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Dr Omar Hasan Kasule Sr.
MB ChB (MUK), MPH (Harvard) DrPH (Harvard)
Professor (Epidemiology and Bioethics)
Faculty of Medicine, King Fahd Medical City
WEB: http://omarkasule.tripod.com
Workshop On Health Research Priorities Organized By The Research Directorate Of The Ministry Of Health At Jeddah 5-7 June 2010
GLOSSARY OF KEY WORDS AND KEY TERMS page 5
· Hospital Information Systems
· Medical Records Department
· The Medical Record
· Performance Indicators: Process and Outcomes
· Hospital Administration
· Introduction
· Birth Rates, Ratios, and Proportions
· Death (Mortality) Rates, Ratios, and Proportions.
· Marriage and Divorce
· Morbidity Rates
· Definition of Basic Rates
· Population Pyramid
· Population Projections
· Demographic Shift/Transition
· Demographic Population Life-Table
PRETEST (INDICATE TRUE/FALSE ON EACH ITEM)
1. The following statements are true about use of hospital data
- Hospital data is not representative of the disease patterns in the community
- Hospital data is used by hospital administrators in planning and forecasting
- Hospital data on discharge diagnosis can be used in surveillance for disease out-breaks
- Hospital-based cancer registries have no contribution at all to the study of cancer epidemiology
- Hospital data is a perfect description of the morbidity in a population
2. The following are uses of public health information systems
A. Detection of epidemics
B. Decision making
C. Problem solving
D. Planning
E. Surveillance
3. The following are sources of public health information
A. Demographic data
B. Morbidity data
C. Mortality data
D. Health care utilization
E. Hospital care records
4. The following statements are true about cancer registries
A. Cancer registration is continuing, systematic collection of data on reportable neoplasms
B. The cancer registry helps physician in follow-up of patients
C. Cancer registries are used for epidemiological studies (incidence and prevalence, immediate causes of death, survival, and treatment)
D. Controls cannot be obtained from cancer registries for case control studies of cancer
E. Disease registries are also available for other diseases.
5. The following statements are true about vital statistics
A. Vital statistics cover exclusively births and deaths and nothing else
B. Vital records are not used for legal purposes
C. Report of births and deaths is required by law
D. Vital data is used for health planning
E. Births and deaths at home may not be recorded
6. The following statements are true about infant mortality
A. IMR is the most important indicator of community health
B. IMR is deaths at ages 0-12 months per 1000 LB per year
C. The denominator for the Infant Mortality Rate (IMR) is the number of live births
D. Infant mortality rate is defined as number of deaths at 0-12 months per 1000 live births per year
7. The following statements are true about census data
A. Censuses are held once every 5 years
B. Vital statistics are used for inter-censual population estimates
C. Censuses cover only health-related questions
D. Censuses based on mailed questionnaires are invalid
E. Census data provides denominators for epidemiological rates
8. The following statements are true about demographic rates
A. TFR is births per year 1000 women in mid-year population aged 15-44
B. Gross reproductive rate is reproductive rate computed for girls only
C. The net reproductive rate is the proportion of girls surviving to the reproductive age out of 1000 LB
D. The replacement level is TFR of 2.1
E. Countries with negative population growth have TFR <2.0
9. The following statements are true about population pyramids
A. Population is described by age, sex, race/ethnicity, marital status, education, and occupation
B. Population pyramids reflect both birth and death rates
C. Population pyramid displays population structure by age
D. Population structure and future projection are determined by fertility, mortality, and migration
E. Population pyramids have a narrow base and a wide top in industrial countries
10. The following statements are true about life-tables
A. Life tables are current or cohort (generational)
B. Life tables cannot be specific for gender, race, and place
C. The population pyramid does not tell us about the sex structure of a population
D. Abridged life-tables cover only certain ages
E. Life tables are used for actuarial, pension, & annuities computations
GLOSSARY OF KEY WORDS AND KEY TERMS
· Catchment area
· Demographic, life table
· Demographic, rates
· Demographic, shift
· Epidemiological, transition
· Health status indicators
· Hospital, morbidity
· Hospital, bed capacity
