Variations in Gender Perceptions of Summer Comfort and Adaptation in Colonial Revival-Style Homes

Abstract

Past investigations have assessed gender variations in thermal comfort and adaptation in different buildings. However, no reported study has evaluated differences in gender perceptions of the thermal environment in US Colonial Revival-style homes. As a result, this study aims to provide an understanding of variations in gender perceptions of summer comfort and adaptation in the buildings. The study evaluated data collected during the field studies of thermal comfort (FSTC), including physical measurements of environmental variables and subjects’ votes. In this study, 67% females and 33% males participated in the field surveys in summertime. The mean neutral temperature of 25.5 °C and preferred temperature of 24.9 °C were noted for females. For males, the mean neutral and preferred temperatures of 25.8 °C and 25.6 °C were observed. Females feel neutral and prefer “no change” to the thermal environment at lower temperatures than males. A difference of 0.3 °C was noted between the average heat indices for females and males. Male respondents who feel warm perceive less air quality more than females. Females and males who perceive being thermally comfortable also perceive good air quality. Females and males who are thermally comfortable rated air humidity to be acceptable. There are similarities and differences between gender perceptions of the thermal environment. The investigation suggests interventions that can help users regulate their skin temperatures and use control measures that are sensitive to clothing insulation. The research also calls for policies that can promote building users’ pivotal adaptive measures to improve their indoor thermal environment. The study enhances our understanding of sustainable indoor environments and how to improve living conditions and adaptive modifications among different groups of occupants in buildings.

1. Introduction

The United States is a country with a blend of cultural backgrounds, diverse ethnicities, and immense talents [1,2]. The nation is usually referred to as the land of cultural diversity. These features and many other attributes make the United States known as a “melting pot” [1]. Even as a nation, the United States also has a diverse geographical landscape and different climate regions. According to Baechler et al. [3], the United States is divided into seven different “Building America Climate” regions. The climate regions include cold, very cold, mixed–humid, hot–humid, mixed–dry, hot–dry, and marine. Additionally, in the “Building America Climate” regions, there are different typologies of residential buildings [4]. The typologies include single-family detached, single-family attached, mobile residences, multi-family between two and four units, multi-family of five or more units (1–3 stories), and multi-family of five or more units (four and above stories). The wall structure of these typologies is classified into masonry, steel frame, and wood frame. Among the prominent multi-family typologies is the Colonial Revival-style multi-family of 2–4 units that are common in the Northeast region of the US [5,6]. Colonial Revival-style buildings are popular in the region for many reasons (such as their unique architectural features, acceptability, form, aesthetic, visual appearance, etc.) and due to the architectural influence of early European settlers. Some states within the region are also known as “New England”. The summary of the climatic data of the US Northeastern region in winter and summer is presented in

Table 1. Averages of the climatic data of the study region in winter and summer.

Variables	Winter	Summer
Maximum temperature (°C)	19.3	35.7
Mean maximum temperature(°C)	15.3	34.0
Average high temperature (°C)	4.3	27.0
Daily mean temperature (°C)	0.3	22.0
Average low temperature (°C)	−4.0	17.3
Mean minimum temperature (°C)	−15.3	11.7
Minimum temperature (°C)	−19.3	9.0
Average precipitation (mm)	95.7	130.3
Average precipitation days (≥1 mm)	9.3	12.3
Mean monthly sunshine hours	172.7	332.0
Mean daily daylight hours	9 h 10 min	14 h 14 min
UV index (month maximum)	3.3	9.7
Wind speed (m/s)	2.8	1.7
Solar energy (kWh)	2.2	6.4
Water temperature (°C)	5.5	19.3
Snowfall (mm)	223.9	0.0
Cloud cover (fraction)—clearer (%)	47.7	58.0
Cloud cover (fraction)—cloudier (%)	52.3	42.0

.

The existing research explained retrofit approaches that deliver reductions in air infiltration in such residences [4]. The study also noted that those strategies should be executed in ways that could reduce or eliminate disruption to occupants’ activities when internal modifications are considered. According to the United Nations Environment Programme Finance Initiative (UNEP FI), approximately 40% of carbon dioxide emissions across the world come from buildings. Of these emissions, building operations account for about 70%, and construction accounts for the remaining 30% [7]. Likewise, Colonial Revival-style residences contribute to the increasing energy consumption in the region because the majority of these buildings were built over seven decades ago. Some of the buildings have undergone partial or total retrofitting, such as the installation of energy-efficient windows, doors, walls, roofs, the addition of insulation, and other measures. However, a significant percentage of these buildings are yet to be retrofitted. These observations suggest higher air infiltration rates, which could impact the overall energy performance of these buildings.

Past studies [5,6] have assessed energy assessment, summertime overheating, and perceptions of occupants’ comfort, control, and adaptation in Colonial Revival-style residences. Also, other studies have assessed the performance of residences and other types of buildings with similar architectural styles and elements in different regions [8,9]. Equally, Indraganti and Humphreys [10] conducted a comparative analysis of gender variations on occupants’ comfort and satisfaction in non-naturally ventilated offices in three Asian countries. The investigation noted that elevated indoor air speeds and the provision of environmental controls could significantly decrease female dissatisfaction and reduce energy consumption in the study location. Indraganti and Humphreys found out that females in the study locations had considerably lower comfort temperatures and mean air speeds than males. The study recommends the need to capture the female points of view and thermal expectations in the design of spaces. However, none of these studies assessed gender variations in the perceptions of thermal comfort and adaptation in Colonial Revival multi-family residences. To the best of the found knowledge, this is the first study that considers a comparative study evaluation of gender variations in perceptions of thermal comfort and adaption in the residences in the study location.

1.1. Literature Review

Fanger and Beshir and Ramsey examined gender studies in regulated thermal environments [11,12]. On the one hand, Fanger reported no differences in gender preferences in the climate-chamber environment [11]. On the other hand, Beshir and Ramsey identified differences in gender preferences in the thermal environment [12]. Field investigations on thermal comfort across various regional climates [13,14,15,16,17,18] and reviews of the literature [19,20,21] also revealed diverse outcomes regarding people’s perceptions of the thermal environment. Additionally, since most geographical areas do not have regional adaptive thermal comfort standards and local building codes to accurately evaluate thermal comfort at the design phase, the predicted mean vote (PMV) model is often considered as a technique to assess thermal comfort in various thermal environments [22,23,24,25].

Zhai et al. examined the thermal comfort of university students in a controlled environment, a hall of residences, and teaching spaces [26]. The study noted that both male and female respondents were similarly satisfied with the environmental thermal conditions, regardless of the region. Zhai et al. also observed a higher rate of dissatisfaction among female respondents than male respondents on the cooler part of the scale, while there was a higher rate of dissatisfaction among male respondents than female respondents on the warmer part of the temperature scale in the regulated environment. In the field investigation conducted along with the study in a regulated environment, differences between genders were similar because the respondents were allowed to adjust their clothing insulation. Karyono and Indraganti et al. assessed gender variations in non-residential buildings in Asian countries and observed higher comfort temperatures among female respondents than male respondents [15,16].

