Ghana Statistical Services.

 
Ghana Statistical Services.
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Table of Contents                                                 Page

CHAPTER ONE                                                              2
  INTRODUCTION                                                           2
    1.1 Background                                                       2
    1.2 Objectives                                                       4
    1.3 Global Trends in Ageing Populations                              4
    1.4 Madrid International Plan of Action                              5
    1.5 Global Strategy and Action Plan on Ageing and Health             5
    1.6 Ghana’s Position on the Global Strategy                          6
    1.7 Review of Policies on Ageing                                     7
    1.8 Review of Ghana’s National Policy on Ageing                      7
    1.9 National Social Protection Policies for Older People             8
    1.10 Understanding Ageing-Related Issues                             9
    1.11 Methodology for the Case Study                                  9
CHAPTER TWO                                                          11
  EVIDENCE OF EXISTING DATA                                          11
    2.0 Introduction                                                 11
    2.1 Study on Global Ageing and Adult Health (SAGE)               11
    2.2 Ghana Health Service Data                                    17
    2.3 Social Security and National Insurance Trust Data            19
    2.4 National Health Insurance Authority Data                     20
    2.5 Livelihood Empowerment Against Poverty (LEAP) Programme      22
    2.6 Ghana Living Standard Survey                                 24
    2.7 2010 Population and Housing Census Data                      26
CHAPTER THREE                                                        30
  ASSESSMENT OF EXISTING DATA                                        30
    Introduction                                                     30
CHAPTER FOUR                                                         32
  IMPROVING THE USE OF EXISTING DATA                                 32
    4.0 Introduction                                                 32
    4.1 Illustration of the Use of SAGE Data:                        32

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4.2 Illustration of the Use of NHIA Data                                        33
    4.3 Illustration of the Use of SSNIT Data                                       33
    4.4 Illustration of the Use of Census and GLSS6 Data                            33
CHAPTER FIVE                                                                        35
  ENCOURAGING THE USE OF DATA – IN THE FUTURE                                       35
CHAPTER SIX                                                                         36
  CONCLUSION AND RECOMMENDATIONS                                                    36
    6.0 Introduction                                                                36
    6.1 Strength of the Data                                                        36
    6.2 Recommendation – Strengthening Capacity for Data Collection and Collation   37
  Appendix A                                                                        39
    Contributors to Ghana's Case Study on Ageing                                    39
    Reviewers of Case Study                                                         39
  Appendix B                                                                        41
    Health Insurance Registration Data                                              42
  References                                                                        43

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CHAPTER ONE

                                        INTRODUCTION
1.1 Background
The population of older adults is increasing in all regions of the world although at a varying pace.
The global population of people aged 60 years and older has increased from 382 million in 1980
to 962 million in 2017 (United Nations, 2017). It is projected that the population of older adults
(60 years and older) will account for about one-fifth (22%) of the world population by 2050 (World
Health Organization, 2018). In the short term, it is estimated that globally the number of older
people aged 60 years and older will outnumber the number of children under five by 2020 (World
Health Organization, 2018).
The absolute and relative increase in the population of older adults has occurred at a varying pace
across different regions of the world. Population ageing is more advanced in countries such as
Japan (United Nations, 2015). While countries such as France have had nearly 150 years to adjust
to changes in the population structure as a result of ageing, developing countries such as India and
China will have just about 20 years to make the necessary adjustments (World Health
Organization, 2018). The World Health Organization estimates that “in 2050 80 % of older people
will be living in low-and middle-income countries”.
Although the African region is regarded as a youthful continent, the population of older persons
in the region is increasing. The population of older persons in sub-Saharan Africa has doubled
between 1990 and 2015, increasing from 23 million to 46 million (United Nations, 2016). It is
projected that sub-Saharan Africa will experience a fast growth in the population of older adults
(64%) over the next 15 years (United Nations, 2015) with a projected increase to 161 million by
2050 (United Nations, 2016). In spite of the rapid rate of population ageing in the sub-Saharan
African region as a whole, the extent of population ageing varies markedly from country to
country. While countries such as Mauritius have about 15 % of their population being older adults,
in Senegal, older adults constitute about 11 % of the population whereas countries such as Uganda
have less than 4 % of the total population being older adults (United Nations, 2016).
The population of Ghana, like other African countries has seen an increase in the absolute number
of older adults. Data from the 2010 Population and Housing Census indicates that the population
of older adults has increased about sevenfold; from 215,258 in 1960 to 1,643,978 in 2010 (National

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Population Council, 2014). It is projected that the population of older adults in Ghana will increase
to 2.3 million in 2025 and 5.6 million by 2050 (Ghana Statistical Service, 2014) as illustrated in
Table 1.

Table 1: Actual and projected population of older adults (60 years and older) in Ghana, 1960 -
2050

While on the one hand, the success of population ageing at the global, regional and national levels
can be attributed to increasing longevity, improvement in health and socio-economic conditions,
on the other hand, the increasing number of older adults presents challenges for the health and
social wellbeing of older adults especially in the sub-Saharan Africa region. Older adults in sub-
Saharan Africa face numerous social, economic and health challenges. For example, older adults
in many sub-Saharan African countries do not receive social pensions except in a few countries
such as South Africa. Additionally, health insurance coverage specifically for older adults is not
available in many African countries except Ghana and Senegal (Parmar et al., 2014; Pham, 2017).
Furthermore, Ghana has instituted the livelihood empowerment against poverty cash transfer
programme that targets households with older adults as eligible beneficiaries (Pham, 2017).
In spite of the implementation of the aforementioned social protection programmes for older adults
in Ghana, there has not been a holistic assessment of the situation of older adults in the country.

1.2 Objectives
This case study seeks to provide empirical evidence in support of identifying and improving
national efforts to build and strengthen local and sub-national data collection systems, establish
linkages across sectors, and promote co-production, analysis and use of data by a wide range of
stakeholders, including older adults themselves.

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1.3 Global Trends in Ageing Populations
In this current age, most people are expected to live beyond 60 years and by 2050, 1 in 5 people
will be 60 years or older (WHO, 2017). Although the growth in the population of older adults is
global in nature, it is more prominent in certain regions. Both developed and developing countries
populations are ageing, however, the growth is much more evident in developing countries.
Between 2000 and 2015, developing countries experienced over 60% growth in the population of
older people and the projected growth between 2015 and 2030 stands at 71%. For developed
countries, the growth in the population of older adults between 2000 and 2015 stood at 29% and it
is expected to grow by 26% between 2015 and 2030. In the sub-Saharan Africa region, the
population of older adults 60 years and older doubled between 1990 and 2015 – increasing from
23 million in 1990 to 46 million in 2015 (United Nations, 2016). The population of older adults
in sub-Saharan Africa is projected to further increase to 161 million in 2050. The World Health
Organization estimates that the projected number of older adults (60 years and older) in Africa in
2050 will constitute about 10% of the population of Africa.

1.4 Madrid International Plan of Action
The Madrid International Plan of Action on Ageing (MIPAA) is a United Nation (UN) document
on population ageing adopted at the Second World Health Assembly on Ageing in April 2002 to replace
the earlier Vienna International Plan of Action on Ageing. The MIPAA was adopted to guide global
policies on ageing for the current century. The main feature of the MIPAA was the society for all
ages concept and its thematic foundation. The first draft had two parts: the long-term strategy on
ageing, as the preamble to the draft Plan of Action; and the main body of the draft revised Plan.
The latter identified three priority directions for policy action: (i) sustaining development in an
ageing world; (ii) advancing health and well-being into old age; and (iii) ensuring enabling and
supportive environments for all ages.
The Madrid Action Plan was followed by the development of an African Union Policy framework
and Plan of Action on Ageing (AU/HAI, 2003). This is in sharp contrast with the period of the
first UN International Plan of Action on Aging. At the time, much of the continent was not aware
of the burgeoning demographic revolution (Apt, 2012).

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In Ghana, there is considerable interest in ageing. The government has responded to the issue with
germane policies and programmes to address ageing-related challenges. Firstly, Ghana has an
ageing policy dubbed “Ageing with Security and Dignity” that focuses on challenges spanning
housing, health, poverty, and gender dynamics of ageing in Ghana (Ministry of Employment and
Social Welfare, 2010). Other policies formulated to address the issue include the National Social
Protection Strategy (which includes the Livelihood Empowerment against Poverty (LEAP)),
Ghana National Disability and National Health Insurance Scheme (NHIS), albeit not solely
directed to older adults. Although Ghana has pockets of policies, initiatives and directions on
ageing, there is no harmonization of the various policies, strategies or interventions. Consequently,
the full potential of these policies and interventions for the health and wellbeing of older adults is
not being realized.

1.5 Global Strategy and Action Plan on Ageing and Health
Population ageing is a global phenomenon and all countries including low-and-middle income
countries are being entreated to ensure that the health and wellbeing of older adults is addressed
in national development plans. The Global Strategy and Action Plan on Ageing envisions “a world
in which everyone can live a long and healthy life” and the African Regional Framework on
Ageing also envisions a region “in which everyone can live a long, healthy and productive life”
(WHO, 2019). The African Regional framework aims to; by 2020, increase awareness and
accelerate actions for healthy ageing in the African Region and establish evidence and partnerships
necessary to support a Decade of Healthy Ageing from 2020 to 2030.
In line with the global and regional action plans aimed at ensuring healthy ageing, the government
of Ghana is committed to establishing frameworks for formulating structures geared toward the
promotion of;
   a. an age-friendly environment
   b. research-based policy initiatives
   c. enhanced engagement with the ageing community
   d. awareness creation on healthy ageing
   e. establishment of systems that align well with the context-specific needs of the older
        generation
   f.   enduring and sustainable care plans in the long term and

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g. efficient feedback loop through research, monitoring and evaluation.

1.6 Ghana’s Position on the Global Strategy
As the coordinating agency for Ghana on this “Healthy Ageing Case Study”, the Ghana Statistical
Service has adopted a multi-sectoral approach to understanding the phenomena of “Healthy
Ageing”. Stakeholders from Academia, Ministries, Departments and Agencies, Civil Society
Organizations and Representatives of donor-support agencies, were collectively involved in
developing the most reflective strategy that will ensure healthy ageing for all. The case study
seeks to take stock of where Ghana is in terms of the situation of older adults, where we want to
go with issues regarding older adults and how the intended goals and targets can be achieved.
Given the right resources and leverage, Ghana is committed to pursuing these strategies aimed at
addressing the needs of older adults. In the national effort to ensure “leaving-no-one-behind” in
the implementation of the SDGs and Ghana’s development framework, the multi-stakeholder team
is committed to drawing policy makers’ attention through publication of various ageing related
statistical products by 2021.

1.7 Review of Policies on Ageing
The change in demographics has implications for several sectors of the various world economies
and raises challenges for policy makers. Institutions such as the African Development Bank
(Governors Consultative Meeting, 2018) describe this situation as a “ticking time bomb” especially
for developing economies where policy formulation and implementation continues to lag behind.
Governments must therefore rise to the challenge and implement policies that will deal with the
situation of population ageing. These policies need to address every aspect of the lives and
wellbeing of older adults. Additionally, policies that address population ageing need to consider
the impacts of these policies on the larger policy framework of every country targeting areas such
as the social, economic, psychological and political dimensions of population ageing. Such a broad
policy outlook is important because population ageing is integral to national development.
The government of Ghana recognizes the importance of population ageing for national
development. Ghana has thus developed national policies and implemented social protection
programmes/projects that seek to cater for the needs of older adults. For instance, the 1992
Constitution of Ghana, the Ghana Shared Growth and Development Agenda 2010-2013, the

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National Population Policy (Revised Edition, 1994), the National Ageing Policy (2010), the
National Health Insurance Act 2003 (Act 650), and the National Social Protection Strategy all seek
to address the needs of older adults in Ghana. The enrolment of older adults 70 years and above
on the National Health Insurance Scheme and the provision of cash grants to poor households with
older adults under the Livelihood Empowerment Against Poverty (LEAP) programme are all
examples of the government of Ghana’s commitment towards ensuring the health and wellbeing
of older adults.