· Hospital, information system
· Hospital, mortality
· Hospital, planning
· Hospital, rates
· Hospital, records
· Life, expectancy
· Life, table (abridged)
· Life, table (cohort or generational
· Life, table (current)
· Life, table (followup)
· Patient discharge
· Population, control
· Population, density
· Population, dynamics
· Population, growth
· Population, life tables
· Population, pyramid
· Quality assurance
· Rate, adjusted rate
· Rate, birth rate
· Rate, crude rate
· Rate, death rate
· Rate, rate density
· Rate, growth rate
· Rate, hazard rate
· Rate, incidence rate
· Rate, morbidity rate
· Rate, mortality rate
· Rate, pregnancy rate
· Rate, specific rate
· Rate, standardized rate
· Rate, vital rate
· Ratio, mortality ratio
· Ratio, odds ratio
· Ratio, risk ratio
· Ratio, vital ratio
· Record linkage
· Records, medical record
· Registration, cancer registration
· Statistics, vital statistics
· Survival rate
1006 HOSPITAL INFORMATION SYSTEMS
Presented at a Workshop On Health Research Priorities Organized By The Research Directorate Of The Ministry Of Health At Jeddah 5-7 June 2010 by Dr Omar Hasan Kasule Sr. MB ChB (MUK), MPH (Harvard) DrPH (Harvard) Professor (Epidemiology and Bioethics) Faculty of Medicine, King Fahd Medical City. Riyadh EM: omarkasule@yahoo.com WEB: http://omarkasule.tripod.com
1.0 MEDICAL RECORDS DEPARTMENT
1.1 The Medical records department is staffed by trained medical record administrators. Its roles are to collect, store, and access information. The information is needed for health care, financial or administrative reasons. The efficiency of the medical records department impacts on clinical care and administration. Quality control is needed to eliminate inaccuracy and inconsistencies. Regular chart review is part of hospital quality assurance. Quality involves both completeness of recording and accuracy.
1.2 Ethical and legal issues arise in medical records departments. The computer revolution enables collection, storage, and retrieval of a lot of information about the patient. In order for this information to be used, it must be readily available to all care-givers. With so many people accessing information the issues of privacy arise in a new form that was not known before the computer age. The problem becomes worse if the data is available on local, regional, or national data net-works.
2.0 THE MEDICAL RECORD
2.1 Medical forms are used to record all medical information and activities: Traditionally medical information was written by hand on various forms each serving a particular purpose. Birth and death certificates are legal documents. The patient's chart consists of admission record, physician notes, psychology notes, social welfare records, laboratory and pathology records, nursing notes, pharmacy records, diet record, dental record, discharge notes, and autopsy records. The forms used are updated regularly to keep up with developments in medical technology and to be user-friendly.
2.2 The Problem oriented medical record was developed to make decision making and follow-up easier. One of the most popular problem-oriented record systems is SOAPIE. SOAPIE is an acronym for Subjective complaints, Objective complaints, Assessment, Plan, Intervention, and Evaluation.
2.3 The electronic medical record (EMR) is becoming popular in many hospitals. Some written records are being scanned to save the time of key-board entry. Physician notes, unlike other types of records, are more difficult to capture in a coded form. This will however be gradually overcome when physicians learn to use check-lists more effectively. EMR enables use of clinical data net-works at the hospital level, the local level (LAN), the national, and the international levels.
2.4 Clinical work station: many hospitals realizing the importance of EMR are experimenting with direct on-line data entry. Computer terminals on wards, laboratories, pharmacies, and other services are used to input data directly into the EMR. For some types of laboratory assays the data is automatically read into the data-base without the necessity of any additional data-input.
2.5 Record linkage: The use of computers, networks and sophisticated software can now enable linkage of many types of records belonging to the same person. The following are examples of linkable records: birth, death, physician, nursing, pharmacy, laboratory, socio-demographic information, and health insurance data. It is conceivable that in the future some personal records like credit-card based purchases of food can also be linked to provide an overall profile of the patient. Some consensus is needed on uniformity of data recording so that record linkage will be easier.
