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Table of Contents 
Year : 2016  |  Volume : 61  |  Issue : 3  |  Page : 261-264
Methodology series module 3: Cross-sectional studies

Department of Epidemiologist, MGM Institute of Health Sciences, Navi Mumbai, Maharashtra, India

Date of Web Publication13-May-2016

Correspondence Address:
Dr. Maninder Singh Setia
MGM Institute of Health Sciences, Navi Mumbai, Maharashtra
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/0019-5154.182410

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Cross-sectional study design is a type of observational study design. In a cross-sectional study, the investigator measures the outcome and the exposures in the study participants at the same time. Unlike in case–control studies (participants selected based on the outcome status) or cohort studies (participants selected based on the exposure status), the participants in a cross-sectional study are just selected based on the inclusion and exclusion criteria set for the study. Once the participants have been selected for the study, the investigator follows the study to assess the exposure and the outcomes. Cross-sectional designs are used for population-based surveys and to assess the prevalence of diseases in clinic-based samples. These studies can usually be conducted relatively faster and are inexpensive. They may be conducted either before planning a cohort study or a baseline in a cohort study. These types of designs will give us information about the prevalence of outcomes or exposures; this information will be useful for designing the cohort study. However, since this is a 1-time measurement of exposure and outcome, it is difficult to derive causal relationships from cross-sectional analysis. We can estimate the prevalence of disease in cross-sectional studies. Furthermore, we will also be able to estimate the odds ratios to study the association between exposure and the outcomes in this design.

Keywords: Cross-sectional studies, design, limitations, strengths

How to cite this article:
Setia MS. Methodology series module 3: Cross-sectional studies. Indian J Dermatol 2016;61:261-4

How to cite this URL:
Setia MS. Methodology series module 3: Cross-sectional studies. Indian J Dermatol [serial online] 2016 [cited 2023 Oct 2];61:261-4. Available from:

   Introduction Top

Cross-sectional study design is a type of observational study design. As discussed in the earlier articles, we have highlighted that in an observational study, the investigator does not alter the exposure status. The investigator measures the outcome and the exposure(s) in the population, and may study their association.

   Design Top

In a cross-sectional study, the investigator measures the outcome and the exposures in the study participants at the same time. Unlike in case–control studies (participants selected based on the outcome status) or cohort studies (participants selected based on the exposure status), the participants in a cross-sectional study are just selected based on the inclusion and exclusion criteria set for the study. Once the participants have been selected for the study, the investigator follows the study to assess the exposure and the outcomes.

After the entry into the study, the participants are measured for outcome and exposure at the same time [Figure 1]. The investigator can study the association between these variables. It is also possible that the investigator will recruit the study participants and examine the outcomes in this population. The investigator may also estimate the prevalence of the outcome in those surveyed.
Figure 1: Example of a cross-sectional study

Click here to view

   Examples of Cross-Sectional Studies Top

Antibiotic resistance in  Propionibacterium acnes Scientific Name Search ana et al., 2016)

A study by Sardana et al . evaluated the antibiotic resistance in isolates of Propionibacterium acnes in a tertiary care hospital in India. They recruited 80 patients of acne vulgaris, collected specimen for isolation from open or closed comedones. These specimens were then cultured, the growth identified, and antibiotic susceptibility and resistance were assessed.

They isolated P. acnes 52% of the cases. In these isolates, resistance for erythromycin, clindamycin, and azithromycin was observed in 98%, 90%, and 100% of the isolates, respectively. However, sensitivity for tetracycline, doxycycline, minocycline, and levofloxacin was observed in 69%, 56%, 98%, and 90% of the isolates, respectively. We will discuss this study briefly later in the manuscript as well.

HIV and male sex workers (Shinde et al., 2009)

The authors presented a cross-sectional analysis to assess the prevalence of HIV and risk behaviors in male sex workers. They also evaluated the association between HIV and sociodemographic factors. The data were collected by interviewer-administered questionnaires (for sociodemographic and behavior data), clinical evaluation for sexually transmitted infections (STIs), and serological evaluation for STIs (including HIV).

