In the current study, two Chinese Northern provinces have relatively high HUA prevalence levels of 13.7% (21.1% in men and 7.9% in women). In the suburbs of big cities with higher standards of living, the HUA levels reach 20.3%, while HUA is only 10.4% in small and medium-sized cities with lower standards of living. To our knowledge, this was the first study to examine the differences in HUA prevalence by geographic region in areas inhabited by Chinese ethnic minorities. Our findings suggest that improved living standards bring about a series of changes in nutrition and metabolism which may have significant impact on HUA. In recent years, dozens of surveys on HUA prevalence in mainland China have been conducted . These surveys may not be representative of the entire Chinese population, because most of the study populations are with specific occupations such as state owned factories and mines laborers, or from specific regions such as coastal areas. Seven of these surveys applied randomized sampling, and these studies showed that the HUA prevalence in mainland China ranges from 9.2% to 25.6% in men and 1.3% to 15.3% in women, with significant differences in different areas [17–23]. Surveys in four regions of the Shandong coastal areas presented HUA prevalence ranges from 5.5% to 18.1% [18, 19]. In the developed areas of inland Chengdu, the HUA prevalence is 15.6% , while in underdeveloped inland Yan’an City the prevalence is 5.4% . According to our results and other published data, we concluded that the HUA prevalence is related to the level of regional economic development and living standards, not whether it is a coastal area. Of interest, in a big city the lifestyle and eating in the suburbs is similar to the city center, but HUA prevalence is higher in the suburbs, which may be because more health education is received in central urban area.
Similar to other researchers , we observed that HUA prevalence in women increased post menopause, which is consistent with estrogen protection and renal function in women gradually decreasing with age. However, menopausal status was not selected in the stepwise logistic regression model, possibly because of missing data (Of all 4714 women, 305 women missed the response to “menopausal status”). In participants aged over 75 years old, the HUA prevalence was higher for women than men. This may be because the decline in renal function of elderly women is faster, resulting in poor HUA buffering capacity. Alternatively, because of a small number of participants in this age group, the estimates presented here may lack reliability. Interestingly, the UA levels are high in young men. These high levels may be associated with high androgen levels in young adults, which promote kidney uric acid re-absorption . Unlike other reports , this study concluded that the lowest HUA prevalence for men is found in participants aged 55–64, and possible causes include that Chinese men of this phase are retired. At this age heavy labor and mental work also decrease, along with lifestyle changes and more attention on health. All of these factors could contribute to the relative control of uric acid levels at age 55–64.
Many studies have reported relationships between HUA prevalence and hypertension, high blood sugar, obesity and abnormal lipid metabolism and other metabolic abnormalities [26–28]. In this study, multiple logistic regression results have further confirmed the association between metabolic abnormalities and HUA, and have conducted further stratified analysis on each metabolic abnormality-related indicator. Our results have shown that TG and BMI are the most significant contributing factors to HUA prevalence, and that when TG ≥ 5.65 mmol/L, odds of HUA increase nearly 5-fold compared with TG < 1.69 mmol/L. In addition, obese participants have an HUA prevalence of 27.0%, while normal weight subjects have a prevalence of 8.9%, meaning that obese people have HUA prevalence 3.27 times that of those of normal weight. For traditional vascular disease risk factors like TC and LDL, to reach a certain level results in a small increase in HUA odds. This suggests that the lipids are involved in energy metabolism and can increase purine biosynthesis and catabolism, which can eventually contribute to HUA risk factors. However, hardening of the arteries caused by abnormal cholesterol that could cause kidney changes may not greatly contribute to HUA. Fasting blood glucose impaired patients have an HUA prevalence of 27.1%, but compared with normal blood glucose (19.2%), the difference is not significant. Although the HUA prevalence in high fasting blood glucose patients reaches up to 15.2%, the odds ratio reduces to 0.44, which may be because high fasting glucose subjects have already been diagnosed with diabetes and have already begun treatment. In stepwise multiple regression, we found that elevated blood pressure is a risk factor in women but not men. In addition, HUA prevalence in those pre-hypertensive and hypertensive were twice the prevalence of normotensives. Further study is needed to explore the differences of abnormal blood pressure impact on HUA prevalence in men and women.
In addition to blood pressure, other differences in HUA risk factors in different genders were obtained by stepwise multiple regression. Unique risk factors for women were mainly demographic characteristics such as marital status, while unique risk factors for men were mainly personal habits such as diet habits, smoking, alcohol consumption, and sleep time. This interesting phenomenon may indicate that men have less concern for their health. If this is true, active intervention measures to lower uric acid may be more effective for men. In addition, the study also found that participants from transportation and government agencies had high HUA prevalence (19.7% and 19.2%). A common feature of these two occupations is long periods of sitting. Additionally, it may not be possible for transportation employees to urinate on time; whether this factor could cause the increase of uric acid in renal tubular re-absorption remains to be further explored.
The study had several limitations. The study is based on a cross-sectional survey, which is unable to determine causality or the temporal relationship between metabolism indicators and HUA. In addition, parameters including some lifestyle factors and educational status were not filled in the questionnaire due to poor compliance of the local population, which resulted in the correlation of these parameters and hyperuricemia were unable to be analyzed completely because of a large amount of missing data.