Dietary and Environmental Risk Factors in Parkinson’s and Alzheimer’s Disease: A Semi-Quantitative Pilot Study : Annals of Indian Academy of Neurology

Secondary Logo

Journal Logo

Original Article

Dietary and Environmental Risk Factors in Parkinson’s and Alzheimer’s Disease: A Semi-Quantitative Pilot Study

Roy, Akash1,2; Choudhury, Supriyo1; Banerjee, Rebecca1; Basu, Purba1; Mondal, Banashree1; Sarkar, Swagata1; Anand, Sidharth Shankar1; Dey, Sanjit2,3; Kumar, Hrishikesh1,

Author Information
Annals of Indian Academy of Neurology 26(2):p 174-192, Mar–Apr 2023. | DOI: 10.4103/aian.aian_823_22
  • Open



“Let food be thy medicine and medicine be thy food.” - Hippocrates

The crosstalk between diet and disease have been mentioned in various ancient scripts and discussed widely since time immemorial.[1] Despite growing awareness about food hygiene and safety, foodborne diseases still remain a major public health concern in the contemporary world. Nearly, 150 million people were affected with foodborne diseases in South-East Asian counties, which resulted in 175000 deaths in 2010.[2] Due to the possibility of gross underreporting, even this enormous estimate of incidence appears to be just the tip of an iceberg. In India, the epidemiological reports of human lathyrism and epidemic dropsy are classical examples of dietary-toxin-induced organ damage.[3] Diet may play an important role in the etiology of Parkinson’s disease, either by altering the oxidative balance in the brain or by serving as a vehicle for environmental neurotoxins.[4] Few epidemiological studies have been able to examine potential associations between diet and Parkinson’s disease (PD) because of its relatively low incidence and insidious onset.[5] Previous studies have highlighted the involvement of Mediterranean diet in neurodegenerative disorders like PD.[6] Nonetheless, the dietary risk factors of neurodegenerative conditions are increasingly identified but yet to reach a consensus. Environmental factors have strong influence on the dietary habit of an individual; hence, these factors should not be studied in isolation.

On that note, dietary and environmental modifiers of PD and Alzheimer’s disease (AD) have gained substantial attention in recent past.[7,8] Epidemiological studies have found association between high intake of dietary animal fat with the increased risk of PD.[9] Similarly, prospective studies have confirmed an association between milk intake and a higher incidence of PD.[10] Micro-contamination of pesticides and urate-lowering effects of milk have been hypothesized to trigger PD-pathogenesis.[11] On the contrary, diet rich in antioxidants, vitamins, polyphenols, and fish have been reported to decrease the risk of neurodegenerative disorders including AD and PD.[12] Notably, fish is often the major source of proteins in coastal regions of India including major part of eastern India. Fatty acids and micronutrients present in fish could lower the risk of neurodegeneration.[13] Not all vitamins are likely to protect from occurrence of PD but consumption of some have surprisingly claimed to increase the chance of PD. A case-control study suggested that consumption of food rich in vitamin E early in adult life might increase the risk of PD in later part of their life. However, this study was underpowered to generate conclusive evidence. There is limited number of studies on dietary restriction as an intervention to modify disease processes relevant to neurodegeneration. Rodent studies have shown reduced rates of immunologic aging, delayed morbidity, and increased longevity with dietary restriction.[14] Moreover, polyphenols present in tea, a widely consumed beverage in India, demonstrated neuroprotection in preclinical models of PD.[15]

Environmental factors are likely to be critical in the pathogenesis of neurodegenerative diseases. For example, exposure to pesticides[16] and rural living has strong association to PD. Rotenone and paraquat have been shown to induce dopaminergic neuronal loss in the substantia nigra and striatum in animals, leading to PD-like symptoms.[17] Recently, b-N-methylamino-L-alanine (BMAA), a natural non-proteinogenic diamino acid produced by cyanobacteria and diatoms present in the pond have shown potential to trigger neurodegeneration.[18] Studies have shown that, living near water body and related BMAA exposure might be responsible for protein misfolding and aggregation, resulting in neuro-inflammation in PD.[19]

Based on these considerations we hypothesize that; past dietary and environmental chemicals-toxins might impact the incidence of PD in the later stage of one’s life. To examine it, we have conducted a hospital-based case-control study using a validated questionnaire to identify dietary and environmental risk factors of PD.


