Cognitive function and cardiometabolic disease risk factors in rural South Africa: baseline evidence from the HAALSI study

Evidence on cognitive function in older South Africans is limited, with few population-based studies. We aimed to estimate baseline associations between cognitive function and cardiometabolic disease risk factors in rural South Africa. We use baseline data from "Health and Aging in Africa: A Lo...

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Published inBMC public health Vol. 19; no. 1; pp. 1579 - 11
Main Authors Houle, Brian, Gaziano, Thomas, Farrell, Meagan, Gómez-Olivé, F Xavier, Kobayashi, Lindsay C, Crowther, Nigel J, Wade, Alisha N, Montana, Livia, Wagner, Ryan G, Berkman, Lisa, Tollman, Stephen M
Format Journal Article
LanguageEnglish
Published England BioMed Central Ltd 27.11.2019
BioMed Central
BMC
Subjects
Acquired immune deficiency syndrome
Africa
Aged
Aging
AIDS
Blood pressure
Body mass index
Cardiometabolic disease
Cardiovascular Diseases - epidemiology
Cardiovascular Diseases - psychology
Cognition
Cognitive ability
Cognitive function
Confidence intervals
Correlation analysis
Cross-sectional studies
Diabetes
Diabetes mellitus
Dyslipidemia
Emtricitabine
Epidemiology
Female
Future predictions
Health
Health risks
HIV
Human immunodeficiency virus
Humans
Hypertension
Life expectancy
Longitudinal Studies
Male
Medical research
Metabolic Diseases - epidemiology
Metabolic Diseases - psychology
Middle Aged
Mortality
Noncommunicable disease
Numeracy
Obesity
Older people
Population
Population studies
Public health
Regression analysis
Retirement
Risk analysis
Risk Factors
Rural areas
Rural Population - statistics & numerical data
Smoking
Sociodemographics
South Africa - epidemiology
Statistical analysis
Studies
Underweight
South Africa
Sub-Saharan Africa
Africa
Cardiometabolic disease
Noncommunicable disease
Cross-sectional studies
Cognitive function
Epidemiology
Africa
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Abstract Evidence on cognitive function in older South Africans is limited, with few population-based studies. We aimed to estimate baseline associations between cognitive function and cardiometabolic disease risk factors in rural South Africa. We use baseline data from "Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa" (HAALSI), a population-based study of adults aged 40 and above in rural South Africa in 2015. Cognitive function was measured using measures of time orientation, immediate and delayed recall, and numeracy adapted from the Health and Retirement Study cognitive battery (overall total cognitive score range 0-26). We used multiple linear regression to estimate associations between cardiometabolic risk factors (including BMI, hypertension, dyslipidemia, diabetes, history of stroke, alcohol frequency, and smoking status) and the overall cognitive function score, adjusted for potential confounders. In multivariable-adjusted analyses (n = 3018; male = 1520; female = 1498; median age 59 (interquartile range 50-67)), cardiometabolic risk factors associated with lower cognitive function scores included: diabetes (b = - 1.11 [95% confidence interval: - 2.01, - 0.20] for controlled diabetes vs. no diabetes); underweight BMI (b = - 0.87 [CI: - 1.48, - 0.26] vs. normal BMI); and current and past smoking history compared to never smokers. Factors associated with higher cognitive function scores included: obese BMI (b = 0.74 [CI: 0.39, 1.10] vs. normal BMI); and controlled hypertension (b = 0.53 [CI: 0.11, 0.96] vs. normotensive). We provide an important baseline from rural South Africa on the associations between cardiometabolic disease risk factors and cognitive function in an older, rural South African population using standardized clinical measurements and cut-offs and widely used cognitive assessments. Future studies are needed to clarify temporal associations as well as patterns between the onset and duration of cardiometabolic conditions and cognitive function. As the South African population ages, effective management of cardiometabolic risk factors may be key to lasting cognitive health.
