Moderately increased albuminuria, chronic kidney disease and incident dementia: the HUNT study

The general health survey known as HUNT 2 (1995–1997) invited all residents ≥20 years (N = 93,898) residing in Nord-Trøndelag County, Norway (see Fig. 1a). Data were collected using questionnaires, clinical measurements and collection of blood and urine samples, and 64,978 (69.2%) residents participated. The details of the HUNT study design have been published previously [17]. Participants who emigrated out of the County (n = 214), lacked a dementia diagnosis date (n = 108), diagnosed with prevalent mild cognitive impairment (MCI) (n = 48), or those who did not provide both clinical examination and self-reported questions on hypertension, diabetes mellitus (DM), stroke, smoking habits, alcohol consumption, and physical activity were removed from the sample (n = 9602). A total of 55,006 participated in both questionnaires and clinical examinations, however, a further 6498 participants were removed due to missing covariate data, resulting in 48,508 participants included in the present study examining the association between CKD and dementia. 668 participants were diagnosed with dementia and 47,840 were not diagnosed with dementia.

Participants of HUNT 2 who self-reported DM and/or treated hypertension (HTN), and a randomly selected, non-diabetic/non-treated hypertensive sample were included in MA screening, and asked to deliver three urine samples from three consecutive days. Details of the MA screening have been published [15]. The flow chart in Fig. 1b shows identical selection and inclusion criteria for both CKD and MA, where participants lacking either questionnaires, clinical examination, or relevant data on dementia diagnosis were excluded (n = 809). A further 46 did not deliver all three urine samples, 246 had an ACR over 30 mmol/L, and 332 were removed from the sample, as participants confirmed self-reported history of hematuria, menstruation, or pregnancy. 8387 remained in the sample and 1363 had missing covariate data and were removed. 7024 participants had complete data and encompass this study sample. Subgroups were created to examine those diagnosed with dementia and DM or treated for HTN (n = 184) and those diagnosed with dementia and without DM or treatment for HTN (n = 30). Similarly, 5135 participants without dementia and with DM or treatment for HTN, and 1675 controls were without DM and were not treated for HTN.

In HUNT 2, the clinical examination was conducted in survey stations. Height and weight was used to generate body mass index (BMI) based on participants wearing light clothes without shoes: height to the nearest centimeter and weight to the nearest half kilogram. Pulse, systolic (SBP) and diastolic blood pressure (DBP) were measured three times using a Dinamap 845XT (Critikon) based on oscillometry. Non-fasting blood sampling occurred at survey stations during HUNT 2. Fresh serum samples were analyzed using Hitachi 91 Autoanalyser (Hitachi, Mito, Japan) and described in detail previously [18]. Serum concentration of creatinine was used to calculate eGFR using the Chronic Kidney Disease Epidemiology Collaboration equation (CKD-EPI). Further description of examination and laboratory procedures have been described in detail according to standardized protocols [17].

A parallel study, known as the health and memory study (HMS) of Nord Trøndelag County, took place from 1995 to 2011. The HMS study is a registry of persons diagnosed with dementia in the county from hospital memory clinics between 1995 and 2010; or from nursing home ascertainments performed in 2010–2011. Dementia ascertainment was uniform amongst hospital and nursing home panels. Ascertainment was based on clinical examination, patient, caregiver history, and diagnostic imaging. The ICD-10 classification system was thereafter applied for diagnoses of AD, VaD, a mixture of AD and VaD. Other dementias refers to patients with frontotemporal dementia (FTD), dementia of Lewy bodies (LBD), and unspecified. Establishing the date of the diagnosis of dementia was determined by a panel of specialists in geriatric medicine and psychiatry in the two hospitals or by asking nursing home staff or next of kin the number of months residents of nursing homes had displayed symptoms of memory loss. Details of this cohort have been previously published [19].

Participants of the MA screening received a unit with three plastic receptacles for three first morning urine samples, three transport tubes, and pre-paid return envelopes addressed to the laboratory. Written instructions provided information how to collect the sample. Participants responded to specific questions pertaining to history of a urinary tract infection during the last week, persistent hematuria over the last year, and whether women were pregnant or menstruating at collection time. Fresh urine samples were analyzed using Hitachi 91 Autoanalyser (Hitachi, Mito, Japan). Urine albumin and creatinine were measured by an immunoturbimetric method (antihuman serum albumin from Dako Norway, Oslo) and Jaffe method [15].