1.8 Review of Ghana’s National Policy on Ageing
Population policies are integral to efforts that influence people’s behaviours and demographic
trends (May, 2012). The population structure of any country is influenced by the three components
of demographic change, i.e. fertility, mortality and migration (both internal and international). The
interplay between these three components of population change has significant consequences for
present and future population structure and socio-economic development. For example, after
World War II, fertility and mortality were documented to be very high in developing countries and
it was realized that reducing fertility levels was essential to improving socio-economic
development (Kwankye & Cofie, 2015). This consequently led to the adoption of population
policies in some African countries. Ghana was the third country after Mauritius and Kenya to adopt
a comprehensive population policy titled “Population Planning for National Progress and
Prosperity in 1969 (Republic of Ghana, 1969). The population growth rate in Ghana between 1960
and 1970 was high at 2.4% per annum. The 1969 population policy thus aimed to reduce the
population growth rate. However, the implementation of the policy was met with failure as it did
not reduce fertility rates as expected. By the early 1990s, the country’s fertility rate had toppled
that of the previous rate, reaching almost 3% per annum. Some of the problems encountered in the
implementation of the policy included the pervasiveness of cultural beliefs about having many
children, lack of commitment from successive governments, overburdened health systems required
to provide family planning services, and neglect of men and rural-dwellers in the family planning
approach. Therefore, in 1994, the first population policy was replaced by the Revised Population
Policy. The revised policy and action plans were formulated within the context of economic growth
and sustainable development. It had fourteen goals, summarized into two overarching goals:

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i. a national population policy and programme are to be developed as organic parts of the social
     and economic planning and development and
  ii. Measures will be undertaken to improve the standards of living and quality of life of the
     people (Government of Ghana, 1994, p. 25).
The specific targets included the reduction of total fertility rate from 5.5 per woman to 5.0 by the
year 2000, 4.0 by 2010 and 3.0 by 2020. Additionally, it was projected that the use of
contraceptives will reach 15% by 2000, 28% in 2010 and 50% in 2020. So far there have been
some gains made: fertility and mortality have declined steadily.

1.9 National Social Protection Policies for Older People
Over the last two decades Ghana has implemented a number of social protection policies, some of
which target older adults in particular. An example is the social health insurance for older adults
implemented under the National Health Insurance Scheme (NHIS). Ghana’s NHIS grants a
premium exemption for older adults who are 70 years and older. The exemption allows older adults
to register for health insurance under the NHIS without having to pay a premium they are however,
required to pay registration and annual renewal fees.

Ghana also operates a national pension scheme which is currently being operated on a three-tier
pension system. It involves a voluntary and a non-voluntary component. The involuntary
component is the first and second tier while the voluntary component is the third tier. Formal
sectors workers are compulsorily enrolled on the tier I and tier II schemes while the tier III is which
is voluntary, is open to all. The totality of contributions for the pension scheme is 18.5% (5.5%
employee and 13% employer). Out of the total 18.5% contribution, 13.5% goes to tier I and 5%
goes tier II. The third tier is the voluntary scheme and is open to all.

1.10 Understanding Ageing-Related Issues
Globally, researchers who study ageing have used different research methods to understand the
phenomena. Such methods include cohort studies, randomized control trials and systematic
reviews and such research have been carried by experts in specific fields including anthropology,
gerontology, psychology, sociology, social work, public health and social policy. There has been
limited research on population ageing in Ghana and older people have been under-represented in
research, policy and discussions on national development discourse. Evidence from existing
research on population ageing gives indication of the use of two main research approaches to

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understanding ageing; qualitative and quantitative (Apt, 1993; 2016; Mba, 2010). These two
approaches are relevant to addressing the multifaceted needs of older people in Ghana. These
research approaches help to unearth and understand the social, mental, physical, psychological and
economic aspects of the ageing process. To a large extent, research on ageing is at a fledgling state
and researchers are progressing toward unravelling what may or may not work in Ghana. In line
with Olsen (2004), using qualitative and quantitative approaches together throws light on
seemingly new and developing social phenomena. Creswell (2009) mentions that quantitative data
in itself provides baseline information and offers researchers the opportunity to appreciate the
superficial statistical significance or otherwise of the data. On the other hand, the use of qualitative
data aids in understanding a particular phenomenon and offer clarifications for quantitative
findings.
In chapter two of this report, an attempt is made to highlight available data set in Ghana on Ageing.
The data sets are described by underscoring the agency from which data is gathered, the purpose,
age bracket of participants of interest, and the method utilized in sourcing respective data.

1.11 Methodology for the Case Study
A participatory approach was employed in developing this case study. Different stakeholders were
engaged in an inception meeting to develop the case study on data, evidence and information on
healthy ageing in Ghana. Subsequently, several meetings were held to better understand the
evidence available with each institution and develop a roadmap for the case study. The team
continued to engage both physically and virtually to complete the case study. Experts from WHO
Headquarters in Geneva and from the Ghana Office participated in the first engagement.
The following institutions were represented:
Ghana Statistical Service (GSS) - the lead institution
Ghana Health Service (GHS)
Ministry of Health (MoH)
National Population Council (NPC)
National Development Planning Commission (NDPC)
Ministry of Planning (MoP)
Ministry of Gender, Children and Social Protection (MoGCSP)
National Health Insurance Authority (NHIA)

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Department of Psychology, University of Ghana
Regional Institute for Population Studies, University of Ghana (RIPS)
Ministry of Local Government and Rural Development (MoLGRD)
Social Security and National Insurance Trust (SSNIT)
Ministry of Food and Agriculture (MoFA)
HelpAge Ghana
Rights and Responsibilities Initiatives, Ghana
University of Ghana Medical School. Department of Community Health
The Center for Ageing studies, University of Ghana

The Ghana Statistical Service provided secretarial support throughout the development of this
case study.

