Health Determinants, Measurements, and
Trends
Richard Skolnik

In order to address global health issues, we must understand:
• The factors that most influence health status
• The indicators used to measure health status
• The trends that have occurred historically

Figure 2.1: Key Determinants of Health
Data from: The Public Health Agency of Canada. What Determines Health.
Available at: http://www.phac-aspc.gc.ca/ph-sp/determinants/indexeng.php#determinants. Accessed November 19, 2010.

Health status indicators are useful for:
• Finding which diseases people suffer from
• Determining the extent to which the disease causes death or disability
• Practicing disease prevention/interventions
To perform these functions, it is important to use a consistent set of indicators and have accurate data

• Vital registration systems record births, deaths, and causes of death
• An accurate system is key to having quality data on a population
• Many low- and middle-income countries lack a vital registration system
• Developing a system is progress towards understanding and addressing health problems – skip to slide 29

•
– # deaths of infants under 28 days of age per
1000 births in a year

Figure 2.4: Neonatal Mortality Rate, by WHO Region, 2004
Trends in neonatal mortality – more recent data
Data from World Health Organization. Neonatal and Perinatal Mortality:
Country, Regional, and Global Estimates 2004. Geneva: WHO; 2007: Table 2.

• One quarter to one half of all deaths occur within the first 24 hours of life
• 75% of deaths occur in the first week
• The 48 hours immediately following birth is the most crucial period for newborn survival
• A baby's chance of survival increases significantly with the presence of a skilled birth attendant at the birth
WHO

Year Population Neonatal mortality rate, deaths/1000 live births
U.S. overall 4.19
2009
Maine
Black infants
White infants
4.2
8.2
3.43
2006
2009
2009

•
– # deaths of infants in the first year of life per 1000 births in a year

Figure 2.3: Infant Mortality Rate, by World Bank Region, 2008
Data from The World Bank. World Development Indicators, Data Query.
Available at: http://databank.worldbank.org. Accessed June 29, 2010.

Population
U.S. overall
Black
Infant mortality rate, deaths/1000 live births
6.8
5.7
6.7
6.42
12.71
Year
2001
2004
2008
2009
2009

•
– aka child mortality rate
– the probability that a newborn infant will die before reaching the age of 5, # per 1000 live births

Figure 2.5: Under-five Child Mortality Rate, by World Bank Region, 2008
Data from The World Bank. World Development Indicators, Data Query.
Available at: http://databank.worldbank.org. Accessed June 29, 2010.

• 6.9 million children under the age of five died in 2011.
• More than half of these early child deaths are due to conditions that could be prevented or treated with access to simple, affordable interventions.

• Leading causes of death:
– pneumonia, preterm birth complications, diarrhea, birth asphyxia and malaria
– ~ one third of all child deaths are linked to malnutrition.
• Children in sub-Saharan Africa are about 16.5 times more likely to die before the age of five than children in developed regions.

• Neonatal mortality rate - # deaths of infants under 28 days of age per 1000 births in a year
• Infant mortality rate - # deaths of infants in the first year of life per 1000 births in a year
• Under 5 mortality rate (aka Child mortality rate) – the probability that a newborn infant will die before reaching the age of 5, # per
1000 live births

•
– # women who die as a result of pregnancy or childbirth complications per 100,000 live births in a year

Figure 2.6: Maternal Mortality Ratio, by World Bank Region, 2005
Data from The World Bank. World Development Indicators, Data Query. Available at: http://databank.worldbank.org. Accessed June 29, 2010..

• 87% deaths in Sub-Saharan Africa and South
Asia
• 50 percent of all deaths occurred in six nations: India, Nigeria, Pakistan, Afghanistan,
Ethiopia, and the Democratic Republic of
Congo

•
– average # of years a newborn could expect to live if current mortality rates were to continue for the rest of the infant’s life

Figure 2.2: Life Expectancy at Birth, by World Bank Region, 2008
Data from the World Bank. World Development Indicators, Data Query.
Available at: http://databank.worldbank.org. Accessed June 29, 2010.

Historical Trends based on Health Status Indicators
Table 2.11: Life Expectancy and Percentage Gain in Life Expectancy, 1960-2008, by
World Bank Region
Data from the World Bank. World Development Indicators, Data Query.
Available at: http://databank.worldbank.org. Accessed July 6, 2010.