Additionally, Kwak et al. noted that male respondents had noticeably higher average skin temperatures under a cooling environment and lower skin temperatures under a heating environment than female participants [14]. Indraganti and Humphreys noted that female respondents’ more rigorous thermal comfort preferences could be considered to assess occupant control provisions and indoor environmental quality benchmarks [10]. Also, Karjalainen conducted a study within the thermal environment in Finland and noted that male respondents were more satisfied with the temperatures than female respondents [17]. Karjalainen explained further that those female occupants preferred higher room temperatures, and they felt uncomfortably cold and uncomfortably hot more regularly than male respondents.

The existing research explored databases on thermal comfort [18,19,27,28] and post-occupancy evaluation [29] to investigate gender differences and their perceptions of the thermal environment in various spaces. An existing study that reviewed a substantial database noted that female occupants are likely to suffer from sick building syndromes, like headache and fatigue, more often than male occupants in approximately 79% of the thermal environment investigated [18]. Wang et al. utilized the size effect (i.e., mean difference) to determine if gender has a noticeable effect on thermal sensation or neutral temperature [19]. The investigation revealed gender had no significant effect on thermal sensitivity or neutral temperature.

In another investigation, the outcome of a meta-analysis of the study showed males are less sensitive than female respondents, while females are likely to be almost two times more dissatisfied than male respondents. Likewise, small differences between neutral temperatures for males and females were reported [20]. Also, the effect of size and significance to establish differences between gender as well as age groups could not be strongly determined [21]. Variations are also reported between male and female respondents regarding the use of thermostats and thermal comfort settings within the thermal environment [20,30]. The existing research revealed that there is a possibility of variations between males and females relating to the use of thermostats and other control measures in buildings [20,29,30]. Therefore, it is important to further evaluate these variations in different thermal environments.

A study utilized an exergy technique to investigate differences in clothing insulation and hormonal scenarios between males and females [31]. The study reported similarities between comfort temperatures within the phase for male and female occupants when they put on light clothing insulation. Other investigations also evaluated indoor environmental conditions and noted that comfortable thermal conditions can promote people’s health, well-being, and productivity [14,32,33,34,35,36]. The existing research noted that the respondents who are thermally satisfied also reported a higher level of productivity and better perception of their spaces than those who are not thermally dissatisfied [37,38]. The literature further revealed that sustaining a comfortable thermal environment can promote occupants’ productivity and reduce the frequency of complaints of thermal dissatisfaction in buildings [29,30,39]. Even though facilities managers are tasked with responding to users’ complaints in some buildings, especially non-residential buildings, maintaining a comfortable indoor thermal environment is likely to reduce the frequency of users’ complaints [10]. Hence, the current study examines whether there are noticeable differences in the perceptions of summer comfort and adaptation between male and female residents of the selected buildings.

1.2. Significance of the Research and Objectives

A report outlined the gender gap index ratings in different countries across the globe and noted that reducing gender inequality can significantly enhance the overall development of a society [40]. While existing research has examined gender variations in thermal comfort and satisfaction in residential [17,27,30] and non-residential buildings [10,16,18], another study discussed the roles of gender and thermal comfort negotiations in energy-use behavior in homes [30].

The novelty of the study is to provide an understanding of differences in gender perceptions of summer comfort and adaptation in the case-study buildings. The current study contributes to ongoing research on assessments of the performance and thermal comfort in Colonial Revival-style homes and residential buildings in general. The principal goal of the research is to carry out a comparative analysis of gender variations on perceptions of summer comfort and adaptation in the residences. The study addresses this question—Do gender variations significantly influence residents’ perceptions of summer comfort and adaptation in the residences? The research objectives include the following:

(a)

To examine the impacts of gender on the perceptions of summer comfort, indoor environmental conditions, and adaptation in the residences;

(b)

To compare the research outcomes with the results from existing research in different regions;

(c)

To identify possible recommendations to address any gaps between gender differences in perceptions of summer comfort and adaptation that may be observed from the study.

2. Materials and Methods

The current study utilizes field studies of thermal comfort (FSTC) [41], including environmental monitoring of variables and thermal comfort surveys to collect data for analysis. The thermal comfort surveys are paper based; the residents were asked to rate their current indoor environmental conditions at the time of completion of the surveys. The on-site monitoring involves physical measurements of variables within the thermal environment. The design of the investigation that outlines the data-collection protocol, analysis, interpretation, and recommendations is shown in Figure 1 below. The figure shows the first step in the framework for the research is data protocol and collection. The next step is data analysis, followed by testing, piloting, and interpreting the results.

2.1. Collection of Data

The study collected data from different residential units in the study location. The study area is one of the most eastern states in the northeast region of the United States. The study identified Colonial Revival-style residential units and used various criteria to select the buildings to evaluate. The distinctive characteristics of Colonial-Revival-style homes, the average age of the houses, and other features have been captured in the existing research [5,6]. Some of the criteria used for the selection of the case-study buildings include similar architectural style (i.e., Colonial Revival architecture), multi-family units, located within the study area, permission to access and evaluate the units, and residents willing to take part in the comfort surveys. In total, the investigation evaluated eight residential units of Colonial Revival-style architecture.

The units are naturally ventilated in summer, the period of the survey. The windows are operable. The units have an average floor area of approximately 150 m² per unit. The median of the U-values range for the building components is also computed. The values for the components are as follows: external walls (0.40 W/m²K), windows (0.30 W/m²K), doors (0.35 W/m²K), roofs (0.28 W/m²K), and floors (1.98 W/m²K). The buildings examined in this study have had their windows replaced in recent years to meet the code requirements. In terms of the HVAC systems, the buildings are equipped with heating and air conditioning split systems. The systems provide residents the opportunity to regulate the thermal environment, especially in cold seasons.

The research team visited the selected residential units to identify and determine the spaces to monitor. In agreement with the residents, selected spaces in each residential unit were identified for the study. The team also examined the residents willing to participate in the study. While the residents were asked to complete the questionnaire, the study also made some observations about the residents’ actions and other adaptive measures taken whenever possible to record such observations. Observations regarding occupants’ behaviors in summer, including evaluation of energy consumption and the use of a control, have been captured in another study [5].

