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Early childhood stunting and later life outcomes: A longitudinal analysis

Deshpande A, Ramachandran R

Econ Hum Biol, 2022 Jan;44:101099.
PMID: 34933274 DOI: 10.1016/j.ehb.2021.101099

Using longitudinal data from four countries-Ethiopia, India, Peru and Vietnam- we show that early childhood stunting is highly persistent as measured by the association between stunting status in early childhood and stunting status at age 15. Stunting in early childhood is associated with lower grade completion by age 22 and has a negative relationship with cognition as measured by math, language and reading scores at ages 8, 12 and 15. Stunting in early childhood is also associated with poorer subjective assessment of a child's health at age 15. Analyzing determinants, we show that lack of preventive care and economic shocks are associated with an increase in the probability of stunting in early childhood.
Fulltext Reliability of odontometric parameters in stature analysis

Ramya K, Deshpande A, Deepika ADN, Rayudu GS, Pendyala SK, Kondreddy K

J Oral Maxillofac Pathol, 2021 05 14;25(1):189-192.
PMID: 34349434 DOI: 10.4103/jomfp.jomfp_17_21

Background: To emphasize the role of odontometric parameters which may be used as a reliable forensic tool especially in cases with partial remains of the individual.
Aim: To assess the reliability of odontometric parameters in stature analysis.
Materials and Methods: The study was conducted on 100 patients (50 male and 50 Female). Mesiodistal width of anterior teeth, inter-canine width, Inter-premolar width and maxillary arch length were the parameters included. The results were tabulated with a linear regression formula obtained for each parameter.
Statistical Analysis: The data collected was statistically analysed using SPSS version 20 and a linear regression formula was obtained thereafter.
Results: Mesio-distal widths of individual maxillary canines, total mesiodistal width of maxillary anteriors and arch length showed a significant co-relation with stature. The combined linear regression formula was obtained for all parameters.
Conclusion: Odontometric parameters of mesio - distal widths of individual maxillary canines, total mesiodistal width of maxillary anteriors and arch length can be used as reliable parameters for stature analysis.
Fulltext Estimating the global economic benefits of physically active populations over 30 years (2020-2050)

Hafner M, Yerushalmi E, Stepanek M, Phillips W, Pollard J, Deshpande A, et al.

Br J Sports Med, 2020 Dec;54(24):1482-1487.
PMID: 33239354 DOI: 10.1136/bjsports-2020-102590

OBJECTIVES: We assess the potential benefits of increased physical activity for the global economy for 23 countries and the rest of the world from 2020 to 2050. The main factors taken into account in the economic assessment are excess mortality and lower productivity.
METHODS: This study links three methodologies. First, we estimate the association between physical inactivity and workplace productivity using multivariable regression models with proprietary data on 120 143 individuals in the UK and six Asian countries (Australia, Malaysia, Hong Kong, Thailand, Singapore and Sri Lanka). Second, we analyse the association between physical activity and mortality risk through a meta-regression analysis with data from 74 prior studies with global coverage. Finally, the estimated effects are combined in a computable general equilibrium macroeconomic model to project the economic benefits of physical activity over time.
RESULTS: Doing at least 150 min of moderate-intensity physical activity per week, as per lower limit of the range recommended by the 2020 WHO guidelines, would lead to an increase in global gross domestic product (GDP) of 0.15%-0.24% per year by 2050, worth up to US$314-446 billion per year and US$6.0-8.6 trillion cumulatively over the 30-year projection horizon (in 2019 prices). The results vary by country due to differences in baseline levels of physical activity and GDP per capita.
CONCLUSIONS: Increasing physical activity in the population would lead to reduction in working-age mortality and morbidity and an increase in productivity, particularly through lower presenteeism, leading to substantial economic gains for the global economy.
Machine learning for cognitive behavioral analysis: datasets, methods, paradigms, and research directions

Bhatt P, Sethi A, Tasgaonkar V, Shroff J, Pendharkar I, Desai A, et al.

Brain Inform, 2023 Jul 31;10(1):18.
PMID: 37524933 DOI: 10.1186/s40708-023-00196-6

Human behaviour reflects cognitive abilities. Human cognition is fundamentally linked to the different experiences or characteristics of consciousness/emotions, such as joy, grief, anger, etc., which assists in effective communication with others. Detection and differentiation between thoughts, feelings, and behaviours are paramount in learning to control our emotions and respond more effectively in stressful circumstances. The ability to perceive, analyse, process, interpret, remember, and retrieve information while making judgments to respond correctly is referred to as Cognitive Behavior. After making a significant mark in emotion analysis, deception detection is one of the key areas to connect human behaviour, mainly in the forensic domain. Detection of lies, deception, malicious intent, abnormal behaviour, emotions, stress, etc., have significant roles in advanced stages of behavioral science. Artificial Intelligence and Machine learning (AI/ML) has helped a great deal in pattern recognition, data extraction and analysis, and interpretations. The goal of using AI and ML in behavioral sciences is to infer human behaviour, mainly for mental health or forensic investigations. The presented work provides an extensive review of the research on cognitive behaviour analysis. A parametric study is presented based on different physical characteristics, emotional behaviours, data collection sensing mechanisms, unimodal and multimodal datasets, modelling AI/ML methods, challenges, and future research directions.
Fulltext Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

Burstein R, Henry NJ, Collison ML, Marczak LB, Sligar A, Watson S, et al.

Nature, 2019 Oct;574(7778):353-358.
PMID: 31619795 DOI: 10.1038/s41586-019-1545-0

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2-to end preventable child deaths by 2030-we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000-2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations.