Lancet Glob Health. 2022 Nov;10(11):e1632-e1645. doi: 10.1016/S2214-109X(22)00371-0.
Analysing trends and levels of the burden of disease at the national level can mask inequalities in health-related progress in lower administrative units such as provinces and districts. We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to analyse health patterns in Indonesia at the provincial level between 1990 and 2019. Long-term analyses of disease burden provide insights on Indonesia's advance to universal health coverage and its ability to meet the United Nations Sustainable Development Goals by 2030.
We analysed GBD 2019 estimated cause-specific mortality, years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted life-years (DALYs), life expectancy at birth, healthy life expectancy, and risk factors for 286 causes of death, 369 causes of non-fatal health loss, and 87 risk factors by year, age, and sex for Indonesia and its 34 provinces from 1990 to 2019. To generate estimates for Indonesia at the national level, we used 138 location-years of data to estimate Indonesia-specific demographic indicators, 317 location-years of data for Indonesia-specific causes of death, 689 location-years of data for Indonesia-specific non-fatal outcomes, 250 location-years of data for Indonesia-specific risk factors, and 1641 location-years of data for Indonesia-specific covariates. For subnational estimates, we used the following source counts: 138 location-years of data to estimate Indonesia-specific demographic indicators; 5848 location-years of data for Indonesia-specific causes of death; 1534 location-years of data for Indonesia-specific non-fatal outcomes; 650 location-years of data for Indonesia-specific risk factors; and 16 016 location-years of data for Indonesia-specific covariates. We generated our GBD 2019 estimates for Indonesia by including 1 915 207 total source metadata rows, and we used 821 total citations.
Life expectancy for males across Indonesia increased from 62·5 years (95% uncertainty interval 61·3-63·7) to 69·4 years (67·2-71·6) between 1990 and 2019, a positive change of 6·9 years. For females during the same period, life expectancy increased from 65·7 years (64·5-66·8) to 73·5 years (71·6-75·6), an increase of 7·8 years. There were large disparities in health outcomes among provinces. In 2019, Bali had the highest life expectancy at birth for males (74·4 years, 70·90-77·9) and North Kalimantan had the highest life expectancy at birth for females (77·7 years, 74·7-81·2), whereas Papua had the lowest life expectancy at birth for males (64·5 years, 60·9-68·2) and North Maluku had the lowest life expectancy at birth for females (64·0 years, 60·7-67·3). The difference in life expectancy for males between the highest-ranked and lowest-ranked provinces was 9·9 years and the difference in life expectacy for females between the highest-ranked and lowest-ranked provinces was 13·7 years. Age-standardised death, YLL, and YLD rates also varied widely among the provinces in 2019. High systolic blood pressure, tobacco, dietary risks, high fasting plasma glucose, and high BMI were the five leading risks contributing to health loss measured as DALYs in 2019.
Our findings highlight that Indonesia faces a double burden of communicable and non-communicable diseases that varies across provinces. From 1990 to 2019, Indonesia witnessed a decline in the infectious disease burden, although communicable diseases such as tuberculosis, diarrhoeal diseases, and lower respiratory infections have remained a main source of DALYs in Indonesia. During that same period, however, all-ages death and disability rates from non-communicable diseases and exposure to their risk factors accounted for larger shares of health loss. The differences in health outcomes between the highest-performing and lowest-performing provinces have also widened since 1990. Our findings support a comprehensive process to revisit current health policies, examine the root causes of variation in the burden of disease among provinces, and strengthen programmes and policies aimed at reducing disparities across the country.
The Bill & Melinda Gates Foundation and the Government of Indonesia.
For the Bahasa Indonesia translation of the abstract see Supplementary Materials section.
在国家层面分析疾病负担的趋势和水平可能掩盖省级以下行政单位(如省和区)在健康相关进展方面的不平等。我们利用全球疾病、伤害和风险因素研究(GBD)2019 年的结果,分析了 1990 年至 2019 年印度尼西亚省级卫生模式。长期的疾病负担分析提供了关于印度尼西亚向全民健康覆盖迈进的见解,以及其在 2030 年实现联合国可持续发展目标的能力。
我们分析了 GBD 2019 年估计的 286 种死亡原因、369 种非致命性健康损失原因和 87 种风险因素的特定死亡率、损失生命年(YLLs)、失能生命年(YLDs)、残疾调整生命年(DALYs)、出生时预期寿命、健康期望寿命和风险因素,以及印度尼西亚及其 34 个省从 1990 年至 2019 年的年龄和性别。为了在国家层面生成印度尼西亚的估计数,我们使用了 138 个位置年的数据来估计印度尼西亚特有的人口统计指标,317 个位置年的数据来估计印度尼西亚特有的死亡原因,689 个位置年的数据来估计印度尼西亚特有的非致命性结果,250 个位置年的数据来估计印度尼西亚特有的风险因素,以及 1641 个位置年的数据来估计印度尼西亚特有的协变量。对于次国家一级的估计数,我们使用了以下来源计数:138 个位置年的数据来估计印度尼西亚特有的人口统计指标;5848 个位置年的数据来估计印度尼西亚特有的死亡原因;1534 个位置年的数据来估计印度尼西亚特有的非致命性结果;650 个位置年的数据来估计印度尼西亚特有的风险因素;以及 16 016 个位置年的数据来估计印度尼西亚特有的协变量。我们通过包括 1 915 207 个总源元数据行并使用 821 个总引文,生成了印度尼西亚的 GBD 2019 估计数。
1990 年至 2019 年间,印度尼西亚男性的预期寿命从 62.5 岁(95%置信区间 61.3-63.7)增加到 69.4 岁(67.2-71.6),增加了 6.9 岁。同期,女性的预期寿命从 65.7 岁(64.5-66.8)增加到 73.5 岁(71.6-75.6),增加了 7.8 岁。各省之间的健康结果存在很大差异。2019 年,巴厘岛男性的出生时预期寿命最高(74.4 岁,70.90-77.9),北加里曼丹女性的出生时预期寿命最高(77.7 岁,74.7-81.2),而巴布亚男性的出生时预期寿命最低(64.5 岁,60.9-68.2),北马鲁古女性的出生时预期寿命最低(64.0 岁,60.7-67.3)。男性预期寿命最高和最低的省份之间的差异为 9.9 岁,女性预期寿命最高和最低的省份之间的差异为 13.7 岁。2019 年,各省的年龄标准化死亡率、YLL 和 YLD 率也存在很大差异。高收缩压、烟草、饮食风险、空腹血糖升高和 BMI 升高是 2019 年导致 DALY 健康损失的五个主要风险因素。
我们的研究结果表明,印度尼西亚面临着传染病和非传染病负担的双重负担,而且这种负担在各省之间存在差异。从 1990 年到 2019 年,印度尼西亚的传染病负担有所下降,尽管结核病、腹泻病和下呼吸道感染等传染病仍是印度尼西亚 DALY 的主要原因。然而,在同一时期,所有年龄段的非传染性疾病和接触其风险因素的死亡率和失能率占健康损失的更大份额。自 1990 年以来,高绩效和低绩效省份之间的健康结果差异也有所扩大。我们的研究结果支持对当前卫生政策进行全面审查,检查各省疾病负担差异的根本原因,并加强旨在减少全国各地区差异的计划和政策。
比尔及梅琳达·盖茨基金会和印度尼西亚政府。