Calibrated HOBO sensors (MX1100 and MX1102 series, Onset Corporations, Bourne, MA, USA) that measured environmental variables (temperature, humidity, etc.) were installed to measure and log the environmental variables during the surveys. The data loggers were placed at 1.1 m above the floor level. Some of the environmental variables captured in this study include temperature, relative humidity, and dew point. The sensors also measured some parameters, such as air speeds, etc. In this study, the assessment of air quality is based on occupants’ perceptions of indoor air quality within the buildings. The research followed the applicable category and protocols of ASHRAE [42]. The study also collected data on metabolic activities and clothing insulation of the survey participants. Additionally, the investigation conducted some computations to check the values of these variables using the applicable charts and approach [42,43].

2.2. Sample of the Subjects, Questionnaire, and Thermal Comfort Surveys

The survey participants’ ages varied from late teens to mid-sixties. All the participants (N = 110) primarily reside in the buildings. More than two-thirds of the respondents were female while the remaining one-third were male. The samples were checked by grouping the collected data based on gender to calculate some statistical variables, such as variance, standard deviation, standard error mean, skewness, and others. The study used statistical software (Statistical Package for the Social Sciences—SPSS version 29) to check and test the samples. The questionnaires were divided into three sections (i.e., general information, questions on perceptions of the thermal environment, and questions relating to overall well-being and additional comments). The structures of the questionnaire and thermal comfort surveys, including the rating scales considered in this study, were similar to the ones discussed in the existing research [5,6,44]. Thus, the current study will not discuss the questionnaire structure and thermal comfort surveys.

2.3. Physical Measurements of Indoor Environmental Variables and External Weather Data

The physical measurements captured different environmental variables within the selected homes in the summer months (i.e., July to September). The measurements were conducted in the residential buildings where the occupants participated in the comfort surveys. The external weather data were retrieved from the meteorological station located near the study area. Similar environmental variables measured within the indoor thermal environment were collected at the weather station for comparison between indoor and outdoor environmental conditions.

2.4. Analysis of Data

Table 2. Summary of the descriptive statistics of the external and internal environmental conditions observed during the study.

Environmental Parameters	Maximum	Mean	Minimum	* SD	** V	*** SS
Outdoor daily average temperature (Tout—°C)	33.0	21.7	10.3	11.350	128.823	257.647
Outdoor daily average dew-point temperature (DPTout—°C)	17.0	15.7	8.0	4.864	23.663	47.327
Outdoor daily average relative humidity (RHout—%)	68.4	68.7	68.9	0.252	0.063	0.1267
Outdoor daily average air speed (Va—m/s)	3.0	2.3	1.7	0.650	0.423	0.847
Outdoor daily average solar energy (kWh/m2)	6.7	4.3	2.0	2.350	5.523	11.047
Outdoor daily average water temperature (Toutwater—°C)	22.0	20.7	20.0	1.015	1.030	2.060
Indoor average air temperature (Tair—°C)	32.6	25.3	20.6	6.047	36.563	73.127
Indoor average globe temperature (Tg—°C)	33.2	19.9	15.4	9.255	85.663	171.326
Indoor average apparent temperature (ATind—°C)	39.1	27.8	21.2	9.052	81.943	163.887
Indoor average dew-point temperature (DPTind—°C)	17.5	17.1	17.0	0.265	0.070	0.140
Indoor average relative humidity (RHind—%)	65.2	61.3	59.0	3.134	9.823	19.647
Indoor average absolute humidity (AHind—g/m3)	744.4	732.7	715.2	14.696	215.963	431.927
Indoor average air speed (m/s)	0.5	0.2	0.1	0.208	0.043	0.087

* SD means standard deviation. ** V means variance. *** SS means sum of squares.

provides a summary of the indoor and outdoor conditions. The study explored the Griffiths approach [45] to analyze the recorded data from the homes to calculate the comfort temperature using the equation below (Equation (1)). In Equation (1), T_c is the comfort temperature, T_g is the indoor globe temperature, TSV is the thermal sensation vote, and G is the Griffiths coefficient. The existing research [10,46] considers 0.5 K⁻¹ as the Griffiths coefficient. In line with the existing research, the current study selects a similar coefficient. Also, it was reported that an insignificant variation in the selection of the coefficient of about 0.2 has an insignificant change to the comfort-temperature estimates.

T_c = T_g + (0 − TSV)/G

(1)

The study also computed the apparent temperature for the thermal environment. Apparent temperature considers four environmental variables (e.g., air temperature, air speed, radiation from the sun, and relative humidity) to define human thermal comfort. Apparent temperature is a thermal index and universal scale developed by Robert Steadman [25,47], and it has been adopted in existing research [25] and establishments, including the Australian Bureau of Meteorology. The study applied Equation (2) to compute the apparent temperature. In Equation (2), T_a stands for air bulb temperature (°C), e stands for saturation vapor pressure (Pa or kPa), ws stands for air speed (m/s), and Q stands for net radiation absorption per unit body surface area (W/m²). Where e is not directly measured, Equation (3) can be applied to calculate the value of ρ. In Equation (3), rh stands for relative humidity. In climates outside Australia, such as the United States, Canada, and the UK, Equation (4) can be considered to compute the apparent temperature. In Equations (3) and (4), ρ stands for water-vapor pressure (hPa).

AT = T_a + 0.348 × e − 0.70 × ws + 0.70 × (Q/ws + 10) − 4.25

(2)

ρ = rh/100 × 6.105 × e^(17.27×T_a/(237.7 + T_a)

(3)

AT = T_a + 0.33 × ρ − 0.70 × ws − 4.00

(4)

The existing research noted differences in the coefficient of some populations when evaluating the data [48]. The differences suggest possibilities of either overestimation or underestimation of the coefficient for a group estimate. Therefore, a value near the upper part of the limit of the estimates will be most suitable to avoid overestimation and underestimation. The study also computed mean neutral and preferred temperatures based on gender differences. Since the study conducted actual measurements of environmental variables and thermal comfort surveys, there was no need to compute adjusted predicted mean votes, adjusted radiant and air temperatures, or adopt the use of ASHRAE’s Elevated Air Speed Comfort Zone Method as outlined in previous work [10,42].

3. Results

3.1. Differences in Gender Responses to the Indoor Thermal Environment

The study examined gender differences within the thermal environment. The variables presented in

Table 3. Summary of the gender responses to the indoor thermal environment.