AbstractList Evidence on cognitive function in older South Africans is limited, with few population-based studies. We aimed to estimate baseline associations between cognitive function and cardiometabolic disease risk factors in rural South Africa. We use baseline data from "Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa" (HAALSI), a population-based study of adults aged 40 and above in rural South Africa in 2015. Cognitive function was measured using measures of time orientation, immediate and delayed recall, and numeracy adapted from the Health and Retirement Study cognitive battery (overall total cognitive score range 0-26). We used multiple linear regression to estimate associations between cardiometabolic risk factors (including BMI, hypertension, dyslipidemia, diabetes, history of stroke, alcohol frequency, and smoking status) and the overall cognitive function score, adjusted for potential confounders. In multivariable-adjusted analyses (n = 3018; male = 1520; female = 1498; median age 59 (interquartile range 50-67)), cardiometabolic risk factors associated with lower cognitive function scores included: diabetes (b = - 1.11 [95% confidence interval: - 2.01, - 0.20] for controlled diabetes vs. no diabetes); underweight BMI (b = - 0.87 [CI: - 1.48, - 0.26] vs. normal BMI); and current and past smoking history compared to never smokers. Factors associated with higher cognitive function scores included: obese BMI (b = 0.74 [CI: 0.39, 1.10] vs. normal BMI); and controlled hypertension (b = 0.53 [CI: 0.11, 0.96] vs. normotensive). We provide an important baseline from rural South Africa on the associations between cardiometabolic disease risk factors and cognitive function in an older, rural South African population using standardized clinical measurements and cut-offs and widely used cognitive assessments. Future studies are needed to clarify temporal associations as well as patterns between the onset and duration of cardiometabolic conditions and cognitive function. As the South African population ages, effective management of cardiometabolic risk factors may be key to lasting cognitive health.
Background Evidence on cognitive function in older South Africans is limited, with few population-based studies. We aimed to estimate baseline associations between cognitive function and cardiometabolic disease risk factors in rural South Africa. Methods We use baseline data from "Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa" (HAALSI), a population-based study of adults aged 40 and above in rural South Africa in 2015. Cognitive function was measured using measures of time orientation, immediate and delayed recall, and numeracy adapted from the Health and Retirement Study cognitive battery (overall total cognitive score range 0-26). We used multiple linear regression to estimate associations between cardiometabolic risk factors (including BMI, hypertension, dyslipidemia, diabetes, history of stroke, alcohol frequency, and smoking status) and the overall cognitive function score, adjusted for potential confounders. Results In multivariable-adjusted analyses (n = 3018; male = 1520; female = 1498; median age 59 (interquartile range 50-67)), cardiometabolic risk factors associated with lower cognitive function scores included: diabetes (b = - 1.11 [95% confidence interval: - 2.01, - 0.20] for controlled diabetes vs. no diabetes); underweight BMI (b = - 0.87 [CI: - 1.48, - 0.26] vs. normal BMI); and current and past smoking history compared to never smokers. Factors associated with higher cognitive function scores included: obese BMI (b = 0.74 [CI: 0.39, 1.10] vs. normal BMI); and controlled hypertension (b = 0.53 [CI: 0.11, 0.96] vs. normotensive). Conclusions We provide an important baseline from rural South Africa on the associations between cardiometabolic disease risk factors and cognitive function in an older, rural South African population using standardized clinical measurements and cut-offs and widely used cognitive assessments. Future studies are needed to clarify temporal associations as well as patterns between the onset and duration of cardiometabolic conditions and cognitive function. As the South African population ages, effective management of cardiometabolic risk factors may be key to lasting cognitive health. Keywords: Africa, Cognitive function, Cross-sectional studies, Epidemiology, Noncommunicable disease, Cardiometabolic disease
Evidence on cognitive function in older South Africans is limited, with few population-based studies. We aimed to estimate baseline associations between cognitive function and cardiometabolic disease risk factors in rural South Africa.BACKGROUNDEvidence on cognitive function in older South Africans is limited, with few population-based studies. We aimed to estimate baseline associations between cognitive function and cardiometabolic disease risk factors in rural South Africa.We use baseline data from "Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa" (HAALSI), a population-based study of adults aged 40 and above in rural South Africa in 2015. Cognitive function was measured using measures of time orientation, immediate and delayed recall, and numeracy adapted from the Health and Retirement Study cognitive battery (overall total cognitive score range 0-26). We used multiple linear regression to estimate associations between cardiometabolic risk factors (including BMI, hypertension, dyslipidemia, diabetes, history