1. Introduction
The global epicenter of non-optimal cholesterol is shifting to low- and middle-income countries, with China ranked as the top countries with the largest magnitudes of increase in mean non-high-density lipoprotein (HDL) cholesterol [
1,
2]. Along with the surge of dyslipidemia was remarkably increased prevalence and a heavy burden of cardiovascular diseases in China [
3]. As a consequence of dietary and behavioral changes, dyslipidemia, usually diagnosed by multiple lipid biomarkers which have mutually independent effects on cardiovascular diseases and mortality, has long been suggested to be primarily managed by modifying dietary intakes, which included limiting total fat and saturated fatty acids (SFA) intake to less than 35% of total energy (TE) and 10% TE, respectively [
4,
5,
6]. Without the assessment of plant oils intake, which is the major source of dietary fats in Chinese adults, the PURE (prospective urban rural epidemiology) study suggested the potential beneficial effect of total fat and the advantage of SFA over carbohydrates on blood lipids [
7,
8]. Additionally, more and more evidence, from Western countries predominantly, suggests the quality of dietary fats, especially food sources of SFA and monounsaturated fatty acids (MUFA), might be more important than quantity in their relations to blood lipids and cardiovascular diseases, with most approval to plant sources and disapproval to animal sources of fats [
9,
10,
11,
12,
13,
14,
15].
The traditional high-carbohydrate diet in the Chinese population is rapidly Westernized with upward fat intake, but the dietary fat intake profile, particularly of various types and food sources, was not fully illustrated with national representative data [
8,
16,
17]. Surprisingly, few studies systematically investigated the effect of dietary fats, particularly of various types and sources, on multiple lipid biomarkers in the Chinese population, although one study conducted in north China had linked dietary patterns with a single lipid marker of HDL cholesterol (HDL-c), and another study with national samples linked increased pork intake with hypercholesterolemia [
18,
19]. To fill the gap, we aimed to study the profile of dietary fat intake of the Chinese population and comprehensively investigate the relationships of dietary fats with lipid biomarkers across various types and sources of dietary fats using data from China Nutrition and Health Surveillance (CNHS) (2015–2017). Our second aim was to examine whether these relationships vary by intake level, and to assess the replacement effect of various fats with carbohydrate/other fats on lipid biomarkers and compare them with the results of the PURE study.
2. Materials and Methods
2.1. Study Population
Data used for analysis were from the CNHS (2015–2017), a national surveillance periodically conducted by the Chinese Center for Disease Control and Prevention (CDC). The present study used data of adult surveillance in 2015. Details about designs, sampling methods, and data collection of the surveillance had been described elsewhere [
20,
21]. Briefly, the CNHS (2015–2017) covered 298 survey sites across 31 provincial administrative units in mainland China. A stratified, multistage, probability-based random sampling scheme was used to select eligible participants, who were aged 18 years and older, living in the sample area for more than 6 months during last 12 months. The targeted population of this cross-sectional study was adults aged between 30 and 70 years (48,693 cases in total). The whole sample (48,315 cases) for analysis of dietary fat profiles among the targeted population excluded 378 participants with abnormal energy intake (<500 kcal or >4000 kcal/day), while the selected sample (39,115 cases) for analysis of the relationships between dietary fats and blood lipids further excluded participants with diagnosed cardiovascular diseases (CVD), cancer (5590 cases), dyslipidemia (2456 cases), or diabetes (1154 cases).
2.2. Assessment of Dietary Fats
Diet was assessed using 3 days (2 weekdays and 1 weekend) of 24 h dietary recalls in addition to weighing household cooking oils and condiments. For each dietary recall day, trained investigators went to the participant’s home and helped to recall and record food items and intakes (eaten in home and outside) during the last 24 h. Investigators also weighed the household cooking oil and condiments, and recorded the number of diners (including guests) at each meal in the home as well as their sex, age, and physical activity level at the beginning and end of each 24 h survey. This information was used to allocate the 3-day consumption proportion of cooking oils and condiments for each participant in the household, and calculate their actual number of meals and consumption during the 3 days.
Each food item (including cooking oils and condiments) was coded according to the constantly updating Chinese Food Composition Database (
https://www.phsciencedata.cn/Share/ky_sjml.jsp?id=577e0301-ab65-432a-9bb7-a8342302e589, accessed on 7 September 2022), classified as animal or plant source according to the major food composition, and further classified into 12 food groups, including pork, other meats, processed meats, poultry, fish, dairy and eggs, nuts and soybeans, oils of high MUFA, oils of high polyunsaturated fatty acids (PUFA), MUFA–PUFA balanced oils, oils of high saturated fatty acids (SFA), and other foods (for detailed definitions see
Supplementary Materials File S1 and Table S1) [
22,
23]. Fat intakes of various types and sources were then calculated using the database.