Study population

This study was conducted between May 2018 and December 2020 after approval from Institutional ethics committee (IEC) (I-NK/MDR/PD Diet/2018 and IHEC/SD/P29/18; dated 26.02.2018. Patients with PD (n = 105) and AD (n = 83) were consecutively recruited from the outpatient department after signing the informed consent approved by the Institutional ethics committee. Standard sample size calculation was followed before participant recruitment. PD was diagnosed as per UK Brain Bank Criteria and AD as per DSM-IV[20] criteria by expert neurologist. We have recruited mild to moderate PD and AD patients to exclude the recall bias of dietary habit and environmental hazards questionnaires. PD and AD patients without dementia and mild to moderate PD patients with H&Y stage less than 3 Moderate to severe, Tremor dominant, and PIGD variant of PD patients were excluded from the study, as patient’s disease course might influence dietary recall. Age-matched Control Subjects (n = 51) were recruited randomly from the hospital staffs and general healthy population of Bengal. Healthy participants with cognitive impairment, any dietary allergic history, and geriatric diseases were excluded. Standard sample size calculation and power calculation were followed. Participants’ details on ethnicity-location, socioeconomic status, and education were also collected. As participants family member’s dietary patterns were also from same kitchen based on our questionnaire and revalidation from patient’s caregiver 10% of AD patient’s family member had forgetfulness and related behavioral anomalies and 5% of PD patients has or had PD like motor, non-motor complications (RBD, Slowness etc.). Recall bias of Food-Frequency Questionnaire could be a limitation of the study. This study aimed to recruit very mild-demented patients based on MoCA criteria: very mild AD (MoCA 21–26 points) to eliminate recall bias.[20] Patient with other parkinsonian disorders, other dementia, and psychotic disorders were excluded.

Motor and cognitive assessment

MDS-UPDRS Part III was used for motor assessment of PD patients. Cognitive assessments were performed through Montreal Cognitive Assessment (MOCA).[21]

Dietary and environmental factors assessments

The structured questionnaire for interview (Supplementary Material) was adopted from tools used in similar studies with the objective to assess environmental exposures[22,23] and dietary habits in PD, AD, and healthy controls. The questionnaire covers details of demography, medical, and personal history as well as pre-morbid food habit and living environment/habitat in two separate parts. The validated Food-Frequency Questionnaire (FFQ) and Environmental Hazard Questionnaire (EHQ) were designed and validated to capture dietary patterns and environmental effects prior to clinical diagnosis of the disease.[22,23] FFQ contains 108 standard food items and there was provision of mentioning additional food items. EHQ contains 20 standard questions related to environmental exposure, Leaving near waterbody “Pond (small/big), River, Lake, Seas or stream” or not (e.g., Distance from Waterbody) and job description (Supplementary Material). Participants were asked to recall any exposure to environmental toxins and waterbody at their pre-disease phase and the duration of exposure. Participants were interviewed by blinded and independent dietitian and often responses were confirmed from patients’ care giver when needed. For EHQ, data were converted to frequency distribution prior to risk analysis. Participants were instructed to report the frequency of consumption of individual food items (number of portions per day or per week). The nutrient-composition of individual food items was computed from the Indian Food Composition Table, National Institute of Nutrition (year 2017).[24] Patients were requested to recall and report their general dietary habits one year prior to the diagnosis of their disease (As they were mild to moderate PD/AD patients), while controls were asked to report their general food intake pattern one year prior to the interview. Finally, we have re-checked the answer of dietary environmental data with patient’s caregiver/family member to avoid any disparity.

Statistical analysis

Descriptive statistics were presented using mean, standard deviation (SD) for numerical variables, and frequency for categorical variables. Normality of data was assessed by Shapiro–Wilk test. Kruskal-Wallis one-way ANOVA followed by Bonferroni’s correction of Multiple comparison was performed to check the inter-group difference of numerical data. For categorical outcome, binary logistic regression was performed, respectively, to find the beta values/Odds Ratios (OR) and 95% Confidence Intervals (CI) of the regressors. Predictive models were developed after adjustment of age, gender, disease duration, BMI, and BSA. Statistical analysis was performed using SPSS-Version 20 software, IBM, USA.