of stroke, alcohol frequency, and smoking status) and the overall cognitive function score, adjusted for potential confounders.METHODSWe use baseline data from "Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa" (HAALSI), a population-based study of adults aged 40 and above in rural South Africa in 2015. Cognitive function was measured using measures of time orientation, immediate and delayed recall, and numeracy adapted from the Health and Retirement Study cognitive battery (overall total cognitive score range 0-26). We used multiple linear regression to estimate associations between cardiometabolic risk factors (including BMI, hypertension, dyslipidemia, diabetes, history of stroke, alcohol frequency, and smoking status) and the overall cognitive function score, adjusted for potential confounders.In multivariable-adjusted analyses (n = 3018; male = 1520; female = 1498; median age 59 (interquartile range 50-67)), cardiometabolic risk factors associated with lower cognitive function scores included: diabetes (b = - 1.11 [95% confidence interval: - 2.01, - 0.20] for controlled diabetes vs. no diabetes); underweight BMI (b = - 0.87 [CI: - 1.48, - 0.26] vs. normal BMI); and current and past smoking history compared to never smokers. Factors associated with higher cognitive function scores included: obese BMI (b = 0.74 [CI: 0.39, 1.10] vs. normal BMI); and controlled hypertension (b = 0.53 [CI: 0.11, 0.96] vs. normotensive).RESULTSIn multivariable-adjusted analyses (n = 3018; male = 1520; female = 1498; median age 59 (interquartile range 50-67)), cardiometabolic risk factors associated with lower cognitive function scores included: diabetes (b = - 1.11 [95% confidence interval: - 2.01, - 0.20] for controlled diabetes vs. no diabetes); underweight BMI (b = - 0.87 [CI: - 1.48, - 0.26] vs. normal BMI); and current and past smoking history compared to never smokers. Factors associated with higher cognitive function scores included: obese BMI (b = 0.74 [CI: 0.39, 1.10] vs. normal BMI); and controlled hypertension (b = 0.53 [CI: 0.11, 0.96] vs. normotensive).We provide an important baseline from rural South Africa on the associations between cardiometabolic disease risk factors and cognitive function in an older, rural South African population using standardized clinical measurements and cut-offs and widely used cognitive assessments. Future studies are needed to clarify temporal associations as well as patterns between the onset and duration of cardiometabolic conditions and cognitive function. As the South African population ages, effective management of cardiometabolic risk factors may be key to lasting cognitive health.CONCLUSIONSWe provide an important baseline from rural South Africa on the associations between cardiometabolic disease risk factors and cognitive function in an older, rural South African population using standardized clinical measurements and cut-offs and widely used cognitive assessments. Future studies are needed to clarify temporal associations as well as patterns between the onset and duration of cardiometabolic conditions and cognitive function. As the South African population ages, effective management of cardiometabolic risk factors may be key to lasting cognitive health.
Abstract Background Evidence on cognitive function in older South Africans is limited, with few population-based studies. We aimed to estimate baseline associations between cognitive function and cardiometabolic disease risk factors in rural South Africa. Methods We use baseline data from “Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa” (HAALSI), a population-based study of adults aged 40 and above in rural South Africa in 2015. Cognitive function was measured using measures of time orientation, immediate and delayed recall, and numeracy adapted from the Health and Retirement Study cognitive battery (overall total cognitive score range 0–26). We used multiple linear regression to estimate associations between cardiometabolic risk factors (including BMI, hypertension, dyslipidemia, diabetes, history of stroke, alcohol frequency, and smoking status) and the overall cognitive function score, adjusted for potential confounders. Results In multivariable-adjusted analyses (n = 3018; male = 1520; female = 1498; median age 59 (interquartile range 50–67)), cardiometabolic risk factors associated with lower cognitive function scores included: diabetes (b = − 1.11 [95% confidence interval: − 2.01, − 0.20] for controlled diabetes vs. no diabetes); underweight BMI (b = − 0.87 [CI: − 1.48, − 0.26] vs. normal BMI); and current and past smoking history compared to never smokers. Factors associated with higher cognitive function scores included: obese BMI (b = 0.74 [CI: 0.39, 1.10] vs. normal BMI); and controlled hypertension (b = 0.53 [CI: 0.11, 0.96] vs. normotensive). Conclusions We provide an important baseline from rural South Africa on the associations between cardiometabolic disease risk factors and cognitive function in an older, rural South African population using standardized clinical measurements and cut-offs and widely used cognitive assessments. Future studies are needed to clarify temporal associations as well as patterns between the onset and duration of cardiometabolic conditions and cognitive function. As the South African population ages, effective management of cardiometabolic risk factors may be key to lasting cognitive health.