2.3. Assessment of Blood Lipids
A fasting blood sample of the participants was collected by health professionals from the local CDC. Serum was separated from the blood and placed in the car refrigerator or box with ice cubes, delivered to the laboratory of the local CDC, and stored in the refrigerator at −20 °C within 2 h. Then, within one week after sample collection, samples were frozen at −80 °C and shipped by air with dry ice to the central laboratory in Beijing, China. Fasting blood samples were analyzed for total cholesterol (TC), low-density lipoprotein (LDL) cholesterol (LDL-c), HDL-c, and triglycerides (TG). The ratio of TC to HDL-c (TCHDL) and the ratio of TG to HDL-c (TGHDL) were also calculated.
2.4. Covariates Assessment
Age, sex, ethnic group (Han, Zhuang, Manchu, Hui, Miao, Uygur, Yi, Tujia, Mongolia, Korean, Tibetan, and other ethnic), education level (illiteracy, primary school, middle school, high school, and college and above), physical activity, drinking behavior (never, moderate, or excessive (15–24.9 or ≥25 g/day)), smoking behavior (never, ever, or current (<10, 10–19, or ≥20 cigarettes/day)), and health information (family history of cardiovascular diseases and diabetes) were collected with individual questionnaires. Physical activity was measured with the global physical activity questionnaire (metabolic equivalent of task (MET)-h/week), and drinking behavior was collected by the food frequency questionnaire.
2.5. Statistical Analysis
Means (standard deviations (SDs)) or median (interquartile range (IQR)) were calculated to summarize continuous variables. Weights were calculated for estimation of population weighted dietary indicators. Methods to calculate weights were reported by a previous study [
24]. The socioeconomic structure of the 2015 Chinese population estimated by the State Statistics Bureau (
https://data.stats.gov.cn, accessed on 4 March 2022) was the basis for the post-stratification weights. General liner model was performed to test the differences and linear trends of dietary indicators among participants with different characteristics, and to estimate the relationship of various dietary fats with lipid biomarkers. The strength of associations between the various dietary fats and blood lipids indicators were compared in common units by standardized coefficients that represented the number of SDs a lipid marker changed per 1 SD increase in dietary fats. Participants with diagnosed hypertension were further excluded in sensitivity analyses. Low or high intake of dietary fat was categorized by the median of total fat intake, and stratified analysis was performed to assess the effect of fat intake level on the slope of association between various fat and lipid biomarkers. Nutrient residual model was used to estimate the effect of isocaloric replacement of various fats with carbohydrate or other fats [
25]. In this procedure, the fat intakes of the individuals were regressed on their total energy intakes. The residuals, representing the differences of individuals’ actual intake independent of energy intake, plus the term of TE were both included in the models. Data analyses were performed with SAS version 9.4 (SAS Institute, Inc., Cary, NC, USA).
4. Discussion
With national data from the CNHS (2015–2017), this observational study illustrated the high intake of total fat, the dominance of plant fat and MUFA in total fat and pork-source fat in animal fat, among the Chinese population, and the slightly favorable effect of total fat on blood lipids compared with carbohydrate. However, animal fats and SFA, were possibly more harmful than carbohydrate when total fat was high (>34.9% TE). While, regardless of fat intake level, plant fat and PUFA were most favorable, especially when used to replace animal fat and SFA. Notably, SFA and MUFA (even plant MUFA) posited an opposite relationship direction with TG and TGHDL before and after their median intakes, and MUFA showed adverse effects on TG, compared with carbohydrate and SFA, despite the effect only being significant when total fat was high. The present study showed a less harmful effect of replacing SFA with carbohydrate and more beneficial effect of replacing SFA with unsaturated fats than the PURE study.
To our knowledge, this is the first study using national representative data to illustrate the contribution of dietary fats in various types and food sources to total fats among Chinese adults. The findings can help the development of food-based dietary guidelines for this population and trans-ethnic comparisons with other populations. Additionally, this is the first comprehensive study to determine the relationship of dietary fat intakes with lipid biomarkers in the Chinese population, with a focus on the effect of type, source, and intake level of dietary fats on multiple lipid biomarkers, which can help to observe the net effect of various dietary fats on blood lipids. Furthermore, the comparison of the present findings with the WHO review and the PURE study can help in developing population-targeted strategies and guidelines in blood lipids management.