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CHAPTER TWO

                                EVIDENCE OF EXISTING DATA
2.0 Introduction
The importance of data, information and evidence to optimize healthy ageing cannot be over
emphasized. Person-centred information on determinants and levels of intrinsic capacities and
functional ability, disaggregated by geographic and socio-economic characteristics of the
population, including by age and sex groups, is needed to support action and inform policy and
decision making in multiple sectors and with multiple stakeholders.

This chapter explores what data sources are available and to what extent these data sources cover
issues of older adults in the country. Particularly, the chapter examines data from Ghana Health
Service (GHS), the WHO Study on Global Ageing and Adult Health (SAGE), the National Health
Insurance Authority (NHIA), the Social Security and National Insurance Trust (SSNIT), the Ghana
National Household Registry and Livelihood (GNHR), the Ghana Living Standards Survey
(GLSS) and the Population and Housing Census (PHC).

2.1 Study on Global Ageing and Adult Health (SAGE)
Background: The World Health Organization’s Study on Global Ageing and Adult Health
(SAGE) aims to address the gap in reliable data and scientific knowledge on ageing and health in
low and middle-income countries (Kowal et al., 2012). The study evolved from the 2003 World
Health Survey (WHS), otherwise known as wave 0, which was an organized effort of WHO, the
Ministries of Health of the various countries involved in the study and the University of Ghana
Medical School, through the Department of Community Health, in the case of Ghana. SAGE is a
longitudinal study with nationally representative samples of persons aged 50 years and above in
China, Ghana, India, Mexico, Russia and South Africa, with a smaller sample of adults aged 18–
49 years in each country for comparisons. Data collection instruments are compatible with other
large high-income country longitudinal studies on ageing. Wave 1 was conducted during 2007–
2010 and included a total of 34,124 respondents aged 50 years and older and 8,340 respondents
aged 18–49 years. In four countries, a subsample consisting of 8,160 respondents participated in
Wave 1 and the World Health Survey (SAGE Wave 0). Wave 2 data collection was conducted in
2012 and 2013, following up all Wave 1 respondents. Wave 2 data is however not publically

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available yet. Data collection for Wave 3 of SAGE is currently on-going. SAGE is committed to
the public release of study instruments, protocols and meta and micro-data: access is provided
upon completion of a user’s Agreement available through the WHO SAGE website
(www.who.int/healthinfo/systems/sage) and WHO’s archive using the National Data Archive
application: (http://apps.who.int/healthinfo/systems/surveydata). Data from waves 0 and 1 can be
accessed via the website on written request.

The SAGE study in Ghana was conducted a collaborative effort between WHO, the Ministry of
Health through the National Health Research and the Department of Community Health at the
University of Ghana Medical School.

The SAGE study in Ghana uses a longitudinal study design with cohorts derived from the world
health survey of 2003. The study has so far been implemented in 6 countries were national samples
have been drawn using probabilistic sampling techniques.
Study Population: In Ghana, all the 6000 households from the WHS made up of 20 households
from the 300 enumeration areas formed the primary sampling units (PSU)
Sampling Design: The sampling method used for SAGE Wave 1 was based on the design for the
world Health survey. It used a multistage sampling approach, in which the primary sampling units
(PSUs) were stratified by region and location (Rural/urban). Selection of the PSUs was based on
proportion allocation by size, with each Enumeration Area (EA) independently selected within
each stratum. In the WHS/SAGE Wave 0, a total of 6000 households were interviewed and
therefore 300 EAs were selected nationwide with twenty households randomly selected in each
EA using systematic sampling. The number of EAs per region was based on the population size of
the region. For SAGE Wave 1, a total of 5000 older adults (50 years and older) and 1000 young
adults (18–49 years) was required. As such 250 EAs out of the 298 EAs of the WHS/ SAGE Wave
0 were used based on the availability of respondents aged 50+ years within the EAs. Enumeration
areas with no 50+ individuals were excluded (WHO, 2007).
Within each EA, 20 households with one or more 50+ individuals and four households with
members aged 18–49 were selected. All respondents aged 50+ within households from the WHS
were automatically selected and additional households with members aged 50+ years were
randomly selected to make a total of 20 households for each EA. The four households of the 18–

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49 years age group were randomly selected from the WHS/SAGE Wave 0 households list per EA.
All the 50+ year olds within the selected households were interviewed together with the four
identified under-50 respondents. Field work and data entry were undertaken between May 2007
and June 2008. All data in tables are from this period, unless otherwise indicated.

Data Collection Technique: A total of 30 interviewers and supervisors were trained in two
phases. Initially, the full survey team was trained for 10 days centrally in Accra with support from
WHO Geneva. Three teams were subsequently formed and assigned to regions and then were
retrained in the field. Data collection was done manually during face-to-face interviews in
respondents’ homes. In urban areas, some respondents were contacted by telephone for re-contacts.
A team consisted of four interviewers and one supervisor assigned to one PSU. Each interviewer
was to complete interviews with two respondents per day, and was to approach households up to
three times to locate respondents. The supervisors conducted editing and also completed the blood
sample collection, blood pressure measurements and spirometry. Re-test interviews were to be
done within seven days. The location’s GPS data were taken in front of respondents’ houses with
a minimum of five satellites available to be accepted for readings to be accurate. These geo-data
could be used for future analysis (for example, distance to health care facilities, finding
respondents for the next round of data collection, finding respondents for validation studies/ sub-
studies). Completed questionnaires were organized and documented centrally before data entry.
Two centres were organized in Ghana for data entry and then the final product was transferred to
Geneva.
Table 1. Description of Households and Individual Questionnaires
 Questionnaire type               Domain                           Wave1 Measure
 Household                        Household        identification, Identification     and    contact
                                  contact and sampling details     details;      structure        of
                                                                   households,              dwelling
                                                                   characteristics,         improved
                                                                   water, sanitation and cooking
                                                                   facilities
                                  Transfers      and     support Family,        community       and
                                  networks                         Government assistance into

