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Solid fuel combustion is a significant source of household air pollution (HAP) and an important risk factor for chronic obstructive pulmonary disease (COPD) and various health risks(1–3). Exposure to biomass has been shown to significantly increase the risk of developing COPD (4). Globally, HAP from solid fuels is responsible for an estimated loss of 86 million healthy life years and causes around 3.2 million deaths annually (2).
The United Nations has established the Sustainable Development Goals (SDGs), specifically SDG7, which aims to ensure universal access to affordable, reliable, sustainable, and modern energy (5). In response to economic reforms and rural development programs, there has been a rapid transformation in household energy use in China (6). Despite this progress, existing literature only includes data on the use of cooking solid fuels until 2015, and there is a notable deficiency in recent data and information concerning the utilization of solid fuels for heating (6–8). Additionally, the common practice of “fuel stacking,” where individuals use traditional fuels in conjunction with clean fuels, is prevalent in China (6,9). If evaluations only consider the primary fuel source, the exposure to HAP may be significantly underestimated. Nevertheless, only a limited number of surveys have gathered data on secondary fuel usage.
This study utilized data from the Chinese COPD surveillance to assess the prevalence and changes in the usage of solid fuels for cooking and heating in China between 2014–2015 and 2019–2020. Additionally, the analysis explored the prevalence of primary and partial use of solid fuels for cooking. These insights enhance the accuracy of estimations regarding household solid fuel exposure and inform the development of policies aimed at preventing related diseases.
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The data analyzed were sourced from the Chinese COPD surveillance, which involved participants aged 40 and above from 125 surveillance points in 31 provinces. This research employed a complex, multistage, and probability-based sampling methodology. The detailed information about the study design and participants recruitment has been introduced previously (10). Following the exclusion of participants lacking fuel-related information, the final analyses comprised data from 75,033 participants from the 2014–2015 survey and 74,556 from the 2019–2020 survey.
Data on general characteristics and utilization of solid fuels were collected through a structured questionnaire managed by trained enumerators. Biomass fuels captured in this analysis included charcoal, wood, crop waste, and animal dung, while coal types consisted of kerosene, paraffin, anthracite, and bitumite. Primary cooking solid fuels use is defined as utilizing solid fuels as the main source of energy for cooking. Cooking solid fuels use encompasses both primary and partial use of biomass or coal for cooking. Similarly, heating solid fuels use is described as utilizing biomass or coal for heating purposes. The Gross Domestic Product (GDP) per capita for the year 2014 and 2019 of each county was sourced from the Statistical Yearbook and categorized into four levels — low, lower-middle, upper-middle, and high — based on median values and quartiles. Geographically, the locations were divided into seven regions: North China, East China, Central China, South China, Southwest China, Northwest China, and Northeast China
1 .The weighted rates and 95% confidence intervals (CIs) of solid fuels use across the overall population and various subgroups were calculated. These weights accounted for the survey’s sampling scheme and incorporated post-stratification adjustments to align with the demographic structure of China’s 2020 Census. Taylor series linearization, accommodating the complex sampling design, was employed to estimate the 95% CIs. Differences among subgroups and changes in solid fuels usage from 2014–2015 to 2019–2020 were evaluated using Rao-Scott chi-squared tests. All statistical analyses were performed using SAS software (version 9.4; SAS Institute Inc., Cary, USA), and all tests were two-tailed with a significance threshold set at 0.05.
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In the 2019–2020 survey, 59.6% of the participants lived in urban areas, 38.0% were aged 60 or older, and 46.0% had attained education up to primary school or less. There were no significant differences in the weighted proportions of these characteristics when compared to the 2014–2015 data (P>0.05). The average GDP per capita increased from 48,872.2 Chinese Yuan (CNY) in 2014–2015 to 64,323.1 CNY in 2019–2020 (P<0.001) (Table 1).
Characteristic 2014–2015 2019–2020 P N* %† N* %† Area type Urban 35,666 59.6 34,236 59.6 0.998 Rural 39,367 40.4 40,320 40.4 Age, years 40–49 23,491 29.9 17,635 29.9 1.000 50–59 24,497 32.1 26,325 32.1 60–69 19,858 21.2 22,766 21.2 ≥70 7,187 16.8 7,830 16.8 Ethnicity§ Han 66,768 95.9 66,890 95.2 0.289 Others 8,263 4.1 7,666 4.8 Educational level§ Primary school or below 38,687 48.3 37,674 46.0 0.248 Junior high and above 36,344 51.7 36,882 54.0 Occupation§ Agriculture 34,937 39.6 31,462 32.1 0.004 Others 40,094 60.4 43,094 67.9 GDP per capita, CNY, X (S)¶ 48,872.2 26,815.6 64,323.1 36,773.7 <0.001 Area East 26,453 42.7 25,874 42.7 1.000 Central 22,186 30.6 22,763 30.6 West 26,394 26.7 25,919 26.7 Region North China 10,199 15.9 10,182 15.6 0.679 East China 19,173 29.7 19,243 30.7 Central China 8,978 15.9 9,603 15.3 South China 7,640 8.7 8,067 6.0 Southwest China 12,226 15.2 12,117 18.5 Northwest China 9,027 6.6 8,365 5.6 Northeast China 7,790 8.0 6,979 8.3 Abbreviation: GDP=Gross domestic product, CNY=Chinese Yuan, X=mean, S=standard deviation.
* No. of participants was the unweighted number of subcategories denominator.
† The percentages were weighted.
§ Data missing in survey 2014 for Ethnicity (n=2), Education level (n=2), Occupation (n=2).
¶ P values for GDP per capita were calculated using t test.Table 1. Characteristics of participants in the 2014–2015 and 2019–2020 surveys.
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The usage rates of solid fuels for cooking were 45.3% (95% CI: 38.5%, 52.2%) and 28.0% (95% CI: 22.6%, 33.5%) for the periods 2014–2015 and 2019–2020, respectively. Similarly, the rates for heating were 33.5% (95% CI: 26.2%, 40.7%) and 23.2% (95% CI: 17.1%, 29.2%) for the same periods (Table 2). In the years 2019–2020, 38.0% of residents used solid fuels for either cooking or heating, with 15.8% primarily using solid fuels for cooking (Table 2,
Supplementary Table S1 ). Residents from rural areas demonstrated higher usage rates, with 47.2% using solid fuels for cooking, and 37.7% for heating, respectively, in 2019–2020. The elderly, less educated individuals, and those from regions with a lower GDP had elevated usage rates of solid fuels in 2019–2020 (P<0.05) (Table 2,Supplementary Table S2 ).Characteristic Cooking Heating Primary cooking* 2014–2015 2019–2020 Absolute
change
(%)†2014–2015 2019–2020 Absolute
change
(%)†2019–2020 Rate (95% CI) Rate (95% CI) Rate (95% CI) Rate (95% CI) Rate (95% CI) Overall 45.3
(38.5, 52.2)28.0
(22.6, 33.5)−17.3§
(−22.1, −12.5)33.5
(26.2, 40.7)23.2
(17.1, 29.2)−10.3§
(−17.1, −3.5)15.8
(12.2, 19.4)Residence Urban 30.0
(22.7, 37.3)15.0
(10.6, 19.5)−15.0§
(−21.0, −8.9)23.3
(16.7, 29.9)13.3
(8.2, 18.4)−10.0§
(−17.0, −3.0 )7.3
(4.8, 9.7)Rural 67.9
(61.6, 74.2)47.2
(41.8, 52.6)−20.7§
(−27.0, −14.5)48.4
(37.8, 59.02)37.7
