27 Importance of mortality studies

Gautam Kshatriya and Divya Mishra

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LEARNING OUTCOME

Upon completion of this module, the student will be able to :

1.  To understand the definition and meaning of mortality and different measure of mortality

2.  Importance of mortality as an indicator of health status of a population

3.  Use of mortality for planning and development.

    INTRODUCTION

 

Mortality is considered to be an important index in population studies. Although the association between mortality and health may not be very explicit ,yet decline in the mortality generally suggests an improvement in living standards and medical facilities.

 

Structure of a population is mainly determined by four main component of population dynamics namely Birth, morality, immigration and emmigration. Immigration and emigration depends on social, economical and environmental factors they do not have direct relation with biological component of population like genetic factors, pathogenecity, physiological factors. But birth and death are directly affected by genetic, physiological and physical factors prevailing in population. Mortality has a great effect on growth of population (Porta, M, ed., 2014). fertility/birth of population normally adjusted according to the carrying capacity of the area. As the resources decrease rate of growth of population decreases and the decreases in growth of population is instrumented by increases in mortality. Hence it can be said that mortality maintain a steady state of population. This statement is further strengthened by the fact that sharp decline in mortality rates, rather than any rise in fertility rate has been responsible for bringing rapid growth of population (Porta, M, ed,.2014). Therefore mortality is a important factor in population studies which must be dealt in detail to understand the demographic behaviour of a population.

 

WHAT IS MORTALITY? DOES MORTALITY AND MORBIDITY MEANS SAME?

 

Mortality and Morbidity are considered as an Indicators of Health Status of a Population. Death is a unique, universal and final event, therefore Mortality is clearly defined as State of being subjected to death. Age at death and cause/reason provide an instant depiction of health status. In high mortality settings, information on trends of death (by causes) substantiate the progress of health programs. But anthropologist and demographist give more importance to the rate of mortality or death rate and the reason of mortality which is of great concern for anthropologist.

 

Mortality rate is a measure of mortality in relation to time. It can be defined as number of deaths in a population scaled to the size of the population per unit time. Mathematically it is expressed as number of deaths per thousand individual in a year (Porta, M, ed,.2014).

 

Mortality Rate = No. of death in a population in a year/total population X 1000

 

(Source: www. healthy. askansas.gov/oovital/formulas.htm)

 

However morbidity is diseased state, disable as per health due to any cause (Jha, P, 2002). It indicates the incidence of ill health in a population.

 

DOES MORTALITY RATE ANSWERS ALL QUESTIONS RELATED TO MORTALITY?

 

Till now we have discussed death rate in crude form i.e. number of death per year per 1000 people. But this simple expression of death rate can be misleading sometime if we consider it without taking age specific and other reasons of mortality in concern.

 

A population with good health care facilities but with a large population with old age individual i.e. the case with developed countries. The crude mortality rate during a specific period may show higher value. Whereas a young population with less health care facility as in case of developing countries may show low crude mortality rate in comparison to an mature population. Therefore different type of mortality rate are used to understand mortality trend in an population.

 

Measures of Mortality Š:

 

These different type of mortality rates are as follows:

 

1)                  Crude Death Rates;

2)                  Age-Specific Death Rates;

3)                  Life Table Estimates – 3(a).Life expectancy – 3(b). Survivorship (by age);

4)                  Cause-Specific Death Rates;

5)                  Special Indicators – 5 (a)Infant and 5(b) maternal mortality rates;

6)                  Prenatal mortality rate;

7)                  Child mortality rate

 

1). The crude Death rate (CDR): is a very general indicator of the health status of a geographic area or population. It can be defined as the number of deaths per 1000 estimated mid -year population .( http://conflict.lshtm.ac.uk/page_98.htm)

 

CDR= Total deaths during a year                             x 1000

total mid year population during that year

 

2). Age specific mortality rate: Total number of death per year per 1000 people of a particular age is called age specific mortality rate. This expression of mortality rate is of great use for insurance companies. They use this expression to calculate premium of life insurance for an individual of a population.( http://conflict.lshtm.ac.uk/page_98.htm)

 

3). Life Table: This records matters of life and death for a population. According to this the organisms in a population will live, die, and/or reproduce at different stages of their lives.

 

3(a). Life expectancy at birth: It is defined by the United Nations Human Development Report as “the years a newborn infant would live if prevailing patterns of age-specific mortality rates at the time of birth were to stay the same throughout the child’s life”.

 

3 (b). A survivorship (by age) curve : This is defined by what fraction of a starting group is still alive at each successive age.

 

4.    Cause specific Mortality Rate: The death rate due to specific cause of death is take as cause specific mortality rate. this expression is very useful to understand the trend of mortality due to an epidemic or an disease prevailing in an population.

