13 Morbidity Survey

Dr. SAA Latheef

Contents:

1. Definition and Scope of Morbidity

2. Prevalence

2.1. Types of prevalence

2.1.1. Point prevalence

2.1.2. Period prevalence

2.1.3. Life time prevalence

2.2. Applications of prevalence

3.1. Types of incidence

3.1.1. Cumulative incidence

3.1.2. Incidence rate

3.2. Applications of incidence

4. Relationship between incidence and prevalence Summary

Learning Outcomes:

By studying the module you will:

•  learn definition and scope of morbidity;
•  understand the definition, types and applications of prevalence;
•  know the definition, types and applications of incidence; and
•  understand the relationship between prevalence and incidence.

1. Definition and scope of morbidity:

Morbidity is defined as the extent of illness, injury or disability in a defined population (Timmreck, 2002). Terms such as disease, illness, injury, disorder and sickness are grouped under the rubric term of morbidity.

World Health Organization Expert committee on Health statistics proposed the criteria for measuring the morbidity using the information such presence of illness, period or spells of experience of illness and duration of illness (Yerushalmy, 1947). Morbidity data are useful to know the burden of diseases in the community; to set the priorities in public health management; to study the causation; to propose the effective intervention if the causes are avoidable; and to know the efficacy of interventions (Park, 2007, Oslen et al., 2010). Morbidity is measured by disease frequency, duration of disease and severity of disease. Disease frequency is assessed by the prevalence and incidence; duration by disability rate; and disease severity by case fatality rate (Park, 2007 and Bonital et al., 2006).

2. Prevalence: This may be defined as the total number of existing cases (new and old) in a defined population at a given point of time (Bonita et al., 2006).

People at risk include the people who have susceptibility to develop the disease under investigation, for example, susceptibility of the smokers to lung cancer. When the data on population at risk is not available, the population in the study area is considered as denominator. Prevalence of particular disease is studied using a representative sample. Appropriate sample size is calculated for the study. Subjects are recruited by employing randomized sample techniques (cluster, stratified, systematic and purposive). Prevalence can be reported by age, sex, socio-economic status, urban and rural. For comparison of the data, the data is age standardized using standard population of the country or world. The prevalence is expressed per 100 or 1000. For the purpose of illustrating the prevalence study, a study conducted to assess the ischemic heart disease (IHD)( a disease characterized by reduced supply of blood to the heart) in Siliguri, West Bengal, is discussed. In this study, Ischemic heart disease was confirmed by the presence of history of angina or infarction or previously diagnosed disease, affirmative response to the Rose questionnaire and Minnesota codes(electro cardiogram) 1-1, 4-1, 5-9, 5-2 or 9-2. Out of 47 wards, two wards namely 23 and 47 containing a total population of 14,568.Criteria for recruitment into the study were: permanent residence in the chosen ward and aged more than 40 years.

Assuming the expected prevalence of IHD among urban populations in India was 9.6%, accepted prevalence of 6%, confidence interval of 95%, non-response rate of 10%, the calculated sample size was 271. By using updated voters list, a total of 271 subjects were enrolled in the study using systematic random sampling technique.

Two hundred and fifty subjects (response rate 92%) participated in the study. A total of 29 subjects were found to have IHD corresponding to 11.6% prevalence (29/250×100=11.6%) (Mandal et al., 2009)

Several factors like longer duration of disease, prolongation of life of an uncured disease patient, increase in incidence, in-migration of cases and susceptible people, out migration of health people and improved diagnostic facilities were shown to increase the prevalence and vice-versa decrease the prevalence (Bonital et al., 2006).

2.1. Types of Prevalence:

Prevalence is of three types i.e. point prevalence, period prevalence and life time prevalence.

2.1.1. Point Prevalence:

The prevalence data collected at one point of time is referred as point prevalence. Data on point prevalence is useful to check whether any outbreak has occurred in the community. For example, study conducted on usage of antimicrobial agents employing European surveillance of antimicrobial consumption point prevalence survey audit tool on 3 separate days in the study period of two weeks in National centre for cancer care and research, Qatar. It was found that the usage of antimicrobials was 43% with penicillin/beta lactamase inhibitor combinations predominantly (39%) (Hammuda et al., 2013).

