Renal function is a determinant of subjective well-being in active seniors but not in patients with subjective memory complaints

Subjects

Active Seniors (AS) cohort was recruited during 2003 and 2004 by a multi-phase sampling procedure aimed at an elderly retired population living in various communities in Central Sweden. The locations for the recruitment were selected to represent a broad range of socioeconomic levels and included rural as well as urban and suburban areas. The sample consisted of 389 senior citizens and was recruited from several retired persons’ organisations, which implicates that they are independent and socially active. Being retired, living independently in their own homes in addition to participation in such organisations were the sole inclusion criteria, not pre-set health criteria. We have designated them as ‘Active Seniors’ in contrast to elderly persons that do not engage themselves in such social activity. All were Caucasians, most of them born in the 1920’s and 1930’s, mean age at sampling was 74 ± 5 years for both sexes and the sex ratio M/F was 127/262. Based upon the cystatin C values in different age groups (Figure 1), the number of AS subjects with cystatin C above the upper reference limit (1.55 mg/L) was 7 women and 3 men (total prevalence 2.6%).

A random subset of the AS cohort was assessed by the Mini Mental State Examination (MMSE) [16] and the clock drawing test (CDT) judged according to Shulman [17]. These subjects (n = 154) were found to be cognitively intact, defined as MMSE ≥ 28 and CDT ≥ 4 Neither the PGWB score nor any of the studied biomarkers differed significantly between this subgroup and the rest of the AS study group. We therefore regard the AS cohort as a cognitively intact group of elderly subjects.

S enior subjects with subjective or objective cognitive complaints (DGM cohort) were recruited from an incident case study at the University Hospital, Örebro Sweden [18]. Briefly this study population consisted of 300 consecutive patients (143 men and 157 women) who were referred to the Memory Unit at the Department of Geriatrics for diagnostic assessment and treatment of suspected cognitive problems. The inclusion period extended from May 2003 to August 2007. The cognitive problems had to be mild or moderate, defined as MMSE score ≥10; according to current Swedish research ethics legislation it is unethical and thus forbidden to include subjects with more severe dementia due to their reduced autonomy. Dementia diagnoses were based on DSM-IV criteria ICD-10 criteria was used to divide dementia patients into different diagnostic categories. Mixed dementia (F 00.2 according to ICD-10) was diagnosed in cases of coexistence of AD and a history of vascular risk factors e.g. transitory ischemic attack(s). atrial fibrillation, hypertension, diabetes mellitus, Hachinski ischemic score ≥ 6 and CT scan showing ischemic changes. Probable AD was diagnosed in accordance with the NINCDS-ADRDA criteria. Of the 73 subjects classified as ND, 39 were MCI. Everyone in the study group completed the PGWB questionnaire without assistance during their visit at the Memory unit. Based upon the cystatin C values in different age groups (Figure 1), the number of DGM subjects with cystatin C above the upper reference limit (1.55 mg/L) was 12 women and 9 men (total prevalence 7%).

All subjects gave a specific and written informed consent to the present study including genotyping and biobanking of the donated samples. The Research Ethics Committee of Örebro County Council and the Regional Ethics Review Board (Uppsala) approved the study. Height and weight (SECA digital scale, 99% of the subjects) were measured and BMI (kg/m2) was calculated. The resting systolic and diastolic blood pressure was measured using an automatic oscillometric method (Dinamap model XL Critikron, Inc., Tampa, Florida.). The equipment has been validated.

Assessment of subjective well-being

The Psychological General Well-Being (PGWB) index, accessible from MAPI Research institute, http://www.mapi-trust.fr, was used to measure subjective well-being or distress [19]. It consists of 22 items that reflect a sense of subjective well-being and distress during the past week. The items are divided into six dimensions, anxiety, depressed mood, positive well-being, self-control, general health, and vitality; these are also combined to a global overall score of SWB. Response categories for all items were simplified to a 6-point Likert scale. A high value indicates a high level of well-being. In order to achieve this interpretation of the score-points even for the dimensions which reflect distress (depressed mood and anxiety). score-points for these items were assigned in the direction of “6” to “1” in contrast to the usual direction of “1” to “6”. The overall sum of scores gives a maximum value of 132 (best SWB) and a minimum of 22 (poorest SWB).

Blood sampling and biochemical measurements

Blood samples were taken with the subjects in the supine position, by venipuncture using vacuum tubes with gel, Becton Dickison. Serum was obtained after clotting for 30 to 60 minutes at room temperature and centrifuging at room temperature for 10 minutes at 2000 g. All samples were stored at -80°C. The serum samples were analysed on a Hitachi 911 multianalyser, Roche, Mannheim, FRG. Creatinine was analysed using a enzymatic method, Crea plus, from Roche/Boehringer Mannheim FRG, and the calibrator was IDMS standardised. Albumin, IgG, IgA and IgM were analysed by immunoturbidimetry using reagents from DAKO, Copenhagen, Denmark and cystatin C by immunoparticle turbidimetry from Gentian AS, Moss, Norway. LDL and HDL cholesterol were measured by direct, homogeneous assays based on detergent treatment of the serum. N-geneous™ HDL-c and N-geneous™ LDL reagents, respectively, from Genzyme Corporation, Cambridge, MA, USA.

Estimated glomerular filtration rate (eGFR) was calculated using the equation which include both creatinine and cystatin C from the Chronic Kidney Disease Epidemiology collaboration. This equation includes both creatinine and cystatin C as well as age, sex and race [20]. In the present study all participants were of European descent.

Statistics

All variables were checked for normality of distribution and collinearity before analysis. Continuous variables with a skewed distribution were transformed using natural logarithms before regression analyses were made. The Mann-Whitney rank sum test was used to compare the PGWB sum and PGWB sub-dimension between gender in the two cohorts, median and interquartile range for descriptive statistics of these variables.

A forward multiple regression was used to determine the degree to which variance in PGWB index was explained by age, BMI, gender and, cystatin C or creatinin. To examine which of the subdimensions contributed to the variance in PGWB index ANCOVA analyses were done with age, BMI, and biomarkers of kidney function as covariates. All multivariate regression models were performed after stratification, since we have found profound differences between SWB in the AS and DGM cohorts [21].

Statistical analyses were performed using SPSS version 15.0 (Chicago, Illinois, USA), and PGWB Statistical significance were considered with a probability value <0.05.

In the AS study group, 4 subjects failed to complete the PGWB questionnaire and responses from 12 subjects failed to answer one or two questions randomly distributed among the 22 questions. The missing answers were imputed using the manual from MAPI research institute.

Baseline characteristics

Biomarkers of renal function and PGWB index

In the AS cohort, serum creatinine too was, in women, significantly and negatively related to PGWB index (P = 0.02) but explained only ≈ 2% of its variance. Adding the covariates age and BMI increased the explanatory power of the model to ≈ 6%. In men, creatinine was unrelated to PGWB index, and adding age and BMI as covariates did not improve the insignificant R² (Table 3, models 4 and 5).

In contrast, in the DGM cohort neither cystatin C nor creatinine were significantly related to PGWB index, and none of the extended models had any explanatory power (Table 3, lower panel).

Cystatin C and PGWB subdimensions

In men, in the AS cohort there was a significantly adverse relation between cystatin C and depressed mood, which explained ≈ 6% of its variance (P = 0.006). In the DGM cohort too, cystatin C in men was significantly and adversely correlated with depressed mood (P = 0.050), although the variance explained was minor (≈ 1%). In the AS cohort, there was also an adverse relation between positive well-being and cystatin C (P = 0.03), explaining ≈ 2.5% of that subdimension.