Prevalence and correlates of Multimorbidity among older adults in rural Nepal: a cross sectional study

Background Multimorbidity among older adults is an increasing challenge for health systems. Compared to a single disease condition, multimorbidity lowers the quality of life and experience higher hospital admission and health care expenditure. Although multimorbidity has gained global attention, it remains a less studied area in Nepal. Our study aimed to estimate the prevalence of major chronic diseases and multimorbidity among older adults in rural Nepal and examine the associated socioeconomic and behavioral risk factors. Methods We analyzed data of 794 Nepalese older adults recruited using a multi-stage cluster sampling approach in two rural setting of Sunsari and Morang District of Nepal. This was a cross-sectional study, conducted between January to April 2018. Socio-demographics and health conditions data [ Osteoarthritis, Cardiovascular diseases (CVD), Diabetes, Chronic Obstructive Pulmonary Diseases (COPD) ] were collected through the help of trained research assistants using a validated questionnaire. The correlates of multimorbidity were examined using mixed-effects logistic regression. Results 48.9% of the participants had at least one chronic condition, and 14% were multimorbid. The prevalence of individual conditions were osteoarthritis- 41.7%, CVD- 2.39%, diabetes- 5.29%, and COPD-15.7%. In the adjusted model, older adults aged 70-79 years, those from underprivileged Madhesi and other ethnic groups, without a history of alcohol drinking, and those physically inactive, were signicantly associated with multimorbidity. Conclusion Our study found a sizeable proportion of the older adults had multimorbidity in our studied population. This prevalence of multimorbidity and its socioeconomic and behavioural correlates, need to be addressed through multi-level preventive strategies, including clinical guidelines and the development of a multidisciplinary workforce to address the needs of the multimorbid older adults.

Conclusion Our study found a sizeable proportion of the older adults had multimorbidity in our studied population. This prevalence of multimorbidity and its socioeconomic and behavioural correlates, need to be addressed through multi-level preventive strategies, including clinical guidelines and the development of a multidisciplinary workforce to address the needs of the multimorbid older adults.

Background
The population of older adults is increasing globally [1] and is projected to increase to over 1.5 billion by 2050 [2]. A similar demographic transition is occurring in Nepal. The Senior Citizen Act in Nepal 2006, de nes "an individual aged 60 and over as a senior citizen" [3]. In the most recent census in Nepal in 2011, there were 2.5 million population older adults (8.1%). This population is growing at a rate of 3.5% annually, which exceeds the nation's overall population growth rate at 1.35% [4]. While we celebrate longevity [5,6], health and quality of life are two crucial agendas for the older population which signi cantly increases the demand on health services [7][8][9].
Multimorbidity is the simultaneous coexistence of two or more chronic conditions in the same individual [10]. Multimorbidity has a signi cant impact on the quality of life and the demand for health care [11,12].
The impact of multimorbidity is greater than the cumulative effect of the single disease [13]. Individuals with multimorbidity are at substantially greater risk of death compared to those with single conditions [14]. Multimorbidity also adds to the existing challenges of providing quality geriatric health care, especially in developing countries with limited resources.
The prevalence of chronic multimorbidity has increased substantially across the globe, especially among those aged 65+ with a reported prevalence of 33.1% [15]. Longevity, coupled with an increase in incident chronic disease and sedentary and unhealthy lifestyles, suggests that the burden of multimorbidity, especially among the older population, will continue to rise globally [10]. Momentum to recognize and address multimorbidity in clinical settings has increased in many high income countries [16]. However, in developing countries, this emerging public health issue is often overlooked [17]. South Asians are comparatively at an elevated risk for developing cardio-metabolic and other chronic diseases [18], which makes them more susceptible to multimorbidity. The Nepal STEPS survey, 2013 reported that 99.6% of the Nepali adults had at least one (of the eight known risk factors for chronic diseases) [19]. Hence, the burden of multimorbidity among Nepalese is anticipated to be higher. There is, however, comparatively little information on its prevalence. Previously, using data from the 2003 World Health Survey, a 15.2% prevalence of multimorbidity among the Nepali population was estimated, which doubled for the older age groups (30.2%) [20]. Previous research on multimorbidity has mostly focused on quantifying the prevalence [20,21], and has not analysed its association with risk behaviours or underlying social and economic factors.
Although multimorbidity requires a multitude of specialists' referrals, biomedical investigations, and polypharmacy, current health care is based on a single disease approach to treatment, which may not be appropriate to manage patients with multimorbidity. Multimorbidity is challenging for both patients and health professionals, especially in setting priority goals for self-management. As we understand more about the multimorbidity and the inequalities in its burden, subpopulations at risk may be identi ed for preventive strategies. Till date, there has been no speci c study that focused on multi-morbidity in Nepalese older adults. Therefore, this study aimed to assess the prevalence of major chronic diseases and multimorbidity among Nepali older adults and examine the associated socioeconomic and behavioural risk factors.

