Literature DB >> 32707793

Trends and Disparities of Energy Intake and Macronutrient Composition in China: A Series of National Surveys, 1982-2012.

Zhenni Zhu1,2, Xiaoguang Yang1, Yuehui Fang1, Jian Zhang1, Zhenyu Yang1, Zhu Wang1, Ailing Liu1, Li He1, Jing Sun1, Yiyao Lian1, Gangqiang Ding1, Yuna He1.   

Abstract

BACKGROUND: China's diet transition might offer guidance to undeveloped countries on the way to prosperity. This report describes the trends and disparities in energy and macronutrient composition among Chinese adults, and between subpopulations.
METHODS: Data for the current study were obtained from the 1982, 1992, 2002, and 2010-2012 China National Nutrition Survey (CNNS) rounds, which were nationally representative cross-sectional surveys. We applied 24-h dietary recall and food weighing to assess dietary intake.
RESULTS: There were 204,877 participants aged 20 years or older included in the current analysis. From 1982 to 2012, the estimated energy intake declined from 2614.7 kcal to 2063.9 kcal. The trend in the estimated percentage of energy intake from fat showed a spike. It increased from 16.3% to 33.1% (1992 vs. 1982 difference, 7.6%; 95% CI 7.4% to 7.7%; 2002 vs. 1992 difference, 7.7%; 95% CI 7.6% to 7.9%; 2012 vs. 2002 difference, 1.6%; 95% CI 1.4% to 1.7%; p < 0.01 for trend). The trends coincided in all the subgroups (all p < 0.01 for trend) except for the subgroup of those educated over 15 years, whose percentage of energy intake from fat declined from 37.4% to 36.6% (2012 vs. 2002 difference, -0.8%; 95% CI -1.6% to 0.0%). The estimated percentage of energy intake from carbohydrates declined from 74.0% to 55.0%. The ranges of the estimated percentage of energy intake from fat, within population subgroups stratified by education level, area and Gross national product (GNP) level, were narrowed.
CONCLUSIONS: Quick improvements in society and the economy effectively curbed undernutrition, but easily triggered overnutrition. Disparities persistently existed between different subpopulations, while the gaps would narrow if comprehensive efforts were made. Education might be a promising way to prevent overnutrition during prosperous progress. The low-social profile populations require specific interventions so as to avoid further disease burdens.

Entities:  

Keywords:  dietary energy; disparity; macronutrient composition; subpopulation; trend

Mesh:

Year:  2020        PMID: 32707793      PMCID: PMC7468974          DOI: 10.3390/nu12082168

Source DB:  PubMed          Journal:  Nutrients        ISSN: 2072-6643            Impact factor:   5.717


1. Introduction

China has been one of the fastest-growing countries over the past three decades. It implemented major social and economic reforms in 1979, and achieved tremendous economic and agricultural productivity improvement [1]. Changes in the economy, food supply and nutrition-related policies can affect diet quality at the population level. The mass Chinese population consume diets that have developed from scarcity to prosperity within only one decade or two, but this has cost a lot with regards to health outcomes, in that the burden of diet-related non-communicable disease has increased [2]. Malnutrition covers two broad groups of conditions: undernutrition and overnutrition [3]. Many developing countries work on the problem of undernutrition, while overnutrition soon emerges [4]. China’s diet transition might give guidance for the developing countries on the way to prosperity. We try to take a close look at this dietary transition during this extraordinary time in China. This report describes data from four rounds of the China National Nutrition Survey (CNNS), from 1982 to 2012. We examined the trends in energy and macronutrient composition among the Chinese population, and we also determined the disparities in dietary quality between subpopulations in terms of area, education level and economic background.

2. Materials and Methods

2.1. Study Population and Sampling

Data for the current study were obtained from the 1982, 1992, 2002 and 2010–2012 CNNS rounds, which were nationally representative cross-sectional surveys conducted by the Chinese Center for Disease Control and Prevention in order to assess the health and nutrition of the Chinese population [5]. The design, sampling and dietary data collection methods of each round were homogeneous. The survey design and methods have been presented in detail previously [5]. A stratified and multistage cluster randomized sampling method was applied. There were initially 238,124, 100,201, 247,464 and 188,622 participants recruited in the surveys from 1982 to 2012, respectively. The response rate was 87.9% in 2002 and 76.5% in 2010–2012. Response rates were not recorded in the 1982 and 1992 surveys. All CNNS rounds collected identical data from household and dietary interviews, body measurements and laboratory tests. Some participants were selected to participate in certain survey items, while others participated in another. For this analysis, we restricted the study sample to adults aged 20 years or older with dietary intake data. Education level was defined as years the participant had received education. Area was defined as urban or rural because China is a two-class society with rural–urban distinctions in many aspects. The urban sector has gained more benefits from social and economic reforms than the rural sector has. Life style and dietary pattern were distinguishing between the two sectors. Gross national product (GNP) level was classified by provincial level according to the GNP quartiles across provinces. In 1982, the first to fourth classes were classified as ≥284, (244, 284), (194, 244) and <194, respectively, in USD; in 1992, the first to fourth classes were classified as USD ≥482, (354, 482), (268, 354) and <268; in 2002, the first to fourth classes were classified as USD ≥1569, (958, 1569), (743, 958) and <743; and in 2012, the first to fourth classes were classified as USD ≥8510, (5761, 8510), (4670, 5761) and <4670. The series of national surveys was approved by the ethics committee of the National Institute for Nutrition and Health at the Chinese Center for Disease Control and Prevention.

2.2. Dietary Assessment

The field work of each round was launched in autumn, considering the comparability between survey rounds. Dietary information was collected for 5 days in 1982 by trained investigators who weighed all available foods in the participants’ homes at the beginning of the first day, recorded (and weighed if necessary) all new foods brought into the homes during the 5 days and weighed all leftovers at the end of the survey to calculate the total amount of food consumed by participants during those 5 days. In the 1992, 2002 and 2010–2012 surveys, diet was assessed via 3 consecutive days (including two weekdays and one weekend) of 24-h dietary recall, in addition to weighing household cooking oil and condiments. For each dietary recall day, investigators went to participants’ homes and helped to record food intake during the past 24 h. Investigators also weighed the household cooking oil and condiments at the beginning and end of each 24 h dietary survey. Nutrient intakes were calculated with the China Food Composition tables (FCTs) [6,7,8], which are continuously updated with commonly consumed foods and changes in nutrient composition. FCT-1981 [8] was used for dietary data from the 1982 round, FCT-2002 [6] for those from the 1992 and 2002 rounds, and FCT-2009 [7] for those from the 2010–2012 round.

2.3. Statistical Analyses

The post-stratification population sampling weights were applied to the estimated nationally representative population levels for intakes of energy and macronutrients. In order to compare dietary intake across years, the weights were derived from the sampling probability of the 2010 Chinese population aged 20 years or older (based on census data) and applied to estimate the representative dietary intake in each survey round. Means and 95% confidence intervals (CIs) of energy, and the percentages of macronutrients contributing to energy, were determined by adjustment for the sample weights. General linear regression models were used to determine the dietary trends across the survey rounds and the dietary differences between and within years. Regarding the difference between years, the year of each survey was treated as an ordinal variable and as the dependent variable. Regarding the difference within years, the subgroup of the two ends within each group (classified by education level, area, GNP level, sex and age group) was treated as an ordinal variable and as the dependent variable. Energy and macronutrient composition were treated as continuous variables and as the independent variable respectively in each model. A two-sided p < 0.05 was considered to indicate statistical significance. Statistical analyses were conducted using SAS statistical software (v. 9.4; SAS Institute, Cary, NC, USA).

3. Results

3.1. Participant Characteristics

There were 204,877 participants aged 20 years or older included in the current analysis. In the survey rounds of 1982, 1992, 2002 and 2010–2012, dietary intake data were available for 39,084, 58,316, 52,426 and 55,051 participants, respectively. The age structure of the participants was assorted across the survey rounds in accordance with the structure of actual change among the Chinese population. The sex ratios were balanced in the samples. Participants in each round had higher education level than the former round. Urban participants gradually accounted for greater percentages of the samples in the survey rounds, due to urbanization progress in China (Table 1).
Table 1

Sociodemographic Characteristics of Participants by China National Nutrition Survey (CNNS) Rounds, 1982–2012.

1982199220022012
n 39,08458,31652,42655,051
Age Group, year
20–2912,642 (32.4)16,116 (27.6)7531 (14.4)5310 (9.7)
30–398729 (22.3)13,840 (23.7)12,959 (24.7)7894 (14.3)
40–496540 (16.7)11,440 (19.6)11,745 (22.4)12,420 (22.6)
50–595533 (14.2)8429 (14.5)10,201 (19.5)12,828 (23.3)
60–693662 (9.4)5598 (9.6)6630 (12.7)10,308 (18.7)
≥701978 (5.1)2893 (5.0)3360 (6.4)6291 (11.4)
Sex
Male19,432 (49.7)28,010 (48.0)24,709 (47.1)25,278 (45.9)
Female19,652 (50.3)30,306 (52.0)27,717 (52.9)29,773 (54.1)
Education Level
under 6 years 23,479 (40.3)6567 (12.5)6901 (12.5)
6 years 8477 (14.5)15,686 (29.9)15,866 (28.8)
9 years 15,620 (26.8)18,075 (34.5)19,064 (34.6)
12 years 7766 (13.3)8433 (16.1)8454 (15.4)
15 years 1514 (2.6)2452 (4.7)2740 (5.0)
over 15 years 1148 (2.0)1115 (2.1)2026 (3.7)
No answer 312 (0.5)98 (0.2)0 (0.0)
Area
Urban13,766 (35.2)17,633 (30.2)17,530 (33.4)27,471 (49.9)
Rural25,318 (64.8)40,683 (69.8)34,896 (66.6)27,580 (50.1)
GNP Level 1
First Class 7195 (18.4)16,635 (28.5)15,374 (29.3)15,384 (27.9)
Second Class11,758 (30.1)13,802 (23.7)10,916 (20.8)14,244 (25.9)
Third Class8508 (21.8)14,544 (24.9)14,693 (28.0)13,818 (25.1)
Fourth Class11,623 (29.7)13,335 (22.9)11,443 (21.8)11,605 (21.1)

CNNS, China National Nutrition Survey; GNP, gross national product. Data are numbers of participants (%), unless otherwise indicated. 1 GNP level was classified at provincial level according to the GNP quartiles across provinces. In 1982, the first to fourth classes were classified as USD ≥284, (244, 284), (194, 244) and <194, respectively; in 1992, the first to fourth class were classified as USD ≥482, (354, 482), (268, 354) and <268; in 2002, the first to fourth classes were classified as USD ≥1569, (958, 1569), (743, 958) and <743; and in 2012, the first to fourth classes were classified as USD ≥8510, (5761, 8510), (4670, 5761) and <4670.

3.2. Trends of Energy and Macronutrient Composition

From 1982 to 2012, the estimated energy intake declined from 2614.7 kcal to 2063.9 kcal (1992 vs. 1982 difference, −82.6; 95% CI −92.5 to −72.7; 2002 vs. 1992 difference, −335.4; 95% CI −344.2 to −326.7; 2012 vs. 2002 difference, −132.7; 95% CI −141.5 to −123.9; p < 0.01 for trend). These were the trends in the population subgroups (Table 2).
Table 2

Trends and Disparities in the Daily Energy Intake of Adults Aged 18 Years or Older by CNNS Round, 1982–2012 1.

Daily Energy Intake-Survey-Weighted Mean, kcal (95% CI)p Value for TrendDifference between Rounds, kcal (95% CI)
19821992200220121992 vs. 19822002 vs. 19922012 vs. 2002
All2614.7 (2606.5-2622.8)2532.1 (2525.9–2538.2)2196.6 (2190.4–2202.8)2063.9 (2057.7–2070.2)<0.01−82.6 (−92.5 to −72.7)−335.4 (−344.2 to −326.7)−132.7 (−141.5 to −123.9)
Education level
under 6 years 2488.7 (2478.3–2499.1)2055.7 (2038.5–2072.8)1882.0 (1865.7–1898.4)<0.01 −433.0 (−454.2 to −411.8)−173.6 (−197.4 to −149.9)
6 years 2618.8 (2602.5–2635.1)2288.5 (2277.2–2299.8)2126.4 (2114.4–2138.3)<0.01 −330.3 (−349.9 to −310.8)−162.1 (−178.5 to −145.6)
9 years 2589.0 (2577.4–2600.6)2269.2 (2258.6–2279.9)2155.5 (2144.5–2166.5)<0.01 −319.8 (−335.6 to −303.9)−113.8 (−129.1 to −98.4)
12 years 2494.3 (2479.0–2509.6)2123.3 (2108.2–2138.4)2015.2 (2000.3–2030.2)<0.01 −371.0 (−392.6 to −349.5)−108.1 (−129.4 to −86.7)
15 years 2500.7 (2467.0–2534.4)2052.3 (2025.4–2079.2)1911.1 (1886.9–1935.3)<0.01 −448.4 (−491.6 to −405.1)−141.2 (−177.3 to −105.2)
over 15 years 2472.2 (2436.3–2508.0)2035.2 (1996.9–2073.5)1883.3 (1855.6–1911.1)<0.01 −437.0 (−489.5 to −384.5)−151.9 (−198.6 to −105.2)
Range within subgroups 146.6 (109.8–183.4)253.3 (220.9–285.6)273.4 (250.7–296.2)
Area
Urban2531.0 (2518.1–2543.9)2423.6 (2413.5–2433.7)1983.9 (1974.2–1993.7)1897.2 (1889.4–1905.0)<0.01−107.4 (−123.5 to −91.2)−439.7 (−453.8 to −425.7)−86.7 (−98.9 to −74.6)
Rural2703.9 (2693.3–2714.5)2647.7 (2639.8–2655.6)2423.5 (2416.0–2431.0)2241.8 (2232.5–2251.1)<0.01−56.2 (−68.9 to −43.4)−224.2 (−235.1 to −213.3)−181.7 (−193.5 to −169.9)
Range within subgroups172.9 (156.7–189.1)224.1 (211.9–236.2)439.6 (427.8–451.4)344.6 (332.5–356.7)
GNP level
First class2624.2 (2605.9–2642.5)2443.4 (2432.9–2453.8)2173.6 (2162.9–2184.3)1963.9 (1953.2–1974.6)<0.01−180.8 (−200.0 to −161.6)−269.7 (−284.7 to −254.8)−209.7 (−224.8 to −194.5)
Second class2555.3 (2540.6–2570.0)2514.8 (2502.3–2527.4)2140.9 (2127.7–2154.2)1936.6 (1925.8–1947.5)<0.01−40.5 (−59.8 to −21.1)−373.9 (−392.1 to −355.7)−204.3 (−221.2 to −187.4)
Third class2629.1 (2611.2–2647.1)2538.4 (2526.3–2550.5)2191.5 (2179.7–2203.4)2141.6 (2128.8–2154.4)<0.01−90.7 (−111.3 to −70.1)−346.9 (−363.9 to −329.9)−49.9 (−67.3 to −32.5)
Fourth class2654.6 (2639.7–2669.6)2681.6 (2667.2–2696.0)2299.3 (2285.0–2313.6)2260.3 (2245.1–2275.6)<0.0127.0 (6.1 to 48.0)−382.3 (−402.7 to −361.9)−39.0 (−59.9 to −18.1)
Range within subgroups99.3 (78.4–120.3)238.3 (220.7–255.8)158.4 (138.9–177.9)323.7 (305.5–342.0)

CNNS, China National Nutrition Survey; GNP, gross national product. 1 Data were adjusted for CNNS weights to be nationally representative. Values may not equal the difference between two years’, or the highest and lowest subgroups’, estimates because of rounding.

The trend of estimated percentage of energy intake from fat showed a spike. It increased from 16.3% to 33.1% (1992 vs. 1982 difference, 7.6%; 95% CI 7.4% to 7.7%; 2002 vs. 1992 difference, 7.7%; 95% CI 7.6% to 7.9%; 2012 vs. 2002 difference, 1.6%; 95% CI 1.4% to 1.7%; p < 0.01 for trend). The trends coincided in the subgroups (all p < 0.01 for trend) except for the subgroup of those educated for over 15 years. In the most recent two survey rounds, the estimated percentage of energy intake from fat among the well-educated population declined from 37.4% to 36.6% (2012 vs. 2002 difference, −0.8%; 95% CI −1.6% to 0.0%) (Table 3).
Table 3

Trends and Disparities in the Estimated Percentage of Energy Intake from Fat of Adults Aged 18 Years or Older by CNNS Round, 1982–2012 1.

Estimated Percentage of Energy Intake from Fat, Survey–Weighted % (95% CI)p Value for TrendDifference between Rounds, % (95% CI)
19821992200220121992 vs. 19822002 vs. 19922012 vs. 2002
All16.3 (16.2–16.4)23.8 (23.7–23.9)31.6 (31.5–31.7)33.1 (33.0–33.2)<0.017.6 (7.4 to 7.7)7.7 (7.6 to 7.9)1.6 (1.4 to 1.7)
Education level
under 6 years 19.9 (19.8–20.0)28.0 (27.7–28.3)30.4 (30.1–30.7)<0.01 8.1 (7.8 to 8.4)2.5 (2.0 to 2.9)
6 years 22.2 (22.0–22.5)28.9 (28.7–29.1)31.1 (31.0–31.3)<0.01 6.6 (6.3 to 6.9)2.3 (2.0 to 2.5)
9 years 25.2 (25.0–25.3)31.0 (30.8–31.2)32.9 (32.7–33.1)<0.01 5.8 (5.6 to 6.1)1.9 (1.7 to 2.1)
12 years 28.2 (28.0–28.4)34.8 (34.6–35.1)35.1 (34.8–35.3)<0.01 6.6 (6.2 to 6.9)0.3 (−0.1 to 0.6)
15 years 30.3 (29.8–30.8)36.5 (36.1–37.0)36.7 (36.3–37.1)<0.01 6.2 (5.5 to 6.9)0.1 (−0.5 to 0.7)
over 15 years 30.5 (30.0–31.0)37.4 (36.8–38.0)36.6 (36.2–37.1)<0.01 6.9 (6.1 to 7.7)−0.8 (−1.6 to 0.0)
Range within subgroups 10.6 (10.1–11.1)9.5 (8.8–10.1)6.3 (5.8–6.7)
Area
Urban19.6 (19.4–19.7)29.0 (28.9–29.2)35.8 (35.7–36.0)36.7 (36.6–36.8)<0.019.5 (9.3 to 9.7)6.8 (6.6 to 7.0)0.9 (0.7 to 1.1)
Rural12.7 (12.6–12.8)18.3 (18.2–18.4)27.0 (26.9–27.1)29.3 (29.2–29.4)<0.015.5 (5.4 to 5.7)8.7 (8.6 to 8.9)2.3 (2.1 to 2.5)
Range within subgroups6.8 (6.7–7.0)10.8 (10.6–10.9)8.9 (8.7–9.1)7.4 (7.2–7.6)
GNP level
First class 17.0 (16.8–17.2)27.5 (27.4–27.7)33.0 (32.8–33.1)35.0 (34.9–35.2)<0.0110.5 (10.3 to 10.8)5.4 (5.2 to 5.7)2.1 (1.8 to 2.3)
Second class15.8 (15.6–15.9)23.7 (23.5–23.9)31.2 (31.0–31.4)33.3 (33.1–33.5)<0.018.0 (7.7 to 8.2)7.5 (7.2 to 7.7)2.1 (1.8 to 2.4)
Third class15.1 (14.9–15.3)20.2 (20.0–20.4)31.3 (31.1–31.5)31.3 (31.1–31.5)<0.015.1 (4.8 to 5.3)11.1 (10.8 to 11.4)0.0 (−0.3 to 0.3)
Fourth class17.1 (17.0–17.3)21.9 (21.7–22.1)30.1 (29.9–30.3)32.5 (32.3–32.7)<0.014.8 (4.5 to 5.1)8.2 (7.9 to 8.5)2.4 (2.1 to 2.7)
Range within subgroups2.0 (1.8–2.3)7.3 (7.1–7.6)2.9 (2.6–3.1)3.7 (3.5–4.0)

CNNS, China National Nutrition Survey; GNP, gross national product. 1 Data were adjusted for CNNS weights to be nationally representative. Values may not equal the difference between two years’, or the highest and lowest subgroups’, estimates because of rounding.

The estimated percentage of energy intake from carbohydrates declined from 74.0% to 55.0% (1992 vs. 1982 difference, −10.5%; 95% CI −10.7% to −10.4%; 2002 vs. 1992 difference, −7.4%; 95% CI −7.5% to −7.2%; 2012 vs. 2002 difference, −1.0%; 95% CI −1.2% to −0.9%; p < 0.01 for trend). The trends in the subgroups were the same (Table 4).
Table 4

Trends and Disparities in the Estimated Percentage of Energy Intake from Carbohydrates of Adults Aged 18 Years or Older by CNNS Round, 1982–2012 1.