2.1.2. Period Prevalence:

Period prevalence is calculated by using numerator ‘total number of cases at any time during a specified period’ and denominator ‘population at risk midway through the period’. For example: study of chronic obstructive pulmonary disease (COPD) patients in UK. COPD( a type of obstructive lung disease characterized by chronically poor airflow) patients admitted to the General Infirmary, St Jame’s University and Killing beck Hospitals, Leeds, were studied for one year period. Eleven patients required intubation (placing of a flexible plastic tube into the trachea (windpipe) to facilitate air way and to serve as a conduit to deliver drugs). Twenty percent of patients had respiratory acidosis (an excessive acid condition of the body fluids). Acidosis was associated with subsequent admission to the intensive care units. In almost half of patients with hypercapnia (abnormally elevated Co2 levels in blood) (kPa>10)(kilo pascle, a unit of pressure),had acidosis. Eighty percent of patients remained acidotic after initial treatment. The calculated prevalence of acidosis was for men (75 (95% CI 61 to 90)/ 100 000/year) and women (57 (95% CI 46 to 69)/100 000/year) respectively. This study also suggested the requirement of non-invasive ventilation for 80% of patients with complaints of acidosis (Plant et al., 2000).

2.1.3. Life time Prevalence:

The total number of persons known to have had the disease for at least some part of their lives, is known as lifetime prevalence. Example: Lifetime prevalence study of psychiatric disorders in South Africa. The data generated in this type of studies are useful for planning mental health services. This study was conducted between January 2002 and June 2004. A three stage probability study design was used in this study. In the first stage, sampling areas were selected, in the second stage, housing unit within sampling area, was selected and in the final stage, adult respondent was randomly chosen. If the selected subject refused to complete the interview, another subject was selected from within the sampling area. For the diagnosis of disorders, World Health Organization’s Composite international Diagnostic interview version 3.0 was used. This tool generates diagnosis according to the criteria of ICD-10(international classification of diseases) and DSM-IV (diagnostic and statistical manual of mental disorders) diagnostic systems. A total of 5089 households, were selected and the authors could interview 4433 households with a response rate of 87%. In the final analysis, data from 4351 household were used. The life time prevalence of various disorders in the following proportions were found: anxiety disorders(15.8%), mood disorders(9.8%), substance use disorder(13.4%) and any disorder(30.3%).Difference in life prevalence of Substance use was observed between racial groups. The earlier median age onset of substance use disorder than anxiety or mood disorders was reported (Stein et al., 2008).

2.2 Applications of prevalence:

Prevalence studies are useful in assessing the burden of diseases, initiating preventive strategies, planning health care infrastructure, identifying high-risk people and finding associations between various variables and diseases. Limitation of prevalence studies is that they are not useful for finding etiology of diseases (Bonita et al., 2006 and Park, 2007).

3. Incidence: It is the rate at which new cases occur in a population.

The incidence is expressed per unit of time (10n can be day, week, month or year). The observation period for the individual in the population is as long as he/she remains disease free. The denominator is calculated by summing all the disease free person time periods during the observation of population at risk.

If the population is large, stable and show low incidence, the denominator is calculated by multiplying the average size of study population by the length of the study period. Each person in the study, add one person year to the denominator for each year (or day, week, month) of observation before the disease develops or the person is lost to follow-up (Bonita et al.,2006).

Example: Incidence of Obesity in children of United States. A cohort of 7738 participants who were in the kindergarten was studied from the period of 1998 to 2007. Their heights and weights were recorded seven times during the study period. At the time of recruitment, 12.4% were obese and 14.9% had overweight. The prevalence of obesity and overweight increased at subsequent years and reached 20.8% obesity and 17% over-weight in the eighth grade. The annual incidence of obesity decreased from 5.4% during kindergarten to 1.7% between fifth and eighth grade. It was hypothesized that incident obesity between the ages of 5 and 14 years was more likely to have occurred at younger ages, primarily among children who had entered kindergarten overweight(Cunnigham et al., 2014).