 

5.  Special Indicators

 

5(a). Infant Mortality rate:-It is defined as number of death of children of less than one year i.e. the infants in one year per 1000 live births. (http://conflict.lshtm.ac.uk/page_98.htm)

 

5(b). Maternal mortality: According to WHO maternal mortality is defined as “the death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the duration and site of the pregnancy, from any cause related to or aggravated by the pregnancy or its management but not from accidental or incidental causes.” .( http://conflict.lshtm.ac.uk/page_98.htm). Maternal Mortality Ratio (MMR) is the ratio of the number of maternal deaths per 100,000 live births. It is one of the indicator in assessing the quality of a health care system. First, aside from the WHO definition, other definitions exist and some include accidental and incidental causes. “Incidental causes” include deaths secondary to violence against women that may be related to the pregnancy and be affected by the socioeconomic and cultural environment. Maternal mortality numbers are unreported, as the major causes of maternal death are bacterial infection, variants of gestational hypertension including pre-eclampsia , obstetrical hemorrhage, ectopic pregnancy, amniotic fluid embolism, and complications of abortions. Indirect causes can be malaria, anemia, HIV/AIDS and cardiovascular disease, complicated pregnancy, among others.

 

6.   Prenatal mortality: The sum of neonatal death and foetal deaths per 1000 births in a year is called prenatal mortality. It can be useful to understand condition of child and mother before and after birth of child like sufficient supplements and health care facilities etc.

 

7.  Child Mortality rate: The number of death of children less than five years per 1000 live births in one year is called child mortality rate.

 

There are two other type of mortality rate which are used in medical studies to assess the success or failure of a treatment procedure.

1.   Early mortality rate:-Death rate in early stage of ongoing treatment.

2.  Late mortality rate:- Death rate during later stage of ongoing treatment.

 

HOW TO GET MORTALITY DATA?

One can get mortality data from various resources:

 

a). National vital registration systems – a major source in developed countries. Universal coverage of the population and is Continuous operation. But its disadvantages that it is late or never reported . Events are collected by a local registration office, usually a government agency. Individual citizens, local officials, physicians, hospital employees, etc reports the information to registration office.

(Source: http://ocw.jhsph.edu/courses/PopulationChange/PDFs/Lecture6.pdf)

 

b). Sample registration systems (e.g., in China and India)

Sample Registration System (SRS). It Began in 1964-65 . It does over 6000 sampling units (about 10,000,000 population). Dual registration systems for births and deaths is the task they perform and Provides fertility and mortality estimates for every state and territory also Cause of death based on lay reporting. 

(Source: http://ocw.jhsph.edu/courses/PopulationChange/PDFs/Lecture6.pdf)

 

c).Household surveys – (to estimate infant and child mortality )

It began during early 1960’s to measure the demographic impact of family planning programs Systematic national household sample surveys was designed in a manner to collect data on population and health. For health assessment of developing countries, family planning and population surveys are still the largest sources of data. There are various Major International Household Surveys: World Fertility Surveys (WFS) (1970s to 1985) ; Demographic and Health Surveys (DHS) (1985 to Present).

(Source: http://ocw.jhsph.edu/courses/PopulationChange/PDFs/Lecture6.pdf)

 

d). Special longitudinal investigations (e.g., maternal mortality studies) :Specialized longitudinal studies takes into account selected events such as Maternal mortality, (in Egypt, Nigeria, Philippines, Bangladesh, etc.) and Continuing longitudinal event registration in selected study populations (in Matlabin Bangladesh, Rakaiin Uganda)

(Source: http://ocw.jhsph.edu/courses/PopulationChange/PDFs/Lecture6.pdf)

 

Types of Mortality studies:

 

