuminuria or low

estimated glomerular filtration rate were statistically significant (Table 3).

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Discussion

Sedentary behavior (particularly television viewing) has been associated with several

risk factors for chronic vascular disease including obesity (27, 31, 32), type 2 diabetes (28,

31), abnormal glucose metabolism (16), high blood pressure (33) and the metabolic

syndrome (17, 27, 34). This large, population-based, prospective study looks for the first

time at the associations between television viewing and markers of chronic kidney disease.

Our analysis indicates deleterious cross-sectional associations between higher categories of

television viewing time and kidney outcomes among men. Observed associations persisted

with adjustment for age and biomedical factors including diabetes, blood pressure and

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cholesterol. The relationship between television viewing and prevalence of a low estimated

glomerular filtration rate in men was also robust to adjustment for lifestyle-related factors

including physical activity, smoking, alcohol consumption, employment and anthropometric

measurements. Overall, adjusted odds of prevalent chronic kidney disease were increased

approximately 50% among men who watched four or more hours of television per day

compared with men who watched less than two hours per day. Interestingly, although a

similar trend was observed in unadjusted analyses, associations between television viewing

and prevalence of albuminuria and estimated glomerular filtration rate in women were

entirely attenuated following adjustment for age. Although trends towards increased five-

year risk of de novo albuminuria and low estimated glomerular filtration rate for higher

categories of television viewing time were observed in unadjusted longitudinal models, these

associations were also non-significant after adjustment for age.

Reasons for the observed gender difference in the relationship between television

viewing category and chronic kidney disease prevalence are not entirely clear. Observed

relationships between self-reported prolonged television viewing time and cardiovascular risk

factors, including abnormal glucose metabolism and the metabolic syndrome, have been

found to be stronger for women than men (17, 29), although these gender differences are

not generally observed for objectively-assessed sedentary time (35). In this cohort current

smoking, heavy alcohol consumption, inadequate physical activity and obesity, factors which

have each been independently linked with kidney outcomes (8, 36), were all more prevalent

among participants who watched more than four hours of television per day. It is well

established that men are overrepresented among end-stage kidney disease patient

populations (37, 38). At the same time, numerous studies have reported that the harmful

effects of lifestyle-related risk factors, in particular smoking and obesity, on kidney outcomes

are restricted to men (39-43). Whether kidney function is truly more susceptible to these risk

factors in men compared with women is disputed (8), although in the case of obesity it is

known that males store a greater proportion of total body fat as visceral fat which is more

closely associated with risks of chronic disease and premature mortality than is glutrofemoral

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obesity (44). This was evidenced in the significant interaction between television viewing

time and obesity observed in the estimated glomerular filtration rate models for men. It is

possible that the observed association between television viewing and chronic kidney

disease prevalence may therefore in part be mediated by the atherosclerotic effects of

abdominal obesity in men, less prevalent in women. Furthermore, it is known that the

vasoprotective effects of estrogen in women result in cardiovascular disease manifesting

approximately ten years later than in men (45). In our population-based cohort

premenopausal women may lag behind men in terms of chronic vascular disease outcomes,

precluding the observation of a cross-sectional relationship between television viewing and

kidney-related outcomes at baseline in women.

Although the associations between television viewing and chronic kidney disease

were for some groups attenuated by age, lifestyle factors and biomedical factors, there

remain clinically warranted reasons for decreasing sedentary behavior. Known risk factors

for chronic kidney disease, namely diabetes, hypertension and obesity, are independently

associated with sedentary behavior (26, 27, 31). Decreasing the prevalence of these risk

factors is likely to subsequently lower incident cases of chronic kidney disease, and, among

individuals with existing chronic kidney disease, reduce the risk of progressing to end stage

kidney disease.

The strengths of this study are its large, representative sample, the objective

measures of chronic kidney disease, the detailed anthropometric assessments, and the

ability to examine both cross-sectional and longitudinal relationships. Television viewing

time and physical activity were self-reported past-week estimates, and hence may be limited

by recall error and social desirability bias. Physical activity was assessed using the standard

self-report items used in Australian population surveys, which deal mainly with leisure -time

activities and which can include major discretionary components. Thus, under-reporting of

television viewing time and over-reporting of physical activity may have introduced

measurement error and limited the possibility of statistically significant associations emerging

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in the study analyses. Another limitation of the study included significant losses to follow-up

in the prospective cohort. Although we observed a significant, multivariate-adjusted, cross-

sectional association between television viewing and kidney outcomes in men, the possibility

of reverse causation, whereby sedentary behavior increases as a result of poor health, is a

limitation of cross-sectional analyses. No robust prospective association could be

demonstrated in these analyses; therefore inferences regarding causality cannot be made

on the basis of our findings. Additionally, only a single sedentary behavior (television

viewing) was examined. Future research should incorporate more comprehensive self-

report measures of sedentary behavior that assess a variety of common activities that may

contribute to an individual’s prolonged sitting time. If possible, use of devices such as

accelerometers would allow the objective measurement of sedentary time across the day

(not just leisure time), and would capture physical activity across the range of intensities.

