臺灣博碩士論文加值系統

Background: Non-communicable diseases (NCDs) are a significant global health issue, leading to 41 million fatalities each year, which represents 74% of all deaths. NCDs, such as cancer, diabetes, and heart disease, are a primary focus of the Sustainable Development Goals (SDGs), aiming to reduce premature NCD deaths by one-third by 2030. In Asia, cardiovascular disease (CVD) caused 10.8 million fatalities in 2019, representing 35% of the total mortality rate and marking a substantial rise from 5.6 million deaths in 2009. The majority of deaths attributed to CVD (87%) were primarily due to ischemic heart disease (47%) or stroke (40%). In Southeast Asia, Myanmar had the highest mortality rate for CVD, followed by Indonesia, while Brunei had the lowest rate, indicating a twofold difference between the highest and lowest rates. In Indonesia, cardiovascular diseases, including stroke, emerged as the leading cause of healthcare expenditure, commanding an annual total of approximately IDR 15.3 trillion, equivalent to 982 million USD. A significant portion of healthcare funds in Indonesia is directed toward managing stroke and heart disease, which are considered catastrophic illnesses.
We examined IFLS data to assess the population attributable fraction for stroke and cardiovascular disease among the adult demographic from 1993 to 2014 (study 1). Additionally, we examined body mass index and hypertension as mediating factors in the association between socioeconomic status (SES) and stroke, as well as the relationship between body mass index, stroke, and heart disease within the adult group (studies 2 and 3).
Methods: The Indonesia Family Life Survey (IFLS) is a continuous longitudinal study conducted in Indonesia to gather data for examining behaviors and outcomes on an individual, household, and community basis. Respondents were randomly selected within these strata to effectively capture Indonesia's socioeconomic diversity and ensure population representation. The survey sample consisted of households and accounted for approximately 83% of the region inhabited by the Indonesian population, covering 13 of the 27 provinces in 1993. The initial study will incorporate data from all waves of the Indonesia Family Life Survey (IFLS), spanning from the first wave in 1993 to the fifth wave in 2014. Subsequent
studies will focus on specific waves, with the second study utilizing data from the fourth wave in 2007 and the fifth wave in 2014, while the third study will concentrate on these same waves.
Results: First study highlighted among fully modifiable risk factors, tobacco consumption consistently exhibits a significant influence across successive waves, with a prevalence exceeding 20% (PAF: >20%), followed by overweight-obesity (prevalence >15%). Factors such as low insurance coverage, limited educational attainment, and urban residency represent partially or fully modifiable risk factors, contributing most significantly to the incidence of stroke and heart disease (PAF: >30%). The prevalence of these risk factors tends to remain stable over time, with no discernible decline in subsequent waves; notably, there is even an upward trend in smoking prevalence, approaching 30%. These findings suggest that the impact of these risk factors on stroke and heart disease may persist more than previously anticipated.
The second study illustrated that unemployed individuals exhibited an adjusted odds ratio (OR) of 1.07 (95% CI: 0.64–1.78) for strokes compared to their employed counterparts. Notably, individuals with lower educational attainment displayed reduced odds of stroke compared to those with higher levels of education, with an adjusted OR (95% CI) of 0.62 (0.39–1.01). Hypertension emerged as the predominant mediator (68%) linking employment status to stroke risk, while body mass index (BMI) played a minor role (19%) in connecting education level to the likelihood of stroke.
In the third study, among 6,688 eligible participants, 334 (5%) were diagnosed with stroke and heart disease in 2014. The incidence rate ratio (IRR) for the probability of stroke and heart disease among individuals with obesity was 2.57 (95% CI: 1.64–4.04) compared to those with normal weight. This elevated probability was particularly pronounced in middle-aged adults (<55 years) rather than older adults (≥55 years), with obese middle-aged adults exhibiting an IRR of 4.18 (95% CI: 2.10–8.31) for stroke and heart disease.
Conclusion: Study one highlights that modified risk factors like BMI, smoking, insurance, and low education contribute to stroke and heart disease in Indonesia. Strengthening national programs is crucial to reduce these risk factors and decrease the prevalence of stroke and heart disease. These findings underscore the need for targeted public health policies. The second study revealed that hypertension plays a significant role in linking employment status to stroke risk, while BMI influences the connection between education level and stroke risk. These findings underscore the importance of policy interventions targeting social determinants such as income inequality, educational disparities, and access to nutritious foods to reduce the incidence of stroke, heart disease, and obesity. The third study identified associations between obesity and stroke and heart disease, particularly among middle-aged adults. Implementing regulations on food and promoting health initiatives focusing on balanced diets and physical activity could be particularly effective in preventing stroke and heart disease among middle-aged adults with higher education levels, employed individuals, and residents of both urban and rural areas.