Estimated Percentage of Energy Intake from Carbohydrates, Survey–Weighted % (95% CI)p Value for TrendDifference between Rounds, % (95% CI)
19821992200220121992 vs. 19822002 vs. 19922012 vs. 2002
All 74.0 (73.8–74.1)63.4 (63.3–63.5)56.0 (55.9–56.1)55.0 (54.9–55.1)<0.01−10.5 (−10.7 to −10.4)−7.4 (−7.5 to −7.2)−1.0 (−1.2 to −0.9)
Education level
under 6 years 68.1 (67.9–68.2)60.5 (60.2–60.8)59.1 (58.8–59.4)<0.01 −7.6 (−7.9 to −7.3)−1.4 (−1.8 to −1.0)
6 years 65.4 (65.2–65.6)59.5 (59.3–59.7)57.7 (57.5–57.9)<0.01 −5.9 (−6.2 to −5.6)−1.8 (−2.0 to −1.5)
9 years 61.9 (61.8–62.1)56.8 (56.6–57.0)55.4 (55.2–55.6)<0.01 −5.1 (−5.4 to −4.9)−1.4 (−1.7 to −1.2)
12 years 58.1 (57.9–58.4)51.9 (51.7–52.2)52.4 (52.1–52.6)<0.01 −6.2 (−6.5 to −5.8)0.4 (0.1 to 0.8)
15 years 55.4 (54.9–55.9)49.6 (49.2–50.0)50.0 (49.6–50.4)<0.01 −5.8 (−6.5 to −5.1)0.4 (−0.2 to 1.0)
over 15 years 55.0 (54.4–55.5)48.1 (47.5–48.7)49.6 (49.2–50.1)<0.01 −6.9 (−7.7 to −6.1)1.5 (0.8 to 2.3)
Range within subgroups 13.1 (12.6–13.6)12.4 (11.8–13.0)9.5 (9.0–10.0)
Area
Urban70.0 (69.8–70.2)57.2 (57.0–57.3)50.8 (50.6–51.0)50.4 (50.2–50.5)<0.01−12.8 (−13.0 to −12.6)−6.4 (−6.6 to −6.2)−0.4 (−0.6 to −0.2)
Rural78.2 (78.0–78.3)70.1 (70.0–70.2)61.6 (61.5–61.7)60.0 (59.8–60.1)<0.01−8.1 (−8.2 to −7.9)−8.4 (−8.6 to −8.3)−1.7 (−1.8 to −1.5)
Range within subgroups8.2 (8.0–8.3)12.9 (12.7–13.0)10.8 (10.7–11.0)9.6 (9.4–9.8)
GNP level
First class 72.7 (72.5–73.0)58.7 (58.5–58.8)53.6 (53.4–53.7)51.6 (51.4–51.8)<0.01−14.1 (−14.3 to −13.8)−5.1 (−5.3 to −4.9)−1.9 (−2.2 to −1.7)
Second class74.5 (74.3–74.7)63.7 (63.5–63.9)56.5 (56.3–56.8)55.4 (55.2–55.6)<0.01−10.8 (−11.0 to −10.5)−7.2 (−7.5 to −6.9)−1.1 (−1.4 to −0.8)
Third class75.6 (75.4–75.8)67.9 (67.7–68.0)56.8 (56.6–57.0)57.4 (57.2–57.6)<0.01−7.8 (−8.0 to −7.5)−11.1 (−11.3 to −10.8)0.6 (0.3 to 0.9)
Fourth class72.9 (72.7–73.1)65.9 (65.7–66.1)58.4 (58.1–58.6)56.3 (56.0–56.5)<0.01−7.0 (−7.3 to −6.7)−7.6 (−7.9 to −7.2)−2.1 (−2.4 to −1.8)
Range within subgroups2.9 (2.6–3.2)9.2 (9.0–9.5)4.8 (4.5–5.1)5.8 (5.5–6.1)

CNNS, China National Nutrition Survey; GNP, gross national product. 1 Data were adjusted for CNNS weights to be nationally representative. Values may not equal the difference between two years’, or the highest and lowest subgroups’, estimates because of rounding.

The estimated percentage of energy intake from protein increased between the first and second rounds, from 10.9% to 12.8%, and slightly declined to 12.3% in the successive two rounds (1992 vs. 1982 difference, 1.9%; 95% CI 1.9% to 1.9%; 2002 vs. 1992 difference, −0.3%; 95% CI −0.4% to −0.3%; 2012 vs. 2002 difference, −0.1%; 95% CI −0.1% to 0.0%) (Table 5).
Table 5

Trends and Disparities in the Estimated Percentage of Energy Intake from Protein of Adults Aged 18 Years or Older by CNNS Round, 1982–2012 1.

Estimated Percentage of Energy Intake from Protein, Survey-Weighted % (95% CI)p Value for TrendDifference between Rounds, % (95% CI)
19821992200220121992 vs. 19822002 vs. 19922012 vs. 2002
All 10.9 (10.8–10.9)12.8 (12.7–12.8)12.4 (12.4–12.4)12.3 (12.3–12.4)<0.011.9 (1.9 to 1.9)−0.3 (−0.4 to −0.3)−0.1 (−0.1 to 0.0)
Education level
under 6 years 12.0 (12.0–12.0)11.5 (11.5–11.6)11.2 (11.2–11.3)<0.01 −0.5 (−0.6 to −0.4)−0.3 (−0.4 to −0.2)
6 years 12.4 (12.3–12.4)11.7 (11.6–11.7)11.5 (11.4–11.5)<0.01 −0.7 (−0.8 to −0.6)−0.2 (−0.2 to −0.1)
9 years 12.9 (12.9–13.0)12.2 (12.2–12.2)12.1 (12.0–12.1)<0.01 −0.7 (−0.8 to −0.6)−0.1 (−0.2 to −0.1)
12 years 13.7 (13.6–13.7)13.2 (13.2–13.3)13.2 (13.1–13.2)<0.01 −0.4 (−0.5 to −0.3)−0.1 (−0.2 to 0.0)
15 years 14.2 (14.0–14.4)13.8 (13.7–14.0)14.1 (14.0–14.3)0.83 −0.4 (−0.6 to −0.2)0.3 (0.1 to 0.5)
over 15 years 14.5 (14.3–14.7)14.5 (14.3–14.7)14.6 (14.4–14.8)0.40 0.0 (−0.3 to 0.2)0.1 (−0.1 to 0.4)
Range within subgroups 2.5 (2.4–2.6)3.0 (2.8–3.1)3.4 (3.3–3.5)
Area
Urban11.2 (11.2–11.3)13.8 (13.7–13.8)13.4 (13.3–13.4)13.5 (13.4–13.5)<0.012.6 (2.5 to 2.6)−0.4 (−0.5 to −0.3)0.1 (0.0 to 0.2)
Rural10.5 (10.5–10.5)11.7 (11.6–11.7)11.4 (11.4–11.4)11.2 (11.1–11.2)<0.011.2 (1.1 to 1.2)−0.3 (−0.3 to −0.2)−0.2 (−0.3 to −0.2)
Range within subgroups0.7 (0.7–0.8)2.1 (2.1–2.1)2.0 (1.9–2.0)2.3 (2.3–2.4)
GNP level
First class 11.0 (10.9–11.0)13.8 (13.8–13.9)13.5 (13.4–13.5)13.6 (13.5–13.7)<0.012.8 (2.8 to 2.9)−0.3 (−0.4 to −0.3)0.1 (0.0 to 0.2)
Second class11.2 (11.2–11.2)12.5 (12.5–12.6)12.3 (12.2–12.3)12.0 (12.0–12.1)<0.011.3 (1.3 to 1.4)−0.3 (−0.3 to −0.2)−0.3 (−0.3 to −0.2)
Third class10.6 (10.5–10.6)12.0 (11.9–12.0)11.9 (11.9–12.0)11.8 (11.8–11.9)<0.011.4 (1.3 to 1.4)0.0 (−0.1 to 0.0)−0.1 (−0.2 to 0.0)
Fourth class10.7 (10.7–10.7)12.1 (12.1–12.2)11.5 (11.5–11.6)11.7 (11.6–11.8)<0.011.4 (1.4 to 1.5)−0.6 (−0.7 to −0.5)0.2 (0.1 to 0.2)
Range within subgroups0.6 (0.5–0.7)1.9 (1.8–1.9)1.9 (1.9–2.0)1.9 (1.8–2.0)

CNNS, China National Nutrition Survey; GNP, gross national product. 1 Data were adjusted for CNNS weights to be nationally representative. Values may not equal the difference between two years’, or the highest and lowest subgroups’, estimates because of rounding.

3.3. Disparities of Macronutrient Composition in Population Subgroups

The estimated percentages of energy intake from fat within population subgroups, stratified by education level, were 10.6% (95% CI 10.1–11.1%) in 1992, 9.5% (95% CI 8.8–10.1%) in 2002 and 6.3% (95% CI 5.8–6.7%) in 2010–2012. Those stratified by area were 6.8% (95% CI 6.7–7.0%) in 1982, 10.8% (95% CI 10.6–10.9%) in 1992, 8.9% (95% CI 8.7–9.1%) in 2002 and 7.4% (95% CI 7.2–7.6%) in 2010–2012. Those stratified by GNP level were 2.0% (95% CI 1.8–2.3%) in 1982, 7.3% (95% CI 7.1–7.6%) in 1992, 2.9% (95% CI 2.6–3.1%) in 2002 and 3.7% (95% CI 3.5–4.0%) in 2010–2012. The ranges of the estimated percentage of energy intake from carbohydrates within population subgroups stratified by education level were 13.1% (95% CI 12.6–13.6%) in 1992, 12.4% (95% CI 11.8–13.0%) in 2002 and 9.5% (95% CI 9.0–10.0%) in 2010–2012. Those stratified by area were 8.2% (95% CI 8.0–8.3%) in 1982, 12.9% (95% CI 12.7–13.0%) in 1992, 10.8% (95% CI 10.7–11.0%) in 2002 and 9.6% (95% CI 9.4–9.8%) in 2010–2012. Those stratified by GNP level were 2.9% (95% CI 2.6–3.2%) in 1982, 9.2% (95% CI 9.0–9.5%) in 1992, 4.8% (95% CI 4.5–5.1%) in 2002 and 5.8% (95% CI 5.5–6.1%) in 2010–2012 (Table 2, Table 3, Table 4 and Table 5 and Figure 1). The trends and disparities stratified by age and sex are given in Table A1, Table A2, Table A3 and Table A4.
Figure 1

Trends and Disparities between Two Ends of Subgroups with regards to Estimated Energy Intake from Macronutrients of Adults Aged 18 Years or Older by CNNS Round, 1982–2012, Stratified by Area, Education Level and GNP Level. The two polygonal lines in each graph represent the two ends of subgroups. (A–C) show percentages of energy intake from fat across survey rounds. (D–F) show percentages of energy intake from carbohydrates across survey rounds. (G–I) show percentages of energy intake from protein across survey rounds.

Table A1

Trends and Disparities in the Daily Energy Intake of Adults Aged 18 Years or Older by CNNS Round, 1982–2012 1 (kcal).

Daily Energy Intake, Survey-Weighted Mean, kcal (95% CI)p Value for TrendDifference between Rounds, kcal (95% CI)
19821992200220121992 vs. 19822002 vs. 19922012 vs. 2002
All2614.7 (2606.5, 2622.8)2532.1 (2525.9, 2538.2)2196.6 (2190.4, 2202.8)2063.9 (2057.7, 2070.2)<0.01−82.6 (−92.5 to −72.7)−335.4 (−344.2 to −326.7)−132.7 (−141.5 to −123.9)
Age group-y
20–292843.2 (2829.0, 2857.5)2639.9 (2627.8, 2651.9)2209.3 (2193.0, 2225.6)2054.3 (2034.8, 2073.9)<0.01−203.4 (−221.8 to −184.9)−430.6 (−449.7 to −411.4)−154.9 (−180.0 to −129.9)
30–392798.9 (2782.0, 2815.8)2625.7 (2613.5, 2638.0)2262.8 (2250.3, 2275.4)2128.8 (2111.7, 2145.9)<0.01−173.2 (−193.4 to −153.1)−362.9 (−380.5 to −345.3)−134.0 (−154.5 to −113.6)
40–492700.0 (2681.3, 2718.8)2594.4 (2581.1, 2607.7)2254.8 (2241.6, 2267.9)2164.5 (2150.9, 2178.1)<0.01−105.6 (−127.6 to −83.7)−339.7 (−358.3 to −321.0)−90.3 (−109.2 to −71.4)
50–592504.3 (2483.3, 2525.3)2526.9 (2511.3, 2542.5)2238.8 (2225.0, 2252.7)2092.7 (2080.0, 2105.4)<0.0122.6 (−2.8 to 48.0)−288.1 (−308.8 to −267.3)−146.1 (−164.9 to −127.4)
60–692181.6 (2160.0, 2203.3)2360.2 (2341.4, 2378.9)2103.9 (2087.4, 2120.5)1955.1 (1942.5, 1967.7)<0.01178.5 (150.4 to 206.7)−256.3 (−281.2 to −231.4)−148.8 (−169.0 to −128.6)
≥701963.5 (1937.0, 1990.1)2002.9 (1978.1, 2027.7)1836.3 (1814.8, 1857.8)1695.5 (1680.6, 1710.4)<0.0139.4 (3.3 to 75.5)−166.6 (−199.2 to −134.0)−140.8 (−165.5 to −116.1)
Range within subgroups879.7 (851.1, 908.3)637.0 (612.2, 661.7)426.5 (402.0, 451.1)469.0 (444.8, 493.2)
Sex
Male2857.7 (2845.9, 2869.4)2738.7 (2729.7, 2747.7)2382.6 (2373.4, 2391.8)2241.6 (2232.0, 2251.2)<0.01−119.0 (−133.4 to −104.5)−356.1 (−369.0 to −343.2)−141.0 (−154.3 to −127.7)
Female2366.9 (2356.9, 2377.0)2321.4 (2313.7, 2329.2)2007.1 (1999.4, 2014.7)1882.8 (1875.3, 1890.4)<0.01−45.5 (−57.9 to −33.2)−314.4 (−325.2 to −303.5)−124.2 (−134.9 to −113.5)
Range within subgroups490.7 (475.2, 506.2)417.3 (405.5, 429.1)375.5 (363.6, 387.5)358.8 (346.7, 370.8)

CNNS, China National Nutrition Survey. 1 Data were adjusted for CNNS weights to be nationally representative. Values may not equal the difference between two years’, or the highest and lowest subgroups’, estimates because of rounding.

Table A2

Trends and Disparities in the Estimated Percentage of Energy Intake from Fat of Adults Aged 18 Years or Older by CNNS Round, 1982–2012 1.