Clinical and demographic data

Clinical and demographic characteristics of healthy controls, PD and AD patients are presented in Table 1. All three groups had comparable age, gender, Body Mass Index (BMI), and Body Surface Area (BSA) (p > 0.05). All participants were from Eastern Indian-Bengal population. Approximately, 93% participants were Bengali, 4% were Muslim, and 3% were others (Marwari and other north-Indians). Socioeconomic status and education were comparable among participants. There was no significant difference in cognitive parameters (MOCA) between PD patients and healthy controls (p > 0.05) but as expected it was significantly low in AD compared to healthy controls (p < 0.05).

Table 1:
Demographic details, clinical characteristics of healthy control, Parkinson’s and Alzheimer’s patients

Profile of past dietary intake

For macronutrients, pre-morbid weekly consumption of carbohydrate and fat was significantly higher in PD compared to AD and healthy controls (p < 0.001) whereas pre-morbid weekly consumption of dietary fiber was significantly lower in PD compared to AD and healthy controls (p < 0.001) [Figure 1].

Figure 1:
Pre-disease dietary profile of PD, AD and Healthy Control. (a-d) Pre-disease intake level of Moisture, Carbohydrate, Protein, Fat, Dietary Fiber, Meat, Fish, Milk, Vegetable, and Fruit in patients with PD, AD, and healthy age-matched controls. Kruskal-Wallis ANOVA with Bonferroni adjustment was used for inter-group comparison; data presented as Mean ± SD. P < 0.05 considered significant *&P < 0.01 as **

Among food groups, weekly intake of meat and milk products were significantly higher in PD compared to AD and healthy controls (p < 0.001) and weekly fruit intake was significantly lower in PD and AD compared to healthy controls (p < 0.001) [Figure 1].

Weekly intake of any of the macronutrients and specific food group except fruit were not significantly different in AD compared to healthy control (p > 0.05). We did not find any inter-group difference of weekly intake of protein, fish, vegetables, and moisture content of food (p > 0.05). As retrospective semi-quantitative approach was followed, we have failed to quantify specific food group (e.g., animal or plant-based protein, etc.) between groups. All the significances retained even after adjustment of Bonferroni’s correction of Multiple comparison [Figure 1].

Dietary risk factors in PD

Continuous dietary data were converted to ranked two categorical variables according to quartiles of distribution among the controls. Odds Ratios (OR) with 95% Confidence Intervals (CI) were calculated with binary logistic regression. Prediction of disease was calculated based on the past intake of the mentioned dietary components. In PD, patients reported a significantly higher consumption of carbohydrate and specific food groups like milk and fruits, as seen in ORs [Table 2] [Figure 2]. According to our data, there were no significant differences in the moisture content of food and consumption of protein, dietary fiber, fish, meat, and vegetables (p > 0.05) [Table 2] [Figure 2].

Table 2:
Adjusted odds ratios of dietary and environmental risk factors (highest versus lowest quartile) with 95% confidence intervals for Parkinson’s disease according to intakes of various foods and food groups
Figure 2:
Dietary Risk Factors in Parkinson’s disease. Forest plots of the odds ratio (OR) and 95% confidence interval (CI) for the association between the food groups and Parkinson’s disease. Binary logistic regression was performed and predictive modeling was devolved after adjustment of age, gender, disease duration, BMI, and BSA. P <0.05 considered significant *& P < 0.01 as **

Multivariate logistic model was established between nutrients, but we have failed to show any collinearity (p > 0.05). All values were adjusted for age, gender, BMI, BSA, and disease duration. Logistic predictive model with the identified variables showed the Nagelkerke R Square value of 0.691 (p < 0.01).

We failed to establish any significant logistic predictive model in AD with the past intake of dietary factors, Nagelkerke R Square value of 0.273 (p 0.821).

Environmental risk factors in PD and AD

Environmental factors like presence of waterbody near (within 500 mtr) the habitat (OR = 7.523, 95% CI: 3.43 – 12.48, P trend = 0.001), consumption of well water (OR = 4.67, 95% CI: 1.43 – 6.95, P trend = 0.001), and rural habitat (OR = 4.185, 95% CI: 2.20 – 5.96, P trend = 0.001) could significantly predict the incidence of PD. Consumption of tobacco-products and water purity did not demonstrate significant risk for PD and AD after adjustment (p > 0.05) [Table 2] [Figure 3a]. Mean exposure to environmental risk factors were 59 ± 6 months. Prediction of disease was calculated based on the environmental and life-style factors. Logistic predictive model with the identified factors showed the Nagelkerke R Square value of 0.435 (p < 0.001). Rural habitat (OR = 0.318, 95% CI: 0.15 – 0.67, P trend = 0.002) not the urban and water body near the habitat (OR = 3.978, 95% CI: 1.90 – 8.35, P trend = 0.001) were significantly associated with increased AD incidence [Figure 3b].