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and out of the household;
                                               informal       personal      care
                                               provision
             Assets,       income        and List of households assets,
             expenditure                       sources      and   amount      of
                                               household income; improved
                                               household      expenditure    on
                                               food, goods and services,
                                               health care
             Household care and health Persons in household needing
             insurance                         care;     mandatory          and
                                               voluntary health insurance
                                               coverage
Individual   Socio-demographic                 Sex, Age, Marital status,
             characteristics                   education,            Ethnicity,
                                               Religion, languages spoken,
                                               etc.
             Work history and Benefits         Length        of time worked,
                                               reason for not working, type
                                               of employment, mode of
                                               payment, hours worked and
                                               retirement
             Health status and descriptions
             Anthropometrics,
             performance        tests    and
             biomarkers
             Risk factors and preventive
             health behaviours.
             Chronic conditions and health
             services coverage.
             Health care utilization

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Social cohesion
                                  Subjective     wellbeing    and
                                  quality of life
                                  Impact of caregiving

Data Collection Tools: This involved questionnaires, health and biomarker measurements.
 Questionnaires: Six types of questionnaires were used in the SAGE study: The household
questionnaire, individual, proxy, proxy validation, re-test and mortality questionnaires. The
respondents were selected in advance and interviewers visited their homes for interviews and
measurements. A household questionnaire and individual questionnaire were administered to each
respondent. In following up households reporting death(s) in the past two years, a verbal
questionnaire was completed. If a respondent was found to be incapable of answering the
individual questionnaire, a proxy questionnaire was completed. Within a PSU, two respondents
were to be randomly selected for re-test and one for proxy validation. In all, each PSU was to have
20 completed interviews for 50+ years respondents (household and individual), four interviews for
the 18-49 years respondents, two re-test questionnaires, one proxy validation questionnaire and
verbal autopsy questionnaires where applicable. One of the 251 selected PSUs was not used. This
was because the EA which was expected to be located at Korle Bu Teaching hospital could not be
traced.
The household and individual questionnaires were translated into two dominant local languages
(Akan and Ga) and used for training. Back translations were also done before use. However, the
questionnaire used for the survey was printed in English. Interviewers were given appendices to
illustrate various items, response options and concepts. In addition, instruments for blood pressure,
height, weight, waist and hip measurements, spirometry, visual acuity (near and distance using
tum-bling E charts), and stopwatches (to time measured walk) were provided. Blood spots were
obtained via finger prick, labelled and stored for future analyses.
Health and Biomarker Measurements: In addition to self-reports on health and well-being,
direct health examination and biomarker measurements (blood samples, anthropometric
measurements and performance tests) were included in the survey.

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Ethics: Informed consent was obtained from each respondent for interviews, measurements and
blood samples.
Survey metrics and data quality: for Wave 0, were generated for all 70 participating countries,
including Ghana. Survey metrics for the new modules/questions in Wave 1 were generated, along
with an assessment of accuracy of age reporting and response rates as a measure of the
representativeness of the population of interest.
Strengths
This is the first longitudinal study on health and ageing in multiple low and middle-income
countries. The six surveys including that of Ghana have nationally representative samples yielding
results that are comparable to those of similar ageing surveys in high-income countries. Initial
response rates were fairly good. GPS coordinates have been taken from all households in order to
reduce problems of finding households.
The study is a collaboration between the WHO and a leading research institutions in the respective
countries, with variable levels of involvement of the national health authorities. In Ghana, the main
research institution involved in the study is the community health department of the University of
Ghana Medical School. The local research institution is particularly critical to the overall success
and strategic use of the results. The collection of a range of biological and clinical markers in
addition to a very comprehensive interview is an asset (He et al., 2007). The SAGE collaborations
with local health and demographic surveillance studies or systems provide an opportunity to link
non-fatal health outcomes data to information from demographic surveillance, such as risk factors,
mortality and migration, and track these populations over time. Data from these sites and systems
can be compared with SAGE national samples in China, Ghana, India and South Africa to assess
plausibility of findings, as well as to generate new hypotheses that can be more intensively studied
using surveillance field sites before incorporating these components into future rounds of SAGE
in national samples.
Weaknesses
The major weakness of the study is those related to the potential high attrition rates that often
characterize national longitudinal sample surveys.
Secondly, possible fatigue of the respondents. The duration of the interview was long (mean time
for Wave 1 was 2.5 hours), as multiple dimensions of health and well-being are measured, which
may be particularly demanding for both respondents and interviewers. This may affect the data

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quality, although no systematic problems have been detected so far. In several countries, urban
dwellers more often refused to participate in the survey, as is the case in other population surveys
internationally.
All countries in future waves of SAGE will use CAPI, which will improve efficiency in terms of
sample and data management. Information from earlier waves will be preloaded in the CAPI for
respondents who are being followed up and consistency checks will be carried out in future rounds.
Data Completeness
The SAGE data has a National representativeness based on the regional population and rural-
urban population sizes. There is also data on verbal autopsy for all deaths within 24 months in the
household. Other household data include household care and health insurance, assets, income and
expenditure as well as transfers and supports system.