Study designs and participants
This study was a community based cross sectional study conducted among Nepalese older adults 60 years or older living rural part of Sunsari and Morang districts of Nepal. We recruited study samples using a multi-stage cluster sampling approach and data was collected from 794 study participants through face to face interview. The data collection period was between January to April 2018. Details of the methodology of this study are documented elsewhere [22]. Data were collected using a validated Nepali version survey questionnaire administered through trained research assistant in the eld. Prior to the interview, thumb impressions were obtained from those who were unable to read and write and written informed consent from all literate participants.

Multimorbidity
Co-variates Included independent variable were age; gender; religion; ethnicity; living arrangement; marital status; occupation; literacy status; monthly personal income; alcohol drinking habits; smoking habit; habit of tobacco chewing and physical activity. These co-variates have been described in the previous work published by Yadav et.al [23]. The study protocol was approved by the Ethics Board of Nepal Health Research Council, Government of Nepal, Kathmandu.

Statistical analysis
Stata (Version 13.0). was used to analyze the data. Descriptive analysis was performed on each of the studied variables. Univariate analysis was performed using the chi-square (χ2) test and the variables with p-value <0.2 were included in a mixed-effected logistic regression model. The generalized estimating equation (GEE) approach with 95% con dence intervals (95% CI) was employed to examine the association between multimorbidity and its associated factors.

Results
The mean age of the participants was 69.9 years, and there was equal participation by gender; 50.4% male and 49.6% female. The majority of participants were Hindu (78.7%), illiterate (80.1%), married (53.8%), from indigenous or Madhesi ethnic groups (72.0%), unemployed (54.2%) and had a family income of 44 USD or less at the time of the survey. The majority of the participants were physically inactive (77.1%) and had a history of tobacco smoking (62.2%), but no history of alcohol use (63.4%) ( Table 2).

Prevalence of multimorbidity
The prevalence of the individual chronic diseases and their combinations is presented in Table 2. The prevalence of osteoarthritis, CVD, diabetes, and COPD was 41.7%, 2.4%, 5.3%, and 15.4%, respectively.
While 48.9% of the participants were suffering from at least one chronic condition, 14.7% were suffering from multimorbidity.
Socioeconomic, lifestyle characteristics and multimorbidity Table 3 shows the distribution of multiple morbidities by different socioeconomic and lifestyle characteristics of the participants. The mean age of the participants suffering from multimorbidity was 70.3 years. The prevalence of multimorbidity was similar in both genders (16.8% vs. 12.5%, p=0.09).

Risk factors associated with multimorbidity
Factors associated with multimorbidity, estimated in the crude and adjusted logistic regression model, are shown in Table 4. In the nal adjusted model, age, ethnicity, alcohol drinking habit, and physical inactivity were signi cantly associated with multimorbidity. Individuals in their 70s (70-79 years) had 62% higher odds of multimorbidity (AOR: 1.62; 95% CI: 1.04-2.54; p-value=0.033) compared to the individuals aged 60-69 years. Individuals from the Madhesi and other ethnic groups had a 52% lower probability of multimorbidity than those of the higher caste (AOR: 0.48; 95% CI: 0.31-0.77; p-value=0.002). Unemployed participants had 50% higher odds of multimorbidity than those employed, although the statistical signi cance was at the borderline (p-value = 0.060). Surprisingly, study participants with no alcohol drinking history had around 50% higher probability of multimorbidity than those with a history. However, physically inactive individuals had ve times higher odds of multimorbidity than those with regular physical activities (AOR: 5.02; 95% CI: 1.47-17.17; p-value=0.010).

