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Ishita Narvekar.jpg

Ishita Narvekar

Jr. Economist intern

Dietary intake of Parkinson's disease patients.

Published on: December 13, 2022

Original author: Baert F, Matthys C, et al. (2020) (DOI: 10.3389/fnut.2020.00105)

Parkinson's disease is the second most prevalent neurodegenerative disorder. Often, dietary management is supplemented as adjuvant therapy. Therefore, dietary-relevant studies may grant an interesting insight into the diet of PD patients and may provide insight as to how to reduce the intensity of various symptoms, thus, improving the patient's quality of life.​ In 2011, the British Dietetics Association (BDA) in partnership with Parkinson’s UK produced a best practice guideline for dieticians on the management of Parkinson's disease, emphasizing the importance of nutritional management in different stages of neurodegenerative disorder. Although no specific diet is required, different symptoms or consequences of PD should be taken into consideration. Not only nutrient composition but also the timing of consumption of meals plays a major role in PD management.​ Some studies suggest the amount of dietary protein intake is important in PD, as amino acids and levodopa (the most frequently used drug in PD) are absorbed via the large-neutral amino acid transporter, both at the level of the small intestine and the blood-brain barrier. Some other studies suggest a protective effect on the intake of different vitamins and antioxidants in PD but require further investigation. A ketonic diet is also proposed as a treatment for motor dysfunction in neurological disease but lacks clinical data and the risk of adverse effects currently prevents their therapeutic use.​ This paper describes the nutrient intake of Belgian PD patients, compare these intakes to the general nutritional recommendations, and further investigates their medical-taking behavior and knowledge of potential food-drug interactions. Methodology An observational, cross-sectional study was conducted. The samples of PD patients were recruited through participation in cooking workshops, and the inclusion criteria were self-reported diagnosis of PD and self-reported intake of any type of PD medication, cross-checked by the research team and the patient's physician. The record was completed during 2 non-consecutive days in the week before the workshop and included dietary and timing of medication intake. The record of 2 non-consecutive was chosen since they are the minimum number of days needed to properly estimate an individual’s intake.​ The general questionnaire was completed during the workshop which comprised multiple-choice questions about the socio-demographic characteristics, medication use, changes in the diet and their underlying reason, knowledge about food-drug interactions, and the sources of information concerning food-drug interactions.​ For the determination of nutrient intake, the Belgian Food Composition Data Base was used. Based on the actual intake, the usual dietary intake was calculated using the Multiple Source Method. Later, the percentage of macronutrients of the daily total energy was calculated using Atwater factors. Also, the energy intake of participants was compared with the average requirements of men and women (aged 60-70) based on energy intake using the physical activity level (PAL) 1.4-1.8. Micronutrient intake was compared with Estimated Average Requirements (age categories 19-70+), to determine the prevalence of inadequate intake using the EAR cut-off method.​ The normality of data was assessed using the Shapiro-Wilk test. If the data was not normally distributed, Mann-Whitney U-test was employed. Possible associations between categorical data of different socio-demographic characteristics were analyzed using Pearson's Chi-square test. A student's t-test was used to analyze the difference in nutrient intake according to gender. Results In total, 52 men and 22 women aged 49-84 years were included in the study. Records showing incompleteness of data or non-compliance to the instructions were excluded.​ Both the nutrients, that is, micro and macro, intake in this study were like the dietary pattern of the general Belgian population. However, results showed that the PD population had a high dietary fiber intake of 26.2±7.7 g/day, which was in line with the recommended intake. Most PD patients had an adequate intake of vitamin D and iron. When looking at food-drug interactions, most PD patients claimed to be aware of the interaction between dietary proteins and levodopa.​ Thus, the results from the study showed that monitoring dietary intake in PD patients is important to detect possible micronutrient insufficiencies. Moreover, the knowledge of patients regarding the importance of correct medication intake should be improved.

Association of multidimensional poverty with dementia in adults aged 50 years or older in South Africa.

Published on: September 28, 2022

Original author: Trani J, Moodley J et al. (2022) (DOI: 10.1001/jamanetworkopen.2022.4160)