2.6 Integrated medical record: Computer technology makes it possible to develop integrated records. The integration must be patient-centered to be useful clinically and for epidemiological purposes. The integrated record should consist of the following types of records: hospital information system, radiological information system including archiving and retrieval of images, laboratory, blood grouping and cross matching, pharmacy, anesthesia, and surgery.
3.0 PERFORMANCE INDICATORS: PROCESS AND OUTCOMES
3.1 Overview: Clinicians, administrators, and other stake-holders are interested in performance indicators to evaluate health care delivery and make necessary strategic decisions. Two types of indicators are used: process indicators and outcome indicators. Epidemiological methodology is used in the computation and interpretations of various rates of these indicators.
3.2 Process indicators describe the daily routines, work out-put or productivity. These include admission rates, discharge rates, average stay in bed-days, average bed occupancy, number of medical/surgical procedures, prescriptions filled, laboratory assays done, and radiological examinations undertaken. Administrators are interested in process indicators for planning, staffing, and cost-control purposes.
3.3 Outcome indicators describe the end-results of medical intervention. Mortality, morbidity, and chronic disability are commonly-used negative outcome indicators. Positive outcomes such as cure rates can also be used. There is still need for developing consensus on outcome classification to enable uniform reporting. The discharge abstract is the source of the routinely used outcome information. Discharge data can be used to estimate morbidity and mortality due to specific conditions. It can also be used to compare outcomes for various medical or surgical procedures and to compare outcomes across various hospitals or institutions. The clinical data-base and patient profiles can be used to predict the rates and risks of various outcomes. Outcome prediction is more important for critical illnesses. It is interesting to compare the predicted and the actual observed statistics. The data-base can also be used to profile patients and the behavior of caregivers relating them to outcome. The data can also be used to explain the factors leading to various outcomes. Clinical, pathological, and radiological information readily available on line can be used to select predictive factors of certain outcomes.
4.0 HOSPITAL ADMINISTRATION
4.1 Planning and projections: Hospital managers as decision-makers analyze hospital data for use in planning, projections, cost analysis, and assessing accessibility and affordability of the services provided. There is concern sometimes about excess bed capacity or inadequate bed capacity. Decisions may have to be made about hospital closure or hospital mergers. The total staffing as well as the structuring of jobs may have to be changed with changing patient and disease profiles. Both epidemiological and clinical data are used to guide planning and projections. Epidemiological disease rates can enable good estimate of disease burden in the community. They also can be used to detect trends and changes in disease incidence that require changing the total number of beds provided or their mix. Data on discharge diagnoses from the hospital data-base can provide information about trends that are used in planning. Trends in disease occurrence can be identified earlier from hospital than epidemiological data.
4.2 Cost analysis: Hospital administrators are interested in both the total cost of health care services as well as the cost of individual diagnostic categories. They also want to make cost-effectiveness and cost-benefit analyses. This data enables them to cut costs where necessary and also to set reasonable rates for their services. Objective financial decisions are based on high quality data. Cost analyses also affect the behavior of care-givers. Physicians for example would be more restrained in ordering some tests of they knew their true costs. Regression techniques can be used to estimate rates for procedures and services. Epidemiological methodology is used in definition of disease categories and also computing rates for cost analysis. Special epidemiological studies may have to be set up to answer specific questions.
4.3 Access and affordability: Discharge abstract can be used to give information about community utilization of services. For better interpretation financial and demographic information is also used.
4.3 Surveillance: A systematic review of the hospital clinical data-base can reveal conditions that may be missed. It can also catch early trends of changing disease risk. Case-finding can detect undiagnosed or under-treated cases.
Presented at a Workshop On Health Research Priorities Organized By The Research Directorate Of The Ministry Of Health At Jeddah 5-7 June 2010 by Dr Omar Hasan Kasule Sr. MB ChB (MUK), MPH (Harvard) DrPH (Harvard) Professor (Epidemiology and Bioethics) Faculty of Medicine, King Fahd Medical City
4.2 EPIDEMIOLOGIC STUDIES
The availability of a lot of computerized data on individual members of the community has opened up a new area of epidemiological investigation. Healthy individuals undergo clinical, laboratory, and radiological assessment on a regular basis as part of annual physical fitness exercises or as part of disease screening or for purposes of employment, life, and health insurance. Socio-demographic data is collected at the same time. When they fall sick they go to hospitals where their clinical data is recorded. The availability of record linkage will bring together all these records so that etiological relationships can be explored. It is possible to design case control and follow up studies.
