This study, set up as a cross-sectional survey, seeks to delve into the disease burden and the demographic specifics of lower urinary tract symptoms (LUTS) among the male community in China. The investigators's main aim is to map out the overall and age-specific prevalence rates of LUTS within the Chinese male population. These insights are critical for understanding the public health dimensions of this condition. Moreover, the investigators plan to investigate several secondary aspects: the correlation of LUTS prevalence with factors like urbanization levels (rural vs. urban), geographical distribution, and lifestyle choices. Another significant focus will involve examining the treatment landscape for LUTS, looking at the portion of sufferers receiving treatment, the diversity in treatment durations, and the types of treatments employed (medication vs. surgery). This comprehensive analysis is intended to shed light on the prevailing management strategies for LUTS in China. The study is scheduled to unfold over 36 months and will comprise three pivotal phases: initial preparations, recruitment of subjects and collection of data, followed by the analysis of data and compilation of reports. The investigators will employ a range of methods such as questionnaires, physical exams, laboratory tests, imaging, and other medical evaluations to amass extensive data. This will allow the investigators to evaluate the prevalence of LUTS across various age groups among men and address the current gaps in epidemiological understanding.

Divide the country into 7 geographical regions and stratify them according to urban and rural areas. Based on the size of the male population over 40 years old in the seventh National Census, employ a multi-stage proportional-to-size (PPS) sampling method. The sampling process is divided into six stages. In the first stage, use provincial-level administrative units as sampling units. Based on population size, use the PPS method to select 2 provincial-level administrative units from each region, totaling 14. In the second stage of sampling, use prefecture-level cities in each province as sampling units. The capital cities are directly sampled; based on population size, use the PPS method to select 1 other prefecture-level city from each province. In the third stage of sampling, use urban districts and counties (including county-level cities) in prefecture-level cities/direct-controlled municipalities as sampling units. Use the PPS method to select 2 urban districts and 2 counties in each prefecture-level city, and 4 urban districts and 4 counties in each direct-controlled municipality. In the fourth stage of sampling, use streets in urban districts and towns/townships in counties as sampling units. Use simple random sampling to select 1 street from each urban district and 1 town/township from each county. In the fifth stage of sampling, use communities in streets and villages in towns/townships as sampling units. Use simple random sampling to select 2 communities from each street and 2 villages from each town/township. In the sixth stage of sampling, stratify males over 40 years old in each community/village by age groups (40-49 years,50-59 years,60-69 years,70 years and above). Number individuals of each age group and randomly sample individuals. This survey includes four parts: questionnaire survey, physical examination, laboratory tests, imaging and other examinations. The questionnaire is conducted face-to-face by trained interviewers.

Inclusion Criteria:

1. Mainland China, aged 40 or older, male, in 31 provincial-level administrative regions.
2. Have resided for a total of 6 months or more in the survey county (district) in the past 12 months.
3. Normal communication, cooperation during physical examination, and good cognitive ability.
4. Willing to participate in and cooperate with this study, and sign the informed consent form.

Exclusion Criteria:

1. Closed communities, such as armed forces and nursing homes.
2. Individuals with mental illnesses or other conditions that prevent cooperation.

community sample

The data involves a large amount of personal information and privacy of the population, and the informed consent promises the confidentiality of personal data.