The authors reported that the prevalence of HIV in male sex workers was 33%. They also found that male-to-female transgendered people were significantly more likely to be HIV-infected compared with males (odds ratio [OR]: 3.5, 95% confidence intervals: 1.0, 11.7). Similarly, they also found that HIV prevalence was higher among those in whom sex work was the main occupation compared with those in whom sex work was not the main occupation (40% vs. 7%, P = 0.02).

There are numerous cross-sectional studies in the literature. We encourage the readers to go through some of these studies to understand the design and analysis of cross-sectional studies.

   Measurements in a Cross-Sectional Study Top

  1. Cross-sectional study designs may be used for population-based surveys

    Example: We are interested to know the prevalence of vitiligo in a village. We design a population-based survey to assess the prevalence of this condition. We go to all the houses that were supposed to be included in the study and examine the population. The total sample surveyed is 5686. Of these, we found that 98 individuals have vitiligo. Thus, the prevalence of vitiligo in this community is: Prevalence = 98/5686 or 17.23/1000 population

  2. Cross-sectional studies may also be used for estimating the prevalence in clinic-based studies.Example: Research question – What is the prevalence of HIV in patients presenting with an STI?

    We evaluate 300 patients with an STI clinic. We record this history, clinical examination, and test them for HIV antibodies (using ELISA) during their first visit to the clinic. We find that 60 of these individuals are HIV infected. Thus, we have detected a prevalence of 20% HIV infection among our STI patients. This type of study will be classified as a cross-sectional study. Kindly note that this being a clinic-based study, it may have all the limitations of a clinic-based study. Thus, the prevalence from these data may have limited generalizability. Nonetheless, this type of study design will be classified as a cross-sectional study.
  3. Cross-sectional studies may also be used to calculate the ORs

    For example, if we wish to understand the association between gender and HIV status, we will able to create a 2 × 2 table for the above-mentioned cross-sectional study. Of the 300 individuals evaluated, we have recruited 200 male and 100 female participants. Of the 60 HIV-infected individuals, 50 are males and 10 are females. The 2 × 2 table will be as follows:

    The OR (as discussed in the earlier methodology series – II case–control studies) is AD/BC or 50*90/10*150. Thus, the OR is 3.0. The interpretation of this OR is that males had a higher odds of being HIV infected compared with females. Since the OR is >1, the outcome is more likely in those exposed (males) compared with those who are not exposed (females). However, we will require confidence intervals to comment on further interpretation of the OR.

   Strengths of a Cross-Sectional Study Top

  1. Cross-sectional studies can usually be conducted relatively faster and are inexpensive – particularly when compared with cohort studies (prospective)
  2. These are studies are conducted either before planning a cohort study or a baseline in a cohort study. These types of designs will give us information about the prevalence of outcomes or exposures; this information will be useful for designing the cohort study
  3. These study designs may be useful for public health planning, monitoring, and evaluation. For example, sometimes the National AIDS Programme conducted cross-sectional sentinel surveys among high-risk groups and ante-natal mothers every year to monitor the prevalence of HIV in these groups.

   Limitations of a Cross-Sectional Study Top

  1. Since this is a 1-time measurement of exposure and outcome, it is difficult to derive causal relationships from cross-sectional analysis
  2. These studies are also prone to certain biases. For example, we wish to study the relation between diet and exercise and being overweight/obese. We conduct a cross-sectional study and recruit 250 individuals. We assess their dietary habits, exercise habits, and body mass index at one point of time in a cross-sectional survey. However, individuals who are overweight/obese have started to exercise more or altered their feeding habits (eat more salads). Hence, in a cross-sectional survey, we may find that overweight/obese individuals are also more likely to eat salads and exercise more. Thus, we have to be careful about interpreting the associations and direction of associations from a cross-sectional survey
  3. The prevalence of an outcome depends on the incidence of the disease as well as the length of survival following the outcome. For example, even if the incidence of HIV (number of new cases) goes down in one particular community, the prevalence (total number of cases – old as well as new) may increase. This may be due to cumulative HIV positive cases over a period. Thus, just performing cross-sectional surveys may not be sufficient to understand disease trends in this situation.

   Additional Points Top

As briefly discussed earlier, multiple cross-sectional surveys are used to assess the changes in exposures and outcomes in a particular population.