The national identification number of every Norwegian inhabitant enables linkage between the Death Registry at Statistics Norway to determine vital status (alive, emigrated, and dead). Each participant contributed in person-years from the date of study entry until the date of death, date diagnosed with dementia or controls who survived to the end of the study (April 23rd, 2011).

First, we analyzed the association between eGFR and dementia and its subtypes AD, VaD, mixed AD/VaD, and other dementia. The Cox proportional hazards model was used to calculate age-and multivariate-adjusted hazard ratios (HRs) with 95% confidence interval (CI) for dementia according to declining eGFR, examined both continuously and using the following categorical cutoffs with eGFR: > 90, 60–89.9, 30–59.9, and < 30. Repeated analyses using the Cox proportional hazards model were performed for ACR. ACR was calculated using the mean of three ACRs and was log transformed when used as a continuous variable in analyses. ACR was also examined categorically as quartiles: 0–.53, .54–.87, .88–1.77, and ≥ 1.78 mg/mmol. Participants’ age was used as a continuous variable in analyses. Level of education was categorized according to primary (seven years or less), secondary (seven to nine years), and upper secondary education (> 10 years). SBP and DBP were calculated as the mean of the second, third of three measurements, and used as continuous variables in analyses. Non-fasting glucose, cholesterol, and iron were scored as continuous variables. Self- report data on history of myocardial infarction (MI), angina, stroke, DM, and smoking were dichotomous variables, and subjective health status was used in analyses categorically according to poor, not so good, good, and very good. The independent-samples t-test and Pearson’s chi squared were used to compare the means between groups for continuous and categorical variables. Four sets of hazard regression models were performed for each endpoint in a hierarchy. Effect modification was examined by testing the age and sex multiplied with both eGFR and log transformed ACR in multi-adjusted models. Finally, supplementary analyses were performed to examine the assumption that lower levels of eGFR comes an increased risk of dying, and death as a competing risk. Competing risk regression was examined with Fine-Gray models using proportional subdistribution hazards (SHs) with 95% CI in models. SPSS Version 25 Software performed analyses shown in Tables 2 and 4. STATA version 14 performed supplementary analyses shown in supplementary material 3.

During the study period, 7606 died and 668 developed dementia. The mean age of the study sample was 49.5 ± 16.7 years, and mean eGFR was 78.8 ± 16.2 ml/min/1.73 m². Persons diagnosed with dementia were older, with reduced eGFR, higher SBP and DBP, and higher prevalence of self-reported cardiovascular disease. Additional characteristics of this sample are shown in Table 1. There was no statistically significant association between eGFR and dementia or its subgroups when examined in hazard regression models, see Table 2. There were interactions between age and eGFR in dementia and its subgroups. Splitting the sample at median age < 72.1; > 72.2, did not change the results in either samples. An age interaction was observed in VaD, however did not provide supportive evidence of any association when examining women and men separately (data not shown). Supplementary analyses with competing risk regression were performed to assess the effect of death on the association between eGFR and dementia, and are shown in Additional file 3. The proportional assumption for the Fine-Gray model was met by testing for time-by-status interaction in the multivariate analysis.

Study participants with a history of DM or using HTN medication, along with participants that did not have a history of DM or treated with HTN medication were examined both combined and in separate analyses. Characteristics are shown in Table 3 for the combined sample, and according to subgroups: DM or HTN and No DM or HTN, see Additional files 1 and 2. Mean ACR did not differ across quartiles of the total sample, and persons diagnosed with dementia were older, had higher SBP, DBP, lower renal function, and higher cholesterol. Table 4 shows the results of age and multivariate-adjusted analyses at different ACR levels expressed in quartiles. We found a positive association between increasing ACR and Combined AD and VaD. ACR in the fourth quartile (> 1.78 mg/mmol) with increased HR of VaD, 3.97 (1.12 to 14.07), compared with ACR in the first quartile (<.53 mg/mmol). In crude analyses, there were no sex interactions or age interactions between ACR and total dementia, combined AD/VaD, Mixed AD/VaD, and VaD.