Dementia has become a global health challenge. It is well documented that poor social determinants of health are directly associated with the disease. Hence a multidimensional approach to poverty (which encompasses various components of well-being measured in terms of individuals functioning and capabilities instead of resources or utility) offers not only a more precise account of risk factors that eventually trigger multiple conditions including dementia but also offers insight into how to improve care and policy. Methodology In this study, final samples from a cross-sectional study of 227 adults aged 50 years or older living in Soweto, Johannesburg, South Africa were collected. The 8-item interview to differentiate Aging and Dementia (Assessing Dementia 8 [AD8]) and the Rowland Universal Dementia Assessment Scale (RUDAS) were used to assess dementia.​ Multidimensional poverty measures: 7 dimensions were considered. Each dimension contained indicators identified in the literature as crucial to human development. ​1. Education: Education is associated with one’s ability to gain employment and earn an income. Study participants were considered deprived if they had access only to primary education. 2. Health: Any severe activity limitation or functioning difficulty was considered as the cut-off for deprivation of health. 3. Economic activity: Unemployment was considered an indicator of deprivation. The cut-off was used if an adult was unemployed, looking for a job, or not looking for a job because the participant was discouraged or could not afford the cost of seeking work or the wages offered were too low. 4. Living standards: Household living standards were composed of 3 indicators (waterpipe, electricity, and flush toilet), for which deprivation within the compound was the cut-off. 5. Social participation and fair treatment: Study participants who were not involved in any group were considered deprived. Discrimination and stigma were measured using the validated 22-item Unfair Treatment subscale of the Discrimination and Stigma Scale. Content and face validity tests were conducted. Moderate discrimination was the cut-off. 6. Psychological well-being: Measures of depression and self-esteem represented deprivation of psychological well-being. Depression was measured using the 10-item Centre for Epidemiologic Studies Depression Scale Revised (CESD-R-10). A score of 10 or higher was the established cut-off. Self-esteem was measured using the 10-item Rosenberg Self-Esteem Scale, with a score below 15 as the established cut-off. Statistical analysis Dimensions of deprivation were independently assessed. Then these multidimensional poverty measures were aggregated which consisted of 2 cut-offs –​ 1. Older adults were considered deprived if they fell below the cut-off on a given dimension. 2. The number of dimensions in which an older adult had to be deprived to be deemed multidimensionally poor. Further, a correlation analysis was performed to assess the overlap of dimensions of deprivation.​ Later, 3 indicators were measured: – 1. The poverty headcount indicates the number of older adults who lived below the poverty line. 2. The mean deprivation share is the mean number of dimensions of deprivation experienced by each older adult who lived below the poverty line. 3. The adjusted headcount ratio is the product of the poverty headcount and the mean deprivation share. The adjusted headcount ratio denotes the intensity of poverty. The study calculated unadjusted and adjusted logistic regression models to identify the association between dementia and multidimensional poverty. A person deprived of 4 or more dimensions was considered multidimensionally poor. Missing values (n=10) were treated as random. Results & discussion The study found that exposure to multidimensional poverty was strongly associated with dementia. Men with dementia were poorer and deprived in a higher number of dimensions than women with dementia. In addition, deprivation of education, health, and employment was identified as major contributors to multidimensional poverty, which constitutes an important indicator that social and environmental determinants of health are associated with dementia. Impact of the research This study provides evidence for physicians, allied health professionals, and policymakers to consider daily stressors associated with multidimensional poverty and aging. It offers some valuable insight into LMICs (low-and-middle-income countries) and what public policies (access to quality education, a strong workforce, and quality and free universal healthcare) could be prioritized that may be associated with dementia prevention and may reduce its effect on families and communities.

Health and its impact on economic growth in India – An explanation.

Published on: July 22, 2022

Original author: L. Nieland et al. (2022) (DOI: 10.1016/j.omto.2022.04.001)

The role of ‘human capital’ in economic growth is vital. An economy depends on human capital is now widely accepted. A higher level of human capital is the result of a higher level of health status, better health education, and new learning and training procedures with a good healthy mental and physical condition. Healthier people are more active and enthusiastic, making them more productive as compared to those who are ill. This paper aims to answer the question “Whether the notion of health status affecting economic growth is valid for India or not?” Methodology The data for the study has been obtained from the official website of 'The World Bank' and contains 55 samples. It uses ‘gross national income per capita’ or ‘GNI per capita as a proxy for economic growth. The health indicators are the life expectancy rate, infant mortality rate, under-five mortality rate, and total fertility rate.​ A linear regression method is used to examine the effect of health variables on gross domestic product per capita growth. However, to get an unbiased estimate of coefficients the two-stage least square method’ (2SLS) was applied using the instrumental variable approach. Results & discussion 1. The results from OLS regression showed that GNI per capita is positively correlated with life expectancy and negatively correlated with all other indicators namely infant mortality rate, under-five mortality rate, and total fertility rate. 2. Moreover, the OLS results reported that - The health indicators do not have a significant effect on gross national income per capita i.e., a simple linear regression showed that health has little or no impact on economic growth in India. The correlation between the health indicators does not show a high correlation between different health indicators and gross national income per capita. 3. Hence, there is the problem of endogeneity. To overcome this, the 2SLS method was used by introducing other explanatory variables like the total fertility rate and the population growth rate. It was found that there were highly significant estimates for the effect of health variables such as life expectancy, infant mortality, and under-five mortality rate. Thus, “Health does have a significant impact on Economic Growth in India.” Impact of the research To sum up, overall health affects the total factor productivity as healthy people are highly productive than their unhealthy counterparts. This paper provides that this fact is true for India also. Therefore, further steps need to be taken to improve the provision of health services as well as physical infrastructure to lift people out of poverty and provide them with a better standard of living.


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