Estimated Percentage of Energy Intake from Fat, Survey-Weighted % (95% CI)p Value for TrendDifference between Rounds, % (95% CI)
19821992200220121992 vs. 19822002 vs. 19922012 vs. 2002
All16.3 (16.2, 16.4)23.8 (23.7, 23.9)31.6 (31.5, 31.7)33.1 (33.0, 33.2)<0.017.6 (7.4 to 7.7)7.7 (7.6 to 7.9)1.6 (1.4 to 1.7)
Age group-y
20–2916.9 (16.8, 17.1)24.4 (24.2, 24.6)32.0 (31.7, 32.3)33.8 (33.5, 34.2)<0.017.5 (7.2 to 7.7)7.6 (7.3 to 7.9)1.8 (1.4 to 2.2)
30–3916.6 (16.4, 16.8)24.7 (24.5, 24.9)31.5 (31.3, 31.7)33.4 (33.2, 33.7)<0.018.1 (7.8 to 8.4)6.8 (6.5 to 7.0)2.0 (1.6 to 2.3)
40–4915.7 (15.5, 15.9)23.3 (23.1, 23.5)31.5 (31.3, 31.8)33.3 (33.1, 33.5)<0.017.6 (7.3 to 7.9)8.3 (8.0 to 8.6)1.8 (1.5 to 2.1)
50–5916.1 (15.8, 16.3)23.6 (23.4, 23.8)31.4 (31.2, 31.7)32.8 (32.6, 33.0)<0.017.5 (7.2 to 7.9)7.8 (7.5 to 8.2)1.4 (1.1 to 1.7)
60–6916.2 (15.9, 16.5)23.1 (22.8, 23.4)31.3 (31.0, 31.6)31.9 (31.7, 32.1)<0.016.9 (6.5 to 7.3)8.2 (7.8 to 8.6)0.6 (0.3 to 1.0)
≥7015.6 (15.2, 16.0)22.7 (22.3, 23.2)31.1 (30.7, 31.5)31.7 (31.4, 32.0)<0.017.1 (6.5 to 7.7)8.3 (7.8 to 8.9)0.7 (0.2 to 1.2)
Range within subgroups1.3 (1.0, 1.7)2.0 (1.6, 2.4)0.9 (0.4, 1.5)2.1 (1.6, 2.6)
Sex
Male16.2 (16.1, 16.4)23.6 (23.5, 23.7)31.4 (31.3, 31.6)32.9 (32.8, 33.1)<0.017.4 (7.2 to 7.6)7.8 (7.6 to 8.0)1.5 (1.3 to 1.7)
Female16.3 (16.2, 16.4)24.1 (23.9, 24.2)31.7 (31.5, 31.8)33.3 (33.2, 33.5)<0.017.8 (7.6 to 7.9)7.6 (7.4 to 7.8)1.6 (1.4 to 1.8)
Range within subgroups0.1 (−0.1, 0.3)0.5 (0.3, 0.6)0.3 (0.0, 0.5)0.4 (0.2, 0.6)

CNNS, China National Nutrition Survey. 1 Data were adjusted for CNNS weights to be nationally representative. Values may not equal the difference between two years’, or the highest and lowest subgroups’, estimates because of rounding.

Table A3

Trends and Disparities in the Estimated Percentage of Energy Intake from Carbohydrates of Adults Aged 18 Years or Older by CNNS Round, 1982–2012 1.

Estimated Percentage of Energy Intake from Carbohydrates, Survey-Weighted % (95% CI)p Value for TrendDifference between Rounds, % (95% CI)
19821992200220121992 vs. 19822002 vs. 19922012 vs. 2002
All 74.0 (73.8, 74.1)63.4 (63.3, 63.5)56.0 (55.9, 56.1)55.0 (54.9, 55.1)<0.01−10.5 (−10.7 to −10.4)−7.4 (−7.5 to −7.2)−1.0 (−1.2 to −0.9)
Age group-y
20–2973.2 (73.0, 73.4)62.9 (62.7, 63.1)55.4 (55.2, 55.7)54.2 (53.9, 54.6)<0.01−10.3 (−10.5 to −10.0)−7.5 (−7.8 to −7.2)−1.2 (−1.7 to −0.8)
30–3973.6 (73.4, 73.8)62.3 (62.1, 62.5)56.1 (55.9, 56.3)54.6 (54.3, 54.8)<0.01−11.3 (−11.6 to −11.0)−6.2 (−6.5 to −5.9)−1.5 (−1.9 to −1.2)
40–4974.6 (74.3, 74.8)64.0 (63.8, 64.3)56.1 (55.8, 56.3)54.8 (54.6, 55.0)<0.01−10.5 (−10.9 to −10.2)−8.0 (−8.3 to −7.7)−1.2 (−1.6 to −0.9)
50–5974.2 (73.9, 74.5)63.7 (63.4, 64.0)56.3 (56.1, 56.5)55.3 (55.1, 55.5)<0.01−10.5 (−10.9 to −10.1)−7.4 (−7.7 to −7.0)−1.0 (−1.3 to −0.7)
60–6974.1 (73.7, 74.4)64.2 (63.9, 64.5)56.4 (56.1, 56.7)56.5 (56.3, 56.8)<0.01−9.9 (−10.3 to −9.4)−7.8 (−8.3 to −7.4)0.2 (−0.2 to 0.5)
≥7074.6 (74.2, 75.1)64.5 (64.1, 65.0)56.5 (56.1, 56.9)56.7 (56.4, 57.0)<0.01−10.1 (−10.8 to −9.5)−8.0 (−8.6 to −7.4)0.3 (−0.2 to 0.8)
Range within subgroups1.5 (1.1, 1.8)2.2 (1.8, 2.6)1.0 (0.5, 1.6)2.5 (2.0, 3.0)
Sex
Male73.9 (73.8, 74.1)63.7 (63.5, 63.8)56.2 (56.0, 56.4)54.7 (54.6, 54.9)<0.01−10.3 (−10.5 to −10.1)−7.5 (−7.7 to −7.2)−1.5 (−1.7 to −1.3)
Female74.0 (73.8, 74.1)63.2 (63.0, 63.3)55.9 (55.7, 56.0)55.3 (55.2, 55.5)<0.01−10.8 (−11.0 to −10.6)−7.3 (−7.5 to −7.1)−0.5 (−0.7 to −0.3)
Range within subgroups0.0 (−0.2, 0.2)0.5 (0.3, 0.7)0.3 (0.1, 0.6)0.6 (0.4, 0.8)

CNNS, China National Nutrition Survey. 1 Data were adjusted for CNNS weights to be nationally representative. Values may not equal the difference between two years’, or the highest and lowest subgroups’, estimates because of rounding.

Table A4

Trends and Disparities in the Estimated Percentage of Energy Intake from Protein of Adults Aged 18 Years or Older by CNNS Round, 1982–2012 1.

