Predictors of decline in kidney function in the general population: a decade of follow-up from the Tehran Lipid and Glucose Study

Abstract

Background and aims

We aimed to assess the potential socio-demographic, clinical, and lifestyle-related risk factors for kidney function decline (KFD), defined as ≥30% estimated glomerular filtration rate (eGFR) decline, in an Iranian cohort study.

Methods

7190 participants (4049 women) aged 20–90 years with 2–5 eGFR data from examinations (2001–2005 to 2015–2018) were included. Cox proportional hazard models were used to examine the association between potential risk factors and eGFR decline.

Results

During 11.5 years of follow-up, 1471 (889 women) participants had incident KFD with a crude incidence rate of 192.1 (182.6–202.2) per 10,000 person-year. Among the total population, older age, female gender, prehypertension, hypertension, diabetes, widowed/divorced states, higher triglycerides (TG), prevalent cardiovascular diseases (CVD), and higher baseline eGFR were significantly associated with higher, while moderate physical activity and a positive family history of diabetes were associated with lower risk of KFD (all p values <.05). Prevalent CVD in women but not men, diabetes, and hypertension among postmenopausal than premenopausal women were significant risk factors of KFD. According to the presence of chronic kidney disease (CKD) at baseline, higher eGFR decreased the risk of KFD in patients with CKD and increased KFD risk in those without CKD (all p for interactions <.05).

Conclusion

KFD is associated with multiple modifiable risk factors among the Iranian urban population that is affected by gender, menopausal status, and initial kidney function. Interventions targeting these factors might potentially help reduce the burden of KFD.

Key messages:

• Menopausal status may influence the relationship between cardiometabolic risk factors and KFD;

• The impact of higher baseline eGFR on the risk of KFD differed between subjects with preserved kidney function and CKD patients.

• The interaction between gender, menopausal status, and baseline kidney function with different risk factors on KFD may help to make renal risk prediction scores to identify those in the general population at risk who may benefit from early prevention.

Keywords:

• eGFR decline
• gender differences
• kidney disease progression
• risk factors
• Tehran Lipid and Glucose Study

Introduction

The Middle East and North Africa (MENA) region has a high and increasing burden of CKD, with more than 48 million subjects suffering from CKD in 2017 [1]; also, the age-standardized prevalence rate of CKD has increased by 37.6% for both genders during the past 3 decades [2]. The prevalence and incidence of CKD also appear to be high among Iranians [3,4], with more than 2% of the population developing CKD annually [4]. While current evidence and clinical practice guidelines regarding primary and secondary prevention of cardiovascular morbidity and mortality focus on the progression of CKD toward end-stage kidney diseases (ESKD), several reports have shown an increased rate of poor health outcomes among people with a moderate deterioration in kidney function [5–10]. Considering the high CVD burden attributable to impaired kidney function in the MENA region [1], it is important to identify risk factors for eGFR decline as a surrogate endpoint for kidney disease incidence and progression.

Multiple studies have reported gender-specific differences in the risk factors for eGFR decline [11–15]. Among CKD patients, the rate of decline in eGFR has been reported to be faster in men, with a higher risk of progression to kidney replacement therapy among men compared to women [16], while women of postmenopausal age are shown to have a faster rate of kidney disease progression [17]. However, results about gender disparities in KFD are still controversial; therefore, the role of its sex-specific predictors remains to be further elucidated.

Most studies on the predictors of KFD have used incident CKD or ESKD, and the remaining studies on longitudinal changes of eGFR are limited by relatively small numbers [18–22] and lack of sequential measurements in kidney function [14,15,18–20,22]. More importantly, to our knowledge, the effect modification of the presence or absence of CKD and menopausal status on potential risk factors for KFD was not addressed in previous studies using appropriate statistical methods. Moreover, current studies have been conducted mainly on American, European, and East Asian populations [14,15,18–25] with a lower age-standardized rate of CVD disability-adjusted life-years (DALYs) attributable to impaired kidney function than MENA region [1].

Hence, this study aimed to investigate the association of potential socio-demographic, clinical, and lifestyle-related risk factors with the risk of KFD, defined as eGFR decline ≥30% [7,26,27], and also the potential effect modification of gender, menopausal status, and baseline kidney function status on KFD risk in the large-scale, long-term, and population-based cohort study known as Tehran Lipid and Glucose Study (TLGS).

Materials and methods

Study design and participants

The TLGS is a large-scale, population-based, prospective cohort study first established to determine the epidemiology of non-communicable diseases (NCDs) and their subsequent risk factors. TLGS enrollment was carried out in two phases: the first enrolment phase was from January 31, 1999, to July 03, 2001, and the second one was from October 20, 2001, to September 22, 2005. Follow-up examinations occurred at approximately 3-year intervals: 2005–2008 (phase 3), 2008–2011 (phase 4), 2011–2014 (phase 5), and 2015–2018 (phase 6). The design, registration, data collection protocols, and survey instruments of the TLGS have been described previously [28].

In the current study, 9138 individuals who were 20 years or older and entered the second phase (2001–2005) were considered for inclusion. As shown in Figure 1, after excluding those with missing values for any of the analyzed variables (N = 1258, considering overlapping features) and subjects without any follow-up measurements after baseline recruitment (N = 690), 7190 individuals (women = 4049) remained for the analysis.

Figure 1. Flow chart of inclusions and exclusions of the study participants. SBP: systolic blood pressure; DBP: diastolic blood pressure; TC: total cholesterol; HDL-C: high-density lipoprotein cholesterol; TG: triglycerides; FPG: fasting plasma glucose; 2-h PG: 2-hour post-challenge plasma glucose; Scr: serum creatinine; eGFR: estimated glomerular filtration rate.

The proposal of this study was approved by the institutional review board of the Research Institute for Endocrine Sciences of Shahid Beheshti University of Medical Sciences, and each participant gave written informed consent.