(29.3, 46.1)−10.7§
(−20.1, −1.3)28.5
(23.4, 33.5)χ2 152.721 −¶ 29.463 59.457 495.980 P <0.001 <0.001 <0.001 <0.001 <0.001 Age, years 40–49 39.1
(32.5, 45.6)19.1
(14.8, 23.4)−20.0§
(−25.2, −14.7)30.9
(23.9, 37.9)19.6
(14.1, 25.2)−11.3§
(−18.1, −4.4)9.4
(6.7, 12.2)50–59 43.6
(36.2, 51.0)26.3
(21.3, 31.3)−17.4§
(−22.5, −12.2)34.9
(27.4, 42.4)23.0
(17.0, 28.9)−11.9§
(−19.4, −4.4)12.9
(9.8, 15.9)60–69 51.1
(42.7, 59.5)34.2
(26.8, 41.6)−16.9§
(−22.7, −11.1)34.2
(26.1, 42.4)24.3
(17.5, 31.2)−9.9§
(−17.7, −2.2)19.9
(15.1, 24.7)≥70 52.4
(44.7, 60.1)39.5
(31.6, 47.4)−13.0§
(−20.8, −5.1)34.3
(25.7, 42.9)28.3
(19.9, 36.7)−6.0
(−14.1, 2.1)27.7
(21.3, 34.1)χ2 37.203 132.462 4.943 17.812 174.460 P <0.001 <0.001 0.176 <0.001 <0.001 Educational level Primary school or below 60.1
(54.1, 66.0)42.0
(36.9, 47.0)−18.1§
(−23.3, −12.9)38.3
(29.7, 46.9)31.3
(24.1, 38.5)−7.0§
(−12.9, −1.1)25.8
(21.6, 29.9)Junior high or above 31.5
(24.5, 38.6)16.1
(11.4, 20.9)−15.4§
(−20.0, −10.8)28.9
(21.4, 36.4)16.2
(10.5, 21.8)−12.7§
(−21.1, −4.3)7.3
(4.9, 9.7)χ2 −¶ −¶ 7.124 36.407 −¶ P <0.001 <0.001 0.008 <0.001 0.031 GDP per capita Low 60.1
(51.1, 69.0)40.1
(29.0, 51.1)−20.0§
(−33.1, −6.9)35.2
(20.7, 49.8)34.1
(20.7, 47.4)−1.2
(−16.1, 13.8)25.5
(17.2, 33.8)Lower-middle 62.1
(51.8, 72.3)38.4
(28.8, 48.0)−23.7§
(−34.2, −13.2)33.6
(18.9, 48.3)33.4
(19.2, 47.7)−0.2
(−14.1, 13.8)21.1
(12.9, 29.2)Upper-middle 45.4
(32.1, 58.8)33.9
(28.3, 39.5)−11.5
(−25.7, 2.7)39.4
(25.8, 53.0)30.2
(19.8, 40.6)−9.2
(−24.7, 6.3)20.3
(15.7, 24.9)High 25.1
(15.0, 35.3)12.2
(5.6, 18.8)−12.9§
(−20.1, −5.8)28.3
(13.7, 42.9)7.1
(0.6, 13.7)−21.2§
(−36.0, −6.4)5.0
(1.9, 8.1)χ2 34.856 42.219 1.327 20.121 39.621 P <0.001 <0.001 0.723 <0.001 <0.001 Region North China 25.1
(10.9, 39.3)12.8
(0.0, 25.7)−12.2§
(−15.7, −8.8)53.6
(39.9, 67.2)14.6
(0.5, 28.6)−39.0§
(−57.7, −20.3)8.1
(0.0, 18.1)East China 43.6
(28.9, 58.3)29.5
(19.5, 39.6)−14.1§
(−25.9, −2.2)25.5
(10.8, 40.2)20.8
(8.6, 33.1)−4.6
(−12.7, 3.4)14.1
(7.9, 20.2)Central China 56.3
(40.8, 71.8)22.8
(13.4, 32.2)−33.5§
(−49.5, −17.5)34.0
(19.0, 49.1)26.9
(13.6, 40.1)−7.2
(−19.3, 4.9)12.5
(7.0, 17.9)South China 50.9
(31.8, 70.1)32.6
(16.8, 48.4)−18.3§
(−28.6, −8.1)14.0
(3.0, 25.1)13.3
(1.1, 25.5)−0.7
(−8.4, 6.9)15.7
(7.0, 24.3)Southwest China 51.2
(39.8, 62.6)37.5
(28.6, 46.4)−13.6§
(−23.4, −3.9)22.7
(7.0, 38.3)16.9
(6.2, 27.7)−5.7
(−16.4, 5.0)22.0
(16.0, 28.0)Northwest China 47.9
(26.4, 69.4)30.2
(15.5, 45.0)−17.7§
(−35.0, −0.4)47.7
(26.1, 69.3)50.0
(31.1, 68.8)2.2
(−19.7, 24.1)20.4
(7.6, 33.2)Northeast China 50.8
(31.9, 69.7)34.6
(16.1, 53.1)−16.2§
(−26.6, −5.8)51.7
(34.0, 69.4)44.0
(22.8, 65.1)−7.7
(−20.9, 5.5)26.4
(11.0, 41.8)χ2 10.823 11.786 20.267 15.052 10.741 P 0.094 0.067 0.003 0.020 0.097 Note: The difference in the rate of solid fuels use between 2014–2015 and 2019–2020 was tested using Rao−Scott χ2.
