Prevalence, Correlates, and Outcomes of Multimorbidity Among Patients Attending Primary Care in Odisha, India

The results of this study are striking. The inverse relationship between MM and SES comes as a great contrast to other findings from high-income countries.

Explanations such as underdiagnosis and low heath care-seeking among low income populations, and participants with higher income have more risk factors for non-communicable diseases, are true but not sufficient.

For example, tobacco smoking, the biggest risk factors for the three main killers in India according to WHO (ischaemic heart disease, chronic obstructive pulmonary disease and stroke) [1], is more prevalent in poor, less educated, scheduled castes and scheduled tribe populations [2]. It would have been interesting if the authors would have gone into deeper descriptions of ethnicity. "Aboriginal" and "non-aboriginal" were used to describe ethnicity. But India is rich in different ethnicities and the country also adds a degree of complexity with the castes. Additionally, the lower castes are notorious for lower health outcomes and lower life expectancy [3,4].

I am not sure the real take-home message of this article is about the prevalence of multimorbidity in India. To me, it is more about the ever-lasting problem of limited access to health care of unprivileged populations, minorities and/or patients with low socioeconomic status.

Maybe I am joining two distant points together, but multimorbidity acts as a proxy for access to health care rather than a picture of its prevalence in India.

The replies to your article also bring interesting points such as the diseases to include and the methodology to collect them. The issue of multimorbidity in low- and middle-income countries will raise many interesting methodologic questions and will need a different approach to the one we have for higher income countries.

I would like to congratulate the authors of the article. It's been a long time since a study like yours has raised that much enthusiasm and questions in me.

I am looking forward to see more from your team.
Best,
Eric

REFERENCES :
1. Center for disease control. CDC in India. 2015. http://www.cdc.gov/globalhealth/countries/india/pdf/india.pdf (accessed Sept 29, 2015).
2. Rani M, Bonu S, Jha P, Nguyen SN, Jamjoum L. Tobacco use in India: prevalence and predictors of smoking and chewing in a national cross sectional household survey. Tobacco Control 2003;12(4):e4
3. Mohanty SK, Ram F. Life expectancy at birth among social and economic groups in India. IIPS research brief. 2010. http://www. iipsindia.org/pdf/RB-13%20file%20for%20 uploading.pdf (accessed Sept 29, 2015).
4. Editorial. The health of India: a future that must be devoid of caste. Lancet. 2014;384(9958):1901.

FOR CORRESPONDENCE : Dr Eric Contant, MD, CFPC, Sherbrooke University. eric.contant@usherbrooke.ca

Competing interests: None declared

In contrast to many western studies, Pati S and colleagues (2015) found that higher socio-economic status (SES) correlated with greater multimorbidity burden in a recent investigation in India [1]. This was similarly seen in our research in China [2], which is also a middle-income country, bordering on India. We reported that people with higher per capita household income tended to report slightly more multimorbidity. One may speculate that the inverse association between SES and health status would commonly exist in other middle-income countries, where the rapid escalation of medical care costs have been taking place and a general practitioner-based gate-keeper system is absent. This may prevent the vast majority of more socioeconomically deprived populations from being clinically diagnosed with long-term conditions due to unaffordablility and inadequate use of healthcare.

An earlier comment from Richards M at Univerite de Sherbrooke raised a concern of the possible existence of differences in hospital visits by public and private sectors due to the affordability. Evidence from a multi-country analysis among China, Scotland, and Hong Kong that we also recently published [3] supports the hypothesis that the impact of socioeconomic deprivation on the use of health care resources could be associated with the health care system itself. The hospital admission rate in healthcare system where universal coverage has not yet been established and primary care is still being developed was clearly driven by the ability to pay, which may be a common phenomenon in developing countries [3].