Background: Non-communicable diseases (NCDs) are a significant global health issue, leading to 41 million fatalities each year, which represents 74% of all deaths. NCDs, such as cancer, diabetes, and heart disease, are a primary focus of the Sustainable Development Goals (SDGs), aiming to reduce premature NCD deaths by one-third by 2030. In Asia, cardiovascular disease (CVD) caused 10.8 million fatalities in 2019, representing 35% of the total mortality rate and marking a substantial rise from 5.6 million deaths in 2009. The majority of deaths attributed to CVD (87%) were primarily due to ischemic heart disease (47%) or stroke (40%). In Southeast Asia, Myanmar had the highest mortality rate for CVD, followed by Indonesia, while Brunei had the lowest rate, indicating a twofold difference between the highest and lowest rates. In Indonesia, cardiovascular diseases, including stroke, emerged as the leading cause of healthcare expenditure, commanding an annual total of approximately IDR 15.3 trillion, equivalent to 982 million USD. A significant portion of healthcare funds in Indonesia is directed toward managing stroke and heart disease, which are considered catastrophic illnesses.
We examined IFLS data to assess the population attributable fraction for stroke and cardiovascular disease among the adult demographic from 1993 to 2014 (study 1). Additionally, we examined body mass index and hypertension as mediating factors in the association between socioeconomic status (SES) and stroke, as well as the relationship between body mass index, stroke, and heart disease within the adult group (studies 2 and 3).
Methods: The Indonesia Family Life Survey (IFLS) is a continuous longitudinal study conducted in Indonesia to gather data for examining behaviors and outcomes on an individual, household, and community basis. Respondents were randomly selected within these strata to effectively capture Indonesia's socioeconomic diversity and ensure population representation. The survey sample consisted of households and accounted for approximately 83% of the region inhabited by the Indonesian population, covering 13 of the 27 provinces in 1993. The initial study will incorporate data from all waves of the Indonesia Family Life Survey (IFLS), spanning from the first wave in 1993 to the fifth wave in 2014. Subsequent
studies will focus on specific waves, with the second study utilizing data from the fourth wave in 2007 and the fifth wave in 2014, while the third study will concentrate on these same waves.
Results: First study highlighted among fully modifiable risk factors, tobacco consumption consistently exhibits a significant influence across successive waves, with a prevalence exceeding 20% (PAF: >20%), followed by overweight-obesity (prevalence >15%). Factors such as low insurance coverage, limited educational attainment, and urban residency represent partially or fully modifiable risk factors, contributing most significantly to the incidence of stroke and heart disease (PAF: >30%). The prevalence of these risk factors tends to remain stable over time, with no discernible decline in subsequent waves; notably, there is even an upward trend in smoking prevalence, approaching 30%. These findings suggest that the impact of these risk factors on stroke and heart disease may persist more than previously anticipated.
The second study illustrated that unemployed individuals exhibited an adjusted odds ratio (OR) of 1.07 (95% CI: 0.64–1.78) for strokes compared to their employed counterparts. Notably, individuals with lower educational attainment displayed reduced odds of stroke compared to those with higher levels of education, with an adjusted OR (95% CI) of 0.62 (0.39–1.01). Hypertension emerged as the predominant mediator (68%) linking employment status to stroke risk, while body mass index (BMI) played a minor role (19%) in connecting education level to the likelihood of stroke.
In the third study, among 6,688 eligible participants, 334 (5%) were diagnosed with stroke and heart disease in 2014. The incidence rate ratio (IRR) for the probability of stroke and heart disease among individuals with obesity was 2.57 (95% CI: 1.64–4.04) compared to those with normal weight. This elevated probability was particularly pronounced in middle-aged adults (<55 years) rather than older adults (≥55 years), with obese middle-aged adults exhibiting an IRR of 4.18 (95% CI: 2.10–8.31) for stroke and heart disease.
Conclusion: Study one highlights that modified risk factors like BMI, smoking, insurance, and low education contribute to stroke and heart disease in Indonesia. Strengthening national programs is crucial to reduce these risk factors and decrease the prevalence of stroke and heart disease. These findings underscore the need for targeted public health policies. The second study revealed that hypertension plays a significant role in linking employment status to stroke risk, while BMI influences the connection between education level and stroke risk. These findings underscore the importance of policy interventions targeting social determinants such as income inequality, educational disparities, and access to nutritious foods to reduce the incidence of stroke, heart disease, and obesity. The third study identified associations between obesity and stroke and heart disease, particularly among middle-aged adults. Implementing regulations on food and promoting health initiatives focusing on balanced diets and physical activity could be particularly effective in preventing stroke and heart disease among middle-aged adults with higher education levels, employed individuals, and residents of both urban and rural areas.