5.0 DISEASE REGISTRIES WITH CANCER AS AN EXAMPLE
5.1 DEFINITION and USES
Cancer registration is continuing, systematic collection of data on reportable neoplasms. The data is comprehensive including socio-demographic, clinical, laboratory, radiological, and treatment variables. The cancer registry helps physician in follow-up of patients because it may be the most integrated data source available. It also contributes data to community, regional, or national cancer registries. Data collected within the hospital can be used for hospital-based epidemiological studies.
5.2 METHODOLOGY OF DATA COLLECTION and VALIDATION
The registry obtains information from various sources: pathology logs, discharge summary, death certificates, and clinical diagnoses. When a case is first identified using one data source, the other sources are also examined to validate and complete the picture. The problem of duplication of records may arise because cancer patients are treated and may go into remission. On recurrence of cancer at the same site or at another site, the patient mat be admitted again and may be treated as a new case. The classification of cancer sites is not easy especially where multiple primaries are involved and where secondary cancers occur following immunosuppressive treatment.
5.3 INCIDENCE AND PREVALENCE ANALYSIS
Hospital registry data does not give true incidence rates because one hospital cannot capture all cases of cancer arising from the community. The incidence rates computed from hospital cancer registries are considered minimal rates. If the hospital is a major referral center, it receives cases from far away places which may inflate the incidence rates for the immediate community unless care is taken to eliminate them from the analysis. The following types of analyses can be made: analysis for trends of incidence, analysis for immediate causes of death, analysis of survival, and analysis of treatment trends.
5.4 ETIOLOGICAL STUDIES
The hospital cancer registry is a good source of controls for case control studies of cancer etiology
5.5 OTHER DISEASE REGISTRIES
The following methods are used for public health decision making: operation systems, decision trees, and game theory. Operational research reduces systems and problems to mathematical relations that aid decisions. Statistical modeling can either be based on memoryless distributions such as the Binomial and the poisson or memory distributions such as the Markov process. When the system is too complex to model resort is made to Monte Carlo techniques. Operations research is used in a wide variety of public health applications: health facility management, outpatient appointments, inpatient admission/discharge scheduling, facility sizing, staffing, support services, regulatory health planning, ambulance systems, epidemic control, clinical decision making, program evaluation and policy analysis. Decision making by decision trees uses sequence trees. Game theory is analysis of a decision against the expected. Zero sum games involve 2 persons. The games may be cooperative or non zero sum games.
6.2 PROBLEM SOLVING IN PUBLIC HEALTH
The problem must be defined and its magnitude is determined. The determined are identified. Strategies and priorities are then considered before deciding on a solution that is then implemented. Evaluation must be carried out at the end.
Presented at a Workshop On Health Research Priorities Organized By The Research Directorate Of The Ministry Of Health At Jeddah 5-7 June 2010 by Dr Omar Hasan Kasule Sr. MB ChB (MUK), MPH (Harvard) DrPH (Harvard) Professor (Epidemiology and Bioethics) Faculty of Medicine, King Fahd Medical City
1.0 INTRODUCTION
1.1 Most of vital statistics are from mandatory reporting. As required by law, reports are made on a prescribed form in the prescribed manner. The event must be recorded when and where it occurs. Other sources of vital information are questionnaires, interviews, observations (informal, critical, and controlled), census, and special studies (case histories, surveys).
1.2 Hypotheses can be generated from analysis of vital data for example a cancer mortality map may suggest hypotheses on environmental causes of cancer. Vital data can be analyzed in conjunction with ecologic or environmental data. Vital data is used in cohort analysis to test hypotheses on the effects of exposures early in life. Cohort effects and period effects can be identified from the data.