Variables	Female (N = 67%)			Male (N = 33%)
	Mean	* SD	Variance	Mean	* SD	Variance
Time (1 = morning, 2 = afternoon, 3 = evening)	2.23	0.786	0.618	1.69	0.822	0.675
Room currently occupied (1 = living room, 2 = bedroom, 3 = kitchen, 4 = dinning)	1.23	0.424	0.179	1.56	0.504	0.254
Space where you spent most of your time in the last hour (the ratings are similar to the room currently occupied)	1.46	0.686	0.471	1.64	0.593	0.352
Have you just come into the building in the last? (1 = 15 min, 2 = 30 min, 3 = 45 min, 4 = 60 min, 5 ≥ 60 min)	3.53	1.738	3.020	3.97	1.464	2.142
Activity within the last hour (where 1 = watching TV, 2 = cooking, 3 = standing, 4 = walking, 5 = washing, 6 = reading and 7 = others)	4.82	2.645	6.996	5.64	2.180	4.752
Do you feel comfortable now?—thermal comfort (where 1 = very uncomfortable, and 7 = very comfortable)	5.01	1.266	1.603	5.14	1.199	1.437
Would you like to be? (1 = cooler, 2 = no change, 3 = warmer)	2.11	0.563	0.317	2.11	0.523	0.273
Thermal acceptability at this moment (1 = acceptable, 2 = not acceptable)	1.05	0.228	0.052	1.06	0.232	0.054
Air temperature at this moment—thermal sensation (where 1 = cold, and 7 = hot)	3.20	1.147	1.315	3.36	1.313	1.723
Air movement at this moment (where 1 = very little, and 7 = very much)	3.53	1.445	2.088	3.81	1.390	1.933
Air humidity at this moment (where 1 = very dry, and 7 = very humid)	3.85	0.715	0.512	3.67	0.956	0.914
Daylighting level at this moment (where 1 = very dim, and 7 = very bright)	5.68	2.008	4.030	6.03	1.844	3.399
Air quality at this moment (where 1 = very stuffy, and 7 = very good)	4.61	1.322	1.748	5.11	1.450	2.102
Thermal preference at this moment (where 1 = much cold, and 5 = much warmer)	3.08	0.614	0.377	3.08	0.554	0.307
Occupant’s activity level during the last 15 min (the rating levels are similar to activity within the last hour)	5.04	2.435	5.930	5.67	2.125	4.514

* SD means standard deviation.

addressed actions taken as of the time of completing the surveys. Some of the questions addressed the residents’ actions within the last hour to improve their thermal comfort and adaptation in the buildings. The findings revealed differences in gender perceptions of the indoor thermal environment across various questions asked during the field investigation. On the one hand, the study showed female residents are less sensitive to daylighting within the indoor spaces. On the other hand, female respondents are more sensitive to the low or poor air quality within the thermal environment. Both female and male residents perceive similar thermal preferences and thermal acceptability within the buildings. Additionally, there is no significant difference in the mean values of thermal comfort and thermal sensation in the indoor spaces. Table 3 (below) shows the results of the standard deviation, variance, and mean values of the variables.

The research also examined the neutral and preferred temperatures using regression analyses. The neutral temperatures were calculated by plotting the average indoor temperatures in the case-study buildings versus the thermal sensation votes. For female respondents, the neutral temperatures varied from 24.1 °C to 26.1 °C. The neutral temperatures for male residents ranged from 24.4 °C to 26.7 °C. The results showed male residents feel “neutral” or “no change” to the indoor thermal environment at higher temperatures than female occupants. Likewise, the preferred temperatures were computed by plotting the average indoor temperatures versus thermal preference votes. The outcomes showed the preferred temperatures for female occupants varied from 23.9 °C to 25.4 °C. For the male occupants, the preferred temperatures ranged from 24.3 °C to 26.5 °C. The study also showed male residents prefer “no change” to the indoor thermal environment at higher temperatures than female residents.

3.2. Differences in Gender Clothing Insulation and Level of Activity

The study assessed the clothing insulation for the female and male respondents examined during the surveys. The research found out that female occupants have higher clothing insulation (clo) values than male occupants by 0.3 to 0.5. The investigation also noted a higher level of activity among male residents than female occupants. For instance, the results for the activity level within the last 15 min showed higher values for male residents (mean = 5.67, SD = 2.125) than female occupants (mean = 5.04, SD = 2.345), as shown in Table 2.

3.3. Differences in Gender Responses between Variables Using Statistical Tests

Correlations and other related statistical tests were considered to establish relationships between the variables and show differences in gender responses within the thermal environment, as shown in Table 3. The results demonstrated some similarities and variations in gender responses and their perceptions of the indoor environment. Correlations and significance exist between thermal sensation and would you like to be cooler, no change, or warmer for females (p < 0.001) and males (p < 0.001). Likewise, correlations and significance are found between thermal sensation and thermal preference for females (p < 0.001) and males (p < 0.001). Correlations are noted between thermal sensation and air quality, but significance is only reported between the variables for male residents (p < 0.001). In some cases, correlations and significance are not observed between the variables. For instance, correlations and significance are not reported between thermal sensation and activity level, as well as between thermal preference and activity level for female and male occupants. The majority of the tests between the variables for male residents revealed significant correlations or associations. The results of the statistical tests between the variables are presented in

Table 4. Statistical tests between variables highlight differences in gender responses to the thermal environment.

Variables	Female (N = 67%)				Male (N = 33%)
	Pearson Correlation	Sig. (2-Tailed)	SS and C-p	C	Pearson Correlation	Sig. (2-Tailed)	SS and C-p	C
Thermal sensation vs. thermal comfort	−0.210	0.073	−22.203	−0.304	−0.688 **	<0.001	−36.806	−1.052
Thermal sensation vs. acceptability	−0.095	0.421	−1.811	−0.025	0.682 **	<0.001	7.278	0.208
Thermal sensation vs. air movement	−0.165	0.161	−19.905	−0.273	−0.634 **	<0.001	−40.472	−1.156
Thermal sensation vs. air humidity	−0.180	0.125	−10.770	−0.148	−0.789 **	<0.001	−34.667	−0.990
Thermal sensation vs. daylighting level	−0.263 *	0.024	−44.135	−0.605	−0.311	0.065	−26.361	−0.753
Thermal sensation vs. air quality	−0.299 **	0.010	−33.122	−0.454	−0.712 **	<0.001	−47.444	−1.356
Thermal sensation vs. Would you like to be cooler, no change, or warmer?	−0.692 **	<0.001	−32.622	−0.447	−0.602 **	<0.001	−14.444	−0.413
Thermal sensation vs. thermal preference	−0.549 **	<0.001	−28.216	−0.387	−0.632 **	<0.001	−16.083	−0.460
Thermal sensation vs. activity level	−0.072	0.544	−14.608	−0.200	0.034	0.843	3.333	0.095
Thermal comfort vs. acceptability	−0.335 **	0.003	−7.054	−0.097	−0.644 **	<0.001	−6.278	−0.179
Thermal comfort vs. thermal preference	0.140	0.236	7.919	0.108	0.326	0.052	7.583	0.217
Thermal comfort vs. air movement	0.146	0.215	19.473	0.267	0.445 **	0.007	25.972	0.742
Thermal comfort vs. air humidity	0.290 *	0.012	19.149	0.262	0.665 **	<0.001	26.667	0.762
Thermal comfort vs. daylighting level	0.072	0.543	13.324	0.183	0.244	0.152	18.861	0.539
Thermal comfort vs. air quality	0.331 **	0.004	40.392	0.553	0.616 **	<0.001	37.444	1.070
Thermal comfort vs. would you like to be cooler, no change, or warmer?	0.036	0.758	1.892	0.026	0.294	0.082	6.444	0.184
Thermal preference vs. acceptability	0.164	0.162	1.676	0.023	−0.481 **	0.003	−2.167	−0.062
Thermal preference vs. air movement	0.090	0.445	5.838	0.080	0.652 **	<0.001	17.583	0.502
Thermal preference vs. air humidity	0.090	0.445	2.892	0.040	0.647 **	<0.001	12.000	0.343
Thermal preference vs. daylighting level	0.211	0.072	18.946	0.260	0.361 *	0.030	12.917	0.369
Thermal preference vs. air quality	0.107	0.363	6.351	0.087	0.593 **	<0.001	16.667	0.476
Thermal preference vs. activity level	0.025	0.831	2.757	0.038	0.121	0.481	5.000	0.143