Figure 3:
Environmental Risk factors in Parkinson’s and Alzheimer’s disease. Forest plots of the odds ratio (OR) and 95% confidence interval (CI) for the association between the environmental factors and Parkinson’s disease (a) and Alzheimer’s disease (b). Binary logistic regression was performed and predictive modeling was devolved after adjustment of age, gender, disease duration, BMI, and BSA. P < 0.05 considered significant *& P < 0.01 as **


The aim of this study was to look for possible dietary and environmental risk factors for PD compared to AD and healthy matched control. In the current study, we could identify a fixed trend of dietary pattern and living environment in PD and AD patients’ independent of possible confounders like age, disease duration, BMI, BSA, and total energy intake.

Pattern of pre-morbid diet in PD

The current study revealed that intake of carbohydrate was higher in PD compared to AD and healthy individuals [Figure 2]. While analyzing the food-groups, we found that pre-morbid consumption of meat and milk was significantly larger in PD. In agreement with our results, recent meta-analysis also showed a relative risk of 1.24 for PD with past carbohydrate intake.[25] Additionally, ultralow-carbohydrate diet or ketogenic diet has shown potential to improve non-motor symptoms in PD. Notably, all kinds of fat might not be beneficial for PD. For example, higher intake of polyunsaturated fatty acids could reduce the risk of PD, whereas higher cholesterol and arachidonic acid intake could elevate PD risk.[21] In the current study, we could not estimate the fatty acid sub-types due to retrospective nature of the study.

Meat is a well-known source of saturated fatty acid. Consumption of meat in high quantity might lead to oxidative stress and neuro-inflammation.[26] Hence, neurodegeneration is not unexpected in individuals who consume meat in large quantity. Additionally, it is reported that meat is a ready exogenous source of a-synuclein (a putative pathogenic protein for PD).[27] Central accumulation of dietary a-synuclein through gastro intestinal tract-brain axes might be one possible reason behind the association of high meat consumption and PD. Similar to several prospective epidemiological studies we also found an association between milk intake and a higher incidence of PD.[11,28] Slow accumulation of pesticides in the brain from contaminated milk might be one of the potential triggers for neurodegeneration. Another possibility is through urate-lowering effects of milk, as urate is a natural antioxidant. Hence, depletion of urate might precipitate oxidative stress-induced neurodegeneration.[29]

We have observed that, past intake of protective factors like dietary fibers and fruit intake to be significantly associated with lower incidence of PD. Previous studies have already highlighted the beneficial role of Mediterranean diet (rich in fruits and vegetables) in PD.[6] We did not find any association of PD with reported pre-morbid dietary moisture content of food, protein, fish, and vegetables.

Surprisingly, we did not find any significant association of AD with past dietary pattern unlike PD. Contrary to our findings, very few studies have observed distinct dietary risk factors for AD.[30] This is not entirely unexpected as their pathogenesis is different to a large extent despite having few similarities. Non-homogenous characteristics and different genetic makeup can be the reason behind this.

Predictability of specific dietary components as risk factors of PD

We checked the independent predictability of specific dietary factor as a risk factor for PD. While pre-morbid consumption of dietary carbohydrate, milk was identified as an independent risk factor for PD, past intake of fruits was found to lower the risk of PD even after adjustment with disease duration. In line with our findings, another study indicated carbohydrate and sweet products as potential risk factors in PD.[22] A recent report showed that subjects who consumed milk are at 1.34 times higher risk of developing PD in the later part of their life than those who consumed milk minimally.[31] Intake of dietary vitamin E and ß-carotene present in fruits and vegetables was found to lower the risk of PD, in a separate case-control study.[32]

Environmental factors as potential risk factor for neurodegenerative disorders

In the current study, we found that subjects living near water bodies are more susceptible to neurodegenerative disorders like AD and PD. A recent report showing the neurotoxicity of BMAA secreted by aquatic fauna (cyanobacteria) might be of relevance to our finding.[33] Accumulated through diet and drinking water, BMAA after biomagnification could trigger neurodegeneration in humans.[34,35] Interaction of BMAA with the mucosal immune system and the enteric nervous system (ENS) through mitochondrial pathways has been shown.[36] BMAA also elicited a pronounced decrease in oxidative phosphorylation, altered calcium homeostasis, and exacerbated ROS production. Recent findings have confirmed that, in addition to the deleterious effects on mitochondria, BMAA exposure also is also associated with the pro-inflammatory profile observed in neurodegenerative diseases.[36]

Contrary to our findings, an in-silico study reported that BMAA is not involved in AD. The authors did not find any protein-protein interaction between BMAA and b-Amyloid on their simulation model.

Rural living and well-water consumption were assessed together as well water consumption is a part of rural or agricultural lifestyle to a large extent.[37] Both these factors were found to be associated with the increased risk of AD and PD. Another study also showed a significant association between PD risk and rural living (RR = 1.17) but not with well-water consumption (RR = 1.09) (p = 0.91). The higher use of pesticide in rural environment could be a potential cause for this association.

The study has few limitations. Small study population is the major limitation of the study. Post hoc power calculation, from major outcome—difference in dietary parameters in disease group found a >90% power with an alpha error of 5%. For example, there is a fair chance of inaccurate reporting of the pre-morbid dietary pattern due to recall bias, which is likely to be higher in patients with dementia. We tried to minimize the impact of this bias, as the responses were often confirmed from the family members. Moreover, patients with severe dementia were excluded from the study. Another potential source of bias might have resulted due to semi-quantitative analysis of past dietary intake. However, exact quantification of dietary sub-group is almost impossible to find in retrospective studies.


In summary, this is the one of the very few studies from south-east Asia designed to identify potential dietary and environmental risk factors for PD. We observed that higher milk and meat consumption or less portions of fruits in pre-morbid stage were associated with greater risk of PD incidence in later part of one’s life. Similarly, upon analyzing the component, we observed that high carbohydrate or low dietary fibers were also associated with the risk of PD. Rural living and habitation near water body in their pre-morbid state were more common in both PD and AD. Consumption of well-water did not demonstrate any significant association with occurrence of PD/AD in later stage of life. A multi-centric large scale cohort study will be necessary for recommending dietary modification as a preventive strategy against PD/AD, at a policy level.

Statistical Analysis: Mr. Akash Roy and Dr Supriyo Choudhury

Author Contribution:

Akash Roy: Study concept and design, acquisition of data, analysis and interpretation, first draft of the manuscript, critical revision of the manuscript for important intellectual content.

[email protected]

Supriyo Choudhury: Study concept and design, Analysis and interpretation, critical revision of the manuscript for important intellectual content

[email protected]

Rebecca Banerjee: Study concept and design, Analysis and interpretation, critical revision of the manuscript for important intellectual content

[email protected]

Purba Basu: Analysis and interpretation, Critical revision of the manuscript for important intellectual content

[email protected]

Banashree Mondal: Analysis and interpretation, Critical revision of the manuscript for important intellectual content

[email protected]

Swagata Sarkar: Analysis and interpretation, Critical revision of the manuscript for important intellectual content

[email protected]

Sidharth Shankar Anand: Analysis and interpretation, Critical revision of the manuscript for important intellectual content

[email protected]

Sanjit Dey: Study concept and design, Critical revision of the manuscript for important intellectual content, study supervision

[email protected], [email protected]

Hrishikesh Kumar: Study concept and design, critical revision of the manuscript for important intellectual content, study supervision

[email protected]

Financial Disclosure:

AR: Senior Research Fellow of Institute of Neurosciences Kolkata and University of Calcutta

SC: Employee of Institute of Neurosciences Kolkata

RB: Employee of Institute of Neurosciences Kolkata

PB: Employee of Institute of Neurosciences Kolkata

SS: Research Fellow of Institute of Neurosciences Kolkata

BM: Research Fellow of Institute of Neurosciences Kolkata

SSA: Employee of Institute of Neurosciences Kolkata

SD: Employee of University of Calcutta

HK: Employee of Institute of Neurosciences Kolkata

Data availability statement

The data that support the findings of this study are freely available from the corresponding author, [S.D], [H.K] upon reasonable request.

Ethical compliance statement

This study was conducted after approval from Institutional ethics committee (IEC), Institute of Neurosciences Kolkata (I-NK/MDR/PD Diet/2018; dated 26.02.2018). Participants were recruited as per the approved protocol and only after the written informed consent. We confirm that we have read the Journal’s position on issues involved in ethical publication and affirm that this work is consistent with those guidelines.

