Adiposity Predicts Cognitive Decline in Older Persons with Diabetes: A 2-Year Follow-Up

BACKGROUND: The mechanisms related to cognitive impairment in older persons with Type 2 diabetes (DM) remains unclear. We tested if adiposity parameters and body fat distribution could predict cognitive decline in older persons with DM vs. normal glucose tolerance (NGT). METHODOLOGY: 693 older persons with no dementia were enrolled: 253 with DM in good metabolic control; 440 with NGT (age range:65-85 years). Longitudinal study comparing DM and NGT individuals according to the association of baseline adiposity parameters (body mass index (BMI), waist-hip-ratio (WHR), waist circumference (WC) and total body fat mass) to cognitive change (Mini Mental State Examination (MMSE), a composite score of executive and attention functioning (CCS) over time. FINDINGS: At baseline, in DM participants, MMSE correlated with WHR (beta = -0.240; p = 0.043), WC (beta = -0.264; p = 0.041) while CCS correlated with WHR (beta = -0.238; p = 0.041), WC (beta = -0.326; p = 0.013) after adjusting for confounders. In NGT subjects, no significant correlations were found among any adiposity parameters and MMSE, while CCS was associated with WHR (beta = -0.194; p = 0.036) and WC (beta = -0.210; p = 0.024). Participants with DM in the 3(rd) tertile of total fat mass showed the greatest decline in cognitive performance compared to those in 1(st) tertile (tests for trend: MMSE(p = 0.007), CCS(p = 0.003)). Logistic regression models showed that 3(rd) vs. 1(st) tertile of total fat mass, WHR, and WC predicted an almost two-fold decline in cognitive function in DM subjects at 2(nd) yr (OR 1.68, 95%IC 1.08-3.52). CONCLUSIONS: Total fat mass and central adiposity predict an increased risk for cognitive decline in older person with DM

Figure 1 depicts patient recruitment and follow-up diagram.

<p>Figure 1 depicts patient recruitment and follow-up diagram.</p

Odds ratio and 95% confidence intervals for cognitive impairment (MMSE <24) at follow-up by adiposity measures in older persons with type 2 diabetes (n = 221).

<p><b>Model 1</b> included the following confounders: age, gender, yrs of education, physical activity, depression.</p><p><b>Model 2 = </b>Model 1 + BMI, hypertension, smoking IMT, Hb1Ac, CV-PPG, IL-6, Drug vs. diet ^§</p>§<p>see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0010333#s4" target="_blank">methods</a>.</p><p>*WHR and WC were entered separately in models.</p

Multivariate linear models testing the independent relationship between CCS, as dependent variable, and adiposity measures according to diabetes status.

<p><b>Model 1</b> included the following confounders: age, gender, yrs of education, physical activity, depression.</p><p><b>Model 2 = </b>Model 1 + BMI, hypertension, smoking IMT, Hb1Ac, CV-PPG, IL-6, Drug vs. diet ^§.</p>§<p>see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0010333#s4" target="_blank">methods</a>.</p><p>*WHR and WC were entered separately in models.</p

Population characteristics at baseline (n = 693).

<p>Note: BMI = body mass index; WC = Waist circumference; WHR = waist-hip-ratio; MMSE = Mini-Mental State Examination; SBP = systolic blood pressure, DBP = diastolic blood pressure.</p><p>TMT = Trail Making Test; DIFF = Difference; DSP = Digit Span; VF = Verbal fluency.</p><p>*p<0.05.</p

Figure 2 shows MMSE scores, CCS and IL-6 levels across baseline tertiles of total fat mass in persons with DM and NGT; (p for trend <0.05 in DM only for all figures).

<p>(black diamonds: DM; black circles: NGT).</p