• 14% of births are attended by a health professional
• Lifetime risk of woman dying as a result of pregnancy or childbirth: 1 in 11
• Life expectancy girl born today = 45

• Under 5 mortality rate: 1 in 5 children die before the age of 5
• Every woman is likely to suffer the loss of a child in her lifetime
• 39% of children moderately or severely underweight
• 52% Do not have access to clean water

• Morbidity – sickness/illness
– physiological and/or psychological
• Mortality – death
– Mortality/Death rate expressed as # deaths per
1000 in a population in a year
• Disability – “temporary or long-term reduction in a person’s capacity to function”

• Prevalence - # of people suffering from a particular health condition over a period of time
– Generally consider at a given point in time (crosssectional) – point prevalence
– Measure of existing cases at a given time
• Incidence rate - # of people contracting a disease per 1000 at risk in a year
– Measure of new cases per year

• Communicable diseases – spread by an infectious agent
– Influenza, HIV/AIDS, measles, malaria, cholera
• Non-communicable diseases – diseases not spread by an infectious agent
– Hypertension, diabetes, lung cancer, CVD
• Injuries
– Accidents, violence, burns, cuts

Figure 2.10: The Burden of Disease by Group of Cause, Percent of Deaths, 2001
Data from Lopez AD, et al Global Burden of Disease and Risk Factors.
Washington, DC and New York: The World Bank and Oxford University Press;
2006:8.

Table 2.10: The "Demographic Divide:" The Example of Nigeria and Japan
Data from PRB. 2009 World Population Data Sheet. Available at http://www.prb.org/Publications/Datasheets/2009/2009wpds.aspx. Accessed November 24,
2010.

• Higher income countries tend to have a greater burden of non-communicable disease
• Lower income countries to have a greater burden of communicable disease

Low and Middle Income
Countries
% Deaths
54 % Non-Communicable Diseases
Rank. Cause of death, % of deaths
36 % Communicable Diseases
10 % Injuries
1. Heart disease 11.8%
2. Strokes 9.5%
5. Perinatal conditions 5.1%
6. COPD 4.9%
3. respiratory infections 7.0%
4. HIV/AIDS 5.3%
7. Diarrheal disease 3.7%
8. TB 3.3%
9. Malaria 2.5%
10. road accidents 2.2%

High Income Countries
% Deaths
87 % Non-Communicable Diseases
Rank. Cause of death, % of deaths
1. Heart disease 17.3%
2. Strokes 9.9%
3. Trachea, lung cancers 5.8%
5. COPD 3.8%
6. Colon and rectal cancers 3.3%
7. Alzheimer’s/dementia 2.6%
8. Diabetes 2.6%
9. Breast cancer 2.0%
10. Stomach cancer 1.9%
4. Respiratory infections 4.4% 5.7 % Communicable Diseases
7.5 % Injuries

• Children in low- and middle-income countries often die of communicable disease
• HIV/AIDS and TB are among the leading causes of death among adults in low and middleincome countries

Table 2.5: The 10 Leading Causes of Death in Children
Ages 0-14, by Broad Income Group, 2001

Table 2.6: The 10 Leading Causes of Death in
Adults 15-59, by Broad Income Group, 2001

In most low- and middle-income countries:
• Rural people will be less healthy
• Disadvantaged ethnic minorities will be less healthy
• Women will suffer as a result of their social positions
• Poor people will be less healthy
• Uneducated people will be less healthy

• Two indicators used to compare how far countries are from a state of good health
• Health-Adjusted Life Expectancy (HALE)summarizes expected number of years to be lived in what might be termed the equivalent of good health
• Disability-Adjusted Life Year (DALY)- a unit for measuring the amount of health lost because of a particular disease or injury

• HALE – Health-Adjusted Life Expectancy
– Calculated by a standard methodology by World
Health Organization (WHO)
– Years of ill health are weighted according to severity and subtracted from overall lifeexpectancy

Table 2.2: Life Expectancy at Birth and Health-Adjusted Life Expectancy,, 2004
Data from WHO. Core Health Indicators. Available at: http://www3.who.int/whosis/core/core_select_process.cfm.
Accessed: September 24, 2006.