These results show a deleterious cross-sectional association between greater

television viewing hours and kidney outcomes among men, however these data did not

demonstrate longitudinal associations between television viewing time and the onset of

albuminuria or low estimated glomerular filtration rate. There may be a number of

explanations for this. While the cross-sectional analyses considered the prevalence of

chronic kidney disease markers in the study sample, the longitudinal analyses were based

on the small number of de novo kidney outcomes occurring in participants who did not have

albuminuria or low estimated glomerular filtration rate at baseline, but developed these in the

subsequent five years. It is possible that five years of follow-up is not a long enough latency

period to observe true associations with behavioral factors such as television viewing. The

small number of de novo cases of albuminuria and low estimated glomerular filtration rate

meant it was not feasible to do gender-specific analyses; if a true gender effect exists, as

indicated by our cross-sectional findings, any significant association for men would be

diluted when data for men and women were analyzed together. Nonetheless this is the first

analysis to examine a possible link between sedentary behavior, in this case television

viewing, and chronic kidney disease, and future prospective studies may be able to verify

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this association and further explore the relative importance of sedentary behavior to kidney

outcomes in men versus women. Males in particular at risk of chronic kidney disease may

benefit not only from participation in regular moderate to intensive physical activity but also

by minimizing time spent watching television and in other sedentary behaviors.

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Table 1: Baseline characteristics of the cross-sectional sample, by television-viewing category

Television-viewing category

Characteristic UnitsAll participants(n = 10,847)

< 2 hrs/day(n = 5,993)

2 – 3.9 hrs/day(n = 3,939)

≥ 4 hrs/day(n = 915)

Age years 51.6 (14.4) 49.4 (13.4) 53.5 (14.8) 57.4 (15.5)

Men % 46.0 42.6 47.9 48.5

Completed high school % 46.3 51.7 40.9 34.1

Employed (full- or part-time job) % 59.1 67.9 52.6 29.8

Current smoker % 15.5 13.8 16.2 24.0

Ever a heavy drinker % 14.3 13.4 14.8 18.5

Physical activity ≥ 150mins/wk % 52.2 53.0 52.4 45.8

Waist to hip ratio cm/cm 0.87 (0.09) 0.85 (0.09) 0.88 (0.09) 0.9 (0.09)

Obese † % 20.6 16.9 23.1 33.9

Diabetes % 4.1 3.0 5.0 7.8

Use of blood pressure lowering medication % 15.8 12.4 18.7 24.8

Total serum cholesterol mmol/L 5.66 (1.07) 5.58 (1.03) 5.73 (1.1) 5.83 (1.09)

Systolic blood pressure mmHg 129.49 (18.83) 127.19 (18.04) 131.74 (19.21) 134.88 (20.00)

Albumin to creatinine ratio mg/mmol 0.55 (0.58) 0.53 (0.50) 0.57 (0.64) 0.65 (0.86)

Estimated glomerular filtration rate mL/min/1.73m2 74.55 (11.74) 79.88 (14.34) 77.84 (15.30) 75.43 (15.71)

Data are crude means (SD) and proportions, with the exception of albumin to creatinine ratio which is non-normally distributed therefore data are median (inter-quartile range).†Obesity defined as waist to hip ratio >1.0 in men and >0.85 in women.

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Table 2: Multivariable logistic regression results describing cross-sectional associations between television viewing category and markers of chronic kidney disease

Model 1 Model 2 Model 3 Model 4

OutcomeTelevision-viewing time Cases OR 95% CI OR 95% CI OR 95% CI OR 95% CI

All participants (n = 10,847) Albuminuria < 2 hrs/day 375 1.00 - 1.00 - 1.00 - 1.00 -

2 – 3.9 hrs/day 317 1.31 1.13 , 1.54 1.02 0.87 , 1.20 0.96 0.82 , 1.13 0.95 0.80 , 1.12≥ 4 hrs/day 108 1.99 1.59 , 2.50 1.28 1.01 , 1.62 1.08 0.85 , 1.38 1.15 0.90 , 1.48