The findings suggest the dietary fat intake of Chinese adults had reached a comparably high level with America and most European countries, yet with significant disparities in types and food sources: higher portion of PUFA for higher plant oils intake, higher proportion of pork-source fats in animal fat, lower SFA from dairy, meat, and meat products, and slightly lower MUFA intake, which is consistent with a previous study and complements some new findings to that one [
8,
28,
29]. However, the high intake of dietary fats appeared to not be associated with an overall deteriorative effect on blood lipids, albeit the very slight increase in TC and LDL-c. A cross-sectional study in Korean adults suggested that total fats were associated with higher odds of abnormality in LDL-c and TC, but lower odds of TG abnormality [
30]. Prospective studies in Western populations had suggested that total fat intake was not associated with CVD risk [
31,
32,
33]. Whether such slight increases in LDL-c, the causal risk biomarker of CVD, can be interpreted as the cause of increased CVD incidence or mortality in the Chinese population requires further studies, which is scarce currently.
The present findings suggested the quantity of dietary fat could affect the association of dietary fats of different types and sources with lipid biomarkers. The replacement of SFA and animal fat with carbohydrate showed both harmful and beneficial effects on blood lipids when total fat was low, but more harmful effects when it was high. In comparison, the PURE study only indicated the neutral effect of SFA and advantage of SFA over carbohydrate on blood lipids. Although the PURE study considered the impact of fat intake level, it seriously underestimated the actual intake of dietary fats in the Chinese population (17.7% TE vs. 34.8% TE in present and 33.2% TE (2011) in previous), particularly unsaturated fats, for no assessment of plant oils [
8]. Hence, it can yield a more biased estimation in the replacement effect of SFA with carbohydrate and unsaturated fats, and could not exactly be applicable to the Chinese population, particularly the majority who consumed relatively high energy from fat. Despite this, the present results support part of its conclusion that SFA might have a neutral effect on blood lipids when it was replaced by carbohydrate and when total fat intake was low, since the present study did observe a beneficial effect of SFA on lowering TG and TGHDL, and elevating HDL-c, albeit the possible harmful effect on elevating TC and LDL-c. In fact, moderate SFA intake (about 7.5% TE in present study) could represent a more balanced diet, particularly for a population with traditionally high carbohydrate intake and with high prevalence of high TG and low HDL-c [
34].
Notably, high fat intake also appeared to affect the relations of MUFA (even plant MUFA) with blood lipids, and undo some of its beneficial effects (lowering TG and TGHDL, for instance) when total fat was high [
35]. The WHO review, whose subjects were predominantly from North America and Europe, indicated a significant reduction of TG and TGHDL when replacing SFA with MUFA, but it did not consider the impact of total fat intake, let alone the impact of disparate food patterns across other districts of the world [
26]. On one hand, the increased fat intake level has been suggested to be associated with a higher risk of obesity in the Chinese population, which is directly associated with hypertriglyceridemia [
36,
37]. On the other hand, higher consumption of dietary fats, although most were plant oils, often was accompanied by higher meat intake (pork as the dominance, whose MUFA is in the largest proportion) in the Chinese population, particularly the southern residents [
23,
38]. This explained why animal MUFA and animal SFA contributed most to the increased percentage of total fat after the median intake, and why MUFA intake (animal and plant) was higher in southern residents. A previous prospective study in the Chinese population indicated that diets of high animal fat (low carbohydrate) were associated with a higher risk of hypertriglyceridemia (odds ratio (OR) = 1.51) [
39]. The high intake of SFA and MUFA, of animal source particularly, when total fat was high, could be exactly the result of such a diet. In addition, regardless of the types, the present study showed the same relationship direction of dietary fats in animal or plant sources with lipid biomarkers. Prospective studies in Western countries also suggested the food source of dietary fats might count more in their relationships with CVD risk [
12,
13,
14,
31].
Compared with the WHO review and other clinical trials, the present results indicated a similar beneficial effect of replacing saturated fats with PUFA on lipid biomarkers, but with a smaller magnitude [
40,
41]. In addition to the mentioned disparities in food patterns, cooking methods of plant oils might also play a role, since many Chinese cuisines were stir-fried, which could impair some beneficial effects of PUFA by oxidation [
42].
The present study had some limitations. The effect of MUFA on lipid markers could be complexed by SFA, due to the simultaneous occurrence of MUFA and SFA in animal fats. The nonlinear relationship of fat intake with lipid biomarkers could lead to bias of estimation when using a linear-based regression model, although the stratification analysis had been performed. Fatty acids of some mixed foods, particularly processed food, were unable to be accurately estimated for the incomplete data in the Chinese Food Composition tables (FCT). We complemented some of them by estimation from similar foods, and referring to the Japanese FCT and United States Department of Agriculture (USDA) food composition database. Furthermore, we did not assess the impact of trans fats on blood lipids, which might affect the replacement effect of other fats. Lastly, we did not assess the optimal fat intake level for blood lipids management in the Chinese population, which is worth further study.