SS and C-p mean sum of squares and cross-products. C means covariance. ** Correlation is significant at the 0.01 level (2 tailed). * Correlation is significant at the 0.05 level (2 tailed).

below.

The research also considered the effect sizes (i.e., the strength of association) of the variables to further understand gender variations and their perceptions of the indoor thermal environment. For instance, on the one hand, Eta squared shows the estimates of the degree or strength of the relationship for the sample. On the other hand, Omega-squared fixed effect and other effect sizes reveal the estimates of the degree or strength of the relationship in the population. These effect sizes show the similarities and differences between these measures of relationship. Because existing research has suggested that Eta-squared can provide bias estimates [49], Omega-squared fixed effect and Omega-squared random effect were considered to provide less biased estimates. The results showed differences in the effect sizes between gender perceptions of the thermal environment. For instance, noticeable differences were observed in the effect sizes of thermal preference for male residents across the tests, while the differences were very small or negligible for the same variable among female residents. The findings of the effect sizes across the variables are summarized in

Table 5. Gender differences in the effect sizes of the variables within the indoor thermal environment.

Variables		Female (N = 67%)			Male (N = 33%)
		Point Estimate	95% Confidence Interval		Point Estimate	95% Confidence Interval
			Lower	Upper		Lower	Upper
Thermal sensation	Eta-squared	0.119	0.000	0.215	0.570	0.201	0.660
	Epsilon-squared	0.054	−0.074	0.158	0.481	0.036	0.590
	Omega-squared Fixed-effect	0.053	−0.072	0.156	0.474	0.035	0.583
	Omega-squared Random-effect	0.011	−0.014	0.036	0.131	0.006	0.189
Would you like to be cooler, no change, or warmer?	Eta-squared	0.061	0.000	0.131	0.834	0.646	0.870
	Epsilon-squared	−0.008	−0.074	0.067	0.800	0.573	0.844
	Omega-squared Fixed-effect	−0.008	−0.072	0.066	0.795	0.566	0.840
	Omega-squared Random-effect	−0.001	−0.014	0.014	0.393	0.178	0.466
Thermal comfort	Eta-squared	0.121	0.000	0.218	0.500	0.115	0.602
	Epsilon-squared	0.056	−0.074	0.160	0.396	−0.068	0.519
	Omega-squared Fixed-effect	0.055	−0.072	0.158	0.389	−0.066	0.512
	Omega-squared Random-effect	0.012	−0.014	0.036	0.096	−0.010	0.149
Air movement	Eta-squared	0.318	0.104	0.431	0.461	0.075	0.569
	Epsilon-squared	0.268	0.038	0.390	0.350	−0.117	0.479
	Omega-squared Fixed-effect	0.265	0.038	0.386	0.343	−0.113	0.472
	Omega-squared Random-effect	0.067	0.008	0.112	0.080	−0.017	0.130
Air humidity	Eta-squared	0.043	0.000	0.096	0.598	0.240	0.684
	Epsilon-squared	−0.028	−0.074	0.029	0.515	0.083	0.618
	Omega-squared Fixed-effect	−0.027	−0.072	0.029	0.508	0.081	0.611
	Omega-squared Random-effect	−0.005	−0.014	0.006	0.147	0.014	0.208
Daylighting level	Eta-squared	0.119	0.000	0.216	0.308	0.000	0.427
	Epsilon-squared	0.054	−0.074	0.158	0.165	−0.207	0.308
	Omega-squared Fixed-effect	0.054	−0.072	0.156	0.161	−0.200	0.302
	Omega-squared Random-effect	0.011	−0.014	0.036	0.031	−0.029	0.067
Air quality	Eta-squared	0.206	0.020	0.318	0.521	0.140	0.619
	Epsilon-squared	0.148	−0.052	0.268	0.422	−0.038	0.541
	Omega-squared Fixed-effect	0.146	−0.051	0.266	0.415	−0.037	0.534
	Omega-squared Random-effect	0.033	−0.010	0.067	0.106	−0.006	0.160
Thermal preference	Eta-squared	0.075	0.000	0.153	0.744	0.475	0.800
	Epsilon-squared	0.007	−0.074	0.091	0.691	0.366	0.758
	Omega-squared Fixed-effect	0.007	−0.072	0.090	0.685	0.359	0.753
	Omega-squared Random-effect	0.001	−0.014	0.019	0.266	0.085	0.337
Activity level	Eta-squared	0.097	0.000	0.186	0.206	0.000	0.316
	Epsilon-squared	0.031	−0.074	0.126	0.042	−0.207	0.174
	Omega-squared Fixed-effect	0.031	−0.072	0.125	0.041	−0.200	0.170
	Omega-squared Random-effect	0.006	−0.014	0.028	0.007	−0.209	0.033
Thermal acceptability	Eta-squared	0.079	0.000	0.160	0.647	0.312	0.723
	Epsilon-squared	0.012	−0.074	0.098	0.574	0.170	0.666
	Omega-squared Fixed-effect	0.011	−0.072	0.097	0.567	0.166	0.659
	Omega-squared Random-effect	0.002	−0.014	0.021	0.179	0.032	0.244

below.

The sum of squares, mean square, F-test, and significance were also checked between groups and within groups of variables to further understand the variations in gender perceptions of the thermal environment (

Table 6. Gender differences in the sum of squares, mean square, and F values within the indoor thermal environment.