2.0 BIRTH RATES, RATIOS, and PROPORTIONS
2.1 Birth rates are affected by the level of socio-economic development. Industrialized countries have lower birth rates than developing countries. The birth rate is reflected in the population structure. Countries with high birth rates have relatively more youthful populations. Ascertaining births in developing countries is not complete because of logistic difficulties. There is confusion between rates and proportions in birth statistics.
2.2 The crude birth rates are true rates. The still-birth, premature, low-birth weight rates are actually ratios or proportions and not true rates although they are customarily referred to as rates. Crude Birth Rate is the total number of births per 100,000 of mid-year population per year. Crude Live Birth Rate is the number of live births per 1000 of mid-year population per year.
2.3 Still-birth (fetal death) Rate is the number of fetal deaths above 20 weeks per 1000 births (Live + still births) per year. A still-birth is defined as a fetus delivered weighing at least 500 grams that showed no signs of life during expulsion or extraction from the mother. The corresponding gestational age is 22 weeks and the corresponding body length is 25 cm crown to heel.
2.4 Premature Birth rate is the number of births at gestation age 28-48 weeks per 1000 live births per year. Low birth weight rate is the number of births with weight less than 2500 grams per 1000 live births per year. Very low birth weight rate is the number of births with weight less than 1500 grams per 1000 live births per year
3.0 DEATH (MORTALITY) RATES, RATIOS, and PROPORTIONS.
3.1 OVER-VIEW
Mortality is highest at extremes of life, infancy and old age. At all ages male mortality is higher than female mortality. Mortality of married persons is lower than that of the unmarried. Environmental factors like climate, seasonal variation, urban or rural residence and SES indicators explain some of the variation in mortality rates. There are problems of certification of cause of death. It may not be possible to distinguish immediate from underlying cause of death. Only one main cause is written but we know that several other causes contribute. Some physicians are not serious in certifying death. Final diagnosis from autopsy comes too late for death certification; rarely do death certificates get corrected.
Changes in disease classification ICD revised every 10 years make it difficult to compare and study trends. Differences in diagnostic terminology and development of new diagnostic categories make comparisons difficult. There is confusion in mortality statistics between rates and proportions or ratios. Many proportions are loosely called rates. In deference to common usage we have not made corrections to the terminology but the discerning student should recognize that some of the rates are actually proportions. The general formula for death rates is: # deaths in a year / # of population in that category at mid-year. The formula for proportions does not prescribe any time period.
3.2 CRUDE AND SPECIFIC RATES/PROPORTIONS
The Crude Death Rate is the number of deaths in a year per 100,000 of mid-year population. Crude rates are not very useful. Specific rates are more meaningful. Specific rates are computed by age, gender, and race for purposes of public health analysis, 4 types of rates are used: standardized or adjusted, and specific. Standardized/Adjusted Death Rates take into account the population age and sex structure such that they are comparable with other populations. Age-Specific Death Rates refer to deaths at certain ages that are of public health importance for example infant mortality rate, neonatal mortality rate, post-neonatal mortality rate, and peri-natal mortality rate. The Cause-specific Rate is the number of deaths from a specified cause per 100,000 mid-year population. The cause-specific death ratio is the percentage of deaths from a specific cause used as a comparative measure of death. Autopsy studies have diagnostic accuracy for cause of death but suffer from selection bias Additional special rates are also used. The proportional mortality ratio is akin to the cause-specific rate. It is the number of deaths of a specified kind for example above 50 years of age or due to malaria as a proportion of the total number of deaths in the year. It is used to compare mortality experience across communities.
3.3 SPECIAL RATES
Case-fatality ratio is the proportion of deaths from persons with a specified disease condition.
Fetal deaths: The fetal death ratio is defined as the total fetal deaths in a year as a proportion of the total live births in a year. It is specifically defined as deaths at or below 20 weeks of gestation per 1000 live births thus still birth rate = (number of stillbirths in a year) / (no of live births + number of stillbirths) x 1000. The abortion ratio is the number of induced abortions per 1000 live births.