* Primary cooking solid fuels means that using solid fuels as primary energy for cooking.
† Absolute change equals prevalence in 2019 minus prevalence in 2014.
§ means P<0.05.
¶ The value of Rao−Scott χ2 could not be calculated.Table 2. Rates and changes in solid fuels use for cooking and heating from 2014–2015 to 2019–2020, and the prevalence of primary solid fuels use for cooking in 2019–2020 among residents aged 40 and older in China, categorized by residence, age, educational level, GDP per capita, and region.
The use of solid fuels for cooking decreased by 17.3%. This significant reduction was observed across all regions, with Central China experiencing the most substantial decrease of 33.5%. Similarly, the use of solid fuels for heating fell by 10.3%, although only North China demonstrated a significant decline, dropping from 53.6% to 14.6% (Table 2).
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The prevalence of cooking biomass utilization was recorded at 35.5% (95% CI: 29.2%, 41.8%) and 24.0% (95% CI: 18.8%, 29.1%), while heating biomass utilization stood at 8.4% (95% CI: 5.1%, 11.7%) and 10.1% (95% CI: 6.5%, 13.8%) in the periods 2014–2015 and 2019–2020, respectively. Both surveys indicated higher biomass use for cooking and heating in rural areas, among elderly populations, those with lower educational attainment, and in regions with lower GDP per capita (P<0.05).
The use of biomass for cooking decreased by 11.5%, with significant reductions observed in all regions except East China. Specifically, biomass use for heating increased by 9.2% in South China and 7.0% in Central China, while it decreased by 6.2% in Northeast China and 2.8% in North China (Table 3).
Characteristic Cooking Heating 2014–2015 2019–2020 Absolute
change (%)*2014–2015 2019–2020 Absolute
change (%)*Rate (95% CI) Rate (95% CI) Rate (95% CI) Rate (95% CI) Overall 35.5 (29.2, 41.8) 24.0 (18.8, 29.1) −11.5† (−15.6, −7.5) 8.4 (5.1, 11.7) 10.1 (6.5, 13.8) 1.7 (−0.7, 4.2) Residence Urban 21.0 (15.2, 26.7) 11.6 (7.8, 15.3) −9.4† (−14.4, −4.4) 3.8 (1.5, 6.2) 5.8 (2.4, 9.2) 2.0† (−0.1, 4.1) Rural 56.9 (49.3, 64.6) 42.3 (36.5, 48.1) −14.6† (−21.7, −7.5) 15.2 (9.6, 20.7) 16.5 (11.4, 21.6) 1.3 (−3.6, 6.3) χ2 122.638 −¶ 35.743 20.685 P <0.001 <0.001 <0.001 <0.001 Age, years 40–49 28.4 (23.2, 33.6) 15.0 (11.2, 18.7) −13.5† (−17.1, −9.8) 6.7 (3.8, 9.5) 7.3 (4.0, 10.5) 0.6 (−1.7, 2.9) 50–59 33.6 (27.0, 40.1) 22.0 (17.4, 26.7) −11.5† (−15.8, −7.3) 8.1 (4.9, 11.3) 9.4 (6.1, 12.7) 1.3 (−0.9, 3.5) 60–69 42.4 (34.0, 50.8) 30.3 (23.2, 37.3) −12.1† (−17.5, −6.8) 8.8 (5.7, 11.9) 11.4 (7.4, 15.4) 2.6† (−0.1, 5.3) ≥70 43.1 (35.4, 50.7) 35.7 (27.9, 43.5) −7.3 (−15.1, 0.4) 11.6 (5.9, 17.3) 15.0 (9.1, 21.0) 3.4 (−2.8, 9.6) χ2 58.384 169.536 20.045 35.931 P <0.001 <0.001 <0.001 <0.001 Educational level Primary school or below 49.5 (43.3, 55.7) 37.0 (31.7, 42.4) −12.5† (−17.4, −7.5) 12.4 (7.9, 16.9) 16.1 (10.7, 21.4) 3.7† (−0.2, 7.5) Junior high or above 22.4 (16.8, 28.1) 12.9 (8.8, 16.9) −9.6† (−12.9, −6.3) 4.7 (2.4, 7.0) 5.1 (2.9, 7.3) 0.4 (−1.0, 1.9) χ2 −¶ −¶ 67.479 178.330 P <0.001 <0.001 <0.001 <0.001 GDP per capita Low 49.2 (38.5, 59.9) 35.3 (24.1, 46.5) −13.9 (−27.9, 0.0) 8.8 (3.6, 14.0) 12.0 (6.0, 18.0) 3.2 (−2.5, 9.0) Lower-middle 49.6 (40.6, 58.7) 30.8 (20.0, 41.5) −18.8† (−28.2, −9.5) 11.4 (4.9, 17.8) 13.8 (2.3, 25.3) 2.5 (−9.1, 14.0) Upper-middle 34.7 (23.0, 46.3) 30.0 (24.4, 35.5) −4.7 (−17.2, 7.9) 14.8 (4.2, 25.5) 17.7 (9.7, 25.7) 2.9 (−9.7, 15.4) High 18.4 (9.2, 27.6) 10.4 (4.3, 16.6) −8.0† (−13.6, −2.4) 1.7 (0.0, 3.5) 1.8 (0.0, 3.9) 0.1 (−1.1, 1.2) χ2 29.242 28.512 14.032 16.269 P <0.001 <0.001 0.003 0.001 Region North China 15.5 (2.5, 28.5) 10.5 (0.0, 21.9) −5.0† (−8.5, −1.5) 3.6 (0.0, 9.4) 0.8 (0.0, 1.6) −2.8† (−8.8, 3.2) East China 33.3 (21.8, 44.7) 25.0 (15.3, 34.6) −8.3 (−17.1, 0.5) 6.4 (0.0, 14.3) 8.2 (1.0, 15.4) 1.8 (−2.3, 5.9) Central China 38.1 (23.7, 52.4) 18.1 (9.4, 26.8) −20.0† (−33.1, −6.8) 13.2 (4.3, 22.0) 20.2 (6.2, 34.2) 7.0† (−0.9, 15.0) South China 44.4 (26.7, 62.1) 27.6 (13.2, 42.0) −16.8† (−26.0, −7.5) 4.0 (0.9, 7.1) 13.2 (1.1, 25.3) 9.2† (−1.2, 19.7) Southwest China 43.9 (31.3, 56.5) 34.0 (24.6, 43.3) −9.9† (−19.9, 0.0) 7.4 (2.4, 12.4) 9.5 (2.9, 16.1) 2.1 (−4.2, 8.5) Northwest China 40.6 (19.5, 61.7) 20.7 (9.4, 31.9) −19.9† (−35.5, −4.3) 6.8 (0.0, 17.5) 6.6 (0.5, 12.7) −0.2 (−6.2, 5.7) Northeast China 48.5 (30.0, 67.0) 33.7 (15.2, 52.2) −14.8† (−26.1, −3.5) 24.2 (15.2, 33.1) 18.0 (6.9, 29.1) −6.2† (−13.9, 1.5) χ2 12.863 13.123 13.992 17.483 P 0.045 0.041 0.030 0.008 Note: The difference in the rate of biomass use between 2014–2015 and 2019–2020 was tested using Rao−Scott χ2.
* Absolute change is calculated as the prevalence in 2019 minus the prevalence in 2014.
† means P<0.05.
¶ The value of Rao−Scott χ2 could not be calculated.Table 3. Rates and changes in biomass usage for cooking and heating among residents aged 40 and above in China, from 2014–2015 to 2019–2020, categorized by residence, age, educational level, GDP per capita, and region.
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The utilization rates of cooking coal decreased from 15.4% (95% CI: 10.8%, 19.9%) in 2014–2015 to 6.8% (95% CI: 4.6%, 9.0%) in 2019–2020. Likewise, the rates for heating coal use declined from 25.0% (95% CI: 18.3%, 31.8%) in 2014–2015 to 13.0% (95% CI: 8.4%, 17.6%) in 2019–2020. In 2019–2020, higher utilization rates of both cooking and heating coal were observed among rural residents, individuals with lower educational attainment, and regions with lower GDP per capita.