Background: Evidence on cognitive function in older South Africans is limited, with few population-based studies. We aimed to estimate baseline associations between cognitive function and cardiometabolic disease risk factors in rural South Africa. Methods: We use baseline data from "Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa" (HAALSI), a population-based study of adults aged 40 and above in rural South Africa in 2015. Cognitive function was measured using measures of time orientation, immediate and delayed recall, and numeracy adapted from the Health and Retirement Study cognitive battery (overall total cognitive score range 0-26). We used multiple linear regression to estimate associations between cardiometabolic risk factors (including BMI, hypertension, dyslipidemia, diabetes, history of stroke, alcohol frequency, and smoking status) and the overall cognitive function score, adjusted for potential confounders. Results: In multivariable-adjusted analyses (n = 3018; male = 1520; female = 1498; median age 59 (interquartile range 50-67)), cardiometabolic risk factors associated with lower cognitive function scores included: diabetes (b = - 1.11 [95% confidence interval: - 2.01, - 0.20] for controlled diabetes vs. no diabetes); underweight BMI (b = - 0.87 [CI: - 1.48, - 0.26] vs. normal BMI); and current and past smoking history compared to never smokers. Factors associated with higher cognitive function scores included: obese BMI (b = 0.74 [CI: 0.39, 1.10] vs. normal BMI); and controlled hypertension (b = 0.53 [CI: 0.11, 0.96] vs. normotensive). Conclusions: We provide an important baseline from rural South Africa on the associations between cardiometabolic disease risk factors and cognitive function in an older, rural South African population using standardized clinical measurements and cut-offs and widely used cognitive assessments. Future studies are needed to clarify temporal associations as well as patterns between the onset and duration of cardiometabolic conditions and cognitive function. As the South African population ages, effective management of cardiometabolic risk factors may be key to lasting cognitive health.
Background Evidence on cognitive function in older South Africans is limited, with few population-based studies. We aimed to estimate baseline associations between cognitive function and cardiometabolic disease risk factors in rural South Africa. Methods We use baseline data from “Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa” (HAALSI), a population-based study of adults aged 40 and above in rural South Africa in 2015. Cognitive function was measured using measures of time orientation, immediate and delayed recall, and numeracy adapted from the Health and Retirement Study cognitive battery (overall total cognitive score range 0–26). We used multiple linear regression to estimate associations between cardiometabolic risk factors (including BMI, hypertension, dyslipidemia, diabetes, history of stroke, alcohol frequency, and smoking status) and the overall cognitive function score, adjusted for potential confounders. Results In multivariable-adjusted analyses (n = 3018; male = 1520; female = 1498; median age 59 (interquartile range 50–67)), cardiometabolic risk factors associated with lower cognitive function scores included: diabetes (b = − 1.11 [95% confidence interval: − 2.01, − 0.20] for controlled diabetes vs. no diabetes); underweight BMI (b = − 0.87 [CI: − 1.48, − 0.26] vs. normal BMI); and current and past smoking history compared to never smokers. Factors associated with higher cognitive function scores included: obese BMI (b = 0.74 [CI: 0.39, 1.10] vs. normal BMI); and controlled hypertension (b = 0.53 [CI: 0.11, 0.96] vs. normotensive). Conclusions We provide an important baseline from rural South Africa on the associations between cardiometabolic disease risk factors and cognitive function in an older, rural South African population using standardized clinical measurements and cut-offs and widely used cognitive assessments. Future studies are needed to clarify temporal associations as well as patterns between the onset and duration of cardiometabolic conditions and cognitive function. As the South African population ages, effective management of cardiometabolic risk factors may be key to lasting cognitive health.