Clinical and laboratory measurements

A standard questionnaire was used to collect demographic information, smoking status, past medical history of CVD, family history of diabetes (FH-DM), drug history, education status, physical activity, and marital status from the study participants. Body measurements of the study population [weight (kg) and height (cm)] were recorded while participants were minimally clothed and removed their shoes. Waist circumference (WC) was measured at the level of the umbilicus while wearing light clothing. After resting for 15 min sitting, the systolic and diastolic blood pressures (SBP and DBP) were measured two times by trained personnel on the right arm with a standard mercury sphygmomanometer. We used the Modifiable Activity Questionnaire (MAQ) to collect data on physical activity [29]; the psychometric properties of the Iranian version of MAQ have been examined among the population from TLGS, with high reliability and acceptable validity [30]. After a 12–14 h overnight fasting, blood samples for biochemical analysis were collected between 7:00 and 9:00 am. For the 2-h post-challenge plasma glucose (2-h PG), subjects not using glucose-lowering medication took 82.5-gram glucose monohydrate solution, and a blood sample was taken 2 h later. Details for laboratory measurements including plasma glucose and lipid profile (i.e. TG, total cholesterol [TC], and high-density lipoprotein cholesterol [HDL-C]) are reported elsewhere [28]. Kidney function was measured by serum creatinine levels (Scr), assayed by kinetic colorimetric Jaffe using commercial kits (Pars Azmoon Inc., Tehran, Iran) and a Selectra 2 auto-analyzer (Vital Scientific, Spankeren, The Netherlands). The sensitivity of the assay was 0.2 mg/dL, and reference intervals according to the recommendations of the manufacturer were 80–115 μmol/L in men and 53–97 μmol/L in women. Both intra- and inter-assay coefficient of variations were <3.1% in all phases. After every 25 tests, an assay performance monitoring was conducted using lyophilized serum controls in normal and abnormal ranges. Analysis of each sample was done only if the internal quality control met acceptable criteria and it was performed on the same day of blood collection at the TLGS research laboratory.

Outcome

The study endpoint was KFD, defined with ≥30% decline in eGFR during follow-up from baseline. This endpoint was recently recommended as a surrogate marker for CKD progression [7,26,27].

Definition of terms

Potential exposures included age (20–34 years (reference), 35–49 years, 50–64 years, and ≥65 years for both genders), gender (male as reference), general obesity status defined as BMI <25 kg/m² [reference], 25–30 kg/m² (overweight), and ≥30 kg/m² (obese). Other exposures included education (<6 years, 6–12 years, and >12 years [reference]), marital status (single, married [reference], divorced/widowed), and smoking (current, past, and never [reference]). Based on the recommendations of JNC 7 Guidelines [31], we categorized the baseline blood pressure of the study participants into 3 groups; optimal, normal: SBP <120 mmHg and DBP <80 mmHg (reference), prehypertension: SBP 120–139 mmHg and/or DBP 80–90 mmHg, and hypertension: SBP ≥140 mmHg or DBP ≥90 mmHg or taking antihypertensive medications. FH-DM was defined as a positive report of diabetes in a first-degree relative. History of CVD was any history of percutaneous coronary intervention, acute coronary syndrome leading to CCU admission, coronary artery bypass graft, angiographic proven coronary artery disease, or history of cerebrovascular accidents.

Diabetes mellitus was defined as having FPG ≥7 mmol/L (≥126 mg/dL) and/or 2-h PG ≥11.1 mmol/L (≥ 200 mg/dL) and/or the use of glucose-lowering medications. Additionally, prediabetes status was defined with 5.6≤ FPG <7 mmol/L (100–125 mg/dL) or 7.8 ≤ 2-h PG <11.1 mmol/L (140–199 mg/dL). Having FPG <5.6 mmol/L and 2-h PG <7.8 was considered normal glucose status. Physical activity levels were categorized based on the average metabolic equivalent tasks score (METs); sufficiently active: physical activity of ≥1500 MET mins/wk, moderately active: 600–1500 MET mins/wk, and inactive: <600 MET mins/wk. CKD at baseline was defined as eGFR <60 mL/min/1.73 m² [32]. eGFR was estimated with the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation [33]: $$\begin{array}{l}\text{eGFR}=\text{141}\times \text{min}{\left(\text{Scr}/\kappa ,\text{1}\right)}^{\text{α}}\times \text{max}{\left(\text{Scr}/\kappa ,\text{1}\right)}^{-\text{1}.\text{2}0\text{9}}\\ \times 0.{\text{993}}^{\text{Age}}\times \text{1}.0\text{18}\left[\text{if}\text{female}\right]\times \text{1}.\text{159}\left[\text{if}\text{black}\right]\end{array}$$

In this equation, eGFR is expressed as mL/min per 1.73 m², Scr is expressed as mg/dL, κ is 0.7 and 0.9 for women and men, respectively, α is −0.329 and −0.411 for women and men, respectively. The Scr levels of study participants were standardized by reducing their levels by five percent as the CKD-EPI equation requires standardized creatinine values [34].