3.1. Types of incidence: There are two types of incidence i.e. cumulative incidence and incidence rate

3.1.1. Cumulative incidence: This measures the occurrence of new disease. The denominator is measured at the starting time of a study. It shows the probability of individuals in the population developing the disease during a specified period. The synonymous terms used for this indicator in the literature are attack rate, case fatality rate, lethality, risk and incidence proportion (Turner and Hanley, 2010 and Vandenbroucke and Pearce, 2012)

The period of observation can range from years to the life time. It is often presented as cases per 1000 population (Bonita et al., 2006).

For example: Food hypersensitivity study in children of Isle of Wight, U.K. A birth cohort consisting of 969 children were assessed, in their first three years of life, on the prevalence and cumulative food hypersensitivity. These children were asked to undergo skin prick testing (pricking the skin with a needle or pin containing a small amount of the allergen)(Basomba et al., 1985), to foods (milk, egg, wheat, peanut, sesame and fish), aero-allergens (house dust mite Dermatophagoides pteronyssinus, cat and grass) and other allergens if identified by history.

The prevalence of sanitization of food for first, second and third year was 2.2%, 3.8% and 4.5% respectively (cumulative prevalence 5%). The cumulative incidence of 6% (58/969) food hypersensitivity (FHS) was observed among study participants. A cumulative incidence of 5% (48/969) FHS was observed when the study participants were subjected to double blinded, placebo controlled, food challenge(Venter et al., 2007).

3.1.2. Incidence rate: In view of the difficulty in establishing the fixed cohort to follow overtime, dynamic populations in which individuals enter the study at different time periods and leave or lost in follow-up due to death or refuse to remain in the study for other reasons are used. Incidence rate (IR) is useful to take care of these variations in the follow-up of the study (Oslen et al., 2010). IR may be defined as the frequency of new case occurrences of an event in a population at risk of the disease in a period of time. The calculation of this indicator requires details like frequency of new cases, the population at risk and the time period. The range of incidence rate can be from zero to infinite depending on the unit of time used to present person time incidence. IR can be used to construct relative risks and also may apply either when enrolment is at about the same time or spread overtime. IR neither useful as a measure of absolute risk nor can predict population estimates (Bhopal, 2002). IR is also known as force of mortality, force of morbidity, incidence density, hazard and hazard rate (Turner and Hanley, 2010 and Vandenbroucke and Pearce, 2012).

The sum of the time that each person remained under observation and was at risk of becoming a case is referred as person-time at risk. Time is expressed as person-day, person-month, person- years. For example: Nephiritis patients follow-up study in Sweden. Patients with Lupus nephritis(LN)(an inflammation of the kidney caused by systemic lupus erythematosus disease) and anti-neutrophil cytoplasmic antibody associated nephritis(ANN)(necrotized and cresentric glomerulonephritis) from Skane Hospital in Lund and the University Hospital in Linkoping, Sweden were followed for 12 years to study the survival and complications in them. In this study, 28 patients with AAN and 27 with LN were diagnosed. The annual incidence of AAN and LN for aged >18 years per million was estimated to be 13.2 and 4.3 respectively. Thirty-six patients with AAN and two patients with LN were died in the follow-up of the study. Nineteen patients with AAN and one patient with LN had developed the end stage renal disease (Mohammad et al., 2014).

Calculation of person-time at risk is illustrated using modified hypothetical example given in the book entitled “Cancer epidemiology: principles and methods” (Isabel dos Santos Silva, 1999).Nine hypothetical persons with numbers 1-9 were followed from the beginning of 1980 to the end of 1984. Four persons (1-4) were joined at the beginning of the study and each was at risk of developing the disease for the entire five year period. Fifth person joined in 1981 and developed the disease in 1983 and at risk for 3years. Sixth person, who joined in 1980, developed the disease in the mid year of 1982 and at risk for 2.5 years. Seventh person, who joined in 1982, developed the disease by the end of the year and at risk for one year. Eighth person who joined in 1980 was last contacted 1983 at risk for 4 years. Ninth person, who joined in the mid year of 1983 and remained till the end of 1984 and at risk for 1.5 years.