The utilization of cooking coal decreased by 8.6%, with significant reductions observed across all regions except South China and Northwest China. Usage of heating coal also fell by 12.0%, with significant decreases in all regions except Northwest China. North China registered the largest drop, from 50.0% to 13.8% (Table 4).
Characteristic Cooking Heating 2014–2015 2019–2020 Absolute
change (%)*2014–2015 2019–2020 Absolute
change (%)*Rate (95% CI) Rate (95% CI) Rate (95% CI) Rate (95% CI) Overall 15.4 (10.8, 19.9) 6.8 (4.6, 9.0) −8.6† (−12.1, −5.1) 25.0 (18.3, 31.8) 13.0 (8.4, 17.6) −12.0† (−18.6, −5.5) Residence Urban 13.0 (8.2, 17.8) 5.2 (3.1, 7.4) −7.7† (−11.9, −3.6) 19.5 (13.5, 25.4) 7.5 (3.9, 11.0) −12.0† (−18.2, −5.9) Rural 18.9 (13.0, 24.9) 9.1 (6.1, 12.1) −9.9† (−14.6, −5.1) 33.3 (23.4, 43.1) 21.2 (14.1, 28.4) −12.0† (−21.5, −2.5) χ2 4.647 8.925 13.654 37.030 P 0.031 0.003 <0.001 0.003 Age, years 40-49 15.3 (10.5, 20.0) 6.0 (3.7, 8.4) −9.2† (−13.3, −5.1) 24.2 (17.8, 30.7) 12.4 (7.9, 16.8) −11.9† (−18.3, −5.4) 50-59 15.6 (11.0, 20.2) 6.8 (4.7, 8.8) −8.8† (−12.6, −5.1) 26.8 (19.5, 34.0) 13.6 (8.8, 18.4) −13.2† (−20.6, −5.8) 60-69 15.2 (10.8, 19.5) 7.1 (4.7, 9.5) −8.1† (−11.7, −4.5) 25.5 (18.1, 32.8) 12.9 (7.9, 17.9) −12.6† (−19.7, −5.4) ≥70 15.5 (9.1, 21.8) 7.8 (4.4, 11.2) −7.7† (−12.9, −2.4) 22.6 (15.3, 30.0) 13.3 (7.6, 18.9) −9.4† (−15.9, −2.9) χ2 0.088 3.444 6.004 1.024 P 0.993 0.328 0.111 0.796 Educational level Primary school or below 17.7 (12.1, 23.4) 8.9 (6.0, 11.9) −8.8† (−13.1, −4.5) 25.9 (18.8, 33.0) 15.3 (10.0, 20.5) −10.7† (−16.4, −4.9) Junior high or above 13.2 (9.0, 17.3) 5.0 (3.1, 6.8) −8.2† (−11.7, −4.7) 24.2 (16.8, 31.7) 11.1 (6.4, 15.8) −13.1† (−21.3, −5.0) χ2 6.139 21.611 0.365 4.673 P 0.013 <0.001 0.546 0.031 GDP per capita Low 17.2 (7.7, 26.7) 8.4 (2.7, 14.1) −8.8† (−15.6, −2.1) 26.5 (13.8, 39.2) 22.1 (10.4, 33.7) −4.4 (−18.2, 9.4) Lower-middle 21.4 (11.3, 31.6) 11.7 (5.9, 17.4) −9.8† (−19.9, 0.3) 22.2 (10.5, 34.0) 19.6 (8.4, 30.7) −2.6 (−14.9, 9.6) Upper-middle 15.7 (4.5, 26.9) 7.5 (3.1, 12.0) −8.1 (−19.9, 3.6) 24.5 (13.2, 35.9) 12.5 (3.7, 21.3) −12.0 (−25.1, 1.1) High 9.9 (3.9, 15.9) 2.8 (1.0, 4.5) −7.1† (−12.7, −1.6) 26.6 (12.1, 41.0) 5.3 (0.0, 10.8) −21.2† (−35.8, −6.7) χ2 3.813 11.780 0.311 9.067 P 0.282 0.008 0.958 0.028 Region North China 15.5 (7.8, 23.3) 5.2 (0.0, 10.5) −10.4† (−14.2, −6.6) 50.0 (36.6, 63.4) 13.8 (0.6, 27.1) −36.2† (−56.7, −15.8) East China 16.6 (5.6, 27.6) 7.7 (2.9, 12.4) −9.0† (−17.5, −0.4) 19.1 (6.8, 31.4) 12.7 (2.6, 22.7) −6.5 (−14.6, 1.7) Central China 23.8 (10.9, 36.8) 6.4 (2.2, 10.5) −17.5† (−31.4, −3.5) 