Social and behavioral determinants of health in the era of artificial intelligence with electronic health records: A scoping review

Background: There is growing evidence that social and behavioral determinants of health (SBDH) play a substantial effect in a wide range of health outcomes. Electronic health records (EHRs) have been widely employed to conduct observational studies in the age of artificial intelligence (AI). However, there has been little research into how to make the most of SBDH information from EHRs. Methods: A systematic search was conducted in six databases to find relevant peer-reviewed publications that had recently been published. Relevance was determined by screening and evaluating the articles. Based on selected relevant studies, a methodological analysis of AI algorithms leveraging SBDH information in EHR data was provided. Results: Our synthesis was driven by an analysis of SBDH categories, the relationship between SBDH and healthcare-related statuses, and several NLP approaches for extracting SDOH from clinical literature. Discussion: The associations between SBDH and health outcomes are complicated and diverse; several pathways may be involved. Using Natural Language Processing (NLP) technology to support the extraction of SBDH and other clinical ideas simplifies the identification and extraction of essential concepts from clinical data, efficiently unlocks unstructured data, and aids in the resolution of unstructured data-related issues. Conclusion: Despite known associations between SBDH and disease, SBDH factors are rarely investigated as interventions to improve patient outcomes. Gaining knowledge about SBDH and how SBDH data can be collected from EHRs using NLP approaches and predictive models improves the chances of influencing health policy change for patient wellness, and ultimately promoting health and health equity. Keywords: Social and Behavioral Determinants of Health, Artificial Intelligence, Electronic Health Records, Natural Language Processing, Predictive ModelComment: 32 pages, 5 figure

DNA methylation as a biomarker for age-related cognitive impairment

PhD ThesisDue to the ageing population, the number of patients diagnosed with age-related diseases such as stroke and Parkinson’s disease are on the rise. In both post-stroke dementia (PSD) and mild cognitive impairment in Parkinson’s disease (PD-MCI), the mechanisms resulting in cognitive decline are unknown. This project aims to identify a biomarker which could predict those patients most at risk of developing cognitive decline, which would subsequently assist healthcare professionals in recommending early treatment and care. Epigenetics is an emerging field in which biomarkers have previously been useful in prognostication of cancers and prediction of cardiovascular disease. In this study, 30 patients from a PSD cohort (COGFAST) and 48 patients from a PD-MCI cohort (ICICLE) were analysed using the Illumina HumanMethylation450 BeadChip to identify differentially methylated positions which could predict patients who would later develop cognitive decline. Top hits were validated using Pyrosequencing to confirm DNA methylation differences in a replication cohort. Individual CpG sites within APOB and NGF were identified as potential blood-based biomarkers for PSD and one CpG site within CHCHD5 was highlighted as a potential blood-based biomarker for PD-MCI. In addition, methylation at one CpG site within NGF and a CpG site (cg18837178) within a non-coding RNA, were found to be associated with Braak staging (degree of brain pathology) using DNA from two brain regions. NGF deregulation has previously been associated with Alzheimer’s disease, and this finding indicates it may also have a role in the development of PSD. These novel findings represent the first steps towards the identification of blood-based biomarkers to assist with diagnosis of PSD and PD-MCI, but require further validation in a larger independent cohort. The differentially methylated genes identified may also give insight into some of the mechanisms involved in these complex diseases, potentially leading to the future development of targeted preventative treatments.Medical Research Council and Newcastle Universit

How to do things with (thousands of) words: Computational approaches to discourse analysis in Alzheimer's disease.