Infant mortality: IMR is the most important indicator of community health. The Infant Mortality Rate is the number of deaths at ages 0-12 months per 1000 live births per year. Neonatal mortality: Neonatal mortality is due to pre-maturity, congenital anomalies, peri and neonatal care, trauma. The Total Neonatal Mortality Rate is the number of deaths of liveborn infants weighing at least 500 grams (corresponding to 22 weeks of gestation or 25 cm crown to heel length) within 1-27 days of birth per 1000 live births. Thus neonatal mortality = (number of neonatal deaths in a year) / (number of live-borns in a year) x 1000. The neonatal mortality rate has two components, early and late. The Early Neonatal Mortality Rate is the number of deaths within 7 days of birth per 1000 live births per year. The Late Neonatal Mortality Rate is the number of deaths at age 7-27 days of birth per 1000 live births per year. Post Neonatal Mortality Rate is the number of deaths aged 28days -1 year of birth per 1000 live births per year. It reflects the impact of nutrition, sanitation, SES, medical care, and infections. Peri-natal Mortality Rate is the number of deaths from gestation age above 28 weeks up to 7 days of birth per 1000 total births (live and still-born) per year thus perinatal mortality rate = (number of stillbirths in a year + early neonatal deaths in a year) / (number of live births in a year + number of stillbirths in a year) x 1000 . The perinatal mortality ratio is the number of fetal deaths >= 28 weeks + deaths within one week of birth per 1000 live births.
Maternal Mortality Rate is the number of deaths in pregnancy or within 42 days of delivery per 100,000 births. The ideal denominator should be the number of women who were pregnant in the year but this is not customarily done. The following problems arise when live birth is used as the denominator: (a) fetal deaths are excluded thus inflating the maternal mortality rate (b) maternal deaths are counted only once for twin pregnancies. This inflates the MMR. (c) Live births are under-registered in developing countries where the problem of MMR is highest. This serves to inflate MMR (d) maternal death may occur in the year following that of birth and may not be counted.
3.4 INTERPRETATION OF TRENDS IN RATES
The determinants of mortality are: (a) socio economic: age, sex, marital status, family size, income, education (b) health-related behavior: smoking, alcohol, drugs (c) maternal factors: maternal age, parity, child spacing (d) environmental (e) nutrition (f) injuries (g) medical care. Artifactual causes of changing disease trends may be due to (a) misdiagnosis of related diseases for example lung cancer may be misdiagnosed as tuberculosis (b) wrong census denominator. Age-specific death rates follow a U-shape being high in infancy and old age. Neonatal deaths are due to congenital anomalies or delivery complications. Post-neonatal deaths are due to social and environmental factors.
4.0 MARRIAGE & DIVORCE
4.1 The marriage rate is number of marriages in a year per 1000 of population. The divorce rate is defined as number of divorces in a year per 1000 or population or per 1000 marriages. It is wrong to relate divorce rates in a year to marriage rates of the same year because those married do not necessarily divorce in the same year. The age at marriage is measured as mean or median age at marriage. Age at remarriage can be described for the 1st, 2nd, 3rd remarriage.
The rates of marriage and divorce are affected by war, economic depression, recession, and social attitudes.
4.2 The total marriage dissolution rate includes both separation and divorce. Separation is usually not recorded in vital events. The divorce rate can be computed by age, order of marriage, and by marriage duration. The median age at marriage or divorce differs by gender. It is also possible to compute the median duration of marriage. Multi-state life-tables can be used to study marriage and divorce. Marriage leads to lower mortality with males benefiting more than females. This is explained by two factors. The healthier and stable persons are more likely to be selected for marriage. Marriage also ensures psychological and economic support.
5.0 MORIBIDITY RATES
5.1 OVERVIEW
Mandatory reporting of specified diseases has been legislated into law in many countries. Compulsory reporting of infectious disease started in one town in UK
5.2 NOTIFIABLE DISEASES
Infections/communicable diseases: The following are examples of reportable conditions: (a) GIT infections: hepatitis, cholera ,typhoid & paratyphoid, amebic dysentery & bacillary dysentery (b) food poisoning (c) respiratory infections: tuberculosis, diphtheria (d) parasites: malaria (e) sexually transmitted td: syphilis, HIV (f) viral: dengue
5.3 OTHER DISEASES
Accident statistics: (a) industrial accidents (b) non-industrial accidents (road traffic accidents, sports and recreation accidents, home accidents)
5.4 CHILD HEALTH
Child growth & health: The following parameters are used to assess child growth and development in the community: (a) Nutritional status: weight for height, BMI (b) Low birth weight rate (c) Mean length 0-1 year; mean height 1-18 years (d) Mean weight 0-1 year, 1-18 years (e) Chest Circumference (f) % immunized fully. School health: vision defects, hearing defects, and dental defects. Food intake: The following are used to assess food intake: (a) Energy kcal/day (b) Protein g/day (c) Fat g/day (d) Minerals (Ca, Fe)
5.5 HEALTH CARE DELIVERY SYSTEM
Medical facilities & personnel: (a) # hospital beds per 10,000 population (b) Hospital stay: patien-days/100,000 population (c) Bed occupancy: # bed-days per year (d) Admissions and discharges per 100,000 of population (e) # outpatient visits per year (f) Physicians, dentists, pharmacists, midwives, & nurses per 100,000 population.
Hospital statistics: admissions, discharges, diagnoses, and procedures
Presented at a Workshop On Health Research Priorities Organized By The Research Directorate Of The Ministry Of Health At Jeddah 5-7 June 2010 by Dr Omar Hasan Kasule Sr. MB ChB (MUK), MPH (Harvard) DrPH (Harvard) Professor (Epidemiology and Bioethics) Faculty of Medicine, King Fahd Medical City Riyadh EM: omarkasule@yahoo.com WEB: http://omarkasule.tripod.com
1.0 DEFINITION OF BASIC RATES
1.1 INTRODUCTION
Interpretation of demographic rates requires knowledge of the following data: Per capita income/ per capita GDP, Adult literacy, Women of child-bearing age as percentage of all women, Contraceptive use rate, Age and sex structure of population, Urban-rural distribution, Dependent vs economically active population. The factors of fertility are: age and sex distribution of the population, socioeconomic indicators (education, occupation), cultural and religious attitudes, marital status, and duration of marriage. Other factors are: migration, mortality, marriage, and desired family size.
1.2 FERTILITY
The Total Fertility Rate is the number of births per year 1000 women in mid-year population aged 15-44. Age-specific, standardized, and differential fertility rates could be computed. The gross reproductive rate is reproductive rate computed for girls only. The net reproductive rate is the proportion of girls surviving to the reproductive age out of 1000 live births.
Determinants of fertility: exposure to sexual intercourse, exposure to contraception, and gestation & successful parturition. The replacement level is TFR of 2.1. The contraceptive failure rate can be measured using life table methods. Multiple decrement life tables are used to account for competing causes of contraceptive failure.
1.3 MIGRATION
Migration may be internal or international. Migration involves pull factors such as economic opportunities and push factors such as war and persecution. Migrants have particular personal, social, or economic characteristics. Interpretation of migratory studies requires knowledge of the following: (a) pre-migratory environment (b) age at migration (c) selection factors for migration. Migratory studies can be designed to compare migrants with siblings who stayed in the mother country
2.0 POPULATION PYRAMID
2.1 Population composition is important in public health because it can indicate disease risk, risk-related behavior. Data used for demographic analysis is the national census, vital statistics, sample surveys, and qualitative surveys. Demographers describe a population using characteristics that do not change: age, sex, race/ethnicity, marital status, education, and occupation.
2.2 The population pyramid of a country reflects both birth and death rates. The birth rate has a bigger impact on the pyramid that the death rate. The pyramid shows the population structure by age, gender and other variables that may be chosen. The age structure is affected by : fertility, mortality, migration. Developed industrial countries have population pyramids with a narrow base and a wide top. Developing countries have a wide base and a narrow top. Atypical pyramids: Major sudden dislocations like war or genocide could produce atypical pyramids by absence of certain age or sex-groups. Migration of young unmarried laborers produced a bulge in the middle of the pyramid the receiving country while leaving a corresponding crest in the originating country. Migration of families with young children causes widening of the base in the receiving and its narrowing in the sending countries.