Incidence rate = 3 ( new cases/total person-years at risk)

                             32

                                 = 094 per person year or 9.375 per 100 (0.094 x 100) or 94 per 1000(0.094×1000) person- years

Example 2: One hundred fifty men with impaired glucose tolerance were followed for the time period of four years. After one year, none was diagnosed with diabetes but 50 subjects left the study. In the second year, one developed the disease, but fifty subjects lost in the follow-up. In the third year, four were diagnosed with the disease, 390 subjects left the study. In the fourth year, six had disease but 196 subjects left the study.

It is assumed that subjects with new diagnosis of diabetes and those left the study were considered disease free for half the year and contributed half year to the denominator (CDC, 2012).

Numerator = number of new cases of diabetes = 0 + 1+4+6=11 Denominator=Person years of observation

=(1×1.5)+(4×2.5)+(6×3.5)+(50X0.5)+(50X1.5)+(390X2.5)+(196X3.5) =1.5+10+21+25+75+975+686=1793.5 or rounded up to 1793

Incidence rate =11/1793=0.0061 cases per person years or 0.6134 cases per 100 person years or 6.1 cases per 1000 person years.

3.3. Applications of Incidence:

Incidence is useful to know the occurrence of new diseases and outbreak of epidemics; to assess the risk of becoming ill; to study the acute diseases and etiology in chronic diseases; and to monitor preventive effects. Incidence is not influenced by the duration of diseases (Park, 2007; Oslen et al., 2010; Bonita et al., 2006).

4. Relationship between Prevalence and Incidence:

The relationship between prevalence and incidence is explained by bath model. The inflow of water is compared as incidence and existing water in the bath is given analogy to the prevalence (Park, 2007). Prevalence is compared with a photograph and an incidence to a movie. Prevalence is decreased due to the death or recovery from the disease, migration of ill people and acute nature of diseases. In case of cancer, prevalence is lower when the incidence and duration of disease are stable (Isabel dos Santos Silva, 1999). In fixed populations, prevalence= incidence x average duration of disease. It is not possible to predict prevalence from the incidence, in dynamic populations, due to migration into and out of population, deaths, changing disease rates, change in prognosis and error in measuring the incidence or prevalence (Bhopal, 2002). Incidence is useful in studies dealing with causation of diseases and assessing the burden in short duration, whereas, prevalence studies may be applicable for the studies assessing the burden in diseases of long duration, behavioral variables and disease related risk factors(Bhopal,2002). In the albescence of incidence rate, prevalence rate can be used provided the duration is taken into consideration (Park, 2007)

Summary

• Morbidity is the extent of illness, injury or disability in a defined population
• Morbidity data is useful for public health planning; to assess the burden of disease and to find etiological factors of diseases
• Morbidity is studied by the data of disease frequency, duration of disease and severity of disease.
• Data on disease frequency is contributed by prevalence and incidence studies
• Prevalence is the total number of existing (old and new) cases in a defined population at a given point of time. Prevalence is of three types i.e. point, period and lifetime.
• The total number of case at one point of time is point prevalence; the total number of cases in particular period of time is period prevalence, while, the total number of cases during some time of life is referred as life time prevalence.
• Prevalence data is useful for assessing the magnitude of disease burden; and to plan for public health infrastructure.
• Incidence is the rate at which new cases occur in a population. Incidence is of two type i.e. cumulative incidence and incidence rate.
• Cumulative incidence reveals the probability of the individuals developing the disease in a population. Incidence rate is the frequency of new case occurrences of an event in a population at risk of the disease in a period of time. Incidence data is useful for studying the occurrence of new cases and studying the aetiology of chronic diseases.
• In fixed population, prevalence data depend on the incidence and duration of disease.