Understanding ageing in Africa through disability statistics - - PDF document

Extended abstract for 2017 International Population Conference (version of 15 December 2016) 1

Understanding ageing in Africa through disability statistics available in 19 Sub-Saharan African censuses Comprendre la vieillessement en Afrique à travers les statistiques du handicap en 19 recensements des pays africains sub- sahariennes

Reiko Hayashi (National Institute of Population and Social Security Research, Japan) Introduction The strong population growth in Sub-Saharan Africa brings also the increase of number of

• elderly. While the proportion of the elderly aged more than 60 years old in Sub-Saharan Africa remains

low, 4.8% in 2015 (compared to 12.3% of the world as a whole) and projected to increase only to 7.6% in 2050 (21.5% in the world), the number of elderly will almost double in only 20 years from 2015 to 2035, which is the same speed as in Asia or Latin America, according to the data estimated by the United Nations. Increasing number of elderly raises demand for health and long-term care in Africa, where the supply is limited in volume and scope of services. A sound evidence on the status of health

• f the elderly is needed more than ever in the era of Universal Health Coverage.

The data on health status of African population is increasing, but most of the sample surveys, notably DHS or MICS, are focusing on children and women of reproductive age. Although the increasing attention is paid to Civil Registration and Vital Statistics, the coverage is not enough so as to produce usable vital statistics. On the contrary, through the support of international community, the decennial censuses are increasing its coverage and as the question on disability is designated as a core topic of census recommended by the United Nations, many Sub-Saharan countries included disability in their census questionnaire. Moreover, many countries offer census microdata to the census microdata repository IPUMS at Minnesota Population Center. Hence, the disability statistics produced by censuses and made public as microdata is one of the few data source which reveal the status of health and functioning in Sub-Saharan Africa. This paper aims to describe the status of disability through comparative analysis. Data Among the 56 countries’ census data containing disability question available in IPUMS, 19 countries are of Sub-Saharan Africa. 8 countries (Burkina Faso, Ethiopia, Mali, Mozambique, Senegal, South Africa, Uganda, Zambia) offer multiple years of censuses which span maximum 23 years (Ethiopia in 1984, 1995 and 2007). The single year census data of Cameroon, Ghana, Kenya, Liberia, Malawi, Rwanda, Sierra Leone, South Sudan, Sudan and Tanzania are of the decade of 2000 and Guinea census data of 1996 is also available. The disability question type differs by country and by

Extended abstract for 2017 International Population Conference (version of 15 December 2016) 2 period but roughly classified as three types; those which use the term “disability” or “handicap” explicitly, those which use filter question (“Do you have disability? if yes…”), and those which use the term “difficulty” instead of “disability” in line with the recommendation of Washington Group on Disability Statistics. The disability category asked can also be roughly classified as “seeing”, “hearing”, “speaking”, “physical”, “mental” and “(having difficulties in) selfcare”. The disability rate is defined as the proportion of persons who have at least one category of disability. The age-specific disability rate is calculated and compared by disability category, by year of census, by gender, by urban/rural residence. Disability rates The all age disability rate differs considerably among 19 Sub-Saharan African countries, ranging from Mali (0.7% in 2009) to South Sudan (5.1% in 2008). The common feature is that disability rates increase with age in all countries (Figure 1). Accordingly, there is a rather strong positive correlation between the proportion of elderly and disability rate (r=0.436) among 19 Sub- Saharan African countries but this correlation becomes stronger and significant among 35 countries of the world which hold disability data (r=0.735). The increase of disability rate by age is gradual starting from 30’s or 40’s of age, and it is difficult to set an objective “threshold” age such as 60 or 65 from which the disability rate rises. Among disability categories, “seeing” is the most frequent disability type in 8 countries, “physical” disability in 3 countries and in the remaining 8 countries, “seeing” and “physical” disability levels are close. In most countries, “seeing”, “hearing” and “physical” disability increases with age whereas “speaking” and “mental” disability does not. The disability of “hearing” and “speaking” often combined as one question and considered to be the same sort of disability but their age trend is quite different which suggests that hearing and speaking should not be mixed especially in the old ages. Rwanda’s “physical” disability rate is by far the largest compared to other disability categories and

• ther country’s “physical” disability rate. The high Rwandan disability rate is already noticed

(Ministry of Local Government, Rwanda, 2010) and it is well possible that the genocide in 1994 left many people with disability. Among 8 countries which have data on several time points, no consistent trend was observed. The age-specific disability rate of Burkina Faso, Ethiopia, Mali, South Africa tends to decrease in recent times, while that of Mozambique, Uganda and Zambia shows increase. Senegal disability rate does not change over the period from 1988 to 2002. Concerning gender difference of disability rate, all-age disability rate for female is generally (15 out of 19 countries) lower than that of male, a trend which is different from other parts of the world where disability rate is normally higher for women (and longer life expectancy). In most countries, middle aged, 20-39 years old disability rate is higher for men than women, but for older age category,