2.3 The size and structure of a population is determined by the birth rate, the death rate, and migration. Fertility has a bigger impact on population age structure than mortality. A high proportion of elderly persons with a deficiency of males indicates higher female longevity. A higher proportion of the elderly will lead to increase of the death rate. Cohort analysis of mortality can indicate long term changes in health.
3.0 POPULATION PROJECTIONS
3.1 Population projections are based on fertility, mortality, and migration data. The rate of natural population increase, NI, is the difference between the crude birth rate (CBR) and the crude death rate (CDR). Negative population growth occurs when CDR > CBR. Positive population growth occurs when CBR > CDR. Population replacement requires that each couple, on the average, produces 2 offspring. The rate may be lower than this in situations of immigration.
3.2 Population projections can not be too precise. Estimates of population increase can be made in 6 different ways: (a) arithmetic method: this assumes an increase of the population by a constant amount each year. This could happen in a situation in which the native population registered neither increase nor decrease (zero population growth) and there is regulated immigration of a fixed number every year. (b) Geometric method: this assumes increase of the population by a constant rate every year. (c) Graphic extrapolation: Extrapolations of graphs beyond the area covered by available data can be used to estimate future population assuming continuation of current trends (d) National vital statistics: use of the previous census together with birth, death, and migration data to estimate the population (e) use growth curve formulas.
4.0 DEMOGRAPHIC SHIFT/TRANSITION
This term is generally used to refer to changes in population structure that occur with socio-economic development. They are a consequence of falling birth rates and falling death rates. The proportion of children decreases while that of the elderly increases.
5.0 DEMOGRAPHIC POPULATION LIFE-TABLE
5.1 DEFINITION
The British astronomer Edmund Halley first developed a life-table to describe longevity of 17th century residents of Breslau . In 1815 Joshua Milne published the first exact life table based on mortality in a city in northern England
5.2 CLASSIFICATION
Life tables can be classified as current or cohort (generational) life tables. The current life tables are the ones most often used. Current life tables are constructed by applying current population death rates to a hypothetical population of 100,000. They change every year with the publication of new current death rates. Cohort life tables are constructed by following a given cohort through its life. Death rates appropriate to each age of the cohort are used. Life tables can also be classified according to the factors of attrition. Ordinary life tables show attrition of a cohort from a single factor like death. Multiple decrement tables show attrition from 2 or more attrition factors. Multi-state life-tables describe changing states like marriage, divorce, and how they impact on death. Life tables can be general or can be constructed for different gender, race, and place groups. A complete life table is computed for each single year of age. An abridged table groups the ages instead of using individual years. The life table can be constructed at birth or starting at the exposure to risk. The cause-elimination life table gives life expectancy after removing competing causes of death
5.3 USES
Actuarial, pension computation & annuities, assess/compare health services. Four types of information can be obtained from a life table. It shows life expectancy at birth and at any future age. It shows survival probability which is the probability of survival for a person at a certain age to a given age in the future. Death rates are derived from life tables and are used to compare populations since the rates are inherently age-standardized. The potential years of life lost can be computed as the difference between life expectancy and age at death.
5.4 ADVANTAGES
The life table has several advantages. It enables conversion of age-specific death rates to life expectancies. It is easier to interpret life expectancies than death rates. Life-table death rate is the reciprocal of life expectancy at birth. The life table also enables comparison of different populations independent of the population age distribution. It is therefore possible to compare mortality experiences without going through the troubles of standardization.
5.5 INTERPRETATION OF LIFE EXPECTANCY AT BIRTH
Life expectancy at year of age zero has a special significance. It is called the expectation of life at birth. Life expectancy at birth is a sensitive indicator of the life of the community. It is the single indicator of current death rates. Life expectancy at birth is higher for females than males. IMR is the single most important determinant of life expectancy at birth. Rich industrialized countries have higher life expectancies at birth because of lower IMR. Life expectancy at birth is lower than that at age 1 because of the heavy toll due to IMR in the first year of life. It is possible to compute the conditional probability of survival from one year of age to another by merely dividing the number of survivors at the start of the year of the former by the number of survivors at the start of the year of the latter.