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William Thomas
William Thomas

Cb Sachdeva Class 12 Macroeconomics Pdf 44 ((TOP))

Disparities in the prevalence of child stunting between the richest and poorest households are observed in all regions and subregions with available estimates (Figure 15). The differences at the regional level in Africa and Asia mask large variances seen at the subregional level. For example, children from the poorest households in Central Asia have significantly lower stunting prevalence than those from the richest households in Southern Asia. Southern Asia is also the only subregion where more than half of the children from the poorest wealth quintile are stunted. The poorest in Northern Africa have a prevalence which is only 1.4 times higher than the richest, the smallest relative difference of all subregions in the world. Western Africa, on the other hand, is the only subregion where the gap in prevalence of stunting between the poorest and richest surpasses 30 percentage points. While the absolute difference between richest and poorest in Latin America and the Caribbean is the smallest of all regions, the relative difference is the largest, with children from the richest households classified as having a low stunting prevalence and those in the poorest households as having a high stunting prevalence in terms of severity level. This suggests the need for intensified efforts to address inequities even in this region where stunting reduction as a whole may no longer be considered a pressing issue.

Cb Sachdeva Class 12 Macroeconomics Pdf 44

An added issue which hampers comparability of dietary estimates and recommendations from different studies and countries is the use of different food group classifications and the total number of food groups used. Classification of foods into food groups can be done based on different aspects, such as the nutritional profiles of foods (e.g. protein-rich), purpose of the analysis (e.g. identify vitamin A and iron-rich foods), and botanical definition and their common use (e.g. tomatoes and eggplants are consumed as vegetables, but botanically they are fruits). Furthermore, imposing a classification on already existing data is circumscribed by the granularity of the data. For example, it is not possible to identify highly processed foods high in fats, sugars and/or salt using Food Balance Sheets or Supply and Utilization Accounts data. The remainder of this section and Part 2 present various analyses which rely on slightly different food groupings. Nevertheless, each analysis is based on a relevant food group classification according to the study purpose and the type of data used.

e Geographical regions were defined according to the United Nations Standard Country or Area Codes for Statistical Use (M49 standard) classification,131 while countries were classified into four country income groups (high-income countries, upper-middle-income countries, lower-middle-income countries and low-income countries) using the World Bank classification for the 2020 year.132

The analysis presented below expands on previous studies by considering cross-country comparable measures of food insecurity that are calibrated against the global FIES scale. It explores dietary patterns according to levels of food insecurity based on the analysis of food security and food consumption data from two lower-middle-income countries, Kenya and Sudan, and two upper-middle-income countries, Mexico and Samoa.g Population average estimates of usual consumption for 11 food groups and of total dietary energy are computed for each food insecurity class. The food groupings were defined on the basis of their nutritional relevance following the classifications used in the FAO/WHO GIFT,89 with some exceptions. Only statistically significant results are reported.h

Minimum dietary energy requirement (MDER): Human energy requirements for an individual in a given sex/age class are determined on the basis of normative requirements for basic metabolic rate (BMR) per kilogram of body mass, multiplied by the ideal weights that a healthy person of that sex/age class may have, given his or her height, and then multiplied by a coefficient of physical activity level (PAL) to take into account physical Given that both healthy BMIs and PALs vary among active and healthy individuals of the same sex and age, a range of energy requirements applies to each sex and age group of the population. The MDER for the average individual in the population, which is the parameter used in the PoU formula, is obtained as the weighted average of the lower bounds of the energy requirement ranges for each sex and age group, using the shares of the population in each sex and age group as weights.

Using sophisticated statistical techniques based on the Rasch measurement model, the information obtained in a survey is validated for internal consistency and converted into a quantitative measure along a scale of severity, ranging from low to high. Based on their responses to the FIES-SM items, the individuals or households interviewed in a nationally representative survey of the population are assigned a probability to be in one of three classes: food secure or only marginally insecure, moderately food insecure and severely food insecure as defined by two globally set thresholds. Based on FIES data collected over three years from 2014 to 2016, FAO has established the FIES reference scale, which is used as the global standard for experience-based food-insecurity measures, and to set the two reference thresholds of severity.

SDG Indicator 2.1.2 is obtained as the cumulated probability to be in the two classes of moderate and severe food insecurity. A separate indicator (FIsev) is computed by considering only the severe food-insecurity class.

General method for assessment of progress against the targets: For all targets except wasting, the assessment of progress is done using an Average Annual Rate of Reduction (AARR).aw First an AARR for the current trend is calculated using estimates from the UN databases which provides an assessment of the rate of progress being made between the baseline year and most recent estimate. The AARR required to reach the target is then calculated using the baseline (2012) estimate from the UN databases and the target. The current AARR is then compared to the required AARR using cut-offs presented in Table A2.1 to classify each subregion or region into their corresponding progress assessment category.

Nevertheless, bearing in mind the caveats outlined above, it is nonetheless possible to use SUA and FBS data to show trends in food available for consumption at the global level, or aggregating countries into regions or by country income group. The advantage of using SUA instead of FBS data is that it gives the user the possibility of classifying the various food items into food groups of choice.

The classification of SUA items into food groups for this analysis differs slightly from the FBS classification, particularly for the following subgroups: (1) plantains, in the FBS classification, are grouped together with fruits, whereas in this analysis, plantains have been grouped together with roots and tubers; (2) fruit juices (100 percent, nectars and concentrate), in the FBS classification, are grouped together with fruits, whereas in this analysis, fruit juices have been classified as beverages; (3) vegetable juices (100 percent, nectars and concentrate), in the FBS classification, are grouped together with vegetables, whereas in this analysis, they have been classified as beverages; (4) soybean and soy-based products, in the FBS classification, are grouped as oil crops, whereas in this analysis, they were grouped with pulses, seeds and nuts.

The contribution of all 13 food groups (cereals; fruits; vegetables; roots, tubers and plantains; pulses, seeds and nuts; meat; eggs; fish and shellfish; dairy products; fats and oils; sugars and sweeteners; beverages; and others) to the total food available and to the dietary energy availability in 2017 are also presented, by country income classification. Estimates are presented (combined into 7 food groups) as food group contribution (percent) to total food available, and food group contribution (percent) to total dietary energy available.

Countries were classified by income level (high-income countries, upper-middle-income countries, lower-middle-income countries and low-income countries) using the World Bank classifications for the 2020 year.28

The average consumption of selected food groups was estimated in daily grams per capita. Foods were classified into 19 groups on the basis of their nutritional relevance following the criteria used in the FAO/WHO Global Individual Food consumption data Tool (GIFT),25 with a few exceptions to cater for the nature of household consumption data. For these analyses, we considered 11 (cereals; roots, tubers, plantains; pulses, seeds and nuts; dairy products; eggs; fish and shellfish; meat; fruits; vegetables; fats and oils; and sweeteners and sugars) out of the 19 food groups. All estimates represent edible quantities.

Economics is a division of social science, which studies the way to use scarce resources to produce valuable commodities and distribute them among different sections of society. It is among the choicest subjects for those willing to opt for Commerce or Humanities in class 12th. The most sought outboard of examination in India, Central Board of Secondary Education (CBSE) provides a very comprehensive syllabus of Economics class 11 by providing a basic understanding of the need and general economic terms. In this blog, we will bring light on the modules covered in the syllabus of Economics class 11th.

Meaning of microeconomics and macroeconomics; positive and normative economics What is an economy? Central problems of an economy: what, how and for whom to produce; concepts of production possibility frontier and opportunity cost. 350c69d7ab

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