Financial support and sponsorship

Institutional research fund, Institute of Neurosciences Kolkata (I-NK) of H.K. and DST-INSPIRE fellowship [IF-170628] Government of India to A.R.

Conflicts of interest

There are no conflicts of interest.


We are thankful to the participants for their consent and to those who provided direct and indirect support to the success of the study. We also want to thank Mr. Basanta Kumar Roy of Indian Institute of Hygiene and Public Health for his scientific inputs in validating the Food-Frequency Questionnaire


1. Huremović D. Brief history of pandemics (pandemics throughout history). Psychiatry of Pandemics. Springer 2019 7–35.
2. Faour-Klingbeil D, Todd ECD. Prevention and control of foodborne diseases in Middle-East North African countries:Review of national control systems. Int J Environ Res Public Health 2019;17:70.
3. Sharma BD, Malhotra S, Bhatia V, Rathee M. Epidemic dropsy in India. Postgrad Med J 1999;75:657–61.
4. Agim ZS, Cannon JR. Dietary factors in the etiology of Parkinson's disease. BioMed Res Int 2015;2015:672838.
5. Chen H, O'Reilly E, McCullough ML, Rodriguez C, Schwarzschild MA, Calle EE, et al. Consumption of dairy products and risk of Parkinson's disease. Am J Epidemiol 2007;165:998–1006.
6. Metcalfe-Roach A, Yu AC, Golz E, Cirstea M, Sundvick K, Kliger D, et al. MIND and mediterranean diets associated with later onset of Parkinson's disease. Mov Disord 2021;36:977–84.
7. Boulos C, Yaghi N, El Hayeck R, Heraoui GNHA, Fakhoury-Sayegh N. Nutritional risk factors, microbiota and Parkinson's disease:What is the current evidence?Nutrients 2019;11:1896.
8. Bellou V, Belbasis L, Tzoulaki I, Evangelou E, Ioannidis JP. Environmental risk factors and Parkinson's disease:An umbrella review of meta-analyses. Parkinsonism Relat Disord 2016;23:1–9.
9. Anderson C, Checkoway H, Franklin GM, Beresford S, Smith-Weller T, Swanson PD. Dietary factors in Parkinson's disease:The role of food groups and specific foods. Mov Disord 1999;14:21–7.
10. Jiang W, Ju C, Jiang H, Zhang D. Dairy foods intake and risk of Parkinson's disease:A dose--response meta-analysis of prospective cohort studies. Eur J Epidemiol 2014;29:613–9.
11. Hughes AJ, Daniel SE, Kilford L, Lees AJ. Accuracy of clinical diagnosis of idiopathic Parkinson's disease:A clinico-pathological study of 100 cases. J Neurol Neurosurg Psychiatry 1992;55:181–4.
12. Ramassamy C, Belkacémi A. Editorial [Hot topic:Nutrition and Alzheimer's disease:Is there any connection?(Guest Editor:C. Ramassamy)]. Curr Alzheimer Res 2011;8:443–4.
13. Canhada S, Castro K, Perry IS, Luft VC. Omega-3 fatty acids'supplementation in Alzheimer's disease:A systematic review. Nutr Neurosci 2018;21:529–38.
14. Weindruch R, Lane MA, Ingram DK, Ershler WB, Roth GS. Dietary restriction in rhesus monkeys:Lymphopenia and reduced mitogen-induced proliferation in peripheral blood mononuclear cells. Aging Clin Exp Res 1997;9:304–8.
15. Zhou ZD, Xie SP, Saw WT, Ho PGH, Wang H, Lei Z, et al. The therapeutic implications of tea polyphenols against dopamine (DA) Neuron Degeneration in Parkinson's disease (PD). Cells 2019;8:911.
16. Cannon JR, Greenamyre JT. The role of environmental exposures in neurodegeneration and neurodegenerative diseases. Toxicol Sci 2011;124:225–50.
17. Cannon JR, Greenamyre JT. Neurotoxic in vivo models of Parkinson's disease:Recent advances. Prog Brain Res 2010;184:17–33.
18. Murch SJ, Cox PA, Banack SA. A mechanism for slow release of biomagnified cyanobacterial neurotoxins and neurodegenerative disease in Guam. Proc Natl Acad Sci 2004;101:12228–31.
19. Gerhardt S, Mohajeri MH. Changes of colonic bacterial composition in Parkinson's disease and other neurodegenerative diseases. Nutrients 2018;10:708.
20. Arevalo-Rodriguez I, Smailagic N, Figuls MRI, Ciapponi A, Sanchez-Perez E, Giannakou A, et al. Mini-mental state examination (MMSE) for the detection of Alzheimer's disease and other dementias in people with mild cognitive impairment (MCI). Cochrane Database Syst Rev 2015;2015:CD010783.
21. Lihala S, Mitra S, Neogy S, Datta N, Choudhury S, Chatterjee K, et al. Dance movement therapy in rehabilitation of Parkinson's disease –A feasibility study. J Bodyw Mov Ther 2021;26:12–7.
22. Hellenbrand W, Seidler A, Boeing H, Robra BP, Vieregge P, Nischan P, et al. Diet and Parkinson's disease I:A possible role for the past intake of specific foods and food groups:Results from a self-administered food-frequency questionnaire in a case-control study. Neurology 1996;47:636–43.
23. Ganguli D, Das N, Saha I, Biswas P, Datta S, Mukhopadhyay B, et al. Major dietary patterns and their associations with cardiovascular risk factors among women in West Bengal, India. Br J Nutr 2011;105:1520–9.
24. Longvah T, Anantan I, Bhaskarachary K, Venkaiah K, Longvah T. Indian Food Composition Tables. National Institute of Nutrition, Indian Council of Medical Research Hyderabad 2017.
25. Wang A, Lin Y, Wu Y, Zhang D. Macronutrients intake and risk of Parkinson's disease:A meta-analysis. Geriatr Gerontol Int 2015;15:606–16.
26. Agnihotri A, Aruoma OI. Alzheimer's disease and Parkinson's disease:A nutritional toxicology perspective of the impact of oxidative stress, mitochondrial dysfunction, nutrigenomics and environmental chemicals. J Am Coll Nutr 2020;39:16–27.
27. Killinger BA, Labrie V. Vertebrate food products as a potential source of prion-like $a$-synuclein. NPJ Parkinsons Dis 2017;3:33.
28. Hughes KC, Gao X, Kim IY, Wang M, Weisskopf MG, Schwarzschild MA, et al. Intake of dairy foods and risk of Parkinson disease. Neurology 2017;89:46–52.
29. Kistner A, Krack P. Parkinson's disease:No milk today?Front Neurol 2014;5:172.
30. Hu N, Yu JT, Tan L, Wang YL, Sun L, Tan L. Nutrition and the risk of Alzheimer's disease. BioMed Res Int 2013;2013:524820.
31. Kyrozis A, Ghika A, Stathopoulos P, Vassilopoulos D, Trichopoulos D, Trichopoulou A. Dietary and lifestyle variables in relation to incidence of Parkinson's disease in Greece. Eur J Epidemiol 2013;28:67–77.
32. Okamoto K, Kihira T, Kobashi G, Washio M, Sasaki S, Yokoyama T, et al. Fruit and vegetable intake and risk of amyotrophic lateral sclerosis in Japan. Neuroepidemiology 2009;32:251–6.
33. Nunes-Costa D, Magalhães JD, G-Fernandes M, Cardoso SM, Empadinhas N. Microbial BMAA and the Pathway for Parkinson's disease neurodegeneration. Front Aging Neurosci 2020;12:26.
34. Banack SA, Johnson HE, Cheng R, Cox PA. Production of the neurotoxin BMAA by a marine cyanobacterium. Mar Drugs 2007;5:180–96.
35. Ra Dunlop, Banack Sa, Bishop Sl, Metcalf Js, Murch Sj, Davis DA, Stommel Ew, et al. “Is exposure to BMAA a risk factor for neurodegenerative diseases?A response to a critical review of the BMAA hypothesis.”. Neurotoxicity research 2021;39:81–106.
36. Beri J, Nash T, Martin RM, Bereman MS. Exposure to BMAA mirrors molecular processes linked to neurodegenerative disease. Proteomics 2017;17:10.1002/pmic. 201700161. doi:10.1002/pmic. 201700161.
37. Breckenridge CB, Berry C, Chang ET, Sielken RL Jr, Mandel JS. Association between Parkinson's disease and cigarette smoking, rural living, well-water consumption, farming and pesticide use:Systematic review and meta-analysis. PloS One 2016;11:e0151841.

Alzheimer’s disease; diet; environment Parkinson’s disease; risk factor

Copyright: © 2023 Annals of Indian Academy of Neurology