Natural Language Processing (NLP) is an ever-growing field of computational science that aims to model natural human language. Combined with advances in machine learning, which learns patterns in data, it offers practical capabilities including automated language analysis. These approaches have garnered interest from clinical researchers seeking to understand the breakdown of language due to pathological changes in the brain, offering fast, replicable and objective methods. The study of Alzheimer's disease (AD), and preclinical Mild Cognitive Impairment (MCI), suggests that changes in discourse (connected speech or writing) may be key to early detection of disease. There is currently no disease-modifying treatment for AD, the leading cause of dementia in people over the age of 65, but detection of those at risk of developing the disease could help with the identification and testing of medications which can take effect before the underlying pathology has irreversibly spread. We outline important components of natural language, as well as NLP tools and approaches with which they can be extracted, analysed and used for disease identification and risk prediction. We review literature using these tools to model discourse across the spectrum of AD, including the contribution of machine learning approaches and Automatic Speech Recognition (ASR). We conclude that NLP and machine learning techniques are starting to greatly enhance research in the field, with measurable and quantifiable language components showing promise for early detection of disease, but there remain research and practical challenges for clinical implementation of these approaches. Challenges discussed include the availability of large and diverse datasets, ethics of data collection and sharing, diagnostic specificity and clinical acceptability

Artificial Intelligence for Cognitive Health Assessment: State-of-the-Art, Open Challenges and Future Directions

The subjectivity and inaccuracy of in-clinic Cognitive Health Assessments (CHA) have led many researchers to explore ways to automate the process to make it more objective and to facilitate the needs of the healthcare industry. Artificial Intelligence (AI) and machine learning (ML) have emerged as the most promising approaches to automate the CHA process. In this paper, we explore the background of CHA and delve into the extensive research recently undertaken in this domain to provide a comprehensive survey of the state-of-the-art. In particular, a careful selection of significant works published in the literature is reviewed to elaborate a range of enabling technologies and AI/ML techniques used for CHA, including conventional supervised and unsupervised machine learning, deep learning, reinforcement learning, natural language processing, and image processing techniques. Furthermore, we provide an overview of various means of data acquisition and the benchmark datasets. Finally, we discuss open issues and challenges in using AI and ML for CHA along with some possible solutions. In summary, this paper presents CHA tools, lists various data acquisition methods for CHA, provides technological advancements, presents the usage of AI for CHA, and open issues, challenges in the CHA domain. We hope this first-of-its-kind survey paper will significantly contribute to identifying research gaps in the complex and rapidly evolving interdisciplinary mental health field

Impact of nutrition on cognition and its association with blood and brain Alzheimer disease related biomarkers

Alzheimer’s disease (AD), the most common form of senile dementia, currently affects over 35 million people worldwide. While there is no cure or effective treatment, early intervention programs hold considerable promise. Following particular dietary patterns represents one potential intervention strategy accessible to all. Results from previous studies investigating the association of diet, cognition and biomarkers of AD are inconsistent: Positive results have been reported (1-7), whilst others have shown no associations. Prior to this thesis, no study has assessed the relationship of four dietary patterns to cognition, blood-based and neuroimaging biomarkers of AD in a large highly-characterised ageing cohort. Participants drawn from the Australian Imaging, Biomarkers, and Lifestyle study of ageing, provided a fasting blood sample, underwent comprehensive neuropsychological assessment and neuroimaging at baseline, 18 and 36 month follow-up assessments, and completed a Cancer Council of Victoria food frequency questionnaire (used to construct dietary patterns) at baseline. Chapter 3 explored the relationship between dietary pattern adherence and cognition. AD participants demonstrated reduced adherence to the ‘healthy’ Mediterranean (MeDi) and prudent diets, and higher adherence to the ‘unhealthy’ western diet and the inflammatory dietary index compared to cognitively healthy controls (HC). Longitudinal analysis conducted on individuals classified as HC at baseline proposes the importance of adhering to a ‘healthy’ dietary pattern such as the MeDi, with respect to reducing risk for cognitive decline: Executive function and visuospatial functioning appeared most susceptible to the influence of diet. Chapter 4 investigated the potential mechanisms underlying the observed effects of dietary patterns on cognition. A lack of significant associations between the MeDi and western diet patterns and biomarker indexes of metabolic syndrome and cardiovascular disease risk, suggests that modulation of these factors may not underlie the effects of diet on cognition reported in Chapter 3. Consistent with published literature, we found our western dietary pattern to be positively associated with levels of blood-based biomarkers of inflammation and the reverse to be true of our MeDi and prudent diet patterns. Our inflammatory dietary index was also strongly positively correlated with levels of numerous inflammatory biomarkers. The strong associations observed suggest that interplay between diet and elevated chronic inflammation may contribute to the effects of diet on cognition described in this thesis. Chapter 5 assessed the ‘reliability’ (similarity of 12 month dietary intake recalled on different occasions) and ‘validity’ (intake agreement between FFQ and a four-day weighed food record) of the online CSIROFFQ following addition of questions regarding foods of interest in AD research. Our results suggest that the modified CSIROFFQ is ‘reliable’ and a ‘relatively valid’ tool which provides acceptable assessment of long-term dietary intake in Australian older adults, particularly in the context of AD research. To our knowledge, this is the first study extensively comparing MeDi, inflammatory dietary index, western and prudent diet patterns to cognition and biomarkers of AD in an elderly, well-characterised cohort. Our results combined with published data, suggest diet has a role to play in AD prevention; however, it is clear that the complex link requires further characterisation