– First measured by World Bank as a “health gap measure”
• Used by World Bank and WHO – controversial measure
– DALYs are thought to be a better indicator of the health of a population than mortality rates
– DALY takes into account that many conditions associated with poor health are not fatal
– A higher DALY value indicates a greater health burden

• “This time-based measure combines years of life lost due to premature mortality and years of life lost due to time lived in states of less than full health.
• The DALY metric was developed in the original
Global Burden of Disease 1990 study to assess the burden of disease consistently across diseases, risk factors and regions.”

• A DALY is a measure of years of fully healthy life lost due to disease, death, …….disability…..
– The higher the DALY value the more years lost due this “condition” – or the more years living with compromised health

• DALYs are intended to provide a comparable measure of the burden of disease
• Used to:
– Aid in setting health care priorities
• Treatment and prevention
– Aid in setting research priorities
– Identify high need populations and target health interventions
– Measure success/effectiveness of interventions

• Measures how many healthy years of life are lost between the population being studied and the healthiest possible populations
– Consider
• Communicable diseases
• Maternal, perinatal (1 st weeks after birth)
• Nutritional disorders
• Non-communicable disorders
• Injuries/accidents
Grouped together

Low and Middle-Income High-Income Countries
Table 2-4 on page 30 shows DALYs in low and middle-income countries by regions

• Disabilities/health conditions are weighted by one of 6 values based on the limitations or reduction in years of life associated with the
“condition”
• The more serious the “condition” the higher the weighting
– Deaf, weighting = .33
– Dead, weighting = 1 (most serious!)
• Calculating DALYs

WEIGHTING of DISABILITIES
• Weightings quantify societal preferences for health states in relation to the societal ideal of good health.
• On average, society judges a year with blindness (weight 0.43) to be preferable to a year with paraplegia (weight 0.57), and a year with paraplegia to be preferable to a year with unremitting unipolar major depression
(weight 0.76).
• Source this slide and next http://www.who.int/quantifying_ehimpacts/publications/en/9241546204chap3.pdf

• On average, society would prefer a person to have a year in good health followed by death, than a year with paraplegia followed by death.
• Society would prefer a person to live three years with paraplegia followed by death (3 years x 0.57 = 1.7 lost “healthy” years), than have one year of good health followed by death (2 lost years of good health).

(without age-weighting and discounting)
• The calculation of DALYs of a woman who has been deaf since she was 5 and dies when she is 50:
(deafness is set at 0.33; life expectancy 80) :
• Number of healthy life years × the disability weight of full health (0) + life years with disability
(50) × disability weight for deafness (0.33) + life years lost (30) × the weighting of death (1)
• (5 × 0)+ (45 × 0.33) + (30 × 1) = 47.35 DALYs

• In addition to adjusting the value of life years with disability weights, and choosing a particular life expectancy, the value of a life year is modified by
• Age weighting
– life years of children and old people are counted less
• Discounting
– the value of a life year now is set higher than the value of future life years

• Girl, 5 years old, with below-knee amputation who lives until she is 82.5:
• DALYs= life years lived with disease
(77.5) × disability weight (0.3) × ageweight (a 1 ) × discounting factor
(3%/year)
• 77.5 × 0.3 × a 1 × d 2 = 10.5 DALYs

• The 5-year-old girl in the prior example yielded
• However, the DALY score without age-weight and discounting would be
• 77.5 × 0.3 =
• This result is twice as high, and would give her a higher priority.

•
– the young
– the elderly
– the disabled
– women

• WHO -
– WHO Health Statistics and Health Information
Systems website is a rich source of data
• Data is available by country and by region of the world
• Could spend the entire semester just mining this data!
• World Bank
• Gapminder – World Data
• MDG related data
– Gapminder MDG data

Figure 2.11: Gross Domestic Product Per Capita and Female Life Expectancy at Birth,
Selected Countries, 2004
Data from WHO. Core Health Indicators. Available at: http://www3.who.int/whosis/core/core_select_process.cfm. Accessed:
September 24, 2006.