  1. The National AIDS Control Organisation's Sentinel Surveillance of HIV is an example of “serial cross-sectional study” or “serial survey.” This may be less expensive compared with a cohort study

    Sentinel Surveillance in Antenatal Clinic: The surveillance recruits consecutive consenting pregnant women, aged 15–45 years in these clinics. The exercise has been in place for nearly two decades. The formal annual sentinel surveillance was instituted in 1998. The surveillance provided data on the prevalence of HIV infection in antenatal women, and thus, the trends of HIV infection in this population

    Such surveys are also conducted in female sex workers, men who have sex with men, and people who inject drugs, migrants, truckers, and male-to-female transgendered people. Repeated cross-sectional surveys provide useful information on the prevalence of HIV in these groups [Figure 2]. It can be seen that the prevalence has, in general, reduced over the past decade in these groups. Thus, repeated cross-sectional surveys are also useful to monitor the trends over a period.
    Figure 2: Data from National HIV Sentinel Surveillance (2003–2011)*. *Graph generated from data in the National HIV Sentinel Surveillance

    Click here to view

  2. We will discuss the previous study by Sardana et al . They conducted one cross-sectional survey to assess the resistance patterns in P. acnes . If the authors conduct the same study consecutively for two more years, they will provide information on the changing resistance patterns in P. acnes. This will be an example of a serial cross-sectional study.

   Summary Top

In a cross-sectional study, the investigator measures the outcome and the exposures in the study participants at the same time. Unlike in case–control studies (participants selected based on the outcome status) or cohort studies (participants selected based on the exposure status), the participants in a cross-sectional study are just selected based on the inclusion and exclusion criteria set for the study. We can measure the prevalence of disease or calculate the OR as a measure of association. These studies are conducted relatively faster and are inexpensive. However, due to the nature of study design, in general, it is difficult to derive causal relationships from cross-sectional analysis.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

   Bibliography Top

  1. Hennekens CH, Buring JE. Epidemiology in Medicine. 1st ed. Philadelphia, USA: Lippincott Williams & Wilkins; 1987.
  2. Jewell N. Statistics for Epidemiology. Boca Raton, US: Chapman and Hall/CRC; 2004.
  3. Rothman KJ, Greenland S, Lash TL. Modern Epidemiology. 3rd ed. Philadelphia, USA: Lippincott Williams & Wilkins; 2008.
  4. Kleinbaum D, Kupper L, Morgenstern H. Epidemiologic Research. New York, US: John Wiley and Sons, Inc.; 1982.
  5. National AIDS Control Organisation. HIV Sentinel Surveillance 2012-13: A Technical Brief. New Delhi, India: Ministry of Health & Family Welfare, Government of India.
  6. Sardana K, Gupta T, Kumar B, Gautam HK, Garg VK. Cross-sectional pilot study of antibiotic resistance in Propionibacterium acnes strains in Indian acne patients using 16s-RNA polymerase chain reaction: A comparison among treatment modalities including antibiotics, benzoyl peroxide, and iso tretinoin. Indian J Dermatol 2016;61:45-52.
  7. Setia MS. Methodology series module 1: Cohort studies. Indian J Dermatol 2016;61:21-5.
  8. Setia MS. Methodology series module 2: Case-control studies. Indian J Dermatol 2016B; 61:146-51.
  9. Shinde S, Setia MS, Row-Kavi A, Anand V, Jerajani H. Male sex workers: Are we ignoring a risk group in Mumbai, India? Indian J Dermatol Venereol Leprol 2009;75:41-6.
  10. Hulley SB, Cummings SR, Browner WS, Grady D, Hearst N, Newman TB. Designing Clinical Research. 2nd ed. Philadelphia, USA: Lippincot Williams & Wilkins; 2001.
  11. Szklo M, Nieto FJ. Epidemiology: Beyond the Basics. Sudbury, MA: Jones and Bartlett Publishers, Inc.; 2004.


