scholarly journals IMPACT OF PRAKRITI ON COGNITION AND WORKING MEMORY: A REVIEW

2021 ◽  
Vol 12 (3) ◽  
pp. 76-78
Author(s):  
Shilpy Gupta ◽  
Vijendra Kumar
Keyword(s):  
Working Memory ◽  
Information Processing ◽  
Health Status ◽  
Mental Function ◽  
Individual Health ◽  
Proper Functioning ◽  
Body Constitution ◽  
Individual Health Status ◽  
Constitution Type

State of body and mind depends upon individual Prakriti (type of body constitution). Medha is grasping power, for which proper functioning of memory and mind is essential. Medha includes Dhee (wisdom), Dhriti (retaining power of mind) and Smriti (memory) which are the component of higher mental function. Cognition involves different kind of information processing, recollection and overall process involved in the formation of memory. Working memory is a mental workspace for processing of both new input and retrieved memories. Dosha decide the Sharirik (bodily constitution) and Mansik Prakriti (psychological constitution) of individual. It helps to understand and describe individual health status and intelligence like characteristics. Prakriti have an effect on the working of higher mental function, every individual has its own constitution type and hence mental function works differently according to its constitution.

scholarly journals Pengaruh Faktor Demografi dan Sosial Ekonomi terhadap Status Kesehatan Individu di Indonesia

2021 ◽  
Vol 5 (2) ◽  
pp. 146-157
Author(s):  
Liani Surya Rakasiwi
Keyword(s):  
Socioeconomic Status ◽  
Health Status ◽  
Low Income ◽  
The Other ◽  
Individual Health ◽  
Indonesia Family Life Survey ◽  
Individual Health Status ◽  
The Individual ◽  
Logit Regression Model ◽  
The Impact

This study analyzed the impact of demography and socioeconomic status on individual health status in Indonesia. The data used Indonesia Family Life Survey 5 (IFLS 5). The study use logit regression model for analysis with health status variable as dependent variable. The other variable such as demography and socioeconomic status as independent variables. Socioeconomic status seen from two measures, namely education and income. The result of this study concludes the demography influence significantly on individual health status in Indonesia. Individual who lives in urban area has higher probability of being health by 1,02 percent compared to individual who lives in rural area. The other variable like socioeconomic status also influences significantly on the individual health status in Indonesia. Individual with longer years of education has higher probability of being health by 3,07 percent compared to individual with less years of education. Individual with high income has higher probability of being health compared to individual with low income.

scholarly journals The Influence of Regional Social Inequality and Labour Market Characteristics on Health

2013 ◽  
Vol 38 (3) ◽  
Author(s):  
Christiane Gross ◽  
Peter Kriwy
Keyword(s):  
Health Status ◽  
Unemployment Rate ◽  
Multilevel Models ◽  
Educational Inequality ◽  
Panel Study ◽  
Regional Unemployment ◽  
Individual Health ◽  
Individual Health Status ◽  
Regional Unemployment Rate ◽  
The Individual

The influence of contextual factors on individual health status has been demonstrated by a number of studies even when controlling for the individual socio-economic situation (and other relevant factors). The article examines whether and to what extent variables of the place of residence have an effect on individual health status. We do not only refer to income levels and inequality, but also to effects of the educational level and inequality and the regional unemployment rate. As data basis for the individual level, we use the 2006 wave of the German Socio-Economic Panel Study (SOEP) and add regional information on the aggregate level based on the regional units (Raumordnungsregionen) of the Microcensus of 2005. These data will be analysed using multilevel models. The results reveal that regional educational inequality intensifies the individual educational effect, whereby members of less-educated groups in educationally disparate regions exhibit particularly low health chances. In addition, a high regional unemployment rate intensifies the negative effect of individual unemployment on men’s health.

scholarly journals Are socio-economic inequalities in breast cancer survival explained by peri-diagnostic factors?

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Laura M. Woods ◽  
Bernard Rachet ◽  
Melanie Morris ◽  
Krishnan Bhaskaran ◽  
Michel P. Coleman
Keyword(s):  
Breast Cancer ◽  
Primary Care ◽  
Health Status ◽  
Cancer Survival ◽  
Breast Surgery ◽  
Clinical Practice Research Datalink ◽  
Net Survival ◽  
Individual Health ◽  
Individual Health Status ◽  
Economic Inequalities

Abstract Background Patients living in more deprived localities have lower cancer survival in England, but the role of individual health status at diagnosis and the utilisation of primary health care in explaining these differentials has not been widely considered. We set out to evaluate whether pre-existing individual health status at diagnosis and primary care consultation history (peri-diagnostic factors) could explain socio-economic differentials in survival amongst women diagnosed with breast cancer. Methods We conducted a retrospective cohort study of women aged 15–99 years diagnosed in England using linked routine data. Ecologically-derived measures of income deprivation were combined with individually-linked data from the English National Cancer Registry, Clinical Practice Research Datalink (CPRD) and Hospital Episodes Statistics (HES) databases. Smoking status, alcohol consumption, BMI, comorbidity, and consultation histories were derived for all patients. Time to breast surgery was derived for women diagnosed after 2005. We estimated net survival and modelled the excess hazard ratio of breast cancer death using flexible parametric models. We accounted for missing data using multiple imputation. Results Net survival was lower amongst more deprived women, with a single unit increase in deprivation quintile inferring a 4.4% (95% CI 1.4–8.8) increase in excess mortality. Peri-diagnostic co-variables varied by deprivation but did not explain the differentials in multivariable analyses. Conclusions These data show that socio-economic inequalities in survival cannot be explained by consultation history or by pre-existing individual health status, as measured in primary care. Differentials in the effectiveness of treatment, beyond those measuring the inclusion of breast surgery and the timing of surgery, should be considered as part of the wider effort to reduce inequalities in premature mortality.

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