Burden of Communicable and Non-Communicable Diseases Among Elderly in India: A Study Based on LASI Survey

Background: While controlling the outbreak of communicable diseases (CDs) remained a priority, non-communicable diseases (NCDs) are placing an unavoidable burden on the health and social security system. India, a developing nation in South Asia, has seen an unprecedented economic growth in the past few years; however, it struggled to ght the burden of communicable and non-communicable diseases. Therefore, this study aimed at examining the burden of CDs and NCDs among elderly in India. Methods: Data from Longitudinal Ageing Study in India (LASI Wave-I, 2017-18) were drawn to conduct this study. Response variables were the occurrence of CDs and NCDs. The bi-variate and binary logistic regression were used to predict the association between communicable and non-communicable diseases by various socio-demographic and health parameters. Furthermore, to understand the inequalities of communicable and non-communicable diseases in urban and rural areas, the Fairlie decomposition technique was used to predict the contribution toward rural-urban inequalities in CDs and NCDs. Results: Prevalence of communicable diseases was higher among uneducated elderly than those with higher education (31.9% vs. 17.3%); however, the prevalence of non-communicable diseases was higher among those with higher education (67.4% vs. 47.1%) than uneducated elderly. The odds of NCDs were higher among female elderly (OR=1.13; C.I. = 1-1.27) than their male counterparts. Similarly, the odds of CDs were lower among urban elderly (OR=0.70; C.I. = 0.62-0.81) than rural elderly, and odds of NCDs were higher among urban elderly (OR=1.85; C.I. = 1.62-2.10) than their rural counterparts. Results found that education (50%) contributes nearly half of the rural-urban inequality in the prevalence of CDs among the elderly. Education status and current working status were the two signicant predictors of widening rural-urban inequality in the prevalence of NCDs among the elderly. Conclusion: The burden of both CD and NCD among the elderly population requires immediate intervention. The needs Double burden of disease refers to the situation where an individual suffers from both non-communicable and infectious diseases. A study classied the burden of diseases in three broad clusters: communicable diseases, non-communicable diseases, and injuries [7]. Our study examines the responses of communicable and non-communicable diseases only. Following diseases were included as communicable disease: Jaundice/ Hepatitis, Tuberculosis (TB), Malaria, Diarrhoea/gastroenteritis, Typhoid, Urinary Tract Infection, Chikungunya and Dengue. Within non-communicable diseases, following conditions were included: Hypertension or high blood pressure, diabetes or high blood sugar, Cancer or a malignant tumour, Chronic lung diseases such as asthma, chronic obstructive pulmonary disease/Chronic bronchitis or other chronic lung problems, Chronic heart diseases such as Coronary heart disease (heart attack or Myocardial Infarction), congestive heart failure, or other chronic heart problems, Stroke, Arthritis or rheumatism, Osteoporosis or other bone/joint diseases, Any neurological, or psychiatric problems such as depression, Alzheimer’s/Dementia, unipolar/bipolar disorders, convulsions, Parkinson’s, etc. and High cholesterol. All communicable and non-communicable diseases are diagnosed by the health professional. education. The results found that the odds of CDs were lower among higher educated elderly (OR = 0.62; C.I. = 0.47–0.81) than uneducated elderly, and odds of NCDs were higher among higher educated elderly (OR = 1.80; C.I. = 1.37–2.35) than their uneducated counterparts. Similarly, the odds of CDs were lower among urban elderly (OR = 0.67; C.I. = 0.59–0.76) than rural elderly, and odds of NCDs were higher among urban elderly (OR = 1.85; C.I. = 1.62–2.10) than their rural counterparts. The results were insignicant for the association between CDs and wealth index; however, the odds of NCDs were higher among the richest elderly (OR = 1.93; C.I. = 1.63–2.28) than the poorest elderly. The odds of CDs (OR = 0.59; C.I. = 0.51–0.68) and NCDs (OR = 0.47; C.I. = 0.41–0.54) immediate intervention. Among both types of diseases, the NCD is recognized as a more fatal and long-duration disease resulting from a combination and role of physiological, environmental, behavioural, and genetic factors throughout the life cycle. Although NCDs are treatable once diagnosed but as a prolonged health condition due to the sedentary lifestyle, it cannot be halted by providing treatment. The needs of men and women and urban and rural elderly must be addressed through appropriate effort. In a developing country like India, preventive measures, rather than curative measures of communicable diseases, will be cost-effective and helpful.

The LASI featured with 72, 250 individuals, including 31, 434 age 60 years and above and 6,749 individuals age 75 years and above. However, this study taken up 60 years and above population.