Table of Contents
Abstract i
Acknowledgement iv
List of Figures vi
List of Abbreviation viii
Chapter 1 Introduction 1
1.1. Background 1
1.2. Research Aims, Specific Objectives and General Hypothesis 4
Chapter 2 Literature Review 5
2.1. Overview of global cardiovascular diseases 5
2.2. Overview of cardiovascular diseases in Indonesia 6
2.3. Population attributable fraction for incident stroke and heart disease among the adult population over time (1993-2014) 14
2.4. Body mass index and hypertension as mediating factors in the association between socioeconomic status (SES) and stroke using Med4way analysis 15
2.5. Body mass index Asian population category and stroke and heart disease in the adult population 16
2.6. Studies conceptual frameworks 18
Chapter 3 Methods 21
3.1. Study design and sampling 21
3.2. Survey instruments 22
3.3. Research ethics 23
3.4. Data collection 23
Chapter 4 First Study 25
4.1. Background 25
4.2. Methods 26
4.3. Results 31
4.4. Discussion 33
4.5. Conclusion 38
Chapter 5 Second Study 39
5.1. Background 39
5.2. Methods 41
5.3. Results 53
5.4. Discussion 61
5.5. Conclusions 66
Chapter 6 Third Study 67
6.1. Background 67
6.2. Methods 69
6.3. Results 77
6.4. Discussion 83
6.5. Conclusions 89
Chapter 7 Conclusion 90
References 92

 

List of Figures
Figure 1. The theoretical framework of non-communicable disease 6
Figure 2. Top 10 causes of deaths change 2009–2019, all ages combined in Indonesia 7
Figure 3. Budget allocated for catastrophic diseases in Indonesia, 2022 9
Figure 4. Catastrophic diseases cases in Indonesia, 2022 10
Figure 5. Cardiovascular-related deaths attributable to risk factors in Indonesia, 11
Figure 6. The first study conceptual framework 18
Figure 7. The second study’s conceptual framework 19
Figure 8. The third study’s conceptual framework 20
Figure 9. The Indonesia Family Life Survey Provinces 21
Figure 10. Sample size analysis The Indonesia Family Life Survey 26
Figure 11. Flow chart of the study participants: The Indonesia Family Life Survey 43
Figure 12. Mediation model 49
Figure 13. Causal diagram for mediation and confounding 50
Figure 14. Association for the total effect of employment status and education level on stroke 53
Figure 15. Flow chart of the study participants: The Indonesia Family Life Survey 2007 and 2014 71


List of Tables

Table 1. The Indonesia Family Life Survey (IFLS) data collection 23
Table 2. Risk factors for stroke and heart disease in the IFLS 1993-2014 30
Table 3. Estimates for population attributable fraction and the number of attributable cases of stroke and heart disease. 31
Table 4. Baseline characteristics of the participants by employment status (n = 3,494) in the Indonesia Family Life Survey (IFLS) 2007. 54
Table 5. Baseline characteristics of the participants by education level (n = 3,494) in the Indonesia Family Life Survey (IFLS) 2007. 56
Table 6. The association of socioeconomic status and stroke (n = 3,494) in the Indonesia Family Life Survey (IFLS) 2007 and 2014. 57
Table 7. The association of socioeconomic status and stroke (n = 3,494) by gender in the Indonesia Family Life Survey (IFLS) 2007 and 2014. 58
Table 8. Four-way decomposition of the association employment status (employment: employee [reference] vs. unemployed) and stroke (n = 3,494) in the Indonesia Family Life Survey (IFLS) 2007 and 2014. 60
Table 9. Four-way decomposition of the association education level (education: high [reference] vs. lower) and stroke (n = 3,494) in the Indonesia Family Life Survey (IFLS) 2007 and 2014. 61
Table 10. Baseline characteristics of the participants by BMI, IFLS 2007 78
Table 11. Incidence rate ratio of stroke and heart disease by BMI, IFLS 2007 and 2014 80
Table 12. Incidence rate ratio of stroke and heart disease by BMI, stratified by age, IFLS 2007 and 2014 81
Table 13. Incidence rate ratio of stroke and heart disease and BMI, age <55 years by living areas 82
Table 14. Incidence rate ratio of stroke and heart disease and BMI, age 55 years by living areas 83

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