Statistical analysis

Baseline characteristics of the study population were shown as mean (standard deviation: SD) values and frequencies (%) for continuous and categorical variables, respectively. For covariates with a skewed distribution (e.g. TG), the median (interquartile range [IQR]) was reported. We compared characteristics of participants according to gender as well as between respondents and non-respondents (those with missing data at baseline or without any follow-up after baseline measurement) using the Student’s t-test, Kruskal–Wallis test, and the Pearson’s χ² test, as appropriate. The person-year method was used to obtain incidence rates of KFD, which was reported as the number of cases per 10,000 person-years. The association of potential risk factors with incident KFD was analyzed using multivariable Cox regression models to calculate the hazard ratio (HR) and 95% confidence interval (CI). We checked the proportionality assumptions to be appropriate (using Schoenfeld’s global test of residuals). No evidence of lack of proportionality in the HRs was found. We also performed a competing risk analysis using the Fine and Grey method [35] to account for the competing risk of death before the incident KFD. We chose the potential risk factors using a priori approach that might be considered potential confounders from important studies in this field [4,15,19]. As needed, variables with a skewed distribution were log-transformed before analysis (e.g. TG). The event date was calculated as the time of incident eGFR decline of ≥30%. The event date for subjects with incident KFD was defined as the mid-time point between the date of the follow-up visit at which the event was detected for the first time and the last attended follow-up visit before the diagnosis; survival time was defined as the difference between the date of the event and the date of baseline visit. For the censored participants, survival time was calculated as the interval between the baseline visit and the time of death, loss to follow-up, or end of the study (April 2018), whichever occurred first. Several subgroup analyses were carried out; the analyses stratified by CKD at baseline, gender, and menopausal status (considering the age of 48.2 years as menopausal age among Iranian women [36]) were further performed. Additionally, as a sensitivity analysis, multiple imputations (20 datasets corresponding to the ∼20% missingness in data, with a rule of thumb of at least 1 imputation per % of incomplete cases [37,38]) of missing data of exposure variables using two-fold fully conditional specification (FCS) algorithm [39] and Rubin’s rules [40] was carried out. We did not impute the outcome variable, as we analyzed only participants for whom incident outcome could be ascertained. For conducting statistical analysis, STATA version 14 SE (StataCorp LP, TX, USA) was used. All p-values were two-tailed. p-value <.05 was considered significant for all tests.

Results

The study population included 7190 participants (4049 women) with a mean age (SD) of 43.54 (14.6) years. As shown in Table S1, study respondents had higher BMI, lower HDL-C levels, and were less physically active, while marriage was found to be less prevalent among the non-respondents. Non-respondents were also more likely to be current smokers, take glucose-lowering and antihypertensive medications, and have higher FPG and CVD prevalence than study respondents. No significant differences regarding age, 2-h PG, WC, SBP, DBP, TC, TG, eGFR at baseline, gender proportion, education level, family history of diabetes, and taking lipid-lowering medications existed between respondents and non-respondents.

The baseline characteristics of the subjects in both genders are shown in Table 1; accordingly, men were older, had lower HDL-C levels, higher WC, SBP, DBP, and TG values, the prevalence of CVD, and FH-DM, were more likely to be current smokers, and physically inactive, while women had lower eGFR values, higher BMI, 2-h PG, TC levels, consumption of medications, were less likely to be highly educated and married.

Table 1. Baseline characteristics of the study participants stratified by gender: Tehran Lipid and Glucose Study.

	Men	Women
Number of participants	3141	4049	p-value
Continuous variables, Mean ± SD
Age (year)	44.55 ± 15.30	42.76 ± 14.05	<.001
BMI (kg/m^2)	26.37 ± 4.16	28.23 ± 4.99	<.001
WC (cm)	93.56 ± 11.01	89.97 ± 12.99	<.001
FPG (mg/dL)	98.06 ± 29.19	98.17 ± 32.45	.881
2-h PG (mg/dL)	113.23 ± 53.50	118.46 ± 50.23	<.001
SBP (mmHg)	119.27 ± 17.41	115.19 ± 19.20	<.001
DBP (mmHg)	75.71 ± 10.70	74.28 ± 10.38	<.001
eGFR at baseline (ml/min/1.73 m^2)	87.83 ± 15.91	84.12 ± 16.03	<.001
TC (mg/dL)	189.28 ± 38.35	195.80 ± 43.46	<.001
HDL-C (mg/dL)	35.48 ± 8.72	41.62 ± 10.62	<.001
TG (mg/dL)	146 (102–211)^a	128 (89–187)^a	<.001
Categorical variables, number (%)
Marital status			<.001
Married	2593 (82.55)	3197 (78.96)
Single	516 (16.43)	415 (10.25)
Widowed/Divorced	32 (1.02)	437 (10.79)
Smoking status			<.001
Never	1783 (56.77)	3843 (94.91)
Former	596 (18.97)	89 (2.20)
Current	762 (24.26)	117 (2.89)
Education level			<.001
>12 years	624 (19.87)	492 (12.15)
6–12 years	1778 (56.61)	2096 (51.77)
<6 years	739 (23.53)	1461 (36.08)
Physical activity			<.001
Inactive	1385 (44.09)	1359 (33.56)
Moderately active	580 (18.47)	1202 (29.69)
Sufficiently active	1176 (37.44)	1488 (36.75)
Prevalent CVD, yes	211 (6.72)	172 (4.25)	<.001
Family history of diabetes, yes	737 (23.46)	650 (16.05)	<.001
Glucose-lowering drug use, yes	133 (4.23)	246 (6.08)	<.001
Antihypertensive drug use, yes	153 (4.87)	427 (10.55)	<.001
Lipid-lowering drug use, yes	77 (2.45)	170 (4.20)	<.001

BMI: body mass index; WC: waist circumference; FPG: fasting plasma glucose; 2-h PG: 2-hour post-challenge plasma glucose; SBP: systolic blood pressure; DBP: diastolic blood pressure; eGFR: estimated glomerular filtration rate; TC: total cholesterol; HDL-C: high-density lipoprotein cholesterol; TG: triglycerides; CVD: cardiovascular disease.

^aData presented as median (IQR) for skewed variables (TG).

During the median follow-up (IQR) of 11.48 (9-39-12.85) years, 1471 participants had incident KFD, and 326 died before the outcome occurrence.

Figure 2 presents the sex-specific crude incidence rates per 10,000 person-year among men and women by 10-year age group categories. In men and women, the incidence of KFD increased at ages 30–40 years and above. The crude incidence rate of KFD was 192.1 (182.6–202.2) per 10,000 person-year in the total population.

Figure 2. The sex-specific crude incidence rate of kidney function decline per 10,000 person-year, stratified by 10-year age group categories. Legend: Due to the small numbers of those aged ≥80 years, all subjects aged ≥70 years were categorized into one age group.