The analysis of occupational cohort mortality studies has traditionally been plagued by the bias resulting from improper comparisons of working populations with the general population. For example, the age-specific mortality rate for arterioslerotic cardiovascular disease (ASCVD) in an unexposed working population is usually 60-90% of the rate in the general population. Thus, the general population cannot serve as an appropriate control group when interest is in detecting relative risks in the range 1.5-2.0. Since present day exposures are, in general, lower than exposures experienced in the past, and since most substances associated with the large increases in relative risk may have already been discovered, occupational epidemiology has become increasingly concerned with detecting relative risks less than 2.0. Recognizing that the general U.S. population is not an adequate control group, occupational epidemiologists have increasingly relied upon comparisons, within a single cohort, among workers who differ in levels of exposure. Unfortunately, if workers at increased risk terminate employment early, standard intracohort methods of analysis that estimate mortality as a function of cumulative exposure can underestimate the true effect of exposure on mortality, whether or not one adjusts for time of termination of employment[l-31. Thus, even in intracohort analyses, increases in the relative risk in the range 1 S-2.0 due to occupational exposures can be masked by the early termination of workers with poor prognosis (which we refer ro us the healthy worker survivor effect). In this monograph we present a set of statistical methods specifically designed to control bias due to the healthy worker survivor effect. Although Gilbert recognized that, for chronic disabling illnesses such as XSCVD, bias due to the healthy worker survivor effect could not be controlled by standard methods, she conjectured that, for diseases for which the interval between clinical manifestation and death is brief, such as lung cancer, any bias due to the healthy worker survivor effect Causal inference in mortalit) studies 1397 could be abolished by estimating the association of mortality with cumulative exposure lagged some ten years (that is, for an individual at risk at age t, any exposure received after age t – 10 is ignored for the purposes of analysis).

 

In cohort mortality studies in which individuals are exposed to the agent under study for sustained periods of time, independent risk factors for death commonly determine later exposure history. For example, in occupational cohorts, we observe that unexposed individuals who terminate employment at any age (say, 40) prior to age 65 have higher subsequent age-specific mortality rates than unexposed individuals who continue to work past that age (at least, in part, because of the healthy worker survivor effect). It follows that termination status is both a determinant of future exposure (since terminated individuals receive no more exposure) and an independent risk factor for death. As pointed out by Gilbert[ I] and Robins[Z, 31, if risk factors for death are determinants of subsequent exposure, the association of observed exposure history with mortality may fail to reflect a causal association. If, in addition, past exposure history is a determinant of subsequent risk factor status, the association of observed exposure history with mortality may be noncausal whether or not one adjusts for the risk factor.

 

USE OF MORTALITY STUDIES : General Descriptive And Demographic Uses

 

It is possible to study mortality, from a number of angles, for various biological, social, economic and cultural factors which affect the health of an individual and consequently the mortality rate in society. Focussing only on mortality never shows the exact picture. For better understanding mortality has to be linked which its cause and other social, economical and cultural factor and this relation of mortality with said factors help us to use mortality in different fields.

 

POPULATION FORECASTING:

 

The study of mortality is useful to analyse contemporary demographic conditions as well as for determining the prediction of potential changes in mortality conditions of the future. Short, medium and long term planning requires population forecasting. Be it Education sector, Modern sector development, public health infrastructure development etc.

 

Education sector: In Education sector it is of necessity to know the size distribution and structure of the school age population so that the planning to educate can be done in a planned manner. School age population will be determined by the future stream of birth attenuated by child deaths. Without proper planning and estimation of future population all planning and preparation can collapse.

 

Modern sector: Urbanization nowadays are demanding for modern lifestyle, and better quality of life. Therefore, at the time of planning and development the population prediction at that particular time in a particular area is of utmost essentiality to make it modernised. (Kennet Hill and United nations secretariat, (1984) Databases Chapter 3)

 

Public health infrastructure: Public health infrastructure are for communities, states, and the Nation. It provides the capacity to these to prevent from disease, uphold better health, and prepare to respond to crisis/ disastrous situation and to the health challenges in progress. A country with weak health infrastructure has high mortality rate. Which has effect on the growth of economy and other measures of development. Every country invest in public health infrastructure as per its GDP. A developed country has a large share of its GDP as health care expenditure and this expenditure must be planned in a systematic manner. Mortality rate and its association with causes of mortality is very useful in determining which area must be focussed on. A ill targeted investment can lead to loss of public exchequer. Hence mortality studies are very useful in public health infrastructure.

 

POLICY MAKING :

 

Information of mortality helps policy makers to plan, design, and implement for the benefit of the population, as it can assess country’s trajectory through epidemiological transition.

 

SOCIAL DESCRIPTIONS:

 

On a shorter time-scale, mortality statistics provide an important indicator of the health and well-being of a population. Mortality statistics are required to estimate summary measures of population health among sub-groups in the population, for example the life expectancy at birth, and infant mortality are included to understand the quality of life. (Kennet Hill and United nations secretariat, (1984) Databases Chapter 3).

 

EPIDEMIOLOGICAL STUDIES:

 

Information on definite cause of death is also significant in various epidemiological studies. Epidemiology uses observed mortality differentials so as to suggest links between risk factors and disease. Mortality by occupation, place of residence, personal habits, or diet, details disaggregation by cause is required (Kenneth Hill and United nations secretariat, (1984) Databases Chapter 3).

