Swiss Re Institute Symposium Insurance at the crossroad of technology development and growth opportunities 31 October 2017
This event may be photographed, videotaped, filmed and/or recorded. A summary of the event, pictures and/or a video of the event in which you may appear may be posted and made available on Swiss Re s internal and external websites and in printed materials.
Afternoon Session 2: Challenges of diabetes Subu Subramanian, Harvard T.H. Chan School of Public Health Christoph Nabholz, Head L&H R&D, Swiss Re
Distribution of Diabetes in India S (Subu) V Subramanian, PhD Professor of Population Health and Geography Harvard University SWISS RE INSTITUTE SYMPOSIUM October 31, 2017, Singapore
Scientific Collaborators Daniel Corsi, William Joe, Sunil Rajpal, Akshay Swaminathan Partner
Outline 1. Distribution of Diabetes Mean differences between population groups (e.g., States, Wealth Groups) Dispersion (between-individuals) within population groups 2. Composition of the diabetics (Wealth groups, and Body Mass Index groups) 3. Coverage Gaps 4. Predicting Diabetes
Mean Differences between Groups Data Source: District Level Household and Facility Survey 2013; National Family Health Survey 2015, National Sample Survey Organization 2014
Prevalence of diabetes (2015)
State-wise prevalence of diabetes (2015)
District differences in prevalence of diabetes (2015)
Prevalence of diabetes by household wealth (2013) 16 14 12 10 8 6 4 Non fasting Fasting 2 0 Poorest Q2 Q3 Q4 Richest Wealth
Prevalence of self-reported diabetes by household income (2013) 3.5 3.24% 3 2.5 2 1.5 1.54% 1 0.91% 0.5 0.14% 0.47% 0 Lowest Quintile Second Quintile Third Quintile Fourth Quintile Highest Quintile
Message 1 Diabetes in India strongly patterned by socioeconomic status, and by geography
Between-Individual Differences Data Source: District Level Household and Facility Survey 2013
r=0.77 r=0.72
Wealth-wise dispersion in blood glucose (2013)
Message 2 Richer households have higher mean glucose BUT also have higher variance States/Districts with higher mean glucose also have higher variance
Who are the Diabetics? Data Source: District Level Household and Facility Survey 2013; National Sample Survey Organization 2014
Distribution of Wealth Status Among Diabetics (>140 mg/dl) 2013 ~70% non-poor
Distribution of Wealth Status Among Self-reported Diabetics 2014 85% non-poor
Distribution of BMI categories Among Diabetics (>140 mg/dl) 2013 ~60% High-BMI
Message 3 Majority of the diabetics are better-off individuals; characterized by high body mass index
Coverage Gaps Data Source: National Sample Survey Organization 2014
Percent with insurance (2014) 90 84% 80 70 60 50 40 30 20 10 0 13% Government Insurance 1% 1% 1% Employer Insurance Household Insurance Other Insurance No Insurance
Percent with insurance by income (2014) Insurance Percentage (%) 100 90 80 70 60 50 40 30 Government supported Employer supported Private purchase Any insurance No insurance 20 10 0 Lowest Second Middle Fourth Highest MPCE quintiles
Percent without insurance by states (2014) All India MIZORAM ANDHRA PRADESH TELENGANA KERALA CHHATTISGARH NAGALAND RAJASTHAN TAMIL NADU MEGHALAYA ODISHA D & N HAVELI DELHI WEST BENGAL DAMAN & DIU GUJARAT GOA TRIPURA CHANDIGARH KARNATAKA HIMACHAL JAMMU & KASHMIR HARYANA MAHARASHTRA BIHAR PUDUCHERRY PUNJAB ARUNACHAL JHARKHAND UTTAR PRADESH ASSAM SIKKIM MADHYA PRADESH LAKSHADWEEP MANIPUR A & N ISLANDS UTTARANCHAL 120 100 80 85 83 83 83 86 86 87 87 88 89 91 92 93 93 94 94 94 95 96 96 97 97 98 99 99100100 73 77 78 79 79 60 60 61 40 26 36 39 20 0
Insurance Status Among Diabetics 2014
Message 4 Huge financial burden on households for health care (for chronic conditions this can lead to substantial reductions in household standard of living)
Predicting Diabetes: A Challenge Data Source: District Level Household and Facility Survey 2013; National Family Health Survey 2015
Blood Glucose Distribution (2013) Districts Betweenindividuals Betweenpopulation States
Source: Authors calculation from District Level Household and Facility Survey, 2012-2013, Age standardized for adult men and women 18 years of age and older. r=0.55
Source: Authors calculation from District Level Household and Facility Survey, 2012-2013, Age standardized for adult men and women 18 years of age and older. r=0.36
Source: Authors calculation from District Level Household and Facility Survey, 2012-2013, Age standardized for adult men and women 18 years of age and older. r=0.16
r=0.40 r=0.61 % Diabetes and % Overweight (2015)
Diet and Cardiovascular Events (RR: 0.80) Cardiovascular Events No Yes Total Diet Mediterranean 4997 Control 2450 Total 7159 288 7447 Estruch, Ramón, et al. "Primary prevention of cardiovascular disease with a Mediterranean diet." New England Journal of Medicine 368.14 (2013): 1279-1290.
Diet and Cardiovascular Events (RR: 0.80) Cardiovascular Events No Yes Total Diet Mediterranean 4818 179 (3.5%) 4997 Control 2450 Total 7159 288 7447 Estruch, Ramón, et al. "Primary prevention of cardiovascular disease with a Mediterranean diet." New England Journal of Medicine 368.14 (2013): 1279-1290.
Diet and Cardiovascular Events (RR: 0.80) Cardiovascular Events No Yes Total Diet Mediterranean 4818 179 (3.5%) 4997 Control 2341 109 (4.4%) 2450 Total 7159 288 7447 Estruch, Ramón, et al. "Primary prevention of cardiovascular disease with a Mediterranean diet." New England Journal of Medicine 368.14 (2013): 1279-1290.
Diet and Cardiovascular Events (RR: 0.80) Cardiovascular Events No Yes Total Diet Mediterranean 4818 Control 2341 179 (62%) 109 (38%) 4997 2450 Total 7159 288 7447 Estruch, Ramón, et al. "Primary prevention of cardiovascular disease with a Mediterranean diet." New England Journal of Medicine 368.14 (2013): 1279-1290.
Danaei G, Friedman AB, Oza S, Murray CJL, Ezzati M. Diabetes prevalence and diagnosis in US states: analysis of health surveys. Population Health Metrics. 2009 Sep 25; 7:16 United States
Take Home Message India-wide picture misleading higher socioecnonomic groups (states/individuals) at higher risk 2/3 rd of diabetics are from higher socioeconomic groups Significant unmet need less than 20% have insurance coverage including those from higher socioecnomic groups) Predicting diabetes is challenging (especially at individual level)
Thank You svsubram@hsph.harvard.edu