2.2 Ghana Health Service Data
Background of Hosting Agency
The Ghana Health Service (GHS) is an autonomous Executive Agency responsible for
implementation of national policies under the control of the Minister for Health (MoH) through its
governing Council - the Ghana Health Service Council. It was established in 1996 through an Act
of Parliamentary (Act 525) and works in liaison with the Ministry of Health. MoH Operates a
decentralized system at five levels: National, Regional, District, Sub- District and Community.
GHS is authorized by MOH to collect, collate and report on all routine health services including
health service data from Mission, Private and Quasi-government health facilities everywhere in
the country.

Primary Data
All service delivery points generate essential routine service data on health service utilization,
morbidity and disease patterns. Such data are very useful to health managers at all levels for
planning, budgeting and decision-making. Routine service data also feed into the Health Sectors’
monitoring and evaluation system for analysis and dissemination of results. Thus helping to reflect
and judge performance, and highlighting weak areas for strengthening intervention programmes.
GHS Collaborated with the University of Oslo to develop a software called the District Health
Information Management System (DHIMSII). DHIMSII is a comprehensive HMIS solution for

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the reporting and analysis needs of district health administrations and health facilities at every
level. It provides a comprehensive HMIS solution based on data warehousing principles and a
modular structure which can easily be customized to the needs of different health systems -
national, regions, districts, and facilities. Data is collected mainly from people who visit the health
facility, as such does not include people who do not access health services. The data may not be
the representative of the entire population.

Secondary Data and Relevance
The DHIMS data is a comprehensive health data source with varied health conditions data of the
population from national, regional and sub-regional levels. Its crosscutting issues allows for
programmes and projects to be developed and implemented to address health challenges of people
at all levels. A Person-centred information on determinants of health of older adults can be easily
achieved with the DHIMSII data. The person centred variables include age, sex, diagnosis, cause
of death etc. The proportion of older adults by age can be generated based on total attendance to
health facilities for any given period. Additional information on occupation, religion, marital
status, place of residence can be obtained from the patients’ registers. However, there is no formal
documentation on the process of using data from the DHIMSII for programming or interventions
for older adults.
Method

The DHIMSII data is an online data system which allows authorized personnel to input directly
daily health data collected from health facilities. It is customized to replicate paper forms – to
simplify the process of data entry. DHIMSII is accessible in all districts and is being used by health
facilities and district health directorates to collect, collate, transmit and analyze routine health
service data The DHIMSII captures data on all persons who access services whether they are
insured or pay out of pocket. The GHS captures basic client/patient data, as well as data pertaining
to their symptoms, conditions, diagnoses etc. when they visit health facilities.

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2.3 Social Security and National Insurance Trust Data
Introduction
The Social Security and National Insurance Trust (SSNIT) or the Trust, is a statutory public Trust
charged with the administration of Ghana’s National Pension Scheme. The Trust is currently the
largest non-bank financial institution in the country.
The primary responsibility of the Scheme is to replace part of lost income due to Old Age (as a
result of retirement from active work), Invalidity, or loss of life. The Pension Scheme administered
by SSNIT has a registered membership of approximately one million, six hundred and twenty-five
thousand, two hundred and fifty-five (1,625, 255) with two hundred and fifteen thousand, eight
hundred and fifty (215,850) pensioners who currently collect their monthly pension from SSNIT.
These are made up both public and private formal sector works as well a few informal sector
workers.
The Social Security and National Insurance Trust or the Trust, was established in 1972 under the
NRCD 127 to administer the National Social Security Scheme. Prior to 1972, the Scheme was
administered jointly by the then Department of Pensions and the State Insurance Corporation from
1965. The Social Security Law (PNDC Law 247) under which the current Social Security Scheme
operates was passed in 1991. Until 1991, the Trust administered a provident fund, and was
converted into the Pension Scheme. In 2008, a new law which the National Pensions Act, Act 766
was promulgated which brought to being the Three Tier Pension Scheme that started operating in
2010 where SSNIT is mandated to manage only the First Tier.

The Core Functions of SSNIT
SSNIT performs a lot of functions but the core ones among them are those listed below:
•      Registration of employers and employees
•      Collection of Social Security Revenues
•      Managing records of members
•      Managing the funds of the Scheme
•      Processing and paying benefits to eligible members and declared nominees.

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The areas of interest for this exercise are the registration of employees and the management of
their records. In the registration of employees, the following information on the employees are
collected;
•      Name,
•      Date of birth
•      Place of birth
•      Date joined scheme or date one commenced working
•      Name of employer (establishment)
•      Salary at first point of employment
•      Parental details
•      Nominees (next of kin)
In managing the records, information such as Name, Employer, Salary and nominees can be
updated or changed while the rest cannot change, especially the date of birth. Additional
information which is collected throughout the working life of all members of the scheme and
managed as well, are the financial data. It must well be emphasized that though, the above
mentioned data are collected at the very beginning of the working life of a member, they are not
used in any way to monitor their conditions of life as they age. The essence of undertaking the
above mentioned set of activities is basically to collect contributions, manage the funds therein
and then pay benefits as and when they fall due (being Old Age, Invalidity of Death).
Another set of data that is collected usually at the tail end is when a pensioner dies. As a means of
verifying the death, the causes of death are also captured and recorded in the database as part of
the investigations conducted to confirm the death of a member of the scheme. This information is
actually not used for any particular agenda afterwards by SSNIT. At the moment the cause of
death data from SSNIT does not inform vital registration.

2.4 National Health Insurance Authority Data
Introduction
The National Health Insurance Scheme (NHIS) was established by an Act of Parliament in 2003
to provide financial risk protection against the cost of basic health care services. The Scheme is a
major social intervention policy of the government to ensure unhindered access to healthcare for
all residents especially the poor and vulnerable. The National Health Insurance Authority (NHIA)

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is the Agency responsible for the implementation of the NHIS. The objective of NHIA is to attain
Universal Health Coverage in relation to persons’ resident in the country and persons who are not
resident but who are on a visit to the country. As at 31st December 2019, about 12.3 million
Ghanaians, representing 41% of the population had enrolled onto the scheme. The NHIS also has
a network of over 4,500 credentialed healthcare providers across the country to improve
geographical access to healthcare by members.