The Double Burden Of Communicable And Non-communicable Diseases
Double burden of disease refers to the situation where an individual suffers from both non-communicable and infectious diseases. A study classi ed the burden of diseases in three broad clusters: communicable diseases, non-communicable diseases, and injuries [7]. Our study examines the responses of communicable and non-communicable diseases only. Following diseases were included as communicable disease: Jaundice/ Hepatitis, Tuberculosis (TB), Malaria, Diarrhoea/gastroenteritis, Typhoid, Urinary Tract Infection, Chikungunya and Dengue. Within non-communicable diseases, following conditions were included: Hypertension or high blood pressure, diabetes or high blood sugar, Cancer or a malignant tumour, Chronic lung diseases such as asthma, chronic obstructive pulmonary disease/Chronic bronchitis or other chronic lung problems, Chronic heart diseases such as Coronary heart disease (heart attack or Myocardial Infarction), congestive heart failure, or other chronic heart problems, Stroke, Arthritis or rheumatism, Osteoporosis or other bone/joint diseases, Any neurological, or psychiatric problems such as depression, Alzheimer's/Dementia, unipolar/bipolar disorders, convulsions, Parkinson's, etc. and High cholesterol. All communicable and non-communicable diseases are diagnosed by the health professional.

Response variable
The response variables for this study are communicable diseases and non-communicable diseases. Communicable diseases are diagnosed by health professionals and asked as "In the past 2 years, have you had any of the following diseases?" and responses have been recorded in 'yes' and 'no.' Similarly, non-communicable diseases are also diagnosed by health professionals and asked in the form of 'yes' and 'no.'

Predictors
The predictors for this study are considered as sex (male and female); age (60-69 and 70 years and above); marital status (currently married, never married, Divorced/Separated/Deserted/Widowhood), education (No education, below primary, primary, secondary, and higher); living arrangements (living alone, with spouse and with others); place of residence (rural and urban); currently working (yes and no); wealth index (poorest, poorer, middle, richer and richest); selfrated health (poor and good; physical activity (yes and no); tobacco use (no and yes); alcohol use (yes and no); ADL disability (severe, moderate and no disability), and IADL disability (severe, moderate and no disability). Furthermore, ADL and IADL disability constructed from ve (bathing, dressing, mobility, feeding, and toileting) and seven (preparing a hot meal (cooking and serving), shopping for groceries, making telephone calls, taking medications, doing work around the house or garden, managing money, such as paying bills and keeping track of expenses and getting around or nding an address in an unfamiliar place) activities. Both the ADL and IADL disability was categorized into the three categories as "severe," "moderate," and "no disability" based on the scale given in previous studies [13,14].

Statistical Measures
The analyses were carried out with statistical software STATA version 16th. The bi-variate technique was used to understand the prevalence of communicable diseases and non-communicable diseases by socio-demographic and health parameters and across the states in India. Further, binary logistic regression was used to predict the association between communicable and non-communicable diseases and socio-demographic and health parameters. The equation for binary logistic regression is given below, In the above regression equation, is the probability of being perceived as communicable or non-communicable diseases, , … are the predictors, is the intercept and , … are the coe cients.
Furthermore, to understand the inequalities of communicable and non-communicable diseases in urban and rural areas, the Fairlie decomposition technique was used to predict the contribution toward rural-urban inequalities in CDs and NCDs. The Fairlie technique was rst initiated by Fairlie in 1999 which used to estimate from a logit or probit model. The equation for Fairlie decomposition can be written as, Where N U and N R is the sample size for urban and rural respectively, and are the average probability of a binary outcome of interest for group urban and rural, F is the cumulative distribution function from the logistic distribution, distribution, and are the set of the average value of the independent variable and and are the coe cient estimates for the urban and rural, respectively. Figure 1 depicts the prevalence of CDs among the elderly in India. Almost 15 percent of the elderly reported Diarrhoea and another 8.6 percent reported Malaria. Almost 5.5 percent of the elderly reported Typhoid. Figure 2 depicts the prevalence of NCDs among the elderly in India. Almost one-third of the elderly reported hypertension (32.8%), and another one-fth (19.7%) reported Arthritis. In addition, nearly 14.3 percent reported Diabetes, and 8.5 percent reported chronic lung diseases. Table 1 depicts the prevalence of communicable and non-communicable diseases among the elderly by various socioeconomic and health characteristics of the elderly. Results found that more elderly females reported communicable (26.8% vs. 26.2%) and non-communicable diseases (55.6% vs. 50.3%) than their male counterparts. Prevalence of communicable diseases was higher among uneducated elderly than those with higher education (29.8% vs. 16.6%); however, the prevalence of non-communicable diseases was higher among those with higher education (67.4% vs. 47.1%) than uneducated elderly. Those who reported good self-rated health had a lower prevalence of communicable (24.9% vs. 36.9%) and non-communicable diseases (50% vs. 70.4%) than those who reported poor self-rated health. Similarly, communicable and non-communicable diseases were higher among those who had severe ADL and IADL disabilities.    Table 3  were lower among those with good self-rated health than those with poor self-rated health. The odds of NCDs (OR = 1.16; C.I. = 1.03-1.29) were higher among the elderly with no physical activity than their counterparts. The odds of NCDs were lower among the elderly who had no ADL (OR = 0.52; C.I. = 0.35-0.78) than those who had severe ADL limitations.  Table 4 depicts the rural-urban inequality in the prevalence of CDs among the elderly by various characteristics. Results found that education (50%)