Associations between diet, cognitive function and dementia risk in UK adults

Cognitive decline and dementia are of increasing concern in aging societies worldwide. Diet, as a modifiable lifestyle factor, represents a target for prevention or limiting progression. However, evidence on associations of cognitive function and dementia with diet remains limited and inconsistent, especially on meat consumption summarized in the systematic review of this project. Cross-sectional associations of dietary factors with one cognitive test (reaction time) and dementia (ascertained via death registers) were conducted in UK Women’s Cohort Study (UKWCS). The results showed that consumption of specific food groups, energy-adjusted nutrient intakes, and adherence to dietary patterns were not statistically associated with reaction time and dementia in the UKWCS. Cross-sectional and longitudinal associations of food consumption, especially meat intakes, with five cognitive tests (visual memory, numeric memory, prospective memory, fluid intelligence, and reaction time) and dementia (ascertained via self-report and linkages to hospital admission data and death registers) were conducted in UK Biobank (UKB). Incident dementia cases occurring within 1-year or 3-year follow-up were excluded due to potential reverse causation, and similar results were observed between the two types of exclusion. The results showed that high consumption of processed meat was associated with increased risks of prevalent and incident dementia; with a non-linear pattern of this association indicated in the UKB. Associations between consumption of other meat types and cognitive performance and dementia risk were not consistent in the UKB. A diet-gene interaction of APOE ε4 allele on dementia risk was explored, and all P values for interaction were not significant. In addition, high consumption of vegetables, fruits, and fish were observed to be associated with poor cognitive performance and increased risk of incident dementia in the UKB although effect sizes were small. This project highlights potentially non-linear associations between meat consumption and dementia risk, which may be independent of APOE ε4 allele carriage. Findings on consumption of vegetables, fruits, and fish were not consistent with the hypotheses proposed of a protective effect in this thesis. However, the effect sizes were relatively small and therefore need to be interpreted with caution and to be confirmed in other studies