Exemption Policy
As a major social intervention programme of the government of Ghana, the NHIS exempt over
60% of its members from payment of annual premium. Exempted members include children below
the age of 18 years, SSNIT Contributors, SSNIT Pensioners, older adults 70 years and above who
are not SSNIT contributors, pregnant women, and the indigent (core poor). Only informal sector
workers pay annual premium to the scheme.
Benefit Package
The NHIS benefit package covers about 95% of all disease conditions in Ghana. This include, Out
Patient Department, In – Patient Department, medicines on NHIS medicines list and investigations.
Other specialized services such as maternal care, dental cares and eye care are also covered. The
benefit is the same for all members irrespective of individual member’s contribution into the NHIS
fund.
Primary Data and Mandate
The NHIA is mandated to register and issue unique membership ID cards to members (including
the aged) to enable them access health care. Biometric data on individuals are collected by staff at
NHIA district offices before ID cards are issued.
Secondary Data
Data on health service utilization and claims are generated by credentialed Service Providers and
submitted to NHIA on monthly basis for vetting and payment. Claims data are submitted either
electronically or manually. Currently about 75% of claims are submitted and vetted manually
(partly because some health facilities do not have electronic systems) with the remaining 25% of
claims vetted electronically.

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Method
Membership data collected at the district offices go directly to a central database of the NHIA and
is managed by MIS Directorate of NHIA. Also, all claims are sent to NHIA Claims Processing
Centers in Accra, Kumasi, Cape Coast and Tamale for vetting and forwarded to Finance for
payment to credentialed providers. There are still some health facilities in Ashanti Region yet to
be consolidated to CPC Kumasi.

Limitations/Challenges with the Data
The NHIA captures data on persons who register with the scheme. The data therefore excludes the
aged who are not registered members of the scheme. Even though the scheme is free for older
adults 70+ years (they do not pay premium), a person needs to register by paying processing fees
to be part of it. In essence, the scheme does not have data on older persons who are not registered.

2.5 Livelihood Empowerment Against Poverty (LEAP) Programme
Background
The Livelihood Empowerment Against Poverty (LEAP) Programme is both a conditional and
unconditional cash transfer. The programme aims to empower the extremely poor, disadvantaged
and the vulnerable in society to come out of poverty thereby, fostering long term human capital
development. Target beneficiary household include households with Orphans and Vulnerable
Children (OVC), older adults aged 65 years and older, pregnant/women with children under one
without support and disabled persons without productive capacity). The overall objective of the
LEAP Programme is to reduce poverty by increasing consumption and promoting access to
services and opportunities among the extreme poor and vulnerable.
The LEAP Programme uses categorical targeting. The Common Targeting Mechanism is used to
select potential beneficiaries. This mechanism has been agreed to by five (5) other government
ministries, specifically Ministry of Gender Children and Social Protection (MoGCSP), Ministry
of Health (MoH), Ministry of Education (MoE), Ministry of Finance (MoF) and Ministry of Local
Government and Rural Development (MLGRD).

The Common Targeting Mechanism used to select potential beneficiary households employs the
following approach;

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i.    Geographic Selection
  ii.   Public information and communication
 iii.   Proxy Means Testing

The household data is collected on all household members. However, having an older adult aged
65 years and above is one of the eligibility criteria for the extremely poor household to qualify.
LEAP data on older adults is collected as part of the general data for all potential beneficiary
households. The range of analysis, however covers older adults 60 years and above and this
includes other household members who might not be benefiting directing from the LEAP
programme.

The LEAP data is not nationally representative of older adults in Ghana although the data is
collected in all the 16 regions and 260 districts in the country. This is because, the programs targets
extremely poor households, which may or may not include older adults. In so doing, many of the
older adults in the LEAP communities may be left out as the baseline criterion for the selection of
the house is first extremely poor before the other categories such as having an older adult are
considered. The targeting process was guided by annual targets determined by the Ministry of
Gender, Children and Social Protection based on available or anticipated resources. Allocations
are made to beneficiaries across all sixteen regions using Regional Poverty Quotas. Majority of
the older adults in LEAP have been identified to be females who are the caregivers while the males
are heads of the households. Analysis of the educational background of the older adults indicates
high levels of illiteracy.

One of the strengths of the LEAP data is that, the data can be used to provide information on older
adults that receives social interventions and their poverty levels as well. In terms of limitations,
the programme is not able to determine the age at death and data from LEAP can only be used for
households that have older adults.

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2.6 Ghana Living Standard Survey
Primary Data and Mandate
The Living Standards Measurement Study (LSMS), customized by implementing countries,
including Ghana (Ghana Living Standards Survey), is a research project that was initiated in 1980
by the Policy Research Division of the World Bank. The objective of the project is to make relevant
data on socio-economic development indicators available for policy makers to measure socio-
economic development and analyze their determinants. The Living Standards Survey is conducted
every 5-7 years.
The 6th round of the survey covered a nationally representative sample of 18,000 households in
1,200 enumeration areas. Of the 18,000 households, 16,772 were successfully enumerated leading
to a response rate of 93.2 % (GLSS 6, 2012/13). The 7th round of GLSS was implemented from
October 2016 to October 2017. The GLSS 7 survey collected information from 16,000 households
with a 93% response rate. Detailed information was collected on the demographic characteristics
of households as well as, indicators on education, health, employment, migration and tourism,
housing conditions, household agriculture, household expenditure and income (including
components such as access to financial services, credit and assets).