Evidence on cognitive function in older South Africans is limited, with few population-based studies. We aimed to estimate baseline associations between cognitive function and cardiometabolic disease risk factors in rural South Africa. We use baseline data from "Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa" (HAALSI), a population-based study of adults aged 40 and above in rural South Africa in 2015. Cognitive function was measured using measures of time orientation, immediate and delayed recall, and numeracy adapted from the Health and Retirement Study cognitive battery (overall total cognitive score range 0-26). We used multiple linear regression to estimate associations between cardiometabolic risk factors (including BMI, hypertension, dyslipidemia, diabetes, history of stroke, alcohol frequency, and smoking status) and the overall cognitive function score, adjusted for potential confounders. In multivariable-adjusted analyses (n = 3018; male = 1520; female = 1498; median age 59 (interquartile range 50-67)), cardiometabolic risk factors associated with lower cognitive function scores included: diabetes (b = - 1.11 [95% confidence interval: - 2.01, - 0.20] for controlled diabetes vs. no diabetes); underweight BMI (b = - 0.87 [CI: - 1.48, - 0.26] vs. normal BMI); and current and past smoking history compared to never smokers. Factors associated with higher cognitive function scores included: obese BMI (b = 0.74 [CI: 0.39, 1.10] vs. normal BMI); and controlled hypertension (b = 0.53 [CI: 0.11, 0.96] vs. normotensive). We provide an important baseline from rural South Africa on the associations between cardiometabolic disease risk factors and cognitive function in an older, rural South African population using standardized clinical measurements and cut-offs and widely used cognitive assessments. Future studies are needed to clarify temporal associations as well as patterns between the onset and duration of cardiometabolic conditions and cognitive function. As the South African population ages, effective management of cardiometabolic risk factors may be key to lasting cognitive health.
ArticleNumber 1579
Audience Academic
Author Houle, Brian
Crowther, Nigel J
Tollman, Stephen M
Gaziano, Thomas
Kobayashi, Lindsay C
Farrell, Meagan
Gómez-Olivé, F Xavier
Montana, Livia
Wagner, Ryan G
Wade, Alisha N
Berkman, Lisa
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  organization: Centre for Global Health Research, Umeå University, Umeå, Sweden
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  fullname: Berkman, Lisa
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  organization: Centre for Global Health Research, Umeå University, Umeå, Sweden. stephen.tollman@wits.ac.za
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Issue 1
Keywords Cardiometabolic disease
Noncommunicable disease
Cross-sectional studies
Cognitive function
Epidemiology
Africa
Language English
License Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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Snippet Evidence on cognitive function in older South Africans is limited, with few population-based studies. We aimed to estimate baseline associations between...
Background Evidence on cognitive function in older South Africans is limited, with few population-based studies. We aimed to estimate baseline associations...
Background: Evidence on cognitive function in older South Africans is limited, with few population-based studies. We aimed to estimate baseline associations...
Abstract Background Evidence on cognitive function in older South Africans is limited, with few population-based studies. We aimed to estimate baseline...
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SubjectTerms Acquired immune deficiency syndrome
Africa
Aged
Aging
AIDS
Blood pressure
Body mass index
Cardiometabolic disease
Cardiovascular Diseases - epidemiology
Cardiovascular Diseases - psychology
Cognition
Cognitive ability
Cognitive function
Confidence intervals
Correlation analysis
Cross-sectional studies
Diabetes
Diabetes mellitus
Dyslipidemia
Emtricitabine
Epidemiology
Female
Future predictions
Health
Health risks
HIV
Human immunodeficiency virus
Humans
Hypertension
Life expectancy
Longitudinal Studies
Male
Medical research
Metabolic Diseases - epidemiology
Metabolic Diseases - psychology
Middle Aged
Mortality
Noncommunicable disease
Numeracy
Obesity
Older people
Population
Population studies
Public health
Regression analysis
Retirement
Risk analysis
Risk Factors
Rural areas
Rural Population - statistics & numerical data
Smoking
Sociodemographics
South Africa - epidemiology
Statistical analysis
Studies
Underweight
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Title Cognitive function and cardiometabolic disease risk factors in rural South Africa: baseline evidence from the HAALSI study
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