Low eGFR < 2 hrs/day 399 1.00 - 1.00 - 1.00 - 1.00 -2 – 3.9 hrs/day 407 1.61 1.39 , 1.86 1.06 0.90 , 1.24 1.03 0.88 , 1.21 1.04 0.88 , 1.22≥ 4 hrs/day 141 2.55 2.08 , 3.14 1.26 1.00 , 1.58 1.19 0.95 , 1.51 1.22 0.97 , 1.53

Men (n = 4,878) Albuminuria < 2 hrs/day 187 1.00 - 1.00 - 1.00 - 1.00 -

2 – 3.9 hrs/day 175 1.29 1.04 , 1.60 1.08 0.86 , 1.35 1.00 0.80 , 1.26 1.00 0.79 , 1.27≥ 4 hrs/day 64 2.13 1.57 , 2.88 1.46 1.06 , 2.01 1.19 0.86 , 1.65 1.44 1.03 , 2.02


Women (n = 5,969) Albuminuria < 2 hrs/day 187 1.00 - 1.00 - 1.00 - 1.00 -

2 – 3.9 hrs/day 142 1.29 1.03 , 1.62 1.00 0.79 , 1.26 0.95 0.75 , 1.20 0.93 0.73 , 1.18≥ 4 hrs/day 43 1.75 1.24 , 2.47 1.13 0.79 , 1.62 1.01 0.70 , 1.46 0.93 0.64 , 1.36


eGFR: estimated glomerular filtration rate.Model 1: ORs unadjusted.Model 2: ORs adjusted for age and gender. Model 3: ORs adjusted for the variables from Model 2 plus baseline physical activity (“insufficiently active” or “sufficiently active”), current smoking (y/n), ever heavy drinker (y/n), waist to hip ratio (cm/cm), and employment status (y/n).Model 4: ORs adjusted for the variables from Model 2 plus prevalent diabetes (y/n), use of blood pressure lowering medications (y/n), systolic blood pressure (mm Hg) and serum total cholesterol (mmol/L). Interaction terms added as Model 5: TV*obesity significant in eGFR model for men (p=0.011), NS for all other models; TV*physical activity NS for all models.

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Table 3: Multivariable logistic regression results describing prospective associations between television viewing category and markers of chronic kidney disease

Model 1 Model 2 Model 3 Model 4

OutcomeTelevision-viewing time Cases OR 95% CI OR 95% CI OR 95% CI OR 95% CI

de novo albuminuria† < 2 hrs/day 79 1.00 - 1.00 - 1.00 - 1.00 -2 – 3.9 hrs/day 72 1.59 1.15 , 2.20 1.22 0.87 , 1.72 1.15 0.82 , 1.63 1.19 0.84 , 1.68≥ 4 hrs/day 12 1.41 0.76 , 2.62 0.94 0.49 , 1.81 0.80 0.41 , 1.56 0.86 0.45 , 1.67

de novo low eGFR§ < 2 hrs/day 248 1.00 - 1.00 - 1.00 - 1.00 -2 – 3.9 hrs/day 203 1.46 1.20, 1.77 1.12 0.91 , 1.39 1.07 0.86 , 1.33 1.12 0.91 , 1.39≥ 4 hrs/day 51 2.04 1.48 , 2.82 1.25 0.86 , 1.80 1.13 0.78 , 1.63 1.23 0.85 , 1.78

eGFR: estimated glomerular filtration rate.Model 1: ORs unadjusted.Model 2: ORs adjusted for age, gender and baseline log albumin to creatinine ratio (for de novo albuminuria) or baseline eGFR (for de novo low eGFR). Model 3: ORs adjusted for the variables from Model 2 plus baseline physical activity (“insufficiently active” or “sufficiently active”), current smoking (y/n), ever heavy drinker (y/n), waist to hip ratio (cm/cm), and employment status (y/n).Model 4: ORs adjusted for the variables from Model 2 plus prevalent diabetes (y/n), use of blood pressure lowering medications (y/n), systolic blood pressure (mm Hg) and serum total cholesterol (mmol/L). Interaction terms added as Model 5: TV*obesity NS for all models; TV*physical activity NS for all models.†De novo albuminuria defined as a doubling of urinary albumin to creatinine ratio over 5 years with a final albumin to creatinine ratio ≥ 2.5 in men and ≥ 3.5 mg/mmol in women, in the absence of albuminuria at baseline; §De novo low eGFR defined as a 5-year decline in eGFR of ≥10% with eGFR ≥ 60 mL/min/1.73m2 at baseline and a final eGFR <60 mL/min/1.73m2.

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Television Viewing Time and Risk of Chronic Kidney Disease in Adults: The AusDiab Study