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60 COVID-19 Vaccination Perceptions in Patients With Rheumatic Disease: A Cross-Sectional Online Survey
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61 Knowledge of Sarcopenia and Associated Factors Among the Malaysian General Public: A Cross-sectional Study
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62 Effectiveness of the Force Account Approach in Tanzanian Local Government Authorities: Do Management Support and Staff Competence Matter?
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63 Pre-Service English Teachers' Awareness of Formulaic Language Use: Implications for Language Instruction
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64 Overview of Acceptance Islamic Payment Gateway System in Malaysia: a Conceptual Framework
Ahmad Mujahid Mat Rasid, Mohammed Hariri Bakri, Mohamad Idham Md Razak, Albert Feisal Muhd Feisal Ismail, Nurul Zarirah Nizam
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65 Anatomical Considerations for Gallbladder Sonography: A Cross-Sectional Study of CT Imaging by the BMI Group
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67 Perceptions and Beliefs About Preconceptional Care Among Primary Healthcare Workers in Jeddah City, Saudi Arabia: An Analytical Cross-Sectional Study
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68 Virtual surgical consultation during the COVID-19 pandemic: a patient-oriented, cross-sectional study using telephone interviews
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69 Racial and Sociodemographic Disparities in Telehealth Access and Utilization during the COVID-19 Pandemic
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70 When to Collect Data? Choosing an Appropriate Time Frame for Data Collection During Ph.D. Program in India?
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71 Physical need assessment of recovery among patients with burn injuries: nursing implications
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72 Knowledge, Practice, Compliance, and Barriers toward Ventilator-Associated Pneumonia among Critical Care Nurses in Eastern Mediterranean Region: A Systematic Review
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73 Students’ Academic Performance and Perceptions towards Online Learning during the COVID-19 Pandemic at a Large Public University in Northern Cyprus
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74 Islands of Milk Insecurity in World’s Leading Milk Producer: A Case of Andaman and Nicobar Islands, India
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75 Fair Play in a Context of Physical Education and Sports Behaviours
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76 Determinants of Burnout among Teachers: A Systematic Review of Longitudinal Studies
Dragan Mijakoski, Dumitru Cheptea, Sandy Carla Marca, Yara Shoman, Cigdem Caglayan, Merete Drevvatne Bugge, Marco Gnesi, Lode Godderis, Sibel Kiran, Damien M. McElvenny, Zakia Mediouni, Olivia Mesot, Jordan Minov, Evangelia Nena, Marina Otelea, Nurka Pranjic, Ingrid Sivesind Mehlum, Henk F. van der Molen, Irina Guseva Canu
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77 Health Literacy Level and Comprehension of Prescription and Nonprescription Drug Information
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78 Perceived Gap of Age-Friendliness among Community-Dwelling Older Adults: Findings from Malaysia, a Middle-Income Country
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79 Socio-Ecological Factors and Well-Being among Self-Employed in Europe during the COVID-19 Pandemic
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80 Recreation and Alcohol Consumption in Sub-Saharan Africa: Addressing Gender and Age Differences in Urban Areas—Praia, Cabo Verde
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81 Noise Disturbance and Well-Being in the North of Spain
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82 Urbanicity—Perspectives from Neuroscience and Public Health: A Scoping Review
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83 Common Bias and Challenges in Physical and Rehabilitation Medicine Research: How to Tackle Them
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84 Analysis of disease burden in socially disadvantaged areas: Mapping of geographical inequalities in COVID-19 morbidity and mortality using a social disadvantage index in Tennessee
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85 Exploring the Early Impacts of the COVID-19 Pandemic on the Construction Industry in New York State
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86 Commentary: Association between methylmalonic acid and cognition—A systematic review and meta-analysis
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87 The impact of long-term orientation on compulsive buying behavior: A cross-cultural study
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88 Prevalence and risk factors of diabetic foot disease among the people with type 2 diabetes using real-world practice data from Catalonia during 2018
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89 Teachers' Perceptions of Ibox Use for Integrated Science Lessons in Secondary Education Improvement Project Schools
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90 The Influence of Icts in Promoting Awareness and Climate Change Conscious Activities within the Okavango Delta Community of Shakawe, Botswana
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91 Non-technical dimensions of communal wastewater treatment plant sustainability in peri-urban Yogyakarta, Indonesia
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92 Applicability of the mandibular canine index for sex estimation: a systematic review
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93 Demystifying the effect of social media eWOM on revisit intention post-COVID-19: an extension of theory of planned behavior
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94 Acceptability and associated factors of indoor residual spraying for malaria control by households in Luangwa district of Zambia: A multilevel analysis
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95 Awareness and willingness to use HIV oral pre-exposure prophylaxis among people who inject drugs in Dar es Salaam, Tanzania: A cross-sectional survey