Table 2 shows the crude and adjusted HR and 95% CI of incident KFD associated with potential risk factors. Accordingly, in the univariable model (model 1), age groups of 50-64 and ≥65 years, BMI ≥30 kg/m², higher WC, female gender, prehypertension, hypertension (43% on antihypertensive medications), prediabetes, diabetes (45% on glucose-lowering medications), being widowed/divorced, education level <6 years, increasing TG, using lipid-lowering medications, and prevalent CVD significantly increased the risk of KFD (all p values < .05). Additionally, among the potential predictors, family history of diabetes and moderate physical activity were associated with lower risks of KFD [HR: 95% CI: 0.82 (0.71–0.94) and 0.86 (0.75–0.98), respectively]. In the multivariable-adjusted analysis including the baseline eGFR (model 3), each 1 mL/min/1.73 m² greater eGFR increased the risk of the incident outcome by 6% [HR: 95% CI: 1.06 (1.05–1.06)]. Additionally, the association of the age groups of 35–49, 50–64, and ≥65 years, female gender [1.61 (1.40–1.85)], prehypertension [1.21 (1.06–1.38)], hypertension [1.73 (1.48–2.01)], diabetes [1.30 (1.10–1.53)], moderate physical activity [0.84 (0.73–0.96)], being widowed/divorced [1.23 (1.01–1.49)], increasing TG [1.09 (1.01–1.17)], prevalent CVD [1.36 (1.09–1.68)], and FH-DM [0.87 (0.76–1.00)] with the KFD were significant in model 3. In the competing risk analysis, results remained unchanged after considering the impact of all-cause mortality events as a competing risk (Table 2).

Table 2. Association of risk factors with decline in kidney function in the Tehran Lipid and Glucose Study.

	Cox regression analysis			Competing risk analysis
Characteristics	Model 1	Model 2	Model 3	Model 3
	HR (95%CI)	HR (95%CI)	HR (95%CI)	SHR (95%CI)
Age (years)
20–34	1.00 (reference)	1.00 (reference)	1.00 (reference)	1.00 (reference)
35–49	1.06 (0.93–1.22)	1.02 (0.88–1.19)	1.83 (1.56–2.16)	1.84 (1.57–2.17)
50–64	1.52 (1.33–1.75)	1.21 (1.00–1.45)	3.78 (3.05–4.69)	3.77 (3.05–4.66)
≥65	2.08 (1.75–2.47)	1.52 (1.20–1.93)	7.84 (5.93–10.38)	6.95 (5.19–9.31)
Female gender (male reference)	1.19 (1.07–1.32)	1.21 (1.06–1.39)	1.61 (1.40–1.85)	1.65 (1.43–1.90)
Blood pressure categories
Normal	1.00 (reference)	1.00 (reference)	1.00 (reference)	1.00 (reference)
Prehypertension	1.23 (1.09–1.39)	1.15 (1.01–1.31)	1.21 (1.06–1.38)	1.21 (1.06–1.38)
Hypertension	1.94 (1.71–2.19)	1.51 (1.30–1.77)	1.73 (1.48–2.01)	1.69 (1.45–1.97)
Glycemic status categories
Normal	1.00 (reference)	1.00 (reference)	1.00 (reference)	1.00 (reference)
Prediabetes	1.16 (1.03–1.33)	0.99 (0.86–1.15)	0.97 (0.84–1.11)	0.97 (0.84–1.12)
Diabetes	1.87 (1.62–2.15)	1.40 (1.19–1.65)	1.30 (1.10–1.53)	1.27 (1.07–1.50)
Body mass index categories
Normal	1.00 (reference)	1.00 (reference)	1.00 (reference)	1.00 (reference)
Overweight	0.97 (0.86–1.09)	0.86 (0.74–1.01)	0.94 (0.80–1.10)	0.94 (0.81–1.10)
Obese	1.16 (1.02–1.33)	0.90 (0.72–1.13)	0.97 (0.77–1.21)	0.96 (0.77–1.20)
Physical activity
Inactive	1.00 (reference)	1.00 (reference)	1.00 (reference)	1.00 (reference)
Moderately active	0.86 (0.75–0.98)	0.83 (0.72–0.95)	0.84 (0.73–0.96)	0.84 (0.73–0.97)
Sufficiently active	1.02 (0.91–1.14)	1.01 (0.90–1.13)	0.95 (0.84–1.07)	0.95 (0.85–1.07)
Marital status
Married	1.00 (reference)	1.00 (reference)	1.00 (reference)	1.00 (reference)
Single	0.90 (0.77–1.06)	1.13 (0.93–1.36)	1.00 (0.83–1.22)	1.01 (0.84–1.22)
Widowed/Divorced	1.62 (1.35–1.94)	1.12 (0.92–1.36)	1.23 (1.01v1.49)	1.24 (1.01–1.53)
Education level
>12 years	1.00 (reference)	1.00 (reference)	1.00 (reference)	1.00 (reference)
6–12 years	1.05 (0.90–1.23)	1.02 (0.87–1.20)	0.90 (0.77–1.06)	0.89 (0.76–1.04)
<6 years	1.61 (1.37–1.90)	1.12 (0.93–1.36)	0.95 (0.79–1.16)	0.93 (0.77–1.13)
Smoking status
Never	1.00 (reference)	1.00 (reference)	1.00 (reference)	1.00 (reference)
Former	0.91 (0.76–1.10)	0.93 (0.76–1.13)	0.96 (0.79–1.17)	0.96 (0.78–1.17)
Current	0.93 (0.79–1.09)	1.15 (0.97–1.38)	1.09 (0.92–1.31)	1.07 (0.89–1.28)
TC/HDL-C, per 1-SD^b	1.02 (0.97–1.07)	0.94 (0.88–1.01)	0.97 (0.90–1.04)	0.97 (0.90–1.04)
TG, per 1-SD^a, ^b	1.09 (1.04–1.15)	1.05 (0.98–1.14)	1.09 (1.01–1.17)	1.09 (1.01–1.17)
Waist circumference, per 1-SD^b	1.10 (1.05–1.16)	1.01 (0.92–1.11)	1.00 (0.91–1.10)	1.01 (0.92–1.11)
Lipid-lowering drug use, yes	1.30 (1.00–1.68)	0.91 (0.69–1.19)	0.99 (0.76–1.30)	0.98 (0.74–1.29)
Prevalent CVD, yes	1.56 (1.27–1.91)	1.12 (0.90–1.39)	1.36 (1.09–1.68)	1.27 (1.01–1.59)
Family history of diabetes, yes	0.82 (0.71–0.94)	0.85 (0.73–0.97)	0.87 (0.76–1.00)	0.87 (0.75–1.00)
eGFR, per 1 mL/min/1.73 m^2 greater	–	–	1.06 (1.05–1.06)	1.06 (1.05–1.06)

