Declining Patterns of Average Height of Adult Indians Between 20 and 49 Years: State Wise Trends and Influence of Socioeconomic Factors

Abstract

In the present study, changes in the average height over ages among women and men have been studied through third round National Family Health Survey data. It is also aimed to study the extent of influence of the different socioeconomic variables on such changes. The sample sizes for female and male are 94,417 and 52,460, respectively. For this study, only adult male and female data and the age ranges 20–49 years have been considered. During the 30 years span, the data set has been divided into three consecutive time periods with 10 years span for each period like (20–29), (30–39) and (40–49) years. Height has been considered as the dependent variable. The background explanatory variables are type of places, educational attainment, religion, ethnicity, occupational categories and wealth index of the families. The study shows that negative changes occur in the heights over the successive age-groups for men and women separately. The changes are found to be negative in all the zones and most of the states in India though it varies in its intensities. It is also an interesting feature to note that the maximum of absolute growth occurs among the men and women in urban areas, among the richest families, higher educated persons and professionals, while it is not so pronounced among the manual labourers, and scheduled tribes. Is it because of the changing lifestyles of most of the urban families and some of the rural families?

Appendix

Data Type

Unit level data as obtained from the third National Family Health Survey (NFHS – III) conducted by the International Institute for Population Sciences (IIPS), Mumbai, in 2005–2006.

Sample Size

The sample sizes consist of 94,417 women and 52,460 men in the age-group 20–49 years. IIPS collected unit level data on reproductive aged men of age (15–54) years and women of age (15–49) years from 29 states in India. However, to maintain parity we have taken age range of (15–49) years for both males and females

Time span for total and consecutive period for Decadal changes: 20–49 years with three consecutive time span like (20–29), (30–39) and (40–49) years.

The Variables Considered in the Paper

All the variables, except height, are grouped into categories. (For regression analysis the variables are treated in a different manner.)

• Height: The height is measured in centimetres.

• Age: (1) 20–29 years, (2) 30–39 years and (3) 40–49 years.

• Place of residence: (1) Rural and (2) Urban areas.

• Educational level: (1) Illiterate (those who can neither read nor write), (2) Primary level (literate up to class IV standard), (3) Middle level (Class V to class X standard) and (iv) High school & above (class XI and above).

• Religion: (1) Hindu (2) Muslim (3) Christian and (4) Others,

• Ethnicity: (1) Scheduled Castes (SC) (2) Scheduled Tribes (ST), (3) Other Backward Categories (OBC) and (4) Others.

• Occupations: (1) Not working; (2) Professionals, managers and technicians, (3) Service or sales (4) Agriculture related works and (5) Skilled, unskilled or manual labourers, and

• Wealth index of the families: (1) Poorest (2) poorer (3) Middle (4) Higher and (5) Highest. The details of how wealth index is classified into these categories are given in the main text.

The Variables Taken in the Linear Regression Analysis

The dependent variable is Height. All the independent variables, except age, are taken as binary variables where ‘0’ is the base category and the rest of the categories are grouped and given the value ‘1’. Age is taken in years. We shall mention only the base categories below:

• Place of residence: Rural;

• Educational level: Primary level or less, i.e., Illiterate or literate up to class IV standard;

• Religion: Hindu or Muslim;

• Ethnicity: SC, ST or OBC;

• Occupations: ‘Service or sales’, ‘Agriculture related works or Skilled’, ‘Unskilled or manual laborers’, i.e., Other than not working, professionals, technicians or managers; and

• Wealth index of the families: Poorest, poorer or Middle income persons.

• Age: Age is taken in years. It should be mentioned here that the regression analyses were performed separately for each group of (1) 20–29 years, (2) 30–39 years and (3) 40–49 years. Thus for the group 20–29 years, say, the age as an explanatory variable takes values from 20 to 29 years.