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Objective: Environmental influence and dietary variations are well-known risk factors for various diseases including neurodegenerative disorders. Preliminary evidence suggests that diet in early-life and living environment might influence the incidence of Parkinson’s disease (PD) in later phase of life. There have been limited epidemiologic studies on this aspect especially in India. In this hospital-based case-control study, we intended to identify dietary and environmental risk factors of PD. Methods: Patients with PD (n = 105), Alzheimer’s disease (AD) (n = 53) and healthy individuals (n = 81) were recruited. Dietary intake and environmental exposures were assessed using a validated Food-Frequency and Environmental Hazard Questionnaire. Their demographic details and living environment were also recorded using the same questionnaire. Results: Pre-morbid consumption of carbohydrate and fat was significantly higher whereas dietary fiber and fruit content was significantly lesser in PD as compared to AD and healthy age-matched controls. Meat and milk intake was the highest among all the food groups in PD patients. Rural living and their habitation near water bodies were significantly more frequent in PD patients. Conclusion: We found that past intake of carbohydrate, fat, milk, and meat are associated with increased risk of PD. On the other hand, rural living and habitat near water bodies might be associated with incidence and severity of PD. Hence, preventive strategies related to dietary and environmental modulators in PD might be clinically useful in the future.

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Parkinson's disease (PD) lacks a definitive diagnosis due to a lack of pathological validation of patients at antemortem. The risk of misdiagnosis is high in the early stages of PD, often eluded by atypical parkinsonian symptoms. Neuroimaging and laboratory biomarkers are being sought to aid in the clinical diagnosis of PD. Nigrosome imaging and neuromelanin (NM)-sensitive magnetic resonance imaging (MRI) are the new emerging tools, both technically simple plus cost-effective for studying nigral pathology, and have shown potential for authenticating the clinical diagnosis of PD. Visual assessment of the nigrosome-1 appearance, at 3 or 7 Tesla, yields excellent diagnostic accuracy for differentiating idiopathic PD from healthy controls. Moreover, midbrain atrophy and putaminal hypointensity in nigrosome-1 imaging are valid pointers in distinguishing PD from allied parkinsonian disorders. The majority of studies employed T2 and susceptibility-weighted imaging MRI sequences to visualize nigrosome abnormalities, whereas T1-weighted fast-spin echo sequences were used for NM imaging. The diagnostic performance of NM-sensitive MRI in discriminating PD from normal HC can be improved further. Longitudinal studies with adequate sampling of varied uncertain PD cases should be designed to accurately evaluate the sensitivity and diagnostic potential of nigrosome and NM imaging techniques. Equal weightage is to be given to uniformity and standardization of protocols, data analysis, and interpretation of results. There is tremendous scope for identifying disease-specific structural changes in varied forms of parkinsonism with these low-cost imaging tools. Nigrosome-1 and midbrain NM imaging may not only provide an accurate diagnosis of PD but could mature into tools for personally tailored treatment and prognosis.