Model 1: Crude model.

Model 2: Adjusted for age, gender, blood pressure, glycemic status, obesity status, physical activity level, marital status, education level, smoking status, TC/HDL-C, TG, waist circumference, lipid-lowering drug use, prevalent CVD, family history of diabetes.

Model 3: Model 2 + baseline eGFR.

TC: total cholesterol; HDL-C: high-density lipoprotein cholesterol; CVD: cardiovascular disease; eGFR: estimated glomerular filtration rate; SHR: sub-distribution hazard ratio; CI: confidence interval.

^aLog-transformed TG was used.

^b1 SD TC/HDL-C, log-transformed TG, and waist circumference are equal to 1.70 mg/dL, 0.55 mg/dL, and 12.30 cm, respectively.

Subgroup analysis

Results of the subgroup analysis by CKD status, gender, and menopausal status are shown in Tables 3–5. As shown in Table 3, among those without prevalent CKD, increasing age, baseline eGFR (p for interaction .037 and <.001, respectively), increasing TG, female gender, prehypertension, hypertension, diabetes, being unmarried, and prevalent CVD increased the risk of KFD. In contrast, moderate physical activity and FH-DM were associated with lower risk. However, for those with CKD, only hypertension was associated with a higher risk of incident KFD, while lower education levels (p for interaction <.05) and higher baseline eGFR decreased the risk.

Table 3. Sub-distribution Hazard ratios and 95% CI of risk factors for the decline in kidney function, stratified by baseline eGFR, in the Tehran Lipid and Glucose Study^a.

Characteristics	eGFR <60 mL/min/1.73 m^2(n = 349) (Events = 69)	eGFR ≥60 mL/min/1.73 m^2(n = 5439) (Events = 1402)	p for interaction
Age, per 1 year greater	0.99 (0.96–1.03)	1.06 (1.05–1.07)	.037
Female gender	0.89 (0.45–1.76)	1.77 (1.53–2.04)	.067
Blood pressure categories
Normal	1.00 (reference)	1.00 (reference)
Prehypertension	2.93 (0.96–6.08)	1.18 (1.03–1.34)	.195
Hypertension	4.97 (1.72–14.41)	1.55 (1.32–1.82)	.069
Glycemic status categories
Normal	1.00 (reference)	1.00 (reference)
Prediabetes	1.11 (0.56–2.21)	0.95 (0.82–1.10)	.907
Diabetes	1.18 (0.59–2.33)	1.23 (1.04–1.47)	.936
Body mass index categories
Normal	1.00 (reference)	1.00 (reference)
Overweight	0.93 (0.46–1.88)	0.96 (0.82–1.12)	.585
Obese	0.82 (0.32–2.13)	1.00 (0.80–1.25)	.827
Physical activity
Inactive	1.00 (reference)	1.00 (reference)
Moderately active	0.97 (0.50–1.88)	0.84 (0.72–0.97)	.659
Sufficiently active	0.79 (0.44–1.45)	0.95 (0.84–1.07)	.814
Marital status
Married	1.00 (reference)	1.00 (reference)
Single/Widowed/Divorced	1.38 (0.71–2.71)	1.20 (1.05–1.38)	.199
Education level
>12 years	1.00 (reference)	1.00 (reference)
6–12 years	0.30 (0.11–0.81)	0.93 (0.79–1.09)	.044
<6 years	0.26 (0.10–0.67)	0.90 (0.74–1.10)	.006
Smoking status
Never	1.00 (reference)	1.00 (reference)
Former	0.94 (0.41–2.13)	0.94 (0.76–1.15)	.586
Current	2.03 (0.56–7.40)	1.06 (0.88–1.27)	.346
TC/HDL-C, per 1-SD	1.04 (0.70–1.53)	0.97 (0.90–1.04)	.098
TG, per 1-SD^b	1.17 (0.81–1.68)	1.09 (1.01–1.17)	.064
Waist circumference, per 1-SD	0.91 (0.59–1.42)	1.00 (0.91–1.10)	.911
Lipid-lowering drug use, yes	1.17 (0.52–2.62)	0.94 (0.70–1.28)	.559
Prevalent CVD, yes	0.73 (0.39–1.39)	1.28 (1.00–1.63)	.366
Family history of diabetes, yes	1.50 (0.75–3.00)	0.86 (0.74–0.99)	.209
eGFR, per 1 mL/min/1.73 m^2 greater	0.96 (0.93–1.00)	1.07 (1.06–1.07)	<.001

Adjusted for age, gender, blood pressure, glycemic status, obesity status, physical activity level, marital status, education level, smoking status, TC/HDL-C, TG, waist circumference, lipid-lowering drug use, prevalent CVD, family history of diabetes, and baseline eGFR.

TC: total cholesterol; HDL-C: high-density lipoprotein cholesterol; CVD: cardiovascular disease; eGFR: estimated glomerular filtration rate; CI: confidence interval.