Estimated Percentage of Energy Intake from Protein, Survey-Weighted % (95% CI)p Value for TrendDifference between Rounds, % (95% CI)
19821992200220121992 vs. 19822002 vs. 19922012 vs. 2002
All 10.9 (10.8, 10.9)12.8 (12.7, 12.8)12.4 (12.4, 12.4)12.3 (12.3, 12.4)<0.011.9 (1.9 to 1.9)−0.3 (−0.4 to −0.3)−0.1 (−0.1 to 0.0)
Age group-y
20–2910.9 (10.9, 10.9)12.7 (12.6, 12.7)12.5 (12.5, 12.6)12.8 (12.7, 12.9)<0.011.8 (1.7 to 1.8)−0.1 (−0.2 to −0.1)0.2 (0.1 to 0.4)
30–3910.9 (10.9, 11.0)13.0 (12.9, 13.0)12.4 (12.4, 12.5)12.5 (12.4, 12.6)<0.012.1 (2.0 to 2.1)−0.6 (−0.6 to −0.5)0.1 (0.0 to 0.2)
40–4910.9 (10.8, 10.9)12.7 (12.6, 12.7)12.4 (12.3, 12.5)12.2 (12.1, 12.2)<0.011.8 (1.7 to 1.9)−0.3 (−0.4 to −0.2)−0.2 (−0.3 to −0.1)
50–5910.8 (10.7, 10.8)12.7 (12.6, 12.8)12.3 (12.2, 12.3)12.1 (12.0, 12.1)<0.011.9 (1.8 to 2.0)−0.4 (−0.5 to −0.3)−0.2 (−0.3 to −0.1)
60–6910.8 (10.7, 10.9)12.7 (12.6, 12.8)12.3 (12.3, 12.4)12.0 (11.9, 12.0)<0.011.9 (1.8 to 2.0)−0.4 (−0.5 to −0.2)−0.3 (−0.4 to −0.3)
≥7010.8 (10.7, 10.9)12.8 (12.6, 12.9)12.4 (12.3, 12.6)12.1 (12.1, 12.2)<0.011.9 (1.8 to 2.1)−0.3 (−0.5 to −0.1)−0.3 (−0.4 to −0.2)
Range within subgroups0.1 (0.1, 0.2)0.3 (0.2, 0.4)0.3 (0.2, 0.4)0.8 (0.7, 0.9)
Sex
Male10.9 (10.9, 10.9)12.7 (12.7, 12.8)12.4 (12.3, 12.4)12.3 (12.3, 12.4)<0.011.9 (1.8 to 1.9)−0.4 (−0.4 to −0.3)0.0 (−0.1 to 0.0)
Female10.9 (10.8, 10.9)12.8 (12.7, 12.8)12.5 (12.4, 12.5)12.4 (12.3, 12.4)<0.011.9 (1.9 to 2.0)−0.3 (−0.4 to −0.3)−0.1 (−0.1 to 0.0)
Range within subgroups0.0 (0.0, 0.1)0.0 (0.0, 0.1)0.1 (0.0, 0.1)0.0 (0.0, 0.1)

CNNS, China National Nutrition Survey. 1 Data were adjusted for CNNS weights to be nationally representative. Values may not equal the difference between two years’, or the highest and lowest subgroups’, estimates because of rounding.

4. Discussion

China has made substantial progress in improving nutrition. Diet quality improved remarkably from 1982 to 2012 in China. The trends of energy intake constantly decreased in the survey rounds due to the fast pace of modernization and urbanization. The percentage of fat’s contribution to energy spiked, that of carbohydrates fell all the way, and that of protein stabilized within a small range. The macronutrient composition went from poor, to ideal, and then to far from ideal again. Though the composition was not satisfying at the beginning round of CNNS, in 1982, which featured excessive carbohydrates and a lack of fat, it became more ideal in the 1992 survey round. The macronutrient composition was within the national recommendations among most subpopulations around that period [9]. However, in the most recent two surveys, the macronutrient composition dropped out of the ideal range, which led to health conditions diametrically opposed to malnutrition, i.e., overnutrition, potentially contributing to the prevalence of nutrition-related non-communicable chronic diseases (NCDs) nation-wide [10]. We considered that different fat compositions at the same level of energy intake could have diverse impacts on the development of obesity. It seemed a paradox in China that overweight and obesity dramatically increased since 1980s, despite energy intake constantly decreasing [1,11]. Reduced physical activity could explain the increasing prevalence of obesity, but most developed countries, like America and Korea, also experience both obesity prevalence and raising energy intakes [12,13,14,15]. Indeed, few countries, like Japan, had a similar situation to ours, whereby the obesity rate went up as the energy intake decreased [16]. New studies suggested that the percentage of fat contributing to energy could be the cause of adiposity, but not carbohydrates or protein [17]. In fact, the proportion of fat in the diet kept going up worldwide, as did the prevalence of obesity [13,16,18,19]. The current findings were based on massive samples and observations over the long-term, which might provide new thoughts as to the cause of obesity. The great achievements following the social and economic shifts after 1979 had a tremendous impact on the diet of the Chinese population [20]. It took no more than one decade for the Chinese people to go from lacking various foods, to having plenty of every food. There was a big leap in nutrition improvement, and diet patterns changed most in the 1980s and 1990s. The macronutrient composition rapidly reached the ideal range at that time. The pace of the change of macronutrient composition slowed down, and it has been unsatisfying in recent years. The promoter of the diet has shifted. Economy and food supply were still continuing to improve, but it was contributing only a little to diet improvement in China. Other things, like nutrition policy retargeting or the availability of nutrition education and knowledge, might be the key to promoting diet quality in China. The disparities persistently existed in different subpopulations across China, but the gaps narrowed in recent years. The Chinese government has put huge effort into poverty reduction, transportation system construction and raising the agricultural yield, which all potentially increased the equity of access to various foods by people with different background. Especially in the most recent survey round, the percentages of fats’ and carbohydrates’ contributions to energy were getting closer between the two ends of the subpopulations as regards area, education level and economic background. It was obvious that the subpopulations with better social profiles (living in urban areas, well-educated and wealthy economic background) were leading the diet trends, and the rest followed in the next decade or two. Nevertheless, the macronutrient compositions of those with better social profiles had been moving toward the overnutrition pattern since around 2002, which was probably a major cause of nutrition-related NCDs prevailing in China [3,10,21]. If people with low social profiles continue to follow the diet trend, there might be another surge of nutrition-related NCDs in China. Moreover, inequalities in health resource access have existed for some time in China [22]. It would deepen the social contradictions if those who suffered from diseases could not be able to access necessary health resources. More governmental interventions should be launched into the subpopulation with low social profiles in order to slow down or even curb their movement into overnutrition. One promising trend was discovered in the well-educated subpopulation. In the survey round of 2012, the macronutrient composition distinctively retuned to the recommended ranges among these people. “Eat well” was linked to “live well” in Chinese culture, but people always confused “eat well” with “eat whatever one wants”. Actually, “eat well” means “eat properly” in the modern nutritional theory, and it leads to “live well”. It is clear that some risks of nutrition-related NCDs can be modified though education improvement [23]. Well-educated people have greater volition and ability to acquire health information which might help them regulate dietary behaviors, rather than following their instinctive appetite or preference. Health education would probably be a useful tool to help China get through the possible dilemma of a further potential surge of NCDs in the subpopulations with low social profiles. This study has several limitations. First, 3-day 24-h dietary recalls were used to obtain food consumption information, and so the accuracy of dietary intake was mostly dependent on the participants’ recall and estimation. Second, for the individual income information variabilities in different survey rounds, the classification of GNP level was applied. It was based on each province’s GNP in the survey year, which might not classify each participant meticulously. Third, a recent study mentioned that the quality or food sources of macronutrients might lead to different health outcomes [24]. Diet quality in the current study was determined based on the macronutrient composition, which might cause bias without taking food composition into consideration. Fourth, the inference of macronutrient composition and consequential health outcome in the discussion was only derived from reports on the national level in an ecological way, rather than the relationships among CNNS participants.

5. Conclusions

Quick improvements in society and the economy effectively curbed undernutrition, but easily triggered larger-scaled overnutrition soon after in China. Disparities have persistently existed in different subpopulations, while these gaps would narrow if major efforts were made. Populations with low social profiles might lag behind the trend of diet transition, but would be more vulnerable to the side-effects of the trend. Education might be a promising way of preventing overnutrition during the prosperous progress of developing countries. Low social profile populations require specific interventions so as to avoid the further burdens of diet-related non-communicable diseases, in order to maintain social stability.
  19 in total

1.  Data Resource Profile: China National Nutrition Surveys.

Authors:  Yuna He; Wenhua Zhao; Jian Zhang; Liyun Zhao; Zhenyu Yang; Junsheng Huo; Lichen Yang; Jingzhong Wang; Li He; Jing Sun; Jianhua Piao; Xiaoguang Yang; Keyou Ge; Gangqiang Ding
Journal:  Int J Epidemiol       Date:  2019-04-01       Impact factor: 7.196

2.  The double burden of under- and overnutrition and nutrient adequacy among Chinese preschool and school-aged children in 2009-2011.