Secondary Data and Relevance
The GLSS data is a rich source of multidisciplinary data and its application is useful for many
areas of study. It covers crosscutting issues and allows for programmes and projects to be
developed and implemented to address challenges in the various sectors of the economy. Data
from the Living Standards Surveys have, therefore, made it possible to provide valuable insights
into the living conditions of developing countries including.
Person-centred information on determinants and levels of intrinsic capacities and functional
ability, disaggregated by geographic and socio-economic characteristics such as age and sex can
be obtained from the GLSS data. Intrinsic capabilities measured in the GLSS data include
disability status (in terms of vision, hearing, and mobility) of every household member 3 years or
older. Some areas of functional ability covered by the GLSS data is the health status of every
household member. Specifically, if any member was sick or injured in the previous two weeks and
if they accessed health services, time spent, cost, satisfaction with service; for those who did not
access health services, why they did not access healthcare services.

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Methods
The Ghana Living Standards Surveys (GLSS 6 & 7), was designed to provide nationally and
regionally representative indicators. A two-stage probability sampling design was used to select
households for the surveys. A representative sample for all regions as well as rural-urban areas
was selected to constitute the sample for the survey.

Detailed information was collected on key elements of socio-economic life using the following
questionnaires:
   o   Household Questionnaire
   o   Non-farm Household Questionnaire
   o   Community Questionnaire
   o   Governance, Peace and Security Questionnaire
   o   Prices of Food and Non-food Items Questionnaire

Reflectivity on Ageing
The Ghana National Ageing policy sought to among others reduce poverty among older adults,
improve health, nutrition and wellbeing of older adults, as well as improve the housing and living
environment of older adults. Again, other policy dimensions of the National Ageing Policy are to
strengthen family and communities to provide adequate support to older adults and improving
income security and enhanced social welfare.
The GLSS data through the use of the Household Questionnaire collected information on seven
sections namely: demographic characteristics of respondents; education and skills training; health
and fertility behaviour; employment; time use (GLSS6 only); migration and tourism; household
agriculture; housing and housing conditions. In addition, age and sex data for each member of the
household was collected. Therefore, routine information needed on everyone – to promote healthy
ageing across the life course and general information – that is needed specifically on older adults,
and further disaggregated by single age and sex can be sourced from the GLSS data.
Additionally, the GLSS collected detailed information on the health conditions of all household
members. Data on health conditions in the two weeks preceding the interview are good sources of
information on the health and wellbeing of older adults.

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Limitations and Challenges
   1. Firstly, although the GLSS data can be disaggregated by several characteristics such as
       age, sex, disability status, occupation and education among others, some indicators cannot
       be disaggregated largely due to the fact that data on important variables such as housing,
       access to financial service are collected at the household rather than the individual level.
       One major policy dimension of the Ageing policy is to reduce poverty among older adults.
       However, the Ghana Poverty Profile which is produced out of the GLSS data falls short of
       measuring poverty among older adults. This is because the lowest unit of disaggregation
       for all indicators of poverty including the poverty index is at the household, rural/urban,
       district and regional levels. Other important policy measures of the ageing policy such as
       housing and income security cannot be measured using the GLSS data because information
       are collected at the household level and not at the individual level.
   2. Secondly, the GLSS survey is a cross sectional survey and therefore does not allow for
       follow-ups on selected individual. This is very necessary in studying lifelong changes
       which is important in studying healthy ageing.
   3. Thirdly, because the GLSS is cross-sectional, data from other sources cannot be linked to
       it for further analysis. At best, it can only be compared with previous GLSS data since the
       GLSS surveys used the same methodology.

2.7 2010 Population and Housing Census Data
Primary Data and Mandate (2010 Population and Housing Census)
The Population and Housing Census is a complete enumeration of the population of Ghana. The
PHC is conducted on a decennial basis and implemented by the Ghana Statistical Service. The
population and housing census has been conducted since 1960. The most recent census was
conducted in 2010 with 26th September designated as the census night.
The census provides benchmark data for policy and planning. Detailed analysis of the census data
provides empirical data to enhance our understanding of the effectiveness of the various
interventions implemented by the government and its collaborators to improve the lives of
Ghanaians in general. Since the census collects data on every individual person in Ghana on the
census night, the data can be used to track demographic and social indicators of all persons
including older adults 60 year and older.

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Secondary Data and Relevance
The Census data is a rich source of data and provides indicators multiple dimensions of population
and socio-economic development which can measure some indicators of population ageing at the
national, regional, district and locality levels. The census data also serves as bench mark data for
other surveys. Census data can be used to extrapolate survey data to the lowest unit of the country
using small area estimation methods. For instance, the 2015 Poverty Mapping Report used the
2010 census and GLSS6 data to produce district level poverty estimates. The cross cutting nature
of the census data allows for programmes and projects to be developed and implemented to address
challenges in the various sectors of the economy such as education, economic activities, housing
conditions, migration, dependency, mortality as well as social and demographic conditions of older
adults among others.

Methods
In the 2010 Population and Housing Census (PHC), people were enumerated at where they spent
the census night (de facto) and not at where they usually resided (de jure). The de facto count was
adopted because it is based on physical presence on a defined date and therefore it is simple,
straightforward, and easy to interpret as well as minimizes the risks of under and over enumeration.
The reference period, the census night, was fixed for 26th September 2010.

A special operation was carried out by staff of the census secretariat and regional statisticians to
identify possible locations of out-door sleepers in major cities such as Accra, Kumasi, Tema,
Sekondi-Takoradi and Tamale before the census night. Out-door sleepers (floating population)
were enumerated on the census night by regional and district census officials using the census
questionnaire (PHC1C). Following the census night on 26th September 2010, enumeration of
household populations started on Monday, 27th September 2010 with visits to houses, compounds
and structures in enumeration areas for a face-to-face interview with all households.

Reflectivity on Ageing
The census questionnaire collected information on seven thematic areas namely: demographic
characteristics of every individual; educational attainment, employment and unemployment;
migration, disability status, mortality, housing and housing conditions. In addition, age and sex

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