20.9 (8.2, 33.5) 6.6 (1.3, 12.0) −14.2† (−26.0, −2.4) South China 11.6 (2.0, 21.3) 8.0 (2.7, 13.3) −3.6 (−15.3, 8.0) 10.1 (1.3, 18.9) 0.1 (0.0, 0.3) −10.0† (−19.2, −0.8) Southwest China 10.8 (0.0, 21.8) 5.8 (0.7, 10.9) −5.0† (−12.5, 2.5) 15.3 (0.7, 29.9) 7.4 (0.0, 15.8) −7.8† (−16.4, 0.8) Northwest China 15.9 (5.3, 26.6) 17.0 (4.4, 29.5) 1.0 (−10.7, 12.7) 40.9 (20.7, 61.1) 43.4 (24.5, 62.2) 2.5 (−18.2, 23.1) Northeast China 6.1 (1.8, 10.5) 1.9 (0.9, 2.8) −4.3† (−9.7, 1.2) 27.5 (15.6, 39.4) 26.0 (10.2, 41.8) −1.5 (−16.5, 13.4) χ2 6.185 9.771 25.334 23.772 P 0.403 0.135 <0.001 0.001 Note: The difference in rate of coal use between 2014–2015 and 2019–2020 was tested using Rao−Scott χ2.
* Absolute change is calculated as the prevalence in 2019 minus the prevalence in 2014.
† means P<0.05.Table 4. Rates and changes in coal use for cooking and heating among residents aged 40 and older in China, from 2014–2015 to 2019–2020, categorized by residence, age, educational level, GDP per capita, and region.
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As shown in Table 5, the usage of biomass for cooking is associated with an increased risk of COPD in urban residents (OR=1.17, 95% CI: 1.03, 1.32). Among rural residents, combined use of biomass and coal fuels for cooking (OR=1.29, 95% CI: 1.12, 1.48), using coal as primary fuel for cooking (OR=1.18 95% CI: 1.00, 1.38), and using solid fuels for cooking or heating are associated with higher risk of COPD (P<0.05) (Table 5).
Solid fuels usage Urban Rural OR (95%CI) P OR (95%CI) P Cooking solid fuel usage No use(ref) 1.00 1.00 Biomass 1.17(1.03,1.32) 0.014 0.98(0.90,1.06) 0.641 Coal 0.85(0.69,1.04) 0.105 1.05(0.90,1.21) 0.537 Biomass or Coal 1.06(0.95,1.18) 0.276 1.02(0.94,1.10) 0.636 Biomass and Coal 0.98(0.74,1.30) 0.896 1.29(1.12,1.48) 0.001 Primary solid cooking fuel usage No use (ref) 1.00 1.00 Biomass 1.12(0.97,1.30) 0.115 1.00(0.92,1.08) 0.951 Coal 0.97(0.73,1.28) 0.822 1.18(1.00,1.38) 0.049 household solid fuel usage No use (ref) 1.00 1.00 Biomass 1.10(0.99,1.24) 0.088 1.02(0.94,1.11) 0.663 Coal 1.04(0.92,1.18) 0.535 1.13(1.02,1.24) 0.014 Biomass or Coal 1.06(0.96,1.17) 0.250 1.04(0.96,1.13) 0.308 * The logistic regression model adjusted Age Educational level, BMI, Smoke smog exposure, Family history of lung disease, and exposure to dust or chemicals in the workplace.
Abbreviation: OR=odd ratio; CI=confidence interval.Table 5. The association of different source of solid fuels usage with chronic obstructive pulmonary disease among residents aged 40 and older in China, 2019-2020, categorized by residence.