^aResults of competing risk analysis.

^bLog-transformed TG was used.

Table 4. Sub-distribution Hazard ratios and 95% CI of risk factors for the decline in kidney function, stratified by gender, in the Tehran Lipid and Glucose Study^a.

Characteristics	Men (n = 3141) (Events = 582)	Women (n = 4049) (Events = 889)	p for interaction
Age (years)
20–34	1.00 (reference)	1.00 (reference)
35–49	1.65 (1.26–2.17)	1.92 (1.56–2.37)	.251
50–64	3.86 (2.75–5.41)	3.65 (2.74–4.85)	.695
≥65	7.29 (4.62–11.50)	6.78 (4.59–10.03)	.611
Blood pressure categories
Normal	1.00 (reference)	1.00 (reference)
Prehypertension	1.04 (0.85–1.26)	1.34 (1.13–1.59)	.061
Hypertension	1.63 (1.28–2.08)	1.73 (1.42–2.12)	.618
Glycemic status categories
Normal	1.00 (reference)	1.00 (reference)
Prediabetes	0.98 (0.79–1.23)	0.95 (0.79–1.15)	.799
Diabetes	1.45 (1.11–1.90)	1.15 (0.93–1.42)	.356
Body mass index categories
Normal	1.00 (reference)	1.00 (reference)
Overweight	0.99 (0.78–1.25)	0.92 (0.75–1.14)	.906
Obese	0.95 (0.65–1.38)	0.97 (0.74–1.28)	.301
Physical activity
Inactive	1.00 (reference)	1.00 (reference)
Moderately active	0.80 (0.63–1.02)	0.86 (0.72–1.02)	.740
Sufficiently active	0.93 (0.78–1.12)	0.96 (0.82–1.12)	.672
Marital status
Married	1.00 (reference)	1.00 (reference)
Single	1.06 (0.79–1.42)	0.96 (0.74–1.24)	.323
Widowed/Divorced	1.00 (0.44–2.27)	1.27 (1.02–1.59)	.646
Education level
>12 years	1.00 (reference)	1.00 (reference)
6–12 years	0.81 (0.65–1.01)	0.99 (0.77–1.26)	.198
<6 years	0.74 (0.55–0.98)	1.12 (0.84–1.48)	.044
Smoking status
Never	1.00 (reference)	1.00 (reference)
Former	0.95 (0.76–1.19)	1.00 (0.61–1.63)	.822
Current	1.09 (0.88–1.34)	1.14 (0.76–1.71)	.762
TC/HDL-C, per 1-SD	0.89 (0.79–1.01)	1.03 (0.94–1.13)	.194
TG, per 1-SD^b	1.17 (1.04–1.31)	1.03 (0.93–1.14)	.827
Waist circumference, per 1-SD	0.97 (0.83–1.13)	1.02 (0.91–1.14)	.278
Lipid-lowering drug use, yes	0.66 (0.35–1.23)	1.13 (0.82–1.57)	.108
Prevalent CVD, yes	0.95 (0.67–1.36)	1.60 (1.20–2.13)	.022
Family history of diabetes, yes	0.94 (0.76–1.15)	0.83 (0.67–1.01)	.331
eGFR, per 1 mL/min/1.73 m^2 greater	1.05 (1.04–1.06)	1.06 (1.05–1.07)	.536

Adjusted for age, blood pressure, glycemic status, obesity status, physical activity level, marital status, education level, smoking status, TC/HDL-C, TG, waist circumference, lipid-lowering drug use, prevalent CVD, family history of diabetes, and baseline eGFR.

TC: total cholesterol; HDL-C: high-density lipoprotein cholesterol; CVD: cardiovascular disease; eGFR: estimated glomerular filtration rate; CI: confidence interval.

^aResults of competing risk analysis.

^bLog-transformed TG was used.

Table 5. Sub-distribution Hazard ratios and 95% CI of risk factors for the decline in kidney function, stratified by menopausal status among women, in the Tehran Lipid and Glucose Study^a.

Characteristics	Premenopausal women (n = 2649) (Events = 506)	Postmenopausal women (n = 1400) (Events = 383)	p for interaction
Age, per 1 year greater	1.07 (1.05–1.09)	1.04 (1.02–1.06)	.750
Blood pressure categories
Normal	1.00 (reference)	1.00 (reference)
Prehypertension	1.35 (1.10–1.67)	1.32 (0.97–1.80)	.950
Hypertension	1.36 (0.93–1.97)	1.84 (1.37–2.46)	.045
Glycemic status categories
Normal	1.00 (reference)	1.00 (reference)
Prediabetes	1.09 (0.83–1.42)	0.87 (0.67–1.14)	.390
Diabetes	0.69 (0.47–1.01)	1.32 (1.01 − 1.73)	<.001
Body mass index categories
Normal	1.00 (reference)	1.00 (reference)
Overweight	0.89 (0.69–1.15)	1.10 (0.74–1.65)	.169
Obese	0.96 (0.67–1.38)	1.15 (0.72–1.84)	.050
Physical activity
Inactive	1.00 (reference)	1.00 (reference)
Moderately active	0.85 (0.67–1.07)	0.89 (0.68–1.16)	.939
Sufficiently active	1.00 (0.81–1.23)	0.95 (0.75–1.21)	.389
Marital status
Married	1.00 (reference)	1.00 (reference)
Single/Widowed/Divorced	1.13 (0.89–1.45)	1.10 (0.86–1.42)	.905
Education level
>12 years	1.00 (reference)	1.00 (reference)
6–12 years	1.00 (0.77–1.30)	1.91 (0.70–5.20)	.198
<6 years	1.03 (0.73–1.46)	1.91 (0.71–5.12)	.225
Smoking status
Never	1.00 (reference)	1.00 (reference)
Former	1.47 (0.81–2.68)	0.78 (0.39–1.56)	.305
Current	0.90 (0.49–1.62)	1.55 (0.89–2.70)	.150
TC/HDL-C, per 1-SD	0.97 (0.84–1.11)	1.10 (0.98–1.24)	.077
TG, per 1-SD^b	1.10 (0.96–1.27)	0.97 (0.82–1.10)	.455
Waist circumference, per 1-SD	0.95 (0.81–1.12)	1.09 (0.92–1.29)	.016
Lipid-lowering drug use, yes	0.17 (0.02–1.25)	1.29 (0.93–1.79)	.026
Prevalent CVD, yes	1.43 (0.68–3.00)	1.31 (0.95–1.80)	.964
Family history of diabetes, yes	0.77 (0.59–1.01)	0.95 (0.69–1.31)	.180
eGFR, per 1 mL/min/1.73 m^2 greater	1.08 (1.07–1.09)	1.04 (1.03–1.06)	<.001

