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The Economics of Type 2 Diabetes in Middle-Income Countries

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The Economics of Type 2 Diabetes in Middle-Income Countries The Economics of Type 2 Diabetes in Middle-Income Countries Till Seuring Doctor of Philosophy (PhD) University of East Anglia, UK Norwich Medical School March 2017 This copy of the thesis has been supplied on condition that anyone who consults it is understood to recognise that its copyright rests with the author and that use of any information derived there from must be in accordance with current UK Copyright Law. In addition, any quotation or extract must include full attribution. Abstract This thesis researches the economics of type 2 diabetes in middle-income coun- tries (MICs). Given the high prevalence of type 2 diabetes in MICs, in-depth country specific analysis is key for understanding the economic consequences of type 2 diabetes. The thesis consists of four studies with the unifying theme of improving the understanding of the causal impact of diabetes on economic out- comes. Study (1) provides an updated overview, critically assesses and identifies gaps in the current literature on the economic costs of type 2 diabetes using a systematic review approach; study (2) investigates the effects of self-reported diabetes on employment probabilities in Mexico, using cross-sectional data and making use of a commonly used instrumental variable approach; study (3) re- visits and extends these results via the use of a fixed effects panel data analy- sis, also considering a broader range of outcomes, including wages and working hours. Further, it makes use of cross-sectional biomarker data that allow for the investigation of undiagnosed diabetes. Study (4) researches the effect of a dia- betes diagnosis on employment as well as behavioural risk factors in China, using longitudinal data and applying an alternative identification strategy, marginal structural models estimation, while comparing these results with fixed effects es- timation results. The thesis identifies a considerable economic burden of diabetes in middle-income countries and uncovers several inequities affecting women, the poor and the uninsured. Biomarker results indicate that the adverse effects are limited to those aware of their diabetes. Finally, women are also found to achieve fewer positive changes of their behavioural risk factors after a diabetes diagnosis than men, offering a potential explanation for their more adverse employment outcomes compared to men. To reduce the economic burden, the groups most affected by the identified inequities should be targeted. Further, the underlying reasons for the found sex differences need to be identified. 2 Contents Abstract 2 List of Figures 4 List of Tables 5 Publications and statement of authorship 6 Acknowledgements 8 Abbreviations 10 1 General introduction 11 Background to the thesis . 12 Types of diabetes . 13 Diabetes complications . 14 Diabetes prevention . 14 The need for further economic research on diabetes . 15 Objectives of the thesis . 15 The economic burden of diabetes across the globe . 16 The labour market impact of type 2 diabetes . 16 Diabetes, behavioural risk factors and employment status . 19 Thesis methods and structure . 21 2 The economic costs of type 2 diabetes: a global systematic review 22 Introduction . 24 Methods . 25 Search strategy . 25 Inclusion and exclusion criteria . 26 Data extraction and analysis . 26 Results . 29 Cost-of-illness studies on type 2 diabetes . 29 The impact of diabetes on employment probabilities and productivity 45 3 Discussion . 59 General findings and developments since the 2004 review of dia- betes COI studies . 59 Labour market studies . 61 Comparison of COI and labour market studies: common themes and lessons learned . 62 Limitations . 64 Conclusion . 65 3 The impact of diabetes on employment in Mexico 66 Introduction . 67 Methodology . 70 Dataset and descriptive statistics . 70 Econometric specification . 72 Results . 76 Probit results . 76 IV results . 76 Differences by age groups . 80 Differences by wealth . 82 Differences by employment type . 84 Conclusion . 86 4 The impact of diabetes on labour market outcomes in Mexico: a panel data and biomarker analysis 89 Introduction . 90 Diabetes and labour market outcomes—existing evidence . 92 Data . 95 Estimation strategy . 98 Panel data on self-reported diabetes . 99 Self-reported diabetes duration . 100 Cross-section: biomarker and self-reported data . 