Extended abstract for 2017 International Population Conference (version of 15 December 2016) 3 there is no common gender propensity among countries. In all countries except Ethiopia, rural population exhibits higher disability rate compared to urban population. The reason of high urban disability rate in Ethiopia is not clear as provincial level desegregation and age-specific disability rate also shows the same trend. Disability free life expectancy The high level of disability can mean that the status of health is low, but in the same time, it can mean that people are living longer while having disability. Especially in case of the elderly population where the mortality level is high, the disability rate should be dealt with mortality rate to ascertain the interaction between the two. For this purpose, the disability-free life expectancy is calculated, using the disability rate obtained from census of 19 Sub-Saharan African countries as well as 16 countries

• f other regions. The life table functions are derived from the data of the United Nations Population

Division and Sullivan method was used for the calculation. The results are shown in Figure 2. Although there are countries with extremely high disability rate such as Puerto Rico, Dominican Republic, Sudan or South Sudan, and countries with extremely low disability rate such as Egypt or Indonesia, there is an overall tendency that the longer the life expectancy, the longer the disability-free life expectancy and the disability duration. The coefficient of correlation between the life expectancy and disability-free life expectancy is significantly high as r=0.930. The coefficient of correlation between the life expectancy and disability duration is less strong (r=0.604) but significant. The society

• f longer life expectancy is where longer disability duration is expected but in other words, people can

live longer with disability. Conclusion To realize the world which “leaves no one behind”, the Sustainable Development Goals (SDGs) urged countries to produce statistics disaggregated by the disability status, and through census, disability statistics is provided amply in many Sub-Saharan African countries. It is often difficult to compare between countries as the question type and population response differs. However, by

• bserving the difference within a country, by age, disability category, gender, type of residence

(urban/rural), the comparison exhibits some meaningful facts. In Sub-Saharan African context, disability rate increases with age, especially for seeing, hearing and physical disability, women are less disabled, and disability rate is higher in rural area. As longer life brings both longer disability-free and disability duration, the effort should be made both to avoid the disability and also to co-exist with disability.

Extended abstract for 2017 International Population Conference (version of 15 December 2016) 4 Figure 1 Age specific disability rate in 19 Sub-Saharan African countries Figure 2 Disability free life expectancy and disability duration 0% 10% 20% 30% 40% 50%

0 to 4 5 to 9 10 to 14 15 to 19 20 to 24 25 to 29 30 to 34 35 to 39 40 to 44 45 to 49 50 to 54 55 to 59 60 to 64 65 to 69 70 to 74 75 to 79 80+

Burkina Faso2006 Cameroon2005 Ethiopia2007 Ghana2010 Guinea1996 Kenya2009 Liberia2008 Malawi2008 Mali2009 Mozambique2007 Rwanda2002 Senegal2002 Sierra Leone2004 South Africa2011 South Sudan2008 Sudan2008 Tanzania2002 Uganda2002 Zambia2010

40.0 46.3 46.6 50.1 50.0 47.4 49.4 52.1 51.6 51.4 51.4 54.6 53.3 54.0 54.9 57.5 57.8 57.4 55.6 63.9 67.7 69.2 69.5 66.1 71.3 58.4 66.5 72.2 67.8 68.5 72.4 73.4 67.5 61.8 67.2 1.3 2.9 3.5 1.5 2.0 4.9 3.1 0.6 1.2 1.3 2.1 1.2 3.2 3.1 3.2 1.4 1.3 2.6 5.3 1.2 0.9 0.6 1.6 5.0 1.5 14.8 7.5 2.5 7.7 8.0 4.6 4.0 11.4 17.4 13.3 10 20 30 40 50 60 70 80 90 Sierra Leone2004 Uganda2002 Rwanda2002 Guinea1996 Mozambique2007 South Sudan2008 Malawi2008 Mali2009 Cameroon2005 Tanzania2002 Zambia2010 Burkina Faso2006 Kenya2009 South Africa2011 Liberia2008 Senegal2002 Ethiopia2007 Ghana2010 Sudan2008 Cambodia2008 Indonesia2010 Egypt2006 Bangladesh2011 El Salvador2007 Iran 2006 Dominican R.2010 Brazil2010 Viet Nam2009 Ecuador2010 Mexico2010 Uruguay2011 Panama2010 USA2010 Puerto Rico2005 Ireland2011

Years

Disability-free life expectancy Disability duration