Impact of Individual and Combined Sensory Impairment in Older Australians

Purpose: To estimate the prevalence and examine the clustering patterns of visual, auditory and olfactory impairments; to estimate the associations of olfactory impairment with neurodegenerative and other morbidities; to estimate the associations of visual and auditory impairments with morbidity and mortality using Cox regression; and to examine the associations of visual and auditory impairments with morbidity and mortality using structural equation modelling to identify potential indirect pathways and assess whether Cox regression underestimated the associations between VI, AI and mortality in a representative sample of older Australians. Methods: The Blue Mountains Eye Study (BMES) examined 3,654 persons aged 49+ during 1992-1994, and after 5 and 10 years. The Blue Mountains Hearing Study (BMHS) invited participants who attended the second cross-sectional survey of the Blue Mountains Eye Study (BMES 2). Persons who moved into the study area or study age group, identified from a repeat door-to door census in 1999, were also invited to participate. The Blue Mountains Hearing Study (BMHS) examined 2956 persons aged 49+ years (75.5% response) during 1997-2000. Vision, hearing and olfaction were assessed in BMES 3. Assessment was by interviewer administered structured questionnaire, clinical examination, audiometry, blood testing and the San Diego Odor Identification Test. A total of 1,497 (74.3% of all participants) had complete vision, auditory and olfactory data after BMES 3. Visual impairment (VI) was categorized as either: presenting visual impairment (PVI), VA less than 6/12 Snellen equivalent (25 decibels hearing level (dBHL). Cognitive impairment was defined as mini mental state exam (MMSE) scores <24. Log-linear models were used to assess the concomitant presence of the three sensory impairments (visual, auditory and olfactory). Observed frequencies of concomitant sensory impairments were compared to the expected frequencies estimated assuming they occurred independently (no clustering tendency). Multivariable adjusted logistic regression models were constructed to estimate associations between olfactory impairment and morbidities, including neurodegenerative conditions. Associations between visual impairment and mortality risk, and between hearing loss and mortality risk, were estimated using Cox regression and structural equation modelling (SEM). Odds ratios (OR), hazard ratios (HR) and 95% confidence intervals (CI) are presented. A p-value of less than 0.05 was considered statistically significant. Australian National Death Index data confirmed deaths until 2005.   Results: After13 years from baseline, 1273 participants had died. After 5 years from BMES 2 (BMHS), 403 participants had died. At BMES 3, the prevalence of PVI, CVI and NCVI was 11%, 8% and 3% respectively. The prevalence of any OI was 27.0% and the prevalence of AI was 43%. The observed prevalence of having all three sensory impairments in persons with PVI (or NCVI) was 2.6 (or 3.0) times greater than predicted if they clustered independently. VI, AI and OI clustered differently in women compared to men. Inverse associations were observed between OI and body mass index (OR per 5 kg/m2 increase, 0.8, CI 0.7-0.9) and between moderate impairment and hypertension (OR 0.6, CI 0.4-0.9). There was no significant relationship with angina, previous myocardial infarction or diabetes. Persons with Parkinson disease had an increased likelihood of both mild (OR 9.8, CI 2.0-47.5) and moderate OI (OR 16.1, CI 3.8-68.2), as did persons with impaired cognitive function (OR 3.3, CI 1.3-8.6 and OR 3.7, CI 1.5-9.6, respectively). After adjusting for mortality risk markers using Cox regression, higher mortality was associated with NCVI (HR 1.35, CI 1.04-1.75). This association was stronger for ages <75 years (HR 2.58, CI 1.42-4.69). Structural equation modelling revealed greater effects of NCVI on mortality risk (HR 5.25, CI 1.97-14.01 for baseline ages <75), with both direct (HR 2.16, CI 1.11-4.23) and indirect effects (HR 2.43, CI 1.17-5.03). Of the mortality risk markers examined, only disability in walking demonstrated a significant indirect pathway for the link between VI and mortality. Disability in walking acted both directly on mortality and via an association with self-rated health. Using Cox regression, hearing loss was associated with increased risk of both cardiovascular (HR 1.36, CI 1.08-1.84) and all-cause mortality (HR 1.39, CI 1.11-1.79) after adjustment for age and sex, but not after multivariable adjustment. Structural equation modelling pathway analysis, however, revealed a higher all-cause mortality risk (HR 2.58, CI 1.64-4.05) in persons with hearing loss, which was mediated by two variables: cognitive impairment (HR 1.45, CI 1.08-1.94) and disability in walking (HR 1.63, CI 1.24-2.15). These variables increased mortality both directly and indirectly through effects on self-rated health. Conclusions: In this representative population of older Australians, over one in ten persons had VI, over one in four persons had OI and almost one in two persons had AI. The prevalence of VI, AI and OI increased with increasing age. The prevalence of AI and OI was higher in males. The prevalence of VI was higher in females. Visual, auditory and olfactory impairments aggregated mutually and dependently. Visual impairment and AI were significantly associated with morbidity and mortality. Visual impairment predicted mortality by both direct and indirect pathways. Auditory impairment predicted mortality via indirect pathways. Disability in walking, which can substantially influence general health, represented a major indirect pathway for both VI and AI. Auditory impairment was also associated with increased all-cause mortality via cognitive impairment and self-rated health. Adjustment for these co-variables using Cox regression underestimated the associations between VI and AI and mortality. Olfactory impairment was inversely associated with BMI and hypertension. Olfactory impairment was significantly higher among persons with Parkinson disease and cognitive impairment. It is important to recognise that persons with sensory impairments are at increased risk of important comorbidities and mortality. Dependent clustering of sensory impairments suggest the possibility of a common underlying mechanism and that separate hearing and vision services may not adequately support older persons

