•When 2009 and 2019 results are compared, a rather interesting conclusion is drawn.
•Sex ratios have remained consistent within the +or-2 per cent range in most of the counties, with an exception of Nairobi and Mombasa counties at positive five per cent.
The 2019 census results revealed that Kenya’s population had stretched by a near nine million mark, representing a 23.2 per cent growth rate in the last decade.
This was a significant reduction compared to the 35 per cent increase that was observed during the 1999 and 2009.
The 2019 census figures further showed as of the night of August24/25, women marginally outnumbered men. Putting this into context, there were 24.0147 million women and 23.5481 million men- a difference of 466,660 in favour of women.
In other words, there were 98 males for every 100 females. A rather new category to this binary sex indicator was the introduction of intersex, which stood at 1,524, representing 0.003 per cent of the total population, meaning three in every 100,000 people.
Of interest was that Kenyans picked this sex ratio and literally ran with it to all media platforms. A number of FM radio morning shows even introduced a comical aspect by encouraging men that an extra woman might be hanging around just for them. But is this really what the census results were telling us? I believe not.
Sex ratios are among the most basic of demographic parameters and provide an indication of the relative survival of females and males, and the future breeding potential of a population. There are three reasons the sex ratio of population differs and why it is rarely equal: One, differences in mortality rates and life expectancy for women and men - women, on average, live longer than men. Second, sex ratios at birth are never equal (50/50) and lastly, migration can also affect the sex ratio of the population.
Further analysis provides a rather interesting perspective. Ten of the 47 counties, from what used to be referred to as the northern frontier region, except Mombasa, have a higher male to female ratio. These are Garissa (120), Wajir (113.5), Marsabit (112.6), Lamu (112.2), Isiolo (108.6), Turkana (106.5) Taita Taveta (103.6), Samburu (102.1), Mombasa (102.0) and Baringo (101,8).
There are obvious similarities among these counties in terms of socioeconomic and cultural dimensions that can explain this result. Second, five counties were found to have equal sex ratios. These are Tana River (100.7), Mandera (100.6) Laikipia (100.1), Elgeyo Marakwet (100.1) and Narok (100.0).
An interesting result from the report is that eight of the counties with lowest sex ratios are all from western — Vihiga (92.6), Nyamira (92.5), Kakamega and Migori (92.4), Kisii (91.6), Busia (91.2), Homabay (91.1) and Siaya (90.4).
Potential reasons for this kind of a tilt need to be scrutinised to avoid speculations.
When 2009 and 2019 results are compared, a rather interesting conclusion is drawn. Sex ratios have remained consistent within the +or-2 per cent range in most of the counties, with an exception of Nairobi and Mombasa counties at positive five per cent. In Nairobi, the sex ratio declined from 104.7 to 99.5, meaning there were more men in 2009 than today. This requires further studies and explanations.
TRENDS IN POPULATION GROWTH
After the release of these results, politicians were among the first to complain, some suggesting the figures were different from the supposed numbers on the ground. For instance, West Pokot Governor John Lonyangapuo said more than 540 births are recorded every month at the Kapenguria Hospital, with over 60,000 recorded births every year in his county.
He emphasised that only half of the births are reported in hospitals. The proud mathematician appeared convincing. However, he did not tell us about deaths and migration events recorded in the same period.
Another vocal politician was Majority leader in the National Assembly and Garissa Township MP Aden Duale. He wanted the servers opened to establish the ‘real’ numbers. As an MP, he ought to have a better understanding of the Statistical Act No. 4 of 2006 (revised 2012), especially on data confidentiality.
Governors Wycliffe Wangamati (Bungoma) and Francis Kimemia (Nyandarua) were equally vocal and vowed to file complaints about the results. They said the results did not reflect the truth on the ground as there was no population growth indicated. Their concerns were that there was no way their respective counties could register minimum population growth for the last 10 years. Let me interrogate the data for them.
Between 1999-09, the population grew by 35 per cent. Between 2009-19, this growth rate reduced to 23.2 per cent, meaning there were fewer people compared to the expected trajectory based on the previous growth rate.
Further analysis shows about seven counties registered a population growth rate of over 40 per cent. These are Isiolo (87.0), Busia (83.1), Kajiado (62.6), Marsabit (57.9), Kiambu (48.9), Lamu (41.7) and Nairobi (40.1). On the other end, eight counties registered growth rates of below 10 per cent — Kisii (9.9), Nyeri (9.4), Turkana (8.4), Tharaka Nithi (7.6) Nyandarua (7.1), Vihiga (6.4), Bungoma (2.4) and Nyamira (1.2).
It may be necessary to explain why some counties experienced higher growth, while others had very marginal growth. Three aspects of demographic dimensions (births, deaths and migration) must be considered when interrogating this issue.
Policy analysts may need to cross-examine data from Isiolo county, which registered the highest growth rate. Are there pieces of evidence on these demographic parameters and what were the enabling factors? What were the reasons for a decline in population growth in, say, Bungoma and Nyamira counties? Could it be that migration and mortality defined elements that led to a paltry growth of say 39,636 people for Bungoma and 7,324 people for Nyamira in the 10-year period? These are some of the pertinent questions that demographers need to grapple from this census results.
As we wait for KNBS to produce analytical reports on different dimensions, my advice is for the county governments to engage demographers who will provide advice on population issues, trends and dynamics within the counties.
Caleb Ouma Ongong’a is a PhD Student at the Population Studies and Research Institute, University of Nairobi