Variables			Female (N = 67%)				Male (N = 33%)
			Sum of Square	Mean Square	F	Sig	Sum of Squares	Mean Square	F	Sig
Thermal sensation	Between Groups	Combined	11.410	2.282	1.835	0.118	34.368	5.728	6.404	<0.001 **
		Linear Term (Weighted)	1.258	1.258	1.102	0.318	14.357	14.357	16.052	<0.001 **
		Linear Term (Deviation)	10.152	2.538	2.041	0.098	20.011	4.002	4.475	0.004 *
	Within Groups		84.549	1.243	NVC	NVC	25.938	0.894	NVC	NVC
Would you like to be cooler, no change, or warmer?	Between Groups	Combined	1.420	0.284	0.890	0.493	7.972	1.329	24.336	<0.001 **
		Linear Term (Weighted)	0.198	0.198	0.621	0.433	0.037	0.037	0.685	0.415
		Linear Term (Deviation)	1.222	0.306	0.957	0.437	7.935	1.587	29.067	<0.001 **
	Within Groups		21.715	0.319	NVC	NVC	1.583	0.055	NVC	NVC
Thermal comfort	Between Groups	Combined	14.119	2.824	1.867	0.112	25.139	4.190	4.828	0.002 *
		Linear Term (Weighted)	4.554	4.554	3.010	0.087	11.026	11.026	12.706	<0.001 **
		Linear Term (Deviation)	9.565	2.391	1.581	0.189	14.113	2.823	3.252	0.019
	Within Groups		102.868	1.513	NVC	NVC	25.167	0.868	NVC *	NVC
Air movement	Between Groups	Combined	48.502	9.700	6.346	<0.001 **	31.201	5.200	4.139	0.004 *
		Linear Term (Weighted)	23.962	23.962	15.676	<0.001 **	11.175	11.175	8.894	0.006
		Linear Term (Deviation)	24.541	6.135	4.014	0.006	20.027	4.005	3.188	0.021
	Within Groups		103.944	1.529	NVC	NVC	36.438	1.256	NVC	NVC
Air humidity	Between Groups	Combined	1.598	0.320	0.608	0.694	19.146	3.191	7.199	<0.001 **
		Linear Term (Weighted)	0.847	0.847	1.611	0.209	9.207	9.207	20.771	<0.001 **
		Linear Term (Deviation)	0.751	0.188	0.357	0.838	9.939	1.988	4.485	0.004 *
	Within Groups		35.766	0.526	NVC	NVC	12.854	0.443	NVC	NVC
Daylighting level	Between Groups	Combined	35.012	7.002	1.837	0.117	36.639	6.106	2.151	0.078
		Linear Term (Weighted)	1.159	1.159	0.304	0.583	0.971	0.971	0.342	0.563
		Linear Term (Deviation)	33.853	8.463	2.220	0.076	35.668	7.134	2.513	0.052
	Within Groups		259.204	3.812	NVC	NVC	82.333	2.839	NVC	NVC
Air quality	Between Groups	Combined	26.325	5.265	3.534	0.007	38.306	6.384	5.252	<0.001 **
		Linear Term (Weighted)	21.902	21.902	14.701	<0.001 **	17.159	17.159	14.116	<0.001 **
		Linear Term (Deviation)	4.423	1.106	0.742	0.567	21.147	4.229	3.479	0.014
	Within Groups		101.310	1.490	NVC	NVC	35.250	1.216	NVC	NVC
Thermal preference	Between Groups	Combined	2.065	0.413	1.104	0.367	8.000	1.333	14.061	<0.001 **
		Linear Term (Weighted)	0.186	0.186	0.497	0.483	0.230	0.230	2.426	0.130
		Linear Term (Deviation)	1.879	0.470	1.255	0.296	7.770	1.554	16.387	<0.001 **
	Within Groups		25.448	0.374	NVC	NVC	2.750	0.095	NVC	NVC
Activity level	Between Groups	Combined	42.167	8.433	1.468	0.212	49.500	8.250	2.205	0.071
		Linear Term (Weighted)	15.838	15.838	2.757	0.101	21.123	21.123	5.646	0.024
		Linear Term (Deviation)	26.329	6.582	1.146	0.343	28.377	5.675	1.517	0.215
	Within Groups		390.711	5.746	NVC	NVC	108.500	3.741	NVC	NVC
Thermal acceptability	Between Groups	Combined	0.300	0.060	1.172	0.332	1.222	0.204	8.861	<0.001 **
		Linear Term (Weighted)	0.254	0.254	4.955	0.029	0.193	0.193	8.375	0.007
		Linear Term (Deviation)	0.046	0.012	0.226	0.923	1.030	0.206	8.958	<0.001 **
	Within Groups		3.484	0.051	NVC	NVC	0.667	0.023	NVC	NVC

** The difference is significant at the 0.01 level (2-tailed). * The difference is significant at the 0.05 level (2 tailed). NVC means “No Value Calculated”.

). The results showed that the level of interaction between some variables is significant. For instance, the level of interaction for thermal sensation votes between groups for combined responses is significant for male residents (F = 6.404, p < 0.001), while the level of interaction between groups for female residents is not significant. The level of association for air movement between groups is significant for female (F = 6.346, p < 0.001) and male (F = 4.139, p = 0.004) residents.

4. Discussion

4.1. Thermal Sensitivity of Gender Responses

The research showed that there are similarities and differences between gender perceptions of thermal environments. The mean values of gender responses varied in some cases, while the mean values of some variables were within the same range. Both female (mean = 5.01, SD = 1.266) and male (mean = 5.16, SD = 1.199) residents are thermally comfortable within the buildings, with a slightly higher mean value for male responses than the mean value for female responses. Female and male residents would like “no change” to the thermal environment of the buildings. In the responses, female and male occupants have the same mean value of 2.11 but different SD values for female (SD = 0.563), and male (SD = 0.523) occupants. Female (mean = 1.05, SD = 0.228) and male (mean = 1.06, SD = 0.232) residents feel that the thermal environment is acceptable to them. The mean thermal sensation votes are slightly higher for males (mean = 3.36, SD = 1.313) than for females (mean = 3.20, SD = 1.147). Male residents feel slightly warmer than female occupants. On the one hand, male respondents (mean = 3.81, SD = 1.390) are more sensitive to air movement than female residents (mean = 3.53, SD = 1.445). On the other hand, female respondents (mean = 3.85, SD = 0.715) are more sensitive to air humidity than male respondents (mean = 3.67, SD = 0.956). Male respondents (mean = 6.03, SD = 1.844) perceive brighter daylighting than female respondents (mean = 5.68, SD = 2.008). Female residents (mean = 4.61, SD = 1.322) perceive lesser air quality than male respondents (mean = 5.11, SD = 1.450).

4.2. Heat Indices and Neutral and Preferred Temperatures

The overall heat index of 25.5 °C was computed across the buildings. The research computed heat indices for different categories of the survey respondents; the mean heat indices of 25.7 °C and 26.0 °C were computed for female and male respondents, respectively. The mean neutral temperatures for female respondents were lower than the average neutral temperatures for male residents across the case-study buildings. The mean neutral temperatures of 25.5 °C and 25.8 °C were calculated for female and male residents correspondingly. The research showed that female residents feel less warm in the thermal environment than male residents. Additionally, the mean preferred temperatures for male residents were noticeably higher than the mean preferred temperatures for female occupants.