101 Results . 104 Incidence of self-reported diabetes . 104 Duration of self-reported diabetes . 109 Cross-sectional biomarker analysis . 114 Conclusion . 121 5 The relationship between diabetes, employment status and behavioural risk factors: An application of marginal structural models and fixed effects to Chinese panel data 124 Introduction . 126 4 Methods . 130 Study sample . 130 Assessment of diabetes . 131 Assessment of outcomes . 131 Statistical analysis . 132 Results . 139 Discussion . 149 Limitations . 149 Potential mechanisms . 150 Conclusion . 153 6 Discussion and conclusions 154 Chapter overview . 155 Summary of principal findings . 155 Implications for policy making . 159 Inequities in the economic burden of diabetes . 159 Strengths and limitations . 170 Suggestions for future research . 171 Conclusion . 174 References 175 Appendices 200 I Appendix to Chapter 1 201 II Appendix to Chapter 2 215 III Appendix to Chapter 3 252 IV Appendix to Chapter 4 269 V Appendix to Chapter 5 272 5 List of Figures 1 PRISMA flowchart. 27 2 Number of COI studies, by costing approach and income group. 32 3 GDP to direct costs ratio by estimation approach. 38 4 Direct and indirect cost relation in studies estimating total costs of type 2 diabetes. 41 5 Kernel-weighted local polynomial regression of employment status on diabetes duration. 111 6 Kernel-weighted local polynomial regression of log hourly wages on diabetes duration. 112 7 Kernel-weighted local polynomial regression of working hours on diabetes duration. 113 8 Direct acyclic graph for the marginal structural model . 134 9 Direct acyclic graph for the fixed effects model . 137 10 The effect of time since diabetes diagnosis on employment, smoking and alcohol consumption (duration groups) . 147 11 The effect of time since diabetes diagnosis on BMI, waist circum- ference and calorie consumption (duration groups) . 148 A1 Analysis of the effect of time since diabetes diagnosis on overweight and obesity (duration groups) . 287 6 List of Tables 1 Summary of direct costs by estimation approach and income status in international dollars $ (2011) for prevalence-based studies. 36 2 Relationship between direct costs and study characteristics (robust linear regression). 39 3 Incidence studies on the costs of diabetes . 43 4 Country level costs prediction studies . 46 5 Studies estimating the relationship between diabetes and employ- ment (2001 – 2014) . 48 6 Studies estimating the relationship between diabetes and other productivity outcomes (2001 – 2014) . 55 7 Summary statistics for males and females with and without diabetes 71 8 Impact of diabetes on employment probabilities (probit) . 77 9 Impact of diabetes on employment probabilities (bivariate probit) 78 10 Impact of diabetes on employment probabilities (linear IV) . 79 11 Impact of diabetes on employment probabilities by age group (probit) 81 12 Impact of diabetes on employment probabilities by wealth group (probit) . 83 13 Impact of diabetes on employment probabilities by employment status (probit) . 85 14 Descriptive statistics for panel and biomarker sample. 97 15 Self-reported diabetes and labour market outcomes. 106 16 Effect of self-reported diabetes on wages and working hours, by type of work. 107 17 Relationship between self-reported diabetes and selection into types of work. 108 18 Relationship between self-reported years since diagnosis and em- ployment probabilities using continuous duration and duration splines.115 19 Relationship between self-reported years since diagnosis and log hourly wage / weekly working hours using continuous duration and duration splines. 116 7 20 Number of observations with diabetes (HbA1c ≥ 6.5%) and self- reported diabetes. 117 21 Biomarker results . 119 22 Self-reported diabetes, biomarkers, diabetes severity and self-reported health and their association with labour market outcomes . 120 23 Sample means for males and females, by diabetes status . 140 24 Time variant and invariant predictors of a diabetes diagnosis (de- nominator of stabilized weights): logistic regression models . 142 25 Analysis of the effect of a diabetes diagnosis on employment status and behavioural outcomes using MSM, FE and RE . 143 26 Analysis of the effect of each year since diabetes diagnosis on em- ployment status and behavioural outcomes using MSM, FE and RE . 145 A1 Household surveys from low- and middle-income countries includ- ing diabetes information as of 2014 . 202 A2 Country Codes . 218 A2 Country Codes . ..
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