• Hans Rosling on Health Statistics and Child
Mortality
– http://www.gapminder.org/videos/reducing-childmortality-a-moral-and-environmental-imperative/

Figure 2.9: The Demographic Transition: (A) High Fertility/High Mortality, (B) Declining
Mortality/High Fertility, (C) Reduced Fertility/Reduced Mortality
Reprinted from U.S. Census Bureau, International Population Reports WP/02,
Global Population Profile: 2002. Washington, DC: U.S. Government Printing
Office; 2004, p. 35.

Figure 2.7: Percentage of Children 0 -5 Whose Births Have been Registered, by Income
Quintile
Data from UNICEF. Progress for Children: Achieving the MDGs with Equity. Available at: http://www.unicef.org/media/files/Progress_for_Children-No.9_EN_081710.pdf.
Accessed September 17, 2010. .

Figure 2.8: World Population - 1950 to 2050
Adapted from: Haub, Carl and PRB. Data from United Nations Population Division. World
Population Prospects, The 2008 Revision. Available at: http://esa.un.org/UNPP/. Accessed
December 4, 2010.

Table 2.1: Key Health Status Indicators
Adapted from: Haupt A, Kane TT. Population Handbook. Washington, DC:
Population Reference Bureau; 2004; World Bank. Beyond Economic Growth
Student Book: Glossary. http://www.worldbank.org/depweb/english/beyond/global/glossary.html.
Accessed April 15, 2007.

Table 2.3: The 10 Leading Causes of Death and DALYs 2001
Adapted with permission from Lopez AD, Mathers CD, Murray CJL. The Burden of Disease and Mortality by Condition: Data, Methods, and Results for 2001. In:
Lopez AD, Mathers CD, Ezzati M, Jamison DT, Murray CJL, eds. Global burden of disease and risk factors. Washington, DC and New York: The World Bank and
Oxford University Press; 2006.

Table 2.4: The Ten Leading Causes of the Burden of Disease in Low- and Middleincome Countries, by Region, 2001
Reprinted with permission from Lopez AD, Mathers CD, Murray CJL. The Burden of Disease and Mortality by Condition: Data, Methods, and Results for 2001. In: Lopez AD, Mathers CD,
Ezzati M, Jamison DT, Murray CJL, eds. Global Burden of Disease and Risk Factors. New York:
Oxford University Press 2006:91. Washington, DC and New York: The World Bank and
Oxford University Press

Table 2.5: The Ten Leading Causes of Death in Children Ages 0-14, by Broad Income
Group, 2001
Adapted with permission from: Lopez A, Begg S, Bos E. Demographic and
Epidemiological Characteristics of Major Regions, 1990-2001. In: Lopez A,
Mathers C, Ezzati M, Jamison D, Murray C, eds. Global Burden of Disease and
Risk Factors. Washington, DC and New York: The World Bank and Oxford
University Press; 2006:70.

Table 2.6: The Ten Leading Causes of Death in Adults 15-59, by Broad Income Group,
2001
Adapted with permission from: Lopez A, Begg S, Bos E. Demographic and
Epidemiological Characteristics of Major Regions, 1990-2001. In: Lopez A,
Mathers C, Ezzati M, Jamison D, Murray C, eds. Global Burden of Disease and
Risk Factors. Washington, DC and New York: The World Bank and Oxford
University Press; 2006:70.

Table 2.7: The Ten Leading Causes of Death by Sex, in Low- and Middle-Income
Countries, 2001
Data from Lopez A, Begg S, Bos E. Demographic and Epidemiological
Characteristics of Major Regions, 1990-2001. In: Lopez A, Mathers C, Ezzati M,
Jamison D, Murray C, eds. Global Burden of Disease and Risk Factors.
Washington, DC and New York: The World Bank and Oxford University Press;
2006:70.

Table 2.9: Percentage of the Population Projected to be Over 65 Years of Age
Based on Haub, Carl and PRB. Data from United Nations Population Division. World Population
Prospects, The 2008 Revision. Available at: http://esa.un.org/UNPP/. Accessed December 4, 2010.

Table 2.12 (cont.): Trends in the Ten Leading Causes of the Burden of Disease, by
Income Group, 2004 - 2031 continued
Data from World Health Organization. Global Burden of Disease (GBD). Available at: http://www.who.int/healthinfo/global_burden_disease/en/. Accessed September 14, 2010.