The study considered regression analyses to determine the mean neutral and preferred temperatures (Figure 2 and Figure 3). The R² values were low, but the analyses are crucial to compute the variables The average preferred temperature of 24.9 °C was calculated for females, while the mean preferred temperature of 25.6 °C was computed for males. The research revealed male residents prefer “no change” to the thermal environment of the case-study buildings at significantly higher temperatures than female residents. The study also showed a difference of 0.1 °C between the mean neutral and preferred temperatures for males. A difference of 0.6 °C is noted between the average neutral and preferred temperatures for females. The study also considered polynomial analyses to further understand relationships between thermal sensation votes and average indoor temperatures. The R² values were also low and similar to the values obtained when regression analyses were considered (Figure 4). The investigation also found similar outcomes between thermal preference votes and average indoor temperatures.

Table 7. Statistical tests between environmental variables and gender responses to determine neutral and preferred temperatures.

Case-Study Buildings	Female (N = 67%)		Male (N = 33%)
	Neutral Temp. (°C)	Preferred Temp. (°C)	Neutral Temp. (°C)	Preferred Temp. (°C)
DW-MLTBB	25.9	25.1	26.0	25.9
DW-MLTLL	25.8	25.4	25.9	25.8
DW-MLTFR	26.1	25.3	26.7	26.5
DW-MLTBS	24.1	23.9	24.4	24.3
Average	25.5	24.9	25.8	25.6

outlines the mean values for the neutral and preferred temperatures for female and male respondents in the buildings.

Figure 2 shows no relationship between the mean sensation (TSV) and average indoor temperatures for males. The regression reveals that a change in the indoor temperatures does not significantly lead to changes in thermal sensation votes, especially from the cooler to the warmer part of the sensation scale among different groups of residents. The result reveals a weak R² value between the mean sensation and indoor temperatures for females and males. Figure 3 shows a weak R² value between the mean thermal preference votes (TSV) and average indoor temperatures for females, while a relationship exists between the variables for males. The finding reveals a rise in indoor temperatures leads to changes in the thermal preference votes among males.

From the analysis outlined in Table 2, the study revealed the mean indoor temperature (25.3 °C) in all the spaces is within the comfort zone (22.0 °C to 27.0 °C) when comparing it to the psychrometric chart. Likewise, the mean relative humidity (61.3%) is slightly higher than the relative humidity range (40% to 60%). Linking the mean environmental variables (i.e., mean temperature and mean relative humidity) to the mean neutral and preferred temperatures for females and males, as well as the mean heat indices, the results suggest that when both males and females are subject to the same thermal environment, male residents are prone to discomfort and heat stress more than female residents in the buildings.

4.3. Relationships between the Variables on Gender Responses

The research conducted tests to understand the relationships between the variables, as highlighted in Table 3. Male residents who feel less warm are thermally comfortable in the buildings (r = −0.688, p < 0.001), while females are thermally uncomfortable (r = −0.210, p = 0.073). Also, male respondents who feel warm perceive less air movement into the thermal environment (r = −0.634, p < 0.001). A contrary result was obtained for females (r = −0.165, p = 0.161). Male residents who feel warm perceive the thermal environment to be “very dry” or “dry” (r = −0.789, p < 0.001), while a different outcome was observed for females (r = −0.180, p = 0.125). Correlations are reported between thermal sensation and air quality. Males who feel warm perceive less air quality (r = −0.712, p < 0.001) more than females (r = −0.299, p < 0.05). Females (r = −0.692, p < 0.001) and males (r = −0.602, p < 0.001) who feel less warm would like “no change” to the thermal environment. Female (r = −0.549, p < 0.001) and male (r = −0.632, p < 0.001) respondents who feel warm prefer the thermal environment to be “cooler” or “much cooler”. Females (r = −0.335, p < 0.05) and males (r = −0.644, p < 0.001) who are thermally comfortable perceive the thermal environment to be acceptable to them. Both female (r = 0.331, p < 0.05) and male (r = 0.616, p < 0.001) residents who are thermally comfortable perceive good air quality within the thermal environment. Females (r = 0290, p < 0.05) and males (r = 0.665, p < 0.001) who are thermally comfortable perceive sufficient air humidity, while no strong relationships were found between thermal comfort and daylighting for females and males.

The study considered significance and F-test (i.e., test statistic) to test if a group of samples or variables are significantly different. For each group of variables, three tests were conducted between groups (i.e., combined, linear term—weighted, and linear term—deviation). Significance is reported between groups of male thermal sensation votes for combined (F = 6.404, p < 0.001), linear term—weighted (F = 16.052, p < 0.001), and linear term—deviation (F = 4.475, p < 0.05), while no significance is noted for females. On would you like to be either “cooler”, “no change”, or “warmer”, significance is not reported between groups for females. However, significance is noted between groups of males for combined (F = 24.336, p < 0.001) and linear term—deviation (F = 29.067, p < 0.001), but there was no significance for linear term—weighted. Likewise, significance is observed between groups of male thermal comfort votes for combined (F = 4.828, p < 0.05) and linear term—weighted (F = 12.706, p < 0.001). But, there was no significance for linear term—deviation, while significance is not noted between groups for females. On air quality, significance is noted between the groups of linear term—weighted for males (F = 14.1116, p < 0.001) and females (F = 14.701, p < 0.001)). Significance is not reported between groups of combined and linear term—deviation for females and males, while significance is noted between groups of combined (F = 5.252, p < 0.001) for male respondents.

4.4. Comparison of the Research Findings with Existing Research

Comparing the research findings with the existing research, the current study identifies some similarities and differences between the outcomes. The existing research assessed gender differences within the thermal environment in extremely low and high temperatures [12,21,50] and noted that female respondents perceived to be more uncomfortable more frequently than male residents. In this study, even though females feel comfortable, males are more comfortable than females. Also in this study, males perceive the thermal environment to be warmer than females. The result aligns with the outcome of a world database that also revealed that male respondents feel noticeably warmer than female respondents within the thermal environment under similar internal and external thermal conditions [51]. The existing research also outlined a combination of factors that influences thermal comfort and differences in gender perceptions of the thermal environment [21,31]. For instance, past investigations mentioned that physiological variations [10,21], hormonal differences [31], and differences in clothing insulation observed in female respondents when compared to male respondents [21], could possibly contribute to some noticeable variations in gender perceptions of the thermal environment. Also, in one of the study locations of the existing research [10], the gender variation in the clothing layer is more noticeable at 0.2 clo, and it indicates approximately a 4 K temperature swing. This observation also aligns with the outcome of this study, as the investigation identifies differences of 0.3 to 0.5 in the clo values between females and males.

