Maasai fertility: Kenya-Tanzania comparisons Impacts of land-use policy on environment, wildlife, demography and socio-economic indicators in east African savannas: the Serengeti Ecological Unit University College London Kenya Wildlife Service University of Dar Es Salaam Catholic University of Louvain European Union [Grant No. IC18-CT ]; Parkes Foundation

“Everyone “knows” the Maasai” (Spear, 1993:1) Ethnographic writing/ Filming Colonial records Tourism Photography Conservation

Sum of demographic knowledge... AuthorMethodInformation Philip (1930) ?Average parity 3.4 births per woman McKay (1950) ?Average parity 3.2 births per woman Jacobs (1973) GuessAverage parity 8 births per woman Kramer (1980) ?Mean age at first marriage = 16.6yrs (f) de Vries (1984) ?IMR “probably falls between / 00 and the 1910 figure of / 00 ” Nangawe (1985) ?IMR / 00 Megan (1994) ?IMR / 00

Extent of “Maasailand”

Campbell (1979) “population growth rate of the Maasai is 2.2%…this is an estimate made by […] who has spent many years studying health- related issues in Maasailand”

Data collection Single Round Demographic Survey Sampling frames  Unavailable/ out of date Sampling strategy  Availability Research instrument  Pre-tested questionnaire Enumeration unit  Household Enumerators  Locally recruited Maasai Sample size  14,928 individuals 1,565 households 2,828 women aged 15-49

Map of study sites

Issues of data collection Enumerators Reference to death Age Counting Paternity El Niño No widowers Birth history

Adult female mortality Widowhood question: “Is your first wife still alive?”XXX Orphanhood question: “Is your biological mother alive?” 

Widowhood data

Maternal Orphanhood Data

Maternal Mortality Maternal death = misdemeanour Based on reports of adult sisters Lifetime risk = 1 in 40 1 in 4 of all reported adult sister deaths was due to maternal causes Pregnancy behaviour

Adult male mortality Widowhood question: “Is your first husband still alive?”  Orphanhood question: “Is your biological father alive?”XXX

Widowhood data

Male life expectancy at birth MaasaiNational Kenya Tanzania

Early age mortality - expectations RaiseLower Nutritional stressPopulation density Healthcare Living environment

Early age mortality 1 q 04 q 1 Kenya1738 Tanzania1739 (per 1,000 live births)

Sexual initiation

Children represent For men Power and influence (political and social) “How can a man without children advise others as to how best to command others?” “The status of an elder ultimately hinges on the fertility of his wives” For women Access to livestock Security in widowhood

Fertility data Collected from all ever-married women “Brass” questions on ceb-cs Births in the last 12 months

Data Quality: Cumulative asfr v. mean reported parity

Mean reported parity

TFR (p/f ratio) by location

TFR in national contexts MaasaiNational Rural Kenya Tanzania6.46.3

Kenya-Tanzania fertility differential nuptiality* lactational amenorrhea sterility* abortion contraception fecundability abstinence

Female age at first marriage KenyaTanzania Median SMAM

Current female marital status Kenya Tanzania

Sterility “It is said…that…the Masai females are becoming increasingly sterile” (1902) “Sterility before marriage and after miscarriage has resulted in a greatly decreased birth rate” (1930) “Healthworkers hold that venereal diseases are rampant in the Maasai communities” (1999)

Sterility Primary sterility Kenya2.9% Tanzania1.8% Secondary sterility Up to age 44 higher levels in Tanzanian Maasai than Kenyan Maasai

Age specific secondary sterility rates, by country

Kenya fertility

Kenyan fertility differentials NarokKajiado Land tenureSub-divisionCommunal Grp. R, Outside interest(s)TourismExtremely limited Wheat farming Land grabbing Agri. PotentialHigh and risingVery restricted Circumcised sonsVery advantageousUnchanged Ecol. sustainabilityFallingUnchanged

Natural Increase (% p.a.) KenyaTanzaniaBoth National Maasai (Census)4.46n/a- Maasai (Survey)--3.9