Adjusted for age, blood pressure, glycemic status, obesity status, physical activity level, marital status, education level, smoking status, TC/HDL-C, TG, waist circumference, lipid-lowering drug use, prevalent CVD, family history of diabetes, and baseline eGFR.

TC: total cholesterol; HDL-C: high-density lipoprotein cholesterol; CVD: cardiovascular disease; eGFR: estimated glomerular filtration rate; CI: confidence interval.

^aResults of competing risk analysis.

^bLog-transformed TG was used.

When stratifying the results by gender, as shown in Table 4, all age groups, hypertension, and increasing baseline eGFR among both genders were associated with a higher incidence of KFD. Moreover, prehypertension [HR: 95% CI: 1.34 (1.13–1.59)] and prevalent CVD [1.60 (1.20–2.13), p for interaction <.05], being widowed/divorced [1.27 (1.02–1.59)] increased the risk of incident KFD among women. Among men, the lowest education levels (p for interaction <.05) decreased the risk of KFD by 26%. Compared to normal glucose levels, diabetes and increasing TG in men were also associated with a significantly higher risk of incident outcome [1.45 (1.11–1.90) and 1.17 (1.04–1.31), respectively].

As shown in Table 5, when we categorized female participants according to menopausal status, hypertension [HR: 95% CI: 1.84 (1.37–2.46)] and diabetes [1.32 (1.01–1.73)] were associated with a greater risk of incident KFD only among postmenopausal women (p for interactions <.05). Moreover, increasing eGFR and age were associated with higher KFD risk in both subgroups; however, the association of the former with the KFD risk was significantly higher among premenopausal women (p for interaction <.05).

The pattern of HRs and their 95% CIs in the sensitivity analysis with multiple imputations in the Cox regression analysis were generally in line with the main analysis (Table S2).

Discussion

We found that among the total population, older age, female gender, prehypertension, hypertension, diabetes, widowed/divorced states, higher TG, prevalent CVD, and higher initial eGFR were associated with greater but moderate physical activity and having a positive family history of diabetes with lower KFD risk.

We also found some significant effect modifications of gender, menopausal status, and having CKD on the impact of different risk factors on incident KFD. The unfavorable effect of prevalent CVD was more pronounced in women than men. Among postmenopausal women, the unfavorable impact of major CVD risk factors was more prominent, while higher initial eGFR was associated with greater risk in premenopausal women. Considering kidney function status, higher baseline eGFR was protective only among the CKD population.

Among traditional risk factors, in line with previous studies [19,20,22,25], we found that older age is associated with a higher risk of KFD. However, Baba et al. [41] found that the higher the baseline eGFR, the higher the rate of decline in kidney function, and that the decline rate became slower with aging since the baseline eGFR was lower in older subjects. Higher age was not a risk factor among those with initial CKD in our study; several reports exist on the link between aging and kidney function decline among the CKD population [42,43]; in fact, several reports exist that young CKD patients are more predisposed to progress to ESKD rather than elderly ones [42,44,45]. These differences might also be due to the selection of the participants; Baba et al. [41] excluded subjects with underlying comorbidities. Another possible explanation might be because of the greater competing risk for death, which we accounted for and observed that age was not associated with incident KFD among those with CKD.

Female gender, per se, was a risk factor for KFD. Similarly, in some [15,21] but not all previous studies [18,22], women had a higher rate of eGFR decline than men. Furthermore, findings of a study of more than 5 million individuals from 34 multinational cohorts reported the female gender as a risk factor for CKD [46]. It is important to note that the progression of CKD might reflect more than biological differences between the sexes, such as differences in lifestyle, cultural, socio-economic, and psychological factors that are affected by gender; however, the precise mechanisms are not fully understood [47]. Several studies, including large meta-analyses, have shown a higher prevalence of CKD among women [48–50]; in contrast, incident ESKD is more common in men [51–53], which might be indicative of gender-specific trajectories in eGFR decline with aging.

High blood pressure is another well-known risk factor for CKD progression [14,15,19,21,22]. The current study showed a higher risk of incident KFD associated with hypertension in both men and women, with a higher impact among postmenopausal women. Encouraging lifestyle changes, including reducing salt intake, which is more than two times greater than the World Health Organization recommended levels among Iranians [54], and introducing diets that are low in animal protein [55–57] as well as antihypertensive medication adherence [58] according to international guidelines might be effective interventions in slowing the progression of renal disease through improving blood pressure control. As shown in a systematic review and meta-analysis, the prevalence of medication adherence among patients with hypertension was 33% in Iran [59]; the corresponding value globally was reported at 45% [60]. A study of 3305 adults with CKD showed that low medication adherence increased the risk for CKD progression by 27% [58]. In the current study, we did not have data regarding medication adherence.

Similar to the results of previous studies [19,21], we found that diabetes was a risk factor for KFD. Our study did not find an interaction between gender and diabetes; however, men had a higher risk for incident KFD than premenopausal women (data not shown). Also, diabetes was associated with greater risk in postmenopausal women than premenopausal ones. Among patients with diabetes, the male gender was associated with faster eGFR decline in previous studies [61,62]. We also extended the previous research by showing the differential impact of diabetes on incident KFD across gender and menopausal status.