The outcomes on gender variations in the percentage of responses on different environmental variables revealed that 42% of females and 61% of males voted for air quality satisfaction. Also, 95% of females and 94% of males voted for thermal acceptability satisfaction. The study showed females have a higher tolerance of satisfaction with the thermal environment. On thermal comfort satisfaction, 68% of females voted that they were satisfied. The result for females on thermal comfort satisfaction votes aligns with the votes reported for females in the existing research [10]. In one of the study locations captured in the existing investigation [10], 34% of females voted that they were uncomfortable and reported colder sensations, even when they put on a higher level of clothing layers. In this study, 32% of females voted uncomfortable and reported either colder or warmer sensations.

The votes on thermal acceptability were similar for females and males. The study revealed that there is no relationship between males’ responses regarding satisfaction rate of thermal comfort, thermal acceptability, air quality, and thermal preference. A weak relationship exists between females’ votes and the satisfaction rate of the environmental variables. There are similarities between satisfaction ratings of other variables among male and female respondents in the buildings.

Additionally, in one of the study locations of an existing investigation [10], females were found to be more susceptible to changes in temperatures than male respondents. A similar outcome was noted in another investigation [50]. The outcome of this study strongly aligns with the findings of existing research [10,50]. In this study, the mean neutral temperature for females was 0.3 °C lower than the average neutral temperature reported for male respondents. Equally, the mean preferred temperature for female respondents was 0.7 °C less than the mean preferred temperature for male occupants. While the research outcomes suggest females have a higher level of adaptation to the thermal environment than males. The study also reveals that females are more prone to thermal discomfort within the thermal environment than male occupants. This research outcome also aligns with existing research that explored indoor environmental quality (IEQ) factors [17], post-occupancy evaluation databases [18], and post-occupancy studies [52] to evaluate thermal satisfaction in different thermal spaces. The investigations noted that females are more likely to perceive thermal dissatisfaction at higher rates than male respondents [17,18,52]. The research outcomes revealed similarities between the current study and the existing research, while some notable differences and new findings are also reported.

4.5. Limitations of the Study and Future Research

The surveys were conducted in the case-study buildings in the summertime. The current study is only limited to Colonial Revival-style residences in the study location. Further research should consider and examine perceptions of comfort and adaptation in Colonial Revival-style residences in other locations. The study did not capture winter surveys to understand variations in gender perceptions of the thermal environment in different seasons. Additionally, female respondents were about two-thirds of the total samples captured during the surveys. It is possible that similar or different outcomes may be obtained if female respondents and male respondents are of equal percentage. The equal samples between females and males may be difficult to obtain in many field surveys because the current study has no control over how frequently the respondents decided to complete subject votes. The unequal samples between females and males were also noted in the existing research [10]. Moreover, due to the samples of the respondents, the current study did not capture variations in neutral and preferred temperatures, adaptation, and thermal responses among different age groups of the same gender, for instance, differences in the temperatures and thermal responses between younger females and older females or younger males and older males. Future research intends to address these limits. Despite these limitations, the current study provides further understanding of differences in gender perceptions of the thermal environment. It is the first reported research that evaluates variations in gender perceptions of thermal comfort and adaptation in the buildings.

5. Conclusions

The current study examines variations in gender perceptions of summer comfort and adaptation in Colonial Revival-style homes. The study explored field studies of thermal comfort (FSTC) that comprise environmental monitoring and comfort surveys to gather data for analysis. The research contributes to ongoing investigations of the evaluation of the performance and thermal comfort in Colonial Revival-style homes and other residential buildings. In this study, 68% of females and 67% of males were comfortable. Females (mean = 5.01, SD = 1.266) and males (mean = 5.16, SD = 1.199) are thermally comfortable within the buildings, with a marginally higher mean value for male residents than those reported for females. Male respondents who feel warm perceive less air quality (r = −0.712, p < 0.001) more than females (r = −0.299, p < 0.05). Females (r = 0.331, p < 0.05) and males (r = 0.616, p < 0.001) who perceive to be thermally comfortable also perceive good air quality. Females (r = 0290, p < 0.05) and males (r = 0.665, p < 0.001) who are thermally comfortable voted that they perceive sufficient air humidity. The mean neutral and preferred temperatures of 25.5 °C and 24.9 °C were reported for females. For males, the average neutral and preferred temperatures of 25.8 °C and 25.6 °C were observed. There were differences of 0.3 °C and 0.7 °C between the mean neutral and preferred temperatures for females and males. Females feel neutral and prefer “no change” to the thermal environment at lower temperatures than males. In this study, the average heat indices of 25.7 °C and 26.0 °C were calculated for females and males. A difference of 0.3 °C was also reported between the mean indices for females and males. Because females can tolerate and adapt to the thermal environment better than males, the study showed they are less prone to heat stress in the buildings.

By exploring various statistical tests, the study demonstrated that males feel warmer than females. The study also demonstrated that males are more sensitive to daylighting than females within the indoor environment. Statistical tests also revealed that males perceive better indoor air quality within the thermal environment than females. On air humidity sensation, females and males appear to perceive the indoor environment to be slightly dry. The investigation showed that females and males are thermally comfortable when the indoor air quality is good. Moreover, females and males are comfortable when the indoor environment is not too humid and dry. On thermal acceptability, 95% of females and 94% of males perceive the thermal environment to be acceptable. Female and male respondents noted that activity level likely influenced their perception of the indoor thermal environment.

The study demonstrated disparity among different groups of occupants regarding their tolerance of thermal preference and air quality. The result shows females can be more sensitive to better indoor air quality and thermal preference over thermal comfort and acceptability than male occupants within the thermal environment. The research revealed air quality and preference for modifications of the thermal environment could be within a wide range among different groups of occupants of buildings.

The investigation pinpoints the need for further research on variations in gender perceptions of thermal comfort in different thermal environments. The study noted that females are more vulnerable to thermal discomfort than males. One of the contributing factors may be because of longer hours of occupation noted among females than males. Additionally, the study received more subject votes from females than males, which implies more complaints from females than males. Equal subject votes from females and males may likely provide a different outcome for thermal comfort votes. On practical implications and applications of this study, the research revealed differences in gender perceptions of the thermal environment. The research revealed a disparity between gender perceptions of summer comfort and their vulnerability to the thermal environment in hot or warm situations. The study calls for the attention of various designers to consider interventions and design strategies that can enhance thermal comfort and adaptation of different groups of genders within the thermal environment. Some of these interventions should capture how users can regulate the thermal environment to adjust their skin temperatures and use control measures that are sensitive to clothing insulation. The research also calls for policies that can promote building users’ pivotal adaptive measures to improve the indoor thermal environment. The investigation increases our understanding of a sustainable indoor environment and how to improve living conditions and adaptive measures among different groups of occupants in buildings.