| Title |
Association of obesity, diabetes and hypertension with cognitive impairment in older age
|
|---|---|
| Published in |
Clinical Epidemiology, July 2018
|
| DOI | 10.2147/clep.s164793 |
| Pubmed ID | |
| Authors |
Insa Feinkohl, Gunnar Lachmann, Wolf-Rüdiger Brockhaus, Friedrich Borchers, Sophie K Piper, Thomas H Ottens, Hendrik M Nathoe, Anne-Mette Sauer, Jan M Dieleman, Finn M Radtke, Diederik van Dijk, Tobias Pischon, Claudia Spies |
| Abstract |
Age-related cognitive impairment is rising in prevalence but is not yet fully characterized in terms of its epidemiology. Here, we aimed to elucidate the role of obesity, diabetes and hypertension as candidate risk factors. Original baseline data from 3 studies (OCTOPUS, DECS, SuDoCo) were obtained for secondary analysis of cross-sectional associations of diabetes, hypertension, blood pressure, obesity (body mass index [BMI] ≥30 kg/m2) and BMI with presence of cognitive impairment in log-binomial regression analyses. Cognitive impairment was defined as scoring more than 2 standard deviations below controls on at least one of 5-11 cognitive tests. Underweight participants (BMI<18.5 kg/m2) were excluded. Results were pooled across studies in fixed-effects inverse variance models. Analyses totaled 1545 participants with a mean age of 61 years (OCTOPUS) to 70 years (SuDoCo). Cognitive impairment was found in 29.0% of participants in DECS, 8.2% in SuDoCo and 45.6% in OCTOPUS. In pooled analyses, after adjustment for age, sex, diabetes and hypertension, obesity was associated with a 1.29-fold increased prevalence of cognitive impairment (risk ratio [RR] 1.29; 95% CI 0.98, 1.72). Each 1 kg/m2 increment in BMI was associated with 3% increased prevalence (RR 1.03; 95% CI 1.00, 1.06). None of the remaining risk factors were associated with impairment. Our results show that older people who are obese have higher prevalence of cognitive impairment compared with normal weight and overweight individuals, and independently of co-morbid hypertension or diabetes. Prospective studies are needed to investigate the temporal relationship of the association. |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Saudi Arabia | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 50 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 8 | 16% |
| Researcher | 5 | 10% |
| Student > Bachelor | 3 | 6% |
| Other | 3 | 6% |
| Student > Doctoral Student | 2 | 4% |
| Other | 6 | 12% |
| Unknown | 23 | 46% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 11 | 22% |
| Nursing and Health Professions | 5 | 10% |
| Psychology | 4 | 8% |
| Biochemistry, Genetics and Molecular Biology | 2 | 4% |
| Engineering | 2 | 4% |
| Other | 3 | 6% |
| Unknown | 23 | 46% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 June 2019.
All research outputs
#2,412,092
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Outputs from Clinical Epidemiology
#103
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Outputs of similar age
#51,876
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Outputs of similar age from Clinical Epidemiology
#5
of 27 outputs
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