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The usage rate of solid fuels is an important indicator reflecting the prevalence and change of solid fuels exposure, one of the major risk factors for COPD. Understanding the usage rate of solid fuels and its changes in China can provide baseline data for assessing the attributable disease burden of COPD and inform the development of policies to prevent COPD. Solid fuels use significantly contributes to HAP, disease burden, and health degradation in low- and middle-income countries (1). This study presents updated, comprehensive, and nationally representative data on the prevalence of solid fuels use for cooking, encompassing both primary and partial usage. According to the World Health Organization (WHO), in 2019, 20.6% of China’s population primarily relied on polluting fuels and technologies for cooking (1). Our findings show a primary solid fuels use rate of 15.8% among individuals aged 40 and above (1), but a total usage rate of 28.0%, indicating that relying solely on primary fuel data may lead to underestimations by nearly 50%. Additionally, the simultaneous use of both traditional and clean stoves and technologies curbs the potential benefits for health and the environment (11). Therefore, it is imperative to implement measures that decrease reliance on traditional solid fuel systems and foster new social preferences to facilitate a complete transition to clean energy (9).
Data on the use of solid fuels for heating are scarce both globally and within China. The WHO currently only provides data on solid fuels used for cooking, with plans to expand coverage to include heating and lighting fuels starting in 2022 (1). Our study indicates that about 60% of household solid fuels consumption can be attributed to heating. Consequently, it is essential to assess the use of solid fuels for heating in studies aimed at estimating disease risks and the burden of HAP exposure. Furthermore, effective interventions, such as clean heating renovations (12), must be implemented to reduce the reliance on solid fuels for heating.
The usage rates of solid fuels for cooking and heating decreased by 17.3% and 10.3%, respectively, from 2014–2015 to 2019–2020, exceeding both the global benchmarks and previous trends observed in China. The Tracking SDG7 initiative indicated a 12% global increase in access to clean cooking fuels between 2010 and 2020 (13). Earlier studies documented a 17% reduction in the use of solid fuels for cooking in rural areas from 2000 to 2010 (12). A notable decrease in the use of solid fuels for heating was primarily observed in Northern China, likely due to the initiation of clean heating initiatives (coal-to-gas/electricity conversions) beginning in 2017 (12).
Significantly, the use of biomass heating, particularly through increased charcoal burning, has risen in Central and South China. This trend is observed in regions where central heating is absent, with charcoal emerging as an important source of heat. However, while charcoal use contributes to PM2.5 emissions, it also poses a significant risk of carbon monoxide (CO) poisoning (14). Consequently, it is imperative to prioritize understanding of health risks and to implement protective measures against CO poisoning from charcoal use.
In this study, the use of solid fuels was significantly higher in rural areas compared to urban areas, a finding that aligns with global data (2) and previous research (8). According to the WHO, in 2022, only 14% of urban populations relied on solid fuels for cooking, in contrast to 52% in rural areas (2). This urban-rural disparity is likely linked to the differences in fuel and technology availability and affordability (7,15). Additionally, this study identifies higher rates of solid fuels use among elderly populations, those with lower educational attainment, and regions with lower GDP per capita, which may reflect limited financial capacity and acceptance of modern, cleaner energy technologies (6-7).
This study is subject to some limitations. It exclusively analyzed households with members aged 40 years and older, potentially leading to an overestimation of the overall solid fuels use rate in China. Furthermore, the data on solid fuel use was gathered through questionnaires, which may introduce recall bias.
In China, the utilization of solid fuels for cooking and heating has substantially declined; however, significant discrepancies between urban and rural areas continue to exist. Individuals of lower socioeconomic status often display higher usage rates of solid fuels. Addressing this issue requires targeted interventions, such as enhancing infrastructure and developing sustainable clean energy systems in rural areas to increase the accessibility of clean fuels (7,15). Additionally, the implementation of health education initiatives and appropriate subsidy policies can improve both the willingness and affordability for lower socioeconomic groups to transition to clean fuels (9,15). It is of great public health importance to proposetargeted fuel substitution measures for various solidfuels in different regions to reduce the risk of COPD.
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Solid Fuels Use for Cooking and Heating and Its Changes
Biomass Use for Cooking and Heating and Its Changes
Coal Use for Cooking and Heating and Its Changes
The Effect of Solid Fuel Usage on COPD
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