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96 Are adults diagnosed with type 2 diabetes at a greater risk of developing depression? Integrative literature review
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97 Identifying cow – level factors and farm characteristics associated with locomotion scores in dairy cows using cumulative link mixed models
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98 A machine learning approach using partitioning around medoids clustering and random forest classification to model groups of farms in regard to production parameters and bulk tank milk antibody status of two major internal parasites in dairy cows
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102 Short-chain fatty acid concentrations in the incidence and risk-stratification of colorectal cancer: a systematic review and meta-analysis
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103 Socio-demographic factors associated with medication adherence among People Living with HIV in the Kumasi Metropolis, Ghana
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104 Gait disorders in CKD patients: muscle wasting or cognitive impairment? A cross-sectional pilot study to investigate gait signatures in Stage 1–5 CKD patients
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105 Exploring health provider’s knowledge on the home-based maternal and neonatal health care package in Rwanda
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106 Do motorcycle helmets reduce road traffic injuries, hospitalizations and mortalities in low and lower-middle income countries in Africa? A systematic review and meta-analysis
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107 Resilience: Key Factors Associated With Resilience of Older People in Botswana
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108 Variation in the Use of Basic Behavioral Management Techniques in General and Pediatric Dental Practice: A Cross-sectional Study
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109 Exploring the eHealth literacy and mobile health application utilisation amongst Malaysian pharmacy students
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111 Obtaining the best value for money through procurement planning: can procurement regulatory compliance intervene?
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113 The predicting effects of professional governance and structural empowerment on job satisfaction among Jordanian nurses: A cross-sectional study
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115 Racial Discrimination and Race-Based Biases on Orthopedic-Related Outcomes
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116 Associations between duration and volume of muscle-strengthening exercise and clinically assessed hypertension among 10 519 UK adults: a cross-sectional study
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119 Comparative Analysis of the Impact of Energy Security on Productivity of SMEs in the Accra Metropolis of Ghana
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120 Psychosocial Functioning and Occupational Participation among Adolescent Children of Parents with Mental Illness: A Mixed Methods Study
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125 Choosing a package carrier during COVID-19 pandemic: An integration of pro-environmental planned behavior (PEPB) theory and service quality (SERVQUAL)
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126 Sociodemographic and clinical correlates of cannabis dependence among Israeli combat veterans
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127 Necessary political competences for nurses from the perception of the student body: Cross-sectional study in Spain
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128 Hazard characterization of bisphenol A (BPA) based on rodent models – Multilevel meta-analysis and dose-response analysis for reproductive toxicity
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129 Local communities' knowledge and perception of FLEGT -VPA - insights from Ghana
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130 Arsenic concentration in topsoil of central Chile is associated with aberrant methylation of P53 gene in human blood cells: a cross-sectional study
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131 Handgrip strength is associated with learning and verbal fluency in older men without dementia: insights from the NHANES
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134 Zooming in or Zoning Out: Examining Undergraduate Learning Experiences and Why Students’ Mind-wander on Zoom
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135 Smog and cognitive issues in the school going children of Lahore and Islamabad, Pakistan
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136 COVID-19 Pandemic Associations on Mental and Physical Health in African Americans Participating in a Behavioral Intervention
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137 Holistic Individual Fire Preparedness in Informal Settlements, Bangladesh
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138 Investigation of the relationships between ADHD risk and digital screen exposure in children aged 4–11: A large population study in Turkey
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139 What is essential remains invisible to the eyes? Blood pressure cuffs colonized by bacterial diversity
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140 Transdiagnostic vulnerability factors in eating disorders: A network analysis
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141 Acceptability of the Direct Health Facility Financing (DHFF) initiative in Tanzania: A mixed methods process evaluation of the moderating factors
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142 Predictors of Seat-Belt Use among Bus Passengers in Ghana: An Application of the Theory of Planned Behaviour and Health Belief Model
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143 Trends in health-related quality of life of female breast cancer survivors using the Medical Expenditure Panel Survey (MEPS), 2008–2016
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147 Household Happiness and Fuel Poverty: a Cross-Sectional Analysis on Turkey
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