Pati S and colleagues (2015) also showed that patients visiting public health care facilities were less likely to have multimorbidity [1]. We previously conducted a study to evaluate patients' experiences in different models of community health centres in China. It showed better patient-reported experiences with respect to first-contact care and coordination of care for government-owned and -managed centres [4]. This may suggest an additional angle to explore the determinants in the process of care delivery that could be associated with multimorbidity outcome. Meanwhile, the challenges from ageing, urbanisation, and increase in prosperity are emergent in many Asian countries [5]. Whether these issues could be fundamentally addressed via redesigning of primary care programmes warrants further exploration.

A high degree of uniformity in the definition and assessment of multimorbidity across different countries is urgently needed. Additional research in the future synthesising more epidemiological evidence from other middle-income developing countries could ultimately lead to the elucidation of the multifaceted links between SES and multimorbidity, and the underlying drivers behind this pattern.

REFERENCES
1. Pati S, Swain S, Hussain MA, Kadam S, Salisbury C. Prevalence, correlates, and outcomes of multimorbidity among patients attending primary care in Odisha, India. Ann Fam Med 2015; 13(5):446-50.
2. Wang HHX, Wang JJ, Wong SYS, Wong MCS, Li FJ, Wang PX, Zhou ZH, Zhu CY, Griffiths SM, Mercer SW. Epidemiology of multimorbidity in China and implications for the healthcare system: cross-sectional survey among 162,464 community household residents in southern China. BMC Med 2014; 12(1):188, 12 pages.
3. Wang HHX, Wang JJ, Lawson KD, Wong SYS, Wong MCS, Li FJ, Wang PX, Zhou ZH, Zhu CY, Yeong YQ, Griffiths SM, Mercer SW. Relationships of multimorbidity and income with hospital admissions in 3 health care systems. Ann Fam Med 2015; 13(2):164-7.
4. Wang HHX, Wong SYS, Wong MCS, Wei XL, Wang JJ, Li DKT, Tang JL, Gao GY, Griffiths SM. Patients' experiences in different models of community health centers in southern China. Ann Fam Med 2013; 11(6):517-26.
5. Wong MCS, Zhang DX, Wang HHX. Rapid emergence of atherosclerosis in Asia: a systematic review of coronary atherosclerotic heart disease epidemiology and implications for prevention and control strategies. Curr Opin Lipidol 2015; 26(4):257-69.

School of Public Health, Sun Yat-Sen University, China (H H X Wang PhD); JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong (H H X Wang, Prof S Y S Wong MD, Prof M C S Wong MD, Prof S M Griffiths FFPH); School of Public Health, Guangzhou Medical University, China (Prof J J Wang MD); General Practice and Primary Care, Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK (H H X Wang, Prof S W Mercer PhD).

FOR CORRESPONDENCE: Stewart W. Mercer, MBChB, PhD, FRCGP, General Practice and Primary Care, Institute of Health and Wellbeing, University of Glasgow, Glasgow G12 9LX, United Kingdom; Stewart.Mercer@glasgow.ac.uk

Competing interests: None declared

Multimorbidity is highly prevalent in high income countries, the growing interest of multimorbidity in a lower middle income country is great news for the prevention of epidemic exacerbation of chronic diseases.

The occidental and indian context are fairly different; In an occidental context, the inclusion of visual difficulty, deafness and chronic back pain in the list of chronic disease would have likely over-represented the multimorbidity in the sample. I would be interested to hear about the authors experience with these conditions in their context.

It has been highlighted by the authors that higher socio-economic status was associated with increased multimorbidity. In the occidental context, salary alone is often not representative of socio-economical status; a combinaison of education level and family income is often used. I would be interested to understand the dichotomic description used for the income level in the analysis and its representativity to population of India.

It was interesting to read about stratified results report for the different age groups and sex. Recent work suggests that a cutoff of three chronic conditions offers a more specific way to identify patient with more complex needs in multimorbidity. It would have been interesting to reports results with both definitions of multimorbidity.

Best Regards, Maxime Sasseville

Competing interests: None declared