Dietary patterns in the older New Zealand adult and their associations with cognitive function and metabolic syndrome : the Researching Eating, Activity, and Cognitive Health (REACH) study : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Nutritional Science at Massey University, Albany, New Zealand

Background: The global population is ageing. Ageing and poor diet are common risk factors for cognitive decline and metabolic syndrome which reduce functionality in later years. A dietary pattern approach considers the full complexity of the diet. Dietary patterns in an older New Zealand context have not been identified nor their associations with cognitive function or metabolic syndrome. Aims and objectives: This thesis, referred to as the REACH (Researching, Eating, Activity, and Cognitive Health) study, explored associations between dietary patterns and cognitive function and metabolic syndrome in older New Zealand adults. To achieve the aim a food frequency questionnaire (FFQ) was assessed for reproducibility, relative validity, and its suitability to derive robust dietary patterns. Further, associations between these dietary patterns and their nutrient and energy intake; the socio-demographic and lifestyle factors of the participants; and cognitive function and metabolic syndrome outcomes were examined. Method: Community-dwelling adults from Auckland, New Zealand were recruited (aged 65-74 years, 36% male, n 371). Dietary patterns were derived from a 109-item FFQ using 57 food groups and principal component analysis. Nutrient, energy, and alcohol intake were calculated using FOODfiles, the New Zealand Food composition database. The REACH FFQ and its derived dietary patterns were assessed for reproducibility and relative validity in a sub-set of the REACH participants (n 294). Reproducibility was assessed using an identical FFQ (FFQ2) administered one month after the initial REACH FFQ. A 4-day food record (4-DFR), collected between FFQ administrations, assessed relative validity. Cognitive function, covering six domains (global cognition, attention and vigilance, executive function, episodic memory, working memory and spatial memory), was assessed using COMPASS (Computerised Mental Performance Assessment System). Self-administered questionnaires collected health (medication and supplement intake), demographic and lifestyle [including sex, education levels, living status (alone or with someone), smoking status, physical activity levels, address (for Index of Multiple Deprivation)], and physical activity (International Physical Activity Questionnaire) data. A fasted blood sample was collected for measuring genetic [Apolipoprotein E -ε4 (APOE -ε4)] and biochemical markers (triglycerides, high- and low-density lipoprotein cholesterol). Blood pressure and anthropometric measures [weight, height, waist circumference, and body fat % (using dual X-ray absorptiometry)] were collected. Metabolic syndrome was defined by the National Cholesterol Education Program Adult Treatment Panel III. Abstract ii Statistical analyses performed: Reproducibility and relative validity of the REACH FFQ (food group intakes) and its derived dietary patterns (scores) were assessed using Spearman correlation coefficients (acceptable correlation rho=0.20-0.49), weighted kappa statistic (κw) (acceptable statistic κw=0.20-0.60), and Bland-Altman analysis including mean difference, limits of agreement, plots, and slope of bias. The similarity between dietary pattern loadings were assessed using Tucker’s congruence coefficient. Linear or logistic regression were used to examine