 

USES FOR DETERMINING PAYMENT COST BY LIFE INSURANCE COMPANY:

 

The premium rate for a life insurance policy is determined by two underlying concepts: mortality and interest. There is also a third variable i.e the expense factor. This factor equals to the amount the company adds to the cost of the policy to cover operating costs of investing the premiums, selling insurance, and paying claims. Life insurance is based on the sharing of the risk of death by a large group of people, i.e. trend of mortality of that population and age specific mortality. To predict the cost to each member of the group the amount at risk must be known. Estimation of cost of death claims is a question of great importance for the life insurance companies and Mortality tables are used to give the company a basic of this estimate. By using a mortality table a life insurer can determine the average life expectancy for each age group.

 

USE IN CHILD HEALTH CARE:

 

The relative ease of calculating the annual rate have resulted in the infant mortality rate being generally used for comparisons across regions, populations and time periods. The comparisons of infant mortality rates are often used in needs assessments and to evaluate the impact of public health programs. The health and well-being of children and families across the globe are measured by infant mortality rates. Widely used as a measure of population health and the quality of health care, infant mortality is defined as the death of an infant before the age of one year. Infant mortality has a major concern with public health. The Federal Children’s Bureau, established in 1912, focused on infant mortality as its first initiative, officially recognizing its importance. The infant mortality rate although measures the risk of death to an infant but it is used also broadly used as an basic indicator of:

  • Community health status
  • Poverty and socioeconomic status levels in a community
  • Availability and quality of health services and medical technology

    LIMITATION OF MORTALITY DATA:

 

With the improved survival of the population with modernization and populations age, mortality measures lack in giving an adequate depiction of a population’s health status. Therefore,Š Indicators of morbidity such as the prevalence of chronic diseases and disabilities become more important than this.

 

Summary

 

Mortality when viewed from the demographic point of view, it is studied to determine changes in the population size and structure. Study of mortality has major significance on public health administration. Such mortality studies are required to know the statistics on death in the population cross-classified by age, sex and the reason for death are of much greater importance in formulation, functioning and assessment of various public health programmes. Statistics on deaths also form the basis of the policies of insurance companies. Most industrialized countries considers mortality data as the only medically relevant complete statistics for the explanation of health and disease in a population. Although mortality data reflect just the opposite of the state of health of a population, specific age and sex mortality rates are important indicators of the health status of a population and beyond that for the social system, e.g. for the effectiveness of the subsystem of health services. Validation studies show that the diagnoses on death certificates are much more reliable than generally thought. Scientists must have access to information from the original death certificates because otherwise the increasingly desirable studies on the threat of environmental noxae to the population cannot be carried out (Frentzel-Beyme et al.,1980) .

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References

  • Porta, M, ed. (2014). “Death rate”. A Dictionary of Epidemiology (5th ed.). Oxford: Oxford University Press. p. 69. ISBN 978-0-19-939005-2.
  • Jha, P (2002). “Avoidable mortality in India: Past progress and future prospects”. The National medical journal of India. 15 Suppl 1: 32–6. PMID 12047131.
  • Kennet Hill and United nations secretariat, (1984) Databases Chapter 3.
  • Uses of mortality data for planning and research. (http://www.un.org/esa/population/publications/UN_1984_Data_Bases_for_Mortality_Measurement/ UN1984_Databases_ch3_Uses_Planning_and_Research.pdf).
  • Frentzel-Beyme, R., Keil, U., Pflanz, M., Struba, R., & Wagner, G. (1980). Mortality data and statistics, importance for health services and epidemiological research (author’s transl). MMW, Munchener medizinische Wochenschrift, 122(24), 901-906.

    Web Links:

  • Source: www. healty. askansas.gov/oovital/formulas.htm
  • Source: http://ocw.jhsph.edu/courses/PopulationChange/PDFs/Lecture6.pdf
  • Source: http://conflict.lshtm.ac.uk/page_98.htm

    Suggested Readings :

  • Mirrors of Mortality: Social Studies in the History of Death, Joachim Whaley Routledge, 2011 – History – 252 pages
  • Robins, J. (1987). A graphical approach to the identification and estimation of causal parameters in mortality studies with sustained exposure periods. Journal of chronic diseases, 40, 139S-161S.
  • Lynch, J. W., Smith, G. D., Kaplan, G. A., & House, J. S. (2000). Income inequality and mortality: importance to health of individual income, psychosocial environment, or material conditions. BMJ: British Medical Journal, 320(7243), 1200.
  • Morrish, N. J., Wang, S. L., Stevens, L. K., Fuller, J. H., Keen, H., & WHO Multinational Study Group. (2001). Mortality and causes of death in the WHO Multinational Study of Vascular Disease in Diabetes. Diabetologia, 44(2), S14.