Correspondence
populations, an economic case2 has been made for immediate action by health-care systems to address the growing complexities of people who might present with several physical or mental health disorders. In addition to this urgency, evidence suggests that the onset of non-communicable diseases (NCDs) might be at a younger age (during peak economically-active years) in low-income and middleincome countries than in high-income countries,3 meaning that the care of patients with multimorbidity (two or more long-term disorders) poses an imminent challenge for all countries. Previously, NCDs and risk factor data needed to inform policy and guide system changes were scarce from low-income and middle-income countries, but this is changing. In a pooled sample of 42 489 people from six middle-income countries during 2007–10, multimorbidity was shown to range from 12% in people aged 18–49 years, to 61% in people aged 70 years and older; in China 20% of people and 35% in Russia had multimorbidity.4 The probability of a person having a disability and depression increases significantly with multimorbidity, even without accounting for dementia (table). Furthermore, prevalence of dementia is high and increasing in developing countries; by 2050, 71% of people with dementia will be living in low-income and middle-income countries. 5
Comorbidities with dementia are high6 and are much less likely to be diagnosed in people in lower-income countries and lower-resource settings than in those in higher-income countries and greater-resource settings. 21st-century health systems worldwide should start counting “past one”1 now, to be ready for the 1·2 billion adults aged 50 years and older who are living in low-income and middle-income countries. PK reports a grant from US National Institute on Aging (R01AG034479) that supported implementation of WHO’s Study on global AGEing and adult health (SAGE). PA, SA, SP, and JJS declare no competing interests. © 2015. World Health Organization. Published by Elsevier Ltd/Inc/BV. All rights reserved.
*Paul Kowal, Perianayagam Arokiasamy, Sara Afshar, Sanghamitra Pati, J Josh Snodgrass [email protected] Study on global AGEing and adult health, WHO, Geneva, CH-1211, Switzerland (PK); University of Newcastle Priority Research Centre for Gender, Health and Ageing, Newcastle, Australia (PK); International Institute for Population Sciences, Mumbai, India (PA); Academic Unit of Primary Care and Population Sciences, Faculty of Medicine, University of Southampton, Southampton, UK (SA); Indian Institute of Public Health Bhubaneswar, Public Health Foundation of India, New Delhi, India (SP); and Department of Anthropology, University of Oregon, Eugene, OR, USA (JJS) 1
2
3
≥1 ADL Unadjusted OR (95% CI)
Banerjee S. Multimorbidity-older adults need health care that can count past one. Lancet 2015; 385: 587–89. Bloom DE, Chatterji S, Kowal P, et al. Macroeconomic implications of population ageing and selected policy responses. Lancet 2015; 385: 649–57. Hunter DJ, Reddy KS. Noncommunicable diseases. N Engl J Med 2013; 369: 1336–43.
Depression* Adjusted OR (95% CI)
Unadjusted OR (95% CI)
Adjusted OR (95% CI)
None† One
2·07 (1·93–2·22)
1·51 (1·38–1·65)
1·77 (1·57–2·01)
1·62 (1·42–1·84)
Two
4·08 (3·78–4·39)
2·47 (2·26–2·72)
2·80 (2·48–3·18)
2·44 (2·14–2·82)
Three
7·28 (6·66–7·92)
3·81 (3·42–4·26)
4·74 (4·12–5·46)
4·05 (3·47–4·75)
≥Four
15·18 (13·58–16·83)
7·21 (6·33–8·17)
8·75 (7·53–10·12)
7·33 (6·24–8·61)
Multilevel logit models were used. Adjusted ORs are controlled for background characteristics (eg, age, sex, living in urban or rural areas, and marital status) and health risk factors (eg, tobacco and alcohol use, physical activity levels, waist-to-hip ratio, and obesity). p
populations, an economic case2 has been made for immediate action by health-care systems to address the growing complexities of people who might present with several physical or mental health disorders. In addition to this urgency, evidence suggests that the onset of non-communicable diseases (NCDs) might be at a younger age (during peak economically-active years) in low-income and middleincome countries than in high-income countries,3 meaning that the care of patients with multimorbidity (two or more long-term disorders) poses an imminent challenge for all countries. Previously, NCDs and risk factor data needed to inform policy and guide system changes were scarce from low-income and middle-income countries, but this is changing. In a pooled sample of 42 489 people from six middle-income countries during 2007–10, multimorbidity was shown to range from 12% in people aged 18–49 years, to 61% in people aged 70 years and older; in China 20% of people and 35% in Russia had multimorbidity.4 The probability of a person having a disability and depression increases significantly with multimorbidity, even without accounting for dementia (table). Furthermore, prevalence of dementia is high and increasing in developing countries; by 2050, 71% of people with dementia will be living in low-income and middle-income countries. 5
Comorbidities with dementia are high6 and are much less likely to be diagnosed in people in lower-income countries and lower-resource settings than in those in higher-income countries and greater-resource settings. 21st-century health systems worldwide should start counting “past one”1 now, to be ready for the 1·2 billion adults aged 50 years and older who are living in low-income and middle-income countries. PK reports a grant from US National Institute on Aging (R01AG034479) that supported implementation of WHO’s Study on global AGEing and adult health (SAGE). PA, SA, SP, and JJS declare no competing interests. © 2015. World Health Organization. Published by Elsevier Ltd/Inc/BV. All rights reserved.
*Paul Kowal, Perianayagam Arokiasamy, Sara Afshar, Sanghamitra Pati, J Josh Snodgrass [email protected] Study on global AGEing and adult health, WHO, Geneva, CH-1211, Switzerland (PK); University of Newcastle Priority Research Centre for Gender, Health and Ageing, Newcastle, Australia (PK); International Institute for Population Sciences, Mumbai, India (PA); Academic Unit of Primary Care and Population Sciences, Faculty of Medicine, University of Southampton, Southampton, UK (SA); Indian Institute of Public Health Bhubaneswar, Public Health Foundation of India, New Delhi, India (SP); and Department of Anthropology, University of Oregon, Eugene, OR, USA (JJS) 1
2
3
≥1 ADL Unadjusted OR (95% CI)
Banerjee S. Multimorbidity-older adults need health care that can count past one. Lancet 2015; 385: 587–89. Bloom DE, Chatterji S, Kowal P, et al. Macroeconomic implications of population ageing and selected policy responses. Lancet 2015; 385: 649–57. Hunter DJ, Reddy KS. Noncommunicable diseases. N Engl J Med 2013; 369: 1336–43.
Depression* Adjusted OR (95% CI)
Unadjusted OR (95% CI)
Adjusted OR (95% CI)
None† One
2·07 (1·93–2·22)
1·51 (1·38–1·65)
1·77 (1·57–2·01)
1·62 (1·42–1·84)
Two
4·08 (3·78–4·39)
2·47 (2·26–2·72)
2·80 (2·48–3·18)
2·44 (2·14–2·82)
Three
7·28 (6·66–7·92)
3·81 (3·42–4·26)
4·74 (4·12–5·46)
4·05 (3·47–4·75)
≥Four
15·18 (13·58–16·83)
7·21 (6·33–8·17)
8·75 (7·53–10·12)
7·33 (6·24–8·61)
Multilevel logit models were used. Adjusted ORs are controlled for background characteristics (eg, age, sex, living in urban or rural areas, and marital status) and health risk factors (eg, tobacco and alcohol use, physical activity levels, waist-to-hip ratio, and obesity). p