associations between dietary patterns and their nutrients; socio-demographic and lifestyle factors; and health outcomes. Confounding adjustments included age, sex, education, index of multiple deprivation, energy intake, APOE -ε4, and physical activity. Results: In the validation study, the FFQ food groups showed good reproducibility (mean correlation coefficient = 0.69, mean κw = 0.62) and acceptable relative validity (mean correlation coefficient = 0.45, mean κw = 0.38) though Bland Altman plots showed bias and mean differences significantly different to zero in some food groups. Three similar dietary patterns were identified from each dietary assessment tool: ‘Mediterranean style’, ‘Western’, and ‘prudent’. Congruence coefficients between factor loadings ranged from 0.54 to 0.80. Correlations of dietary pattern scores ranged from 0.47 to 0.59 (reproducibility) and 0.33 to 0.43 (validity) (all P<0.001); weighted kappa scores from 0.40 to 0.48 (reproducibility) and 0.27 to 0.37 (validity); limits of agreement from ± 1.79 to ± 2.09 (reproducibility) and ± 2.09 to ± 2.27 (validity); a slope of bias was seen in the ‘prudent’ pattern for reproducibility and validity (P<0.001). From the full REACH dietary data set, three valid dietary patterns were derived explaining 18% of the variation in the diet. The ‘Mediterranean style’ pattern (salad vegetables; leafy cruciferous vegetables; other vegetables; avocados and olives; alliums; nuts and seeds; white fish and shellfish; oily fish; berries; water; salad dressings; cruciferous vegetables; eggs; cheese; tomatoes; and all other fruit) was associated with higher levels of beta-carotene equivalents, vitamin E, and folate intake (all P<0.001, all R2 ≥ 0.26), along with being female, having a higher physical activity level, and higher education (P<0.001, R2 = 0.07). The ‘Western’ pattern (processed meat; sauces and condiments; cakes, biscuits and puddings; meat pies and chips; processed fish; confectionery; vegetable oils; beer; chocolate; salad dressings; cheese; and sweetened cereal) was associated with higher daily energy intake (P<0.001, R2 = 0.43), along with being male, having a higher alcohol intake, living with others, and a secondary education (males only) (P<0.001, R2 = 0.16). The ‘prudent’ pattern (dried legumes; soy-based foods; fresh and frozen legumes; whole grains; carrots; and Abstract iii spices) was associated with a higher fibre and carbohydrate intake (both P<0.001, both R2 ≥ 0.25), along with higher physical activity and lower alcohol intake (P<0.001, R2 = 0.15). Neither the ‘Mediterranean style’ nor ‘prudent’ patterns were associated with either cognitive function or metabolic syndrome. The ‘Western’ pattern was not associated with cognitive function, but was positively associated with metabolic syndrome [odds ratio = 1 .67 (95% CI 1.08, 2.63)] (P=0.02). Being younger (P<0.05), female (P<0.001), having a higher education (P<0.01) or no APOE -ε4 allele (P<0.05) were associated with better cognitive function. Higher deprivation (P<0.001) was associated with metabolic syndrome. Conclusion: A novel and robust study with valid tools did not find any associations between dietary patterns and cognitive function in older adults living in New Zealand. Age, sex, education, and the APOE -ε4 allele were more predictive of cognitive function than the dietary patterns. A ‘Western’ dietary pattern and higher deprivation were predictive of metabolic syndrome. To reduce the odds of metabolic syndrome, actions should aim to improve deprivation, and shift people’s dietary intake away from the ‘Western’ dietary pattern