Discussion
This is the rst study to assess the prevalence and correlates of multimorbidity among older adults in rural Nepal. We found that almost half (48.9%) of the older adults had at least one NCD conditions. Approximately, 15% had multimorbidity -most frequently involving osteoarthritis and COPD. Participant's age and behavioral risk factors (alcohol use and physical inactivity) were associated with multimorbidity.
A sizeable proportion of the older adults had multimorbidity, despite having a mean age of 69.9 years which is low compared to studies in other countries Previous studies of multimorbidity among the Nepalese population are limited, and the only available estimates come from the World Health Survey (2003), which showed a prevalence of 15.2% among the Nepali population, which doubled for the age group 65+ (30.2%) [20]. Since Nepal is in the epidemiologic transition, we would expect to see a higher prevalence of multimorbidity compared to the estimates from 2003 [20]. However, our prevalence estimate (14%) is half that of the 2003 World Health Survey for the older age group. In our study, the possible reasons behind this discrepancy could be due to the measurement of a limited number of common chronic conditions (only four conditions were included) [22], methodological differences, or geographical variation. In this regard, we suggest the need to develop a uniform standardized de nition of multimorbidity, including the speci c conditions to be included. A study from India showed that illiterate participants tend to overestimate health problems when self-reported [24]. In the present context, illiteracy is high among older Nepali adults [4], which may explain the higher prevalence of multimorbidity in the World Health Survey, resulting from overestimates of self-reported conditions. Second, in the study of multimorbidity, the number, and type of chronic conditions included in the count contributed to greater variability in estimates between the studies [25]. Given that the high prevalence of depression among older Nepali adults (50% )[26], the inclusion of depression (included in World Health Survey but not in our study) is likely to explain the higher prevalence of multimorbidity estimated in that survey.
The nding that one in seven older people in the study had multimorbidity is, however, not surprising given the high prevalence of chronic diseases and the increasing rates of physical inactivity and excessive alcohol consumption [19]. These risk behaviors increase the incidence of chronic conditions as well as the progression into multimorbidity from a single condition. The observed prevalence of multimorbidity is of concern because the impact of multimorbidity is greater than the cumulative effects of single disease [13]. Multimorbidity substantially reduces the quality of life and increases the risk of premature death [11,14]. It increases the demand for health care and thus adds to the existing challenges faced by health and social services [11,12].
Signi cant differences in multimorbidity by ethnicity were noted: minority groups, particularly the Madhesi ethnic group, were slightly more likely to suffer from multimorbidity than the upper caste groups. Our nding is consistent with previous literature from Nepal, which documented a higher burden of chronic disease among the Madhesi ethnic group [22,27]. Historically, the Madhesi ethnic group was considered disadvantaged in the society as they were discriminated against by the upper caste groups and had limited access to education and employment [28]. As one of the marginalized groups, these groups have a comparatively lower socioeconomic status increasing threats to their poor outcomes in health and wellbeing [29].
The increased risk of multimorbidity among physically inactive individuals is consistent with other research [30-32]. However, surprisingly, study participants with no prior history of alcohol use had 50% higher odds of multimorbidity than those with alcohol use. The literature on the association between alcohol consumption and multimorbidity has been inconsistent since previous studies have reported lower odds of having multimorbidity among those who consumed alcohol daily [30], whereas other studies found no association between alcohol consumption and multimorbidity [31,33]. Two things may explain the ndings. First, in a society where alcohol consumption is prohibited, self-reported measures of alcohol consumption are not reliable, and participants' responses may be subjected to social desirability bias. Second, in a low-income setting such as ours, the ability to consume alcohol also indicates an individual's purchase capacity and relative wealth. Hence, older adults who could afford to consume alcohol may have had a relatively better socio-economic status that may have provided an advantage to better health in later life.
In light of our ndings, we suggest the need to shift from the approach of treating and management of single conditions to a more integrated approach where patients' needs can be more comprehensively met.
Our study demonstrated the strong association between multimorbidity and physical inactivity, which suggests both the opportunity for early prevention and the need for tailoring the physical activity to the level of disability (especially for osteoarthritis). In this regard, our ndings have implications at the primary health care level as well as at the secondary/tertiary levels, where health care providers can assess physical activity level among the multimorbidity patients and can tailor interventions accordingly to avert the further health consequences among the people with multimorbidity, especially among socioeconomically deprived communities.., Physical activity needs to be mainstreamed in existing community health programs and at all levels of care. We also underscore the need for the attention of policymakers and the implementors to invest more in the development of multidisciplinary management packages for chronic multimorbid conditions. Moreover, we suggest the need for a community based longitudinal study that can look at a large number of conditions with a more precise measurement of the lifestyle factors. Further, we also suggest the need for qualitative research to understand the problems at the individual and population levels, community/family level, and organizational level, which might be help to develop a comprehensive intervention package for people with chronic multimorbid conditions. Some of the strengths of this study include a very high response rate, data collection by trained enumerators who were uent local languages (Maithili/Tharu/Nepali). Limitations included: a) crosssectional design that precludes examination of the cause-effect relationship; b) limited generalizability to younger age groups and geography other than Morang and Sunsari districts of Nepal. Additional limitation includes the inclusion of only four chronic conditions in the de nition of multimorbidity. Further, our lifestyle measures may be subject to social desirability bias.

Conclusions
This study found a high prevalence of multimorbidity among older adults in rural Nepal. There is a need to conduct a more comprehensive, nationally representative study to obtain a more reliable estimate of prevalence and correlates of its multimorbidity. In recent years, there have been increased concerns and commitments from the Nepal government to identify and address the health and social needs of older Nepali adults. As such, the ndings will help policymakers and stakeholders to identify needs, develop preventive strategies and clinical guidelines, and address the needs of a growing multi-morbid older population.  Clinical assessment as evident in the medical records or use of bronchodilators, or self-reported production of sputum for last three months with any smoking history.

Cardiovascular disease
Presence of any of the following conditions: -Hypertension -self-report of diagnosed hypertension; verified by blood pressure level in the provided medical records.
Self-report of heart attack, angina, or "heart trouble" Stroke -self-reported presence of valve disease or taking medications for those.

Osteoarthritis
Self-report of joint pain problems

Multimorbidity
Presence of more than one of the four aforementioned conditions in the same individual. Multimorbidity was then dichotomized as present (i.e. 2-4 conditions) or absent (i.e., single condition) for assessing relationships with the independent variables. 1 Suffering from at least one of the chronic conditions: osteoarthritis, CVD, diabetes, and COPD. 2 Suffering from two or more chronic conditions.

Supplementary Files
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