Results
contributes nearly half of the rural-urban inequality in the prevalence of CDs among the elderly. Self-rated health was another signi cant predictor that explained nearly one-sixth (16.01%) of the rural-urban inequality in the prevalence of CDs among the elderly in India. ***p < 0.001; **p < 0.05; *p < 0.10 Table 5 depicts the rural-urban inequality in the prevalence of NCDs among the elderly by various characteristics. Education status and current working status were the two signi cant predictors of widening rural-urban inequality in the prevalence of NCDs among the elderly. On the other hand, wealth index, Self-rated health, and IADL disability were the three factors narrowing down the rural-urban inequality in the prevalence of NCDs among the elderly in India.

Discussion
Our study attempts to assess the prevalence of CDs and NCDs among the elderly and its associated factors. The nding of this study shows that a fatal across countries. Globally, the heart diseases (cardiovascular diseases) has the highest fatality rate among all NCDs and account for nearly 17.9 million death annually which is followed by death because of cancers (9.3 million), chronic lung diseases (4.1 million), and diabetes (1.5 million) [23]. In India, these four NCDs, including stroke, account for nearly 5.8 million deaths annually [15,24]. On the other hand, with these NCDs, the CDs continue to pose a signi cant challenge to India's elderly life.
Corroborating with previous ndings [25,26], the study noted a higher likelihood of NCDs among the female elderly than their male counterparts. In developing countries, including India, women report more about symptoms of their illness than men, which could be attributed to their higher prevalence of disease as outlined in this study [27,28]. Also, it has been noted that females tend to suffer from chronic debilitating conditions but not fatal ones, and this explains the paradox of high morbidity and less mortality among them compared to men [29]. In line with previous studies [26,30], the study noted a higher odds of CDs among rural elderly, whereas the risk of NCDs was higher among urban elderly than their respective counterparts. A sedentary lifestyle and physical inactivity could expose the urban population to a high risk of NCDs [31,32]. Furthermore, nuclear family setup causing loneliness lack of care could be another reason of high NCDs among the urban population [33]. The ndings of higher odds of NCDs among highly educated and richest elderly agree with previous literature [30]. Educated and richest elderly are more likely to follow sedentary lifestyles, which could be a plausible reason for higher NCDs.

Strengths And Limitations
The study has some potential limitations. The study has attempted to ll in the literature gap by examining the CDs and NCDs in a single study among the elderly in India using an extensive nationally representative sample survey-based data. Despite its considerable strength, the study has few signi cant limitations. The cross-sectional nature of data limits our understanding of causal interferences. Moreover, the reporting of NCDs could be affected by the recall bias.

Conclusion
The burden of both CD and NCD among the elderly population requires immediate intervention. Among both types of diseases, the NCD is recognized as a more fatal and long-duration disease resulting from a combination and role of physiological, environmental, behavioural, and genetic factors throughout the life cycle. Although NCDs are treatable once diagnosed but as a prolonged health condition due to the sedentary lifestyle, it cannot be halted by providing treatment. The needs of men and women and urban and rural elderly must be addressed through appropriate effort. In a developing country like India, preventive measures, rather than curative measures of communicable diseases, will be cost-effective and helpful. Declarations Ethics approval and consent to participate: The authors were not involved in data collection process and therefore they did not require any ethical approval or consent to participate. The LASI data is secondary in nature. The data is freely available on request and survey agencies that conducted the eld survey for the data collection have collected a prior consent from the respondent. The ethical clearance was provided by Indian Council of Medical Research (ICMR), India. The survey agencies that collected data followed all the protocols. To maximize the cooperation of the sampled HHs and individuals, participants were provided with information brochures explaining the purpose of the survey, ways of protecting their privacy, and the safety of the health assessments as part of the ethics protocols. As per ethics protocols, consent forms were administered to each HH and age-eligible individual. In accordance with Human Subjects to: datacenter@iips.net for further processing. After successfully sending the mail, individual will receive the data in a reasonable time. Proportion of non-communicable diseases among elderly Non-communicable diseases