Authors:  C Piernas; D Wang; S Du; B Zhang; Z Wang; C Su; B M Popkin
Journal:  Eur J Clin Nutr       Date:  2015-07-01       Impact factor: 4.016

3.  Rapid health transition in China, 1990-2010: findings from the Global Burden of Disease Study 2010.

Authors:  Gonghuan Yang; Yu Wang; Yixin Zeng; George F Gao; Xiaofeng Liang; Maigeng Zhou; Xia Wan; Shicheng Yu; Yuhong Jiang; Mohsen Naghavi; Theo Vos; Haidong Wang; Alan D Lopez; Christopher J L Murray
Journal:  Lancet       Date:  2013-06-08       Impact factor: 79.321

4.  Trends in energy intake among adults in the United States: findings from NHANES.

Authors:  Earl S Ford; William H Dietz
Journal:  Am J Clin Nutr       Date:  2013-02-20       Impact factor: 7.045

Review 5.  China in the period of transition from scarcity and extensive undernutrition to emerging nutrition-related non-communicable diseases, 1949-1992.

Authors:  S F Du; H J Wang; B Zhang; F Y Zhai; B M Popkin
Journal:  Obes Rev       Date:  2014-01       Impact factor: 9.213

6.  Dietary Fat, but Not Protein or Carbohydrate, Regulates Energy Intake and Causes Adiposity in Mice.

Authors:  Sumei Hu; Lu Wang; Dengbao Yang; Li Li; Jacques Togo; Yingga Wu; Quansheng Liu; Baoguo Li; Min Li; Guanlin Wang; Xueying Zhang; Chaoqun Niu; Jianbo Li; Yanchao Xu; Elspeth Couper; Andrew Whittington-Davies; Mohsen Mazidi; Lijuan Luo; Shengnan Wang; Alex Douglas; John R Speakman
Journal:  Cell Metab       Date:  2018-07-12       Impact factor: 27.287

7.  Cardiovascular Diseases and Risk-Factor Burden in Urban and Rural Communities in High-, Middle-, and Low-Income Regions of China: A Large Community-Based Epidemiological Study.

Authors:  Ruohua Yan; Wei Li; Lu Yin; Yang Wang; Jian Bo
Journal:  J Am Heart Assoc       Date:  2017-02-06       Impact factor: 5.501

8.  Trends in energy intake among Korean adults, 1998-2015: Results from the Korea National Health and Nutrition Examination Survey.

Authors:  Sungha Yun; Hyun Ja Kim; Kyungwon Oh
Journal:  Nutr Res Pract       Date:  2017-03-02       Impact factor: 1.926

9.  Increased Inequalities in Health Resource and Access to Health Care in Rural China.

Authors:  Suhang Song; Beibei Yuan; Luyu Zhang; Gang Cheng; Weiming Zhu; Zhiyuan Hou; Li He; Xiaochen Ma; Qingyue Meng
Journal:  Int J Environ Res Public Health       Date:  2018-12-25       Impact factor: 3.390

10.  Global, regional, and national consumption levels of dietary fats and oils in 1990 and 2010: a systematic analysis including 266 country-specific nutrition surveys.

Authors:  Renata Micha; Shahab Khatibzadeh; Peilin Shi; Saman Fahimi; Stephen Lim; Kathryn G Andrews; Rebecca E Engell; John Powles; Majid Ezzati; Dariush Mozaffarian
Journal:  BMJ       Date:  2014-04-15
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  12 in total

1.  Associations between Adverse Childhood Experiences and Obesity in a Developing Country: A Cross-Sectional Study among Middle-Aged and Older Chinese Adults.

Authors:  Li Lin; Weiqing Chen; Weidi Sun; Minyan Chen; Jinghua Li; Jichuan Shen; Vivian Yawei Guo
Journal:  Int J Environ Res Public Health       Date:  2022-06-02       Impact factor: 4.614

2.  Dietary Intake and Chronic Disease Prevention.

Authors:  Annalisa Noce; Annalisa Romani; Roberta Bernini
Journal:  Nutrients       Date:  2021-04-19       Impact factor: 5.717

3.  Multi-Trajectories of Macronutrient Intake and Their Associations with Obesity among Chinese Adults from 1991 to 2018: A Prospective Study.

Authors:  Xiaofan Zhang; Jiguo Zhang; Wenwen Du; Chang Su; Yifei Ouyang; Feifei Huang; Xiaofang Jia; Li Li; Jing Bai; Bing Zhang; Zhihong Wang; Shufa Du; Huijun Wang
Journal:  Nutrients       Date:  2021-12-21       Impact factor: 6.706

4.  The Influencing Factors of Nutrition and Diet Health Knowledge Dissemination Using the WeChat Official Account in Health Promotion.

Authors:  Dongsheng Bian; Yongmei Shi; Wenjia Tang; Dong Li; Kangni Han; Chenshu Shi; Guohong Li; Fan Zhu
Journal:  Front Public Health       Date:  2021-11-25

5.  Food and Grain Consumption Per Capita in the Qinghai-Tibet Plateau and Implications for Conservation.

Authors:  Lijing Wang; Yi Xiao; Zhiyun Ouyang
Journal:  Nutrients       Date:  2021-10-23       Impact factor: 5.717

6.  Thirty-Year Urbanization Trajectories and Obesity in Modernizing China.

Authors:  Wenwen Du; Huijun Wang; Chang Su; Xiaofang Jia; Bing Zhang
Journal:  Int J Environ Res Public Health       Date:  2022-02-09       Impact factor: 3.390

7.  The Status of Dietary Energy and Nutrients Intakes among Chinese Elderly Aged 80 and Above: Data from the CACDNS 2015.

Authors:  Fanglei Zhao; Li He; Liyun Zhao; Qiya Guo; Dongmei Yu; Lahong Ju; Hongyun Fang
Journal:  Nutrients       Date:  2021-05-12       Impact factor: 5.717

8.  Trends and Urban-Rural Disparities of Energy Intake and Macronutrient Composition among Chinese Children: Findings from the China Health and Nutrition Survey (1991 to 2015).

Authors:  Jian Zhao; Lijun Zuo; Jian Sun; Chang Su; Huijun Wang
Journal:  Nutrients       Date:  2021-06-04       Impact factor: 5.717

9.  Jejunal mucosa proteomics unravel metabolic adaptive processes to mild chronic heat stress in dairy cows.

Authors:  Franziska Koch; Dirk Albrecht; Solvig Görs; Björn Kuhla
Journal:  Sci Rep       Date:  2021-06-14       Impact factor: 4.379

10.  Association between Milk Intake and All-Cause Mortality among Chinese Adults: A Prospective Study.

Authors:  Xiaona Na; Hanglian Lan; Yu Wang; Yuefeng Tan; Jian Zhang; Ai Zhao
Journal:  Nutrients       Date:  2022-01-11       Impact factor: 5.717

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