Regarding social status and modifiable risk factors, being unmarried and living alone has been associated with a greater risk of rapid eGFR decline among middle-aged and elderly subjects with preserved kidney function [63]; our study found similar findings. In the current study, lower education levels among men and CKD patients were associated with lower risk. Qin et al. [18] followed 2518 Chinese adults without CKD and found no association between higher education levels and incident KFD, similar to our population without CKD. We believe that dietary choices, occupational status, and psychosocial factors might justify the impact of lower education on KFD incidence. We also found inconsistent findings regarding physical activity across subgroups, showing a possible protective effect of moderate physical activity among those without CKD; high physical activity has been linked with a lower risk of developing CKD [64].

In our study, the presence of a family history of diabetes resulted in about 13% lower risk for incident KFD, an issue that was reported previously in our population [4]. It is speculated that subjects with a family history of diabetes may be more aware of the risks associated with CKD and more proactive in maintaining a healthy lifestyle, monitoring their blood glucose levels, and seeking medical attention, when necessary, from a young age. Moreover, previous studies conducted among American and Chinese populations found no risk of CKD for those with a positive family history of diabetes [65,66].

We also found that high baseline eGFR increased the risk of KFD in both men and women of the general population, which was in line with previous reports [22,25,41]. Melsom et al. [67] showed that among those without CKD, higher measured GFR at baseline was associated with faster GFR decline regardless of the presence or absence of diabetes; for every 10-mL/min higher baseline GFR, the annual rate of GFR decline was 0.31 mL/min faster in the Norwegian cohort and 0.46 mL/min faster in the Pima cohort. The reason why the incidence of KFD was higher with a higher baseline eGFR among the non-CKD population is unclear. Salt and sodium intake, which are higher among the Iranian population [54], are reported to be associated with higher filtration fraction, especially among hypertensive subjects [41,68]. Moreover, we also noted that eGFR ≥82.23 mL/min/1.73 m² was associated with a more than 20% increase in the risk of future prehypertension [69], a potential risk factor for eGFR decline [18]. In this line, a previous study also showed that the risk of doubling the serum creatinine increased at higher and lower levels of eGFR compared to intermediate levels, but the risk of chronic dialysis treatment was inversely associated with eGFR [70]. In contrast, we also found that higher eGFR was a protective factor among CKD patients. Previous work shows that the lower eGFR, the higher the risk of CKD progression and incident ESKD among those with CKD [71,72].

In the current analysis, cardiometabolic risk factors, including diabetes, hypertension, and obesity, had stronger effects in developing KFD among postmenopausal women compared to premenopausal ones; many studies addressed the protective role of women’s sex steroids (i.e. estradiol) and duration of exposure to these hormones (i.e. reproductive life span) in the development of CKD [73,74]. Experimental studies have demonstrated that estrogen exerts its biological actions through estrogen receptors [75], which are present in the kidney’s mesangial, endothelial, and vascular smooth muscle cells [76]. Although the precise underlying mechanisms are not clear, studies suggest that after menopause, the decline in serum estrogen levels and its renoprotective effects can accelerate the progression of glomerulosclerosis and kidney dysfunction [77,78]; the finding is based on the fact that studies including postmenopausal women did not show a greater risk of progressive CKD in men [17,44]. In our study, the impact of diabetes on KFD in men and postmenopausal women but not in premenopausal women adds to the importance of hormonal and biological consequences of menopause.

The key strength of our study is being the first to investigate the risk factors of KFD in the MENA region with a high burden of CKD, using the well-known and large TLGS cohort. Second, using subsequent measurements and a relatively long follow-up for assessing renal function to identify most potential risk factors. Third, data were obtained using direct administrative measures, and standard questionnaires were used for the minimal self-reported data.

There were some limitations in our study. First, we did not have data on albuminuria in subjects included in the study. However, in an individual meta-analysis of 1.7 million participants of 35 cohorts in the CKD Prognosis Consortium (including TLGS), data on albuminuria were available in 679,322 and 431,532 for the mortality and ESRD outcomes, respectively [7]; the authors found that the strong association between eGFR decline and ESRD and mortality events did not change after further adjustment for albuminuria, suggesting eGFR decline as a robust determinant. Second, although GFR was not directly measured in our study, using eGFR with Scr is accurate and valid against gold standards [79,80]. Finally, there was also the risk of unmeasured confounders such as serum electrolyte levels (e.g. sodium, potassium, calcium, and phosphorus), which we might have failed to take into account.

Conclusions

Taken together, important predictors for KFD identified among the Iranian population were older age, female gender, high blood pressure, diabetes, widowed/divorced states, higher TG, prevalent CVD, and higher initial eGFR. Moderate physical activity and having a positive family history of diabetes were protective factors. Higher initial eGFR was a risk factor in those without CKD, while it was protective in CKD patients. Importantly, hypertension and diabetes were risk factors in postmenopausal women. Our findings shed more light on the interaction between gender, menopausal status, and baseline kidney function with different risk factors on KFD. The issue should be considered in personalized preventive medicine.

Author contributions

S.M. and F.H. raised the presented idea and designed the study; S.M. analyzed and interpreted the data; S.M. and D.A. drafted the initial manuscript; M.A reviewed the manuscript; F.H. and F.A. critically reviewed the project and approved the final version of the manuscript; all authors read and approved the final manuscript.

Acknowledgments

We express our appreciation to the participants in the Tehran Lipid and Glucose Study for their enthusiastic support as well as the staff of the Tehran Lipid and Glucose Study Unit of the Research Institute for Endocrine Sciences for their valuable help.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data supporting this study’s findings are available from the corresponding author, F.H., upon reasonable request.

Additional information

Funding

No funding from any source was obtained for this study.