The singulate mean age of marriage data reveals an overwhelming amount of details about any country! A thoughtful introspection of the data may highlight the dynamics of demographic structure and the intricacy of socio-economic conditions of a country. Let's explore.
The SMAM is the mean age at first marriage among persons who ever marry by a certain age limit, usually before the age of 50 years. It measures the average number of years lived as single or “never married” by a hypothetical cohort of individuals for which the proportions never married at each age are the same as those observed at a moment in time for a given population.
The mean age of marriage differs between male and female for the same country.
The mean age of marriage is lower for women as compared to that of men throughout the world. However, the gap between SMAM for male and female is not consistent among countries.
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In the following world map, counties are categorized into the 9 classes. A closer look reveals some prominent clusters of countries. At continent level, the most variation is found in Africa. The SMAM for countries like Algeria, Libya, Namibia is high for both male and female. In contrary, it is lower for both in central and eastern Africa. Countries in Western and Southern Africa the SMAM varies over boundary and gender. For most of the countries in Europe, especially in western and Northern Europe, the SMAM is comparatively on the higher side for both male and female. For large or populous countries like Russia, China, USA, most part of South America, the SMAM is more than 27 but below 32 years for male and more than 22 but less than 28 years for female. The SMAM is low for both the genders in India.
While there are some spatial clusters of countries having homogenous SMAM, the variations can be better explained using other socio-economic and demographic indicators. The level of human developemnt, expressed by HDI by United Nations, percentage of Urban Population in countries, the expected years of schooling and total fertility rate are among the most prominent indicators having close correlation with male and female SMAM. In general, countries having similar or very close values of these indicators have homogenous SMAM for male and female. If we plot the data into scatter plots using SMAM male on horizontal axis (x axis) and SMAM female on vertical axis (y axis) for groups of countries, varying degrees of correlation can be explained.
The human development index shows a close relation to singulate mean age of marriage of male and female in countries. In the following charts, it can be clearly seen that the higher the HDI value, higher is the SMAM for both male and female. However, it can also be seen that for less developed countries, the SMAM for female is comparatively lower than that of male.
Less Developed Countries
The percentage of urban population is considered as one of the most significant indicators for understanding the socio-economic setups and the standard of living. Once again, more urbanized the country is, higher is the SMAM of male and female.
More Than 70%
Between 40% to 70%
Less than 40%
It is one of the most commonly used quantitative variable used to measure the human development status of any country. As one might expect, the mean years of schooling exhibits positive correlation with SMAM for both male and female. It can be attributed to the fact that, people prefer get married only after completing their schooling or education, better education may provide better employability which may further attribute to higher SMAM.
More than 16
Between 12 to 16
Less Than 12
And finally the total fertility rate can also be used to group the countries according to male and female SMAM. However, a basic difference with other indicators is that, the TFR can be treated as a resulting factor of varying SMAM among countries. It can be said that, lower the SMAM especially for female, higher is the total fertility rate.
Less than 2
Between 2 to 4
More Than 4